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estimation</title> <meta name="description" content="Search results for: Depth estimation"> <meta name="keywords" content="Depth estimation"> <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 class="d-block d-lg-none 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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="Depth estimation"> <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> 5082</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: Depth estimation</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">5082</span> Depth Estimation in DNN Using Stereo Thermal Image Pairs</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ahmet%20Faruk%20Akyuz">Ahmet Faruk Akyuz</a>, <a href="https://publications.waset.org/abstracts/search?q=Hasan%20Sakir%20Bilge">Hasan Sakir Bilge</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Depth estimation using stereo images is a challenging problem in computer vision. Many different studies have been carried out to solve this problem. With advancing machine learning, tackling this problem is often done with neural network-based solutions. The images used in these studies are mostly in the visible spectrum. However, the need to use the Infrared (IR) spectrum for depth estimation has emerged because it gives better results than visible spectra in some conditions. At this point, we recommend using thermal-thermal (IR) image pairs for depth estimation. In this study, we used two well-known networks (PSMNet, FADNet) with minor modifications to demonstrate the viability of this idea. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=thermal%20stereo%20matching" title="thermal stereo matching">thermal stereo matching</a>, <a href="https://publications.waset.org/abstracts/search?q=deep%20neural%20networks" title="deep neural networks">deep neural networks</a>, <a href="https://publications.waset.org/abstracts/search?q=CNN" title="CNN">CNN</a>, <a href="https://publications.waset.org/abstracts/search?q=Depth%20estimation" title="Depth estimation">Depth estimation</a> </p> <a href="https://publications.waset.org/abstracts/140133/depth-estimation-in-dnn-using-stereo-thermal-image-pairs" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/140133.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">279</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">5081</span> Estimation of Slab Depth, Column Size and Rebar Location of Concrete Specimen Using Impact Echo Method</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Y.%20T.%20Lee">Y. T. Lee</a>, <a href="https://publications.waset.org/abstracts/search?q=J.%20H.%20Na"> J. H. Na</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20H.%20Kim"> S. H. Kim</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20U.%20Hong"> S. U. Hong</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this study, an experimental research for estimation of slab depth, column size and location of rebar of concrete specimen is conducted using the Impact Echo Method (IE) based on stress wave among non-destructive test methods. Estimation of slab depth had total length of 1800×300 and 6 different depths including 150 mm, 180 mm, 210 mm, 240 mm, 270 mm and 300 mm. The concrete column specimen was manufactured by differentiating the size into 300×300×300 mm, 400×400×400 mm and 500×500×500 mm. In case of the specimen for estimation of rebar, rebar of ∅22 mm was used in a specimen of 300×370×200 and arranged at 130 mm and 150 mm from the top to the rebar top. As a result of error rate of slab depth was overall mean of 3.1%. Error rate of column size was overall mean of 1.7%. Mean error rate of rebar location was 1.72% for top, 1.19% for bottom and 1.5% for overall mean showing relative accuracy. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=impact%20echo%20method" title="impact echo method">impact echo method</a>, <a href="https://publications.waset.org/abstracts/search?q=estimation" title=" estimation"> estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=slab%20depth" title=" slab depth"> slab depth</a>, <a href="https://publications.waset.org/abstracts/search?q=column%20size" title=" column size"> column size</a>, <a href="https://publications.waset.org/abstracts/search?q=rebar%20location" title=" rebar location"> rebar location</a>, <a href="https://publications.waset.org/abstracts/search?q=concrete" title=" concrete"> concrete</a> </p> <a href="https://publications.waset.org/abstracts/6106/estimation-of-slab-depth-column-size-and-rebar-location-of-concrete-specimen-using-impact-echo-method" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/6106.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">351</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">5080</span> Regression Model Evaluation on Depth Camera Data for Gaze Estimation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=James%20Purnama">James Purnama</a>, <a href="https://publications.waset.org/abstracts/search?q=Riri%20Fitri%20Sari"> Riri Fitri Sari</a> </p> <p class="card-text"><strong>Abstract:</strong></p> We investigate the machine learning algorithm selection problem in the term of a depth image based eye gaze estimation, with respect to its essential difficulty in reducing the number of required training samples and duration time of training. Statistics based prediction accuracy are increasingly used to assess and evaluate prediction or estimation in gaze estimation. This article evaluates Root Mean Squared Error (RMSE) and R-Squared statistical analysis to assess machine learning methods on depth camera data for gaze estimation. There are 4 machines learning methods have been evaluated: Random Forest Regression, Regression Tree, Support Vector Machine (SVM), and Linear Regression. The experiment results show that the Random Forest Regression has the lowest RMSE and the highest R-Squared, which means that it is the best among other methods. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=gaze%20estimation" title="gaze estimation">gaze estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=gaze%20tracking" title=" gaze tracking"> gaze tracking</a>, <a href="https://publications.waset.org/abstracts/search?q=eye%20tracking" title=" eye tracking"> eye tracking</a>, <a href="https://publications.waset.org/abstracts/search?q=kinect" title=" kinect"> kinect</a>, <a href="https://publications.waset.org/abstracts/search?q=regression%20model" title=" regression model"> regression model</a>, <a href="https://publications.waset.org/abstracts/search?q=orange%20python" title=" orange python"> orange python</a> </p> <a href="https://publications.waset.org/abstracts/17938/regression-model-evaluation-on-depth-camera-data-for-gaze-estimation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/17938.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">538</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">5079</span> Extended Constraint Mask Based One-Bit Transform for Low-Complexity Fast Motion Estimation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=O%C4%9Fuzhan%20Urhan">Oğuzhan Urhan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, an improved motion estimation (ME) approach based on weighted constrained one-bit transform is proposed for block-based ME employed in video encoders. Binary ME approaches utilize low bit-depth representation of the original image frames with a Boolean exclusive-OR based hardware efficient matching criterion to decrease computational burden of the ME stage. Weighted constrained one-bit transform (WC‑1BT) based approach improves the performance of conventional C-1BT based ME employing 2-bit depth constraint mask instead of a 1-bit depth mask. In this work, the range of constraint mask is further extended to increase ME performance of WC-1BT approach. Experiments reveal that the proposed method provides better ME accuracy compared existing similar ME methods in the literature. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=fast%20motion%20estimation%3B%20low-complexity%20motion%20estimation" title="fast motion estimation; low-complexity motion estimation">fast motion estimation; low-complexity motion estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=video%20coding" title=" video coding"> video coding</a> </p> <a href="https://publications.waset.org/abstracts/76760/extended-constraint-mask-based-one-bit-transform-for-low-complexity-fast-motion-estimation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/76760.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">316</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">5078</span> Hardware Implementation of Local Binary Pattern Based Two-Bit Transform Motion Estimation </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Seda%20Yavuz">Seda Yavuz</a>, <a href="https://publications.waset.org/abstracts/search?q=An%C4%B1l%20%C3%87elebi"> Anıl Çelebi</a>, <a href="https://publications.waset.org/abstracts/search?q=Aysun%20Ta%C5%9Fyap%C4%B1%20%C3%87elebi"> Aysun Taşyapı Çelebi</a>, <a href="https://publications.waset.org/abstracts/search?q=O%C4%9Fuzhan%20Urhan"> Oğuzhan Urhan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Nowadays, demand for using real-time video transmission capable devices is ever-increasing. So, high resolution videos have made efficient video compression techniques an essential component for capturing and transmitting video data. Motion estimation has a critical role in encoding raw video. Hence, various motion estimation methods are introduced to efficiently compress the video. Low bit‑depth representation based motion estimation methods facilitate computation of matching criteria and thus, provide small hardware footprint. In this paper, a hardware implementation of a two-bit transformation based low-complexity motion estimation method using local binary pattern approach is proposed. Image frames are represented in two-bit depth instead of full-depth by making use of the local binary pattern as a binarization approach and the binarization part of the hardware architecture is explained in detail. Experimental results demonstrate the difference between the proposed hardware architecture and the architectures of well-known low-complexity motion estimation methods in terms of important aspects such as resource utilization, energy and power consumption. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=binarization" title="binarization">binarization</a>, <a href="https://publications.waset.org/abstracts/search?q=hardware%20architecture" title=" hardware architecture"> hardware architecture</a>, <a href="https://publications.waset.org/abstracts/search?q=local%20binary%20pattern" title=" local binary pattern"> local binary pattern</a>, <a href="https://publications.waset.org/abstracts/search?q=motion%20estimation" title=" motion estimation"> motion estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=two-bit%20transform" title=" two-bit transform"> two-bit transform</a> </p> <a href="https://publications.waset.org/abstracts/77730/hardware-implementation-of-local-binary-pattern-based-two-bit-transform-motion-estimation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/77730.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">311</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">5077</span> Monocular Depth Estimation Benchmarking with Thermal Dataset</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ali%20Akyar">Ali Akyar</a>, <a href="https://publications.waset.org/abstracts/search?q=Osman%20Serdar%20Gedik"> Osman Serdar Gedik</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Depth estimation is a challenging computer vision task that involves estimating the distance between objects in a scene and the camera. It predicts how far each pixel in the 2D image is from the capturing point. There are some important Monocular Depth Estimation (MDE) studies that are based on Vision Transformers (ViT). We benchmark three major studies. The first work aims to build a simple and powerful foundation model that deals with any images under any condition. The second work proposes a method by mixing multiple datasets during training and a robust training objective. The third work combines generalization performance and state-of-the-art results on specific datasets. Although there are studies with thermal images too, we wanted to benchmark these three non-thermal, state-of-the-art studies with a hybrid image dataset which is taken by Multi-Spectral Dynamic Imaging (MSX) technology. MSX technology produces detailed thermal images by bringing together the thermal and visual spectrums. Using this technology, our dataset images are not blur and poorly detailed as the normal thermal images. On the other hand, they are not taken at the perfect light conditions as RGB images. We compared three methods under test with our thermal dataset which was not done before. Additionally, we propose an image enhancement deep learning model for thermal data. This model helps extract the features required for monocular depth estimation. The experimental results demonstrate that, after using our proposed model, the performance of these three methods under test increased significantly for thermal image depth prediction. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=monocular%20depth%20estimation" title="monocular depth estimation">monocular depth estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=thermal%20dataset" title=" thermal dataset"> thermal dataset</a>, <a href="https://publications.waset.org/abstracts/search?q=benchmarking" title=" benchmarking"> benchmarking</a>, <a href="https://publications.waset.org/abstracts/search?q=vision%20transformers" title=" vision transformers"> vision transformers</a> </p> <a href="https://publications.waset.org/abstracts/186398/monocular-depth-estimation-benchmarking-with-thermal-dataset" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/186398.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">32</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">5076</span> Scour Depth Prediction around Bridge Piers Using Neuro-Fuzzy and Neural Network Approaches</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=H.%20Bonakdari">H. Bonakdari</a>, <a href="https://publications.waset.org/abstracts/search?q=I.%20Ebtehaj"> I. Ebtehaj</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The prediction of scour depth around bridge piers is frequently considered in river engineering. One of the key aspects in efficient and optimum bridge structure design is considered to be scour depth estimation around bridge piers. In this study, scour depth around bridge piers is estimated using two methods, namely the Adaptive Neuro-Fuzzy Inference System (ANFIS) and Artificial Neural Network (ANN). Therefore, the effective parameters in scour depth prediction are determined using the ANN and ANFIS methods via dimensional analysis, and subsequently, the parameters are predicted. In the current study, the methods’ performances are compared with the nonlinear regression (NLR) method. The results show that both methods presented in this study outperform existing methods. Moreover, using the ratio of pier length to flow depth, ratio of median diameter of particles to flow depth, ratio of pier width to flow depth, the Froude number and standard deviation of bed grain size parameters leads to optimal performance in scour depth estimation. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=adaptive%20neuro-fuzzy%20inference%20system%20%28ANFIS%29" title="adaptive neuro-fuzzy inference system (ANFIS)">adaptive neuro-fuzzy inference system (ANFIS)</a>, <a href="https://publications.waset.org/abstracts/search?q=artificial%20neural%20network%20%28ANN%29" title=" artificial neural network (ANN)"> artificial neural network (ANN)</a>, <a href="https://publications.waset.org/abstracts/search?q=bridge%20pier" title=" bridge pier"> bridge pier</a>, <a href="https://publications.waset.org/abstracts/search?q=scour%20depth" title=" scour depth"> scour depth</a>, <a href="https://publications.waset.org/abstracts/search?q=nonlinear%20regression%20%28NLR%29" title=" nonlinear regression (NLR)"> nonlinear regression (NLR)</a> </p> <a href="https://publications.waset.org/abstracts/73889/scour-depth-prediction-around-bridge-piers-using-neuro-fuzzy-and-neural-network-approaches" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/73889.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">218</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">5075</span> Estimation of Source Parameters Using Source Parameters Imaging Method From Digitised High Resolution Airborne Magnetic Data of a Basement Complex</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=O.%20T.%20Oluriz">O. T. Oluriz</a>, <a href="https://publications.waset.org/abstracts/search?q=O.%20D.%20Akinyemi"> O. D. Akinyemi</a>, <a href="https://publications.waset.org/abstracts/search?q=J.%20A.Olowofela"> J. A.Olowofela</a>, <a href="https://publications.waset.org/abstracts/search?q=O.%20A.%20Idowu"> O. A. Idowu</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20A.%20Ganiyu"> S. A. Ganiyu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This study was carried out using aeromagnetic data which record variation in the magnitude of the earth magnetic field in order to detect local changes in the properties of the underlying geology. The aeromagnetic data (Sheet No. 261) was acquired from the archives of Nigeria Geological Survey Agency of Nigeria, obtained in 2009. The study present estimation of source parameters within an area of about 3,025 square kilometers on geographic latitude to and longitude to within Ibadan and it’s environs in Oyo State, southwestern Nigeria. The area under study belongs to part of basement complex in southwestern Nigeria. Estimation of source parameters of aeromagnetic data was achieve through the application of source imaging parameters (SPI) techniques that provide delineation, depth, dip contact, susceptibility contrast and mineral potentials of magnetic signatures within the region. The depth to the magnetic sources in the area ranges from 0.675 km to 4.48 km. The estimated depth limit to shallow sources is 0.695 km and depth to deep sources is 4.48 km. The apparent susceptibility values of the entire study area obtained ranges from 0.01 to 0.005 [SI]. This study has shown that the magnetic susceptibility within study area is controlled mainly by super paramagnetic minerals. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=aeromagnetic" title="aeromagnetic">aeromagnetic</a>, <a href="https://publications.waset.org/abstracts/search?q=basement%20complex" title=" basement complex"> basement complex</a>, <a href="https://publications.waset.org/abstracts/search?q=meta-sediment" title=" meta-sediment"> meta-sediment</a>, <a href="https://publications.waset.org/abstracts/search?q=precambrian" title=" precambrian"> precambrian</a> </p> <a href="https://publications.waset.org/abstracts/3195/estimation-of-source-parameters-using-source-parameters-imaging-method-from-digitised-high-resolution-airborne-magnetic-data-of-a-basement-complex" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/3195.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">430</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">5074</span> Determining the Width and Depths of Cut in Milling on the Basis of a Multi-Dexel Model</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jens%20Friedrich">Jens Friedrich</a>, <a href="https://publications.waset.org/abstracts/search?q=Matthias%20A.%20Gebele"> Matthias A. Gebele</a>, <a href="https://publications.waset.org/abstracts/search?q=Armin%20Lechler"> Armin Lechler</a>, <a href="https://publications.waset.org/abstracts/search?q=Alexander%20Verl"> Alexander Verl</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Chatter vibrations and process instabilities are the most important factors limiting the productivity of the milling process. Chatter can leads to damage of the tool, the part or the machine tool. Therefore, the estimation and prediction of the process stability is very important. The process stability depends on the spindle speed, the depth of cut and the width of cut. In milling, the process conditions are defined in the NC-program. While the spindle speed is directly coded in the NC-program, the depth and width of cut are unknown. This paper presents a new simulation based approach for the prediction of the depth and width of cut of a milling process. The prediction is based on a material removal simulation with an analytically represented tool shape and a multi-dexel approach for the work piece. The new calculation method allows the direct estimation of the depth and width of cut, which are the influencing parameters of the process stability, instead of the removed volume as existing approaches do. The knowledge can be used to predict the stability of new, unknown parts. Moreover with an additional vibration sensor, the stability lobe diagram of a milling process can be estimated and improved based on the estimated depth and width of cut. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=dexel" title="dexel">dexel</a>, <a href="https://publications.waset.org/abstracts/search?q=process%20stability" title=" process stability"> process stability</a>, <a href="https://publications.waset.org/abstracts/search?q=material%20removal" title=" material removal"> material removal</a>, <a href="https://publications.waset.org/abstracts/search?q=milling" title=" milling"> milling</a> </p> <a href="https://publications.waset.org/abstracts/31429/determining-the-width-and-depths-of-cut-in-milling-on-the-basis-of-a-multi-dexel-model" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/31429.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">525</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">5073</span> Effect of Soil Corrosion in Failures of Buried Gas Pipelines</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Saima%20Ali">Saima Ali</a>, <a href="https://publications.waset.org/abstracts/search?q=Pathamanathan%20Rajeev"> Pathamanathan Rajeev</a>, <a href="https://publications.waset.org/abstracts/search?q=Imteaz%20A.%20Monzur"> Imteaz A. Monzur</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, a brief review of the corrosion mechanism in buried pipe and modes of failure is provided together with the available corrosion models. Moreover, the sensitivity analysis is performed to understand the influence of corrosion model parameters on the remaining life estimation. Further, the probabilistic analysis is performed to propagate the uncertainty in the corrosion model on the estimation of the renaming life of the pipe. Finally, the comparison among the corrosion models on the basis of the remaining life estimation will be provided to improve the renewal plan. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=corrosion" title="corrosion">corrosion</a>, <a href="https://publications.waset.org/abstracts/search?q=pit%20depth" title=" pit depth"> pit depth</a>, <a href="https://publications.waset.org/abstracts/search?q=sensitivity%20analysis" title=" sensitivity analysis"> sensitivity analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=exposure%20period" title=" exposure period"> exposure period</a> </p> <a href="https://publications.waset.org/abstracts/28777/effect-of-soil-corrosion-in-failures-of-buried-gas-pipelines" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/28777.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">530</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">5072</span> A Transformer-Based Approach for Multi-Human 3D Pose Estimation Using Color and Depth Images</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Qiang%20Wang">Qiang Wang</a>, <a href="https://publications.waset.org/abstracts/search?q=Hongyang%20Yu"> Hongyang Yu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Multi-human 3D pose estimation is a challenging task in computer vision, which aims to recover the 3D joint locations of multiple people from multi-view images. In contrast to traditional methods, which typically only use color (RGB) images as input, our approach utilizes both color and depth (D) information contained in RGB-D images. We also employ a transformer-based model as the backbone of our approach, which is able to capture long-range dependencies and has been shown to perform well on various sequence modeling tasks. Our method is trained and tested on the Carnegie Mellon University (CMU) Panoptic dataset, which contains a diverse set of indoor and outdoor scenes with multiple people in varying poses and clothing. We evaluate the performance of our model on the standard 3D pose estimation metrics of mean per-joint position error (MPJPE). Our results show that the transformer-based approach outperforms traditional methods and achieves competitive results on the CMU Panoptic dataset. We also perform an ablation study to understand the impact of different design choices on the overall performance of the model. In summary, our work demonstrates the effectiveness of using a transformer-based approach with RGB-D images for multi-human 3D pose estimation and has potential applications in real-world scenarios such as human-computer interaction, robotics, and augmented reality. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=multi-human%203D%20pose%20estimation" title="multi-human 3D pose estimation">multi-human 3D pose estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=RGB-D%20images" title=" RGB-D images"> RGB-D images</a>, <a href="https://publications.waset.org/abstracts/search?q=transformer" title=" transformer"> transformer</a>, <a href="https://publications.waset.org/abstracts/search?q=3D%20joint%20locations" title=" 3D joint locations"> 3D joint locations</a> </p> <a href="https://publications.waset.org/abstracts/162957/a-transformer-based-approach-for-multi-human-3d-pose-estimation-using-color-and-depth-images" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/162957.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">80</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">5071</span> Estimations of Spectral Dependence of Tropospheric Aerosol Single Scattering Albedo in Sukhothai, Thailand</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Siriluk%20Ruangrungrote">Siriluk Ruangrungrote</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Analyses of available data from MFR-7 measurement were performed and discussed on the study of tropospheric aerosol and its consequence in Thailand. Since, ASSA (w) is one of the most important parameters for a determination of aerosol effect on radioactive forcing. Here the estimation of w was directly determined in terms of the ratio of aerosol scattering optical depth to aerosol extinction optical depth (ωscat/ωext) without any utilization of aerosol computer code models. This is of benefit for providing the elimination of uncertainty causing by the modeling assumptions and the estimation of actual aerosol input data. Diurnal w of 5 cloudless-days in winter and early summer at 5 distinct wavelengths of 415, 500, 615, 673 and 870 nm with the consideration of Rayleigh scattering and atmospheric column NO2 and Ozone contents were investigated, respectively. Besides, the tendency of spectral dependence of ω representing two seasons was observed. The characteristic of spectral results reveals that during wintertime the atmosphere of the inland rural vicinity for the period of measurement possibly dominated with a lesser amount of soil dust aerosols loading than one in early summer. Hence, the major aerosol loading particularly in summer was subject to a mixture of both soil dust and biomass burning aerosols. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=aerosol%20scattering%20optical%20depth" title="aerosol scattering optical depth">aerosol scattering optical depth</a>, <a href="https://publications.waset.org/abstracts/search?q=aerosol%20extinction%20optical%20depth" title=" aerosol extinction optical depth"> aerosol extinction optical depth</a>, <a href="https://publications.waset.org/abstracts/search?q=biomass%20burning%20aerosol" title=" biomass burning aerosol"> biomass burning aerosol</a>, <a href="https://publications.waset.org/abstracts/search?q=soil%20dust%20aerosol" title=" soil dust aerosol"> soil dust aerosol</a> </p> <a href="https://publications.waset.org/abstracts/38336/estimations-of-spectral-dependence-of-tropospheric-aerosol-single-scattering-albedo-in-sukhothai-thailand" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/38336.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">405</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">5070</span> GIS Application in Surface Runoff Estimation for Upper Klang River Basin, Malaysia</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Suzana%20Ramli">Suzana Ramli</a>, <a href="https://publications.waset.org/abstracts/search?q=Wardah%20Tahir"> Wardah Tahir</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Estimation of surface runoff depth is a vital part in any rainfall-runoff modeling. It leads to stream flow calculation and later predicts flood occurrences. GIS (Geographic Information System) is an advanced and opposite tool used in simulating hydrological model due to its realistic application on topography. The paper discusses on calculation of surface runoff depth for two selected events by using GIS with Curve Number method for Upper Klang River basin. GIS enables maps intersection between soil type and land use that later produces curve number map. The results show good correlation between simulated and observed values with more than 0.7 of R2. Acceptable performance of statistical measurements namely mean error, absolute mean error, RMSE, and bias are also deduced in the paper. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=surface%20runoff" title="surface runoff">surface runoff</a>, <a href="https://publications.waset.org/abstracts/search?q=geographic%20information%20system" title=" geographic information system"> geographic information system</a>, <a href="https://publications.waset.org/abstracts/search?q=curve%20number%20method" title=" curve number method"> curve number method</a>, <a href="https://publications.waset.org/abstracts/search?q=environment" title=" environment"> environment</a> </p> <a href="https://publications.waset.org/abstracts/4351/gis-application-in-surface-runoff-estimation-for-upper-klang-river-basin-malaysia" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/4351.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">282</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">5069</span> Simulation of 3-D Direction-of-Arrival Estimation Using MUSIC Algorithm</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Duckyong%20Kim">Duckyong Kim</a>, <a href="https://publications.waset.org/abstracts/search?q=Jong%20Kang%20Park"> Jong Kang Park</a>, <a href="https://publications.waset.org/abstracts/search?q=Jong%20Tae%20Kim"> Jong Tae Kim</a> </p> <p class="card-text"><strong>Abstract:</strong></p> DOA (Direction of Arrival) estimation is an important method in array signal processing and has a wide range of applications such as direction finding, beam forming, and so on. In this paper, we briefly introduce the MUSIC (Multiple Signal Classification) Algorithm, one of DOA estimation methods for analyzing several targets. Then we apply the MUSIC algorithm to the two-dimensional antenna array to analyze DOA estimation in 3D space through MATLAB simulation. We also analyze the design factors that can affect the accuracy of DOA estimation through simulation, and proceed with further consideration on how to apply the system. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=DOA%20estimation" title="DOA estimation">DOA estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=MUSIC%20algorithm" title=" MUSIC algorithm"> MUSIC algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=spatial%20spectrum" title=" spatial spectrum"> spatial spectrum</a>, <a href="https://publications.waset.org/abstracts/search?q=array%20signal%20processing" title=" array signal processing"> array signal processing</a> </p> <a href="https://publications.waset.org/abstracts/88658/simulation-of-3-d-direction-of-arrival-estimation-using-music-algorithm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/88658.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">379</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">5068</span> A Comprehensive Approach to Scour Depth Estimation Through HEC-RAS 2D and Physical Modeling</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ashvinie%20Thembiliyagoda">Ashvinie Thembiliyagoda</a>, <a href="https://publications.waset.org/abstracts/search?q=Kasun%20De%20Silva"> Kasun De Silva</a>, <a href="https://publications.waset.org/abstracts/search?q=Nimal%20Wijayaratna"> Nimal Wijayaratna</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The lowering of the riverbed level as a result of water erosion is termed as scouring. This phenomenon remarkably undermines the potential stability of the bridge pier, causing a threat of failure or collapse. The formation of vortices in the vicinity of bridges due to the obstruction caused by river flow is the main reason behind this pursuit. Scouring is aggravated by factors including high flow rates, bridge pier geometry, sediment configuration etc. Tackling scour-related problems when they become severe is more costly and disruptive compared to implementing preventive measures based on predicted scour depths. This paper presents a comprehensive investigation of the development of a numerical model that could reproduce the scouring effect around bridge piers and estimate the scour depth. The numerical model was developed for one selected bridge in Sri Lanka, the Kelanisiri Bridge. HEC-RAS two-dimensional (2D) modeling approach was utilized for the development of the model and was calibrated and validated with field data. To further enhance the reliability of the model, a physical model was developed, allowing for additional validation. Results from the numerical model were compared with those obtained from the physical model, revealing a strong correlation between the two methods and confirming the numerical model's accuracy in predicting scour depths. The findings from this study underscore the ability of the HEC-RAS two-dimensional modeling approach for the estimation of scour depth around bridge piers. The developed model is able to estimate the scour depth under varying flow conditions, and its flexibility allows it to be adapted for application to other bridges with similar hydraulic and geomorphological conditions, providing a robust tool for widespread use in scour estimation. The developed two-dimensional model not only offers reliable predictions for the case study bridge but also holds significant potential for broader implementation, contributing to the improved design and maintenance of bridge structures in diverse environments. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=piers" title="piers">piers</a>, <a href="https://publications.waset.org/abstracts/search?q=scouring" title=" scouring"> scouring</a>, <a href="https://publications.waset.org/abstracts/search?q=HEC-RAS" title=" HEC-RAS"> HEC-RAS</a>, <a href="https://publications.waset.org/abstracts/search?q=physical%20model" title=" physical model"> physical model</a> </p> <a href="https://publications.waset.org/abstracts/193088/a-comprehensive-approach-to-scour-depth-estimation-through-hec-ras-2d-and-physical-modeling" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/193088.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">15</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">5067</span> Lithium-Ion Battery State of Charge Estimation Using One State Hysteresis Model with Nonlinear Estimation Strategies</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mohammed%20Farag">Mohammed Farag</a>, <a href="https://publications.waset.org/abstracts/search?q=Mina%20Attari"> Mina Attari</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20Andrew%20Gadsden"> S. Andrew Gadsden</a>, <a href="https://publications.waset.org/abstracts/search?q=Saeid%20R.%20Habibi"> Saeid R. Habibi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Battery state of charge (SOC) estimation is an important parameter as it measures the total amount of electrical energy stored at a current time. The SOC percentage acts as a fuel gauge if it is compared with a conventional vehicle. Estimating the SOC is, therefore, essential for monitoring the amount of useful life remaining in the battery system. This paper looks at the implementation of three nonlinear estimation strategies for Li-Ion battery SOC estimation. One of the most common behavioral battery models is the one state hysteresis (OSH) model. The extended Kalman filter (EKF), the smooth variable structure filter (SVSF), and the time-varying smoothing boundary layer SVSF are applied on this model, and the results are compared. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=state%20of%20charge%20estimation" title="state of charge estimation">state of charge estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=battery%20modeling" title=" battery modeling"> battery modeling</a>, <a href="https://publications.waset.org/abstracts/search?q=one-state%20hysteresis" title=" one-state hysteresis"> one-state hysteresis</a>, <a href="https://publications.waset.org/abstracts/search?q=filtering%20and%20estimation" title=" filtering and estimation"> filtering and estimation</a> </p> <a href="https://publications.waset.org/abstracts/68017/lithium-ion-battery-state-of-charge-estimation-using-one-state-hysteresis-model-with-nonlinear-estimation-strategies" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/68017.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">444</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">5066</span> Hybrid Deep Learning and FAST-BRISK 3D Object Detection Technique for Bin-Picking Application</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Thanakrit%20Taweesoontorn">Thanakrit Taweesoontorn</a>, <a href="https://publications.waset.org/abstracts/search?q=Sarucha%20Yanyong"> Sarucha Yanyong</a>, <a href="https://publications.waset.org/abstracts/search?q=Poom%20Konghuayrob"> Poom Konghuayrob</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Robotic arms have gained popularity in various industries due to their accuracy and efficiency. This research proposes a method for bin-picking tasks using the Cobot, combining the YOLOv5 CNNs model for object detection and pose estimation with traditional feature detection (FAST), feature description (BRISK), and matching algorithms. By integrating these algorithms and utilizing a small-scale depth sensor camera for capturing depth and color images, the system achieves real-time object detection and accurate pose estimation, enabling the robotic arm to pick objects correctly in both position and orientation. Furthermore, the proposed method is implemented within the ROS framework to provide a seamless platform for robotic control and integration. This integration of robotics, cameras, and AI technology contributes to the development of industrial robotics, opening up new possibilities for automating challenging tasks and improving overall operational efficiency. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=robotic%20vision" title="robotic vision">robotic vision</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20processing" title=" image processing"> image processing</a>, <a href="https://publications.waset.org/abstracts/search?q=applications%20of%20robotics" title=" applications of robotics"> applications of robotics</a>, <a href="https://publications.waset.org/abstracts/search?q=artificial%20intelligent" title=" artificial intelligent"> artificial intelligent</a> </p> <a href="https://publications.waset.org/abstracts/176550/hybrid-deep-learning-and-fast-brisk-3d-object-detection-technique-for-bin-picking-application" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/176550.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">97</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">5065</span> Three-Dimensional CFD Modeling of Flow Field and Scouring around Bridge Piers</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=P.%20Deepak%20Kumar">P. Deepak Kumar</a>, <a href="https://publications.waset.org/abstracts/search?q=P.%20R.%20Maiti"> P. R. Maiti</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In recent years, sediment scour near bridge piers and abutment is a serious problem which causes nationwide concern because it has resulted in more bridge failures than other causes. Scour is the formation of scour hole around the structure mounted on and embedded in erodible channel bed due to the erosion of soil by flowing water. The formation of scour hole around the structures depends upon shape and size of the pier, depth of flow as well as angle of attack of flow and sediment characteristics. The flow characteristics around these structures change due to man-made obstruction in the natural flow path which changes the kinetic energy of the flow around these structures. Excessive scour affects the stability of the foundation of the structure by the removal of the bed material. The accurate estimation of scour depth around bridge pier is very difficult. The foundation of bridge piers have to be taken deeper and to provide sufficient anchorage length required for stability of the foundation. In this study, computational model simulations using a 3D Computational Fluid Dynamics (CFD) model were conducted to examine the mechanism of scour around a cylindrical pier. Subsequently, the flow characteristics around these structures are presented for different flow conditions. Mechanism of scouring phenomenon, the formation of vortex and its consequent effect is discussed for a straight channel. Effort was made towards estimation of scour depth around bridge piers under different flow conditions. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=bridge%20pier" title="bridge pier">bridge pier</a>, <a href="https://publications.waset.org/abstracts/search?q=computational%20fluid%20dynamics" title=" computational fluid dynamics"> computational fluid dynamics</a>, <a href="https://publications.waset.org/abstracts/search?q=multigrid" title=" multigrid"> multigrid</a>, <a href="https://publications.waset.org/abstracts/search?q=pier%20shape" title=" pier shape"> pier shape</a>, <a href="https://publications.waset.org/abstracts/search?q=scour" title=" scour"> scour</a> </p> <a href="https://publications.waset.org/abstracts/47338/three-dimensional-cfd-modeling-of-flow-field-and-scouring-around-bridge-piers" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/47338.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">296</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">5064</span> Frequency Offset Estimation Schemes Based on ML for OFDM Systems in Non-Gaussian Noise Environments</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Keunhong%20Chae">Keunhong Chae</a>, <a href="https://publications.waset.org/abstracts/search?q=Seokho%20Yoon"> Seokho Yoon</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, frequency offset (FO) estimation schemes robust to the non-Gaussian noise environments are proposed for orthogonal frequency division multiplexing (OFDM) systems. First, a maximum-likelihood (ML) estimation scheme in non-Gaussian noise environments is proposed, and then, the complexity of the ML estimation scheme is reduced by employing a reduced set of candidate values. In numerical results, it is demonstrated that the proposed schemes provide a significant performance improvement over the conventional estimation scheme in non-Gaussian noise environments while maintaining the performance similar to the estimation performance in Gaussian noise environments. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=frequency%20offset%20estimation" title="frequency offset estimation">frequency offset estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=maximum-likelihood" title=" maximum-likelihood"> maximum-likelihood</a>, <a href="https://publications.waset.org/abstracts/search?q=non-Gaussian%20noise%0D%0Aenvironment" title=" non-Gaussian noise environment"> non-Gaussian noise environment</a>, <a href="https://publications.waset.org/abstracts/search?q=OFDM" title=" OFDM"> OFDM</a>, <a href="https://publications.waset.org/abstracts/search?q=training%20symbol" title=" training symbol"> training symbol</a> </p> <a href="https://publications.waset.org/abstracts/9430/frequency-offset-estimation-schemes-based-on-ml-for-ofdm-systems-in-non-gaussian-noise-environments" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/9430.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">353</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">5063</span> Parameters Estimation of Multidimensional Possibility Distributions</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sergey%20Sorokin">Sergey Sorokin</a>, <a href="https://publications.waset.org/abstracts/search?q=Irina%20Sorokina"> Irina Sorokina</a>, <a href="https://publications.waset.org/abstracts/search?q=Alexander%20Yazenin"> Alexander Yazenin</a> </p> <p class="card-text"><strong>Abstract:</strong></p> We present a solution to the Maxmin u/E parameters estimation problem of possibility distributions in m-dimensional case. Our method is based on geometrical approach, where minimal area enclosing ellipsoid is constructed around the sample. Also we demonstrate that one can improve results of well-known algorithms in fuzzy model identification task using Maxmin u/E parameters estimation. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=possibility%20distribution" title="possibility distribution">possibility distribution</a>, <a href="https://publications.waset.org/abstracts/search?q=parameters%20estimation" title=" parameters estimation"> parameters estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=Maxmin%20u%5CE%20estimator" title=" Maxmin u\E estimator"> Maxmin u\E estimator</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20model%20identification" title=" fuzzy model identification"> fuzzy model identification</a> </p> <a href="https://publications.waset.org/abstracts/16751/parameters-estimation-of-multidimensional-possibility-distributions" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/16751.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">470</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">5062</span> Biomass and CPUA Estimation and Distribution Pattern of Saurida Tumbil in the Northwest of Persian Gulf</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Negar%20Ghotbeddin">Negar Ghotbeddin</a>, <a href="https://publications.waset.org/abstracts/search?q=Izadpanah%20Zeinab"> Izadpanah Zeinab</a>, <a href="https://publications.waset.org/abstracts/search?q=Tooraj%20Valinassab"> Tooraj Valinassab</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohammad%20Azhir"> Mohammad Azhir</a> </p> <p class="card-text"><strong>Abstract:</strong></p> It is reported on results of a trawls survey in 2011 to assess the amount of biomass and Catch Per Unit of Area (CPUA) and also to determine the distribution pattern of Synodonidae family of demersal fishes (with emphasize on great lizardfish, Saurida tumbil) as one the most important and commercial fish species in the northwest of Persian Gulf. Samples were collected at a total 65 trawl stations selected a stratified random procedure. The study area was stratified to five strata (A to E) covering the depth layers of 10-20, 20-30 and 30-50 m. The catch rates of CPUA and biomass of lizardfishes were estimated to be approximately 316.20 kg/nm2, and 2902.1 tons, respectively. The highest value of biomass of Synodontids was recorded in the east of the study area, Bordkhoon to Dayer (stratum D & E, approximately 1310.6 tonnes) and in depth layer of 30-50 m; and the lowest value was estimated for stratum A (West of Khuzestan Province) and in depth layer of 10-20 m. On the other hand, the highest CPUA was recorded in stratum D and depth layer of 20-30 m; and the lowest value for stratum A and 10-20 m depth. It was concluded that stratum D (namely from Bordkhoon to Dayer) contains the best fishing area from the point of higher density and distribution of Synodontidae in the covering area, and from the point of depth distribution, they are found in depths more than 30 m. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Saurida%20tumbil" title="Saurida tumbil">Saurida tumbil</a>, <a href="https://publications.waset.org/abstracts/search?q=CPUA" title=" CPUA"> CPUA</a>, <a href="https://publications.waset.org/abstracts/search?q=biomass" title=" biomass"> biomass</a>, <a href="https://publications.waset.org/abstracts/search?q=distribution" title=" distribution"> distribution</a>, <a href="https://publications.waset.org/abstracts/search?q=fishing%20area" title=" fishing area"> fishing area</a>, <a href="https://publications.waset.org/abstracts/search?q=Persian%20gulf" title=" Persian gulf"> Persian gulf</a> </p> <a href="https://publications.waset.org/abstracts/41009/biomass-and-cpua-estimation-and-distribution-pattern-of-saurida-tumbil-in-the-northwest-of-persian-gulf" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/41009.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">406</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">5061</span> A Packet Loss Probability Estimation Filter Using Most Recent Finite Traffic Measurements</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>, <a href="https://publications.waset.org/abstracts/search?q=Eung%20Hyuk%20Lee"> Eung Hyuk Lee</a>, <a href="https://publications.waset.org/abstracts/search?q=Mun%20Suck%20Jang"> Mun Suck Jang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A packet loss probability (PLP) estimation filter with finite memory structure is proposed to estimate the packet rate mean and variance of the input traffic process in real-time while removing undesired system and measurement noises. The proposed PLP estimation filter is developed under a weighted least square criterion using only the finite traffic measurements on the most recent window. The proposed PLP estimation filter is shown to have several inherent properties such as unbiasedness, deadbeat, robustness. A guideline for choosing appropriate window length is described since it can affect significantly the estimation performance. Using computer simulations, the proposed PLP estimation filter is shown to be superior to the Kalman filter for the temporarily uncertain system. One possible explanation for this is that the proposed PLP estimation filter can have greater convergence time of a filtered estimate as the window length M decreases. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=packet%20loss%20probability%20estimation" title="packet loss probability estimation">packet loss probability estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=finite%20memory%20filter" title=" finite memory filter"> finite memory filter</a>, <a href="https://publications.waset.org/abstracts/search?q=infinite%20memory%20filter" title=" infinite memory filter"> infinite memory filter</a>, <a href="https://publications.waset.org/abstracts/search?q=Kalman%20filter" title=" Kalman filter"> Kalman filter</a> </p> <a href="https://publications.waset.org/abstracts/9519/a-packet-loss-probability-estimation-filter-using-most-recent-finite-traffic-measurements" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/9519.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">674</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">5060</span> Numerical Modeling of the Depth-Averaged Flow over a Hill</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Anna%20Avramenko">Anna Avramenko</a>, <a href="https://publications.waset.org/abstracts/search?q=Heikki%20Haario"> Heikki Haario</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper reports the development and application of a 2D depth-averaged model. The main goal of this contribution is to apply the depth averaged equations to a wind park model in which the treatment of the geometry, introduced on the mathematical model by the mass and momentum source terms. The depth-averaged model will be used in future to find the optimal position of wind turbines in the wind park. K-E and 2D LES turbulence models were consider in this article. 2D CFD simulations for one hill was done to check the depth-averaged model in practise. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=depth-averaged%20equations" title="depth-averaged equations">depth-averaged equations</a>, <a href="https://publications.waset.org/abstracts/search?q=numerical%20modeling" title=" numerical modeling"> numerical modeling</a>, <a href="https://publications.waset.org/abstracts/search?q=CFD" title=" CFD"> CFD</a>, <a href="https://publications.waset.org/abstracts/search?q=wind%20park%20model" title=" wind park model"> wind park model</a> </p> <a href="https://publications.waset.org/abstracts/21445/numerical-modeling-of-the-depth-averaged-flow-over-a-hill" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/21445.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">603</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">5059</span> RGB-D SLAM Algorithm Based on pixel level Dense Depth Map</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hao%20Zhang">Hao Zhang</a>, <a href="https://publications.waset.org/abstracts/search?q=Hongyang%20Yu"> Hongyang Yu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Scale uncertainty is a well-known challenging problem in visual SLAM. Because RGB-D sensor provides depth information, RGB-D SLAM improves this scale uncertainty problem. However, due to the limitation of physical hardware, the depth map output by RGB-D sensor usually contains a large area of missing depth values. These missing depth information affect the accuracy and robustness of RGB-D SLAM. In order to reduce these effects, this paper completes the missing area of the depth map output by RGB-D sensor and then fuses the completed dense depth map into ORB SLAM2. By adding the process of obtaining pixel-level dense depth maps, a better RGB-D visual SLAM algorithm is finally obtained. In the process of obtaining dense depth maps, a deep learning model of indoor scenes is adopted. Experiments are conducted on public datasets and real-world environments of indoor scenes. Experimental results show that the proposed SLAM algorithm has better robustness than ORB SLAM2. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=RGB-D" title="RGB-D">RGB-D</a>, <a href="https://publications.waset.org/abstracts/search?q=SLAM" title=" SLAM"> SLAM</a>, <a href="https://publications.waset.org/abstracts/search?q=dense%20depth" title=" dense depth"> dense depth</a>, <a href="https://publications.waset.org/abstracts/search?q=depth%20map" title=" depth map"> depth map</a> </p> <a href="https://publications.waset.org/abstracts/147802/rgb-d-slam-algorithm-based-on-pixel-level-dense-depth-map" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/147802.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">140</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">5058</span> Time Delay Estimation Using Signal Envelopes for Synchronisation of Recordings</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sergei%20Aleinik">Sergei Aleinik</a>, <a href="https://publications.waset.org/abstracts/search?q=Mikhail%20Stolbov"> Mikhail Stolbov</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this work, a method of time delay estimation for dual-channel acoustic signals (speech, music, etc.) recorded under reverberant conditions is investigated. Standard methods based on cross-correlation of the signals show poor results in cases involving strong reverberation, large distances between microphones and asynchronous recordings. Under similar conditions, a method based on cross-correlation of temporal envelopes of the signals delivers a delay estimation of acceptable quality. This method and its properties are described and investigated in detail, including its limits of applicability. The method’s optimal parameter estimation and a comparison with other known methods of time delay estimation are also provided. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=cross-correlation" title="cross-correlation">cross-correlation</a>, <a href="https://publications.waset.org/abstracts/search?q=delay%20estimation" title=" delay estimation"> delay estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=signal%20envelope" title=" signal envelope"> signal envelope</a>, <a href="https://publications.waset.org/abstracts/search?q=signal%20processing" title=" signal processing"> signal processing</a> </p> <a href="https://publications.waset.org/abstracts/2280/time-delay-estimation-using-signal-envelopes-for-synchronisation-of-recordings" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/2280.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">485</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">5057</span> VaR Estimation Using the Informational Content of Futures Traded Volume</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Amel%20Oueslati">Amel Oueslati</a>, <a href="https://publications.waset.org/abstracts/search?q=Olfa%20Benouda"> Olfa Benouda</a> </p> <p class="card-text"><strong>Abstract:</strong></p> New Value at Risk (VaR) estimation is proposed and investigated. The well-known two stages Garch-EVT approach uses conditional volatility to generate one step ahead forecasts of VaR. With daily data for twelve stocks that decompose the Dow Jones Industrial Average (DJIA) index, this paper incorporates the volume in the first stage volatility estimation. Afterwards, the forecasting ability of this conditional volatility concerning the VaR estimation is compared to that of a basic volatility model without considering any trading component. The results are significant and bring out the importance of the trading volume in the VaR measure. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Garch-EVT" title="Garch-EVT">Garch-EVT</a>, <a href="https://publications.waset.org/abstracts/search?q=value%20at%20risk" title=" value at risk"> value at risk</a>, <a href="https://publications.waset.org/abstracts/search?q=volume" title=" volume"> volume</a>, <a href="https://publications.waset.org/abstracts/search?q=volatility" title=" volatility"> volatility</a> </p> <a href="https://publications.waset.org/abstracts/56021/var-estimation-using-the-informational-content-of-futures-traded-volume" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/56021.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">285</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">5056</span> Multiple Linear Regression for Rapid Estimation of Subsurface Resistivity from Apparent Resistivity Measurements</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sabiu%20Bala%20Muhammad">Sabiu Bala Muhammad</a>, <a href="https://publications.waset.org/abstracts/search?q=Rosli%20Saad"> Rosli Saad</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Multiple linear regression (MLR) models for fast estimation of true subsurface resistivity from apparent resistivity field measurements are developed and assessed in this study. The parameters investigated were apparent resistivity (ρₐ), horizontal location (X) and depth (Z) of measurement as the independent variables; and true resistivity (ρₜ) as the dependent variable. To achieve linearity in both resistivity variables, datasets were first transformed into logarithmic domain following diagnostic checks of normality of the dependent variable and heteroscedasticity to ensure accurate models. Four MLR models were developed based on hierarchical combination of the independent variables. The generated MLR coefficients were applied to another data set to estimate ρₜ values for validation. Contours of the estimated ρₜ values were plotted and compared to the observed data plots at the colour scale and blanking for visual assessment. The accuracy of the models was assessed using coefficient of determination (R²), standard error (SE) and weighted mean absolute percentage error (wMAPE). It is concluded that the MLR models can estimate ρₜ for with high level of accuracy. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=apparent%20resistivity" title="apparent resistivity">apparent resistivity</a>, <a href="https://publications.waset.org/abstracts/search?q=depth" title=" depth"> depth</a>, <a href="https://publications.waset.org/abstracts/search?q=horizontal%20location" title=" horizontal location"> horizontal location</a>, <a href="https://publications.waset.org/abstracts/search?q=multiple%20linear%20regression" title=" multiple linear regression"> multiple linear regression</a>, <a href="https://publications.waset.org/abstracts/search?q=true%20resistivity" title=" true resistivity"> true resistivity</a> </p> <a href="https://publications.waset.org/abstracts/70171/multiple-linear-regression-for-rapid-estimation-of-subsurface-resistivity-from-apparent-resistivity-measurements" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/70171.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">276</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">5055</span> Parameter Estimation of Induction Motors by PSO Algorithm</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=A.%20Mohammadi">A. Mohammadi</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20Asghari"> S. Asghari</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20Aien"> M. Aien</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20Rashidinejad"> M. Rashidinejad</a> </p> <p class="card-text"><strong>Abstract:</strong></p> After emergent of alternative current networks and their popularity, asynchronous motors became more widespread than other kinds of industrial motors. In order to control and run these motors efficiently, an accurate estimation of motor parameters is needed. There are different methods to obtain these parameters such as rotor locked test, no load test, DC test, analytical methods, and so on. The most common drawback of these methods is their inaccuracy in estimation of some motor parameters. In order to remove this concern, a novel method for parameter estimation of induction motors using particle swarm optimization (PSO) algorithm is proposed. In the proposed method, transient state of motor is used for parameter estimation. Comparison of the simulation results purtuined to the PSO algorithm with other available methods justifies the effectiveness of the proposed method. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=induction%20motor" title="induction motor">induction motor</a>, <a href="https://publications.waset.org/abstracts/search?q=motor%20parameter%20estimation" title=" motor parameter estimation"> motor parameter estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=PSO%20algorithm" title=" PSO algorithm"> PSO algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=analytical%20method" title=" analytical method"> analytical method</a> </p> <a href="https://publications.waset.org/abstracts/15433/parameter-estimation-of-induction-motors-by-pso-algorithm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/15433.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">633</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">5054</span> Online Pose Estimation and Tracking Approach with Siamese Region Proposal Network</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Cheng%20Fang">Cheng Fang</a>, <a href="https://publications.waset.org/abstracts/search?q=Lingwei%20Quan"> Lingwei Quan</a>, <a href="https://publications.waset.org/abstracts/search?q=Cunyue%20Lu"> Cunyue Lu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Human pose estimation and tracking are to accurately identify and locate the positions of human joints in the video. It is a computer vision task which is of great significance for human motion recognition, behavior understanding and scene analysis. There has been remarkable progress on human pose estimation in recent years. However, more researches are needed for human pose tracking especially for online tracking. In this paper, a framework, called PoseSRPN, is proposed for online single-person pose estimation and tracking. We use Siamese network attaching a pose estimation branch to incorporate Single-person Pose Tracking (SPT) and Visual Object Tracking (VOT) into one framework. The pose estimation branch has a simple network structure that replaces the complex upsampling and convolution network structure with deconvolution. By augmenting the loss of fully convolutional Siamese network with the pose estimation task, pose estimation and tracking can be trained in one stage. Once trained, PoseSRPN only relies on a single bounding box initialization and producing human joints location. The experimental results show that while maintaining the good accuracy of pose estimation on COCO and PoseTrack datasets, the proposed method achieves a speed of 59 frame/s, which is superior to other pose tracking frameworks. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=computer%20vision" title="computer vision">computer vision</a>, <a href="https://publications.waset.org/abstracts/search?q=pose%20estimation" title=" pose estimation"> pose estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=pose%20tracking" title=" pose tracking"> pose tracking</a>, <a href="https://publications.waset.org/abstracts/search?q=Siamese%20network" title=" Siamese network"> Siamese network</a> </p> <a href="https://publications.waset.org/abstracts/112839/online-pose-estimation-and-tracking-approach-with-siamese-region-proposal-network" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/112839.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">153</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">5053</span> Analytical Solution for End Depth Ratio in Rectangular Channels</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Abdulrahman%20Abdulrahman">Abdulrahman Abdulrahman</a>, <a href="https://publications.waset.org/abstracts/search?q=Abir%20Abdulrahman"> Abir Abdulrahman</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Free over-fall is an instrument for measuring discharge in open channels by measuring end depth. A comprehensive researchers investigated theoretically and experimentally brink phenomenon with various approaches for different cross-sectional shapes. Anderson's method, based on Boussinq's approximation and energy approach was used to derive a pressure distribution factor at end depth. Applying the one-dimensional momentum equation and the principles of limit slope analysis, a relevant analytical solution may be derived for brink depth ratio (EDR) in prismatic rectangular channel. Also relationships between end depth ratio and slope ratio for a given non-dimensional normal or critical depth with upstream supercritical flow regime are presented. Simple indirect procedure is used to estimate the end depth discharge ratio (EDD) for subcritical and supercritical flow using measured end depth. The comparison of this analysis with all previous theoretical and experimental studies showed an excellent agreement. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=analytical%20solution" title="analytical solution">analytical solution</a>, <a href="https://publications.waset.org/abstracts/search?q=brink%20depth" title=" brink depth"> brink depth</a>, <a href="https://publications.waset.org/abstracts/search?q=end%20depth" title=" end depth"> end depth</a>, <a href="https://publications.waset.org/abstracts/search?q=flow%20measurement" title=" flow measurement"> flow measurement</a>, <a href="https://publications.waset.org/abstracts/search?q=free%20over%20fall" title=" free over fall"> free over fall</a>, <a href="https://publications.waset.org/abstracts/search?q=hydraulics" title=" hydraulics"> hydraulics</a>, <a href="https://publications.waset.org/abstracts/search?q=rectangular%20channel" title=" rectangular channel"> rectangular channel</a> </p> <a href="https://publications.waset.org/abstracts/92286/analytical-solution-for-end-depth-ratio-in-rectangular-channels" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/92286.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">181</span> </span> </div> </div> <ul class="pagination"> <li class="page-item disabled"><span class="page-link">&lsaquo;</span></li> <li class="page-item active"><span class="page-link">1</span></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=Depth%20estimation&page=2">2</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=Depth%20estimation&page=3">3</a></li> <li class="page-item"><a class="page-link" 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