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Adversarial Network</title> <meta name="description" content="Search results for: Generative Adversarial Network"> <meta name="keywords" content="Generative Adversarial Network"> <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> 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action="https://publications.waset.org/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="Generative Adversarial Network"> <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> 2786</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: Generative Adversarial Network</h1> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2786</span> Semi-Supervised Outlier Detection Using a Generative and Adversary Framework</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Jindong%20Gu">Jindong Gu</a>, <a href="https://publications.waset.org/search?q=Matthias%20Schubert"> Matthias Schubert</a>, <a href="https://publications.waset.org/search?q=Volker%20Tresp"> Volker Tresp</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In many outlier detection tasks, only training data belonging to one class, i.e., the positive class, is available. The task is then to predict a new data point as belonging either to the positive class or to the negative class, in which case the data point is considered an outlier. For this task, we propose a novel corrupted Generative Adversarial Network (CorGAN). In the adversarial process of training CorGAN, the Generator generates outlier samples for the negative class, and the Discriminator is trained to distinguish the positive training data from the generated negative data. The proposed framework is evaluated using an image dataset and a real-world network intrusion dataset. Our outlier-detection method achieves state-of-the-art performance on both tasks. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Outlier%20detection" title="Outlier detection">Outlier detection</a>, <a href="https://publications.waset.org/search?q=generative%20adversary%20networks" title=" generative adversary networks"> generative adversary networks</a>, <a href="https://publications.waset.org/search?q=semi-supervised%20learning." title=" semi-supervised learning."> semi-supervised learning.</a> </p> <a href="https://publications.waset.org/10009674/semi-supervised-outlier-detection-using-a-generative-and-adversary-framework" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/10009674/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/10009674/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/10009674/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/10009674/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/10009674/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/10009674/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/10009674/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/10009674/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/10009674/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/10009674/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/10009674.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">1074</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2785</span> Time Series Simulation by Conditional Generative Adversarial Net</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Rao%20Fu">Rao Fu</a>, <a href="https://publications.waset.org/search?q=Jie%20Chen"> Jie Chen</a>, <a href="https://publications.waset.org/search?q=Shutian%20Zeng"> Shutian Zeng</a>, <a href="https://publications.waset.org/search?q=Yiping%20Zhuang"> Yiping Zhuang</a>, <a href="https://publications.waset.org/search?q=Agus%20Sudjianto"> Agus Sudjianto</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>Generative Adversarial Net (GAN) has proved to be a powerful machine learning tool in image data analysis and generation. In this paper, we propose to use Conditional Generative Adversarial Net (CGAN) to learn and simulate time series data. The conditions include both categorical and continuous variables with different auxiliary information. Our simulation studies show that CGAN has the capability to learn different types of normal and heavy-tailed distributions, as well as dependent structures of different time series. It also has the capability to generate conditional predictive distributions consistent with training data distributions. We also provide an in-depth discussion on the rationale behind GAN and the neural networks as hierarchical splines to establish a clear connection with existing statistical methods of distribution generation. In practice, CGAN has a wide range of applications in market risk and counterparty risk analysis: it can be applied to learn historical data and generate scenarios for the calculation of Value-at-Risk (VaR) and Expected Shortfall (ES), and it can also predict the movement of the market risk factors. We present a real data analysis including a backtesting to demonstrate that CGAN can outperform Historical Simulation (HS), a popular method in market risk analysis to calculate VaR. CGAN can also be applied in economic time series modeling and forecasting. In this regard, we have included an example of hypothetical shock analysis for economic models and the generation of potential CCAR scenarios by CGAN at the end of the paper.</p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Conditional%20Generative%20Adversarial%20Net" title="Conditional Generative Adversarial Net">Conditional Generative Adversarial Net</a>, <a href="https://publications.waset.org/search?q=market%20and%20credit%20risk%20management" title=" market and credit risk management"> market and credit risk management</a>, <a href="https://publications.waset.org/search?q=neural%20network" title=" neural network"> neural network</a>, <a href="https://publications.waset.org/search?q=time%20series." title=" time series."> time series.</a> </p> <a href="https://publications.waset.org/10011273/time-series-simulation-by-conditional-generative-adversarial-net" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/10011273/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/10011273/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/10011273/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/10011273/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/10011273/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/10011273/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/10011273/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/10011273/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/10011273/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/10011273/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/10011273.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">1199</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2784</span> An Adversarial Construction of Instability Bounds in LIS Networks</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Dimitrios%20Koukopoulos">Dimitrios Koukopoulos</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this work, we study the impact of dynamically changing link slowdowns on the stability properties of packetswitched networks under the Adversarial Queueing Theory framework. Especially, we consider the Adversarial, Quasi-Static Slowdown Queueing Theory model, where each link slowdown may take on values in the two-valued set of integers {1, D} with D > 1 which remain fixed for a long time, under a (w, ¤ü)-adversary. In this framework, we present an innovative systematic construction for the estimation of adversarial injection rate lower bounds, which, if exceeded, cause instability in networks that use the LIS (Longest-in- System) protocol for contention-resolution. In addition, we show that a network that uses the LIS protocol for contention-resolution may result in dropping its instability bound at injection rates ¤ü > 0 when the network size and the high slowdown D take large values. This is the best ever known instability lower bound for LIS networks. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Network%20stability" title="Network stability">Network stability</a>, <a href="https://publications.waset.org/search?q=quality%20of%20service" title=" quality of service"> quality of service</a>, <a href="https://publications.waset.org/search?q=adversarial%0Aqueueing%20theory" title=" adversarial queueing theory"> adversarial queueing theory</a>, <a href="https://publications.waset.org/search?q=greedy%20scheduling%20protocols." title=" greedy scheduling protocols."> greedy scheduling protocols.</a> </p> <a href="https://publications.waset.org/9398/an-adversarial-construction-of-instability-bounds-in-lis-networks" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/9398/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/9398/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/9398/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/9398/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/9398/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/9398/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/9398/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/9398/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/9398/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/9398/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/9398.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">1229</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2783</span> Adversarial Disentanglement Using Latent Classifier for Pose-Independent Representation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Hamed%20Alqahtani">Hamed Alqahtani</a>, <a href="https://publications.waset.org/search?q=Manolya%20Kavakli-Thorne"> Manolya Kavakli-Thorne</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The large pose discrepancy is one of the critical challenges in face recognition during video surveillance. Due to the entanglement of pose attributes with identity information, the conventional approaches for pose-independent representation lack in providing quality results in recognizing largely posed faces. In this paper, we propose a practical approach to disentangle the pose attribute from the identity information followed by synthesis of a face using a classifier network in latent space. The proposed approach employs a modified generative adversarial network framework consisting of an encoder-decoder structure embedded with a classifier in manifold space for carrying out factorization on the latent encoding. It can be further generalized to other face and non-face attributes for real-life video frames containing faces with significant attribute variations. Experimental results and comparison with state of the art in the field prove that the learned representation of the proposed approach synthesizes more compelling perceptual images through a combination of adversarial and classification losses. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Video%20surveillance" title="Video surveillance">Video surveillance</a>, <a href="https://publications.waset.org/search?q=disentanglement" title=" disentanglement"> disentanglement</a>, <a href="https://publications.waset.org/search?q=face%20detection." title=" face detection."> face detection.</a> </p> <a href="https://publications.waset.org/10010834/adversarial-disentanglement-using-latent-classifier-for-pose-independent-representation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/10010834/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/10010834/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/10010834/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/10010834/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/10010834/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/10010834/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/10010834/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/10010834/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/10010834/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/10010834/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/10010834.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">607</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2782</span> ECG-Based Heartbeat Classification Using Convolutional Neural Networks</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Jacqueline%20R.%20T.%20Alipo-on">Jacqueline R. T. Alipo-on</a>, <a href="https://publications.waset.org/search?q=Francesca%20I.%20F.%20Escobar"> Francesca I. F. Escobar</a>, <a href="https://publications.waset.org/search?q=Myles%20J.%20T.%20Tan"> Myles J. T. Tan</a>, <a href="https://publications.waset.org/search?q=Hezerul%20Abdul%20Karim"> Hezerul Abdul Karim</a>, <a href="https://publications.waset.org/search?q=Nouar%20AlDahoul"> Nouar AlDahoul</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>Electrocardiogram (ECG) signal analysis and processing are crucial in the diagnosis of cardiovascular diseases which are considered as one of the leading causes of mortality worldwide. However, the traditional rule-based analysis of large volumes of ECG data is time-consuming, labor-intensive, and prone to human errors. With the advancement of the programming paradigm, algorithms such as machine learning have been increasingly used to perform an analysis on the ECG signals. In this paper, various deep learning algorithms were adapted to classify five classes of heart beat types. The dataset used in this work is the synthetic MIT-Beth Israel Hospital (MIT-BIH) Arrhythmia dataset produced from generative adversarial networks (GANs). Various deep learning models such as ResNet-50 convolutional neural network (CNN), 1-D CNN, and long short-term memory (LSTM) were evaluated and compared. ResNet-50 was found to outperform other models in terms of recall and F1 score using a five-fold average score of 98.88% and 98.87%, respectively. 1-D CNN, on the other hand, was found to have the highest average precision of 98.93%.</p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Heartbeat%20classification" title="Heartbeat classification">Heartbeat classification</a>, <a href="https://publications.waset.org/search?q=convolutional%20neural%20network" title=" convolutional neural network"> convolutional neural network</a>, <a href="https://publications.waset.org/search?q=electrocardiogram%20signals" title=" electrocardiogram signals"> electrocardiogram signals</a>, <a href="https://publications.waset.org/search?q=ECG%20signals" title=" ECG signals"> ECG signals</a>, <a href="https://publications.waset.org/search?q=generative%20adversarial%20networks" title=" generative adversarial networks"> generative adversarial networks</a>, <a href="https://publications.waset.org/search?q=long%20short-term%20memory" title=" long short-term memory"> long short-term memory</a>, <a href="https://publications.waset.org/search?q=LSTM" title=" LSTM"> LSTM</a>, <a href="https://publications.waset.org/search?q=ResNet-50." title=" ResNet-50."> ResNet-50.</a> </p> <a href="https://publications.waset.org/10013427/ecg-based-heartbeat-classification-using-convolutional-neural-networks" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/10013427/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/10013427/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/10013427/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/10013427/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/10013427/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/10013427/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/10013427/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/10013427/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/10013427/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/10013427/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/10013427.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">188</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2781</span> A Systematic Construction of Instability Bounds in LIS Networks</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Dimitrios%20Koukopoulos">Dimitrios Koukopoulos</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>In this work, we study the impact of dynamically changing link slowdowns on the stability properties of packetswitched networks under the Adversarial Queueing Theory framework. Especially, we consider the Adversarial, Quasi-Static Slowdown Queueing Theory model, where each link slowdown may take on values in the two-valued set of integers {1, D} with D > 1 which remain fixed for a long time, under a (w, <em>p</em>)-adversary. In this framework, we present an innovative systematic construction for the estimation of adversarial injection rate lower bounds, which, if exceeded, cause instability in networks that use the LIS (Longest-in- System) protocol for contention-resolution. In addition, we show that a network that uses the LIS protocol for contention-resolution may result in dropping its instability bound at injection rates <em>p</em> > 0 when the network size and the high slowdown D take large values. This is the best ever known instability lower bound for LIS networks.</p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Parallel%20computing" title="Parallel computing">Parallel computing</a>, <a href="https://publications.waset.org/search?q=network%20stability" title=" network stability"> network stability</a>, <a href="https://publications.waset.org/search?q=adversarial%20queuing%20theory" title=" adversarial queuing theory"> adversarial queuing theory</a>, <a href="https://publications.waset.org/search?q=greedy%20scheduling%20protocols." title=" greedy scheduling protocols."> greedy scheduling protocols.</a> </p> <a href="https://publications.waset.org/3541/a-systematic-construction-of-instability-bounds-in-lis-networks" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/3541/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/3541/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/3541/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/3541/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/3541/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/3541/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/3541/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/3541/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/3541/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/3541/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/3541.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">1415</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2780</span> On Dialogue Systems Based on Deep Learning</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Yifan%20Fan">Yifan Fan</a>, <a href="https://publications.waset.org/search?q=Xudong%20Luo"> Xudong Luo</a>, <a href="https://publications.waset.org/search?q=Pingping%20Lin"> Pingping Lin</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Nowadays, dialogue systems increasingly become the way for humans to access many computer systems. So, humans can interact with computers in natural language. A dialogue system consists of three parts: understanding what humans say in natural language, managing dialogue, and generating responses in natural language. In this paper, we survey deep learning based methods for dialogue management, response generation and dialogue evaluation. Specifically, these methods are based on neural network, long short-term memory network, deep reinforcement learning, pre-training and generative adversarial network. We compare these methods and point out the further research directions. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Dialogue%20management" title="Dialogue management">Dialogue management</a>, <a href="https://publications.waset.org/search?q=response%20generation" title=" response generation"> response generation</a>, <a href="https://publications.waset.org/search?q=reinforcement%20learning" title=" reinforcement learning"> reinforcement learning</a>, <a href="https://publications.waset.org/search?q=deep%20learning" title=" deep learning"> deep learning</a>, <a href="https://publications.waset.org/search?q=evaluation." title=" evaluation."> evaluation.</a> </p> <a href="https://publications.waset.org/10011653/on-dialogue-systems-based-on-deep-learning" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/10011653/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/10011653/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/10011653/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/10011653/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/10011653/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/10011653/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/10011653/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/10011653/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/10011653/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/10011653/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/10011653.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">787</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2779</span> A Simulated Environment Approach to Investigate the Effect of Adversarial Perturbations on Traffic Sign for Automotive Software-in-Loop Testing</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Sunil%20Patel">Sunil Patel</a>, <a href="https://publications.waset.org/search?q=Pallab%20Maji"> Pallab Maji</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>To study the effect of adversarial attack environment must be controlled. Autonomous driving includes mainly 5 phases sense, perceive, map, plan, and drive. Autonomous vehicles sense their surrounding with the help of different sensors like cameras, radars, and lidars. Deep learning techniques are considered Blackbox and found to be vulnerable to adversarial attacks. In this research, we study the effect of the various known adversarial attacks with the help of the Unreal Engine-based, high-fidelity, real-time raytraced simulated environment. The goal of this experiment is to find out if adversarial attacks work in moving vehicles and if an unknown network may be targeted. We discovered that the existing Blackbox and Whitebox attacks have varying effects on different traffic signs. We observed that attacks that impair detection in static scenarios do not have the same effect on moving vehicles. It was found that some adversarial attacks with hardly noticeable perturbations entirely blocked the recognition of certain traffic signs. We observed that the daylight condition has a substantial impact on the model's performance by simulating the interplay of light on traffic signs. Our findings have been found to closely resemble outcomes encountered in the real world.</p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Adversarial%20attack%20simulation" title="Adversarial attack simulation">Adversarial attack simulation</a>, <a href="https://publications.waset.org/search?q=computer%20simulation" title=" computer simulation"> computer simulation</a>, <a href="https://publications.waset.org/search?q=ray-traced%20environment" title=" ray-traced environment"> ray-traced environment</a>, <a href="https://publications.waset.org/search?q=realistic%20simulation" title=" realistic simulation"> realistic simulation</a>, <a href="https://publications.waset.org/search?q=unreal%20engine." title=" unreal engine."> unreal engine.</a> </p> <a href="https://publications.waset.org/10012675/a-simulated-environment-approach-to-investigate-the-effect-of-adversarial-perturbations-on-traffic-sign-for-automotive-software-in-loop-testing" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/10012675/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/10012675/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/10012675/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/10012675/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/10012675/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/10012675/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/10012675/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/10012675/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/10012675/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/10012675/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/10012675.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">433</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2778</span> Predicting Shot Making in Basketball Learnt from Adversarial Multiagent Trajectories</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Mark%20Harmon">Mark Harmon</a>, <a href="https://publications.waset.org/search?q=Abdolghani%20Ebrahimi"> Abdolghani Ebrahimi</a>, <a href="https://publications.waset.org/search?q=Patrick%20Lucey"> Patrick Lucey</a>, <a href="https://publications.waset.org/search?q=Diego%20Klabjan"> Diego Klabjan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>In this paper, we predict the likelihood of a player making a shot in basketball from multiagent trajectories. To approach this problem, we present a convolutional neural network (CNN) approach where we initially represent the multiagent behavior as an image. To encode the adversarial nature of basketball, we use a multichannel image which we then feed into a CNN. Additionally, to capture the temporal aspect of the trajectories we use “fading.” We find that this approach is superior to a traditional FFN model. By using gradient ascent, we were able to discover what the CNN filters look for during training. Last, we find that a combined FFN+CNN is the best performing network with an error rate of 39%.</p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=basketball" title="basketball">basketball</a>, <a href="https://publications.waset.org/search?q=computer%20vision" title=" computer vision"> computer vision</a>, <a href="https://publications.waset.org/search?q=image%20processing" title=" image processing"> image processing</a>, <a href="https://publications.waset.org/search?q=convolutional%20neural%20network" title=" convolutional neural network"> convolutional neural network</a> </p> <a href="https://publications.waset.org/10012320/predicting-shot-making-in-basketball-learnt-from-adversarial-multiagent-trajectories" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/10012320/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/10012320/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/10012320/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/10012320/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/10012320/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/10012320/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/10012320/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/10012320/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/10012320/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/10012320/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/10012320.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">705</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2777</span> Resilient Machine Learning in the Nuclear Industry: Crack Detection as a Case Study</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Anita%20Khadka">Anita Khadka</a>, <a href="https://publications.waset.org/search?q=Gregory%20Epiphaniou"> Gregory Epiphaniou</a>, <a href="https://publications.waset.org/search?q=Carsten%20Maple"> Carsten Maple</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>There is a dramatic surge in the adoption of Machine Learning (ML) techniques in many areas, including the nuclear industry (such as fault diagnosis and fuel management in nuclear power plants), autonomous systems (including self-driving vehicles), space systems (space debris recovery, for example), medical surgery, network intrusion detection, malware detection, to name a few. Artificial Intelligence (AI) has become a part of everyday modern human life. To date, the predominant focus has been developing underpinning ML algorithms that can improve accuracy, while factors such as resiliency and robustness of algorithms have been largely overlooked. If an adversarial attack is able to compromise the learning method or data, the consequences can be fatal, especially but not exclusively in safety-critical applications. In this paper, we present an in-depth analysis of five adversarial attacks and two defence methods on a crack detection ML model. Our analysis shows that it can be dangerous to adopt ML techniques without rigorous testing, since they may be vulnerable to adversarial attacks, especially in security-critical areas such as the nuclear industry. We observed that while the adopted defence methods can effectively defend against different attacks, none of them could protect against all five adversarial attacks entirely.</p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Resilient%20Machine%20Learning" title="Resilient Machine Learning">Resilient Machine Learning</a>, <a href="https://publications.waset.org/search?q=attacks" title=" attacks"> attacks</a>, <a href="https://publications.waset.org/search?q=defences" title=" defences"> defences</a>, <a href="https://publications.waset.org/search?q=nuclear%0D%0Aindustry" title=" nuclear industry"> nuclear industry</a>, <a href="https://publications.waset.org/search?q=crack%20detection." title=" crack detection."> crack detection.</a> </p> <a href="https://publications.waset.org/10012926/resilient-machine-learning-in-the-nuclear-industry-crack-detection-as-a-case-study" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/10012926/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/10012926/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/10012926/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/10012926/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/10012926/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/10012926/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/10012926/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/10012926/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/10012926/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/10012926/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/10012926.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">500</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2776</span> NANCY: Combining Adversarial Networks with Cycle-Consistency for Robust Multi-Modal Image Registration</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Mirjana%20Ruppel">Mirjana Ruppel</a>, <a href="https://publications.waset.org/search?q=Rajendra%20Persad"> Rajendra Persad</a>, <a href="https://publications.waset.org/search?q=Amit%20Bahl"> Amit Bahl</a>, <a href="https://publications.waset.org/search?q=Sanja%20Dogramadzi"> Sanja Dogramadzi</a>, <a href="https://publications.waset.org/search?q=Chris%20Melhuish"> Chris Melhuish</a>, <a href="https://publications.waset.org/search?q=Lyndon%20Smith"> Lyndon Smith</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Multimodal image registration is a profoundly complex task which is why deep learning has been used widely to address it in recent years. However, two main challenges remain: Firstly, the lack of ground truth data calls for an unsupervised learning approach, which leads to the second challenge of defining a feasible loss function that can compare two images of different modalities to judge their level of alignment. To avoid this issue altogether we implement a generative adversarial network consisting of two registration networks GAB, GBA and two discrimination networks DA, DB connected by spatial transformation layers. GAB learns to generate a deformation field which registers an image of the modality B to an image of the modality A. To do that, it uses the feedback of the discriminator DB which is learning to judge the quality of alignment of the registered image B. GBA and DA learn a mapping from modality A to modality B. Additionally, a cycle-consistency loss is implemented. For this, both registration networks are employed twice, therefore resulting in images &circ;A, &circ;B which were registered to &tilde;B, &tilde;A which were registered to the initial image pair A, B. Thus the resulting and initial images of the same modality can be easily compared. A dataset of liver CT and MRI was used to evaluate the quality of our approach and to compare it against learning and non-learning based registration algorithms. Our approach leads to dice scores of up to 0.80 ± 0.01 and is therefore comparable to and slightly more successful than algorithms like SimpleElastix and VoxelMorph. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Multimodal%20image%20registration" title="Multimodal image registration">Multimodal image registration</a>, <a href="https://publications.waset.org/search?q=GAN" title=" GAN"> GAN</a>, <a href="https://publications.waset.org/search?q=cycle%0D%0Aconsistency" title=" cycle consistency"> cycle consistency</a>, <a href="https://publications.waset.org/search?q=deep%20learning." title=" deep learning."> deep learning.</a> </p> <a href="https://publications.waset.org/10011399/nancy-combining-adversarial-networks-with-cycle-consistency-for-robust-multi-modal-image-registration" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/10011399/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/10011399/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/10011399/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/10011399/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/10011399/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/10011399/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/10011399/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/10011399/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/10011399/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/10011399/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/10011399.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">810</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2775</span> Rejuvenate: Face and Body Retouching Using Image Inpainting</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=H.%20AbdelRahman">H. AbdelRahman</a>, <a href="https://publications.waset.org/search?q=S.%20Rostom"> S. Rostom</a>, <a href="https://publications.waset.org/search?q=Y.%20Lotfy"> Y. Lotfy</a>, <a href="https://publications.waset.org/search?q=S.%20Salah%20Eldeen"> S. Salah Eldeen</a>, <a href="https://publications.waset.org/search?q=R.%20Yassein"> R. Yassein</a>, <a href="https://publications.waset.org/search?q=N.%20Awny"> N. Awny</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>People are growing more concerned with their appearance in today's society. But they are terrified of what they will look like after a plastic surgery. People's mental health suffers when they have accidents, burns, or genetic issues that cause them to cleave certain body parts, which makes them feel uncomfortable and unappreciated. The method provides an innovative deep learning-based technique for image inpainting that analyzes different picture structures and fixes damaged images. This study proposes a model based on the Stable Diffusion Inpainting method for in-painting medical images. One significant advancement made possible by deep neural networks is image inpainting, which is the process of reconstructing damaged and missing portions of an image. The patient can see the outcome more easily since the system uses the user's input of an image to identify a problem. It then modifies the image and outputs a fixed image.</p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Generative%20Adversarial%20Network" title="Generative Adversarial Network">Generative Adversarial Network</a>, <a href="https://publications.waset.org/search?q=GAN" title=" GAN"> GAN</a>, <a href="https://publications.waset.org/search?q=Large%20Mask%20Inpainting" title=" Large Mask Inpainting"> Large Mask Inpainting</a>, <a href="https://publications.waset.org/search?q=LAMA" title=" LAMA"> LAMA</a>, <a href="https://publications.waset.org/search?q=Stable%20Diffusion%20Inpainting." title=" Stable Diffusion Inpainting."> Stable Diffusion Inpainting.</a> </p> <a href="https://publications.waset.org/10013665/rejuvenate-face-and-body-retouching-using-image-inpainting" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/10013665/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/10013665/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/10013665/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/10013665/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/10013665/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/10013665/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/10013665/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/10013665/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/10013665/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/10013665/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/10013665.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">107</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2774</span> Enhancing Hand Efficiency of Smart Glass Cleaning Robot through Generative Design Module</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Pankaj%20Gupta">Pankaj Gupta</a>, <a href="https://publications.waset.org/search?q=Amit%20Kumar%20Srivastava"> Amit Kumar Srivastava</a>, <a href="https://publications.waset.org/search?q=Nitesh%20Pandey"> Nitesh Pandey</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>This article explores the domain of generative design in order to enhance the development of robot designs for innovative and efficient maintenance approaches for tall buildings. This study aims to optimize the design of robotic hands by focusing on minimizing mass and volume while ensuring they can withstand the specified pressure with equal strength. The research procedure is structured and systematic. The purpose of optimization is to enhance the efficiency of the robot and reduce the manufacturing expenses. The project seeks to investigate the application of generative design in order to optimize products. Autodesk Fusion 360 offers the capability to immediately apply the generative design functionality to the solid model. The effort involved creating a solid model of the Smart Glass Cleaning Robot and optimizing one of its components, the Hand, using generative techniques. The article has thoroughly examined the designs, outcomes, and procedure. These loads serve as a benchmark for creating designs that can endure the necessary level of pressure and preserve their structural integrity. The efficacy of the generative design process is contingent upon the selection of materials, as different materials possess distinct physical attributes. The study utilizes five different materials, namely Steel, Stainless Steel, Titanium, Aluminum, and CFRP (Carbon Fiber Reinforced Polymer), in order to investigate a range of design possibilities.</p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Generative%20design" title="Generative design">Generative design</a>, <a href="https://publications.waset.org/search?q=mass%20and%20volume%20optimization" title=" mass and volume optimization"> mass and volume optimization</a>, <a href="https://publications.waset.org/search?q=material%20strength%20analysis" title=" material strength analysis"> material strength analysis</a>, <a href="https://publications.waset.org/search?q=generative%20design" title=" generative design"> generative design</a>, <a href="https://publications.waset.org/search?q=smart%20glass%20cleaning%20robot." title=" smart glass cleaning robot."> smart glass cleaning robot.</a> </p> <a href="https://publications.waset.org/10013508/enhancing-hand-efficiency-of-smart-glass-cleaning-robot-through-generative-design-module" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/10013508/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/10013508/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/10013508/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/10013508/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/10013508/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/10013508/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/10013508/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/10013508/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/10013508/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/10013508/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/10013508.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">201</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2773</span> Vision Based Hand Gesture Recognition Using Generative and Discriminative Stochastic Models</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Mahmoud%20Elmezain">Mahmoud Elmezain</a>, <a href="https://publications.waset.org/search?q=Samar%20El-shinawy"> Samar El-shinawy</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>Many approaches to pattern recognition are founded on probability theory, and can be broadly characterized as either generative or discriminative according to whether or not the distribution of the image features. Generative and discriminative models have very different characteristics, as well as complementary strengths and weaknesses. In this paper, we study these models to recognize the patterns of alphabet characters (A-Z) and numbers (0-9). To handle isolated pattern, generative model as Hidden Markov Model (HMM) and discriminative models like Conditional Random Field (CRF), Hidden Conditional Random Field (HCRF) and Latent-Dynamic Conditional Random Field (LDCRF) with different number of window size are applied on extracted pattern features. The gesture recognition rate is improved initially as the window size increase, but degrades as window size increase further. Experimental results show that the LDCRF is the best in terms of results than CRF, HCRF and HMM at window size equal 4. Additionally, our results show that; an overall recognition rates are 91.52%, 95.28%, 96.94% and 98.05% for CRF, HCRF, HMM and LDCRF respectively.</p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Statistical%20Pattern%20Recognition" title="Statistical Pattern Recognition">Statistical Pattern Recognition</a>, <a href="https://publications.waset.org/search?q=Generative%20Model" title=" Generative Model"> Generative Model</a>, <a href="https://publications.waset.org/search?q=Discriminative%20Model" title=" Discriminative Model"> Discriminative Model</a>, <a href="https://publications.waset.org/search?q=Human%20Computer%20Interaction." title=" Human Computer Interaction."> Human Computer Interaction.</a> </p> <a href="https://publications.waset.org/17283/vision-based-hand-gesture-recognition-using-generative-and-discriminative-stochastic-models" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/17283/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/17283/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/17283/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/17283/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/17283/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/17283/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/17283/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/17283/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/17283/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/17283/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/17283.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">2936</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2772</span> Generative Adversarial Network Based Fingerprint Anti-Spoofing Limitations</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Yehjune%20Heo">Yehjune Heo</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>Fingerprint Anti-Spoofing approaches have been actively developed and applied in real-world applications. One of the main problems for Fingerprint Anti-Spoofing is not robust to unseen samples, especially in real-world scenarios. A possible solution will be to generate artificial, but realistic fingerprint samples and use them for training in order to achieve good generalization. This paper contains experimental and comparative results with currently popular GAN based methods and uses realistic synthesis of fingerprints in training in order to increase the performance. Among various GAN models, the most popular StyleGAN is used for the experiments. The CNN models were first trained with the dataset that did not contain generated fake images and the accuracy along with the mean average error rate were recorded. Then, the fake generated images (fake images of live fingerprints and fake images of spoof fingerprints) were each combined with the original images (real images of live fingerprints and real images of spoof fingerprints), and various CNN models were trained. The best performances for each CNN model, trained with the dataset of generated fake images and each time the accuracy and the mean average error rate, were recorded. We observe that current GAN based approaches need significant improvements for the Anti-Spoofing performance, although the overall quality of the synthesized fingerprints seems to be reasonable. We include the analysis of this performance degradation, especially with a small number of samples. In addition, we suggest several approaches towards improved generalization with a small number of samples, by focusing on what GAN based approaches should learn and should not learn.</p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Anti-spoofing" title="Anti-spoofing">Anti-spoofing</a>, <a href="https://publications.waset.org/search?q=CNN" title=" CNN"> CNN</a>, <a href="https://publications.waset.org/search?q=fingerprint%20recognition" title=" fingerprint recognition"> fingerprint recognition</a>, <a href="https://publications.waset.org/search?q=GAN." title=" GAN."> GAN.</a> </p> <a href="https://publications.waset.org/10012066/generative-adversarial-network-based-fingerprint-anti-spoofing-limitations" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/10012066/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/10012066/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/10012066/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/10012066/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/10012066/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/10012066/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/10012066/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/10012066/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/10012066/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/10012066/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/10012066.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">593</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2771</span> Conditions for Fault Recovery of Interconnected Asynchronous Sequential Machines with State Feedback</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Jung%E2%80%93Min%20Yang">Jung–Min Yang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, fault recovery for parallel interconnected asynchronous sequential machines is studied. An adversarial input can infiltrate into one of two submachines comprising parallel composition of the considered asynchronous sequential machine, causing an unauthorized state transition. The control objective is to elucidate the condition for the existence of a corrective controller that makes the closed-loop system immune against any occurrence of adversarial inputs. In particular, an efficient existence condition is presented that does not need the complete modeling of the interconnected asynchronous sequential machine. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Asynchronous%20sequential%20machines" title="Asynchronous sequential machines">Asynchronous sequential machines</a>, <a href="https://publications.waset.org/search?q=parallel%0D%0Acomposition" title=" parallel composition"> parallel composition</a>, <a href="https://publications.waset.org/search?q=corrective%20control" title=" corrective control"> corrective control</a>, <a href="https://publications.waset.org/search?q=fault%20tolerance." title=" fault tolerance."> fault tolerance.</a> </p> <a href="https://publications.waset.org/10008376/conditions-for-fault-recovery-of-interconnected-asynchronous-sequential-machines-with-state-feedback" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/10008376/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/10008376/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/10008376/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/10008376/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/10008376/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/10008376/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/10008376/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/10008376/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/10008376/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/10008376/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/10008376.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">839</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2770</span> Mapping Semantic Networks to Undirected Networks</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Marko%20A.%20Rodriguez">Marko A. Rodriguez</a> </p> <p class="card-text"><strong>Abstract:</strong></p> There exists an injective, information-preserving function that maps a semantic network (i.e a directed labeled network) to a directed network (i.e. a directed unlabeled network). The edge label in the semantic network is represented as a topological feature of the directed network. Also, there exists an injective function that maps a directed network to an undirected network (i.e. an undirected unlabeled network). The edge directionality in the directed network is represented as a topological feature of the undirected network. Through function composition, there exists an injective function that maps a semantic network to an undirected network. Thus, aside from space constraints, the semantic network construct does not have any modeling functionality that is not possible with either a directed or undirected network representation. Two proofs of this idea will be presented. The first is a proof of the aforementioned function composition concept. The second is a simpler proof involving an undirected binary encoding of a semantic network. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=general-modeling" title="general-modeling">general-modeling</a>, <a href="https://publications.waset.org/search?q=multi-relational%20networks" title=" multi-relational networks"> multi-relational networks</a>, <a href="https://publications.waset.org/search?q=semantic%20networks" title=" semantic networks"> semantic networks</a> </p> <a href="https://publications.waset.org/9658/mapping-semantic-networks-to-undirected-networks" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/9658/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/9658/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/9658/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/9658/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/9658/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/9658/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/9658/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/9658/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/9658/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/9658/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/9658.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">1442</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2769</span> An efficient Activity Network Reduction Algorithm based on the Label Correcting Tracing Algorithm</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Weng%20Ming%20Chu">Weng Ming Chu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> When faced with stochastic networks with an uncertain duration for their activities, the securing of network completion time becomes problematical, not only because of the non-identical pdf of duration for each node, but also because of the interdependence of network paths. As evidenced by Adlakha & Kulkarni [1], many methods and algorithms have been put forward in attempt to resolve this issue, but most have encountered this same large-size network problem. Therefore, in this research, we focus on network reduction through a Series/Parallel combined mechanism. Our suggested algorithm, named the Activity Network Reduction Algorithm (ANRA), can efficiently transfer a large-size network into an S/P Irreducible Network (SPIN). SPIN can enhance stochastic network analysis, as well as serve as the judgment of symmetry for the Graph Theory. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Series%2FParallel%20network" title="Series/Parallel network">Series/Parallel network</a>, <a href="https://publications.waset.org/search?q=Stochastic%20network" title=" Stochastic network"> Stochastic network</a>, <a href="https://publications.waset.org/search?q=Network%0Areduction" title=" Network reduction"> Network reduction</a>, <a href="https://publications.waset.org/search?q=Interdictive%20Graph" title=" Interdictive Graph"> Interdictive Graph</a>, <a href="https://publications.waset.org/search?q=Complexity%20Index." title=" Complexity Index."> Complexity Index.</a> </p> <a href="https://publications.waset.org/15982/an-efficient-activity-network-reduction-algorithm-based-on-the-label-correcting-tracing-algorithm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/15982/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/15982/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/15982/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/15982/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/15982/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/15982/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/15982/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/15982/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/15982/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/15982/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/15982.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">1379</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2768</span> Security of Mobile Agent in Ad hoc Network using Threshold Cryptography</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=S.M.%20Sarwarul%20Islam%20Rizvi">S.M. Sarwarul Islam Rizvi</a>, <a href="https://publications.waset.org/search?q=Zinat%20Sultana"> Zinat Sultana</a>, <a href="https://publications.waset.org/search?q=Bo%20Sun"> Bo Sun</a>, <a href="https://publications.waset.org/search?q=Md.%20Washiqul%20Islam"> Md. Washiqul Islam</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>In a very simple form a Mobile Agent is an independent piece of code that has mobility and autonomy behavior. One of the main advantages of using Mobile Agent in a network is - it reduces network traffic load. In an, ad hoc network Mobile Agent can be used to protect the network by using agent based IDS or IPS. Besides, to deploy dynamic software in the network or to retrieve information from network nodes Mobile Agent can be useful. But in an ad hoc network the Mobile Agent itself needs some security. Security services should be guaranteed both for Mobile Agent and for Agent Server. In this paper to protect the Mobile Agent and Agent Server in an ad hoc network we have proposed a solution which is based on Threshold Cryptography, a new vibe in the cryptographic world where trust is distributed among multiple nodes in the network.</p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Ad%20hoc%20network" title="Ad hoc network">Ad hoc network</a>, <a href="https://publications.waset.org/search?q=Mobile%20Agent" title=" Mobile Agent"> Mobile Agent</a>, <a href="https://publications.waset.org/search?q=Security" title=" Security"> Security</a>, <a href="https://publications.waset.org/search?q=Threats" title=" Threats"> Threats</a>, <a href="https://publications.waset.org/search?q=Threshold%20Cryptography." title="Threshold Cryptography.">Threshold Cryptography.</a> </p> <a href="https://publications.waset.org/4803/security-of-mobile-agent-in-ad-hoc-network-using-threshold-cryptography" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/4803/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/4803/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/4803/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/4803/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/4803/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/4803/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/4803/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/4803/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/4803/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/4803/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/4803.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">1967</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2767</span> Heuristic Optimization Techniques for Network Reconfiguration in Distribution System</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=A.%20Charlangsut">A. Charlangsut</a>, <a href="https://publications.waset.org/search?q=N.%20Rugthaicharoencheep"> N. Rugthaicharoencheep</a>, <a href="https://publications.waset.org/search?q=S.%20Auchariyamet"> S. Auchariyamet</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Network reconfiguration is an operation to modify the network topology. The implementation of network reconfiguration has many advantages such as loss minimization, increasing system security and others. In this paper, two topics about the network reconfiguration in distribution system are briefly described. The first topic summarizes its impacts while the second explains some heuristic optimization techniques for solving the network reconfiguration problem. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Network%20Reconfiguration" title="Network Reconfiguration">Network Reconfiguration</a>, <a href="https://publications.waset.org/search?q=Optimization%20Techniques" title=" Optimization Techniques"> Optimization Techniques</a>, <a href="https://publications.waset.org/search?q=Distribution%20System" title="Distribution System">Distribution System</a> </p> <a href="https://publications.waset.org/12829/heuristic-optimization-techniques-for-network-reconfiguration-in-distribution-system" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/12829/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/12829/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/12829/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/12829/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/12829/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/12829/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/12829/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/12829/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/12829/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/12829/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/12829.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">2756</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2766</span> A Network Traffic Prediction Algorithm Based On Data Mining Technique</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=D.%20Prangchumpol">D. Prangchumpol</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>This paper is a description approach to predict incoming and outgoing data rate in network system by using association rule discover, which is one of the data mining techniques. Information of incoming and outgoing data in each times and network bandwidth are network performance parameters, which needed to solve in the traffic problem. Since congestion and data loss are important network problems. The result of this technique can predicted future network traffic. In addition, this research is useful for network routing selection and network performance improvement.</p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Traffic%20prediction" title="Traffic prediction">Traffic prediction</a>, <a href="https://publications.waset.org/search?q=association%20rule" title=" association rule"> association rule</a>, <a href="https://publications.waset.org/search?q=data%20mining." title=" data mining."> data mining.</a> </p> <a href="https://publications.waset.org/16461/a-network-traffic-prediction-algorithm-based-on-data-mining-technique" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/16461/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/16461/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/16461/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/16461/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/16461/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/16461/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/16461/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/16461/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/16461/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/16461/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/16461.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">3669</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2765</span> A Survey: Bandwidth Management in an IP Based Network</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=M.%20Kassim">M. Kassim</a>, <a href="https://publications.waset.org/search?q=M.%20Ismail"> M. Ismail</a>, <a href="https://publications.waset.org/search?q=K.%20Jumari"> K. Jumari</a>, <a href="https://publications.waset.org/search?q=M.I%20Yusof"> M.I Yusof</a> </p> <p class="card-text"><strong>Abstract:</strong></p> this paper presented a survey analysis subjected on network bandwidth management from published papers referred in IEEE Explorer database in three years from 2009 to 2011. Network Bandwidth Management is discussed in today-s issues for computer engineering applications and systems. Detailed comparison is presented between published papers to look further in the IP based network critical research area for network bandwidth management. Important information such as the network focus area, a few modeling in the IP Based Network and filtering or scheduling used in the network applications layer is presented. Many researches on bandwidth management have been done in the broad network area but fewer are done in IP Based network specifically at the applications network layer. A few researches has contributed new scheme or enhanced modeling but still the issue of bandwidth management still arise at the applications network layer. This survey is taken as a basic research towards implementations of network bandwidth management technique, new framework model and scheduling scheme or algorithm in an IP Based network which will focus in a control bandwidth mechanism in prioritizing the network traffic the applications layer. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Bandwidth%20Management%20%28BM%29" title="Bandwidth Management (BM)">Bandwidth Management (BM)</a>, <a href="https://publications.waset.org/search?q=IP%20Based%20network" title=" IP Based network"> IP Based network</a>, <a href="https://publications.waset.org/search?q=modeling" title=" modeling"> modeling</a>, <a href="https://publications.waset.org/search?q=algorithm" title=" algorithm"> algorithm</a>, <a href="https://publications.waset.org/search?q=internet%20traffic" title=" internet traffic"> internet traffic</a>, <a href="https://publications.waset.org/search?q=network%20Management" title=" network Management"> network Management</a>, <a href="https://publications.waset.org/search?q=Quality%0Aof%20Service%20%28QoS%29." title=" Quality of Service (QoS)."> Quality of Service (QoS).</a> </p> <a href="https://publications.waset.org/3739/a-survey-bandwidth-management-in-an-ip-based-network" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/3739/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/3739/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/3739/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/3739/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/3739/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/3739/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/3739/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/3739/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/3739/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/3739/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/3739.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">3333</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2764</span> Proposed a Method for Increasing the Delivery Performance in Dynamic Supply Network</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=M.%20Safaei">M. Safaei</a>, <a href="https://publications.waset.org/search?q=M.%20Seifert"> M. Seifert</a>, <a href="https://publications.waset.org/search?q=K.%20D.%20Thoben"> K. D. Thoben</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Supply network management adopts a systematic and integrative approach to managing the operations and relationships of various parties in a supply network. The objective of the manufactures in their supply network is to reduce inventory costs and increase customer satisfaction levels. One way of doing that is to synchronize delivery performance. A supply network can be described by nodes representing the companies and the links (relationships) between these nodes. Uncertainty in delivery time depends on type of network relationship between suppliers. The problem is to understand how the individual uncertainties influence the total uncertainty of the network and identify those parts of the network, which has the highest potential for improving the total delivery time uncertainty. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Delivery%20time%20uncertainty" title="Delivery time uncertainty">Delivery time uncertainty</a>, <a href="https://publications.waset.org/search?q=Distribution%20function" title=" Distribution function"> Distribution function</a>, <a href="https://publications.waset.org/search?q=Statistical%20method" title="Statistical method">Statistical method</a>, <a href="https://publications.waset.org/search?q=Supply%20Network." title=" Supply Network."> Supply Network.</a> </p> <a href="https://publications.waset.org/14586/proposed-a-method-for-increasing-the-delivery-performance-in-dynamic-supply-network" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/14586/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/14586/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/14586/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/14586/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/14586/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/14586/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/14586/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/14586/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/14586/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/14586/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/14586.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">1674</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2763</span> Enhancing the Network Security with Gray Code</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Thomas%20Adi%20Purnomo%20Sidhi">Thomas Adi Purnomo Sidhi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>Nowadays, network is an essential need in almost every part of human daily activities. People now can seamlessly connect to others through the Internet. With advanced technology, our personal data now can be more easily accessed. One of many components we are concerned for delivering the best network is a security issue. This paper is proposing a method that provides more options for security. This research aims to improve network security by focusing on the physical layer which is the first layer of the OSI model. The layer consists of the basic networking hardware transmission technologies of a network. With the use of observation method, the research produces a schematic design for enhancing the network security through the gray code converter.</p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Network" title="Network">Network</a>, <a href="https://publications.waset.org/search?q=network%20security" title=" network security"> network security</a>, <a href="https://publications.waset.org/search?q=gray%20code" title=" gray code"> gray code</a>, <a href="https://publications.waset.org/search?q=physical%20layer." title=" physical layer."> physical layer.</a> </p> <a href="https://publications.waset.org/10003931/enhancing-the-network-security-with-gray-code" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/10003931/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/10003931/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/10003931/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/10003931/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/10003931/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/10003931/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/10003931/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/10003931/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/10003931/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/10003931/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/10003931.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">2168</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2762</span> The Application of Non-quantitative Modelling in the Analysis of a Network Warfare Environment</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=N.%20Veerasamy">N. Veerasamy</a>, <a href="https://publications.waset.org/search?q=JPH%20Eloff"> JPH Eloff</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>Network warfare is an emerging concept that focuses on the network and computer based forms through which information is attacked and defended. Various computer and network security concepts thus play a role in network warfare. Due the intricacy of the various interacting components, a model to better understand the complexity in a network warfare environment would be beneficial. Non-quantitative modeling is a useful method to better characterize the field due to the rich ideas that can be generated based on the use of secular associations, chronological origins, linked concepts, categorizations and context specifications. This paper proposes the use of non-quantitative methods through a morphological analysis to better explore and define the influential conditions in a network warfare environment.</p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Morphological" title="Morphological">Morphological</a>, <a href="https://publications.waset.org/search?q=non-quantitative" title=" non-quantitative"> non-quantitative</a>, <a href="https://publications.waset.org/search?q=network%20warfare." title=" network warfare."> network warfare.</a> </p> <a href="https://publications.waset.org/8346/the-application-of-non-quantitative-modelling-in-the-analysis-of-a-network-warfare-environment" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/8346/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/8346/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/8346/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/8346/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/8346/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/8346/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/8346/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/8346/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/8346/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/8346/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/8346.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">1387</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2761</span> DEVS Modeling of Network Vulnerability</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Hee%20Suk%20Seo">Hee Suk Seo</a>, <a href="https://publications.waset.org/search?q=Tae%20Kyung%20Kim"> Tae Kyung Kim</a> </p> <p class="card-text"><strong>Abstract:</strong></p> As network components grow larger and more diverse, and as securing them on a host-by-host basis grow more difficult, more sites are turning to a network security model. We concentrate on controlling network access to various hosts and the services they offer, rather than on securing them one by one with a network security model. We present how the policy rules from vulnerabilities stored in SVDB (Simulation based Vulnerability Data Base) are inducted, and how to be used in PBN. In the network security environment, each simulation model is hierarchically designed by DEVS (Discrete EVent system Specification) formalism. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=SVDB" title="SVDB">SVDB</a>, <a href="https://publications.waset.org/search?q=PBN" title=" PBN"> PBN</a>, <a href="https://publications.waset.org/search?q=DEVS" title=" DEVS"> DEVS</a>, <a href="https://publications.waset.org/search?q=Network%20security." title=" Network security."> Network security.</a> </p> <a href="https://publications.waset.org/7155/devs-modeling-of-network-vulnerability" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/7155/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/7155/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/7155/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/7155/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/7155/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/7155/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/7155/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/7155/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/7155/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/7155/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/7155.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">1569</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2760</span> Reliability Optimization for 3G Cellular Access Networks</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Ekkaluk%20Eksook">Ekkaluk Eksook</a>, <a href="https://publications.waset.org/search?q=Chutima%20Prommak"> Chutima Prommak</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper address the network reliability optimization problem in the optical access network design for the 3G cellular systems. We presents a novel 0-1 integer programming model for designing optical access network topologies comprised of multi-rings with common-edge in order to guarantee always-on services. The results show that the proposed model yields access network topologies with the optimal reliablity and satisfies both network cost limitations and traffic demand requirements. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Network%20Reliability" title="Network Reliability">Network Reliability</a>, <a href="https://publications.waset.org/search?q=Topological%20Network%20Design" title=" Topological Network Design"> Topological Network Design</a>, <a href="https://publications.waset.org/search?q=3G%20Cellular%20Networks." title=" 3G Cellular Networks."> 3G Cellular Networks.</a> </p> <a href="https://publications.waset.org/9883/reliability-optimization-for-3g-cellular-access-networks" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/9883/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/9883/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/9883/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/9883/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/9883/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/9883/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/9883/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/9883/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/9883/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/9883/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/9883.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">1539</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2759</span> Retrieval Augmented Generation against the Machine: Merging Human Cyber Security Expertise with Generative AI</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Brennan%20Lodge">Brennan Lodge</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>Amidst a complex regulatory landscape, Retrieval Augmented Generation (RAG) emerges as a transformative tool for Governance Risk and Compliance (GRC) officers. This paper details the application of RAG in synthesizing Large Language Models (LLMs) with external knowledge bases, offering GRC professionals an advanced means to adapt to rapid changes in compliance requirements. While the development for standalone LLMs is exciting, such models do have their downsides. LLMs cannot easily expand or revise their memory, and they cannot straightforwardly provide insight into their predictions, and may produce “hallucinations.” Leveraging a pre-trained seq2seq transformer and a dense vector index of domain-specific data, this approach integrates real-time data retrieval into the generative process, enabling gap analysis and the dynamic generation of compliance and risk management content. We delve into the mechanics of RAG, focusing on its dual structure that pairs parametric knowledge contained within the transformer model with non-parametric data extracted from an updatable corpus. This hybrid model enhances decision-making through context-rich insights, drawing from the most current and relevant information, thereby enabling GRC officers to maintain a proactive compliance stance. Our methodology aligns with the latest advances in neural network fine-tuning, providing a granular, token-level application of retrieved information to inform and generate compliance narratives. By employing RAG, we exhibit a scalable solution that can adapt to novel regulatory challenges and cybersecurity threats, offering GRC officers a robust, predictive tool that augments their expertise. The granular application of RAG’s dual structure not only improves compliance and risk management protocols but also informs the development of compliance narratives with pinpoint accuracy. It underscores AI’s emerging role in strategic risk mitigation and proactive policy formation, positioning GRC officers to anticipate and navigate the complexities of regulatory evolution confidently.</p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Retrieval%20Augmented%20Generation" title="Retrieval Augmented Generation">Retrieval Augmented Generation</a>, <a href="https://publications.waset.org/search?q=Governance%20Risk%20and%20Compliance" title=" Governance Risk and Compliance"> Governance Risk and Compliance</a>, <a href="https://publications.waset.org/search?q=Cybersecurity" title=" Cybersecurity"> Cybersecurity</a>, <a href="https://publications.waset.org/search?q=AI-driven%20Compliance" title=" AI-driven Compliance"> AI-driven Compliance</a>, <a href="https://publications.waset.org/search?q=Risk%20Management" title=" Risk Management"> Risk Management</a>, <a href="https://publications.waset.org/search?q=Generative%20AI." title=" Generative AI."> Generative AI.</a> </p> <a href="https://publications.waset.org/10013734/retrieval-augmented-generation-against-the-machine-merging-human-cyber-security-expertise-with-generative-ai" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/10013734/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/10013734/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/10013734/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/10013734/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/10013734/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/10013734/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/10013734/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/10013734/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/10013734/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/10013734/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/10013734.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">124</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2758</span> Home Network-Specific RBAC Model</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Geon-Woo%20Kim">Geon-Woo Kim</a>, <a href="https://publications.waset.org/search?q=Do-Woo%20Kim"> Do-Woo Kim</a>, <a href="https://publications.waset.org/search?q=Jun-Ho%20Lee"> Jun-Ho Lee</a>, <a href="https://publications.waset.org/search?q=Jin-Beon%20Hwang"> Jin-Beon Hwang</a>, <a href="https://publications.waset.org/search?q=Jong-Wook%20Han"> Jong-Wook Han</a> </p> <p class="card-text"><strong>Abstract:</strong></p> As various mobile sensing technologies, remote control and ubiquitous infrastructure are developing and expectations on quality of life are increasing, a lot of researches and developments on home network technologies and services are actively on going, Until now, we have focused on how to provide users with high-level home network services, while not many researches on home network security for guaranteeing safety are progressing. So, in this paper, we propose an access control model specific to home network that provides various kinds of users with home network services up one-s characteristics and features, and protects home network systems from illegal/unnecessary accesses or intrusions. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Home%20network%20security" title="Home network security">Home network security</a>, <a href="https://publications.waset.org/search?q=RBAC" title=" RBAC"> RBAC</a>, <a href="https://publications.waset.org/search?q=access%20control" title=" access control"> access control</a>, <a href="https://publications.waset.org/search?q=authentication." title=" authentication."> authentication.</a> </p> <a href="https://publications.waset.org/10772/home-network-specific-rbac-model" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/10772/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/10772/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/10772/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/10772/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/10772/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/10772/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/10772/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/10772/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/10772/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/10772/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/10772.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">1730</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2757</span> Techniques Used in String Matching for Network Security</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Jamuna%20Bhandari">Jamuna Bhandari</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>String matching also known as pattern matching is one of primary concept for network security. In this area the effectiveness and efficiency of string matching algorithms is important for applications in network security such as network intrusion detection, virus detection, signature matching and web content filtering system. This paper presents brief review on some of string matching techniques used for network security.</p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Filtering" title="Filtering">Filtering</a>, <a href="https://publications.waset.org/search?q=honeypot" title=" honeypot"> honeypot</a>, <a href="https://publications.waset.org/search?q=network%20telescope" title=" network telescope"> network telescope</a>, <a href="https://publications.waset.org/search?q=pattern" title=" pattern"> pattern</a>, <a href="https://publications.waset.org/search?q=string" title=" string"> string</a>, <a href="https://publications.waset.org/search?q=signature." title=" signature."> signature.</a> </p> <a href="https://publications.waset.org/9998719/techniques-used-in-string-matching-for-network-security" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/9998719/apa" target="_blank" rel="nofollow" class="btn btn-primary 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