CINXE.COM

<!DOCTYPE html><html lang="en-US" itemscope itemtype="http://schema.org/WebPage"><head><meta charset="utf-8"><script nonce="N2_63Ev6TPDUMb2QXboYWA">var DOCS_timing={}; DOCS_timing['sl']=new Date().getTime();</script><script nonce="N2_63Ev6TPDUMb2QXboYWA">function _DumpException(e) {throw e;}</script><script data-id="_gd" nonce="N2_63Ev6TPDUMb2QXboYWA">window.WIZ_global_data = {"K1cgmc":"%.@.[null,null,null,[null,1,[1732003548,280410000]]]]","nQyAE":{}};</script><script nonce="N2_63Ev6TPDUMb2QXboYWA">_docs_flag_initialData={"atari-emtpr":false,"atari-eibrm":false,"docs-text-elei":false,"docs-text-usc":true,"atari-bae":false,"docs-text-emtps":true,"docs-text-etsrdpn":false,"docs-text-etsrds":false,"docs-text-endes":false,"docs-text-escpv":true,"docs-text-ecfs":false,"docs-text-ecis":true,"docs-text-eectfs":true,"docs-text-edctzs":true,"docs-text-eetxpc":false,"docs-text-eetxp":false,"docs-text-ertkmcp":true,"docs-text-ettctvs":false,"docs-text-ettts":true,"docs-text-escoubs":false,"docs-text-escivs":false,"docs-text-escitrbs":false,"docs-text-ecgvd":false,"docs-text-esbbcts":true,"docs-text-etccdts":false,"docs-text-etcchrs":false,"docs-text-etctrs":false,"docs-text-eltbbs":true,"docs-text-ecvdis":false,"docs-text-elaiabbs":false,"docs-text-eiosmc":false,"docs-text-ecslpo":false,"docs-text-etb":false,"docs-text-esbefr":false,"docs-text-ipi":false,"docs-etshc":false,"docs-text-tbcb":2.0E7,"docs-efsmsdl":false,"docs-text-etof":false,"docs-text-ehlb":false,"docs-text-epa":true,"docs-text-dwit":false,"docs-text-elawp":false,"docs-eec":false,"docs-ecot":"","docs-text-enbcr":false,"docs-sup":"","umss":false,"docs-eldi":false,"docs-dli":false,"docs-liap":"/logImpressions","ilcm":{"eui":"AHKXmL1QXALclq-GDZ5chEUbGxvLqnrraj-WRBwY2_7AjD3WMYxtTbCf-P9gOoWIZK5BXkuPlmk7","je":1,"sstu":1732376365593869,"si":"CI3qje_k8okDFUYnbwYdFHIs4w","gsc":null,"ei":[5703839,5704621,5706832,5706836,5707711,5737784,5737800,5738513,5738529,5740798,5740814,5743108,5743124,5747265,5748013,5748029,5752678,5752694,5753313,5753329,5754213,5754229,5755080,5755096,5758807,5758823,5762243,5762259,5764252,5764268,5765535,5765551,5766761,5766777,5773662,5773678,5774331,5774347,5774836,5774852,5776501,5776517,5784931,5784947,5784951,5784967,5791766,5791782,5796457,5796473,14101306,14101502,14101510,14101534,49372435,49372443,49375314,49375322,49472063,49472071,49622823,49622831,49623173,49623181,49643568,49643576,49644015,49644023,49769337,49769345,49822921,49822929,49823164,49823172,49833462,49833470,49842855,49842863,49924706,49924714,50221720,50221728,50266222,50266230,50273528,50273536,50297076,50297084,50297426,50297434,50498907,50498915,50529103,50529111,50586962,50586970,70971256,70971264,71035517,71035525,71038255,71038263,71079938,71079946,71085241,71085249,71185170,71185178,71197826,71197834,71238946,71238954,71289146,71289154,71387889,71387897,71429507,71429515,71478200,71478208,71478589,71478597,71502841,71502849,71528597,71528605,71530083,71530091,71544834,71544842,71545513,71545521,71546425,71546433,71560069,71560077,71561541,71561549,71573870,71573878,71642103,71642111,71652840,71652848,71658040,71658048,71659813,71659821,71689860,71689868,71699841,71699849,71720760,71721087,71721095,71733083,71733091,71798420,71798436,71798440,71798456,71849655,71849663,71882106,71882114,71897827,71897835,71960540,71960548,71961126,71961134,94327661,94327669,94333153,94333161,94353368,94353376,94390153,94390161,94397741,94397749,94413607,94413615,94420737,94420745,94434257,94434265,94435578,94435586,94444282,94444290,94484634,94484642,94489858,94489866,94502654,94502662,94526768,94526776,94545004,94545012,94597639,94597647,94630911,94661802,94661810,94707424,94707432,94784571,94784579,94875009,94875017,94904089,94904097,94929210,94929218,94942490,94942498,95065889,95065897,95087186,95087194,95112873,95112881,95118551,95118559,95135933,95135941,95234185,95234871,95234879,95251262,95251270,95254920,95254928,95266740,95266748,95270945,95270953,95271343,95271351,95314802,95314810,95317985,99237681,99237689,99247596,99247604,99310979,99310987,99338440,99338448,99368792,99368800,99401881,99401889,99402331,99402339,99437441,99437449,99460069,100130662,100130678,101406734,101406742,101442805,101442813,101456452,101456460,101488823,101488831,101489187,101489195,101507186,101507194,101519280,101519288,101544667,101544675,101606928,101606936,101617516,101617524,101631040,101631048,101705089,101708583,101708591,101771970,101771978,101776366,101776374,101783430,101783446,101922729,101922737],"crc":0,"cvi":[]},"docs-ccdil":false,"docs-eil":true,"info_params":{},"buildLabel":"editors.sites-viewer-frontend_20241112.02_p1","docs-show_debug_info":false,"atari-jefp":"/_/view/jserror","docs-jern":"view","atari-rhpp":"/_/view","docs-ecuach":false,"docs-cclt":2033,"docs-ecci":true,"docs-esi":false,"docs-efypr":true,"docs-eyprp":true}; _docs_flag_cek= null ; if (window['DOCS_timing']) {DOCS_timing['ifdld']=new Date().getTime();}</script><meta name="viewport" content="width=device-width, initial-scale=1"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="referrer" content="origin"><link rel="icon" href="https://lh3.googleusercontent.com/HG-pdeuCDAL6hx0Mlo-J4aMgggrgXKGwPKmqj3uJiQpwqRFuDkr49_IJgxDt-Oj-hTeBrkr5W2YAw1np33lOjaPv1flc5xCbk827tqvstVvROVEM"><meta property="og:title" content="Accepted Papers"><meta property="og:type" content="website"><meta property="og:url" content="https://sites.google.com/view/soea2022/accepted-papers"><meta property="og:description" content=" Accepted Papers"><meta itemprop="name" content="Accepted Papers"><meta itemprop="description" content=" Accepted Papers"><meta itemprop="url" content="https://sites.google.com/view/soea2022/accepted-papers"><meta itemprop="thumbnailUrl" content="https://lh3.googleusercontent.com/HG-pdeuCDAL6hx0Mlo-J4aMgggrgXKGwPKmqj3uJiQpwqRFuDkr49_IJgxDt-Oj-hTeBrkr5W2YAw1np33lOjaPv1flc5xCbk827tqvstVvROVEM"><meta itemprop="image" content="https://lh3.googleusercontent.com/HG-pdeuCDAL6hx0Mlo-J4aMgggrgXKGwPKmqj3uJiQpwqRFuDkr49_IJgxDt-Oj-hTeBrkr5W2YAw1np33lOjaPv1flc5xCbk827tqvstVvROVEM"><meta itemprop="imageUrl" content="https://lh3.googleusercontent.com/HG-pdeuCDAL6hx0Mlo-J4aMgggrgXKGwPKmqj3uJiQpwqRFuDkr49_IJgxDt-Oj-hTeBrkr5W2YAw1np33lOjaPv1flc5xCbk827tqvstVvROVEM"><meta property="og:image" content="https://lh3.googleusercontent.com/HG-pdeuCDAL6hx0Mlo-J4aMgggrgXKGwPKmqj3uJiQpwqRFuDkr49_IJgxDt-Oj-hTeBrkr5W2YAw1np33lOjaPv1flc5xCbk827tqvstVvROVEM"><link href="https://fonts.googleapis.com/css?family=Lato%3A300%2C300italic%2C400%2C400italic%2C700%2C700italic&display=swap" rel="stylesheet" nonce="I0EXnkVM2EFUPefyDO3QGA"><link href="https://fonts.googleapis.com/css?family=Google+Sans:400,500|Roboto:300,400,500,700|Source+Code+Pro:400,700&display=swap" rel="stylesheet" nonce="I0EXnkVM2EFUPefyDO3QGA"><link href="https://fonts.googleapis.com/css?family=Roboto%3Ai%2Cbi%2C700%2C400&display=swap" rel="stylesheet" nonce="I0EXnkVM2EFUPefyDO3QGA"><style nonce="I0EXnkVM2EFUPefyDO3QGA">@media only screen and (max-width: 479px){.jgG6ef{font-size: 17.0pt;}}@media only screen and (min-width: 480px) and (max-width: 767px){.jgG6ef{font-size: 17.0pt;}}@media only screen and (min-width: 768px) and (max-width: 1279px){.jgG6ef{font-size: 18.0pt;}}@media only screen and (min-width: 1280px){.jgG6ef{font-size: 18.0pt;}}</style><link rel="stylesheet" href="https://www.gstatic.com/_/atari/_/ss/k=atari.vw.7R57rYYVGiA.L.X.O/am=MBiA/d=1/rs=AGEqA5nH97dOwqY0iGblvGlWiaR59owncA" data-id="_cl" nonce="I0EXnkVM2EFUPefyDO3QGA"><script nonce="N2_63Ev6TPDUMb2QXboYWA"></script><title>Accepted Papers</title><style jsname="ptDGoc" nonce="I0EXnkVM2EFUPefyDO3QGA">.M63kCb{background-color: rgba(255,255,255,1);}.OUGEr{color: rgba(33,33,33,1);}.duRjpb .OUGEr{color: rgba(34,110,147,1);}.JYVBee .OUGEr{color: rgba(34,110,147,1);}.OmQG5e .OUGEr{color: rgba(33,33,33,1);}.iwQgFb{background-color: rgba(0,0,0,0.150000006);}.ySLm4c{font-family: Lato, sans-serif;}.CbiMKe{background-color: rgba(30,108,147,1);}.qeLZfd .zfr3Q{color: rgba(33,33,33,1);}.qeLZfd .qnVSj{color: rgba(33,33,33,1);}.qeLZfd .Glwbz{color: rgba(33,33,33,1);}.qeLZfd .duRjpb{color: rgba(34,110,147,1);}.qeLZfd .qLrapd{color: rgba(34,110,147,1);}.qeLZfd .JYVBee{color: rgba(34,110,147,1);}.qeLZfd .aHM7ed{color: rgba(34,110,147,1);}.qeLZfd .OmQG5e{color: rgba(33,33,33,1);}.qeLZfd .NHD4Gf{color: rgba(33,33,33,1);}.qeLZfd .aw5Odc{color: rgba(0,101,128,1);}.qeLZfd .dhtgD:hover{color: rgba(0,0,0,1);}.qeLZfd .dhtgD:visited{color: rgba(0,101,128,1);}.qeLZfd .iwQgFb{background-color: rgba(0,0,0,0.150000006);}.qeLZfd .OUGEr{color: rgba(33,33,33,1);}.qeLZfd .duRjpb .OUGEr{color: rgba(34,110,147,1);}.qeLZfd .JYVBee .OUGEr{color: rgba(34,110,147,1);}.qeLZfd .OmQG5e .OUGEr{color: rgba(33,33,33,1);}.qeLZfd:before{background-color: rgba(242,242,242,1); display: block;}.lQAHbd .zfr3Q{color: rgba(255,255,255,1);}.lQAHbd .qnVSj{color: rgba(255,255,255,1);}.lQAHbd .Glwbz{color: rgba(255,255,255,1);}.lQAHbd .duRjpb{color: rgba(255,255,255,1);}.lQAHbd .qLrapd{color: rgba(255,255,255,1);}.lQAHbd .JYVBee{color: rgba(255,255,255,1);}.lQAHbd .aHM7ed{color: rgba(255,255,255,1);}.lQAHbd .OmQG5e{color: rgba(255,255,255,1);}.lQAHbd .NHD4Gf{color: rgba(255,255,255,1);}.lQAHbd .aw5Odc{color: rgba(255,255,255,1);}.lQAHbd .dhtgD:hover{color: rgba(255,255,255,1);}.lQAHbd .dhtgD:visited{color: rgba(255,255,255,1);}.lQAHbd .iwQgFb{background-color: rgba(255,255,255,0.150000006);}.lQAHbd .OUGEr{color: rgba(255,255,255,1);}.lQAHbd .duRjpb .OUGEr{color: rgba(255,255,255,1);}.lQAHbd .JYVBee .OUGEr{color: rgba(255,255,255,1);}.lQAHbd .OmQG5e .OUGEr{color: rgba(255,255,255,1);}.lQAHbd .CbiMKe{background-color: rgba(255,255,255,1);}.lQAHbd:before{background-color: rgba(30,108,147,1); display: block;}.cJgDec .zfr3Q{color: rgba(255,255,255,1);}.cJgDec .zfr3Q .OUGEr{color: rgba(255,255,255,1);}.cJgDec .qnVSj{color: rgba(255,255,255,1);}.cJgDec .Glwbz{color: rgba(255,255,255,1);}.cJgDec .qLrapd{color: rgba(255,255,255,1);}.cJgDec .aHM7ed{color: rgba(255,255,255,1);}.cJgDec .NHD4Gf{color: rgba(255,255,255,1);}.cJgDec .IFuOkc:before{background-color: rgba(33,33,33,1); opacity: 0; display: block;}.O13XJf{height: 340px; padding-bottom: 60px; padding-top: 60px;}.O13XJf .IFuOkc{background-color: rgba(34,110,147,1); background-image: url(https://ssl.gstatic.com/atari/images/simple-header-blended-small.png);}.O13XJf .IFuOkc:before{background-color: rgba(33,33,33,1); opacity: 0.4; display: block;}.O13XJf .zfr3Q{color: rgba(255,255,255,1);}.O13XJf .qnVSj{color: rgba(255,255,255,1);}.O13XJf .Glwbz{color: rgba(255,255,255,1);}.O13XJf .duRjpb{color: rgba(255,255,255,1);}.O13XJf .qLrapd{color: rgba(255,255,255,1);}.O13XJf .JYVBee{color: rgba(255,255,255,1);}.O13XJf .aHM7ed{color: rgba(255,255,255,1);}.O13XJf .OmQG5e{color: rgba(255,255,255,1);}.O13XJf .NHD4Gf{color: rgba(255,255,255,1);}.tpmmCb .zfr3Q{color: rgba(33,33,33,1);}.tpmmCb .zfr3Q .OUGEr{color: rgba(33,33,33,1);}.tpmmCb .qnVSj{color: rgba(33,33,33,1);}.tpmmCb .Glwbz{color: rgba(33,33,33,1);}.tpmmCb .qLrapd{color: rgba(33,33,33,1);}.tpmmCb .aHM7ed{color: rgba(33,33,33,1);}.tpmmCb .NHD4Gf{color: rgba(33,33,33,1);}.tpmmCb .IFuOkc:before{background-color: rgba(255,255,255,1); display: block;}.tpmmCb .Wew9ke{fill: rgba(33,33,33,1);}.aw5Odc{color: rgba(0,101,128,1);}.dhtgD:hover{color: rgba(0,122,147,1);}.dhtgD:active{color: rgba(0,122,147,1);}.dhtgD:visited{color: rgba(0,101,128,1);}.Zjiec{color: rgba(255,255,255,1); font-family: Lato, sans-serif; font-size: 19pt; font-weight: 300; letter-spacing: 1px; line-height: 1.3; padding-bottom: 62.5px; padding-left: 48px; padding-right: 36px; padding-top: 11.5px;}.XMyrgf{margin-top: 0px; margin-left: 48px; margin-bottom: 24px; margin-right: 24px;}.TlfmSc{color: rgba(255,255,255,1); font-family: Lato, sans-serif; font-size: 15pt; font-weight: 300; line-height: 1.333;}.Mz8gvb{color: rgba(255,255,255,1);}.zDUgLc{background-color: rgba(33,33,33,1);}.QTKDff.chg4Jd:focus{background-color: rgba(255,255,255,0.1199999973);}.YTv4We{color: rgba(178,178,178,1);}.YTv4We:hover:before{background-color: rgba(255,255,255,0.1199999973); display: block;}.YTv4We.chg4Jd:focus:before{border-color: rgba(255,255,255,0.3600000143); display: block;}.eWDljc{background-color: rgba(33,33,33,1);}.eWDljc .hDrhEe{padding-left: 8px;}.ZXW7w{color: rgba(255,255,255,1); opacity: 0.26;}.PsKE7e{color: rgba(255,255,255,1); font-family: Lato, sans-serif; font-size: 12pt; font-weight: 300;}.lhZOrc{color: rgba(73,170,212,1);}.hDrhEe:hover{color: rgba(73,170,212,1);}.M9vuGd{color: rgba(73,170,212,1); font-weight: 400;}.jgXgSe:hover{color: rgba(73,170,212,1);}.j10yRb:hover{color: rgba(0,188,212,1);}.j10yRb.chg4Jd:focus:before{border-color: rgba(255,255,255,0.3600000143); display: block;}.tCHXDc{color: rgba(255,255,255,1);}.iWs3gf.chg4Jd:focus{background-color: rgba(255,255,255,0.1199999973);}.wgxiMe{background-color: rgba(33,33,33,1);}.fOU46b .TlfmSc{color: rgba(255,255,255,1);}.fOU46b .KJll8d{background-color: rgba(255,255,255,1);}.fOU46b .Mz8gvb{color: rgba(255,255,255,1);}.fOU46b .Mz8gvb.chg4Jd:focus:before{border-color: rgba(255,255,255,1); display: block;}.fOU46b .qV4dIc{color: rgba(255,255,255,0.8700000048);}.fOU46b .jgXgSe:hover{color: rgba(255,255,255,1);}.fOU46b .M9vuGd{color: rgba(255,255,255,1);}.fOU46b .tCHXDc{color: rgba(255,255,255,0.8700000048);}.fOU46b .iWs3gf.chg4Jd:focus{background-color: rgba(255,255,255,0.1199999973);}.fOU46b .G8QRnc .Mz8gvb{color: rgba(0,0,0,0.8000000119);}.fOU46b .G8QRnc .Mz8gvb.chg4Jd:focus:before{border-color: rgba(0,0,0,0.8000000119); display: block;}.fOU46b .G8QRnc .ZXW7w{color: rgba(0,0,0,0.8000000119);}.fOU46b .G8QRnc .TlfmSc{color: rgba(0,0,0,0.8000000119);}.fOU46b .G8QRnc .KJll8d{background-color: rgba(0,0,0,0.8000000119);}.fOU46b .G8QRnc .qV4dIc{color: rgba(0,0,0,0.6399999857);}.fOU46b .G8QRnc .jgXgSe:hover{color: rgba(0,0,0,0.8199999928);}.fOU46b .G8QRnc .M9vuGd{color: rgba(0,0,0,0.8199999928);}.fOU46b .G8QRnc .tCHXDc{color: rgba(0,0,0,0.6399999857);}.fOU46b .G8QRnc .iWs3gf.chg4Jd:focus{background-color: rgba(0,0,0,0.1199999973);}.fOU46b .usN8rf .Mz8gvb{color: rgba(0,0,0,0.8000000119);}.fOU46b .usN8rf .Mz8gvb.chg4Jd:focus:before{border-color: rgba(0,0,0,0.8000000119); display: block;}.fOU46b .usN8rf .ZXW7w{color: rgba(0,0,0,0.8000000119);}.fOU46b .usN8rf .TlfmSc{color: rgba(0,0,0,0.8000000119);}.fOU46b .usN8rf .KJll8d{background-color: rgba(0,0,0,0.8000000119);}.fOU46b .usN8rf .qV4dIc{color: rgba(0,0,0,0.6399999857);}.fOU46b .usN8rf .jgXgSe:hover{color: rgba(0,0,0,0.8199999928);}.fOU46b .usN8rf .M9vuGd{color: rgba(0,0,0,0.8199999928);}.fOU46b .usN8rf .tCHXDc{color: rgba(0,0,0,0.6399999857);}.fOU46b .usN8rf .iWs3gf.chg4Jd:focus{background-color: rgba(0,0,0,0.1199999973);}.fOU46b .aCIEDd .qV4dIc{color: rgba(33,33,33,1);}.fOU46b .aCIEDd .TlfmSc{color: rgba(33,33,33,1);}.fOU46b .aCIEDd .KJll8d{background-color: rgba(33,33,33,1);}.fOU46b .aCIEDd .ZXW7w{color: rgba(33,33,33,1);}.fOU46b .aCIEDd .jgXgSe:hover{color: rgba(33,33,33,1); opacity: 0.82;}.fOU46b .aCIEDd .Mz8gvb{color: rgba(33,33,33,1);}.fOU46b .aCIEDd .tCHXDc{color: rgba(33,33,33,1);}.fOU46b .aCIEDd .iWs3gf.chg4Jd:focus{background-color: rgba(33,33,33,0.1199999973);}.fOU46b .a3ETed .qV4dIc{color: rgba(255,255,255,1);}.fOU46b .a3ETed .TlfmSc{color: rgba(255,255,255,1);}.fOU46b .a3ETed .KJll8d{background-color: rgba(255,255,255,1);}.fOU46b .a3ETed .ZXW7w{color: rgba(255,255,255,1);}.fOU46b .a3ETed .jgXgSe:hover{color: rgba(255,255,255,1); opacity: 0.82;}.fOU46b .a3ETed .Mz8gvb{color: rgba(255,255,255,1);}.fOU46b .a3ETed .tCHXDc{color: rgba(255,255,255,1);}.fOU46b .a3ETed .iWs3gf.chg4Jd:focus{background-color: rgba(255,255,255,0.1199999973);}@media only screen and (min-width: 1280px){.XeSM4.b2Iqye.fOU46b .LBrwzc .tCHXDc{color: rgba(255,255,255,0.8700000048);}}.XeSM4.b2Iqye.fOU46b .LBrwzc .iWs3gf.chg4Jd:focus{background-color: rgba(255,255,255,0.1199999973);}@media only screen and (min-width: 1280px){.KuNac.b2Iqye.fOU46b .tCHXDc{color: rgba(0,0,0,0.6399999857);}}.KuNac.b2Iqye.fOU46b .iWs3gf.chg4Jd:focus{background-color: rgba(0,0,0,0.1199999973);}.fOU46b .zDUgLc{opacity: 0;}.LBrwzc .ZXW7w{color: rgba(0,0,0,1);}.LBrwzc .KJll8d{background-color: rgba(0,0,0,1);}.GBy4H .ZXW7w{color: rgba(255,255,255,1);}.GBy4H .KJll8d{background-color: rgba(255,255,255,1);}.eBSUbc{background-color: rgba(33,33,33,1); color: rgba(0,188,212,0.6999999881);}.BFDQOb:hover{color: rgba(73,170,212,1);}.ImnMyf{background-color: rgba(255,255,255,1); color: rgba(33,33,33,1);}.Vs12Bd{background-color: rgba(242,242,242,1); color: rgba(33,33,33,1);}.S5d9Rd{background-color: rgba(30,108,147,1); color: rgba(255,255,255,1);}.zfr3Q{color: rgba(33,33,33,1); font-family: Lato, sans-serif; font-size: 11pt; font-weight: 400; line-height: 1.6667; margin-top: 12px;}.qnVSj{color: rgba(33,33,33,1);}.Glwbz{color: rgba(33,33,33,1);}.duRjpb{color: rgba(34,110,147,1); font-family: Lato, sans-serif; font-size: 34pt; font-weight: 300; letter-spacing: 0.5px; line-height: 1.2; margin-top: 30px;}.Ap4VC{margin-bottom: -30px;}.qLrapd{color: rgba(34,110,147,1);}.JYVBee{color: rgba(34,110,147,1); font-family: Lato, sans-serif; font-size: 19pt; font-weight: 400; line-height: 1.4; margin-top: 20px;}.CobnVe{margin-bottom: -20px;}.aHM7ed{color: rgba(34,110,147,1);}.OmQG5e{color: rgba(33,33,33,1); font-family: Lato, sans-serif; font-size: 15pt; font-style: normal; font-weight: 400; line-height: 1.25; margin-top: 16px;}.GV3q8e{margin-bottom: -16px;}.NHD4Gf{color: rgba(33,33,33,1);}.LB7kq .duRjpb{font-size: 64pt; letter-spacing: 2px; line-height: 1; margin-top: 40px;}.LB7kq .JYVBee{font-size: 25pt; font-weight: 300; line-height: 1.1; margin-top: 25px;}@media only screen and (max-width: 479px){.LB7kq .duRjpb{font-size: 40pt;}}@media only screen and (min-width: 480px) and (max-width: 767px){.LB7kq .duRjpb{font-size: 53pt;}}@media only screen and (max-width: 479px){.LB7kq .JYVBee{font-size: 19pt;}}@media only screen and (min-width: 480px) and (max-width: 767px){.LB7kq .JYVBee{font-size: 22pt;}}.O13XJf{height: 340px; padding-bottom: 60px; padding-top: 60px;}@media only screen and (min-width: 480px) and (max-width: 767px){.O13XJf{height: 280px; padding-bottom: 40px; padding-top: 40px;}}@media only screen and (max-width: 479px){.O13XJf{height: 250px; padding-bottom: 30px; padding-top: 30px;}}.SBrW1{height: 520px;}@media only screen and (min-width: 480px) and (max-width: 767px){.SBrW1{height: 520px;}}@media only screen and (max-width: 479px){.SBrW1{height: 400px;}}.Wew9ke{fill: rgba(255,255,255,1);}.gk8rDe{height: 180px; padding-bottom: 32px; padding-top: 60px;}.gk8rDe .zfr3Q{color: rgba(0,0,0,1);}.gk8rDe .duRjpb{color: rgba(34,110,147,1); font-size: 45pt; line-height: 1.1;}.gk8rDe .qLrapd{color: rgba(34,110,147,1);}.gk8rDe .JYVBee{color: rgba(34,110,147,1); font-size: 27pt; line-height: 1.35; margin-top: 15px;}.gk8rDe .aHM7ed{color: rgba(34,110,147,1);}.gk8rDe .OmQG5e{color: rgba(33,33,33,1);}.gk8rDe .NHD4Gf{color: rgba(33,33,33,1);}@media only screen and (max-width: 479px){.gk8rDe .duRjpb{font-size: 30pt;}}@media only screen and (min-width: 480px) and (max-width: 767px){.gk8rDe .duRjpb{font-size: 38pt;}}@media only screen and (max-width: 479px){.gk8rDe .JYVBee{font-size: 20pt;}}@media only screen and (min-width: 480px) and (max-width: 767px){.gk8rDe .JYVBee{font-size: 24pt;}}@media only screen and (min-width: 480px) and (max-width: 767px){.gk8rDe{padding-top: 45px;}}@media only screen and (max-width: 479px){.gk8rDe{padding-bottom: 0px; padding-top: 30px;}}.dhtgD{text-decoration: underline;}.JzO0Vc{background-color: rgba(33,33,33,1); font-family: Lato, sans-serif; width: 250px;}@media only screen and (min-width: 1280px){.JzO0Vc{padding-top: 48.5px;}}.TlfmSc{font-family: Lato, sans-serif; font-size: 15pt; font-weight: 300; line-height: 1.333;}.PsKE7e{font-family: Lato, sans-serif; font-size: 12pt;}.IKA38e{line-height: 1.21;}.hDrhEe{padding-bottom: 11.5px; padding-top: 11.5px;}.zDUgLc{opacity: 1;}.QmpIrf{background-color: rgba(30,108,147,1); border-color: rgba(255,255,255,1); color: rgba(255,255,255,1); font-family: Lato, sans-serif; font-size: 11pt; line-height: normal;}.xkUom{border-color: rgba(30,108,147,1); color: rgba(30,108,147,1); font-family: Lato, sans-serif; font-size: 11pt; line-height: normal;}.xkUom:hover{background-color: rgba(30,108,147,0.1000000015);}.KjwKmc{color: rgba(30,108,147,1); font-family: Lato, sans-serif; font-size: 11pt; line-height: normal; line-height: normal;}.KjwKmc:hover{background-color: rgba(30,108,147,0.1000000015);}.lQAHbd .QmpIrf{background-color: rgba(255,255,255,1); border-color: rgba(34,110,147,1); color: rgba(34,110,147,1); font-family: Lato, sans-serif; font-size: 11pt; line-height: normal;}.lQAHbd .xkUom{border-color: rgba(242,242,242,1); color: rgba(242,242,242,1); font-family: Lato, sans-serif; font-size: 11pt; line-height: normal;}.lQAHbd .xkUom:hover{background-color: rgba(255,255,255,0.1000000015);}.lQAHbd .KjwKmc{color: rgba(242,242,242,1); font-family: Lato, sans-serif; font-size: 11pt; line-height: normal;}.lQAHbd .KjwKmc:hover{background-color: rgba(255,255,255,0.1000000015);}.lQAHbd .Mt0nFe{border-color: rgba(255,255,255,0.200000003);}.cJgDec .QmpIrf{background-color: rgba(255,255,255,1); border-color: rgba(34,110,147,1); color: rgba(34,110,147,1); font-family: Lato, sans-serif; font-size: 11pt; line-height: normal;}.cJgDec .xkUom{border-color: rgba(242,242,242,1); color: rgba(242,242,242,1); font-family: Lato, sans-serif; font-size: 11pt; line-height: normal;}.cJgDec .xkUom:hover{background-color: rgba(255,255,255,0.1000000015);}.cJgDec .KjwKmc{color: rgba(242,242,242,1); font-family: Lato, sans-serif; font-size: 11pt; line-height: normal;}.cJgDec .KjwKmc:hover{background-color: rgba(255,255,255,0.1000000015);}.tpmmCb .QmpIrf{background-color: rgba(255,255,255,1); border-color: rgba(34,110,147,1); color: rgba(34,110,147,1); font-family: Lato, sans-serif; font-size: 11pt; line-height: normal;}.tpmmCb .xkUom{border-color: rgba(30,108,147,1); color: rgba(30,108,147,1); font-family: Lato, sans-serif; font-size: 11pt; line-height: normal;}.tpmmCb .xkUom:hover{background-color: rgba(30,108,147,0.1000000015);}.tpmmCb .KjwKmc{color: rgba(30,108,147,1); font-family: Lato, sans-serif; font-size: 11pt; line-height: normal;}.tpmmCb .KjwKmc:hover{background-color: rgba(30,108,147,0.1000000015);}.gk8rDe .QmpIrf{background-color: rgba(30,108,147,1); border-color: rgba(255,255,255,1); color: rgba(255,255,255,1); font-family: Lato, sans-serif; font-size: 11pt; line-height: normal;}.gk8rDe .xkUom{border-color: rgba(30,108,147,1); color: rgba(30,108,147,1); font-family: Lato, sans-serif; font-size: 11pt; line-height: normal;}.gk8rDe .xkUom:hover{background-color: rgba(30,108,147,0.1000000015);}.gk8rDe .KjwKmc{color: rgba(30,108,147,1); font-family: Lato, sans-serif; font-size: 11pt; line-height: normal;}.gk8rDe .KjwKmc:hover{background-color: rgba(30,108,147,0.1000000015);}.O13XJf .QmpIrf{background-color: rgba(255,255,255,1); border-color: rgba(34,110,147,1); color: rgba(34,110,147,1); font-family: Lato, sans-serif; font-size: 11pt; line-height: normal;}.O13XJf .xkUom{border-color: rgba(242,242,242,1); color: rgba(242,242,242,1); font-family: Lato, sans-serif; font-size: 11pt; line-height: normal;}.O13XJf .xkUom:hover{background-color: rgba(255,255,255,0.1000000015);}.O13XJf .KjwKmc{color: rgba(242,242,242,1); font-family: Lato, sans-serif; font-size: 11pt; line-height: normal;}.O13XJf .KjwKmc:hover{background-color: rgba(255,255,255,0.1000000015);}.Y4CpGd{font-family: Lato, sans-serif; font-size: 11pt;}.CMArNe{background-color: rgba(242,242,242,1);}.LBrwzc .TlfmSc{color: rgba(0,0,0,0.8000000119);}.LBrwzc .YTv4We{color: rgba(0,0,0,0.6399999857);}.LBrwzc .YTv4We.chg4Jd:focus:before{border-color: rgba(0,0,0,0.6399999857); display: block;}.LBrwzc .Mz8gvb{color: rgba(0,0,0,0.6399999857);}.LBrwzc .tCHXDc{color: rgba(0,0,0,0.6399999857);}.LBrwzc .iWs3gf.chg4Jd:focus{background-color: rgba(0,0,0,0.1199999973);}.LBrwzc .wgxiMe{background-color: rgba(255,255,255,1);}.LBrwzc .qV4dIc{color: rgba(0,0,0,0.6399999857);}.LBrwzc .M9vuGd{color: rgba(0,0,0,0.8000000119); font-weight: bold;}.LBrwzc .Zjiec{color: rgba(0,0,0,0.8000000119);}.LBrwzc .IKA38e{color: rgba(0,0,0,0.6399999857);}.LBrwzc .lhZOrc.IKA38e{color: rgba(0,0,0,0.8000000119); font-weight: bold;}.LBrwzc .j10yRb:hover{color: rgba(0,0,0,0.8000000119);}.LBrwzc .eBSUbc{color: rgba(0,0,0,0.8000000119);}.LBrwzc .hDrhEe:hover{color: rgba(0,0,0,0.8000000119);}.LBrwzc .jgXgSe:hover{color: rgba(0,0,0,0.8000000119);}.LBrwzc .M9vuGd:hover{color: rgba(0,0,0,0.8000000119);}.LBrwzc .zDUgLc{border-bottom-color: rgba(204,204,204,1); border-bottom-width: 1px; border-bottom-style: solid;}.fOU46b .LBrwzc .M9vuGd{color: rgba(0,0,0,0.8000000119);}.fOU46b .LBrwzc .jgXgSe:hover{color: rgba(0,0,0,0.8000000119);}.fOU46b .LBrwzc .zDUgLc{opacity: 1; border-bottom-style: none;}.fOU46b .LBrwzc .tCHXDc{color: rgba(0,0,0,0.6399999857);}.fOU46b .LBrwzc .iWs3gf.chg4Jd:focus{background-color: rgba(0,0,0,0.1199999973);}.fOU46b .GBy4H .M9vuGd{color: rgba(255,255,255,1);}.fOU46b .GBy4H .jgXgSe:hover{color: rgba(255,255,255,1);}.fOU46b .GBy4H .zDUgLc{opacity: 1;}.fOU46b .GBy4H .tCHXDc{color: rgba(255,255,255,0.8700000048);}.fOU46b .GBy4H .iWs3gf.chg4Jd:focus{background-color: rgba(255,255,255,0.1199999973);}.XeSM4.G9Qloe.fOU46b .LBrwzc .tCHXDc{color: rgba(0,0,0,0.6399999857);}.XeSM4.G9Qloe.fOU46b .LBrwzc .iWs3gf.chg4Jd:focus{background-color: rgba(0,0,0,0.1199999973);}.GBy4H .lhZOrc.IKA38e{color: rgba(255,255,255,1);}.GBy4H .eBSUbc{color: rgba(255,255,255,0.8700000048);}.GBy4H .hDrhEe:hover{color: rgba(255,255,255,1);}.GBy4H .j10yRb:hover{color: rgba(255,255,255,1);}.GBy4H .YTv4We{color: rgba(255,255,255,1);}.GBy4H .YTv4We.chg4Jd:focus:before{border-color: rgba(255,255,255,1); display: block;}.GBy4H .tCHXDc{color: rgba(255,255,255,0.8700000048);}.GBy4H .iWs3gf.chg4Jd:focus{background-color: rgba(255,255,255,0.1199999973);}.GBy4H .jgXgSe:hover{color: rgba(255,255,255,1);}.GBy4H .jgXgSe:hover{color: rgba(255,255,255,1);}.GBy4H .M9vuGd{color: rgba(255,255,255,1);}.GBy4H .M9vuGd:hover{color: rgba(255,255,255,1);}.QcmuFb{padding-left: 20px;}.vDPrib{padding-left: 40px;}.TBDXjd{padding-left: 60px;}.bYeK8e{padding-left: 80px;}.CuqSDe{padding-left: 100px;}.Havqpe{padding-left: 120px;}.JvDrRe{padding-left: 140px;}.o5lrIf{padding-left: 160px;}.yOJW7c{padding-left: 180px;}.rB8cye{padding-left: 200px;}.RuayVd{padding-right: 20px;}.YzcKX{padding-right: 40px;}.reTV0b{padding-right: 60px;}.vSYeUc{padding-right: 80px;}.PxtZIe{padding-right: 100px;}.ahQMed{padding-right: 120px;}.rzhcXb{padding-right: 140px;}.PBhj0b{padding-right: 160px;}.TlN46c{padding-right: 180px;}.GEdNnc{padding-right: 200px;}.TMjjoe{font-family: Lato, sans-serif; font-size: 9pt; line-height: 1.2; margin-top: 0px;}@media only screen and (min-width: 1280px){.yxgWrb{margin-left: 250px;}}@media only screen and (max-width: 479px){.Zjiec{font-size: 15pt;}}@media only screen and (min-width: 480px) and (max-width: 767px){.Zjiec{font-size: 17pt;}}@media only screen and (max-width: 479px){.TlfmSc{font-size: 13pt;}}@media only screen and (min-width: 480px) and (max-width: 767px){.TlfmSc{font-size: 14pt;}}@media only screen and (max-width: 479px){.PsKE7e{font-size: 12pt;}}@media only screen and (min-width: 480px) and (max-width: 767px){.PsKE7e{font-size: 12pt;}}@media only screen and (max-width: 479px){.duRjpb{font-size: 24pt;}}@media only screen and (min-width: 480px) and (max-width: 767px){.duRjpb{font-size: 29pt;}}@media only screen and (max-width: 479px){.JYVBee{font-size: 15pt;}}@media only screen and (min-width: 480px) and (max-width: 767px){.JYVBee{font-size: 17pt;}}@media only screen and (max-width: 479px){.OmQG5e{font-size: 13pt;}}@media only screen and (min-width: 480px) and (max-width: 767px){.OmQG5e{font-size: 14pt;}}@media only screen and (max-width: 479px){.TlfmSc{font-size: 13pt;}}@media only screen and (min-width: 480px) and (max-width: 767px){.TlfmSc{font-size: 14pt;}}@media only screen and (max-width: 479px){.PsKE7e{font-size: 12pt;}}@media only screen and (min-width: 480px) and (max-width: 767px){.PsKE7e{font-size: 12pt;}}@media only screen and (max-width: 479px){.TMjjoe{font-size: 9pt;}}@media only screen and (min-width: 480px) and (max-width: 767px){.TMjjoe{font-size: 9pt;}}section[id="h.676d26285ac99631_25"] .IFuOkc:before{opacity: 0.4;}section[id="h.1c268780ba2a67e_120"] .IFuOkc:before{opacity: 0.5;}</style><script nonce="N2_63Ev6TPDUMb2QXboYWA">_at_config = [null,"AIzaSyChg3MFqzdi1P5J-YvEyakkSA1yU7HRcDI","897606708560-a63d8ia0t9dhtpdt4i3djab2m42see7o.apps.googleusercontent.com",null,null,null,null,null,null,null,null,null,null,null,"SITES_%s",null,null,null,null,null,null,null,null,null,["AHKXmL1QXALclq-GDZ5chEUbGxvLqnrraj-WRBwY2_7AjD3WMYxtTbCf-P9gOoWIZK5BXkuPlmk7",1,"CI3qje_k8okDFUYnbwYdFHIs4w",1732376365593869,[5703839,5704621,5706832,5706836,5707711,5737784,5737800,5738513,5738529,5740798,5740814,5743108,5743124,5747265,5748013,5748029,5752678,5752694,5753313,5753329,5754213,5754229,5755080,5755096,5758807,5758823,5762243,5762259,5764252,5764268,5765535,5765551,5766761,5766777,5773662,5773678,5774331,5774347,5774836,5774852,5776501,5776517,5784931,5784947,5784951,5784967,5791766,5791782,5796457,5796473,14101306,14101502,14101510,14101534,49372435,49372443,49375314,49375322,49472063,49472071,49622823,49622831,49623173,49623181,49643568,49643576,49644015,49644023,49769337,49769345,49822921,49822929,49823164,49823172,49833462,49833470,49842855,49842863,49924706,49924714,50221720,50221728,50266222,50266230,50273528,50273536,50297076,50297084,50297426,50297434,50498907,50498915,50529103,50529111,50586962,50586970,70971256,70971264,71035517,71035525,71038255,71038263,71079938,71079946,71085241,71085249,71185170,71185178,71197826,71197834,71238946,71238954,71289146,71289154,71387889,71387897,71429507,71429515,71478200,71478208,71478589,71478597,71502841,71502849,71528597,71528605,71530083,71530091,71544834,71544842,71545513,71545521,71546425,71546433,71560069,71560077,71561541,71561549,71573870,71573878,71642103,71642111,71652840,71652848,71658040,71658048,71659813,71659821,71689860,71689868,71699841,71699849,71720760,71721087,71721095,71733083,71733091,71798420,71798436,71798440,71798456,71849655,71849663,71882106,71882114,71897827,71897835,71960540,71960548,71961126,71961134,94327661,94327669,94333153,94333161,94353368,94353376,94390153,94390161,94397741,94397749,94413607,94413615,94420737,94420745,94434257,94434265,94435578,94435586,94444282,94444290,94484634,94484642,94489858,94489866,94502654,94502662,94526768,94526776,94545004,94545012,94597639,94597647,94630911,94661802,94661810,94707424,94707432,94784571,94784579,94875009,94875017,94904089,94904097,94929210,94929218,94942490,94942498,95065889,95065897,95087186,95087194,95112873,95112881,95118551,95118559,95135933,95135941,95234185,95234871,95234879,95251262,95251270,95254920,95254928,95266740,95266748,95270945,95270953,95271343,95271351,95314802,95314810,95317985,99237681,99237689,99247596,99247604,99310979,99310987,99338440,99338448,99368792,99368800,99401881,99401889,99402331,99402339,99437441,99437449,99460069,100130662,100130678,101406734,101406742,101442805,101442813,101456452,101456460,101488823,101488831,101489187,101489195,101507186,101507194,101519280,101519288,101544667,101544675,101606928,101606936,101617516,101617524,101631040,101631048,101705089,101708583,101708591,101771970,101771978,101776366,101776374,101783430,101783446,101922729,101922737]],null,null,null,null,0,null,null,null,null,null,null,null,null,null,"https://drive.google.com",null,null,null,null,null,null,null,null,null,0,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"v2internal","https://docs.google.com",null,null,null,null,null,null,"https://sites.google.com/new/",null,null,null,null,null,0,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,1,"",null,null,null,null,null,null,null,null,null,null,null,null,6,null,null,"https://accounts.google.com/o/oauth2/auth","https://accounts.google.com/o/oauth2/postmessageRelay",null,null,null,null,78,"https://sites.google.com/new/?usp\u003dviewer_footer",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"https://www.gstatic.com/atari/embeds/83a60601c213b72fb19c1855fb0c5f26/intermediate-frame-minified.html",0,null,"v2beta",null,null,null,null,null,null,4,"https://accounts.google.com/o/oauth2/iframe",null,null,null,null,null,null,"https://1533269465-atari-embeds.googleusercontent.com/embeds/16cb204cf3a9d4d223a0a3fd8b0eec5d/inner-frame-minified.html",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,0,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,"https://sites.google.com/view/soea2022/accepted-papers",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,0,null,null,null,null,null,null,0,null,"",null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,1,null,null,null,null,0,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,1,null,null,[1732376365594,"editors.sites-viewer-frontend_20241112.02_p1","695977640",null,1,1,""],null,null,null,null,0,null,null,0,null,null,null,null,null,null,null,null,20,500,"https://domains.google.com",null,0,null,null,null,null,null,null,null,null,null,null,null,0,null,null,null,null,null,null,null,null,null,null,1,0,1,0,0,0,0,null,null,null,null,null,"https://www.google.com/calendar/embed",null,null,null,null,0,null,null,null,null,null,null,null,null,null,null,0,null,null,null,null,null,null,null,null,null,null,null,null,null,"PROD",0,null,0,null,1]; window.globals = {"enableAnalytics":true,"webPropertyId":"","showDebug":false,"hashedSiteId":"d49f5527a67bb64812fff8e9d853e29c0d7deb13d51e1ecdc3b8596f9b729f5f","normalizedPath":"view/soea2022/accepted-papers","pageTitle":"Accepted Papers"}; function gapiLoaded() {if (globals.gapiLoaded == undefined) {globals.gapiLoaded = true;} else {globals.gapiLoaded();}}window.messages = []; window.addEventListener && window.addEventListener('message', function(e) {if (window.messages && e.data && e.data.magic == 'SHIC') {window.messages.push(e);}});</script><script src="https://apis.google.com/js/client.js?onload=gapiLoaded" nonce="N2_63Ev6TPDUMb2QXboYWA"></script><script nonce="N2_63Ev6TPDUMb2QXboYWA">(function(){}).call(this); </script><script nonce="N2_63Ev6TPDUMb2QXboYWA">const imageUrl = 'https:\/\/lh5.googleusercontent.com\/Fuyz451TWQz3Tf158T-7vbVVPnYNXeE-gRsyVeiGhJL7rJtr4WYcUj9PId6RFEYX7lC6lCw_TWU8JggyXpkVt8o\x3dw16383'; function bgImgLoaded() { if (!globals.headerBgImgLoaded) { globals.headerBgImgLoaded = new Date().getTime(); } else { globals.headerBgImgLoaded(); } } if (imageUrl) { const img = new Image(); img.src = imageUrl; img.onload = bgImgLoaded; globals.headerBgImgExists = true; } else { globals.headerBgImgExists = false; } </script></head><body dir="ltr" itemscope itemtype="http://schema.org/WebPage" id="yDmH0d" css="yDmH0d"><div jscontroller="pc62j" jsmodel="iTeaXe" jsaction="rcuQ6b:WYd;GvneHb:og1FDd;vbaUQc:uAM5ec;"><div id="docs-banner-container"><div id="docs-banners"><div id="HB1eCd-mzNpsf-r8s4j-ORHb"></div><div id="HB1eCd-TZk80d-r8s4j-ORHb" aria-live="assertive" aria-atomic="true"></div></div><div class="HB1eCd-Vkfede-NBtyUd-PvRhvb-LwH6nd"></div></div><div jscontroller="X4BaPc" jsaction="rcuQ6b:WYd;o6xM5b:Pg9eo;HuL2Hd:mHeCvf;VMhF5:FFYy5e;sk3Qmb:HI1Mdd;JIbuQc:rSzFEd(z2EeY),aSaF6e(ilzYPe);"><div jscontroller="o1L5Wb" data-sitename="soea2022" data-search-scope="1" data-universe="1" jsmodel="fNFZH" jsaction="Pe9H6d:cZFEp;WMZaJ:VsGN3;hJluRd:UADL7b;zuqEgd:HI9w0;tr6QDd:Y8aXB;MxH79b:xDkBfb;JIbuQc:SPXMTb(uxAMZ),LjG1Ed(a6mxbb);" jsname="G0jgYd"><div jsname="gYwusb" class="p9b27"></div><div jscontroller="RrXLpc" jsname="XeeWQc" role="banner" jsaction="keydown:uiKYid(OH0EC);rcuQ6b:WYd;zuqEgd:ufqpf;JIbuQc:XfTnxb(lfEfFf),AlTiYc(GeGHKb),AlTiYc(m1xNUe),zZlNMe(pZn8Oc);YqO5N:ELcyfe;"><div jsname="bF1uUb" class="BuY5Fd" jsaction="click:xVuwSc;"></div><div jsname="MVsrn" class="TbNlJb "><div role="button" class="U26fgb mUbCce fKz7Od h3nfre M9Bg4d" jscontroller="VXdfxd" jsaction="click:cOuCgd; mousedown:UX7yZ; mouseup:lbsD7e; mouseenter:tfO1Yc; mouseleave:JywGue; focus:AHmuwe; blur:O22p3e; contextmenu:mg9Pef;touchstart:p6p2H; touchmove:FwuNnf; touchend:yfqBxc(preventDefault=true); touchcancel:JMtRjd;" jsshadow jsname="GeGHKb" aria-label="Back to site" aria-disabled="false" tabindex="0" data-tooltip="Back to site" data-tooltip-vertical-offset="-12" data-tooltip-horizontal-offset="0"><div class="VTBa7b MbhUzd" jsname="ksKsZd"></div><span jsslot class="xjKiLb"><span class="Ce1Y1c" style="top: -12px"><svg class="V4YR2c" viewBox="0 0 24 24" focusable="false"><path d="M0 0h24v24H0z" fill="none"/><path d="M20 11H7.83l5.59-5.59L12 4l-8 8 8 8 1.41-1.41L7.83 13H20v-2z"/></svg></span></span></div><div class="E2UJ5" jsname="M6JdT"><div class="rFrNMe b7AJhc zKHdkd" jscontroller="pxq3x" jsaction="clickonly:KjsqPd; focus:Jt1EX; blur:fpfTEe; input:Lg5SV" jsshadow jsname="OH0EC" aria-expanded="true"><div class="aCsJod oJeWuf"><div class="aXBtI I0VJ4d Wic03c"><span jsslot class="A37UZe qgcB3c iHd5yb"><div role="button" class="U26fgb mUbCce fKz7Od i3PoXe M9Bg4d" jscontroller="VXdfxd" jsaction="click:cOuCgd; mousedown:UX7yZ; mouseup:lbsD7e; mouseenter:tfO1Yc; mouseleave:JywGue; focus:AHmuwe; blur:O22p3e; contextmenu:mg9Pef;touchstart:p6p2H; touchmove:FwuNnf; touchend:yfqBxc(preventDefault=true); touchcancel:JMtRjd;" jsshadow jsname="lfEfFf" aria-label="Search" aria-disabled="false" tabindex="0" data-tooltip="Search" data-tooltip-vertical-offset="-12" data-tooltip-horizontal-offset="0"><div class="VTBa7b MbhUzd" jsname="ksKsZd"></div><span jsslot class="xjKiLb"><span class="Ce1Y1c" style="top: -12px"><svg class="vu8Pwe" viewBox="0 0 24 24" focusable="false"><path d="M15.5 14h-.79l-.28-.27C15.41 12.59 16 11.11 16 9.5 16 5.91 13.09 3 9.5 3S3 5.91 3 9.5 5.91 16 9.5 16c1.61 0 3.09-.59 4.23-1.57l.27.28v.79l5 4.99L20.49 19l-4.99-5zm-6 0C7.01 14 5 11.99 5 9.5S7.01 5 9.5 5 14 7.01 14 9.5 11.99 14 9.5 14z"/><path d="M0 0h24v24H0z" fill="none"/></svg></span></span></div><div class="EmVfjc SKShhf" data-loadingmessage="Loading…" jscontroller="qAKInc" jsaction="animationend:kWijWc;dyRcpb:dyRcpb" jsname="aZ2wEe"><div class="Cg7hO" aria-live="assertive" jsname="vyyg5"></div><div jsname="Hxlbvc" class="xu46lf"><div class="ir3uv uWlRce co39ub"><div class="xq3j6 ERcjC"><div class="X6jHbb GOJTSe"></div></div><div class="HBnAAc"><div class="X6jHbb GOJTSe"></div></div><div class="xq3j6 dj3yTd"><div class="X6jHbb GOJTSe"></div></div></div><div class="ir3uv GFoASc Cn087"><div class="xq3j6 ERcjC"><div class="X6jHbb GOJTSe"></div></div><div class="HBnAAc"><div class="X6jHbb GOJTSe"></div></div><div class="xq3j6 dj3yTd"><div class="X6jHbb GOJTSe"></div></div></div><div class="ir3uv WpeOqd hfsr6b"><div class="xq3j6 ERcjC"><div class="X6jHbb GOJTSe"></div></div><div class="HBnAAc"><div class="X6jHbb GOJTSe"></div></div><div class="xq3j6 dj3yTd"><div class="X6jHbb GOJTSe"></div></div></div><div class="ir3uv rHV3jf EjXFBf"><div class="xq3j6 ERcjC"><div class="X6jHbb GOJTSe"></div></div><div class="HBnAAc"><div class="X6jHbb GOJTSe"></div></div><div class="xq3j6 dj3yTd"><div class="X6jHbb GOJTSe"></div></div></div></div></div><div role="button" class="U26fgb mUbCce fKz7Od JyJRXe M9Bg4d" jscontroller="VXdfxd" jsaction="click:cOuCgd; mousedown:UX7yZ; mouseup:lbsD7e; mouseenter:tfO1Yc; mouseleave:JywGue; focus:AHmuwe; blur:O22p3e; contextmenu:mg9Pef;touchstart:p6p2H; touchmove:FwuNnf; touchend:yfqBxc(preventDefault=true); touchcancel:JMtRjd;" jsshadow jsname="m1xNUe" aria-label="Back to site" aria-disabled="false" tabindex="0" data-tooltip="Back to site" data-tooltip-vertical-offset="-12" data-tooltip-horizontal-offset="0"><div class="VTBa7b MbhUzd" jsname="ksKsZd"></div><span jsslot class="xjKiLb"><span class="Ce1Y1c" style="top: -12px"><svg class="V4YR2c" viewBox="0 0 24 24" focusable="false"><path d="M0 0h24v24H0z" fill="none"/><path d="M20 11H7.83l5.59-5.59L12 4l-8 8 8 8 1.41-1.41L7.83 13H20v-2z"/></svg></span></span></div></span><div class="Xb9hP"><input type="search" class="whsOnd zHQkBf" jsname="YPqjbf" autocomplete="off" tabindex="0" aria-label="Search this site" value="" aria-disabled="false" autofocus role="combobox" data-initial-value=""/><div jsname="LwH6nd" class="ndJi5d snByac" aria-hidden="true">Search this site</div></div><span jsslot class="A37UZe sxyYjd MQL3Ob"><div role="button" class="U26fgb mUbCce fKz7Od Kk06A M9Bg4d" jscontroller="VXdfxd" jsaction="click:cOuCgd; mousedown:UX7yZ; mouseup:lbsD7e; mouseenter:tfO1Yc; mouseleave:JywGue; focus:AHmuwe; blur:O22p3e; contextmenu:mg9Pef;touchstart:p6p2H; touchmove:FwuNnf; touchend:yfqBxc(preventDefault=true); touchcancel:JMtRjd;" jsshadow jsname="pZn8Oc" aria-label="Clear search" aria-disabled="false" tabindex="0" data-tooltip="Clear search" data-tooltip-vertical-offset="-12" data-tooltip-horizontal-offset="0"><div class="VTBa7b MbhUzd" jsname="ksKsZd"></div><span jsslot class="xjKiLb"><span class="Ce1Y1c" style="top: -12px"><svg class="fAUEUd" viewBox="0 0 24 24" focusable="false"><path d="M19 6.41L17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12z"></path><path d="M0 0h24v24H0z" fill="none"></path></svg></span></span></div></span><div class="i9lrp mIZh1c"></div><div jsname="XmnwAc" class="OabDMe cXrdqd"></div></div></div><div class="LXRPh"><div jsname="ty6ygf" class="ovnfwe Is7Fhb"></div></div></div></div></div></div></div><div jsname="tiN4bf"><style nonce="I0EXnkVM2EFUPefyDO3QGA">.rrJNTc{opacity: 0;}.bKy5e{pointer-events: none; position: absolute; top: 0;}</style><div class="bKy5e"><div class="rrJNTc" tabindex="-1"><div class="VfPpkd-dgl2Hf-ppHlrf-sM5MNb" data-is-touch-wrapper='true'><button class="VfPpkd-LgbsSe VfPpkd-LgbsSe-OWXEXe-dgl2Hf LjDxcd XhPA0b LQeN7 WsSUlf jz7fPb" jscontroller="soHxf" jsaction="click:cOuCgd; mousedown:UX7yZ; mouseup:lbsD7e; mouseenter:tfO1Yc; mouseleave:JywGue; touchstart:p6p2H; touchmove:FwuNnf; touchend:yfqBxc; touchcancel:JMtRjd; focus:AHmuwe; blur:O22p3e; contextmenu:mg9Pef;mlnRJb:fLiPzd;" data-idom-class="LjDxcd XhPA0b LQeN7 WsSUlf jz7fPb" jsname="z2EeY" tabindex="0"><div class="VfPpkd-Jh9lGc"></div><div class="VfPpkd-J1Ukfc-LhBDec"></div><div class="VfPpkd-RLmnJb"></div><span jsname="V67aGc" class="VfPpkd-vQzf8d">Skip to main content</span></button></div><div class="VfPpkd-dgl2Hf-ppHlrf-sM5MNb" data-is-touch-wrapper='true'><button class="VfPpkd-LgbsSe VfPpkd-LgbsSe-OWXEXe-dgl2Hf LjDxcd XhPA0b LQeN7 WsSUlf br90J" jscontroller="soHxf" jsaction="click:cOuCgd; mousedown:UX7yZ; mouseup:lbsD7e; mouseenter:tfO1Yc; mouseleave:JywGue; touchstart:p6p2H; touchmove:FwuNnf; touchend:yfqBxc; touchcancel:JMtRjd; focus:AHmuwe; blur:O22p3e; contextmenu:mg9Pef;mlnRJb:fLiPzd;" data-idom-class="LjDxcd XhPA0b LQeN7 WsSUlf br90J" jsname="ilzYPe" tabindex="0"><div class="VfPpkd-Jh9lGc"></div><div class="VfPpkd-J1Ukfc-LhBDec"></div><div class="VfPpkd-RLmnJb"></div><span jsname="V67aGc" class="VfPpkd-vQzf8d">Skip to navigation</span></button></div></div></div><div class="M63kCb N63NQ"></div><div class="QZ3zWd"><div class="fktJzd AKpWA fOU46b G9Qloe XeSM4 XxIgdb" jsname="UzWXSb" data-uses-custom-theme="false" data-legacy-theme-name="QualityBasics" data-legacy-theme-font-kit="Light" data-legacy-theme-color-kit="Blue" jscontroller="Md9ENb" jsaction="gsiSmd:Ffcznf;yj5fUd:cpPetb;HNXL3:q0Vyke;e2SXKd:IPDu5e;BdXpgd:nhk7K;rcuQ6b:WYd;"><header id="atIdViewHeader"><div class="BbxBP HP6J1d K5Zlne" jsname="WA9qLc" jscontroller="RQOkef" jsaction="rcuQ6b:JdcaS;MxH79b:JdcaS;VbOlFf:ywL4Jf;FaOgy:ywL4Jf; keydown:Hq2uPe; wheel:Ut4Ahc;" data-top-navigation="true" data-is-preview="false"><div class="DXsoRd YTv4We oNsfjf" role="button" tabindex="0" jsaction="click:LUvzV" jsname="z4Tpl" id="s9iPrd" aria-haspopup="true" aria-controls="yuynLe" aria-expanded="false"><svg class="wFCWne" viewBox="0 0 24 24" stroke="currentColor" jsname="B1n9ub" focusable="false"><g transform="translate(12,12)"><path class="hlJH0" d="M-9 -5 L9 -5" fill="none" stroke-width="2"/><path class="HBu6N" d="M-9 0 L9 0" fill="none" stroke-width="2"/><path class="cLAGQe" d="M-9 5 L9 5" fill="none" stroke-width="2"/></g></svg></div><nav class="JzO0Vc" jsname="ihoMLd" role="navigation" tabindex="-1" id="yuynLe" jsaction="transitionend:UD2r5"><ul class="jYxBte Fpy8Db" tabindex="-1"><li jsname="ibnC6b" data-nav-level="1"><div class="PsKE7e r8s4j-R6PoUb IKA38e baH5ib oNsfjf"><div class="I35ICb" jsaction="keydown:mPuKz(QwLHlb); click:vHQTA(QwLHlb);"><a class="aJHbb dk90Ob hDrhEe HlqNPb" jsname="QwLHlb" role="link" tabindex="0" data-navtype="1" href="/view/soea2022/home" data-url="/view/soea2022/home" data-type="1" data-level="1">Home</a></div></div></li><li jsname="ibnC6b" data-nav-level="1"><div class="PsKE7e r8s4j-R6PoUb IKA38e baH5ib oNsfjf"><div class="I35ICb" jsaction="keydown:mPuKz(QwLHlb); click:vHQTA(QwLHlb);"><a class="aJHbb dk90Ob hDrhEe HlqNPb" jsname="QwLHlb" role="link" tabindex="0" data-navtype="1" href="/view/soea2022/paper-submission" data-url="/view/soea2022/paper-submission" data-type="1" data-level="1">Paper Submission</a></div></div></li><li jsname="ibnC6b" data-nav-level="1"><div class="PsKE7e r8s4j-R6PoUb IKA38e baH5ib oNsfjf"><div class="I35ICb" jsaction="keydown:mPuKz(QwLHlb); click:vHQTA(QwLHlb);"><a class="aJHbb dk90Ob hDrhEe HlqNPb" jsname="QwLHlb" role="link" tabindex="0" data-navtype="1" href="/view/soea2022/program-commitee" data-url="/view/soea2022/program-commitee" data-type="1" data-level="1">Program Commitee</a></div></div></li><li jsname="ibnC6b" data-nav-level="1"><div class="PsKE7e r8s4j-R6PoUb IKA38e baH5ib oNsfjf lhZOrc" aria-current="true"><div class="I35ICb" jsaction="keydown:mPuKz(QwLHlb); click:vHQTA(QwLHlb);"><a class="aJHbb dk90Ob hDrhEe HlqNPb" jsname="QwLHlb" role="link" tabindex="0" data-navtype="1" aria-selected="true" href="/view/soea2022/accepted-papers" data-url="/view/soea2022/accepted-papers" data-type="1" data-level="1">Accepted Papers</a></div></div></li><li jsname="ibnC6b" data-nav-level="1"><div class="PsKE7e r8s4j-R6PoUb IKA38e baH5ib oNsfjf"><div class="I35ICb" jsaction="keydown:mPuKz(QwLHlb); click:vHQTA(QwLHlb);"><a class="aJHbb dk90Ob hDrhEe HlqNPb" jsname="QwLHlb" role="link" tabindex="0" data-navtype="1" href="/view/soea2022/venue" data-url="/view/soea2022/venue" data-type="1" data-level="1">Venue</a></div></div></li><li jsname="ibnC6b" data-nav-level="1"><div class="PsKE7e r8s4j-R6PoUb IKA38e baH5ib oNsfjf"><div class="I35ICb" jsaction="keydown:mPuKz(QwLHlb); click:vHQTA(QwLHlb);"><a class="aJHbb dk90Ob hDrhEe HlqNPb" jsname="QwLHlb" role="link" tabindex="0" data-navtype="1" href="/view/soea2022/contact" data-url="/view/soea2022/contact" data-type="1" data-level="1">Contact</a></div></div></li></ul></nav><div class="VLoccc K5Zlne QDWEj U8eYrb" jsname="rtFGi"><div class="Pvc6xe"><div jsname="I8J07e" class="TlfmSc YSH9J"> </div><nav class="plFg0c" jscontroller="HXO1uc" jsaction="rcuQ6b:rcuQ6b;MxH79b:CfS0pe;" id="WDxLfe" data-is-preview="false" style="visibility: hidden;" role="navigation" tabindex="-1"><ul jsname="waIgnc" class="K1Ci7d oXBWEc jYxBte"><li jsname="ibnC6b" data-nav-level="1" class="VsJjtf"><div class="PsKE7e qV4dIc Qrrb5 YSH9J"><div class="I35ICb" jsaction="click:vHQTA(QwLHlb); keydown:mPuKz(QwLHlb);"><a class="aJHbb dk90Ob jgXgSe HlqNPb" jscontroller="yUHiM" jsaction="rcuQ6b:WYd;" jsname="QwLHlb" role="link" tabindex="0" data-navtype="1" href="/view/soea2022/home" data-url="/view/soea2022/home" data-type="1" data-level="1">Home</a></div></div><div class="rgLkl"></div></li><li jsname="ibnC6b" data-nav-level="1" class="VsJjtf"><div class="PsKE7e qV4dIc Qrrb5 YSH9J"><div class="I35ICb" jsaction="click:vHQTA(QwLHlb); keydown:mPuKz(QwLHlb);"><a class="aJHbb dk90Ob jgXgSe HlqNPb" jscontroller="yUHiM" jsaction="rcuQ6b:WYd;" jsname="QwLHlb" role="link" tabindex="0" data-navtype="1" href="/view/soea2022/paper-submission" data-url="/view/soea2022/paper-submission" data-type="1" data-level="1">Paper Submission</a></div></div><div class="rgLkl"></div></li><li jsname="ibnC6b" data-nav-level="1" class="VsJjtf"><div class="PsKE7e qV4dIc Qrrb5 YSH9J"><div class="I35ICb" jsaction="click:vHQTA(QwLHlb); keydown:mPuKz(QwLHlb);"><a class="aJHbb dk90Ob jgXgSe HlqNPb" jscontroller="yUHiM" jsaction="rcuQ6b:WYd;" jsname="QwLHlb" role="link" tabindex="0" data-navtype="1" href="/view/soea2022/program-commitee" data-url="/view/soea2022/program-commitee" data-type="1" data-level="1">Program Commitee</a></div></div><div class="rgLkl"></div></li><li jsname="ibnC6b" data-nav-level="1" class="VsJjtf"><div class="PsKE7e qV4dIc Qrrb5 YSH9J M9vuGd" aria-current="true"><div class="I35ICb" jsaction="click:vHQTA(QwLHlb); keydown:mPuKz(QwLHlb);"><a class="aJHbb dk90Ob jgXgSe HlqNPb" jscontroller="yUHiM" jsaction="rcuQ6b:WYd;" jsname="QwLHlb" role="link" tabindex="0" data-navtype="1" aria-selected="true" href="/view/soea2022/accepted-papers" data-url="/view/soea2022/accepted-papers" data-type="1" data-level="1">Accepted Papers</a></div></div><div class="rgLkl"></div></li><li jsname="ibnC6b" data-nav-level="1" class="VsJjtf"><div class="PsKE7e qV4dIc Qrrb5 YSH9J"><div class="I35ICb" jsaction="click:vHQTA(QwLHlb); keydown:mPuKz(QwLHlb);"><a class="aJHbb dk90Ob jgXgSe HlqNPb" jscontroller="yUHiM" jsaction="rcuQ6b:WYd;" jsname="QwLHlb" role="link" tabindex="0" data-navtype="1" href="/view/soea2022/venue" data-url="/view/soea2022/venue" data-type="1" data-level="1">Venue</a></div></div><div class="rgLkl"></div></li><li jsname="ibnC6b" data-nav-level="1" class="VsJjtf"><div class="PsKE7e qV4dIc Qrrb5 YSH9J"><div class="I35ICb" jsaction="click:vHQTA(QwLHlb); keydown:mPuKz(QwLHlb);"><a class="aJHbb dk90Ob jgXgSe HlqNPb" jscontroller="yUHiM" jsaction="rcuQ6b:WYd;" jsname="QwLHlb" role="link" tabindex="0" data-navtype="1" href="/view/soea2022/contact" data-url="/view/soea2022/contact" data-type="1" data-level="1">Contact</a></div></div><div class="rgLkl"></div></li><li jsname="ibnC6b" data-nav-level="1" class="VsJjtf ZmrVpf oXBWEc" more-menu-item jsaction="mouseenter:Vx8Jlb; mouseleave:ysDRUd"><div class="PsKE7e qV4dIc Qrrb5 YSH9J"><div class="I35ICb" jsaction="click:vHQTA(QwLHlb); keydown:mPuKz(QwLHlb);"><a class="aJHbb dk90Ob jgXgSe HlqNPb" jscontroller="yUHiM" jsaction="rcuQ6b:WYd;" jsname="QwLHlb" role="link" tabindex="0" data-navtype="1" aria-expanded="false" aria-haspopup="true" data-level="1">More</a><div class="mBHtvb u5fiyc" role="presentation" title="Expand/Collapse" jsaction="click:oESVTe" jsname="ix0Hvc"><svg class="dvmRw" viewBox="0 0 24 24" stroke="currentColor" jsname="HIH2V" focusable="false"><g transform="translate(9.7,12) rotate(45)"><path class="K4B8Y" d="M-4.2 0 L4.2 0" stroke-width="2"/></g><g transform="translate(14.3,12) rotate(-45)"><path class="MrYMx" d="M-4.2 0 L4.2 0" stroke-width="2"/></g></svg></div></div></div><div class="oGuwee eWDljc RPRy1e Mkt3Tc" style="display:none;" jsname="QXE97" jsaction="transitionend:SJBdh" role="group"><ul class="VcS63b"><li jsname="ibnC6b" data-nav-level="2" class="ijMPi ZmrVpf" in-more-item><div class="PsKE7e IKA38e oNsfjf"><div class="I35ICb" jsaction="click:vHQTA(QwLHlb); keydown:mPuKz(QwLHlb);"><a class="aJHbb hDrhEe HlqNPb" jscontroller="yUHiM" jsaction="rcuQ6b:WYd;" jsname="QwLHlb" role="link" tabindex="0" data-navtype="1" href="/view/soea2022/home" data-url="/view/soea2022/home" data-type="1" data-in-more-submenu="true" data-level="2">Home</a></div></div></li><li jsname="ibnC6b" data-nav-level="2" class="ijMPi ZmrVpf" in-more-item><div class="PsKE7e IKA38e oNsfjf"><div class="I35ICb" jsaction="click:vHQTA(QwLHlb); keydown:mPuKz(QwLHlb);"><a class="aJHbb hDrhEe HlqNPb" jscontroller="yUHiM" jsaction="rcuQ6b:WYd;" jsname="QwLHlb" role="link" tabindex="0" data-navtype="1" href="/view/soea2022/paper-submission" data-url="/view/soea2022/paper-submission" data-type="1" data-in-more-submenu="true" data-level="2">Paper Submission</a></div></div></li><li jsname="ibnC6b" data-nav-level="2" class="ijMPi ZmrVpf" in-more-item><div class="PsKE7e IKA38e oNsfjf"><div class="I35ICb" jsaction="click:vHQTA(QwLHlb); keydown:mPuKz(QwLHlb);"><a class="aJHbb hDrhEe HlqNPb" jscontroller="yUHiM" jsaction="rcuQ6b:WYd;" jsname="QwLHlb" role="link" tabindex="0" data-navtype="1" href="/view/soea2022/program-commitee" data-url="/view/soea2022/program-commitee" data-type="1" data-in-more-submenu="true" data-level="2">Program Commitee</a></div></div></li><li jsname="ibnC6b" data-nav-level="2" class="ijMPi ZmrVpf" in-more-item><div class="PsKE7e IKA38e oNsfjf lhZOrc" aria-current="true"><div class="I35ICb" jsaction="click:vHQTA(QwLHlb); keydown:mPuKz(QwLHlb);"><a class="aJHbb hDrhEe HlqNPb" jscontroller="yUHiM" jsaction="rcuQ6b:WYd;" jsname="QwLHlb" role="link" tabindex="0" data-navtype="1" aria-selected="true" href="/view/soea2022/accepted-papers" data-url="/view/soea2022/accepted-papers" data-type="1" data-in-more-submenu="true" data-level="2">Accepted Papers</a></div></div></li><li jsname="ibnC6b" data-nav-level="2" class="ijMPi ZmrVpf" in-more-item><div class="PsKE7e IKA38e oNsfjf"><div class="I35ICb" jsaction="click:vHQTA(QwLHlb); keydown:mPuKz(QwLHlb);"><a class="aJHbb hDrhEe HlqNPb" jscontroller="yUHiM" jsaction="rcuQ6b:WYd;" jsname="QwLHlb" role="link" tabindex="0" data-navtype="1" href="/view/soea2022/venue" data-url="/view/soea2022/venue" data-type="1" data-in-more-submenu="true" data-level="2">Venue</a></div></div></li><li jsname="ibnC6b" data-nav-level="2" class="ijMPi ZmrVpf" in-more-item><div class="PsKE7e IKA38e oNsfjf"><div class="I35ICb" jsaction="click:vHQTA(QwLHlb); keydown:mPuKz(QwLHlb);"><a class="aJHbb hDrhEe HlqNPb" jscontroller="yUHiM" jsaction="rcuQ6b:WYd;" jsname="QwLHlb" role="link" tabindex="0" data-navtype="1" href="/view/soea2022/contact" data-url="/view/soea2022/contact" data-type="1" data-in-more-submenu="true" data-level="2">Contact</a></div></div></li></ul></div></li></ul></nav><div jscontroller="gK4msf" class="RBEWZc" jsname="h04Zod" jsaction="rcuQ6b:WYd;JIbuQc:AT95Ub;VbOlFf:HgE5D;FaOgy:HgE5D;MxH79b:JdcaS;" data-side-navigation="false"><div role="button" class="U26fgb mUbCce fKz7Od iWs3gf Wdnjke M9Bg4d" jscontroller="VXdfxd" jsaction="click:cOuCgd; mousedown:UX7yZ; mouseup:lbsD7e; mouseenter:tfO1Yc; mouseleave:JywGue; focus:AHmuwe; blur:O22p3e; contextmenu:mg9Pef;touchstart:p6p2H; touchmove:FwuNnf; touchend:yfqBxc(preventDefault=true); touchcancel:JMtRjd;" jsshadow jsname="R9oOZd" aria-label="Open search bar" aria-disabled="false" tabindex="0" data-tooltip="Open search bar" aria-expanded="false" data-tooltip-vertical-offset="-12" data-tooltip-horizontal-offset="0"><div class="VTBa7b MbhUzd" jsname="ksKsZd"></div><span jsslot class="xjKiLb"><span class="Ce1Y1c" style="top: -12px"><svg class="vu8Pwe tCHXDc YSH9J" viewBox="0 0 24 24" focusable="false"><path d="M15.5 14h-.79l-.28-.27C15.41 12.59 16 11.11 16 9.5 16 5.91 13.09 3 9.5 3S3 5.91 3 9.5 5.91 16 9.5 16c1.61 0 3.09-.59 4.23-1.57l.27.28v.79l5 4.99L20.49 19l-4.99-5zm-6 0C7.01 14 5 11.99 5 9.5S7.01 5 9.5 5 14 7.01 14 9.5 11.99 14 9.5 14z"/><path d="M0 0h24v24H0z" fill="none"/></svg></span></span></div></div></div><div jsname="mADGA" class="zDUgLc"></div></div><div class="TxnWlb" jsname="BDdyze" jsaction="click:LUvzV"></div></div></header><div role="main" tabindex="-1" class="UtePc RCETm" dir="ltr"><section id="h.676d26285ac99631_25" class="yaqOZd LB7kq cJgDec nyKByd O13XJf KEFykf" style=""><div class="Nu95r"><div class="IFuOkc" style="background-size: cover; background-position: center center; background-image: url(https://lh5.googleusercontent.com/Fuyz451TWQz3Tf158T-7vbVVPnYNXeE-gRsyVeiGhJL7rJtr4WYcUj9PId6RFEYX7lC6lCw_TWU8JggyXpkVt8o=w16383);" jsname="LQX2Vd"></div></div><div class="mYVXT"><div class="LS81yb VICjCf j5pSsc db35Fc" tabindex="-1"><div class="hJDwNd-AhqUyc-uQSCkd Ft7HRd-AhqUyc-uQSCkd purZT-AhqUyc-II5mzb ZcASvf-AhqUyc-II5mzb pSzOP-AhqUyc-qWD73c Ktthjf-AhqUyc-qWD73c JNdkSc SQVYQc"><div class="JNdkSc-SmKAyb LkDMRd"><div class="" jscontroller="sGwD4d" jsaction="zXBUYb:zTPCnb;zQF9Uc:Qxe3nd;" jsname="F57UId"><div class="oKdM2c ZZyype Kzv0Me"><div id="h.676d26285ac99631_28" class="hJDwNd-AhqUyc-uQSCkd Ft7HRd-AhqUyc-uQSCkd jXK9ad D2fZ2 zu5uec OjCsFc dmUFtb wHaque g5GTcb JYTMs"><div class="jXK9ad-SmKAyb"><div class="tyJCtd mGzaTb Depvyb baZpAe lkHyyc"><h2 id="h.iqgisv8b4ok9" dir="ltr" class="CDt4Ke zfr3Q JYVBee" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 4pt; margin-top: 14pt; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0; text-align: center;"><span class=" jgG6ef" style="color: #ffffff; font-family: 'Times New Roman'; font-variant: normal; vertical-align: baseline;"><strong>6</strong></span><sup style="color: #ffffff; font-family: 'Times New Roman'; font-size: 10.799999999999999pt; font-variant: normal;"><strong>th</strong></sup><span class=" jgG6ef" style="color: #ffffff; font-family: 'Times New Roman'; font-variant: normal; vertical-align: baseline;"><strong> International Conference on Software Engineering and Applications (SOEA 2022)</strong></span></h2><h3 id="h.qr0hhwz0urqc" dir="ltr" class="CDt4Ke zfr3Q OmQG5e" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 2pt; margin-top: 11pt; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0; text-align: center;"><span style="color: #ffffff; font-family: 'Times New Roman'; font-size: 14pt; font-variant: normal; vertical-align: baseline;"><strong>January 29~30, 2022, Copenhagen, Denmark</strong></span></h3></div></div></div></div></div></div></div></div></div><div class="DnLU4" jsaction="JIbuQc:v5IJLd(ipHvib);"><div role="button" class="U26fgb mUbCce fKz7Od HqAAld Wew9ke M9Bg4d" jscontroller="VXdfxd" jsaction="click:cOuCgd; mousedown:UX7yZ; mouseup:lbsD7e; mouseenter:tfO1Yc; mouseleave:JywGue; focus:AHmuwe; blur:O22p3e; contextmenu:mg9Pef;touchstart:p6p2H; touchmove:FwuNnf; touchend:yfqBxc(preventDefault=true); touchcancel:JMtRjd;" jsshadow jsname="ipHvib" aria-label="Scroll down" aria-disabled="false" tabindex="0"><div class="VTBa7b MbhUzd" jsname="ksKsZd"></div><span jsslot class="xjKiLb"><span class="Ce1Y1c" style="top: -12px"><svg class="XE8yyf" viewBox="0 0 24 24" focusable="false"><path d="M7.41 7.84L12 12.42l4.59-4.58L18 9.25l-6 6-6-6z"/><path d="M0-.75h24v24H0z" fill="none"/></svg></span></span></div></div></section><section id="h.676d26285ac99631_47" class="yaqOZd" style=""><div class="IFuOkc"></div><div class="mYVXT"><div class="LS81yb VICjCf j5pSsc db35Fc" tabindex="-1"><div class="hJDwNd-AhqUyc-uQSCkd Ft7HRd-AhqUyc-uQSCkd purZT-AhqUyc-II5mzb ZcASvf-AhqUyc-II5mzb pSzOP-AhqUyc-qWD73c Ktthjf-AhqUyc-qWD73c JNdkSc SQVYQc"><div class="JNdkSc-SmKAyb LkDMRd"><div class="" jscontroller="sGwD4d" jsaction="zXBUYb:zTPCnb;zQF9Uc:Qxe3nd;" jsname="F57UId"><div class="oKdM2c ZZyype Kzv0Me"><div id="h.676d26285ac99631_50" class="hJDwNd-AhqUyc-uQSCkd Ft7HRd-AhqUyc-uQSCkd jXK9ad D2fZ2 zu5uec OjCsFc dmUFtb wHaque g5GTcb JYTMs"><div class="jXK9ad-SmKAyb"><div class="tyJCtd mGzaTb Depvyb baZpAe"><div id="h.67hz89bce9mn" class="CobnVe aP9Z7e"></div><h2 id="h.67hz89bce9mn_l" dir="ltr" class="CDt4Ke zfr3Q JYVBee" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 2pt; margin-top: 11pt; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0; text-align: center;" tabindex="-1"><div jscontroller="Ae65rd" jsaction="touchstart:UrsOsc; click:KjsqPd; focusout:QZoaZ; mouseover:y0pDld; mouseout:dq0hvd;fv1Rjc:jbFSOd;CrfLRd:SzACGe;" class="CjVfdc"><div class="PPhIP rviiZ" jsname="haAclf"><div role="presentation" class="U26fgb mUbCce fKz7Od LRAOtb Znu9nd M9Bg4d" jscontroller="mxS5xe" jsaction="click:cOuCgd; mousedown:UX7yZ; mouseup:lbsD7e; mouseenter:tfO1Yc; mouseleave:JywGue; focus:AHmuwe; blur:O22p3e; contextmenu:mg9Pef;" jsshadow aria-describedby="h.67hz89bce9mn_l" aria-label="Copy heading link" aria-disabled="false" data-tooltip="Copy heading link" aria-hidden="true" data-tooltip-position="top" data-tooltip-vertical-offset="12" data-tooltip-horizontal-offset="0"><a class="FKF6mc TpQm9d" href="#h.67hz89bce9mn" aria-label="Copy heading link" jsname="hiK3ld" role="button" aria-describedby="h.67hz89bce9mn_l"><div class="VTBa7b MbhUzd" jsname="ksKsZd"></div><span jsslot class="xjKiLb"><span class="Ce1Y1c" style="top: -11px"><svg class="OUGEr QdAdhf" width="22px" height="22px" viewBox="0 0 24 24" fill="currentColor" focusable="false"><path d="M0 0h24v24H0z" fill="none"/><path d="M3.9 12c0-1.71 1.39-3.1 3.1-3.1h4V7H7c-2.76 0-5 2.24-5 5s2.24 5 5 5h4v-1.9H7c-1.71 0-3.1-1.39-3.1-3.1zM8 13h8v-2H8v2zm9-6h-4v1.9h4c1.71 0 3.1 1.39 3.1 3.1s-1.39 3.1-3.1 3.1h-4V17h4c2.76 0 5-2.24 5-5s-2.24-5-5-5z"/></svg></span></span></a></div></div><span style="color: #000000; font-family: 'Times New Roman'; font-size: 14pt; font-variant: normal; vertical-align: baseline;"><strong>Accepted Papers</strong></span></div></h2></div></div></div></div></div></div></div></div></div></section><section id="h.676d26285ac99631_54" class="yaqOZd" style=""><div class="IFuOkc"></div><div class="mYVXT"><div class="LS81yb VICjCf j5pSsc db35Fc" tabindex="-1"><div class="hJDwNd-AhqUyc-uQSCkd Ft7HRd-AhqUyc-uQSCkd purZT-AhqUyc-II5mzb ZcASvf-AhqUyc-II5mzb pSzOP-AhqUyc-qWD73c Ktthjf-AhqUyc-qWD73c JNdkSc SQVYQc"><div class="JNdkSc-SmKAyb LkDMRd"><div class="" jscontroller="sGwD4d" jsaction="zXBUYb:zTPCnb;zQF9Uc:Qxe3nd;" jsname="F57UId"><div class="oKdM2c ZZyype Kzv0Me"><div id="h.676d26285ac99631_51" class="hJDwNd-AhqUyc-uQSCkd Ft7HRd-AhqUyc-uQSCkd jXK9ad D2fZ2 zu5uec OjCsFc dmUFtb wHaque g5GTcb JYTMs"><div class="jXK9ad-SmKAyb"><div class="tyJCtd mGzaTb Depvyb baZpAe"><p id="h.g68f7ul81k3l" dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 2pt; margin-top: 11pt; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 14pt; font-variant: normal; vertical-align: baseline;"><strong>Using Convolutional Neural Network to Enhance Heart Diseases Predictions in South African Men Living in the Western Cape Region</strong></span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0; text-align: justify; white-space: normal;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">Elias Tabane, University of South Africa, South Africa</span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0; text-align: justify; white-space: normal;"><br></p><p id="h.lsmk7iw8uhvn" dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 2pt; margin-top: 11pt; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; vertical-align: baseline;"><strong>ABSTRACT</strong></span></p><p id="h.zeeh14f7ckq4" dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 2pt; margin-top: 11pt; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><br></p><small dir="ltr" class="CDt4Ke zfr3Q TMjjoe" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; display: block; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0; text-align: justify; white-space: normal;"><span style="font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">The medical analysis space is most every now and again referenced to be a valu-able wellspring of rich information yet with helpless acumens with medical input . The Heart Disease is among the significant reasons for mortally all around the world. Early recognition of heart disease might aid the decrease rates that is identified with mortality, but the significant experience lies in the trouble and vastness of this information with regards to anticipating while applying the ordinary strategies . The point of this re-search exposition is to utilize the authentic medical information to foresee CHD utilizing Machine Learning Algorithms. The extent of this paper is restricted to utilizing strategic relapse Algorithm. Utilizing the South African Heart Dis-ease dataset of 462 examples, the model is based on Python with 10-crease cross validation as-sessment philosophy.</span></small><small dir="ltr" class="CDt4Ke zfr3Q TMjjoe" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; display: block; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0; text-align: justify; white-space: normal;"><br></small><p id="h.297rve3yn0uj" dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 2pt; margin-top: 11pt; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; vertical-align: baseline;"><strong>KEYWORDS</strong></span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0; text-align: justify; white-space: normal;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">Coronary Heart Disease, Support Vector machine, Random forest, Logistical regression., convolutional neural network.</span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><br></p><p id="h.3g0c3fgm8aq" dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 2pt; margin-top: 11pt; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 14pt; font-variant: normal; vertical-align: baseline;"><strong>Brain Oscillatory Representations of Vibrotactile Parameters: an ECG Study</strong></span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0; text-align: justify; white-space: normal;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">Xinrong WANG, Xinyue FANG, Xinyi ZHENG, Xuemei DENG, Yong LI, and Mei WANG, Department of Mechanical Engineering, Sichuan University, Chengdu, China</span></p><p id="h.uruk99uz02an" dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 2pt; margin-top: 11pt; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; vertical-align: baseline;"><strong>ABSTRACT</strong></span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0; text-align: justify; white-space: normal;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">In this work, we tried to explore brain oscillatory representations triggered by vibrotactile parameters. We utilized amplitude-modulated vibrotactile stimuli that have four envelope frequencies and four amplitudes. Brain oscillations in five frequency bands and ten channels were measured by noninvasive EEG technique, and they were represented in power spectral density (PSD) forms. Results showed that when envelope frequency (Fe)=20Hz or 40Hz, for all four amplitudes, brain oscillations over the ipsilateral sensorimotor cortex decrease with the frequency bands, additionally, a slight decrease of activation in the contralateral frontal regions was founded when amplitude (A)=0.8Grms. When amplitude (A)=0.8Grms, the overall variation tendency of spectrum was similar to that mentioned above. In terms of oscillatory differences, the activation regions were the bilateral sensorimotor cortex, additionally, a increase of oscillations in the frontal and parietal regions was founded when Fe=20Hz and Fe=40Hz. Results contribute to better physiological understandings for physical vibrotactile parameters.</span></p><p id="h.y3h1s8j5saqc" dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 2pt; margin-top: 11pt; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; vertical-align: baseline;"><strong>KEYWORDS</strong></span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0; text-align: justify; white-space: normal;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">Vibrotactile Stimuli, Brain Oscillations, Haptic Feedback.</span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><br></p><p id="h.cqlod7mx8y9u" dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 2pt; margin-top: 11pt; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 14pt; font-variant: normal; vertical-align: baseline;"><strong>Fixed-Point Code Synthesis for Neural Networks</strong></span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0; text-align: justify; white-space: normal;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">Hanane Benmaghnia</span><sup style="color: #000000; font-family: 'Times New Roman'; font-size: 7.199999999999999pt; font-variant: normal; font-weight: normal;">1</sup><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">, Matthieu Martel</span><sup style="color: #000000; font-family: 'Times New Roman'; font-size: 7.199999999999999pt; font-variant: normal; font-weight: normal;">1,2</sup><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">, and Yassamine Seladji</span><sup style="color: #000000; font-family: 'Times New Roman'; font-size: 7.199999999999999pt; font-variant: normal; font-weight: normal;">3</sup><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">, </span><sup style="color: #000000; font-family: 'Times New Roman'; font-size: 7.199999999999999pt; font-variant: normal; font-weight: normal;">1</sup><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">University of Perpignan Via Domitia, Perpignan, France, </span><sup style="color: #000000; font-family: 'Times New Roman'; font-size: 7.199999999999999pt; font-variant: normal; font-weight: normal;">2</sup><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">Numalis, Cap Omega, Rond-point Benjamin Franklin 34960 Montpellier, France, </span><sup style="color: #000000; font-family: 'Times New Roman'; font-size: 7.199999999999999pt; font-variant: normal; font-weight: normal;">3</sup><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">University of Tlemcen Aboubekr Belkaid, Tlemcen, Algeria</span></p><p id="h.jtkr0v1l8pgc" dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 2pt; margin-top: 11pt; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; vertical-align: baseline;"><strong>ABSTRACT</strong></span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0; text-align: justify; white-space: normal;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">Over the last few years, neural networks have started penetrating safety critical systems to take decisions in robots, rockets, autonomous driving car, etc. A problem is that these critical systems often have limited computing resources. Often, they use the fixed-point arithmetic for its many advantages (rapidity, compatibility with small memory devices.) In this article, a new technique is introduced to tune the formats (precision) of already trained neural networks using fixed-point arithmetic, which can be implemented using integer operations only. The new optimized neural network computes the output with fixed-point numbers without modifying the accuracy up to a threshold fixed by the user. A fixed-point code is synthesized for the new optimized neural network ensuring the respect of the threshold for any input vector belonging the range [xmin, xmax] determined during the analysis. From a technical point of view, we do a preliminary analysis of our floating neural network to determine the worst cases , then we generate a system of linear constraints among integer variables that we can solve by linear programming. The solution of this system is the new fixed-point format of each neuron. The experimental results obtained show the efficiency of our method which can ensure that the new fixed-point neural network has the same behavior as the initial floating-point neural network.</span></p><p id="h.xa6e3935lngv" dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 2pt; margin-top: 11pt; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; vertical-align: baseline;"><strong>KEYWORDS</strong></span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0; text-align: justify; white-space: normal;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">Computer Arithmetic, Code Synthesis, Formal Methods, Linear Programming, Numerical Accuracy, Static Analysis.</span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><br></p><p id="h.r8vgqqczgvao" dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 2pt; margin-top: 11pt; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 14pt; font-variant: normal; vertical-align: baseline;"><strong>Detection Datasets: Forged Characters for Passport and Driving Licence</strong></span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0; text-align: justify; white-space: normal;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">Teerath Kumar</span><sup style="color: #000000; font-family: 'Times New Roman'; font-size: 7.199999999999999pt; font-variant: normal; font-weight: normal;">1</sup><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">, Muhammad Turab</span><sup style="color: #000000; font-family: 'Times New Roman'; font-size: 7.199999999999999pt; font-variant: normal; font-weight: normal;">2</sup><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">, Shahnawaz Talpur</span><sup style="color: #000000; font-family: 'Times New Roman'; font-size: 7.199999999999999pt; font-variant: normal; font-weight: normal;">2</sup><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">, Rob Brennan</span><sup style="color: #000000; font-family: 'Times New Roman'; font-size: 7.199999999999999pt; font-variant: normal; font-weight: normal;">1</sup><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;"> and Malika Bendechache</span><sup style="color: #000000; font-family: 'Times New Roman'; font-size: 7.199999999999999pt; font-variant: normal; font-weight: normal;">1</sup><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">, </span><sup style="color: #000000; font-family: 'Times New Roman'; font-size: 7.199999999999999pt; font-variant: normal; font-weight: normal;">1</sup><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">CRT AI and ADAPT, School of Computing, Dublin City University, Ireland, </span><sup style="color: #000000; font-family: 'Times New Roman'; font-size: 7.199999999999999pt; font-variant: normal; font-weight: normal;">2</sup><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">Department of Computer Systems Engineering, Mehran University of Engineering and Technology, Jamshoro, Pakistan</span></p><p id="h.4pvjt0suw14e" dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 2pt; margin-top: 11pt; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; vertical-align: baseline;"><strong>ABSTRACT</strong></span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0; text-align: justify; white-space: normal;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">Forged characters detection from personal documents i.e. passport or driving licence is an extremely important and challenging task in digital image forensics, as forged information on personal documents can be used for fraud purposes i.e. theft, robbery etc. For any detection task i.e. forged character detection, deep learning models are data hungry and getting the forged characters dataset for personal documents is very difficult due to various reasons, including information privacy, unlabeled data or existing work is evaluated on private datasets with limited access and getting data labelled is another big challenge. To address these issues, we propose a new algorithm that generates two new datasets named forged characters detection on passport (FCD-P) and forged characters detection on driving licence (FCD-D). To the best of our knowledge, we are the first to release these datasets. The proposed algorithm first reads the plain image, then performs forging tasks i.e. randomly changes the position of the random character or randomly adds little noise. At the same time, the algorithm also records the bounding boxes of the forged characters. To meet real world situations, we perform multiple data augmentation on cards very carefully. Overall, each dataset consists of 15000 images, each image with size of 950 x 550. Our algorithm code, FCD-P and FCD-D are publicly available.</span></p><p id="h.kdostbojab5d" dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 2pt; margin-top: 11pt; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; vertical-align: baseline;"><strong>KEYWORDS</strong></span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0; text-align: justify; white-space: normal;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">Character detection dataset, Deep learning forgery, Forged character detection.</span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><br></p><p id="h.lf6zgnjd77vp" dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 2pt; margin-top: 11pt; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 14pt; font-variant: normal; vertical-align: baseline;"><strong>Stride Random Erasing Augmentation</strong></span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0; text-align: justify; white-space: normal;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">Teerath Kumar, Rob Brennan and Malika Bendechache, CRT AI and ADAPT, School of Computing, Dublin City University, Ireland</span></p><p id="h.ys8apwxph6ok" dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 2pt; margin-top: 11pt; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; vertical-align: baseline;"><strong>ABSTRACT</strong></span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0; text-align: justify; white-space: normal;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">This paper presents a new method for data augmentation called Stride Random Erasing Augmentation (SREA) to improve classification performance. In SREA, probability based strides of one image are pasted onto another image and also labels of both images are mixed with the same probability as the image mixing, to generate a new augmented image and augmented label. Stride augmentation overcomes limitations of the popular random erasing data augmentation method, where a random portion of an image is erased with 0 or 255 or the mean of a dataset without considering the location of the important feature(s) within the image. A variety of experiments have been performed using different network flavours and the popular datasets including fashion-MNIST, CIFAR10, CIFAR100 and STL10. The experiments showed that SREA is more generalized than both the baseline and random erasing method. Furthermore, the effect of stride size in SREA was investigated by performing experiments with different stride sizes. Random stride size showed better performance. SREA outperforms the baseline and random erasing especially on the fashion-MNIST dataset. To enable the reuse, reproduction and extension of SREA, the source code is provided in a public git repository.</span></p><p id="h.du4xjoiwrhnj" dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 2pt; margin-top: 11pt; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; vertical-align: baseline;"><strong>KEYWORDS</strong></span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0; text-align: justify; white-space: normal;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">Data Augmentation, Image Classification, Erasing Augmentation.</span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><br></p><p id="h.abl89qkuu91v" dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 2pt; margin-top: 11pt; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 14pt; font-variant: normal; vertical-align: baseline;"><strong>Research on Dual Channel News Headline Classification Based on ERNIE Pre-training Model</strong></span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0; text-align: justify; white-space: normal;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">Junjie Li and Hui Cao, Key Laboratory of Chinas Ethnic Languages and Information Technology of Ministry of Education Northwest Minzu University Lanzhou, China</span></p><p id="h.b2vg30yz85yn" dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 2pt; margin-top: 11pt; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; vertical-align: baseline;"><strong>ABSTRACT</strong></span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0; text-align: justify; white-space: normal;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">The quality and style of news headlines in the information age directly determine the click-through rate and popularity of their news content, and have a significant impact on the expression of news centers and the guidance of public opinion. Based on ERNIE to extract the lexical, semantic and contextual feature information of the bottom of the text, generate dynamic word vector representations that integrate the contextual context, and then use the BiLSTM-AT network channel to extract the global features of the contextual temporal information for a second time, and use the attention mechanism to The key part is given higher weight, and the DPCNN channel is used to extract long-distance text dependencies to obtain deep-level local features, and the dual-channel feature vectors are spliced, and finally passed into the fully connected layer and output the final classification result through Softmax. The experimental results show that this classification method has improved the accuracy of news headline classification compared with the multiple comparison models set in the experiment.</span></p><p id="h.rdtvply32us" dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 2pt; margin-top: 11pt; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; vertical-align: baseline;"><strong>KEYWORDS</strong></span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0; text-align: justify; white-space: normal;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">Text Classification, ERNIE, Dual-Channel, BiLSTM, Attention, DPCNN.</span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><br></p><p id="h.gh6oeih4ujgn" dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 2pt; margin-top: 11pt; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 14pt; font-variant: normal; vertical-align: baseline;"><strong>Advanced Service Data Provisioning In ROF-based Mobile Backhauls/Fronthauls</strong></span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0; text-align: justify; white-space: normal;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">Mikhail E. Belkin, Leonid Zhukov and Alexander S. Sigov, Russian Technological University MIREA, Moscow, Russia</span></p><p id="h.my9kpj1ebwt6" dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 2pt; margin-top: 11pt; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; vertical-align: baseline;"><strong>ABSTRACT</strong></span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0; text-align: justify; white-space: normal;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">A new cost-efficient concept to realize a real-time monitoring of quality-of-service metrics and other service data in 5G and beyond access network using a separate return channel based on a vertical cavity surface emitting laser in the optical injection locked mode that simultaneously operates as an optical transmitter and as a resonant cavity enhanced photodetector, is proposed and discussed. The feasibility and efficiency of the proposed approach are confirmed by a proof-of-concept experiment when optically transceiving high-speed digital signal with multi-position quadrature amplitude modulation of a radio-frequency carrier.</span></p><p id="h.bxr03qjibj6n" dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 2pt; margin-top: 11pt; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; vertical-align: baseline;"><strong>KEYWORDS</strong></span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0; text-align: justify; white-space: normal;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">5G and beyond, access network, RoF-based mobile fronthaul/backhaul, real-time monitoring, QoS metrics, OIL-VCSEL.</span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><br></p><p id="h.pv0p9bgfqij5" dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 2pt; margin-top: 11pt; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 14pt; font-variant: normal; vertical-align: baseline;"><strong>An Automated Quantitative Information Flow Analysis for Concurrent Programs</strong></span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0; text-align: justify; white-space: normal;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">Khayyam Salehi</span><sup style="color: #000000; font-family: 'Times New Roman'; font-size: 7.199999999999999pt; font-variant: normal; font-weight: normal;">1</sup><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">, Ali A. Noroozi</span><sup style="color: #000000; font-family: 'Times New Roman'; font-size: 7.199999999999999pt; font-variant: normal; font-weight: normal;">2</sup><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">, Sepehr Amir-Mohammadian</span><sup style="color: #000000; font-family: 'Times New Roman'; font-size: 7.199999999999999pt; font-variant: normal; font-weight: normal;">3</sup><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;"> and Jaber Karimpour</span><sup style="color: #000000; font-family: 'Times New Roman'; font-size: 7.199999999999999pt; font-variant: normal; font-weight: normal;">2</sup><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">, </span><sup style="color: #000000; font-family: 'Times New Roman'; font-size: 7.199999999999999pt; font-variant: normal; font-weight: normal;">1</sup><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">Shahrekord University, Shahrekord, Iran, </span><sup style="color: #000000; font-family: 'Times New Roman'; font-size: 7.199999999999999pt; font-variant: normal; font-weight: normal;">2</sup><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">University of Tabriz, Tabriz, Iran, </span><sup style="color: #000000; font-family: 'Times New Roman'; font-size: 7.199999999999999pt; font-variant: normal; font-weight: normal;">3</sup><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">University of the Pacific, Stockton, CA, USA</span></p><p id="h.2vc9rb31vbs4" dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 2pt; margin-top: 11pt; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; vertical-align: baseline;"><strong>ABSTRACT</strong></span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0; text-align: justify; white-space: normal;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">Quantitative information flow is a rigorous approach for evaluating the security of a system, including network protocols. It is used to quantify the amount of secret in formation leaked to the public outputs. In this paper, we propose an automated approach for quantitative information flow analysis of concurrent programs, which are widely used to implement network and communication systems. Markovian processes are used to model the behavior of these programs. To this end, we assume that the attacker is capable of observing the internal behavior of the program and propose an equivalence relation, back-bisimulation, to capture the attacker’s view of the program behavior. A partition refinement algorithm is developed to construct the back-bisimulation quotient of the program model and then a quantification method is proposed for computing the information leakage using the quotient. We have implemented our proposed approach as a leakage quantification tool, called PRISM Leak. It is built on the probabilistic model checker PRISM. Finally, an anonymous protocols, dining cryptographers, is analyzed as a case study to show applicability and scalability of the proposed approach.</span></p><p id="h.pnhjwm3zl6sl" dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 2pt; margin-top: 11pt; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; vertical-align: baseline;"><strong>KEYWORDS</strong></span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0; text-align: justify; white-space: normal;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">Information leakage, Network protocol security, Quantitative information flow, Confidentiality, PRISM-Leak.</span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><br></p><p id="h.unajevebpw7" dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 2pt; margin-top: 11pt; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 14pt; font-variant: normal; vertical-align: baseline;"><strong>A Functional Review of the Most Common Opportunistic Routing Protocols</strong></span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0; text-align: justify; white-space: normal;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">Swati Sharma, Amita Dev, and Arun Sharma, Indira Gandhi Delhi Technical University for Women, Delhi, India</span></p><p id="h.s6qyeilvd8ar" dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 2pt; margin-top: 11pt; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; vertical-align: baseline;"><strong>ABSTRACT</strong></span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0; text-align: justify; white-space: normal;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">Opportunistic Networks are basically on-demand wireless networks that do not undertake routing overheads until there is a packet to send from a source to a destination node. The intermediary nodes on the network operate as forwarding nodes thereby assisting in the process. The selection of these forwarding nodes, coordination between these forwarding nodes and the utilization of critical resources in these processes determine the basic operation of an opportunistic routing protocol. The performance of these protocols is assessed based on the utilization of key network parameters or Metrics. This paper provides a functional review of the operation of the most common opportunistic routing protocols. It compares these protocols in terms of their operation and critical-resource utilization. This literature also summarizes the metrics used and challenges encountered in opportunistic routing protocols. Most of the protocols discussed here are used as benchmarks for routing in opportunistic networks.</span></p><p id="h.n5odanyeig2c" dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 2pt; margin-top: 11pt; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; vertical-align: baseline;"><strong>KEYWORDS</strong></span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0; text-align: justify; white-space: normal;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">Opportunistic Networks, Opportunistic Routing Protocols, Forwarding Set, Routing Metrics.</span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><br></p><p id="h.lvbj3nfez0gs" dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 2pt; margin-top: 11pt; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 14pt; font-variant: normal; vertical-align: baseline;"><strong>Sentiment Analysis of Cybersecurity Topics in Twitter and Reddit</strong></span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0; text-align: justify; white-space: normal;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">Bipun Thapa, College of Business, Innovation, Leadership, and Technology, Marymount University, USA</span></p><p id="h.yxupbqqs75u6" dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 2pt; margin-top: 11pt; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; vertical-align: baseline;"><strong>ABSTRACT</strong></span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0; text-align: justify; white-space: normal;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">Sentiment Analysis provides an opportunity to understand the subject(s), especially in the digital age, due to an abundance of public data points and effective algorithms. Cybersecurity is a subject where opinions are plentiful and differing in the public domain. This descriptive research aims to analyze cybersecurity topics in Twitter and Reddit, and provide a breakdown of its sentiment. In order to conduct this research, data is collected from Twitter, Reddit and an online survey and analyzed through an NLP (Natural Language Processing) algorithm. The results produce mostly positive and neutral sentiments based on the data collected. In addition, the NLP algorithm is evaluated for its accuracy based on human classification. The goal of the research is to capture a snapshot of public sentiment on social media platforms at a given timeframe and potentially advance explanatory research opportunities to find influential variables for appropriate polarity.</span></p><p id="h.2vicuptsxd0f" dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 2pt; margin-top: 11pt; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; vertical-align: baseline;"><strong>KEYWORDS</strong></span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0; text-align: justify; white-space: normal;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">NTLK, NLP, VADER, Sentiment Analysis, API, Python, Polarity, Evaluation Metrics.</span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><br></p><p id="h.y3i5c8tqo354" dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 2pt; margin-top: 11pt; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 14pt; font-variant: normal; vertical-align: baseline;"><strong>An New Approach for Speech Keyword Detection on Noisy Environment</strong></span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0; text-align: justify; white-space: normal;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">Peiwen Ye and Hancong Duan, School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan, China</span></p><p id="h.lwxg5d8p5vmz" dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 2pt; margin-top: 11pt; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; vertical-align: baseline;"><strong>ABSTRACT</strong></span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0; text-align: justify; white-space: normal;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">Keyword Spotting, a.k.a., keyword recognition, has been widely used in products such as mobile devices and smart homes. By detecting wake-up keywords in the continuous voice stream, the corresponding program can be started intelligently. Neural networks have dominated keyword spotting recently. Meanwhile, attention mechanism has been widely used in natural language processing and has achieved great performance improvement. However, few researchers concerned about the noise issue in noisy speech keyword recognition. Thus, we propose a new neural network architecture combined with attention mechanism, which employs the backbone network of LSTM and CNN to emphasize significant information in the keyword. We use separable convolution instead of ordinary convolution to reduce the number of parameters of the model. We train our model on Google Speech Commands dataset to compare recognition accuracy. Besides, to improve the performance of the model in noisy environment, we apply data enhancement methods such as time masking and frequency masking to this task, and add noise of various scenes with different signal-to-noise ratios to the training data. The experimental results show that our model finally achieves the accuracy of 94.93% at most, which exceeds existing models on noisy environment.</span></p><p id="h.xoahguw9bgaj" dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 2pt; margin-top: 11pt; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; vertical-align: baseline;"><strong>KEYWORDS</strong></span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0; text-align: justify; white-space: normal;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">Keyword Spotting, Noise robustness, Command Recognition, Attention Mechanism, Data augmentation.</span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><br></p><p id="h.efo34d6idf9q" dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 2pt; margin-top: 11pt; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 14pt; font-variant: normal; vertical-align: baseline;"><strong>An Educational Electronic Health Record with a Configurable User Interface</strong></span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0; text-align: justify; white-space: normal;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">Yichun Zhao,Florianë Shala,Evangeline Wagner, University of Victoria</span></p><p id="h.2r1be2gxa1k5" dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 2pt; margin-top: 11pt; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; vertical-align: baseline;"><strong>ABSTRACT</strong></span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0; text-align: justify; white-space: normal;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">Background: Proper educational training and support are proven to be major components of EHR implementation and use. However, the majority of health providers are not sufficiently trained in EHR use, leading to adverse events, errors, and decreased quality of care. In response to this, students studying Health Information Science, Public Health, Nursing, and Medicine should all gain a thorough understanding of EHR use at different levels for different purposes. The design of a usable and safe EHR system that accommodates the needs and workflows of different users, user groups, and disciplines is required for EHR learning to be efficient and effective. Objectives: This project builds several artifacts which seek to address both the educational and usability aspects of an educational EHR. The artifacts proposed are models for and examples of such an EHR with a configurable UI to be learnt by students who need a background in EHR use during their degrees.Methods: Review literature and gather professional opinions from domain experts on usability, the use of workflow patterns, UI configurability and design, and the educational aspect of EHR use. Conduct interviews in a semi-casual virtual setting with open discussion in order to gain a deeper understanding of the principal aspects of EHR use in educational settings. Select a specific task and user group to illustrate how the proposed solution will function based on the current research. Develop three artifacts based on the available research, professional opinions, and prior knowledge of the topic. The artifacts capture the user task and user’s interactions with the EHR for learning. The first generic model provides a general understanding of the EHR system process. The second model is a specific example of performing the task of MRI ordering with a configurable UI. The third artifact includes UI mock-ups showcasing the models in a practical and visual way.Significance: Due to the lack of educational EHRs, medical professionals do not receive sufficient EHR training. Implementing an educational EHR with a usable and configurable interface to suit the needs of different user groups and disciplines will help facilitate EHR learning and training, and ultimately improve the quality of patient care.</span></p><p id="h.rh7tozxztpbj" dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 2pt; margin-top: 11pt; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; vertical-align: baseline;"><strong>KEYWORDS</strong></span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0; text-align: justify; white-space: normal;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">Education, Usability, EHR.</span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><br></p><p id="h.d4cmvmiqkg0a" dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 2pt; margin-top: 11pt; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 14pt; font-variant: normal; vertical-align: baseline;"><strong>Understanding of Comorbidities Using Modeling Techniques on EHR</strong></span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0; text-align: justify; white-space: normal;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">Comorbidities refer to the existence of numerous, co-occurring diseases in medicine. The course of one comorbidity is typically extremely dependent on the course of the other condition due to their co-occurrence, and therapies can have major spill-over effects. Despite the high occurrence of comorbidities among patients, there is no complete statistical framework for modelling comorbidity longitudinal dynamics. We propose a probabilistic approach for studying comorbidity dynamics in patients over time in this paper. Coupled- HMM is a linked hidden Markov model with a personalized, non-homogeneous transition mechanism that we developed. Clinical research influenced the design of our coupled-HMM: (1) It accounts for different disease stages (acute, stable) in disease progression by providing clinically meaningful latent phases. (2) It simulates a relationship between the trajectories of comorbidities and the dynamics of capturing co-evolution. (3) The transition mechanism takes into account between-patient heterogeneity (e.g., risk factors, treatments). Based on 675 health trajectories, we assessed our proposed Coupled-HMM, which investigates the concomitant evolution of diabetes mellitus and chronic liver disease. We find that our Coupled-HMM provides a superior fit when compared to competing models without coupling. We also assess the spill-over impact, or the amount to which diabetic therapies are linked to a shift in chronic liver disease from an acute to a stable condition. As a result, our approach has immediate application in both treatment planning and clinical research in the context of comorbidities.CCS Concepts Applied computing ? Health informatics; Mathematics of computing ? Bayesian computation; Markov processes.</span></p><p id="h.39ufldn8dwcw" dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 2pt; margin-top: 11pt; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; vertical-align: baseline;"><strong>KEYWORDS</strong></span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0; text-align: justify; white-space: normal;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">Longitudinal data analysis, Disease dynamics, Comorbidity, Hidden Markov model, Bayesian analysis.</span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><br></p><p id="h.ys6hv9ifu7ld" dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 2pt; margin-top: 11pt; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 14pt; font-variant: normal; vertical-align: baseline;"><strong>Bigdata Platform to Accelerate Insights Generation from Healthcare Data</strong></span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0; text-align: justify; white-space: normal;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">Arun Sundararaman, Healthcare Data and Analytics Practice Head, Accenture Technology, Chennai, India</span></p><p id="h.xzf9rpp47kz2" dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 2pt; margin-top: 11pt; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; vertical-align: baseline;"><strong>ABSTRACT</strong></span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0; text-align: justify; white-space: normal;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">Healthcare Industry is abundant with data, yet poor in insights. Gaps are primary due to highly unstructured data prevalent in medical notes, clinical records, lab results etc. This challenge is compounded with lack of integration of data sources; data that is required for effective medical outcomes is spread across 4 large islands viz., EMRs, Health Administrators, Personal Health Records (including wearables, lifestyle data, implanted medical devices) and Public Health data. Integrating such disparate sources, structures and making meaningful use of healthcare data continues to be time consuming and costly. The Industry cannot afford longer timelines and excessive costs in the form of multiple proprietary environments to integrate such datasets. Emergence of data platforms on the cloud are expected to address these challenges. This paper discusses the need for a Healthcare Data Platform to accelerate insights generation and presents a patented cloud health data platform solution that accelerates insights generation. This paper discusses in detail the Architecture and Design principles, technical details and benefits and value from implementation experiences, besides outlining future directions.</span></p><p id="h.bit3u5gy5inl" dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 2pt; margin-top: 11pt; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; vertical-align: baseline;"><strong>KEYWORDS</strong></span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0; text-align: justify; white-space: normal;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">Data Supply chain, accelerated insights, Healthcare Data Platform, modular design, Big Data.</span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><br></p><p id="h.tvqyipowch80" dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 2pt; margin-top: 11pt; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 14pt; font-variant: normal; vertical-align: baseline;"><strong>Discovery of Association Rules of the Relationship between Food Consumption and Life Style Diseases from Swiss Nutrition’s (Menuch) Dataset & Multiple Swiss Health Datasets from 1992 to 2012</strong></span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0; text-align: justify; white-space: normal;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">Timo Lustenberger</span><sup style="color: #000000; font-family: 'Times New Roman'; font-size: 7.199999999999999pt; font-variant: normal; font-weight: normal;">1</sup><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">, Helena Jenzer</span><sup style="color: #000000; font-family: 'Times New Roman'; font-size: 7.199999999999999pt; font-variant: normal; font-weight: normal;">2</sup><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;"> and Farshideh Einsele</span><sup style="color: #000000; font-family: 'Times New Roman'; font-size: 7.199999999999999pt; font-variant: normal; font-weight: normal;">1</sup><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">, </span><sup style="color: #000000; font-family: 'Times New Roman'; font-size: 7.199999999999999pt; font-variant: normal; font-weight: normal;">1</sup><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">Section of Business Information, Bern University of Applied Sciences, Switzerland, </span><sup style="color: #000000; font-family: 'Times New Roman'; font-size: 7.199999999999999pt; font-variant: normal; font-weight: normal;">2</sup><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">Hospital of Psychiatry, University of Zurich, Switzerland</span></p><p id="h.k7h5qif5hnr3" dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 2pt; margin-top: 11pt; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; vertical-align: baseline;"><strong>ABSTRACT</strong></span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0; text-align: justify; white-space: normal;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">This article demonstrates that using data mining methods such as Weighted Association Rule Mining (WARM) on an integrated Swiss database derived from a Swiss national dietary survey (menuCH) and 25 years of Swiss demographical and health data is a powerful way to determine whether a specific population subgroup is at particular risk for developing a lifestyle disease based on its food consumption patterns. The objective of the study was to discover critical food consumption patterns linked with lifestyle diseases known to be strongly tied with food consumption. Food consumption databases from a Swiss national survey menuCH were gathered along with data of large surveys of demographics and health data collected over 25 years from Swiss population conducted by Swiss Federal Office of Public Health (FOPH). These databases were integrated and reported in a previous study as a single integrated database. A data mining method such as WARM was applied to this integrated database. A set of promising rules and their corresponding interpretation was generated. As an example, the found rules of the sample show that the consumption of alcohol in small quantities does not have a negative impact on health, whereas the consumption of vegetables is important for the supply of vitamins of the B group, which help the energy metabolism to pro-vide energy. These vitamins are particularly lacking in alcoholics and should then be taken with supplements. Another finding is that dietary supplements do little specially by diabetes. Applying WARM algorithm was beneficial for this study since no interesting rules were pruned out early and the significance of the rules could be highly increased as compared to a previous study using pure Apriori Algorithm.</span></p><p id="h.yxy6k868frm3" dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 2pt; margin-top: 11pt; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; vertical-align: baseline;"><strong>KEYWORDS</strong></span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0; text-align: justify; white-space: normal;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">Data Mining, WARM Association Analysis, Diet & Chronical Diseases, Health Informatics.</span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><br></p><p id="h.l9581dp730vn" dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 2pt; margin-top: 11pt; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 14pt; font-variant: normal; vertical-align: baseline;"><strong>Encryption Based Watermarking Technique for Security of Medical Image</strong></span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0; text-align: justify; white-space: normal;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">Abderrahmane Daham</span><sup style="color: #000000; font-family: 'Times New Roman'; font-size: 7.199999999999999pt; font-variant: normal; font-weight: normal;">1</sup><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;"> and Mohamed ouslim</span><sup style="color: #000000; font-family: 'Times New Roman'; font-size: 7.199999999999999pt; font-variant: normal; font-weight: normal;">2</sup><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">, </span><sup style="color: #000000; font-family: 'Times New Roman'; font-size: 7.199999999999999pt; font-variant: normal; font-weight: normal;">1</sup><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">Department of Computer Engineering, Bechar University (UTMB), </span><sup style="color: #000000; font-family: 'Times New Roman'; font-size: 7.199999999999999pt; font-variant: normal; font-weight: normal;">2</sup><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">University of Science and Technology of Oran (USTO)</span></p><p id="h.b91z75pvy0s4" dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 2pt; margin-top: 11pt; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; vertical-align: baseline;"><strong>ABSTRACT</strong></span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0; text-align: justify; white-space: normal;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">This paper proposes an encryption-based image watermarking scheme for medical images using an adaptive quantization of wavelet coefficient and a crypto-system based on the chaotic encryption of Singular Value Decomposition (SVD). In order to increase the robustness of the algorithm and provide extra security, an improved SVD-CHAOS embedding and extraction procedure has been used to scramble the watermark logo in the preprocessing step of the proposed method. In the process of watermark embedding, an R-level discrete wavelet transform was applied to the host image. The high frequency wavelet coefficients are selected to carry these scrambled-watermarks by using adaptive quantization low bit modulation (LBM). The proposed image watermarking method endures all attacks and aptly extracts the concealed watermark without significant degradation in the image quality, Thus when the Peak Signal to Noise Ratio (PSNR) and Normalized Correlation (NC) performance of the proposed algorithm is correlated with other related techniques.</span></p><p id="h.nt42yn3yp83e" dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 2pt; margin-top: 11pt; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; vertical-align: baseline;"><strong>KEYWORDS</strong></span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0; text-align: justify; white-space: normal;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">Watermarking, medical image, discrete wavelet transform, singular value decomposition, quantization, chaos cryptosystem.</span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><br></p><p id="h.a72gxt5v22iv" dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 2pt; margin-top: 11pt; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 14pt; font-variant: normal; vertical-align: baseline;"><strong>Improving Forecasting Demand for Maintenance Spare Parts: Case Study of Power Utility</strong></span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0; text-align: justify; white-space: normal;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">Abdulaziz A. Afandi, Department of Engineering College, Islamic University of Medina, Medina, Saudi Arabia</span></p><p id="h.uwxbsyxc1su6" dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 2pt; margin-top: 11pt; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; vertical-align: baseline;"><strong>ABSTRACT</strong></span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0; text-align: justify; white-space: normal;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">The need to reduce inventory holding costs and increasing system operational availability are the main motivation behind improving spare parts inventory management in a major power utility company in Medina. This paper reports in an effort made to optimize the orders quantities of spare parts by improving the method of forecasting the demand. The study focuses on equipment that has frequent spare part’s purchase orders with uncertain demand. The pattern of the demand considers lumpy pattern which makes conventional forecasting methods less effective. A comparison was made by benchmarking various methods of forecasting based on experts’ criteria to select the most suitable method for the case-study. Three actual data sets were used to make the forecast in this case study. Two neural network (NN) approaches were utilized and compared, namely long short-term memory (LSTM) and multilayer perceptron (MLP). The results as expected, showed that the NN models gave better results than traditional forecasting method (judgmental method). In addition, the LSTM model had a higher predictive accuracy than the MLP model.</span></p><p id="h.y5ahyfv236xu" dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 2pt; margin-top: 11pt; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; vertical-align: baseline;"><strong>KEYWORDS</strong></span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0; text-align: justify; white-space: normal;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">ANN, long short-term memory, multilayer perceptron, forecasting demand, inventory management, spare parts.</span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><br></p><p id="h.34k800xejais" dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 2pt; margin-top: 11pt; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 14pt; font-variant: normal; vertical-align: baseline;"><strong>AI and Machine Learning Applications in Medicine</strong></span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0; text-align: justify; white-space: normal;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">Prof. Dr. Mitat Uysal</span><sup style="color: #000000; font-family: 'Times New Roman'; font-size: 7.199999999999999pt; font-variant: normal; font-weight: normal;">1</sup><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">, M. Ozan Uysal</span><sup style="color: #000000; font-family: 'Times New Roman'; font-size: 7.199999999999999pt; font-variant: normal; font-weight: normal;">2</sup><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;"> and R.A. Nurdanur Pehlivan</span><sup style="color: #000000; font-family: 'Times New Roman'; font-size: 7.199999999999999pt; font-variant: normal; font-weight: normal;">3</sup><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">, </span><sup style="color: #000000; font-family: 'Times New Roman'; font-size: 7.199999999999999pt; font-variant: normal; font-weight: normal;">1</sup><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">Faculty of Software Engineering, Dogus University, Istanbul, Turkey, </span><sup style="color: #000000; font-family: 'Times New Roman'; font-size: 7.199999999999999pt; font-variant: normal; font-weight: normal;">2</sup><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">Appcent Ltd, Istanbul, Turkey, </span><sup style="color: #000000; font-family: 'Times New Roman'; font-size: 7.199999999999999pt; font-variant: normal; font-weight: normal;">3</sup><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">Faculty of Software Engineering, Istanbul, Turkey</span></p><p id="h.np1kabwd1otu" dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 2pt; margin-top: 11pt; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; vertical-align: baseline;"><strong>ABSTRACT</strong></span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0; text-align: justify; white-space: normal;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">In this study the importance and chance of using of Artificial Intelligence and Machine Learning methods are discussed and several application samples are given from this area.Machine Learning methods provide more accuracy in Diagnosis of Medical images than the outputs of human experts.A new found metaheuristic optimization algorithm called as MBO (migrating birds algorithm) is used with SVM for classification of cancer tumors. The new developed model gives very satisfactory results in this area.</span></p><p id="h.xr39qn3c4lds" dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 2pt; margin-top: 11pt; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; vertical-align: baseline;"><strong>KEYWORDS</strong></span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0; text-align: justify; white-space: normal;"><span style="color: #000000; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; font-weight: normal; vertical-align: baseline;">AI, machine learning, MBO, SVM.</span></p><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.2; margin-bottom: 0; margin-top: 0; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0;"><br></p><p dir="ltr" class="CDt4Ke zfr3Q"><br></p></div></div></div></div></div></div></div></div></div></section></div><div class="Xpil1b xgQ6eb"></div><footer jsname="yePe5c"><section id="h.1c268780ba2a67e_120" class="yaqOZd cJgDec nyKByd" style=""><div class="IFuOkc" style="background-size: cover; background-position: center center; background-image: url(https://lh5.googleusercontent.com/uQUl0uOnr17XAtrRgSvLSNyBSXQ0kRg0y-yF82-wR6gucAX_SqjHM-2L__L29w2yRFRvBuwuGhn1JTxgdc-QxWs=w16383);"></div><div class="mYVXT"><div class="LS81yb VICjCf j5pSsc db35Fc" tabindex="-1"><div class="hJDwNd-AhqUyc-c5RTEf Ft7HRd-AhqUyc-c5RTEf purZT-AhqUyc-II5mzb ZcASvf-AhqUyc-II5mzb pSzOP-AhqUyc-qWD73c Ktthjf-AhqUyc-qWD73c JNdkSc SQVYQc"><div class="JNdkSc-SmKAyb LkDMRd"><div class="" jscontroller="sGwD4d" jsaction="zXBUYb:zTPCnb;zQF9Uc:Qxe3nd;" jsname="F57UId"><div class="oKdM2c ZZyype Kzv0Me"><div id="h.1c268780ba2a67e_117" class="hJDwNd-AhqUyc-c5RTEf Ft7HRd-AhqUyc-c5RTEf purZT-AhqUyc-II5mzb ZcASvf-AhqUyc-II5mzb pSzOP-AhqUyc-qWD73c Ktthjf-AhqUyc-qWD73c jXK9ad D2fZ2 zu5uec OjCsFc dmUFtb wHaque g5GTcb JYTMs"><div class="jXK9ad-SmKAyb"><div class="tyJCtd mGzaTb Depvyb baZpAe"><div id="h.g1qo7rrakoo" class="CobnVe aP9Z7e"></div><h2 id="h.g1qo7rrakoo_l" dir="ltr" class="CDt4Ke zfr3Q JYVBee" style="line-height: 1.44; text-align: center;" tabindex="-1"><div jscontroller="Ae65rd" jsaction="touchstart:UrsOsc; click:KjsqPd; focusout:QZoaZ; mouseover:y0pDld; mouseout:dq0hvd;fv1Rjc:jbFSOd;CrfLRd:SzACGe;" class="CjVfdc"><div class="PPhIP rviiZ" jsname="haAclf"><div role="presentation" class="U26fgb mUbCce fKz7Od LRAOtb Znu9nd M9Bg4d" jscontroller="mxS5xe" jsaction="click:cOuCgd; mousedown:UX7yZ; mouseup:lbsD7e; mouseenter:tfO1Yc; mouseleave:JywGue; focus:AHmuwe; blur:O22p3e; contextmenu:mg9Pef;" jsshadow aria-describedby="h.g1qo7rrakoo_l" aria-label="Copy heading link" aria-disabled="false" data-tooltip="Copy heading link" aria-hidden="true" data-tooltip-position="top" data-tooltip-vertical-offset="12" data-tooltip-horizontal-offset="0"><a class="FKF6mc TpQm9d" href="#h.g1qo7rrakoo" aria-label="Copy heading link" jsname="hiK3ld" role="button" aria-describedby="h.g1qo7rrakoo_l"><div class="VTBa7b MbhUzd" jsname="ksKsZd"></div><span jsslot class="xjKiLb"><span class="Ce1Y1c" style="top: -11px"><svg class="OUGEr QdAdhf" width="22px" height="22px" viewBox="0 0 24 24" fill="currentColor" focusable="false"><path d="M0 0h24v24H0z" fill="none"/><path d="M3.9 12c0-1.71 1.39-3.1 3.1-3.1h4V7H7c-2.76 0-5 2.24-5 5s2.24 5 5 5h4v-1.9H7c-1.71 0-3.1-1.39-3.1-3.1zM8 13h8v-2H8v2zm9-6h-4v1.9h4c1.71 0 3.1 1.39 3.1 3.1s-1.39 3.1-3.1 3.1h-4V17h4c2.76 0 5-2.24 5-5s-2.24-5-5-5z"/></svg></span></span></a></div></div><span style="color: #ffffff; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; vertical-align: baseline;"><strong>Contact</strong></span></div></h2><p dir="ltr" class="CDt4Ke zfr3Q" style="background-color: transparent; border-bottom: none; border-left: none; border-right: none; border-top: none; line-height: 1.44; margin-bottom: 11pt; margin-left: 0; margin-top: 11pt; padding-bottom: 0; padding-left: 0; padding-right: 0; padding-top: 0; text-align: center; text-indent: 0;"><span style="color: #ffffff; font-family: 'Times New Roman'; font-size: 12pt; font-variant: normal; vertical-align: baseline;"><a class="XqQF9c rXJpyf" href="mailto:soea.conf@yahoo.com" target="_blank"><strong>soea.conf@yahoo.com</strong></a></span></p></div></div></div></div></div></div></div><div class="hJDwNd-AhqUyc-Clt0zb Ft7HRd-AhqUyc-Clt0zb JNdkSc SQVYQc L6cTce-purZT L6cTce-pSzOP"><div class="JNdkSc-SmKAyb LkDMRd"><div class="" jscontroller="sGwD4d" jsaction="zXBUYb:zTPCnb;zQF9Uc:Qxe3nd;" jsname="F57UId"></div></div></div></div></div></section><section id="h.45146a2d848aee7_35" class="yaqOZd" style=""><div class="IFuOkc"></div><div class="mYVXT"><div class="LS81yb VICjCf j5pSsc db35Fc" tabindex="-1"><div class="hJDwNd-AhqUyc-uQSCkd Ft7HRd-AhqUyc-uQSCkd purZT-AhqUyc-II5mzb ZcASvf-AhqUyc-II5mzb pSzOP-AhqUyc-qWD73c Ktthjf-AhqUyc-qWD73c JNdkSc SQVYQc"><div class="JNdkSc-SmKAyb LkDMRd"><div class="" jscontroller="sGwD4d" jsaction="zXBUYb:zTPCnb;zQF9Uc:Qxe3nd;" jsname="F57UId"><div class="oKdM2c ZZyype Kzv0Me"><div id="h.45146a2d848aee7_32" class="hJDwNd-AhqUyc-uQSCkd Ft7HRd-AhqUyc-uQSCkd jXK9ad D2fZ2 zu5uec OjCsFc dmUFtb wHaque g5GTcb JYTMs"><div class="jXK9ad-SmKAyb"><div class="tyJCtd mGzaTb Depvyb baZpAe"><div id="h.gyucupqrixz5" class="GV3q8e aP9Z7e"></div><h3 id="h.gyucupqrixz5_l" dir="ltr" class="CDt4Ke zfr3Q OmQG5e" style="text-align: center;" tabindex="-1"><div jscontroller="Ae65rd" jsaction="touchstart:UrsOsc; click:KjsqPd; focusout:QZoaZ; mouseover:y0pDld; mouseout:dq0hvd;fv1Rjc:jbFSOd;CrfLRd:SzACGe;" class="CjVfdc"><div class="PPhIP rviiZ" jsname="haAclf"><div role="presentation" class="U26fgb mUbCce fKz7Od LRAOtb Znu9nd M9Bg4d" jscontroller="mxS5xe" jsaction="click:cOuCgd; mousedown:UX7yZ; mouseup:lbsD7e; mouseenter:tfO1Yc; mouseleave:JywGue; focus:AHmuwe; blur:O22p3e; contextmenu:mg9Pef;" jsshadow aria-describedby="h.gyucupqrixz5_l" aria-label="Copy heading link" aria-disabled="false" data-tooltip="Copy heading link" aria-hidden="true" data-tooltip-position="top" data-tooltip-vertical-offset="12" data-tooltip-horizontal-offset="0"><a class="FKF6mc TpQm9d" href="#h.gyucupqrixz5" aria-label="Copy heading link" jsname="hiK3ld" role="button" aria-describedby="h.gyucupqrixz5_l"><div class="VTBa7b MbhUzd" jsname="ksKsZd"></div><span jsslot class="xjKiLb"><span class="Ce1Y1c" style="top: -11px"><svg class="OUGEr QdAdhf" width="22px" height="22px" viewBox="0 0 24 24" fill="currentColor" focusable="false"><path d="M0 0h24v24H0z" fill="none"/><path d="M3.9 12c0-1.71 1.39-3.1 3.1-3.1h4V7H7c-2.76 0-5 2.24-5 5s2.24 5 5 5h4v-1.9H7c-1.71 0-3.1-1.39-3.1-3.1zM8 13h8v-2H8v2zm9-6h-4v1.9h4c1.71 0 3.1 1.39 3.1 3.1s-1.39 3.1-3.1 3.1h-4V17h4c2.76 0 5-2.24 5-5s-2.24-5-5-5z"/></svg></span></span></a></div></div><span style="color: #000000; font-family: 'Times New Roman'; font-size: 10.5pt; font-variant: normal; vertical-align: baseline;"><strong>All Rights Reserved ® </strong></span><span style="color: #000000; font-family: 'Times New Roman'; font-size: 10.5pt; vertical-align: baseline;"><strong>SOEA </strong></span><span style="color: #000000; font-family: 'Times New Roman'; font-size: 10.5pt; font-variant: normal; vertical-align: baseline;"><strong>202</strong></span><span style="color: #000000; font-family: 'Roboto'; font-size: 10.5pt; font-variant: normal; vertical-align: baseline;"><strong>2</strong></span><span style="color: #000000; font-family: 'Arial'; font-size: 11pt; font-variant: normal; vertical-align: baseline;"><strong> </strong></span></div></h3></div></div></div></div></div></div></div></div></div></section></footer><div jscontroller="j1RDQb" jsaction="rcuQ6b:rcuQ6b;MxH79b:JdcaS;FaOgy:XuHpsb;" class="dZA9kd ynRLnc" data-last-updated-at-time="1647318396179" data-is-preview="false"><div role="button" class="U26fgb JRtysb WzwrXb I12f0b K2mXPb zXBiaf ynRLnc" jscontroller="iSvg6e" jsaction="click:cOuCgd; mousedown:UX7yZ; mouseup:lbsD7e; mouseenter:tfO1Yc; mouseleave:JywGue; focus:AHmuwe; blur:O22p3e; contextmenu:mg9Pef;touchstart:p6p2H; touchmove:FwuNnf; touchend:yfqBxc(preventDefault=true); touchcancel:JMtRjd;;keydown:I481le;" jsshadow jsname="Bg3gkf" aria-label="Site actions" aria-disabled="false" tabindex="0" aria-haspopup="true" aria-expanded="false" data-menu-corner="bottom-start" data-anchor-corner="top-start"><div class="NWlf3e MbhUzd" jsname="ksKsZd"></div><span jsslot class="MhXXcc oJeWuf"><span class="Lw7GHd snByac"><svg width="24" height="24" viewBox="0 0 24 24" focusable="false" class=" NMm5M"><path d="M11 17h2v-6h-2v6zm1-15C6.48 2 2 6.48 2 12s4.48 10 10 10 10-4.48 10-10S17.52 2 12 2zm0 18c-4.41 0-8-3.59-8-8s3.59-8 8-8 8 3.59 8 8-3.59 8-8 8zM11 9h2V7h-2v2z"/></svg></span></span><div jsname="xl07Ob" style="display:none" aria-hidden="true"><div class="JPdR6b hVNH5c" jscontroller="uY3Nvd" jsaction="IpSVtb:TvD9Pc;fEN2Ze:xzS4ub;frq95c:LNeFm;cFpp9e:J9oOtd; click:H8nU8b; mouseup:H8nU8b; keydown:I481le; keypress:Kr2w4b; blur:O22p3e; focus:H8nU8b" role="menu" tabindex="0" style="position:fixed"><div class="XvhY1d" jsaction="mousedown:p8EH2c; touchstart:p8EH2c;"><div class="JAPqpe K0NPx"><span jsslot class="z80M1 FeRvI" jsaction="click:o6ZaF(preventDefault=true); mousedown:lAhnzb; mouseup:Osgxgf; mouseenter:SKyDAe; mouseleave:xq3APb;touchstart:jJiBRc; touchmove:kZeBdd; touchend:VfAz8" jsname="j7LFlb" aria-label="Google Sites" role="menuitem" tabindex="-1"><div class="aBBjbd MbhUzd" jsname="ksKsZd"></div><div class="uyYuVb oJeWuf" jsaction="JIbuQc:Toy3n;" jsname="V2zOu"><div class="jO7h3c">Google Sites</div></div></span><span jsslot class="z80M1 FeRvI" jsaction="click:o6ZaF(preventDefault=true); mousedown:lAhnzb; mouseup:Osgxgf; mouseenter:SKyDAe; mouseleave:xq3APb;touchstart:jJiBRc; touchmove:kZeBdd; touchend:VfAz8" jsname="j7LFlb" data-disabled-tooltip="Report abuse is not available in preview mode" aria-label="Report abuse" role="menuitem" tabindex="-1"><div class="aBBjbd MbhUzd" jsname="ksKsZd"></div><div class="uyYuVb oJeWuf" jscontroller="HYv29e" jsaction="JIbuQc:dQ6O0c;" jsname="lV5oke" data-abuse-proto="%.@.null,null,"https://sites.google.com/view/soea2022/accepted-papers"]" data-abuse-reporting-widget-proto="%.@.null,"https://sites.google.com/view/soea2022/accepted-papers"]"><div class="jO7h3c">Report abuse</div></div></span><span jsslot class="z80M1 FeRvI" jsaction="click:o6ZaF(preventDefault=true); mousedown:lAhnzb; mouseup:Osgxgf; mouseenter:SKyDAe; mouseleave:xq3APb;touchstart:jJiBRc; touchmove:kZeBdd; touchend:VfAz8" jsname="j7LFlb" aria-label="Page details" role="menuitem" tabindex="-1"><div class="aBBjbd MbhUzd" jsname="ksKsZd"></div><div class="uyYuVb oJeWuf" jsaction="JIbuQc:hriXLd;" jsname="Rg8K2c"><div class="jO7h3c">Page details</div></div></span></div></div></div></div></div></div><div jscontroller="j1RDQb" jsaction="focusin:gBxDVb(srlkmf); focusout:zvXhGb(srlkmf); click:ro2KTd(psdQ5e);JIbuQc:DSypkd(Bg3gkf);MxH79b:JdcaS;rcuQ6b:rcuQ6b;" class="LqzjUe ynRLnc" data-last-updated-at-time="1647318396179" data-is-preview="false"><div jsname="psdQ5e" class="Q0cSn"></div><div jsname="bN97Pc" class="hBW7Hb"><div role="button" class="U26fgb mUbCce fKz7Od kpPxtd QMuaBc M9Bg4d" jscontroller="VXdfxd" jsaction="click:cOuCgd; mousedown:UX7yZ; mouseup:lbsD7e; mouseenter:tfO1Yc; mouseleave:JywGue; focus:AHmuwe; blur:O22p3e; contextmenu:mg9Pef;touchstart:p6p2H; touchmove:FwuNnf; touchend:yfqBxc(preventDefault=true); touchcancel:JMtRjd;" jsshadow jsname="Bg3gkf" aria-label="Site actions" aria-disabled="false" tabindex="-1" aria-hidden="true"><div class="VTBa7b MbhUzd" jsname="ksKsZd"></div><span jsslot class="xjKiLb"><span class="Ce1Y1c" style="top: -12px"><svg width="24" height="24" viewBox="0 0 24 24" focusable="false" class=" NMm5M"><path d="M11 17h2v-6h-2v6zm1-15C6.48 2 2 6.48 2 12s4.48 10 10 10 10-4.48 10-10S17.52 2 12 2zm0 18c-4.41 0-8-3.59-8-8s3.59-8 8-8 8 3.59 8 8-3.59 8-8 8zM11 9h2V7h-2v2z"/></svg></span></span></div><div jsname="srlkmf" class="hUphyc"><div class="YkaBSd"><div class="iBkmkf"><span>Page updated</span> <span jsname="CFIm1b" class="dji00c" jsaction="AHmuwe:eGiyHb; mouseover:eGiyHb;" tabindex="0" role="contentinfo"></span></div></div><div class="YkaBSd" jsaction="click:Toy3n;"><div role="button" class="U26fgb kpPxtd J7BuEb" jsshadow jsname="V2zOu" aria-disabled="false" tabindex="0">Google Sites</div></div><div class="YkaBSd" jscontroller="HYv29e" jsaction="click:dQ6O0c;" data-abuse-proto="%.@.null,null,"https://sites.google.com/view/soea2022/accepted-papers"]" data-abuse-reporting-widget-proto="%.@.null,"https://sites.google.com/view/soea2022/accepted-papers"]"><div role="button" class="U26fgb kpPxtd J7BuEb" jsshadow aria-label="Report abuse" aria-disabled="false" tabindex="0">Report abuse</div></div></div></div></div></div></div></div><script nonce="N2_63Ev6TPDUMb2QXboYWA">DOCS_timing['cov']=new Date().getTime();</script><script src="https://www.gstatic.com/_/atari/_/js/k=atari.vw.en_US.fw_mAcuwUyE.O/am=MBiA/d=1/rs=AGEqA5lwNXFYaHUUDGYHiMqlOO36DqQAOw/m=view" id="base-js" nonce="N2_63Ev6TPDUMb2QXboYWA"></script></div></div><div jscontroller="YV8yqd" jsaction="rcuQ6b:npT2md"></div></body></html>