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graph neuron</title> <meta name="description" content="Search results for: hierarchical graph neuron"> <meta name="keywords" content="hierarchical graph neuron"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div class="container"> <nav class="navbar navbar-expand-lg navbar-light"> <a class="navbar-brand" href="https://waset.org"> <img src="https://cdn.waset.org/static/images/wasetc.png" alt="Open Science Research Excellence" title="Open Science Research Excellence" /> </a> <button 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action="https://publications.waset.org/abstracts/search"> <div id="custom-search-input"> <div class="input-group"> <i class="fas fa-search"></i> <input type="text" class="search-query" name="q" placeholder="Author, Title, Abstract, Keywords" value="hierarchical graph neuron"> <input type="submit" class="btn_search" value="Search"> </div> </div> </form> </div> </div> <div class="row mt-3"> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Commenced</strong> in January 2007</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Frequency:</strong> Monthly</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Edition:</strong> International</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Paper Count:</strong> 1123</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: hierarchical graph neuron</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1003</span> Research on Knowledge Graph Inference Technology Based on Proximal Policy Optimization</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yihao%20Kuang">Yihao Kuang</a>, <a href="https://publications.waset.org/abstracts/search?q=Bowen%20Ding"> Bowen Ding</a> </p> <p class="card-text"><strong>Abstract:</strong></p> With the increasing scale and complexity of knowledge graph, modern knowledge graph contains more and more types of entity, relationship, and attribute information. Therefore, in recent years, it has been a trend for knowledge graph inference to use reinforcement learning to deal with large-scale, incomplete, and noisy knowledge graphs and improve the inference effect and interpretability. The Proximal Policy Optimization (PPO) algorithm utilizes a near-end strategy optimization approach. This allows for more extensive updates of policy parameters while constraining the update extent to maintain training stability. This characteristic enables PPOs to converge to improved strategies more rapidly, often demonstrating enhanced performance early in the training process. Furthermore, PPO has the advantage of offline learning, effectively utilizing historical experience data for training and enhancing sample utilization. This means that even with limited resources, PPOs can efficiently train for reinforcement learning tasks. Based on these characteristics, this paper aims to obtain a better and more efficient inference effect by introducing PPO into knowledge inference technology. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=reinforcement%20learning" title="reinforcement learning">reinforcement learning</a>, <a href="https://publications.waset.org/abstracts/search?q=PPO" title=" PPO"> PPO</a>, <a href="https://publications.waset.org/abstracts/search?q=knowledge%20inference" title=" knowledge inference"> knowledge inference</a> </p> <a href="https://publications.waset.org/abstracts/168844/research-on-knowledge-graph-inference-technology-based-on-proximal-policy-optimization" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/168844.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">243</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1002</span> QoS-CBMG: A Model for e-Commerce Customer Behavior</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hoda%20Ghavamipoor">Hoda Ghavamipoor</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20Alireza%20Hashemi%20Golpayegani"> S. Alireza Hashemi Golpayegani</a> </p> <p class="card-text"><strong>Abstract:</strong></p> An approach to model the customer interaction with e-commerce websites is presented. Considering the service quality level as a predictive feature, we offer an improved method based on the Customer Behavior Model Graph (CBMG), a state-transition graph model. To derive the Quality of Service sensitive-CBMG (QoS-CBMG) model, process-mining techniques is applied to pre-processed website server logs which are categorized as ‘buy’ or ‘visit’. Experimental results on an e-commerce website data confirmed that the proposed method outperforms CBMG based method. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=customer%20behavior%20model" title="customer behavior model">customer behavior model</a>, <a href="https://publications.waset.org/abstracts/search?q=electronic%20commerce" title=" electronic commerce"> electronic commerce</a>, <a href="https://publications.waset.org/abstracts/search?q=quality%20of%20service" title=" quality of service"> quality of service</a>, <a href="https://publications.waset.org/abstracts/search?q=customer%20behavior%20model%20graph" title=" customer behavior model graph"> customer behavior model graph</a>, <a href="https://publications.waset.org/abstracts/search?q=process%20mining" title=" process mining"> process mining</a> </p> <a href="https://publications.waset.org/abstracts/41945/qos-cbmg-a-model-for-e-commerce-customer-behavior" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/41945.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">416</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1001</span> GRCNN: Graph Recognition Convolutional Neural Network for Synthesizing Programs from Flow Charts</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Lin%20Cheng">Lin Cheng</a>, <a href="https://publications.waset.org/abstracts/search?q=Zijiang%20Yang"> Zijiang Yang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Program synthesis is the task to automatically generate programs based on user specification. In this paper, we present a framework that synthesizes programs from flow charts that serve as accurate and intuitive specification. In order doing so, we propose a deep neural network called GRCNN that recognizes graph structure from its image. GRCNN is trained end-to-end, which can predict edge and node information of the flow chart simultaneously. Experiments show that the accuracy rate to synthesize a program is 66.4%, and the accuracy rates to recognize edge and node are 94.1% and 67.9%, respectively. On average, it takes about 60 milliseconds to synthesize a program. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=program%20synthesis" title="program synthesis">program synthesis</a>, <a href="https://publications.waset.org/abstracts/search?q=flow%20chart" title=" flow chart"> flow chart</a>, <a href="https://publications.waset.org/abstracts/search?q=specification" title=" specification"> specification</a>, <a href="https://publications.waset.org/abstracts/search?q=graph%20recognition" title=" graph recognition"> graph recognition</a>, <a href="https://publications.waset.org/abstracts/search?q=CNN" title=" CNN"> CNN</a> </p> <a href="https://publications.waset.org/abstracts/124641/grcnn-graph-recognition-convolutional-neural-network-for-synthesizing-programs-from-flow-charts" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/124641.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">119</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1000</span> Mostar Type Indices and QSPR Analysis of Octane Isomers</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=B.%20Roopa%20Sri">B. Roopa Sri</a>, <a href="https://publications.waset.org/abstracts/search?q=Y%20Lakshmi%20Naidu"> Y Lakshmi Naidu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Chemical Graph Theory (CGT) is the branch of mathematical chemistry in which molecules are modeled to study their physicochemical properties using molecular descriptors. Amongst these descriptors, topological indices play a vital role in predicting the properties by defining the graph topology of the molecule. Recently, the bond-additive topological index known as the Mostar index has been proposed. In this paper, we compute the Mostar-type indices of octane isomers and use the data obtained to perform QSPR analysis. Furthermore, we show the correlation between the Mostar type indices and the properties. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=chemical%20graph%20theory" title="chemical graph theory">chemical graph theory</a>, <a href="https://publications.waset.org/abstracts/search?q=mostar%20type%20indices" title=" mostar type indices"> mostar type indices</a>, <a href="https://publications.waset.org/abstracts/search?q=octane%20isomers" title=" octane isomers"> octane isomers</a>, <a href="https://publications.waset.org/abstracts/search?q=qspr%20analysis" title=" qspr analysis"> qspr analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=topological%20index" title=" topological index"> topological index</a> </p> <a href="https://publications.waset.org/abstracts/153959/mostar-type-indices-and-qspr-analysis-of-octane-isomers" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/153959.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">130</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">999</span> Using Wearable Device with Neuron Network to Classify Severity of Sleep Disorder</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ru-Yin%20Yang">Ru-Yin Yang</a>, <a href="https://publications.waset.org/abstracts/search?q=Chi%20Wu"> Chi Wu</a>, <a href="https://publications.waset.org/abstracts/search?q=Cheng-Yu%20Tsai"> Cheng-Yu Tsai</a>, <a href="https://publications.waset.org/abstracts/search?q=Yin-Tzu%20Lin"> Yin-Tzu Lin</a>, <a href="https://publications.waset.org/abstracts/search?q=Wen-Te%20Liu"> Wen-Te Liu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Background: Sleep breathing disorder (SDB) is a condition demonstrated by recurrent episodes of the airway obstruction leading to intermittent hypoxia and quality fragmentation during sleep time. However, the procedures for SDB severity examination remain complicated and costly. Objective: The objective of this study is to establish a simplified examination method for SDB by the respiratory impendence pattern sensor combining the signal processing and machine learning model. Methodologies: We records heart rate variability by the electrocardiogram and respiratory pattern by impendence. After the polysomnography (PSG) been done with the diagnosis of SDB by the apnea and hypopnea index (AHI), we calculate the episodes with the absence of flow and arousal index (AI) from device record. Subjects were divided into training and testing groups. Neuron network was used to establish a prediction model to classify the severity of the SDB by the AI, episodes, and body profiles. The performance was evaluated by classification in the testing group compared with PSG. Results: In this study, we enrolled 66 subjects (Male/Female: 37/29; Age:49.9±13.2) with the diagnosis of SDB in a sleep center in Taipei city, Taiwan, from 2015 to 2016. The accuracy from the confusion matrix on the test group by NN is 71.94 %. Conclusion: Based on the models, we established a prediction model for SDB by means of the wearable sensor. With more cases incoming and training, this system may be used to rapidly and automatically screen the risk of SDB in the future. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=sleep%20breathing%20disorder" title="sleep breathing disorder">sleep breathing disorder</a>, <a href="https://publications.waset.org/abstracts/search?q=apnea%20and%20hypopnea%20index" title=" apnea and hypopnea index"> apnea and hypopnea index</a>, <a href="https://publications.waset.org/abstracts/search?q=body%20parameters" title=" body parameters"> body parameters</a>, <a href="https://publications.waset.org/abstracts/search?q=neuron%20network" title=" neuron network"> neuron network</a> </p> <a href="https://publications.waset.org/abstracts/98071/using-wearable-device-with-neuron-network-to-classify-severity-of-sleep-disorder" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/98071.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">150</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">998</span> Direct Electrophoretic Deposition of Hierarchical Structured Electrode Supercapacitor Application</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jhen-Ting%20Huang">Jhen-Ting Huang</a>, <a href="https://publications.waset.org/abstracts/search?q=Chia-Chia%20Chang"> Chia-Chia Chang</a>, <a href="https://publications.waset.org/abstracts/search?q=Hu-Cheng%20Weng"> Hu-Cheng Weng</a>, <a href="https://publications.waset.org/abstracts/search?q=An-Ya%20Lo"> An-Ya Lo</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this study, Co3O4-CNT-Graphene composite electrode was deposited by electrophoretic deposition (EPD) method, where micro polystyrene spheres (PSs) were added for co-deposition. Applied with heat treatment, a hierarchical porosity is left in the electrode which is beneficial for supercapacitor application. In terms of charge and discharge performance, we discussed the optimal CNT/Graphene ratio, macroporous ratio, and the effect of Co3O4 addition on electrode capacitance. For materials characterization, scanning electron microscope (SEM), X-ray diffraction, and BET were applied, while cyclic voltammetry (CV) and chronopotentiometry (CP) measurements, and Ragone plot were applied as in-situ analyses. Based on this, the effects of PS amount on the structure, porosity and their effect on capacitance of the electrodes were investigated. Finally, the full device performance was examined with charge-discharge and electron impedance spectrum (EIS) methods. The results show that the EPD coating with hierarchical porosity was successfully demonstrated in this study. As a result, the capacitance was greatly enhanced by 2.6 times with the hierarchical structure. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=supercapacitor" title="supercapacitor">supercapacitor</a>, <a href="https://publications.waset.org/abstracts/search?q=nanocarbon%20tub" title=" nanocarbon tub"> nanocarbon tub</a>, <a href="https://publications.waset.org/abstracts/search?q=graphene" title=" graphene"> graphene</a>, <a href="https://publications.waset.org/abstracts/search?q=metal%20oxide" title=" metal oxide"> metal oxide</a> </p> <a href="https://publications.waset.org/abstracts/107788/direct-electrophoretic-deposition-of-hierarchical-structured-electrode-supercapacitor-application" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/107788.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">139</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">997</span> Drug-Drug Interaction Prediction in Diabetes Mellitus</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Rashini%20Maduka">Rashini Maduka</a>, <a href="https://publications.waset.org/abstracts/search?q=C.%20R.%20Wijesinghe"> C. R. Wijesinghe</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20R.%20Weerasinghe"> A. R. Weerasinghe</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Drug-drug interactions (DDIs) can happen when two or more drugs are taken together. Today DDIs have become a serious health issue due to adverse drug effects. In vivo and in vitro methods for identifying DDIs are time-consuming and costly. Therefore, in-silico-based approaches are preferred in DDI identification. Most machine learning models for DDI prediction are used chemical and biological drug properties as features. However, some drug features are not available and costly to extract. Therefore, it is better to make automatic feature engineering. Furthermore, people who have diabetes already suffer from other diseases and take more than one medicine together. Then adverse drug effects may happen to diabetic patients and cause unpleasant reactions in the body. In this study, we present a model with a graph convolutional autoencoder and a graph decoder using a dataset from DrugBank version 5.1.3. The main objective of the model is to identify unknown interactions between antidiabetic drugs and the drugs taken by diabetic patients for other diseases. We considered automatic feature engineering and used Known DDIs only as the input for the model. Our model has achieved 0.86 in AUC and 0.86 in AP. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=drug-drug%20interaction%20prediction" title="drug-drug interaction prediction">drug-drug interaction prediction</a>, <a href="https://publications.waset.org/abstracts/search?q=graph%20embedding" title=" graph embedding"> graph embedding</a>, <a href="https://publications.waset.org/abstracts/search?q=graph%20convolutional%20networks" title=" graph convolutional networks"> graph convolutional networks</a>, <a href="https://publications.waset.org/abstracts/search?q=adverse%20drug%20effects" title=" adverse drug effects"> adverse drug effects</a> </p> <a href="https://publications.waset.org/abstracts/165305/drug-drug-interaction-prediction-in-diabetes-mellitus" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/165305.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">100</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">996</span> Hierarchical Zeolites as Potential Carriers of Curcumin</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ewelina%20Musielak">Ewelina Musielak</a>, <a href="https://publications.waset.org/abstracts/search?q=Agnieszka%20Feliczak-Guzik"> Agnieszka Feliczak-Guzik</a>, <a href="https://publications.waset.org/abstracts/search?q=Izabela%20Nowak"> Izabela Nowak</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Based on the latest data, it is expected that the substances of therapeutic interest used will be as natural as possible. Therefore, active substances with the highest possible efficacy and low toxicity are sought. Among natural substances with therapeutic effects, those of plant origin stand out. Curcumin isolated from the Curcuma longa plant has proven to be particularly important from a medical point of view. Due to its ability to regulate many important transcription factors, cytokines, and protein kinases, curcumin has found use as an anti-inflammatory, antioxidant, antiproliferative, antiangiogenic, and anticancer agent. The unfavorable properties of curcumin, such as low solubility, poor bioavailability, and rapid degradation under neutral or alkaline pH conditions, limit its clinical application. These problems can be solved by combining curcumin with suitable carriers such as hierarchical zeolites. This is a new class of materials that exhibit several advantages. Hierarchical zeolites used as drug carriers enable delayed release of the active ingredient and promote drug transport to the desired tissues and organs. In addition, hierarchical zeolites play an important role in regulating micronutrient levels in the body and have been used successfully in cancer diagnosis and therapy. To apply curcumin to hierarchical zeolites synthesized from commercial FAU zeolite, solutions containing curcumin, carrier and acetone were prepared. The prepared mixtures were then stirred on a magnetic stirrer for 24 h at room temperature. The curcumin-filled hierarchical zeolites were drained into a glass funnel, where they were washed three times with acetone and distilled water, after which the obtained material was air-dried until completely dry. In addition, the effect of piperine addition to zeolite carrier containing a sufficient amount of curcumin was studied. The resulting products were weighed and the percentage of pure curcumin in the hierarchical zeolite was calculated. All the synthesized materials were characterized by several techniques: elemental analysis, transmission electron microscopy (TEM), Fourier transform infrared spectroscopy, Fourier transform infrared (FT-IR), N2 adsorption, and X-ray diffraction (XRD) and thermogravimetric analysis (TGA). The aim of the presented study was to improve the biological activity of curcumin by applying it to hierarchical zeolites based on FAU zeolite. The results showed that the loading efficiency of curcumin into hierarchical zeolites based on commercial FAU-type zeolite is enhanced by modifying the zeolite carrier itself. The hierarchical zeolites proved to be very good and efficient carriers of plant-derived active ingredients such as curcumin. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=carriers%20of%20active%20substances" title="carriers of active substances">carriers of active substances</a>, <a href="https://publications.waset.org/abstracts/search?q=curcumin" title=" curcumin"> curcumin</a>, <a href="https://publications.waset.org/abstracts/search?q=hierarchical%20zeolites" title=" hierarchical zeolites"> hierarchical zeolites</a>, <a href="https://publications.waset.org/abstracts/search?q=incorporation" title=" incorporation"> incorporation</a> </p> <a href="https://publications.waset.org/abstracts/149020/hierarchical-zeolites-as-potential-carriers-of-curcumin" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/149020.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">98</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">995</span> Scheduling in Cloud Networks Using Chakoos Algorithm</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Masoumeh%20Ali%20Pouri">Masoumeh Ali Pouri</a>, <a href="https://publications.waset.org/abstracts/search?q=Hamid%20Haj%20Seyyed%20Javadi"> Hamid Haj Seyyed Javadi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Nowadays, cloud processing is one of the important issues in information technology. Since scheduling of tasks graph is an NP-hard problem, considering approaches based on undeterminisitic methods such as evolutionary processing, mostly genetic and cuckoo algorithms, will be effective. Therefore, an efficient algorithm has been proposed for scheduling of tasks graph to obtain an appropriate scheduling with minimum time. In this algorithm, the new approach is based on making the length of the critical path shorter and reducing the cost of communication. Finally, the results obtained from the implementation of the presented method show that this algorithm acts the same as other algorithms when it faces graphs without communication cost. It performs quicker and better than some algorithms like DSC and MCP algorithms when it faces the graphs involving communication cost. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=cloud%20computing" title="cloud computing">cloud computing</a>, <a href="https://publications.waset.org/abstracts/search?q=scheduling" title=" scheduling"> scheduling</a>, <a href="https://publications.waset.org/abstracts/search?q=tasks%20graph" title=" tasks graph"> tasks graph</a>, <a href="https://publications.waset.org/abstracts/search?q=chakoos%20algorithm" title=" chakoos algorithm"> chakoos algorithm</a> </p> <a href="https://publications.waset.org/abstracts/175869/scheduling-in-cloud-networks-using-chakoos-algorithm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/175869.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">65</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">994</span> Nonlinear Evolution on Graphs</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Benniche%20Omar">Benniche Omar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> We are concerned with abstract fully nonlinear differential equations having the form y’(t)=Ay(t)+f(t,y(t)) where A is an m—dissipative operator (possibly multi—valued) defined on a subset D(A) of a Banach space X with values in X and f is a given function defined on I×X with values in X. We consider a graph K in I×X. We recall that K is said to be viable with respect to the above abstract differential equation if for each initial data in K there exists at least one trajectory starting from that initial data and remaining in K at least for a short time. The viability problem has been studied by many authors by using various techniques and frames. If K is closed, it is shown that a tangency condition, which is mainly linked to the dynamic, is crucial for viability. In the case when X is infinite dimensional, compactness and convexity assumptions are needed. In this paper, we are concerned with the notion of near viability for a given graph K with respect to y’(t)=Ay(t)+f(t,y(t)). Roughly speaking, the graph K is said to be near viable with respect to y’(t)=Ay(t)+f(t,y(t)), if for each initial data in K there exists at least one trajectory remaining arbitrary close to K at least for short time. It is interesting to note that the near viability is equivalent to an appropriate tangency condition under mild assumptions on the dynamic. Adding natural convexity and compactness assumptions on the dynamic, we may recover the (exact) viability. Here we investigate near viability for a graph K in I×X with respect to y’(t)=Ay(t)+f(t,y(t)) where A and f are as above. We emphasis that the t—dependence on the perturbation f leads us to introduce a new tangency concept. In the base of a tangency conditions expressed in terms of that tangency concept, we formulate criteria for K to be near viable with respect to y’(t)=Ay(t)+f(t,y(t)). As application, an abstract null—controllability theorem is given. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=abstract%20differential%20equation" title="abstract differential equation">abstract differential equation</a>, <a href="https://publications.waset.org/abstracts/search?q=graph" title=" graph"> graph</a>, <a href="https://publications.waset.org/abstracts/search?q=tangency%20condition" title=" tangency condition"> tangency condition</a>, <a href="https://publications.waset.org/abstracts/search?q=viability" title=" viability"> viability</a> </p> <a href="https://publications.waset.org/abstracts/93317/nonlinear-evolution-on-graphs" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/93317.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">145</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">993</span> Application of Metric Dimension of Graph in Unraveling the Complexity of Hyperacusis</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hassan%20Ibrahim">Hassan Ibrahim</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The prevalence of hyperacusis, an auditory condition characterized by heightened sensitivity to sounds, continues to rise, posing challenges for effective diagnosis and intervention. It is believed that this work deepens will deepens the understanding of hyperacusis etiology by employing graph theory as a novel analytical framework. We constructed a comprehensive graph wherein nodes represent various factors associated with hyperacusis, including aging, head or neck trauma, infection/virus, depression, migraines, ear infection, anxiety, and other potential contributors. Relationships between factors are modeled as edges, allowing us to visualize and quantify the interactions within the etiological landscape of hyperacusis. it employ the concept of the metric dimension of a connected graph to identify key nodes (landmarks) that serve as critical influencers in the interconnected web of hyperacusis causes. This approach offers a unique perspective on the relative importance and centrality of different factors, shedding light on the complex interplay between physiological, psychological, and environmental determinants. Visualization techniques were also employed to enhance the interpretation and facilitate the identification of the central nodes. This research contributes to the growing body of knowledge surrounding hyperacusis by offering a network-centric perspective on its multifaceted causes. The outcomes hold the potential to inform clinical practices, guiding healthcare professionals in prioritizing interventions and personalized treatment plans based on the identified landmarks within the etiological network. Through the integration of graph theory into hyperacusis research, the complexity of this auditory condition was unraveled and pave the way for more effective approaches to its management. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=auditory%20condition" title="auditory condition">auditory condition</a>, <a href="https://publications.waset.org/abstracts/search?q=connected%20graph" title=" connected graph"> connected graph</a>, <a href="https://publications.waset.org/abstracts/search?q=hyperacusis" title=" hyperacusis"> hyperacusis</a>, <a href="https://publications.waset.org/abstracts/search?q=metric%20dimension" title=" metric dimension"> metric dimension</a> </p> <a href="https://publications.waset.org/abstracts/186986/application-of-metric-dimension-of-graph-in-unraveling-the-complexity-of-hyperacusis" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/186986.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">38</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">992</span> Unraveling the Complexity of Hyperacusis: A Metric Dimension of a Graph Concept</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hassan%20Ibrahim">Hassan Ibrahim</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The prevalence of hyperacusis, an auditory condition characterized by heightened sensitivity to sounds, continues to rise, posing challenges for effective diagnosis and intervention. It is believed that this work deepens will deepens the understanding of hyperacusis etiology by employing graph theory as a novel analytical framework. it constructed a comprehensive graph wherein nodes represent various factors associated with hyperacusis, including aging, head or neck trauma, infection/virus, depression, migraines, ear infection, anxiety, and other potential contributors. Relationships between factors are modeled as edges, allowing us to visualize and quantify the interactions within the etiological landscape of hyperacusis. it employ the concept of the metric dimension of a connected graph to identify key nodes (landmarks) that serve as critical influencers in the interconnected web of hyperacusis causes. This approach offers a unique perspective on the relative importance and centrality of different factors, shedding light on the complex interplay between physiological, psychological, and environmental determinants. Visualization techniques were also employed to enhance the interpretation and facilitate the identification of the central nodes. This research contributes to the growing body of knowledge surrounding hyperacusis by offering a network-centric perspective on its multifaceted causes. The outcomes hold the potential to inform clinical practices, guiding healthcare professionals in prioritizing interventions and personalized treatment plans based on the identified landmarks within the etiological network. Through the integration of graph theory into hyperacusis research, the complexity of this auditory condition was unraveled and pave the way for more effective approaches to its management. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=auditory%20condition" title="auditory condition">auditory condition</a>, <a href="https://publications.waset.org/abstracts/search?q=connected%20graph" title=" connected graph"> connected graph</a>, <a href="https://publications.waset.org/abstracts/search?q=hyperacusis" title=" hyperacusis"> hyperacusis</a>, <a href="https://publications.waset.org/abstracts/search?q=metric%20dimension" title=" metric dimension"> metric dimension</a> </p> <a href="https://publications.waset.org/abstracts/191632/unraveling-the-complexity-of-hyperacusis-a-metric-dimension-of-a-graph-concept" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/191632.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">24</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">991</span> Modeling and Simulation of a Cycloconverter with a Bond Graph Approach</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Gerardo%20Ayala-Jaimes">Gerardo Ayala-Jaimes</a>, <a href="https://publications.waset.org/abstracts/search?q=Gilberto%20Gonzalez-Avalos"> Gilberto Gonzalez-Avalos</a>, <a href="https://publications.waset.org/abstracts/search?q=Allen%20A.%20Castillo"> Allen A. Castillo</a>, <a href="https://publications.waset.org/abstracts/search?q=Alejandra%20Jimenez"> Alejandra Jimenez</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The modeling of a single-phase cycloconverter in Bond Graph is presented, which includes an alternating current power supply, hybrid dynamics, switch control, and resistive load; this approach facilitates the integration of systems across different energy domains and structural analysis. Cycloconverters, used in motor control, demonstrate the viability of graphical modeling. The use of Bonds is proposed to model the hybrid interaction of the system, and the results are displayed through simulations using 20Sim and Multisim software. The motivation behind developing these models with a graphical approach is to design and build low-cost energy converters, thereby making the main contribution of this document the modeling and simulation of a single-phase cycloconverter. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=bond%20graph" title="bond graph">bond graph</a>, <a href="https://publications.waset.org/abstracts/search?q=hybrid%20system" title=" hybrid system"> hybrid system</a>, <a href="https://publications.waset.org/abstracts/search?q=rectifier" title=" rectifier"> rectifier</a>, <a href="https://publications.waset.org/abstracts/search?q=cycloconverter" title=" cycloconverter"> cycloconverter</a>, <a href="https://publications.waset.org/abstracts/search?q=modelling" title=" modelling"> modelling</a> </p> <a href="https://publications.waset.org/abstracts/187321/modeling-and-simulation-of-a-cycloconverter-with-a-bond-graph-approach" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/187321.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">38</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">990</span> FLEX: A Backdoor Detection and Elimination Method in Federated Scenario</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Shuqi%20Zhang">Shuqi Zhang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Federated learning allows users to participate in collaborative model training without sending data to third-party servers, reducing the risk of user data privacy leakage, and is widely used in smart finance and smart healthcare. However, the distributed architecture design of federation learning itself and the existence of secure aggregation protocols make it inherently vulnerable to backdoor attacks. To solve this problem, the federated learning backdoor defense framework FLEX based on group aggregation, cluster analysis, and neuron pruning is proposed, and inter-compatibility with secure aggregation protocols is achieved. The good performance of FLEX is verified by building a horizontal federated learning framework on the CIFAR-10 dataset for experiments, which achieves 98% success rate of backdoor detection and reduces the success rate of backdoor tasks to 0% ~ 10%. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=federated%20learning" title="federated learning">federated learning</a>, <a href="https://publications.waset.org/abstracts/search?q=secure%20aggregation" title=" secure aggregation"> secure aggregation</a>, <a href="https://publications.waset.org/abstracts/search?q=backdoor%20attack" title=" backdoor attack"> backdoor attack</a>, <a href="https://publications.waset.org/abstracts/search?q=cluster%20analysis" title=" cluster analysis"> cluster analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=neuron%20pruning" title=" neuron pruning"> neuron pruning</a> </p> <a href="https://publications.waset.org/abstracts/158139/flex-a-backdoor-detection-and-elimination-method-in-federated-scenario" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/158139.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">96</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">989</span> Robust Diagnosis Efficiency by Bond-Graph Approach</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Benazzouz%20Djamel">Benazzouz Djamel</a>, <a href="https://publications.waset.org/abstracts/search?q=Termeche%20Adel"> Termeche Adel</a>, <a href="https://publications.waset.org/abstracts/search?q=Touati%20Youcef"> Touati Youcef</a>, <a href="https://publications.waset.org/abstracts/search?q=Alem%20Said"> Alem Said</a>, <a href="https://publications.waset.org/abstracts/search?q=Ouziala%20Mahdi"> Ouziala Mahdi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents an approach which detect and isolate efficiently a fault in a system. This approach avoids false alarms, non-detections and delays in detecting faults. A study case have been proposed to show the importance of taking into consideration the uncertainties in the decision-making procedure and their effect on the degradation diagnostic performance and advantage of using Bond Graph (BG) for such degradation. The use of BG in the Linear Fractional Transformation (LFT) form allows generating robust Analytical Redundancy Relations (ARR’s), where the uncertain part of ARR’s is used to generate the residuals adaptive thresholds. The study case concerns an electromechanical system composed of a motor, a reducer and an external load. The aim of this application is to show the effectiveness of the BG-LFT approach to robust fault detection. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=bond%20graph" title="bond graph">bond graph</a>, <a href="https://publications.waset.org/abstracts/search?q=LFT" title=" LFT"> LFT</a>, <a href="https://publications.waset.org/abstracts/search?q=uncertainties" title=" uncertainties"> uncertainties</a>, <a href="https://publications.waset.org/abstracts/search?q=detection%20and%20faults%20isolation" title=" detection and faults isolation"> detection and faults isolation</a>, <a href="https://publications.waset.org/abstracts/search?q=ARR" title=" ARR"> ARR</a> </p> <a href="https://publications.waset.org/abstracts/44029/robust-diagnosis-efficiency-by-bond-graph-approach" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/44029.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">305</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">988</span> Development of Antibacterial Surface Based on Bio-Inspired Hierarchical Surface</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=M.Ayazi">M.Ayazi</a>, <a href="https://publications.waset.org/abstracts/search?q=N.%20Golshan%20Ebrahimi"> N. Golshan Ebrahimi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The development of antibacterial surface has devoted extensive researches and important field due to the growing antimicrobial resistance strains. The superhydrophobic surface has raised attention because of reducing bacteria adhesion in the absence of antibiotic agents. Evaluating the current development antibacterial surface has to be investigating to consider the potential of applying superhydrophobic surface to reduce bacterial adhesion or role of patterned surfaces on it. In this study, we present different samples with bio-inspired hierarchical and microstructures to consider their ability in reducing bacterial adhesion. The structures have inspired from rice-like pattern and lotus-leaf that developed on the polydimethylsiloxane (PDMS) and polypropylene (PP). The results of the attachment behaviors have considered on two bacteria strains of gram-negative Escherichia coli (E. coli) bacteria and gram-positive Staphylococcus aureus (S. aureus). The reduction of bacteria adhesion on these roughness surfaces demonstrated the effectiveness of rinsing ability on removing bacterial cells on structured plastic surfaces. Results have also offered the important role of bacterial species, material chemistry and hierarchical structure to prevent bacterial adhesion. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=hierarchical%20structure" title="hierarchical structure">hierarchical structure</a>, <a href="https://publications.waset.org/abstracts/search?q=self-cleaning" title=" self-cleaning"> self-cleaning</a>, <a href="https://publications.waset.org/abstracts/search?q=lotus-effect" title=" lotus-effect"> lotus-effect</a>, <a href="https://publications.waset.org/abstracts/search?q=bactericidal" title=" bactericidal"> bactericidal</a> </p> <a href="https://publications.waset.org/abstracts/98682/development-of-antibacterial-surface-based-on-bio-inspired-hierarchical-surface" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/98682.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">136</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">987</span> GeneNet: Temporal Graph Data Visualization for Gene Nomenclature and Relationships</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jake%20Gonzalez">Jake Gonzalez</a>, <a href="https://publications.waset.org/abstracts/search?q=Tommy%20Dang"> Tommy Dang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper proposes a temporal graph approach to visualize and analyze the evolution of gene relationships and nomenclature over time. An interactive web-based tool implements this temporal graph, enabling researchers to traverse a timeline and observe coupled dynamics in network topology and naming conventions. Analysis of a real human genomic dataset reveals the emergence of densely interconnected functional modules over time, representing groups of genes involved in key biological processes. For example, the antimicrobial peptide DEFA1A3 shows increased connections to related alpha-defensins involved in infection response. Tracking degree and betweenness centrality shifts over timeline iterations also quantitatively highlight the reprioritization of certain genes’ topological importance as knowledge advances. Examination of the CNR1 gene encoding the cannabinoid receptor CB1 demonstrates changing synonymous relationships and consolidating naming patterns over time, reflecting its unique functional role discovery. The integrated framework interconnecting these topological and nomenclature dynamics provides richer contextual insights compared to isolated analysis methods. Overall, this temporal graph approach enables a more holistic study of knowledge evolution to elucidate complex biology. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=temporal%20graph" title="temporal graph">temporal graph</a>, <a href="https://publications.waset.org/abstracts/search?q=gene%20relationships" title=" gene relationships"> gene relationships</a>, <a href="https://publications.waset.org/abstracts/search?q=nomenclature%20evolution" title=" nomenclature evolution"> nomenclature evolution</a>, <a href="https://publications.waset.org/abstracts/search?q=interactive%20visualization" title=" interactive visualization"> interactive visualization</a>, <a href="https://publications.waset.org/abstracts/search?q=biological%20insights" title=" biological insights"> biological insights</a> </p> <a href="https://publications.waset.org/abstracts/179111/genenet-temporal-graph-data-visualization-for-gene-nomenclature-and-relationships" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/179111.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">61</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">986</span> Image Segmentation Using 2-D Histogram in RGB Color Space in Digital Libraries </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=El%20Asnaoui%20Khalid">El Asnaoui Khalid</a>, <a href="https://publications.waset.org/abstracts/search?q=Aksasse%20Brahim"> Aksasse Brahim</a>, <a href="https://publications.waset.org/abstracts/search?q=Ouanan%20Mohammed"> Ouanan Mohammed </a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents an unsupervised color image segmentation method. It is based on a hierarchical analysis of 2-D histogram in RGB color space. This histogram minimizes storage space of images and thus facilitates the operations between them. The improved segmentation approach shows a better identification of objects in a color image and, at the same time, the system is fast. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=image%20segmentation" title="image segmentation">image segmentation</a>, <a href="https://publications.waset.org/abstracts/search?q=hierarchical%20analysis" title=" hierarchical analysis"> hierarchical analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=2-D%20histogram" title=" 2-D histogram"> 2-D histogram</a>, <a href="https://publications.waset.org/abstracts/search?q=classification" title=" classification"> classification</a> </p> <a href="https://publications.waset.org/abstracts/42096/image-segmentation-using-2-d-histogram-in-rgb-color-space-in-digital-libraries" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/42096.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">380</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">985</span> A Reactive Fast Inter-MAP Handover for Hierarchical Mobile IPv6</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Pyung%20Soo%20Kim">Pyung Soo Kim</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper proposes an optimized reactive fast intermobility anchor point (MAP) handover scheme for Hierarchical Mobile IPv6, called the ORFH-HMIPv6, to minimize packet loss of the existing scheme. The key idea of the proposed ORFHHMIPv6 scheme is that the serving MAP buffers packets toward the mobile node (MN) as soon as the link layer between MN and serving base station is disconnected. To implement the proposed scheme, the MAP discovery message exchanged between MN and serving MAP is extended. In addition, the IEEE 802.21 Media Independent Handover Function (MIHF) event service message is defined newly. Through analytic performance evaluation, the proposed ORFH-HMIPv6 scheme can be shown to minimize packet loss much than the existing scheme. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=hierarchical%20mobile%20IPv6%20%28HMIPv6%29" title="hierarchical mobile IPv6 (HMIPv6)">hierarchical mobile IPv6 (HMIPv6)</a>, <a href="https://publications.waset.org/abstracts/search?q=fast%20handover" title=" fast handover"> fast handover</a>, <a href="https://publications.waset.org/abstracts/search?q=reactive%20behavior" title=" reactive behavior"> reactive behavior</a>, <a href="https://publications.waset.org/abstracts/search?q=packet%20loss" title=" packet loss"> packet loss</a> </p> <a href="https://publications.waset.org/abstracts/47084/a-reactive-fast-inter-map-handover-for-hierarchical-mobile-ipv6" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/47084.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">213</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">984</span> Constructing Orthogonal De Bruijn and Kautz Sequences and Applications</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yaw-Ling%20Lin">Yaw-Ling Lin</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A de Bruijn graph of order k is a graph whose vertices representing all length-k sequences with edges joining pairs of vertices whose sequences have maximum possible overlap (length k−1). Every Hamiltonian cycle of this graph defines a distinct, minimum length de Bruijn sequence containing all k-mers exactly once. A Kautz sequence is the minimal generating sequence so as the sequence of minimal length that produces all possible length-k sequences with the restriction that every two consecutive alphabets in the sequences must be different. A collection of de Bruijn/Kautz sequences are orthogonal if any two sequences are of maximally differ in sequence composition; that is, the maximum length of their common substring is k. In this paper, we discuss how such a collection of (maximal) orthogonal de Bruijn/Kautz sequences can be made and use the algorithm to build up a web application service for the synthesized DNA and other related biomolecular sequences. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=biomolecular%20sequence%20synthesis" title="biomolecular sequence synthesis">biomolecular sequence synthesis</a>, <a href="https://publications.waset.org/abstracts/search?q=de%20Bruijn%20sequences" title=" de Bruijn sequences"> de Bruijn sequences</a>, <a href="https://publications.waset.org/abstracts/search?q=Eulerian%20cycle" title=" Eulerian cycle"> Eulerian cycle</a>, <a href="https://publications.waset.org/abstracts/search?q=Hamiltonian%20cycle" title=" Hamiltonian cycle"> Hamiltonian cycle</a>, <a href="https://publications.waset.org/abstracts/search?q=Kautz%20sequences" title=" Kautz sequences"> Kautz sequences</a>, <a href="https://publications.waset.org/abstracts/search?q=orthogonal%20sequences" title=" orthogonal sequences"> orthogonal sequences</a> </p> <a href="https://publications.waset.org/abstracts/121912/constructing-orthogonal-de-bruijn-and-kautz-sequences-and-applications" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/121912.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">167</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">983</span> Graph Neural Network-Based Classification for Disease Prediction in Health Care Heterogeneous Data Structures of Electronic Health Record</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Raghavi%20C.%20Janaswamy">Raghavi C. Janaswamy</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In the healthcare sector, heterogenous data elements such as patients, diagnosis, symptoms, conditions, observation text from physician notes, and prescriptions form the essentials of the Electronic Health Record (EHR). The data in the form of clear text and images are stored or processed in a relational format in most systems. However, the intrinsic structure restrictions and complex joins of relational databases limit the widespread utility. In this regard, the design and development of realistic mapping and deep connections as real-time objects offer unparallel advantages. Herein, a graph neural network-based classification of EHR data has been developed. The patient conditions have been predicted as a node classification task using a graph-based open source EHR data, Synthea Database, stored in Tigergraph. The Synthea DB dataset is leveraged due to its closer representation of the real-time data and being voluminous. The graph model is built from the EHR heterogeneous data using python modules, namely, pyTigerGraph to get nodes and edges from the Tigergraph database, PyTorch to tensorize the nodes and edges, PyTorch-Geometric (PyG) to train the Graph Neural Network (GNN) and adopt the self-supervised learning techniques with the AutoEncoders to generate the node embeddings and eventually perform the node classifications using the node embeddings. The model predicts patient conditions ranging from common to rare situations. The outcome is deemed to open up opportunities for data querying toward better predictions and accuracy. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=electronic%20health%20record" title="electronic health record">electronic health record</a>, <a href="https://publications.waset.org/abstracts/search?q=graph%20neural%20network" title=" graph neural network"> graph neural network</a>, <a href="https://publications.waset.org/abstracts/search?q=heterogeneous%20data" title=" heterogeneous data"> heterogeneous data</a>, <a href="https://publications.waset.org/abstracts/search?q=prediction" title=" prediction"> prediction</a> </p> <a href="https://publications.waset.org/abstracts/157840/graph-neural-network-based-classification-for-disease-prediction-in-health-care-heterogeneous-data-structures-of-electronic-health-record" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/157840.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">86</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">982</span> Aspect-Level Sentiment Analysis with Multi-Channel and Graph Convolutional Networks</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jiajun%20Wang">Jiajun Wang</a>, <a href="https://publications.waset.org/abstracts/search?q=Xiaoge%20Li"> Xiaoge Li</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The purpose of the aspect-level sentiment analysis task is to identify the sentiment polarity of aspects in a sentence. Currently, most methods mainly focus on using neural networks and attention mechanisms to model the relationship between aspects and context, but they ignore the dependence of words in different ranges in the sentence, resulting in deviation when assigning relationship weight to other words other than aspect words. To solve these problems, we propose a new aspect-level sentiment analysis model that combines a multi-channel convolutional network and graph convolutional network (GCN). Firstly, the context and the degree of association between words are characterized by Long Short-Term Memory (LSTM) and self-attention mechanism. Besides, a multi-channel convolutional network is used to extract the features of words in different ranges. Finally, a convolutional graph network is used to associate the node information of the dependency tree structure. We conduct experiments on four benchmark datasets. The experimental results are compared with those of other models, which shows that our model is better and more effective. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=aspect-level%20sentiment%20analysis" title="aspect-level sentiment analysis">aspect-level sentiment analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=attention" title=" attention"> attention</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-channel%20convolution%20network" title=" multi-channel convolution network"> multi-channel convolution network</a>, <a href="https://publications.waset.org/abstracts/search?q=graph%20convolution%20network" title=" graph convolution network"> graph convolution network</a>, <a href="https://publications.waset.org/abstracts/search?q=dependency%20tree" title=" dependency tree"> dependency tree</a> </p> <a href="https://publications.waset.org/abstracts/146513/aspect-level-sentiment-analysis-with-multi-channel-and-graph-convolutional-networks" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/146513.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">219</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">981</span> Surface to the Deeper: A Universal Entity Alignment Approach Focusing on Surface Information</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Zheng%20Baichuan">Zheng Baichuan</a>, <a href="https://publications.waset.org/abstracts/search?q=Li%20Shenghui"> Li Shenghui</a>, <a href="https://publications.waset.org/abstracts/search?q=Li%20Bingqian"> Li Bingqian</a>, <a href="https://publications.waset.org/abstracts/search?q=Zhang%20Ning"> Zhang Ning</a>, <a href="https://publications.waset.org/abstracts/search?q=Chen%20Kai"> Chen Kai</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Entity alignment (EA) tasks in knowledge graphs often play a pivotal role in the integration of knowledge graphs, where structural differences often exist between the source and target graphs, such as the presence or absence of attribute information and the types of attribute information (text, timestamps, images, etc.). However, most current research efforts are focused on improving alignment accuracy, often along with an increased reliance on specific structures -a dependency that inevitably diminishes their practical value and causes difficulties when facing knowledge graph alignment tasks with varying structures. Therefore, we propose a universal knowledge graph alignment approach that only utilizes the common basic structures shared by knowledge graphs. We have demonstrated through experiments that our method achieves state-of-the-art performance in fair comparisons. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=knowledge%20graph" title="knowledge graph">knowledge graph</a>, <a href="https://publications.waset.org/abstracts/search?q=entity%20alignment" title=" entity alignment"> entity alignment</a>, <a href="https://publications.waset.org/abstracts/search?q=transformer" title=" transformer"> transformer</a>, <a href="https://publications.waset.org/abstracts/search?q=deep%20learning" title=" deep learning"> deep learning</a> </p> <a href="https://publications.waset.org/abstracts/185816/surface-to-the-deeper-a-universal-entity-alignment-approach-focusing-on-surface-information" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/185816.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">45</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">980</span> Robust Diagnosability of PEMFC Based on Bond Graph LFT</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ould%20Bouamama">Ould Bouamama</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20Bressel"> M. Bressel</a>, <a href="https://publications.waset.org/abstracts/search?q=D.%20Hissel"> D. Hissel</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20Hilairet"> M. Hilairet</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Fuel cell (FC) is one of the best alternatives of fossil energy. Recently, the research community of fuel cell has shown a considerable interest for diagnosis in view to ensure safety, security, and availability when faults occur in the process. The problematic for model based FC diagnosis consists in that the model is complex because of coupling of several kind of energies and the numerical values of parameters are not always known or are uncertain. The present paper deals with use of one tool: the Linear Fractional Transformation bond graph tool not only for uncertain modelling but also for monitorability (ability to detect and isolate faults) analysis and formal generation of robust fault indicators with respect to parameter uncertainties.The developed theory applied to a nonlinear FC system has proved its efficiency. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=bond%20graph" title="bond graph">bond graph</a>, <a href="https://publications.waset.org/abstracts/search?q=fuel%20cell" title=" fuel cell"> fuel cell</a>, <a href="https://publications.waset.org/abstracts/search?q=fault%20detection%20and%20isolation%20%28FDI%29" title=" fault detection and isolation (FDI)"> fault detection and isolation (FDI)</a>, <a href="https://publications.waset.org/abstracts/search?q=robust%20diagnosis" title=" robust diagnosis"> robust diagnosis</a>, <a href="https://publications.waset.org/abstracts/search?q=structural%20analysis" title=" structural analysis"> structural analysis</a> </p> <a href="https://publications.waset.org/abstracts/29565/robust-diagnosability-of-pemfc-based-on-bond-graph-lft" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/29565.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">366</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">979</span> Dynamics of the Coupled Fitzhugh-Rinzel Neurons</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sanjeev%20Kumar%20Sharma">Sanjeev Kumar Sharma</a>, <a href="https://publications.waset.org/abstracts/search?q=Arnab%20Mondal"> Arnab Mondal</a>, <a href="https://publications.waset.org/abstracts/search?q=Ranjit%20Kumar%20Upadhyay"> Ranjit Kumar Upadhyay</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Excitable cells often produce different oscillatory activities that help us to understand the transmitting and processing of signals in the neural system. We consider a FitzHugh-Rinzel (FH-R) model and studied the different dynamics of the model by considering the parameter c as the predominant parameter. The model exhibits different types of neuronal responses such as regular spiking, mixed-mode bursting oscillations (MMBOs), elliptic bursting, etc. Based on the bifurcation diagram, we consider the three regimes (MMBOs, elliptic bursting, and quiescent state). An analytical treatment for the occurrence of the supercritical Hopf bifurcation is studied. Further, we extend our study to a network of a hundred neurons by considering the bi-directional synaptic coupling between them. In this article, we investigate the alternation of spiking propagation and bursting phenomena of an uncoupled and coupled FH-R neurons. We explore that the complete graph of heterogenous desynchronized neurons can exhibit different types of bursting oscillations for certain coupling strength. For higher coupling strength, all the neurons in the network show complete synchronization. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=excitable%20neuron%20model" title="excitable neuron model">excitable neuron model</a>, <a href="https://publications.waset.org/abstracts/search?q=spiking-bursting" title=" spiking-bursting"> spiking-bursting</a>, <a href="https://publications.waset.org/abstracts/search?q=stability%20and%20bifurcation" title=" stability and bifurcation"> stability and bifurcation</a>, <a href="https://publications.waset.org/abstracts/search?q=synchronization%20networks" title=" synchronization networks"> synchronization networks</a> </p> <a href="https://publications.waset.org/abstracts/116729/dynamics-of-the-coupled-fitzhugh-rinzel-neurons" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/116729.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">128</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">978</span> Electricity Generation from Renewables and Targets: An Application of Multivariate Statistical Techniques </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Filiz%20Ersoz">Filiz Ersoz</a>, <a href="https://publications.waset.org/abstracts/search?q=Taner%20Ersoz"> Taner Ersoz</a>, <a href="https://publications.waset.org/abstracts/search?q=Tugrul%20Bayraktar"> Tugrul Bayraktar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Renewable energy is referred to as "clean energy" and common popular support for the use of renewable energy (RE) is to provide electricity with zero carbon dioxide emissions. This study provides useful insight into the European Union (EU) RE, especially, into electricity generation obtained from renewables, and their targets. The objective of this study is to identify groups of European countries, using multivariate statistical analysis and selected indicators. The hierarchical clustering method is used to decide the number of clusters for EU countries. The conducted statistical hierarchical cluster analysis is based on the Ward’s clustering method and squared Euclidean distances. Hierarchical cluster analysis identified eight distinct clusters of European countries. Then, non-hierarchical clustering (k-means) method was applied. Discriminant analysis was used to determine the validity of the results with data normalized by Z score transformation. To explore the relationship between the selected indicators, correlation coefficients were computed. The results of the study reveal the current situation of RE in European Union Member States. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=share%20of%20electricity%20generation" title="share of electricity generation">share of electricity generation</a>, <a href="https://publications.waset.org/abstracts/search?q=k-means%20clustering" title=" k-means clustering"> k-means clustering</a>, <a href="https://publications.waset.org/abstracts/search?q=discriminant" title=" discriminant"> discriminant</a>, <a href="https://publications.waset.org/abstracts/search?q=CO2%20emission" title=" CO2 emission"> CO2 emission</a> </p> <a href="https://publications.waset.org/abstracts/53237/electricity-generation-from-renewables-and-targets-an-application-of-multivariate-statistical-techniques" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/53237.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">415</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">977</span> Exploring the Activity Fabric of an Intelligent Environment with Hierarchical Hidden Markov Theory</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Chiung-Hui%20Chen">Chiung-Hui Chen</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The Internet of Things (IoT) was designed for widespread convenience. With the smart tag and the sensing network, a large quantity of dynamic information is immediately presented in the IoT. Through the internal communication and interaction, meaningful objects provide real-time services for users. Therefore, the service with appropriate decision-making has become an essential issue. Based on the science of human behavior, this study employed the environment model to record the time sequences and locations of different behaviors and adopted the probability module of the hierarchical Hidden Markov Model for the inference. The statistical analysis was conducted to achieve the following objectives: First, define user behaviors and predict the user behavior routes with the environment model to analyze user purposes. Second, construct the hierarchical Hidden Markov Model according to the logic framework, and establish the sequential intensity among behaviors to get acquainted with the use and activity fabric of the intelligent environment. Third, establish the intensity of the relation between the probability of objects’ being used and the objects. The indicator can describe the possible limitations of the mechanism. As the process is recorded in the information of the system created in this study, these data can be reused to adjust the procedure of intelligent design services. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=behavior" title="behavior">behavior</a>, <a href="https://publications.waset.org/abstracts/search?q=big%20data" title=" big data"> big data</a>, <a href="https://publications.waset.org/abstracts/search?q=hierarchical%20hidden%20Markov%20model" title=" hierarchical hidden Markov model"> hierarchical hidden Markov model</a>, <a href="https://publications.waset.org/abstracts/search?q=intelligent%20object" title=" intelligent object"> intelligent object</a> </p> <a href="https://publications.waset.org/abstracts/68970/exploring-the-activity-fabric-of-an-intelligent-environment-with-hierarchical-hidden-markov-theory" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/68970.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">233</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">976</span> Design of a Tool for Generating Test Cases from BPMN</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Prat%20Yotyawilai">Prat Yotyawilai</a>, <a href="https://publications.waset.org/abstracts/search?q=Taratip%20Suwannasart"> Taratip Suwannasart</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Business Process Model and Notation (BPMN) is more important in the business process and creating functional models, and is a standard for OMG, which becomes popular in various organizations and in education. Researches related to software testing based on models are prominent. Although most researches use the UML model in software testing, not many researches use the BPMN Model in creating test cases. Therefore, this research proposes a design of a tool for generating test cases from the BPMN. The model is analyzed and the details of the various components are extracted before creating a flow graph. Both details of components and the flow graph are used in generating test cases. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=software%20testing" title="software testing">software testing</a>, <a href="https://publications.waset.org/abstracts/search?q=test%20case" title=" test case"> test case</a>, <a href="https://publications.waset.org/abstracts/search?q=BPMN" title=" BPMN"> BPMN</a>, <a href="https://publications.waset.org/abstracts/search?q=flow%20graph" title=" flow graph"> flow graph</a> </p> <a href="https://publications.waset.org/abstracts/17143/design-of-a-tool-for-generating-test-cases-from-bpmn" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/17143.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">555</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">975</span> Autism Spectrum Disorder Classification Algorithm Using Multimodal Data Based on Graph Convolutional Network</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yuntao%20Liu">Yuntao Liu</a>, <a href="https://publications.waset.org/abstracts/search?q=Lei%20Wang"> Lei Wang</a>, <a href="https://publications.waset.org/abstracts/search?q=Haoran%20Xia"> Haoran Xia</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Machine learning has shown extensive applications in the development of classification models for autism spectrum disorder (ASD) using neural image data. This paper proposes a fusion multi-modal classification network based on a graph neural network. First, the brain is segmented into 116 regions of interest using a medical segmentation template (AAL, Anatomical Automatic Labeling). The image features of sMRI and the signal features of fMRI are extracted, which build the node and edge embedding representations of the brain map. Then, we construct a dynamically updated brain map neural network and propose a method based on a dynamic brain map adjacency matrix update mechanism and learnable graph to further improve the accuracy of autism diagnosis and recognition results. Based on the Autism Brain Imaging Data Exchange I dataset(ABIDE I), we reached a prediction accuracy of 74% between ASD and TD subjects. Besides, to study the biomarkers that can help doctors analyze diseases and interpretability, we used the features by extracting the top five maximum and minimum ROI weights. This work provides a meaningful way for brain disorder identification. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=autism%20spectrum%20disorder" title="autism spectrum disorder">autism spectrum disorder</a>, <a href="https://publications.waset.org/abstracts/search?q=brain%20map" title=" brain map"> brain map</a>, <a href="https://publications.waset.org/abstracts/search?q=supervised%20machine%20learning" title=" supervised machine learning"> supervised machine learning</a>, <a href="https://publications.waset.org/abstracts/search?q=graph%20network" title=" graph network"> graph network</a>, <a href="https://publications.waset.org/abstracts/search?q=multimodal%20data" title=" multimodal data"> multimodal data</a>, <a href="https://publications.waset.org/abstracts/search?q=model%20interpretability" title=" model interpretability"> model interpretability</a> </p> <a href="https://publications.waset.org/abstracts/183319/autism-spectrum-disorder-classification-algorithm-using-multimodal-data-based-on-graph-convolutional-network" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/183319.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">67</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">974</span> Using Closed Frequent Itemsets for Hierarchical Document Clustering</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Cheng-Jhe%20Lee">Cheng-Jhe Lee</a>, <a href="https://publications.waset.org/abstracts/search?q=Chiun-Chieh%20Hsu"> Chiun-Chieh Hsu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Due to the rapid development of the Internet and the increased availability of digital documents, the excessive information on the Internet has led to information overflow problem. In order to solve these problems for effective information retrieval, document clustering in text mining becomes a popular research topic. Clustering is the unsupervised classification of data items into groups without the need of training data. Many conventional document clustering methods perform inefficiently for large document collections because they were originally designed for relational database. Therefore they are impractical in real-world document clustering and require special handling for high dimensionality and high volume. We propose the FIHC (Frequent Itemset-based Hierarchical Clustering) method, which is a hierarchical clustering method developed for document clustering, where the intuition of FIHC is that there exist some common words for each cluster. FIHC uses such words to cluster documents and builds hierarchical topic tree. In this paper, we combine FIHC algorithm with ontology to solve the semantic problem and mine the meaning behind the words in documents. Furthermore, we use the closed frequent itemsets instead of only use frequent itemsets, which increases efficiency and scalability. The experimental results show that our method is more accurate than those of well-known document clustering algorithms. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=FIHC" title="FIHC">FIHC</a>, <a href="https://publications.waset.org/abstracts/search?q=documents%20clustering" title=" documents clustering"> documents clustering</a>, <a href="https://publications.waset.org/abstracts/search?q=ontology" title=" ontology"> ontology</a>, <a href="https://publications.waset.org/abstracts/search?q=closed%20frequent%20itemset" title=" closed frequent itemset"> closed frequent itemset</a> </p> <a href="https://publications.waset.org/abstracts/41381/using-closed-frequent-itemsets-for-hierarchical-document-clustering" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/41381.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right 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