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short-term memory (LSTM)</title> <meta name="description" content="Search results for: long short-term memory (LSTM)"> <meta name="keywords" content="long short-term memory (LSTM)"> <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/abstracts/search"> <div id="custom-search-input"> <div class="input-group"> <i class="fas fa-search"></i> <input type="text" class="search-query" name="q" placeholder="Author, Title, Abstract, Keywords" value="long short-term memory (LSTM)"> <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> 7009</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: long short-term memory (LSTM)</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6919</span> Neural Networks and Genetic Algorithms Approach for Word Correction and Prediction</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Rodrigo%20S.%20Fonseca">Rodrigo S. Fonseca</a>, <a href="https://publications.waset.org/abstracts/search?q=Ant%C3%B4nio%20C.%20P.%20Veiga"> Antônio C. P. Veiga</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Aiming at helping people with some movement limitation that makes typing and communication difficult, there is a need to customize an assistive tool with a learning environment that helps the user in order to optimize text input, identifying the error and providing the correction and possibilities of choice in the Portuguese language. The work presents an Orthographic and Grammatical System that can be incorporated into writing environments, improving and facilitating the use of an alphanumeric keyboard, using a prototype built using a genetic algorithm in addition to carrying out the prediction, which can occur based on the quantity and position of the inserted letters and even placement in the sentence, ensuring the sequence of ideas using a Long Short Term Memory (LSTM) neural network. The prototype optimizes data entry, being a component of assistive technology for the textual formulation, detecting errors, seeking solutions and informing the user of accurate predictions quickly and effectively through machine learning. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=genetic%20algorithm" title="genetic algorithm">genetic algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=neural%20networks" title=" neural networks"> neural networks</a>, <a href="https://publications.waset.org/abstracts/search?q=word%20prediction" title=" word prediction"> word prediction</a>, <a href="https://publications.waset.org/abstracts/search?q=machine%20learning" title=" machine learning"> machine learning</a> </p> <a href="https://publications.waset.org/abstracts/141048/neural-networks-and-genetic-algorithms-approach-for-word-correction-and-prediction" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/141048.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">194</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6918</span> Design of an Automated Deep Learning Recurrent Neural Networks System Integrated with IoT for Anomaly Detection in Residential Electric Vehicle Charging in Smart Cities</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Wanchalerm%20Patanacharoenwong">Wanchalerm Patanacharoenwong</a>, <a href="https://publications.waset.org/abstracts/search?q=Panaya%20Sudta"> Panaya Sudta</a>, <a href="https://publications.waset.org/abstracts/search?q=Prachya%20Bumrungkun"> Prachya Bumrungkun</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The paper focuses on the development of a system that combines Internet of Things (IoT) technologies and deep learning algorithms for anomaly detection in residential Electric Vehicle (EV) charging in smart cities. With the increasing number of EVs, ensuring efficient and reliable charging systems has become crucial. The aim of this research is to develop an integrated IoT and deep learning system for detecting anomalies in residential EV charging and enhancing EV load profiling and event detection in smart cities. This approach utilizes IoT devices equipped with infrared cameras to collect thermal images and household EV charging profiles from the database of Thailand utility, subsequently transmitting this data to a cloud database for comprehensive analysis. The methodology includes the use of advanced deep learning techniques such as Recurrent Neural Networks (RNN) and Long Short-Term Memory (LSTM) algorithms. IoT devices equipped with infrared cameras are used to collect thermal images and EV charging profiles. The data is transmitted to a cloud database for comprehensive analysis. The researchers also utilize feature-based Gaussian mixture models for EV load profiling and event detection. Moreover, the research findings demonstrate the effectiveness of the developed system in detecting anomalies and critical profiles in EV charging behavior. The system provides timely alarms to users regarding potential issues and categorizes the severity of detected problems based on a health index for each charging device. The system also outperforms existing models in event detection accuracy. This research contributes to the field by showcasing the potential of integrating IoT and deep learning techniques in managing residential EV charging in smart cities. The system ensures operational safety and efficiency while also promoting sustainable energy management. The data is collected using IoT devices equipped with infrared cameras and is stored in a cloud database for analysis. The collected data is then analyzed using RNN, LSTM, and feature-based Gaussian mixture models. The approach includes both EV load profiling and event detection, utilizing a feature-based Gaussian mixture model. This comprehensive method aids in identifying unique power consumption patterns among EV owners and outperforms existing models in event detection accuracy. In summary, the research concludes that integrating IoT and deep learning techniques can effectively detect anomalies in residential EV charging and enhance EV load profiling and event detection accuracy. The developed system ensures operational safety and efficiency, contributing to sustainable energy management in smart cities. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=cloud%20computing%20framework" title="cloud computing framework">cloud computing framework</a>, <a href="https://publications.waset.org/abstracts/search?q=recurrent%20neural%20networks" title=" recurrent neural networks"> recurrent neural networks</a>, <a href="https://publications.waset.org/abstracts/search?q=long%20short-term%20memory" title=" long short-term memory"> long short-term memory</a>, <a href="https://publications.waset.org/abstracts/search?q=Iot" title=" Iot"> Iot</a>, <a href="https://publications.waset.org/abstracts/search?q=EV%20charging" title=" EV charging"> EV charging</a>, <a href="https://publications.waset.org/abstracts/search?q=smart%20grids" title=" smart grids"> smart grids</a> </p> <a href="https://publications.waset.org/abstracts/181575/design-of-an-automated-deep-learning-recurrent-neural-networks-system-integrated-with-iot-for-anomaly-detection-in-residential-electric-vehicle-charging-in-smart-cities" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/181575.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">64</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6917</span> Digital Memory plus City Cultural Heritage: The Peking Memory Project Experience</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Huiling%20Feng">Huiling Feng</a>, <a href="https://publications.waset.org/abstracts/search?q=Xiaoshuang%20Jia"> Xiaoshuang Jia</a>, <a href="https://publications.waset.org/abstracts/search?q=Jihong%20Liang"> Jihong Liang</a>, <a href="https://publications.waset.org/abstracts/search?q=Li%20Niu"> Li Niu </a> </p> <p class="card-text"><strong>Abstract:</strong></p> Beijing, formerly romanized as Peking, is the capital of the People's Republic of China and the world's second most populous city proper and most populous capital city. Beijing is a noted historical and cultural whose city history dates back three millennia which is extremely rich in terms of cultural heritage. In 2012, a digital memory project led by Humanistic Beijing Studies Center in Renmin University of China started with the goal to build a total digital collection of knowledge assets about Beijing and represent Beijing memories in new fresh ways. The title of the entire project is ‘Peking Memory Project(PMP)’. The main goal is for safeguarding the documentary heritage and intellectual memory of Beijing, more specifically speaking, from the perspective of historical humanities and public participation, PMP will comprehensively applied digital technologies like digital capture, digital storage, digital process, digital presentation and digital communication to transform different kinds of cultural heritage of Beijing into digital formats that can be stored, re-organized and shared. These digital memories can be interpreted with a new perspective, be organized with a new theme, be presented in a new way and be utilized with a new need. Taking social memory as theoretical basis and digital technologies as tools, PMP is framed with ‘Two Sites and A Repository’. Two sites mean the special website(s) characterized by ‘professional’ and an interactive website characterized by ‘crowdsourcing’. A Repository means the storage pool used for safety long-time preservation of the digital memories. The work of PMP has ultimately helped to highlight the important role in safeguarding the documentary heritage and intellectual memory of Beijing. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=digital%20memory" title="digital memory">digital memory</a>, <a href="https://publications.waset.org/abstracts/search?q=cultural%20heritage" title=" cultural heritage"> cultural heritage</a>, <a href="https://publications.waset.org/abstracts/search?q=digital%20technologies" title=" digital technologies"> digital technologies</a>, <a href="https://publications.waset.org/abstracts/search?q=peking%20memory%20project" title=" peking memory project"> peking memory project</a> </p> <a href="https://publications.waset.org/abstracts/87341/digital-memory-plus-city-cultural-heritage-the-peking-memory-project-experience" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/87341.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">176</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6916</span> The Involvement of Visual and Verbal Representations Within a Quantitative and Qualitative Visual Change Detection Paradigm</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Laura%20Jenkins">Laura Jenkins</a>, <a href="https://publications.waset.org/abstracts/search?q=Tim%20Eschle"> Tim Eschle</a>, <a href="https://publications.waset.org/abstracts/search?q=Joanne%20Ciafone"> Joanne Ciafone</a>, <a href="https://publications.waset.org/abstracts/search?q=Colin%20Hamilton"> Colin Hamilton</a> </p> <p class="card-text"><strong>Abstract:</strong></p> An original working memory model suggested the separation of visual and verbal systems in working memory architecture, in which only visual working memory components were used during visual working memory tasks. It was later suggested that the visuo spatial sketch pad was the only memory component at use during visual working memory tasks, and components such as the phonological loop were not considered. In more recent years, a contrasting approach has been developed with the use of an executive resource to incorporate both visual and verbal representations in visual working memory paradigms. This was supported using research demonstrating the use of verbal representations and an executive resource in a visual matrix patterns task. The aim of the current research is to investigate the working memory architecture during both a quantitative and a qualitative visual working memory task. A dual task method will be used. Three secondary tasks will be used which are designed to hit specific components within the working memory architecture – Dynamic Visual Noise (visual components), Visual Attention (spatial components) and Verbal Attention (verbal components). A comparison of the visual working memory tasks will be made to discover if verbal representations are at use, as the previous literature suggested. This direct comparison has not been made so far in the literature. Considerations will be made as to whether a domain specific approach should be employed when discussing visual working memory tasks, or whether a more domain general approach could be used instead. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=semantic%20organisation" title="semantic organisation">semantic organisation</a>, <a href="https://publications.waset.org/abstracts/search?q=visual%20memory" title=" visual memory"> visual memory</a>, <a href="https://publications.waset.org/abstracts/search?q=change%20detection" title=" change detection"> change detection</a> </p> <a href="https://publications.waset.org/abstracts/22696/the-involvement-of-visual-and-verbal-representations-within-a-quantitative-and-qualitative-visual-change-detection-paradigm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/22696.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">595</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6915</span> Hydrogen: Contention-Aware Hybrid Memory Management for Heterogeneous CPU-GPU Architectures</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yiwei%20Li">Yiwei Li</a>, <a href="https://publications.waset.org/abstracts/search?q=Mingyu%20Gao"> Mingyu Gao</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Integrating hybrid memories with heterogeneous processors could leverage heterogeneity in both compute and memory domains for better system efficiency. To ensure performance isolation, we introduce Hydrogen, a hardware architecture to optimize the allocation of hybrid memory resources to heterogeneous CPU-GPU systems. Hydrogen supports efficient capacity and bandwidth partitioning between CPUs and GPUs in both memory tiers. We propose decoupled memory channel mapping and token-based data migration throttling to enable flexible partitioning. We also support epoch-based online search for optimized configurations and lightweight reconfiguration with reduced data movements. Hydrogen significantly outperforms existing designs by 1.21x on average and up to 1.31x. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=hybrid%20memory" title="hybrid memory">hybrid memory</a>, <a href="https://publications.waset.org/abstracts/search?q=heterogeneous%20systems" title=" heterogeneous systems"> heterogeneous systems</a>, <a href="https://publications.waset.org/abstracts/search?q=dram%20cache" title=" dram cache"> dram cache</a>, <a href="https://publications.waset.org/abstracts/search?q=graphics%20processing%20units" title=" graphics processing units"> graphics processing units</a> </p> <a href="https://publications.waset.org/abstracts/183187/hydrogen-contention-aware-hybrid-memory-management-for-heterogeneous-cpu-gpu-architectures" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/183187.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">96</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6914</span> Contactless Heart Rate Measurement System based on FMCW Radar and LSTM for Automotive Applications</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Asma%20Omri">Asma Omri</a>, <a href="https://publications.waset.org/abstracts/search?q=Iheb%20Sifaoui"> Iheb Sifaoui</a>, <a href="https://publications.waset.org/abstracts/search?q=Sofiane%20Sayahi"> Sofiane Sayahi</a>, <a href="https://publications.waset.org/abstracts/search?q=Hichem%20Besbes"> Hichem Besbes</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Future vehicle systems demand advanced capabilities, notably in-cabin life detection and driver monitoring systems, with a particular emphasis on drowsiness detection. To meet these requirements, several techniques employ artificial intelligence methods based on real-time vital sign measurements. In parallel, Frequency-Modulated Continuous-Wave (FMCW) radar technology has garnered considerable attention in the domains of healthcare and biomedical engineering for non-invasive vital sign monitoring. FMCW radar offers a multitude of advantages, including its non-intrusive nature, continuous monitoring capacity, and its ability to penetrate through clothing. In this paper, we propose a system utilizing the AWR6843AOP radar from Texas Instruments (TI) to extract precise vital sign information. The radar allows us to estimate Ballistocardiogram (BCG) signals, which capture the mechanical movements of the body, particularly the ballistic forces generated by heartbeats and respiration. These signals are rich sources of information about the cardiac cycle, rendering them suitable for heart rate estimation. The process begins with real-time subject positioning, followed by clutter removal, computation of Doppler phase differences, and the use of various filtering methods to accurately capture subtle physiological movements. To address the challenges associated with FMCW radar-based vital sign monitoring, including motion artifacts due to subjects' movement or radar micro-vibrations, Long Short-Term Memory (LSTM) networks are implemented. LSTM's adaptability to different heart rate patterns and ability to handle real-time data make it suitable for continuous monitoring applications. Several crucial steps were taken, including feature extraction (involving amplitude, time intervals, and signal morphology), sequence modeling, heart rate estimation through the analysis of detected cardiac cycles and their temporal relationships, and performance evaluation using metrics such as Root Mean Square Error (RMSE) and correlation with reference heart rate measurements. For dataset construction and LSTM training, a comprehensive data collection system was established, integrating the AWR6843AOP radar, a Heart Rate Belt, and a smart watch for ground truth measurements. Rigorous synchronization of these devices ensured data accuracy. Twenty participants engaged in various scenarios, encompassing indoor and real-world conditions within a moving vehicle equipped with the radar system. Static and dynamic subject’s conditions were considered. The heart rate estimation through LSTM outperforms traditional signal processing techniques that rely on filtering, Fast Fourier Transform (FFT), and thresholding. It delivers an average accuracy of approximately 91% with an RMSE of 1.01 beat per minute (bpm). In conclusion, this paper underscores the promising potential of FMCW radar technology integrated with artificial intelligence algorithms in the context of automotive applications. This innovation not only enhances road safety but also paves the way for its integration into the automotive ecosystem to improve driver well-being and overall vehicular safety. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=ballistocardiogram" title="ballistocardiogram">ballistocardiogram</a>, <a href="https://publications.waset.org/abstracts/search?q=FMCW%20Radar" title=" FMCW Radar"> FMCW Radar</a>, <a href="https://publications.waset.org/abstracts/search?q=vital%20sign%20monitoring" title=" vital sign monitoring"> vital sign monitoring</a>, <a href="https://publications.waset.org/abstracts/search?q=LSTM" title=" LSTM"> LSTM</a> </p> <a href="https://publications.waset.org/abstracts/175052/contactless-heart-rate-measurement-system-based-on-fmcw-radar-and-lstm-for-automotive-applications" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/175052.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">72</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6913</span> Detecting Covid-19 Fake News Using Deep Learning Technique</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=AnjalI%20A.%20Prasad">AnjalI A. Prasad</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Nowadays, social media played an important role in spreading misinformation or fake news. This study analyzes the fake news related to the COVID-19 pandemic spread in social media. This paper aims at evaluating and comparing different approaches that are used to mitigate this issue, including popular deep learning approaches, such as CNN, RNN, LSTM, and BERT algorithm for classification. To evaluate models’ performance, we used accuracy, precision, recall, and F1-score as the evaluation metrics. And finally, compare which algorithm shows better result among the four algorithms. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=BERT" title="BERT">BERT</a>, <a href="https://publications.waset.org/abstracts/search?q=CNN" title=" CNN"> CNN</a>, <a href="https://publications.waset.org/abstracts/search?q=LSTM" title=" LSTM"> LSTM</a>, <a href="https://publications.waset.org/abstracts/search?q=RNN" title=" RNN"> RNN</a> </p> <a href="https://publications.waset.org/abstracts/135210/detecting-covid-19-fake-news-using-deep-learning-technique" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/135210.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">205</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6912</span> Normalizing Logarithms of Realized Volatility in an ARFIMA Model</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=G.%20L.%20C.%20Yap">G. L. C. Yap</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Modelling realized volatility with high-frequency returns is popular as it is an unbiased and efficient estimator of return volatility. A computationally simple model is fitting the logarithms of the realized volatilities with a fractionally integrated long-memory Gaussian process. The Gaussianity assumption simplifies the parameter estimation using the Whittle approximation. Nonetheless, this assumption may not be met in the finite samples and there may be a need to normalize the financial series. Based on the empirical indices S&P500 and DAX, this paper examines the performance of the linear volatility model pre-treated with normalization compared to its existing counterpart. The empirical results show that by including normalization as a pre-treatment procedure, the forecast performance outperforms the existing model in terms of statistical and economic evaluations. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Gaussian%20process" title="Gaussian process">Gaussian process</a>, <a href="https://publications.waset.org/abstracts/search?q=long-memory" title=" long-memory"> long-memory</a>, <a href="https://publications.waset.org/abstracts/search?q=normalization" title=" normalization"> normalization</a>, <a href="https://publications.waset.org/abstracts/search?q=value-at-risk" title=" value-at-risk"> value-at-risk</a>, <a href="https://publications.waset.org/abstracts/search?q=volatility" title=" volatility"> volatility</a>, <a href="https://publications.waset.org/abstracts/search?q=Whittle%20estimator" title=" Whittle estimator"> Whittle estimator</a> </p> <a href="https://publications.waset.org/abstracts/58573/normalizing-logarithms-of-realized-volatility-in-an-arfima-model" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/58573.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">354</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6911</span> On the Impact of Oil Price Fluctuations on Stock Markets: A Multivariate Long-Memory GARCH Framework</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Manel%20Youssef">Manel Youssef</a>, <a href="https://publications.waset.org/abstracts/search?q=Lotfi%20Belkacem"> Lotfi Belkacem</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper employs multivariate long memory GARCH models to simultaneously estimate mean and conditional variance spillover effects between oil prices and different financial markets. Since different financial assets are traded based on these market sector returns, it’s important for financial market participants to understand the volatility transmission mechanism over time and across these series in order to make optimal portfolio allocation decisions. We examine weekly returns from January 1, 2003 to November 30, 2012 and find evidence of significant transmission of shocks and volatilities between oil prices and some of the examined financial markets. The findings support the idea of cross-market hedging and sharing of common information by investors. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=oil%20prices" title="oil prices">oil prices</a>, <a href="https://publications.waset.org/abstracts/search?q=stock%20indices%20returns" title=" stock indices returns"> stock indices returns</a>, <a href="https://publications.waset.org/abstracts/search?q=oil%20volatility" title=" oil volatility"> oil volatility</a>, <a href="https://publications.waset.org/abstracts/search?q=contagion" title=" contagion"> contagion</a>, <a href="https://publications.waset.org/abstracts/search?q=DCC-multivariate%20%28FI%29%20GARCH" title=" DCC-multivariate (FI) GARCH"> DCC-multivariate (FI) GARCH</a> </p> <a href="https://publications.waset.org/abstracts/20756/on-the-impact-of-oil-price-fluctuations-on-stock-markets-a-multivariate-long-memory-garch-framework" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/20756.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">533</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6910</span> Learning outside the Box by Using Memory Techniques Skill: Case Study in Indonesia Memory Sports Council</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Muhammad%20Fajar%20Suardi">Muhammad Fajar Suardi</a>, <a href="https://publications.waset.org/abstracts/search?q=Fathimatufzzahra"> Fathimatufzzahra</a>, <a href="https://publications.waset.org/abstracts/search?q=Dela%20Isnaini%20Sendra"> Dela Isnaini Sendra</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Learning is an activity that has been used to do, especially for a student or academics. But a handful of people have not been using and maximizing their brains work and some also do not know a good brain work time in capturing the lessons, so that knowledge is absorbed is also less than the maximum. Indonesia Memory Sports Council (IMSC) is an institution which is engaged in the performance of the brain and the development of effective learning methods by using several techniques that can be used in considering the lessons and knowledge to grasp well, including: loci method, substitution method, and chain method. This study aims to determine the techniques and benefits of using the method given in learning and memorization by applying memory techniques taught by Indonesia Memory Sports Council (IMSC) to students and the difference if not using this method. This research uses quantitative research with survey method addressed to students of Indonesian Memory Sports Council (IMSC). The results of this study indicate that learn, understand and remember the lesson using the techniques of memory which is taught in Indonesia Memory Sport Council is very effective and faster to absorb the lesson than learning without using the techniques of memory, and this affects the academic achievement of students in each educational institution. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=chain%20method" title="chain method">chain method</a>, <a href="https://publications.waset.org/abstracts/search?q=Indonesia%20memory%20sports%20council" title=" Indonesia memory sports council"> Indonesia memory sports council</a>, <a href="https://publications.waset.org/abstracts/search?q=loci%20method" title=" loci method"> loci method</a>, <a href="https://publications.waset.org/abstracts/search?q=substitution%20method" title=" substitution method"> substitution method</a> </p> <a href="https://publications.waset.org/abstracts/86450/learning-outside-the-box-by-using-memory-techniques-skill-case-study-in-indonesia-memory-sports-council" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/86450.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">290</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6909</span> Tactile Cues and Spatial Navigation in Mice</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Rubaiyea%20Uddin">Rubaiyea Uddin</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The hippocampus, located in the limbic system, is most commonly known for its role in memory and spatial navigation (as cited in Brain Reward and Pathways). It maintains an especially important role in specifically episodic and declarative memory. The hippocampus has also recently been linked to dopamine, the reward pathway’s primary neurotransmitter. Since research has found that dopamine also contributes to memory consolidation and hippocampal plasticity, this neurotransmitter is potentially responsible for contributing to the hippocampus’s role in memory formation. In this experiment we tested to see the effect of tactile cues on spatial navigation for eight different mice. We used a radial arm that had one designated 'reward' arm containing sucrose. The presence or absence of bedding was our tactile cue. We attempted to see if the memory of that cue would enhance the mice’s memory of having received the reward in that arm. The results from our study showed there was no significant response from the use of tactile cues on spatial navigation on our 129 mice. Tactile cues therefore do not influence spatial navigation. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=mice" title="mice">mice</a>, <a href="https://publications.waset.org/abstracts/search?q=radial%20arm%20maze" title=" radial arm maze"> radial arm maze</a>, <a href="https://publications.waset.org/abstracts/search?q=memory" title=" memory"> memory</a>, <a href="https://publications.waset.org/abstracts/search?q=spatial%20navigation" title=" spatial navigation"> spatial navigation</a>, <a href="https://publications.waset.org/abstracts/search?q=tactile%20cues" title=" tactile cues"> tactile cues</a>, <a href="https://publications.waset.org/abstracts/search?q=hippocampus" title=" hippocampus"> hippocampus</a>, <a href="https://publications.waset.org/abstracts/search?q=reward" title=" reward"> reward</a>, <a href="https://publications.waset.org/abstracts/search?q=sensory%20skills" title=" sensory skills"> sensory skills</a>, <a href="https://publications.waset.org/abstracts/search?q=Alzheimer%E2%80%99s" title=" Alzheimer’s"> Alzheimer’s</a>, <a href="https://publications.waset.org/abstracts/search?q=neurodegnerative%20disease" title=" neurodegnerative disease"> neurodegnerative disease</a> </p> <a href="https://publications.waset.org/abstracts/21710/tactile-cues-and-spatial-navigation-in-mice" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/21710.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">649</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6908</span> Promoting Public Participation in the Digital Memory Project: Experience from My Peking Memory Project(MPMP)</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Xiaoshuang%20Jia">Xiaoshuang Jia</a>, <a href="https://publications.waset.org/abstracts/search?q=Huiling%20Feng"> Huiling Feng</a>, <a href="https://publications.waset.org/abstracts/search?q=Li%20Niu"> Li Niu</a>, <a href="https://publications.waset.org/abstracts/search?q=Wei%20Hai"> Wei Hai</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Led by Humanistic Beijing Studies Center in Renmin University of China, My Peking Memory Project(MPMP) is a long-time digital memory project under guarantee of public participation to enable the cultural and intellectual memory of Beijing to be collected, organized, preserved and promoted for discovery and research. Taking digital memory as a new way, MPMP is an important part of Peking Memory Project(PMP) which is aimed at using digital technologies to protect and (re)present the cultural heritage in Beijing. The key outcome of MPMP is the co-building of a total digital collection of knowledge assets about Beijing. Institutional memories are central to Beijing’s collection and consist of the official published documentary content of Beijing. These have already fall under the archival collection purview. The advances in information and communication technology and the knowledge form social memory theory have allowed us to collect more comprehensively beyond institutional collections. It is now possible to engage citizens on a large scale to collect private memories through crowdsourcing in digital formats. Private memories go beyond official published content to include personal narratives, some of which are just in people’s minds until they are captured by MPMP. One aim of MPMP is to engage individuals, communities, groups or institutions who have formed memories and content about Beijing, and would like to contribute them. The project hopes to build a culture of remembering and it believes ‘Every Memory Matters’. Digital memory contribution was achieved through the development of the MPMP. In reducing barriers to digital contribution and promoting high public Participation, MPMP has taken explored the harvesting of transcribe service for digital ingestion, mobile platform and some off-line activities like holding social forum. MPMP has also cooperated with the ‘Implementation Plan of Support Plan for Growth of Talents in Renmin University of China’ to get manpower and intellectual support. After six months of operation, now MPMP have more than 2000 memories added and 7 Special Memory Collections now online. The work of MPMP has ultimately helped to highlight the important role in safeguarding the documentary heritage and intellectual memory of Beijing. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=digital%20memory" title="digital memory">digital memory</a>, <a href="https://publications.waset.org/abstracts/search?q=public%20participation" title=" public participation"> public participation</a>, <a href="https://publications.waset.org/abstracts/search?q=MPMP" title=" MPMP"> MPMP</a>, <a href="https://publications.waset.org/abstracts/search?q=cultural%20heritage" title=" cultural heritage"> cultural heritage</a>, <a href="https://publications.waset.org/abstracts/search?q=collection" title=" collection"> collection</a> </p> <a href="https://publications.waset.org/abstracts/87156/promoting-public-participation-in-the-digital-memory-project-experience-from-my-peking-memory-projectmpmp" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/87156.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">169</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6907</span> Protective Effect of the Histamine H3 Receptor Antagonist DL77 in Behavioral Cognitive Deficits Associated with Schizophrenia</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=B.%20Sadek">B. Sadek</a>, <a href="https://publications.waset.org/abstracts/search?q=N.%20Khan"> N. Khan</a>, <a href="https://publications.waset.org/abstracts/search?q=D.%20%C5%81a%C5%BCewska"> D. Łażewska</a>, <a href="https://publications.waset.org/abstracts/search?q=K.%20Kie%C4%87-Kononowicz"> K. Kieć-Kononowicz</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The eﬀects of the non-imidazole histamine H3 receptor (H3R) antagonist DL77 in passive avoidance paradigm (PAP) and novel object recognition (NOR) task in MK801-induced cognitive deficits associated with schizophrenia (CDS) in adult male rats, and applying donepezil (DOZ) as a reference drug were investigated. The results show that acute systemic administration of DL77 (2.5, 5, and 10 mg/kg, i.p.) significantly improved MK801-induced (0.1 mg/kg, i.p.) memory deficits in PAP. The ameliorating activity of DL77 (5 mg/kg, i.p.) in MK801-induced deficits was partly reversed when rats were pretreated with the centrally-acting H2R antagonist zolantidine (ZOL, 10 mg/kg, i.p.) or with the antimuscarinic antagonist scopolamine (SCO, 0.1 mg/kg, i.p.), but not with the CNS penetrant H1R antagonist pyrilamine (PYR, 10 mg/kg, i.p.). Moreover, the memory enhancing effect of DL77 (5 mg/kg, i.p.) in MK801-induced memory deficits in PAP was strongly reversed when rats were pretreated with a combination of ZOL (10 mg/kg, i.p.) and SCO (1.0 mg/kg, i.p.). Furthermore, the significant ameliorative effect of DL77 (5 mg/kg, i.p.) on MK801-induced long-term memory (LTM) impairment in NOR test was comparable to the DOZ-provided memory-enhancing effect, and was abrogated when animals were pretreated with the histamine H3R agonist R-(α)-methylhistamine (RAMH, 10 mg/kg, i.p.). However, DL77(5 mg/kg, i.p.) failed to provide procognitive effect on MK801-induced short-term memory (STM) impairment in NOR test. In addition, DL77 (5 mg/kg) did not alter anxiety levels and locomotor activity of animals naive to elevated-plus maze (EPM), demonstrating that improved performances with DL77 (5 mg/kg) in PAP or NOR are unrelated to changes in emotional responding or spontaneous locomotor activity. These results provide evidence for the potential of H3Rs for the treatment of neurodegenerative disorders related to impaired memory function, e.g. CDS. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=histamine%20H3%20receptor" title="histamine H3 receptor">histamine H3 receptor</a>, <a href="https://publications.waset.org/abstracts/search?q=antagonist" title=" antagonist"> antagonist</a>, <a href="https://publications.waset.org/abstracts/search?q=learning" title=" learning"> learning</a>, <a href="https://publications.waset.org/abstracts/search?q=memory%20impairment" title=" memory impairment"> memory impairment</a>, <a href="https://publications.waset.org/abstracts/search?q=passive%20avoidance%20paradigm" title=" passive avoidance paradigm"> passive avoidance paradigm</a>, <a href="https://publications.waset.org/abstracts/search?q=novel%20object%20recognition" title=" novel object recognition"> novel object recognition</a> </p> <a href="https://publications.waset.org/abstracts/74343/protective-effect-of-the-histamine-h3-receptor-antagonist-dl77-in-behavioral-cognitive-deficits-associated-with-schizophrenia" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/74343.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">203</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6906</span> A Machine Learning Approach for Earthquake Prediction in Various Zones Based on Solar Activity</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Viacheslav%20Shkuratskyy">Viacheslav Shkuratskyy</a>, <a href="https://publications.waset.org/abstracts/search?q=Aminu%20Bello%20Usman"> Aminu Bello Usman</a>, <a href="https://publications.waset.org/abstracts/search?q=Michael%20O%E2%80%99Dea"> Michael O’Dea</a>, <a href="https://publications.waset.org/abstracts/search?q=Saifur%20Rahman%20Sabuj"> Saifur Rahman Sabuj</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper examines relationships between solar activity and earthquakes; it applied machine learning techniques: K-nearest neighbour, support vector regression, random forest regression, and long short-term memory network. Data from the SILSO World Data Center, the NOAA National Center, the GOES satellite, NASA OMNIWeb, and the United States Geological Survey were used for the experiment. The 23rd and 24th solar cycles, daily sunspot number, solar wind velocity, proton density, and proton temperature were all included in the dataset. The study also examined sunspots, solar wind, and solar flares, which all reflect solar activity and earthquake frequency distribution by magnitude and depth. The findings showed that the long short-term memory network model predicts earthquakes more correctly than the other models applied in the study, and solar activity is more likely to affect earthquakes of lower magnitude and shallow depth than earthquakes of magnitude 5.5 or larger with intermediate depth and deep depth. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=k-nearest%20neighbour" title="k-nearest neighbour">k-nearest neighbour</a>, <a href="https://publications.waset.org/abstracts/search?q=support%20vector%20regression" title=" support vector regression"> support vector regression</a>, <a href="https://publications.waset.org/abstracts/search?q=random%20forest%20regression" title=" random forest regression"> random forest regression</a>, <a href="https://publications.waset.org/abstracts/search?q=long%20short-term%20memory%20network" title=" long short-term memory network"> long short-term memory network</a>, <a href="https://publications.waset.org/abstracts/search?q=earthquakes" title=" earthquakes"> earthquakes</a>, <a href="https://publications.waset.org/abstracts/search?q=solar%20activity" title=" solar activity"> solar activity</a>, <a href="https://publications.waset.org/abstracts/search?q=sunspot%20number" title=" sunspot number"> sunspot number</a>, <a href="https://publications.waset.org/abstracts/search?q=solar%20wind" title=" solar wind"> solar wind</a>, <a href="https://publications.waset.org/abstracts/search?q=solar%20flares" title=" solar flares"> solar flares</a> </p> <a href="https://publications.waset.org/abstracts/170933/a-machine-learning-approach-for-earthquake-prediction-in-various-zones-based-on-solar-activity" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/170933.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">73</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6905</span> Implementation of an Associative Memory Using a Restricted Hopfield Network</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Tet%20H.%20Yeap">Tet H. Yeap</a> </p> <p class="card-text"><strong>Abstract:</strong></p> An analog restricted Hopfield Network is presented in this paper. It consists of two layers of nodes, visible and hidden nodes, connected by directional weighted paths forming a bipartite graph with no intralayer connection. An energy or Lyapunov function was derived to show that the proposed network will converge to stable states. By introducing hidden nodes, the proposed network can be trained to store patterns and has increased memory capacity. Training to be an associative memory, simulation results show that the associative memory performs better than a classical Hopfield network by being able to perform better memory recall when the input is noisy. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=restricted%20Hopfield%20network" title="restricted Hopfield network">restricted Hopfield network</a>, <a href="https://publications.waset.org/abstracts/search?q=Lyapunov%20function" title=" Lyapunov function"> Lyapunov function</a>, <a href="https://publications.waset.org/abstracts/search?q=simultaneous%20perturbation%20stochastic%20approximation" title=" simultaneous perturbation stochastic approximation"> simultaneous perturbation stochastic approximation</a> </p> <a href="https://publications.waset.org/abstracts/122365/implementation-of-an-associative-memory-using-a-restricted-hopfield-network" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/122365.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">133</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6904</span> WormHex: Evidence Retrieval Tool of Social Media from Volatile Memory</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Norah%20Almubairik">Norah Almubairik</a>, <a href="https://publications.waset.org/abstracts/search?q=Wadha%20Almattar"> Wadha Almattar</a>, <a href="https://publications.waset.org/abstracts/search?q=Amani%20Alqarni"> Amani Alqarni</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Social media applications are increasingly being used in our everyday communications. These applications utilise end-to-end encryption mechanisms, which make them suitable tools for criminals to exchange messages. These messages are preserved in the volatile memory until the device is restarted. Therefore, volatile forensics has become an important branch of digital forensics. In this study, the WormHex tool was developed to inspect the memory dump files of Windows and Mac-based workstations. The tool supports digital investigators to extract valuable data written in Arabic and English through web-based WhatsApp and Twitter applications. The results verify that social media applications write their data into the memory regardless of the operating system running the application, with there being no major differences between Windows and Mac. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=volatile%20memory" title="volatile memory">volatile memory</a>, <a href="https://publications.waset.org/abstracts/search?q=REGEX" title=" REGEX"> REGEX</a>, <a href="https://publications.waset.org/abstracts/search?q=digital%20forensics" title=" digital forensics"> digital forensics</a>, <a href="https://publications.waset.org/abstracts/search?q=memory%20acquisition" title=" memory acquisition"> memory acquisition</a> </p> <a href="https://publications.waset.org/abstracts/147426/wormhex-evidence-retrieval-tool-of-social-media-from-volatile-memory" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/147426.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">190</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6903</span> Rheological Modeling for Shape-Memory Thermoplastic Polymers </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=H.%20Hosseini">H. Hosseini</a>, <a href="https://publications.waset.org/abstracts/search?q=B.%20V.%20Berdyshev"> B. V. Berdyshev</a>, <a href="https://publications.waset.org/abstracts/search?q=I.%20Iskopintsev"> I. Iskopintsev</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents a rheological model for producing shape-memory thermoplastic polymers. Shape-memory occurs as a result of internal rearrangement of the structural elements of a polymer. A non-linear viscoelastic model was developed that allows qualitative and quantitative prediction of the stress-strain behavior of shape-memory polymers during heating. This research was done to develop a technique to determine the maximum possible change in size of heat-shrinkable products during heating. The rheological model used in this work was particularly suitable for defining process parameters and constructive parameters of the processing equipment. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=elastic%20deformation" title="elastic deformation">elastic deformation</a>, <a href="https://publications.waset.org/abstracts/search?q=heating" title=" heating"> heating</a>, <a href="https://publications.waset.org/abstracts/search?q=shape-memory%20polymers" title=" shape-memory polymers"> shape-memory polymers</a>, <a href="https://publications.waset.org/abstracts/search?q=stress-strain%20behavior" title=" stress-strain behavior"> stress-strain behavior</a>, <a href="https://publications.waset.org/abstracts/search?q=viscoelastic%20model" title=" viscoelastic model"> viscoelastic model</a> </p> <a href="https://publications.waset.org/abstracts/34080/rheological-modeling-for-shape-memory-thermoplastic-polymers" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/34080.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">323</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6902</span> The Role of Planning and Memory in the Navigational Ability</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Greeshma%20Sharma">Greeshma Sharma</a>, <a href="https://publications.waset.org/abstracts/search?q=Sushil%20Chandra"> Sushil Chandra</a>, <a href="https://publications.waset.org/abstracts/search?q=Vijander%20Singh"> Vijander Singh</a>, <a href="https://publications.waset.org/abstracts/search?q=Alok%20Prakash%20Mittal"> Alok Prakash Mittal</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Navigational ability requires spatial representation, planning, and memory. It covers three interdependent domains, i.e. cognitive and perceptual factors, neural information processing, and variability in brain microstructure. Many attempts have been made to see the role of spatial representation in the navigational ability, and the individual differences have been identified in the neural substrate. But, there is also a need to address the influence of planning, memory on navigational ability. The present study aims to evaluate relations of aforementioned factors in the navigational ability. Total 30 participants volunteered in the study of a virtual shopping complex and subsequently were classified into good and bad navigators based on their performances. The result showed that planning ability was the most correlated factor for the navigational ability and also the discriminating factor between the good and bad navigators. There was also found the correlations between spatial memory recall and navigational ability. However, non-verbal episodic memory and spatial memory recall were also found to be correlated with the learning variable. This study attempts to identify differences between people with more and less navigational ability on the basis of planning and memory. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=memory" title="memory">memory</a>, <a href="https://publications.waset.org/abstracts/search?q=planning%20navigational%20ability" title=" planning navigational ability"> planning navigational ability</a>, <a href="https://publications.waset.org/abstracts/search?q=virtual%20reality" title=" virtual reality"> virtual reality</a> </p> <a href="https://publications.waset.org/abstracts/54114/the-role-of-planning-and-memory-in-the-navigational-ability" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/54114.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">336</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6901</span> Evaluating Language Loss Effect on Autobiographical Memory by Examining Memory Phenomenology in Bilingual Speakers</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Anastasia%20Sorokina">Anastasia Sorokina</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Graduate language loss or attrition has been well documented in individuals who migrate and become emersed in a different language environment. This phenomenon of first language (L1) attrition is an example of non-pathological (not due to trauma) and can manifest itself in frequent pauses, search for words, or grammatical errors. While the widely experienced loss of one’s first language might seem harmless, there is convincing evidence from the disciplines of Developmental Psychology, Bilingual Studies, and even Psychotherapy that language plays a crucial role in the memory of self. In fact, we remember, store, and share personal memories with the help of language. Dual-Coding Theory suggests that language memory code deterioration could lead to forgetting. Yet, no one has investigated a possible connection between language loss and memory. The present study aims to address this research gap by examining a corpus of 1,495 memories of Russian-English bilinguals who are on a continuum of L1 (first language) attrition. Since phenomenological properties capture how well a memory is remembered, the following descriptors were selected - vividness, ease of recall, emotional valence, personal significance, and confidence in the event. A series of linear regression statistical analyses were run to examine the possible negative effects of L1 attrition on autobiographical memory. The results revealed that L1 attrition might compromise perceived vividness and confidence in the event, which is indicative of memory deterioration. These findings suggest the importance of heritage language maintenance in immigrant communities who might be forced to assimilate as language loss might negatively affect the memory of self. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=L1%20attrition" title="L1 attrition">L1 attrition</a>, <a href="https://publications.waset.org/abstracts/search?q=autobiographical%20memory" title=" autobiographical memory"> autobiographical memory</a>, <a href="https://publications.waset.org/abstracts/search?q=language%20loss" title=" language loss"> language loss</a>, <a href="https://publications.waset.org/abstracts/search?q=memory%20phenomenology" title=" memory phenomenology"> memory phenomenology</a>, <a href="https://publications.waset.org/abstracts/search?q=dual%20coding" title=" dual coding"> dual coding</a> </p> <a href="https://publications.waset.org/abstracts/151680/evaluating-language-loss-effect-on-autobiographical-memory-by-examining-memory-phenomenology-in-bilingual-speakers" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/151680.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">119</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6900</span> Hate Speech Detection in Tunisian Dialect</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Helmi%20Baazaoui">Helmi Baazaoui</a>, <a href="https://publications.waset.org/abstracts/search?q=Mounir%20Zrigui"> Mounir Zrigui</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This study addresses the challenge of hate speech detection in Tunisian Arabic text, a critical issue for online safety and moderation. Leveraging the strengths of the AraBERT model, we fine-tuned and evaluated its performance against the Bi-LSTM model across four distinct datasets: T-HSAB, TNHS, TUNIZI-Dataset, and a newly compiled dataset with diverse labels such as Offensive Language, Racism, and Religious Intolerance. Our experimental results demonstrate that AraBERT significantly outperforms Bi-LSTM in terms of Recall, Precision, F1-Score, and Accuracy across all datasets. The findings underline the robustness of AraBERT in capturing the nuanced features of Tunisian Arabic and its superior capability in classification tasks. This research not only advances the technology for hate speech detection but also provides practical implications for social media moderation and policy-making in Tunisia. Future work will focus on expanding the datasets and exploring more sophisticated architectures to further enhance detection accuracy, thus promoting safer online interactions. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=hate%20speech%20detection" title="hate speech detection">hate speech detection</a>, <a href="https://publications.waset.org/abstracts/search?q=Tunisian%20Arabic" title=" Tunisian Arabic"> Tunisian Arabic</a>, <a href="https://publications.waset.org/abstracts/search?q=AraBERT" title=" AraBERT"> AraBERT</a>, <a href="https://publications.waset.org/abstracts/search?q=Bi-LSTM" title=" Bi-LSTM"> Bi-LSTM</a>, <a href="https://publications.waset.org/abstracts/search?q=Gemini%20annotation%20tool" title=" Gemini annotation tool"> Gemini annotation tool</a>, <a href="https://publications.waset.org/abstracts/search?q=social%20media%20moderation" title=" social media moderation"> social media moderation</a> </p> <a href="https://publications.waset.org/abstracts/193877/hate-speech-detection-in-tunisian-dialect" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/193877.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">11</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6899</span> Aspect-Level Sentiment Analysis with Multi-Channel and Graph Convolutional Networks</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jiajun%20Wang">Jiajun Wang</a>, <a href="https://publications.waset.org/abstracts/search?q=Xiaoge%20Li"> Xiaoge Li</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The purpose of the aspect-level sentiment analysis task is to identify the sentiment polarity of aspects in a sentence. Currently, most methods mainly focus on using neural networks and attention mechanisms to model the relationship between aspects and context, but they ignore the dependence of words in different ranges in the sentence, resulting in deviation when assigning relationship weight to other words other than aspect words. To solve these problems, we propose a new aspect-level sentiment analysis model that combines a multi-channel convolutional network and graph convolutional network (GCN). Firstly, the context and the degree of association between words are characterized by Long Short-Term Memory (LSTM) and self-attention mechanism. Besides, a multi-channel convolutional network is used to extract the features of words in different ranges. Finally, a convolutional graph network is used to associate the node information of the dependency tree structure. We conduct experiments on four benchmark datasets. The experimental results are compared with those of other models, which shows that our model is better and more effective. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=aspect-level%20sentiment%20analysis" title="aspect-level sentiment analysis">aspect-level sentiment analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=attention" title=" attention"> attention</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-channel%20convolution%20network" title=" multi-channel convolution network"> multi-channel convolution network</a>, <a href="https://publications.waset.org/abstracts/search?q=graph%20convolution%20network" title=" graph convolution network"> graph convolution network</a>, <a href="https://publications.waset.org/abstracts/search?q=dependency%20tree" title=" dependency tree"> dependency tree</a> </p> <a href="https://publications.waset.org/abstracts/146513/aspect-level-sentiment-analysis-with-multi-channel-and-graph-convolutional-networks" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/146513.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">217</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6898</span> Evidences for Better Recall with Compatible Items in Episodic Memory</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=X.%20Laurent">X. Laurent</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20A.%20Estevez"> M. A. Estevez</a>, <a href="https://publications.waset.org/abstracts/search?q=P.%20Mari-Beffa"> P. Mari-Beffa</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A focus of recent research is to understand the role of our own response goals in the selection of information that will be encoded in episodic memory. For example, if we respond to a target in the presence of distractors, an important aspect under study is whether the distractor and the target share a common response (compatible) or not (incompatible). Some studies have found that compatible objects tend to be groups together and stored in episodic memory, whereas others found that targets in the presence of incompatible distractors are remembered better. Our current research seems to support both views. We used a Tulving-based definition of episodic memory to differentiate memory from episodic and non-episodic traces. In this task, participants first had to classify a blue object as human or animal (target) which appeared in the presence of a green one (distractor) that could belong to the same category of the target (compatible), to the opposite (incompatible) or to an irrelevant one (neutral). Later they had to report the identity (What), location (Where) and time (When) of both target objects (which had been previously responded to) and distractors (which had been ignored). Episodic memory was inferred when the three scene properties (identity, location and time) were correct. The measure of non-episodic memory consisted of those trials in which the identity was correctly remembered, but not the location or time. Our results showed that episodic memory for compatible stimuli is significantly superior to incompatible ones. In sharp contrast, non-episodic measures found superior memory for targets in the presence of incompatible distractors. Our results demonstrate that response compatibility affects the encoding of episodic and non-episodic memory traces in different ways. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=episodic%20memory" title="episodic memory">episodic memory</a>, <a href="https://publications.waset.org/abstracts/search?q=action%20systems" title=" action systems"> action systems</a>, <a href="https://publications.waset.org/abstracts/search?q=compatible%20response" title=" compatible response"> compatible response</a>, <a href="https://publications.waset.org/abstracts/search?q=what-where-when%20task" title=" what-where-when task"> what-where-when task</a> </p> <a href="https://publications.waset.org/abstracts/100701/evidences-for-better-recall-with-compatible-items-in-episodic-memory" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/100701.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">176</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6897</span> Resistive Switching in TaN/AlNx/TiN Cell</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hsin-Ping%20Huang">Hsin-Ping Huang</a>, <a href="https://publications.waset.org/abstracts/search?q=Shyankay%20Jou"> Shyankay Jou</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Resistive switching of aluminum nitride (AlNx) thin film was demonstrated in a TaN/AlNx/TiN memory cell that was prepared by sputter deposition techniques. The memory cell showed bipolar switching of resistance between +3.5 V and –3.5 V. The resistance ratio of high resistance state (HRS) to low resistance state (HRS), RHRS/RLRS, was about 2 over 100 cycles of endurance test. Both the LRS and HRS of the memory cell exhibited ohmic conduction at low voltages and Poole-Frenkel emission at high voltages. The electrical conduction in the TaN/AlNx/TiN memory cell was possibly attributed to the interactions between charges and defects in the AlNx film. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=aluminum%20nitride" title="aluminum nitride">aluminum nitride</a>, <a href="https://publications.waset.org/abstracts/search?q=nonvolatile%20memory" title=" nonvolatile memory"> nonvolatile memory</a>, <a href="https://publications.waset.org/abstracts/search?q=resistive%20switching" title=" resistive switching"> resistive switching</a>, <a href="https://publications.waset.org/abstracts/search?q=thin%20films" title=" thin films"> thin films</a> </p> <a href="https://publications.waset.org/abstracts/7604/resistive-switching-in-tanalnxtin-cell" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/7604.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">399</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6896</span> Molecular Dynamics Simulation on Nanoelectromechanical Graphene Nanoflake Shuttle Device</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Eunae%20Lee">Eunae Lee</a>, <a href="https://publications.waset.org/abstracts/search?q=Oh-Kuen%20Kwon"> Oh-Kuen Kwon</a>, <a href="https://publications.waset.org/abstracts/search?q=Ki-Sub%20Kim"> Ki-Sub Kim</a>, <a href="https://publications.waset.org/abstracts/search?q=Jeong%20Won%20Kang"> Jeong Won Kang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> We investigated the dynamic properties of graphene-nanoribbon (GNR) memory encapsulating graphene-nanoflake (GNF) shuttle in the potential to be applicable as a non-volatile random access memory via molecular dynamics simulations. This work explicitly demonstrates that the GNR encapsulating the GNF shuttle can be applied to nonvolatile memory. The potential well was originated by the increase of the attractive vdW energy between the GNRs when the GNF approached the edges of the GNRs. So the bistable positions were located near the edges of the GNRs. Such a nanoelectromechanical non-volatile memory based on graphene is also applicable to the development of switches, sensors, and quantum computing. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=graphene%20nanoribbon" title="graphene nanoribbon">graphene nanoribbon</a>, <a href="https://publications.waset.org/abstracts/search?q=graphene%20nanoflake" title=" graphene nanoflake"> graphene nanoflake</a>, <a href="https://publications.waset.org/abstracts/search?q=shuttle%20memory" title=" shuttle memory"> shuttle memory</a>, <a href="https://publications.waset.org/abstracts/search?q=molecular%20dynamics" title=" molecular dynamics"> molecular dynamics</a> </p> <a href="https://publications.waset.org/abstracts/37278/molecular-dynamics-simulation-on-nanoelectromechanical-graphene-nanoflake-shuttle-device" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/37278.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">461</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6895</span> Exposure to Tactile Cues Does Not Influence Spatial Navigation in 129 S1/SvLm Mice</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Rubaiyea%20Uddin">Rubaiyea Uddin</a>, <a href="https://publications.waset.org/abstracts/search?q=Rebecca%20Taylor"> Rebecca Taylor</a>, <a href="https://publications.waset.org/abstracts/search?q=Emily%20Levesque"> Emily Levesque</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The hippocampus, located in the limbic system, is most commonly known for its role in memory and spatial navigation (as cited in Brain Reward and Pathways). It maintains an especially important role in specifically episodic and declarative memory. The hippocampus has also recently been linked to dopamine, the reward pathway’s primary neurotransmitter. Since research has found that dopamine also contributes to memory consolidation and hippocampal plasticity, this neurotransmitter is potentially responsible for contributing to the hippocampus’s role in memory formation. In this experiment we tested to see the effect of tactile cues on spatial navigation for eight different mice. We used a radial arm that had one designated “reward” arm containing sucrose. The presence or absence of bedding was our tactile cue. We attempted to see if the memory of that cue would enhance the mice’s memory of having received the reward in that arm. The results from our study showed there was no significant response from the use of tactile cues on spatial navigation on our 129 mice. Tactile cues therefore do not influence spatial navigation. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=mice" title="mice">mice</a>, <a href="https://publications.waset.org/abstracts/search?q=radial%20arm%20maze" title=" radial arm maze"> radial arm maze</a>, <a href="https://publications.waset.org/abstracts/search?q=memory" title=" memory"> memory</a>, <a href="https://publications.waset.org/abstracts/search?q=spatial%20navigation" title=" spatial navigation"> spatial navigation</a>, <a href="https://publications.waset.org/abstracts/search?q=tactile%20cues" title=" tactile cues"> tactile cues</a>, <a href="https://publications.waset.org/abstracts/search?q=hippocampus" title=" hippocampus"> hippocampus</a>, <a href="https://publications.waset.org/abstracts/search?q=reward" title=" reward"> reward</a>, <a href="https://publications.waset.org/abstracts/search?q=sensory%20skills" title=" sensory skills"> sensory skills</a>, <a href="https://publications.waset.org/abstracts/search?q=Alzheimer%27s" title=" Alzheimer's"> Alzheimer's</a>, <a href="https://publications.waset.org/abstracts/search?q=neuro-degenerative%20diseases" title=" neuro-degenerative diseases"> neuro-degenerative diseases</a> </p> <a href="https://publications.waset.org/abstracts/17816/exposure-to-tactile-cues-does-not-influence-spatial-navigation-in-129-s1svlm-mice" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/17816.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">688</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6894</span> Memory and Narratives Rereading before and after One Week</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Abigail%20M.%20Csik">Abigail M. Csik</a>, <a href="https://publications.waset.org/abstracts/search?q=Gabriel%20A.%20Radvansky"> Gabriel A. Radvansky</a> </p> <p class="card-text"><strong>Abstract:</strong></p> As people read through event-based narratives, they construct an event model that captures information about the characters, goals, location, time, and causality. For many reasons, memory for such narratives is represented at different levels, namely, the surface form, textbase, and event model levels. Rereading has been shown to decrease surface form memory, while, at the same time, increasing textbase and event model memories. More generally, distributed practice has consistently shown memory benefits over massed practice for different types of materials, including texts. However, little research has investigated distributed practice of narratives at different inter-study intervals and these effects on these three levels of memory. Recent work in our lab has indicated that there may be dramatic changes in patterns of forgetting around one week, which may affect the three levels of memory. The present experiment aimed to determine the effects of rereading on the three levels of memory as a factor of whether the texts were reread before versus after one week. Participants (N = 42) read a set of stories, re-read them either before or after one week (with an inter-study interval of three days, seven days, or fourteen days), and then took a recognition test, from which the three levels of representation were derived. Signal detection results from this study reveal that differential patterns at the three levels as a factor of whether the narratives were re-read prior to one week or after one week. In particular, an ANOVA revealed that surface form memory was lower (p = .08) while textbase (p = .02) and event model memory (p = .04) were greater if narratives were re-read 14 days later compared to memory when narratives were re-read 3 days later. These results have implications for what type of memory benefits from distributed practice at various inter-study intervals. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=memory" title="memory">memory</a>, <a href="https://publications.waset.org/abstracts/search?q=event%20cognition" title=" event cognition"> event cognition</a>, <a href="https://publications.waset.org/abstracts/search?q=distributed%20practice" title=" distributed practice"> distributed practice</a>, <a href="https://publications.waset.org/abstracts/search?q=consolidation" title=" consolidation"> consolidation</a> </p> <a href="https://publications.waset.org/abstracts/80409/memory-and-narratives-rereading-before-and-after-one-week" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/80409.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">225</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6893</span> Formal Verification of Cache System Using a Novel Cache Memory Model</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Guowei%20Hou">Guowei Hou</a>, <a href="https://publications.waset.org/abstracts/search?q=Lixin%20Yu"> Lixin Yu</a>, <a href="https://publications.waset.org/abstracts/search?q=Wei%20Zhuang"> Wei Zhuang</a>, <a href="https://publications.waset.org/abstracts/search?q=Hui%20Qin"> Hui Qin</a>, <a href="https://publications.waset.org/abstracts/search?q=Xue%20Yang"> Xue Yang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Formal verification is proposed to ensure the correctness of the design and make functional verification more efficient. As cache plays a vital role in the design of System on Chip (SoC), and cache with Memory Management Unit (MMU) and cache memory unit makes the state space too large for simulation to verify, then a formal verification is presented for such system design. In the paper, a formal model checking verification flow is suggested and a new cache memory model which is called “exhaustive search model” is proposed. Instead of using large size ram to denote the whole cache memory, exhaustive search model employs just two cache blocks. For cache system contains data cache (Dcache) and instruction cache (Icache), Dcache memory model and Icache memory model are established separately using the same mechanism. At last, the novel model is employed to the verification of a cache which is module of a custom-built SoC system that has been applied in practical, and the result shows that the cache system is verified correctly using the exhaustive search model, and it makes the verification much more manageable and flexible. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=cache%20system" title="cache system">cache system</a>, <a href="https://publications.waset.org/abstracts/search?q=formal%20verification" title=" formal verification"> formal verification</a>, <a href="https://publications.waset.org/abstracts/search?q=novel%20model" title=" novel model"> novel model</a>, <a href="https://publications.waset.org/abstracts/search?q=system%20on%20chip%20%28SoC%29" title=" system on chip (SoC)"> system on chip (SoC)</a> </p> <a href="https://publications.waset.org/abstracts/26581/formal-verification-of-cache-system-using-a-novel-cache-memory-model" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/26581.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">496</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6892</span> Data Collection Techniques for Robotics to Identify the Facial Expressions of Traumatic Brain Injured Patients</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Chaudhary%20Muhammad%20Aqdus%20Ilyas">Chaudhary Muhammad Aqdus Ilyas</a>, <a href="https://publications.waset.org/abstracts/search?q=Matthias%20Rehm"> Matthias Rehm</a>, <a href="https://publications.waset.org/abstracts/search?q=Kamal%20Nasrollahi"> Kamal Nasrollahi</a>, <a href="https://publications.waset.org/abstracts/search?q=Thomas%20B.%20Moeslund"> Thomas B. Moeslund</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents the investigation of data collection procedures, associated with robots when placed with traumatic brain injured (TBI) patients for rehabilitation purposes through facial expression and mood analysis. Rehabilitation after TBI is very crucial due to nature of injury and variation in recovery time. It is advantageous to analyze these emotional signals in a contactless manner, due to the non-supportive behavior of patients, limited muscle movements and increase in negative emotional expressions. This work aims at the development of framework where robots can recognize TBI emotions through facial expressions to perform rehabilitation tasks by physical, cognitive or interactive activities. The result of these studies shows that with customized data collection strategies, proposed framework identify facial and emotional expressions more accurately that can be utilized in enhancing recovery treatment and social interaction in robotic context. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=computer%20vision" title="computer vision">computer vision</a>, <a href="https://publications.waset.org/abstracts/search?q=convolution%20neural%20network-%20long%20short%20term%20memory%20network%20%28CNN-LSTM%29" title=" convolution neural network- long short term memory network (CNN-LSTM)"> convolution neural network- long short term memory network (CNN-LSTM)</a>, <a href="https://publications.waset.org/abstracts/search?q=facial%20expression%20and%20mood%20recognition" title=" facial expression and mood recognition"> facial expression and mood recognition</a>, <a href="https://publications.waset.org/abstracts/search?q=multimodal%20%28RGB-thermal%29%20analysis" title=" multimodal (RGB-thermal) analysis"> multimodal (RGB-thermal) analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=rehabilitation" title=" rehabilitation"> rehabilitation</a>, <a href="https://publications.waset.org/abstracts/search?q=robots" title=" robots"> robots</a>, <a href="https://publications.waset.org/abstracts/search?q=traumatic%20brain%20injured%20patients" title=" traumatic brain injured patients"> traumatic brain injured patients</a> </p> <a href="https://publications.waset.org/abstracts/98560/data-collection-techniques-for-robotics-to-identify-the-facial-expressions-of-traumatic-brain-injured-patients" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/98560.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">155</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6891</span> One-Step Time Series Predictions with Recurrent Neural Networks</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Vaidehi%20Iyer">Vaidehi Iyer</a>, <a href="https://publications.waset.org/abstracts/search?q=Konstantin%20Borozdin"> Konstantin Borozdin</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Time series prediction problems have many important practical applications, but are notoriously difficult for statistical modeling. Recently, machine learning methods have been attracted significant interest as a practical tool applied to a variety of problems, even though developments in this field tend to be semi-empirical. This paper explores application of Long Short Term Memory based Recurrent Neural Networks to the one-step prediction of time series for both trend and stochastic components. Two types of data are analyzed - daily stock prices, that are often considered to be a typical example of a random walk, - and weather patterns dominated by seasonal variations. Results from both analyses are compared, and reinforced learning framework is used to select more efficient between Recurrent Neural Networks and more traditional auto regression methods. It is shown that both methods are able to follow long-term trends and seasonal variations closely, but have difficulties with reproducing day-to-day variability. Future research directions and potential real world applications are briefly discussed. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=long%20short%20term%20memory" title="long short term memory">long short term memory</a>, <a href="https://publications.waset.org/abstracts/search?q=prediction%20methods" title=" prediction methods"> prediction methods</a>, <a href="https://publications.waset.org/abstracts/search?q=recurrent%20neural%20networks" title=" recurrent neural networks"> recurrent neural networks</a>, <a href="https://publications.waset.org/abstracts/search?q=reinforcement%20learning" title=" reinforcement learning"> reinforcement learning</a> </p> <a href="https://publications.waset.org/abstracts/78110/one-step-time-series-predictions-with-recurrent-neural-networks" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/78110.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">228</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6890</span> Sustainable Renovation and Restoration of the Rural — Based on the View Point of Psychology</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Luo%20Jin%20China">Luo Jin China</a>, <a href="https://publications.waset.org/abstracts/search?q=Jin%20Fang"> Jin Fang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Countryside has been generally recognized and regarded as a characteristic symbol which presents in human memory for a long time. As a result of the change of times, because of it’s failure to meet the growing needs of the growing life and mental decline, the vast rural area began to decline. But their history feature image which accumulated by the ancient tradition provides people with the origins of existence on the spiritual level, such as "identity" and "belonging", makes people closer to the others in the spiritual and psychological aspects of a common experience about the past, thus the sense of a lack of culture caused by the losing of memory symbols is weakened. So, in the modernization process, how to repair its vitality and transform and planning it in a sustainable way has become a hot topics in architectural and urban planning. This paper aims to break the constraints of disciplines, from the perspective of interdiscipline, using the research methods of systems science to analyze and discuss the theories and methods of rural form factors, which based on the viewpoint of memory in psychology. So, we can find a right way to transform the Rural to give full play to the role of the countryside in the actual use and the shape of history spirits. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=rural" title="rural">rural</a>, <a href="https://publications.waset.org/abstracts/search?q=sustainable%20renovation" title=" sustainable renovation"> sustainable renovation</a>, <a href="https://publications.waset.org/abstracts/search?q=restoration" title=" restoration"> restoration</a>, <a href="https://publications.waset.org/abstracts/search?q=psychology" title=" psychology"> psychology</a>, <a href="https://publications.waset.org/abstracts/search?q=memory" title=" memory"> memory</a> </p> <a href="https://publications.waset.org/abstracts/30379/sustainable-renovation-and-restoration-of-the-rural-based-on-the-view-point-of-psychology" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/30379.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">573</span> </span> </div> </div> <ul class="pagination"> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=long%20short-term%20memory%20%28LSTM%29&page=3" rel="prev">&lsaquo;</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=long%20short-term%20memory%20%28LSTM%29&page=1">1</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=long%20short-term%20memory%20%28LSTM%29&page=2">2</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=long%20short-term%20memory%20%28LSTM%29&page=3">3</a></li> <li class="page-item active"><span class="page-link">4</span></li> <li 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