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network</title> <meta name="description" content="Search results for: eco state network"> <meta name="keywords" content="eco state network"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div class="container"> <nav class="navbar navbar-expand-lg navbar-light"> <a class="navbar-brand" href="https://waset.org"> <img src="https://cdn.waset.org/static/images/wasetc.png" alt="Open Science Research Excellence" title="Open Science Research Excellence" /> </a> <button class="d-block d-lg-none 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action="https://publications.waset.org/abstracts/search"> <div id="custom-search-input"> <div class="input-group"> <i class="fas fa-search"></i> <input type="text" class="search-query" name="q" placeholder="Author, Title, Abstract, Keywords" value="eco state network"> <input type="submit" class="btn_search" value="Search"> </div> </div> </form> </div> </div> <div class="row mt-3"> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Commenced</strong> in January 2007</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Frequency:</strong> Monthly</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Edition:</strong> International</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Paper Count:</strong> 11596</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: eco state network</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">11596</span> Modelling the Education Supply Chain with Network Data Envelopment Analysis</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sourour%20Ramzi">Sourour Ramzi</a>, <a href="https://publications.waset.org/abstracts/search?q=Claudia%20Sarrico"> Claudia Sarrico</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Little has been done on network DEA in education, and nobody has attempted to model the whole education supply chain using network DEA. As such the contribution of the present paper is to propose a model for measuring the efficiency of education supply chains using network DEA. First, we use a general survey of data envelopment analysis (DEA) to establish the emergent themes for research in DEA, and focus on the theme of Network DEA. Second, we use a survey on two-stage DEA models, and Network DEA to write a state of the art on Network DEA, particularly applied to supply chain management. Third, we use a survey on DEA applications to establish the most influential papers on DEA education applications, in order to establish the state of the art on applications of DEA in education, in general, and applications of DEA to education using network DEA, in particular. Finally, we propose a model for measuring the performance of education supply chains of different education systems (countries or states within a country, for instance). We then use this model on some empirical data. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=supply%20chain" title="supply chain">supply chain</a>, <a href="https://publications.waset.org/abstracts/search?q=education" title=" education"> education</a>, <a href="https://publications.waset.org/abstracts/search?q=data%20envelopment%20analysis" title=" data envelopment analysis"> data envelopment analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=network%20DEA" title=" network DEA"> network DEA</a> </p> <a href="https://publications.waset.org/abstracts/57510/modelling-the-education-supply-chain-with-network-data-envelopment-analysis" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/57510.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">368</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">11595</span> Survey on Securing the Optimized Link State Routing (OLSR) Protocol in Mobile Ad-hoc Network</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Kimaya%20Subhash%20Gaikwad">Kimaya Subhash Gaikwad</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20B.%20Waykar"> S. B. Waykar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The mobile ad-hoc network (MANET) is collection of various types of nodes. In MANET various protocols are used for communication. In OLSR protocol, a node is selected as multipoint relay (MPR) node which broadcast the messages. As the MANET is open kind of network any malicious node can easily enter into the network and affect the performance of the network. The performance of network mainly depends on the components which are taking part into the communication. If the proper nodes are not selected for the communication then the probability of network being attacked is more. Therefore, it is important to select the more reliable and secure components in the network. MANET does not have any filtering so that only selected nodes can be used for communication. The openness of the MANET makes it easier to attack the communication. The most of the attack are on the Quality of service (QoS) of the network. This paper gives the overview of the various attacks that are possible on OLSR protocol and some solutions. The papers focus mainly on the OLSR protocol. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=communication" title="communication">communication</a>, <a href="https://publications.waset.org/abstracts/search?q=MANET" title=" MANET"> MANET</a>, <a href="https://publications.waset.org/abstracts/search?q=OLSR" title=" OLSR"> OLSR</a>, <a href="https://publications.waset.org/abstracts/search?q=QoS" title=" QoS"> QoS</a> </p> <a href="https://publications.waset.org/abstracts/43772/survey-on-securing-the-optimized-link-state-routing-olsr-protocol-in-mobile-ad-hoc-network" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/43772.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">451</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">11594</span> Replacing an Old PFN System with a Solid State Modulator without Changing the Klystron Transformer</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Klas%20Elmquist">Klas Elmquist</a>, <a href="https://publications.waset.org/abstracts/search?q=Anders%20Larsson"> Anders Larsson</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Until the year 2000, almost all short pulse modulators in the accelerator world were made with the pulse forming network (PFN) technique. The pulse forming network systems have since then been replaced with solid state modulators that have better efficiency, better stability, and lower cost of ownership, and they are much smaller. In this paper, it is shown that it is possible to replace a pulse forming network system with a solid-state system without changing the klystron tank and the klystron transformer. The solid-state modulator uses semiconductors switching at 1 kV level. A first pulse transformer transforms the voltage up to 10 kV. The 10 kV pulse is finally fed into the original transformer that is placed under the klystron. A flatness of 0.8 percent and stability of 100 PPM is achieved. The test is done with a CPI 8262 type of klystron. It is also shown that it is possible to run such a system with long cables between the transformers. When using this technique, it will be possible to keep original sub-systems like filament systems, vacuum systems, focusing solenoid systems, and cooling systems for the klystron. This will substantially reduce the cost of an upgrade and prolong the life of the klystron system. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=modulator" title="modulator">modulator</a>, <a href="https://publications.waset.org/abstracts/search?q=solid-state" title=" solid-state"> solid-state</a>, <a href="https://publications.waset.org/abstracts/search?q=PFN-system" title=" PFN-system"> PFN-system</a>, <a href="https://publications.waset.org/abstracts/search?q=thyratron" title=" thyratron"> thyratron</a> </p> <a href="https://publications.waset.org/abstracts/158666/replacing-an-old-pfn-system-with-a-solid-state-modulator-without-changing-the-klystron-transformer" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/158666.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">134</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">11593</span> Suitable Models and Methods for the Steady-State Analysis of Multi-Energy Networks</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Juan%20Jos%C3%A9%20Mesas">Juan José Mesas</a>, <a href="https://publications.waset.org/abstracts/search?q=Luis%20Sainz"> Luis Sainz</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The motivation for the development of this paper lies in the need for energy networks to reduce losses, improve performance, optimize their operation and try to benefit from the interconnection capacity with other networks enabled for other energy carriers. These interconnections generate interdependencies between some energy networks and others, which requires suitable models and methods for their analysis. Traditionally, the modeling and study of energy networks have been carried out independently for each energy carrier. Thus, there are well-established models and methods for the steady-state analysis of electrical networks, gas networks, and thermal networks separately. What is intended is to extend and combine them adequately to be able to face in an integrated way the steady-state analysis of networks with multiple energy carriers. Firstly, the added value of multi-energy networks, their operation, and the basic principles that characterize them are explained. In addition, two current aspects of great relevance are exposed: the storage technologies and the coupling elements used to interconnect one energy network with another. Secondly, the characteristic equations of the different energy networks necessary to carry out the steady-state analysis are detailed. The electrical network, the natural gas network, and the thermal network of heat and cold are considered in this paper. After the presentation of the equations, a particular case of the steady-state analysis of a specific multi-energy network is studied. This network is represented graphically, the interconnections between the different energy carriers are described, their technical data are exposed and the equations that have previously been presented theoretically are formulated and developed. Finally, the two iterative numerical resolution methods considered in this paper are presented, as well as the resolution procedure and the results obtained. The pros and cons of the application of both methods are explained. It is verified that the results obtained for the electrical network (voltages in modulus and angle), the natural gas network (pressures), and the thermal network (mass flows and temperatures) are correct since they comply with the distribution, operation, consumption and technical characteristics of the multi-energy network under study. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=coupling%20elements" title="coupling elements">coupling elements</a>, <a href="https://publications.waset.org/abstracts/search?q=energy%20carriers" title=" energy carriers"> energy carriers</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-energy%20networks" title=" multi-energy networks"> multi-energy networks</a>, <a href="https://publications.waset.org/abstracts/search?q=steady-state%20analysis" title=" steady-state analysis"> steady-state analysis</a> </p> <a href="https://publications.waset.org/abstracts/162363/suitable-models-and-methods-for-the-steady-state-analysis-of-multi-energy-networks" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/162363.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">79</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">11592</span> Increasing of Resiliency by Using Gas Storage in Iranian Gas Network</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mohsen%20Dourandish">Mohsen Dourandish</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Iran has a huge pipeline network in every state of country which is the longest and vastest pipeline network after Russia and USA (360,000 Km high pressure pipelines and 250,000 Km distribution networks). Furthermore in recent years National Iranian Gas Company is planning to develop natural gas network to cover all cities and villages above 20 families, in a way that 97 percent of Iran population will be gas consumer by 2020. In this condition, network resiliency will be the first priority of NIGC and due to that several planning for increasing resiliency of gas network is under construction. The most important strategy of NIGC is converting tree form pattern network to loop gas networks and developing underground gas storage near main gas consuming centers. In this regard NIGC is planning for construction of over 3500 km high-pressure pipeline and also 10 TCM gas storage capacities in UGSs. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Iranian%20gas%20network" title="Iranian gas network">Iranian gas network</a>, <a href="https://publications.waset.org/abstracts/search?q=peak%20shaving" title=" peak shaving"> peak shaving</a>, <a href="https://publications.waset.org/abstracts/search?q=resiliency" title=" resiliency"> resiliency</a>, <a href="https://publications.waset.org/abstracts/search?q=underground%20gas%20storage" title=" underground gas storage"> underground gas storage</a> </p> <a href="https://publications.waset.org/abstracts/46485/increasing-of-resiliency-by-using-gas-storage-in-iranian-gas-network" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/46485.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">325</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">11591</span> Practical Techniques of Improving State Estimator Solution</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Kiamran%20Radjabli">Kiamran Radjabli</a> </p> <p class="card-text"><strong>Abstract:</strong></p> State Estimator became an intrinsic part of Energy Management Systems (EMS). The SCADA measurements received from the field are processed by the State Estimator in order to accurately determine the actual operating state of the power systems and provide that information to other real-time network applications. All EMS vendors offer a State Estimator functionality in their baseline products. However, setting up and ensuring that State Estimator consistently produces a reliable solution often consumes a substantial engineering effort. This paper provides generic recommendations and describes a simple practical approach to efficient tuning of State Estimator, based on the working experience with major EMS software platforms and consulting projects in many electrical utilities of the USA. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=convergence" title="convergence">convergence</a>, <a href="https://publications.waset.org/abstracts/search?q=monitoring" title=" monitoring"> monitoring</a>, <a href="https://publications.waset.org/abstracts/search?q=state%20estimator" title=" state estimator"> state estimator</a>, <a href="https://publications.waset.org/abstracts/search?q=performance" title=" performance"> performance</a>, <a href="https://publications.waset.org/abstracts/search?q=troubleshooting" title=" troubleshooting"> troubleshooting</a>, <a href="https://publications.waset.org/abstracts/search?q=tuning" title=" tuning"> tuning</a>, <a href="https://publications.waset.org/abstracts/search?q=power%20systems" title=" power systems"> power systems</a> </p> <a href="https://publications.waset.org/abstracts/124338/practical-techniques-of-improving-state-estimator-solution" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/124338.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">156</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">11590</span> Development and State in Brazil: How Do Some Institutions Think and Influence These Issues</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Alessandro%20Andre%20Leme">Alessandro Andre Leme</a> </p> <p class="card-text"><strong>Abstract:</strong></p> To analyze three Brazilian think tanks: a) Fernando Henrique Foundation; b) Celso Furtado International Center; c) Millennium Institute and how they dispute interpretations about the type of development and State that should be adopted in Brazil. We will make use of Network and content analysis of the sites. The analyzes show a dispute that goes from a defense of ultraliberalism to developmentalism, going through a hybrid between State and Market voiced in each of the Think Tanks. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=sociopolitical%20and%20economic%20thinking" title="sociopolitical and economic thinking">sociopolitical and economic thinking</a>, <a href="https://publications.waset.org/abstracts/search?q=development" title=" development"> development</a>, <a href="https://publications.waset.org/abstracts/search?q=strategies" title=" strategies"> strategies</a>, <a href="https://publications.waset.org/abstracts/search?q=intellectuals" title=" intellectuals"> intellectuals</a>, <a href="https://publications.waset.org/abstracts/search?q=state" title=" state"> state</a> </p> <a href="https://publications.waset.org/abstracts/153525/development-and-state-in-brazil-how-do-some-institutions-think-and-influence-these-issues" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/153525.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">151</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">11589</span> Analysis and Prediction of COVID-19 by Using Recurrent LSTM Neural Network Model in Machine Learning</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Grienggrai%20Rajchakit">Grienggrai Rajchakit</a> </p> <p class="card-text"><strong>Abstract:</strong></p> As we all know that coronavirus is announced as a pandemic in the world by WHO. It is speeded all over the world with few days of time. To control this spreading, every citizen maintains social distance and self-preventive measures are the best strategies. As of now, many researchers and scientists are continuing their research in finding out the exact vaccine. The machine learning model finds that the coronavirus disease behaves in an exponential manner. To abolish the consequence of this pandemic, an efficient step should be taken to analyze this disease. In this paper, a recurrent neural network model is chosen to predict the number of active cases in a particular state. To make this prediction of active cases, we need a database. The database of COVID-19 is downloaded from the KAGGLE website and is analyzed by applying a recurrent LSTM neural network with univariant features to predict the number of active cases of patients suffering from the corona virus. The downloaded database is divided into training and testing the chosen neural network model. The model is trained with the training data set and tested with a testing dataset to predict the number of active cases in a particular state; here, we have concentrated on Andhra Pradesh state. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=COVID-19" title="COVID-19">COVID-19</a>, <a href="https://publications.waset.org/abstracts/search?q=coronavirus" title=" coronavirus"> coronavirus</a>, <a href="https://publications.waset.org/abstracts/search?q=KAGGLE" title=" KAGGLE"> KAGGLE</a>, <a href="https://publications.waset.org/abstracts/search?q=LSTM%20neural%20network" title=" LSTM neural network"> LSTM neural network</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/143094/analysis-and-prediction-of-covid-19-by-using-recurrent-lstm-neural-network-model-in-machine-learning" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/143094.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">160</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">11588</span> Tracking Filtering Algorithm Based on ConvLSTM</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ailing%20Yang">Ailing Yang</a>, <a href="https://publications.waset.org/abstracts/search?q=Penghan%20Song"> Penghan Song</a>, <a href="https://publications.waset.org/abstracts/search?q=Aihua%20Cai"> Aihua Cai</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The nonlinear maneuvering target tracking problem is mainly a state estimation problem when the target motion model is uncertain. Traditional solutions include Kalman filtering based on Bayesian filtering framework and extended Kalman filtering. However, these methods need prior knowledge such as kinematics model and state system distribution, and their performance is poor in state estimation of nonprior complex dynamic systems. Therefore, in view of the problems existing in traditional algorithms, a convolution LSTM target state estimation (SAConvLSTM-SE) algorithm based on Self-Attention memory (SAM) is proposed to learn the historical motion state of the target and the error distribution information measured at the current time. The measured track point data of airborne radar are processed into data sets. After supervised training, the data-driven deep neural network based on SAConvLSTM can directly obtain the target state at the next moment. Through experiments on two different maneuvering targets, we find that the network has stronger robustness and better tracking accuracy than the existing tracking methods. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=maneuvering%20target" title="maneuvering target">maneuvering target</a>, <a href="https://publications.waset.org/abstracts/search?q=state%20estimation" title=" state estimation"> state estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=Kalman%20filter" title=" Kalman filter"> Kalman filter</a>, <a href="https://publications.waset.org/abstracts/search?q=LSTM" title=" LSTM"> LSTM</a>, <a href="https://publications.waset.org/abstracts/search?q=self-attention" title=" self-attention"> self-attention</a> </p> <a href="https://publications.waset.org/abstracts/164893/tracking-filtering-algorithm-based-on-convlstm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/164893.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">177</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">11587</span> Reduction of the Number of Traffic Accidents by Function of Driver's Anger Detection</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Masahiro%20Miyaji">Masahiro Miyaji</a> </p> <p class="card-text"><strong>Abstract:</strong></p> When a driver happens to be involved in some traffic congestion or after traffic incidents, the driver may fall in a state of anger. State of anger may encounter decisive risk resulting in severer traffic accidents. Preventive safety function using driver’s psychosomatic state with regard to anger may be one of solutions which would avoid that kind of risks. Identifying driver’s anger state is important to create countermeasures to prevent the risk of traffic accidents. As a first step, this research figured out root cause of traffic incidents by means of using Internet survey. From statistical analysis of the survey, dominant psychosomatic states immediately before traffic incidents were haste, distraction, drowsiness and anger. Then, we replicated anger state of a driver while driving, and then, replicated it by means of using driving simulator on bench test basis. Six types of facial expressions including anger were introduced as alternative characteristics. Kohonen neural network was adopted to classify anger state. Then, we created a methodology to detect anger state of a driver in high accuracy. We presented a driving support safety function. The function adapts driver’s anger state in cooperation with an autonomous driving unit to reduce the number of traffic accidents. Consequently, e evaluated reduction rate of driver’s anger in the traffic accident. To validate the estimation results, we referred the reduction rate of Advanced Safety Vehicle (ASV) as well as Intelligent Transportation Systems (ITS). <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Kohonen%20neural%20network" title="Kohonen neural network">Kohonen neural network</a>, <a href="https://publications.waset.org/abstracts/search?q=driver%E2%80%99s%20anger%20state" title=" driver’s anger state"> driver’s anger state</a>, <a href="https://publications.waset.org/abstracts/search?q=reduction%20of%20traffic%20accidents" title=" reduction of traffic accidents"> reduction of traffic accidents</a>, <a href="https://publications.waset.org/abstracts/search?q=driver%E2%80%99s%20state%20adaptive%20driving%20support%20safety" title=" driver’s state adaptive driving support safety"> driver’s state adaptive driving support safety</a> </p> <a href="https://publications.waset.org/abstracts/48011/reduction-of-the-number-of-traffic-accidents-by-function-of-drivers-anger-detection" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/48011.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">359</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">11586</span> Cellular Traffic Prediction through Multi-Layer Hybrid Network</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Supriya%20H.%20S.">Supriya H. S.</a>, <a href="https://publications.waset.org/abstracts/search?q=Chandrakala%20B.%20M."> Chandrakala B. M.</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Deep learning based models have been recently successful adoption for network traffic prediction. However, training a deep learning model for various prediction tasks is considered one of the critical tasks due to various reasons. This research work develops Multi-Layer Hybrid Network (MLHN) for network traffic prediction and analysis; MLHN comprises the three distinctive networks for handling the different inputs for custom feature extraction. Furthermore, an optimized and efficient parameter-tuning algorithm is introduced to enhance parameter learning. MLHN is evaluated considering the “Big Data Challenge” dataset considering the Mean Absolute Error, Root Mean Square Error and R^2as metrics; furthermore, MLHN efficiency is proved through comparison with a state-of-art approach. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=MLHN" title="MLHN">MLHN</a>, <a href="https://publications.waset.org/abstracts/search?q=network%20traffic%20prediction" title=" network traffic prediction"> network traffic prediction</a> </p> <a href="https://publications.waset.org/abstracts/154887/cellular-traffic-prediction-through-multi-layer-hybrid-network" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/154887.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">89</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">11585</span> Relations of Progression in Cognitive Decline with Initial EEG Resting-State Functional Network in Mild Cognitive Impairment</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Chia-Feng%20Lu">Chia-Feng Lu</a>, <a href="https://publications.waset.org/abstracts/search?q=Yuh-Jen%20Wang"> Yuh-Jen Wang</a>, <a href="https://publications.waset.org/abstracts/search?q=Yu-Te%20Wu"> Yu-Te Wu</a>, <a href="https://publications.waset.org/abstracts/search?q=Sui-Hing%20Yan"> Sui-Hing Yan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This study aimed at investigating whether the functional brain networks constructed using the initial EEG (obtained when patients first visited hospital) can be correlated with the progression of cognitive decline calculated as the changes of mini-mental state examination (MMSE) scores between the latest and initial examinations. We integrated the time–frequency cross mutual information (TFCMI) method to estimate the EEG functional connectivity between cortical regions, and the network analysis based on graph theory to investigate the organization of functional networks in aMCI. Our finding suggested that higher integrated functional network with sufficient connection strengths, dense connection between local regions, and high network efficiency in processing information at the initial stage may result in a better prognosis of the subsequent cognitive functions for aMCI. In conclusion, the functional connectivity can be a useful biomarker to assist in prediction of cognitive declines in aMCI. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=cognitive%20decline" title="cognitive decline">cognitive decline</a>, <a href="https://publications.waset.org/abstracts/search?q=functional%20connectivity" title=" functional connectivity"> functional connectivity</a>, <a href="https://publications.waset.org/abstracts/search?q=MCI" title=" MCI"> MCI</a>, <a href="https://publications.waset.org/abstracts/search?q=MMSE" title=" MMSE"> MMSE</a> </p> <a href="https://publications.waset.org/abstracts/13287/relations-of-progression-in-cognitive-decline-with-initial-eeg-resting-state-functional-network-in-mild-cognitive-impairment" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/13287.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">383</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">11584</span> GIS-Based Topographical Network for Minimum “Exertion” Routing</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Katherine%20Carl%20Payne">Katherine Carl Payne</a>, <a href="https://publications.waset.org/abstracts/search?q=Moshe%20Dror"> Moshe Dror</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The problem of minimum cost routing has been extensively explored in a variety of contexts. While there is a prevalence of routing applications based on least distance, time, and related attributes, exertion-based routing has remained relatively unexplored. In particular, the network structures traditionally used to construct minimum cost paths are not suited to representing exertion or finding paths of least exertion based on road gradient. In this paper, we introduce a topographical network or “topograph” that enables minimum cost routing based on the exertion metric on each arc in a given road network as it is related to changes in road gradient. We describe an algorithm for topograph construction and present the implementation of the topograph on a road network of the state of California with ~22 million nodes. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=topograph" title="topograph">topograph</a>, <a href="https://publications.waset.org/abstracts/search?q=RPE" title=" RPE"> RPE</a>, <a href="https://publications.waset.org/abstracts/search?q=routing" title=" routing"> routing</a>, <a href="https://publications.waset.org/abstracts/search?q=GIS" title=" GIS"> GIS</a> </p> <a href="https://publications.waset.org/abstracts/20618/gis-based-topographical-network-for-minimum-exertion-routing" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/20618.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">546</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">11583</span> Solving the Quadratic Programming Problem Using a Recurrent Neural Network</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=A.%20A.%20Behroozpoor">A. A. Behroozpoor</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20M.%20Mazarei"> M. M. Mazarei </a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, a fuzzy recurrent neural network is proposed for solving the classical quadratic control problem subject to linear equality and bound constraints. The convergence of the state variables of the proposed neural network to achieve solution optimality is guaranteed. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=REFERENCES%20%20%0D%0A%5B1%5D%09Xia" title="REFERENCES [1] Xia">REFERENCES [1] Xia</a>, <a href="https://publications.waset.org/abstracts/search?q=Y" title=" Y"> Y</a>, <a href="https://publications.waset.org/abstracts/search?q=A%20new%20neural%20network%20for%20solving%20linear%20and%20quadratic%20programming%20problems.%20IEEE%20Transactions%20on%20Neural%20Networks" title=" A new neural network for solving linear and quadratic programming problems. IEEE Transactions on Neural Networks"> A new neural network for solving linear and quadratic programming problems. IEEE Transactions on Neural Networks</a>, <a href="https://publications.waset.org/abstracts/search?q=7%286%29" title=" 7(6)"> 7(6)</a>, <a href="https://publications.waset.org/abstracts/search?q=1996" title=" 1996"> 1996</a>, <a href="https://publications.waset.org/abstracts/search?q=pp.1544%E2%80%931548.%0D%0A%5B2%5D%09Xia" title=" pp.1544–1548. [2] Xia"> pp.1544–1548. [2] Xia</a>, <a href="https://publications.waset.org/abstracts/search?q=Y." title=" Y."> Y.</a>, <a href="https://publications.waset.org/abstracts/search?q=%26%20Wang" title=" & Wang"> & Wang</a>, <a href="https://publications.waset.org/abstracts/search?q=J" title=" J"> J</a>, <a href="https://publications.waset.org/abstracts/search?q=A%20recurrent%20neural%20network%20for%20solving%20nonlinear%20convex%20programs%20subject%20to%20linear%20constraints.%20IEEE%20Transactions%20on%20Neural%20Networks" title=" A recurrent neural network for solving nonlinear convex programs subject to linear constraints. IEEE Transactions on Neural Networks"> A recurrent neural network for solving nonlinear convex programs subject to linear constraints. IEEE Transactions on Neural Networks</a>, <a href="https://publications.waset.org/abstracts/search?q=16%282%29" title="16(2)">16(2)</a>, <a href="https://publications.waset.org/abstracts/search?q=2005" title=" 2005"> 2005</a>, <a href="https://publications.waset.org/abstracts/search?q=pp.%20379%E2%80%93386.%0D%0A%5B3%5D%09Xia" title=" pp. 379–386. [3] Xia"> pp. 379–386. [3] Xia</a>, <a href="https://publications.waset.org/abstracts/search?q=Y." title=" Y."> Y.</a>, <a href="https://publications.waset.org/abstracts/search?q=H" title=" H"> H</a>, <a href="https://publications.waset.org/abstracts/search?q=Leung" title=" Leung"> Leung</a>, <a href="https://publications.waset.org/abstracts/search?q=%26%20J" title=" & J"> & J</a>, <a href="https://publications.waset.org/abstracts/search?q=Wang" title=" Wang"> Wang</a>, <a href="https://publications.waset.org/abstracts/search?q=A%20projection%20neural%20network%20and%20its%20application%20to%20constrained%20optimization%20problems.%20IEEE%20Transactions%20Circuits%20and%20Systems-I" title=" A projection neural network and its application to constrained optimization problems. IEEE Transactions Circuits and Systems-I"> A projection neural network and its application to constrained optimization problems. IEEE Transactions Circuits and Systems-I</a>, <a href="https://publications.waset.org/abstracts/search?q=49%284%29" title=" 49(4)"> 49(4)</a>, <a href="https://publications.waset.org/abstracts/search?q=2002" title=" 2002"> 2002</a>, <a href="https://publications.waset.org/abstracts/search?q=pp.447%E2%80%93458.B.%20%0D%0A%5B4%5D%09Q.%20Liu" title=" pp.447–458.B. [4] Q. Liu"> pp.447–458.B. [4] Q. Liu</a>, <a href="https://publications.waset.org/abstracts/search?q=Z.%20Guo" title=" Z. Guo"> Z. Guo</a>, <a href="https://publications.waset.org/abstracts/search?q=J.%20Wang" title=" J. Wang"> J. Wang</a>, <a href="https://publications.waset.org/abstracts/search?q=A%20one-layer%20recurrent%20neural%20network%20for%20constrained%20seudoconvex%20optimization%20and%20its%20application%20for%20dynamic%20portfolio%20optimization.%20Neural%20Networks" title=" A one-layer recurrent neural network for constrained seudoconvex optimization and its application for dynamic portfolio optimization. Neural Networks"> A one-layer recurrent neural network for constrained seudoconvex optimization and its application for dynamic portfolio optimization. Neural Networks</a>, <a href="https://publications.waset.org/abstracts/search?q=26" title=" 26"> 26</a>, <a href="https://publications.waset.org/abstracts/search?q=2012" title=" 2012"> 2012</a>, <a href="https://publications.waset.org/abstracts/search?q=pp.%2099-109." title=" pp. 99-109. "> pp. 99-109. </a> </p> <a href="https://publications.waset.org/abstracts/19435/solving-the-quadratic-programming-problem-using-a-recurrent-neural-network" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/19435.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">644</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">11582</span> MarginDistillation: Distillation for Face Recognition Neural Networks with Margin-Based Softmax</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Svitov%20David">Svitov David</a>, <a href="https://publications.waset.org/abstracts/search?q=Alyamkin%20Sergey"> Alyamkin Sergey</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The usage of convolutional neural networks (CNNs) in conjunction with the margin-based softmax approach demonstrates the state-of-the-art performance for the face recognition problem. Recently, lightweight neural network models trained with the margin-based softmax have been introduced for the face identification task for edge devices. In this paper, we propose a distillation method for lightweight neural network architectures that outperforms other known methods for the face recognition task on LFW, AgeDB-30 and Megaface datasets. The idea of the proposed method is to use class centers from the teacher network for the student network. Then the student network is trained to get the same angles between the class centers and face embeddings predicted by the teacher network. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=ArcFace" title="ArcFace">ArcFace</a>, <a href="https://publications.waset.org/abstracts/search?q=distillation" title=" distillation"> distillation</a>, <a href="https://publications.waset.org/abstracts/search?q=face%20recognition" title=" face recognition"> face recognition</a>, <a href="https://publications.waset.org/abstracts/search?q=margin-based%20softmax" title=" margin-based softmax"> margin-based softmax</a> </p> <a href="https://publications.waset.org/abstracts/127812/margindistillation-distillation-for-face-recognition-neural-networks-with-margin-based-softmax" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/127812.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">146</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">11581</span> Internet of Things: Route Search Optimization Applying Ant Colony Algorithm and Theory of Computer Science</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Tushar%20Bhardwaj">Tushar Bhardwaj</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Internet of Things (IoT) possesses a dynamic network where the network nodes (mobile devices) are added and removed constantly and randomly, hence the traffic distribution in the network is quite variable and irregular. The basic but very important part in any network is route searching. We have many conventional route searching algorithms like link-state, and distance vector algorithms but they are restricted to the static point to point network topology. In this paper we propose a model that uses the Ant Colony Algorithm for route searching. It is dynamic in nature and has positive feedback mechanism that conforms to the route searching. We have also embedded the concept of Non-Deterministic Finite Automata [NDFA] minimization to reduce the network to increase the performance. Results show that Ant Colony Algorithm gives the shortest path from the source to destination node and NDFA minimization reduces the broadcasting storm effectively. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=routing" title="routing">routing</a>, <a href="https://publications.waset.org/abstracts/search?q=ant%20colony%20algorithm" title=" ant colony algorithm"> ant colony algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=NDFA" title=" NDFA"> NDFA</a>, <a href="https://publications.waset.org/abstracts/search?q=IoT" title=" IoT"> IoT</a> </p> <a href="https://publications.waset.org/abstracts/1965/internet-of-things-route-search-optimization-applying-ant-colony-algorithm-and-theory-of-computer-science" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/1965.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">444</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">11580</span> Steady State Analysis of Distribution System with Wind Generation Uncertainity</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Zakir%20Husain">Zakir Husain</a>, <a href="https://publications.waset.org/abstracts/search?q=Neem%20Sagar"> Neem Sagar</a>, <a href="https://publications.waset.org/abstracts/search?q=Neeraj%20Gupta"> Neeraj Gupta</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Due to the increased penetration of renewable energy resources in the distribution system, the system is no longer passive in nature. In this paper, a steady state analysis of the distribution system has been done with the inclusion of wind generation. The modeling of wind turbine generator system and wind generator has been made to obtain the average active and the reactive power injection into the system. The study has been conducted on a IEEE-33 bus system with two wind generators. The present research work is useful not only to utilities but also to customers. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=distributed%20generation" title="distributed generation">distributed generation</a>, <a href="https://publications.waset.org/abstracts/search?q=distribution%20network" title=" distribution network"> distribution network</a>, <a href="https://publications.waset.org/abstracts/search?q=radial%20network" title=" radial network"> radial network</a>, <a href="https://publications.waset.org/abstracts/search?q=wind%20turbine%20generating%20system" title=" wind turbine generating system"> wind turbine generating system</a> </p> <a href="https://publications.waset.org/abstracts/83863/steady-state-analysis-of-distribution-system-with-wind-generation-uncertainity" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/83863.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">407</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">11579</span> A New Realization of Multidimensional System for Grid Sensor Network</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yang%20Xiong">Yang Xiong</a>, <a href="https://publications.waset.org/abstracts/search?q=Hua%20Cheng"> Hua Cheng</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, for the basic problem of wireless sensor network topology control and deployment, the Roesser model in rectangular grid sensor networks is presented. In addition, a general constructive realization procedure will be proposed. The procedure enables a distributed implementation of linear systems on a sensor network. A non-trivial example is illustrated. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=grid%20sensor%20networks" title="grid sensor networks">grid sensor networks</a>, <a href="https://publications.waset.org/abstracts/search?q=Roesser%20model" title=" Roesser model"> Roesser model</a>, <a href="https://publications.waset.org/abstracts/search?q=state-space%20realization" title=" state-space realization"> state-space realization</a>, <a href="https://publications.waset.org/abstracts/search?q=multidimensional%20systems" title=" multidimensional systems"> multidimensional systems</a> </p> <a href="https://publications.waset.org/abstracts/19671/a-new-realization-of-multidimensional-system-for-grid-sensor-network" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/19671.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">655</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">11578</span> IoT: State-of-the-Art and Future Directions</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Bashir%20Abdu%20Muzakkari">Bashir Abdu Muzakkari</a>, <a href="https://publications.waset.org/abstracts/search?q=Aisha%20Umar%20Sulaiman"> Aisha Umar Sulaiman</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohamed%20Afendee%20Muhamad"> Mohamed Afendee Muhamad</a>, <a href="https://publications.waset.org/abstracts/search?q=Sanah%20Abdullahi%20Muaz"> Sanah Abdullahi Muaz</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The field of the Internet of Things (IoT) is rapidly expanding and has the potential to completely change how we work, live, and interact with the world. The Internet of Things (IoT) is the term used to describe a network of networked physical objects, including machinery, vehicles, and buildings, which are equipped with electronics, software, sensors, and network connectivity. This review paper aims to provide a comprehensive overview of the current state of IoT, including its definition, key components, development history, and current applications. The paper will also discuss the challenges and opportunities presented by IoT, as well as its potential impact on various industries, such as healthcare, agriculture, and transportation. In addition, this paper will highlight the ethical and security concerns associated with IoT and the need for effective solutions to address these challenges. The paper concludes by highlighting the prospects of IoT and the directions for future research in this field. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=internet%20of%20things" title="internet of things">internet of things</a>, <a href="https://publications.waset.org/abstracts/search?q=IoT" title=" IoT"> IoT</a>, <a href="https://publications.waset.org/abstracts/search?q=sensors" title=" sensors"> sensors</a>, <a href="https://publications.waset.org/abstracts/search?q=network" title=" network"> network</a> </p> <a href="https://publications.waset.org/abstracts/170950/iot-state-of-the-art-and-future-directions" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/170950.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">174</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">11577</span> Network Security Attacks and Defences</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ranbir%20Singh">Ranbir Singh</a>, <a href="https://publications.waset.org/abstracts/search?q=Deepinder%20Kaur"> Deepinder Kaur</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Network security is an important aspect in every field like government offices, Educational Institute and any business organization. Network security consists of the policies adopted to prevent and monitor forbidden access, misuse, modification, or denial of a computer network. Network security is very complicated subject and deal by only well trained and experienced people. However, as more and more people become wired, an increasing number of people need to understand the basics of security in a networked world. The history of the network security included an introduction to the TCP/IP and interworking. Network security starts with authenticating, commonly with a username and a password. In this paper, we study about various types of attacks on network security and how to handle or prevent this attack. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=network%20security" title="network security">network security</a>, <a href="https://publications.waset.org/abstracts/search?q=attacks" title=" attacks"> attacks</a>, <a href="https://publications.waset.org/abstracts/search?q=denial" title=" denial"> denial</a>, <a href="https://publications.waset.org/abstracts/search?q=authenticating" title=" authenticating"> authenticating</a> </p> <a href="https://publications.waset.org/abstracts/53007/network-security-attacks-and-defences" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/53007.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">404</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">11576</span> Impacts on Marine Ecosystems Using a Multilayer Network Approach</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Nelson%20F.%20F.%20Ebecken">Nelson F. F. Ebecken</a>, <a href="https://publications.waset.org/abstracts/search?q=Gilberto%20C.%20Pereira"> Gilberto C. Pereira</a>, <a href="https://publications.waset.org/abstracts/search?q=Lucio%20P.%20de%20Andrade"> Lucio P. de Andrade</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Bays, estuaries and coastal ecosystems are some of the most used and threatened natural systems globally. Its deterioration is due to intense and increasing human activities. This paper aims to monitor the socio-ecological in Brazil, model and simulate it through a multilayer network representing a DPSIR structure (Drivers, Pressures, States-Impacts-Responses) considering the concept of Management based on Ecosystems to support decision-making under the National/State/Municipal Coastal Management policy. This approach considers several interferences and can represent a significant advance in several scientific aspects. The main objective of this paper is the coupling of three different types of complex networks, the first being an ecological network, the second a social network, and the third a network of economic activities, in order to model the marine ecosystem. Multilayer networks comprise two or more "layers", which may represent different types of interactions, different communities, different points in time, and so on. The dependency between layers results from processes that affect the various layers. For example, the dispersion of individuals between two patches affects the network structure of both samples. A multilayer network consists of (i) a set of physical nodes representing entities (e.g., species, people, companies); (ii) a set of layers, which may include multiple layering aspects (e.g., time dependency and multiple types of relationships); (iii) a set of state nodes, each of which corresponds to the manifestation of a given physical node in a layer-specific; and (iv) a set of edges (weighted or not) to connect the state nodes among themselves. The edge set includes the intralayer edges familiar and interlayer ones, which connect state nodes between layers. The applied methodology in an existent case uses the Flow cytometry process and the modeling of ecological relationships (trophic and non-trophic) following fuzzy theory concepts and graph visualization. The identification of subnetworks in the fuzzy graphs is carried out using a specific computational method. This methodology allows considering the influence of different factors and helps their contributions to the decision-making process. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=marine%20ecosystems" title="marine ecosystems">marine ecosystems</a>, <a href="https://publications.waset.org/abstracts/search?q=complex%20systems" title=" complex systems"> complex systems</a>, <a href="https://publications.waset.org/abstracts/search?q=multilayer%20network" title=" multilayer network"> multilayer network</a>, <a href="https://publications.waset.org/abstracts/search?q=ecosystems%20management" title=" ecosystems management"> ecosystems management</a> </p> <a href="https://publications.waset.org/abstracts/163480/impacts-on-marine-ecosystems-using-a-multilayer-network-approach" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/163480.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">113</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">11575</span> A Video Surveillance System Using an Ensemble of Simple Neural Network Classifiers</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Rodrigo%20S.%20Moreira">Rodrigo S. Moreira</a>, <a href="https://publications.waset.org/abstracts/search?q=Nelson%20F.%20F.%20Ebecken"> Nelson F. F. Ebecken</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper proposes a maritime vessel tracker composed of an ensemble of WiSARD weightless neural network classifiers. A failure detector analyzes vessel movement with a Kalman filter and corrects the tracking, if necessary, using FFT matching. The use of the WiSARD neural network to track objects is uncommon. The additional contributions of the present study include a performance comparison with four state-of-art trackers, an experimental study of the features that improve maritime vessel tracking, the first use of an ensemble of classifiers to track maritime vessels and a new quantization algorithm that compares the values of pixel pairs. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=ram%20memory" title="ram memory">ram memory</a>, <a href="https://publications.waset.org/abstracts/search?q=WiSARD%20weightless%20neural%20network" title=" WiSARD weightless neural network"> WiSARD weightless neural network</a>, <a href="https://publications.waset.org/abstracts/search?q=object%20tracking" title=" object tracking"> object tracking</a>, <a href="https://publications.waset.org/abstracts/search?q=quantization" title=" quantization"> quantization</a> </p> <a href="https://publications.waset.org/abstracts/49928/a-video-surveillance-system-using-an-ensemble-of-simple-neural-network-classifiers" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/49928.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">310</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">11574</span> Altered Network Organization in Mild Alzheimer's Disease Compared to Mild Cognitive Impairment Using Resting-State EEG</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Chia-Feng%20Lu">Chia-Feng Lu</a>, <a href="https://publications.waset.org/abstracts/search?q=Yuh-Jen%20Wang"> Yuh-Jen Wang</a>, <a href="https://publications.waset.org/abstracts/search?q=Shin%20Teng"> Shin Teng</a>, <a href="https://publications.waset.org/abstracts/search?q=Yu-Te%20Wu"> Yu-Te Wu</a>, <a href="https://publications.waset.org/abstracts/search?q=Sui-Hing%20Yan"> Sui-Hing Yan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Brain functional networks based on resting-state EEG data were compared between patients with mild Alzheimer’s disease (mAD) and matched patients with amnestic subtype of mild cognitive impairment (aMCI). We integrated the time–frequency cross mutual information (TFCMI) method to estimate the EEG functional connectivity between cortical regions and the network analysis based on graph theory to further investigate the alterations of functional networks in mAD compared with aMCI group. We aimed at investigating the changes of network integrity, local clustering, information processing efficiency, and fault tolerance in mAD brain networks for different frequency bands based on several topological properties, including degree, strength, clustering coefficient, shortest path length, and efficiency. Results showed that the disruptions of network integrity and reductions of network efficiency in mAD characterized by lower degree, decreased clustering coefficient, higher shortest path length, and reduced global and local efficiencies in the delta, theta, beta2, and gamma bands were evident. The significant changes in network organization can be used in assisting discrimination of mAD from aMCI in clinical. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=EEG" title="EEG">EEG</a>, <a href="https://publications.waset.org/abstracts/search?q=functional%20connectivity" title=" functional connectivity"> functional connectivity</a>, <a href="https://publications.waset.org/abstracts/search?q=graph%20theory" title=" graph theory"> graph theory</a>, <a href="https://publications.waset.org/abstracts/search?q=TFCMI" title=" TFCMI"> TFCMI</a> </p> <a href="https://publications.waset.org/abstracts/13268/altered-network-organization-in-mild-alzheimers-disease-compared-to-mild-cognitive-impairment-using-resting-state-eeg" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/13268.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">431</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">11573</span> An ANN Approach for Detection and Localization of Fatigue Damage in Aircraft Structures</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Reza%20Rezaeipour%20Honarmandzad">Reza Rezaeipour Honarmandzad</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper we propose an ANN for detection and localization of fatigue damage in aircraft structures. We used network of piezoelectric transducers for Lamb-wave measurements in order to calculate damage indices. Data gathered by the sensors was given to neural network classifier. A set of neural network electors of different architecture cooperates to achieve consensus concerning the state of each monitored path. Sensed signal variations in the ROI, detected by the networks at each path, were used to assess the state of the structure as well as to localize detected damage and to filter out ambient changes. The classifier has been extensively tested on large data sets acquired in the tests of specimens with artificially introduced notches as well as the results of numerous fatigue experiments. Effect of the classifier structure and test data used for training on the results was evaluated. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=ANN" title="ANN">ANN</a>, <a href="https://publications.waset.org/abstracts/search?q=fatigue%20damage" title=" fatigue damage"> fatigue damage</a>, <a href="https://publications.waset.org/abstracts/search?q=aircraft%20structures" title=" aircraft structures"> aircraft structures</a>, <a href="https://publications.waset.org/abstracts/search?q=piezoelectric%20transducers" title=" piezoelectric transducers"> piezoelectric transducers</a>, <a href="https://publications.waset.org/abstracts/search?q=lamb-wave%20measurements" title=" lamb-wave measurements"> lamb-wave measurements</a> </p> <a href="https://publications.waset.org/abstracts/29801/an-ann-approach-for-detection-and-localization-of-fatigue-damage-in-aircraft-structures" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/29801.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">417</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">11572</span> An Inverse Optimal Control Approach for the Nonlinear System Design Using ANN</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=M.%20P.%20Nanda%20Kumar">M. P. Nanda Kumar</a>, <a href="https://publications.waset.org/abstracts/search?q=K.%20Dheeraj"> K. Dheeraj</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The design of a feedback controller, so as to minimize a given performance criterion, for a general non-linear dynamical system is difficult; if not impossible. But for a large class of non-linear dynamical systems, the open loop control that minimizes a performance criterion can be obtained using calculus of variations and Pontryagin’s minimum principle. In this paper, the open loop optimal trajectories, that minimizes a given performance measure, is used to train the neural network whose inputs are state variables of non-linear dynamical systems and the open loop optimal control as the desired output. This trained neural network is used as the feedback controller. In other words, attempts are made here to solve the “inverse optimal control problem” by using the state and control trajectories that are optimal in an open loop sense. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=inverse%20optimal%20control" title="inverse optimal control">inverse optimal control</a>, <a href="https://publications.waset.org/abstracts/search?q=radial%20basis%20function" title=" radial basis function"> radial basis function</a>, <a href="https://publications.waset.org/abstracts/search?q=neural%20network" title=" neural network"> neural network</a>, <a href="https://publications.waset.org/abstracts/search?q=controller%20design" title=" controller design"> controller design</a> </p> <a href="https://publications.waset.org/abstracts/9888/an-inverse-optimal-control-approach-for-the-nonlinear-system-design-using-ann" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/9888.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">553</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">11571</span> Enhancing the Network Security with Gray Code</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Thomas%20Adi%20Purnomo%20Sidhi">Thomas Adi Purnomo Sidhi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Nowadays, network is an essential need in almost every part of human daily activities. People now can seamlessly connect to others through the Internet. With advanced technology, our personal data now can be more easily accessed. One of many components we are concerned for delivering the best network is a security issue. This paper is proposing a method that provides more options for security. This research aims to improve network security by focusing on the physical layer which is the first layer of the OSI model. The layer consists of the basic networking hardware transmission technologies of a network. With the use of observation method, the research produces a schematic design for enhancing the network security through the gray code converter. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=network" title="network">network</a>, <a href="https://publications.waset.org/abstracts/search?q=network%20security" title=" network security"> network security</a>, <a href="https://publications.waset.org/abstracts/search?q=grey%20code" title=" grey code"> grey code</a>, <a href="https://publications.waset.org/abstracts/search?q=physical%20layer" title=" physical layer"> physical layer</a> </p> <a href="https://publications.waset.org/abstracts/41361/enhancing-the-network-security-with-gray-code" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/41361.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">504</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">11570</span> Network Functions Virtualization-Based Virtual Routing Function Deployment under Network Delay Constraints</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Kenichiro%20Hida">Kenichiro Hida</a>, <a href="https://publications.waset.org/abstracts/search?q=Shin-Ichi%20Kuribayashi"> Shin-Ichi Kuribayashi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> NFV-based network implements a variety of network functions with software on general-purpose servers, and this allows the network operator to select any capabilities and locations of network functions without any physical constraints. In this paper, we evaluate the influence of the maximum tolerable network delay on the virtual routing function deployment guidelines which the authors proposed previously. Our evaluation results have revealed the following: (1) the more the maximum tolerable network delay condition becomes severe, the more the number of areas where the route selection function is installed increases and the total network cost increases, (2) the higher the routing function cost relative to the circuit bandwidth cost, the increase ratio of total network cost becomes larger according to the maximum tolerable network delay condition. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=NFV%20%28Network%20Functions%20Virtualization%29" title="NFV (Network Functions Virtualization)">NFV (Network Functions Virtualization)</a>, <a href="https://publications.waset.org/abstracts/search?q=resource%20allocation" title=" resource allocation"> resource allocation</a>, <a href="https://publications.waset.org/abstracts/search?q=virtual%20routing%20function" title=" virtual routing function"> virtual routing function</a>, <a href="https://publications.waset.org/abstracts/search?q=minimum%20total%20network%20cost" title=" minimum total network cost"> minimum total network cost</a> </p> <a href="https://publications.waset.org/abstracts/79667/network-functions-virtualization-based-virtual-routing-function-deployment-under-network-delay-constraints" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/79667.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">247</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">11569</span> Performance Analysis of Routing Protocols for WLAN Based Wireless Sensor Networks (WSNs)</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Noman%20Shabbir">Noman Shabbir</a>, <a href="https://publications.waset.org/abstracts/search?q=Roheel%20Nawaz"> Roheel Nawaz</a>, <a href="https://publications.waset.org/abstracts/search?q=Muhammad%20N.%20Iqbal"> Muhammad N. Iqbal</a>, <a href="https://publications.waset.org/abstracts/search?q=Junaid%20Zafar"> Junaid Zafar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper focuses on the performance evaluation of routing protocols in WLAN based Wireless Sensor Networks (WSNs). A comparative analysis of routing protocols such as Ad-hoc On-demand Distance Vector Routing System (AODV), Dynamic Source Routing (DSR) and Optimized Link State Routing (OLSR) is been made against different network parameters like network load, end to end delay and throughput in small, medium and large-scale sensor network scenarios to identify the best performing protocol. Simulation results indicate that OLSR gives minimum network load in all three scenarios while AODV gives the best throughput in small scale network but in medium and large scale networks, DSR is better. In terms of delay, OLSR is more efficient in small and medium scale network while AODV is slightly better in large networks. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=WLAN" title="WLAN">WLAN</a>, <a href="https://publications.waset.org/abstracts/search?q=WSN" title=" WSN"> WSN</a>, <a href="https://publications.waset.org/abstracts/search?q=AODV" title=" AODV"> AODV</a>, <a href="https://publications.waset.org/abstracts/search?q=DSR" title=" DSR"> DSR</a>, <a href="https://publications.waset.org/abstracts/search?q=OLSR" title=" OLSR"> OLSR</a> </p> <a href="https://publications.waset.org/abstracts/48412/performance-analysis-of-routing-protocols-for-wlan-based-wireless-sensor-networks-wsns" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/48412.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">450</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">11568</span> State Estimator Performance Enhancement: Methods for Identifying Errors in Modelling and Telemetry</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=M.%20Ananthakrishnan">M. Ananthakrishnan</a>, <a href="https://publications.waset.org/abstracts/search?q=Sunil%20K%20Patil"> Sunil K Patil</a>, <a href="https://publications.waset.org/abstracts/search?q=Koti%20Naveen"> Koti Naveen</a>, <a href="https://publications.waset.org/abstracts/search?q=Inuganti%20Hemanth%20Kumar"> Inuganti Hemanth Kumar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> State estimation output of EMS forms the base case for all other advanced applications used in real time by a power system operator. Ensuring tuning of state estimator is a repeated process and cannot be left once a good solution is obtained. This paper attempts to demonstrate methods to improve state estimator solution by identifying incorrect modelling and telemetry inputs to the application. In this work, identification of database topology modelling error by plotting static network using node-to-node connection details is demonstrated with examples. Analytical methods to identify wrong transmission parameters, incorrect limits and mistakes in pseudo load and generator modelling are explained with various cases observed. Further, methods used for active and reactive power tuning using bus summation display, reactive power absorption summary, and transformer tap correction are also described. In a large power system, verifying all network static data and modelling parameter on regular basis is difficult .The proposed tuning methods can be easily used by operators to quickly identify errors to obtain the best possible state estimation performance. This, in turn, can lead to improved decision-support capabilities, ultimately enhancing the safety and reliability of the power grid. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=active%20power%20tuning" title="active power tuning">active power tuning</a>, <a href="https://publications.waset.org/abstracts/search?q=database%20modelling" title=" database modelling"> database modelling</a>, <a href="https://publications.waset.org/abstracts/search?q=reactive%20power" title=" reactive power"> reactive power</a>, <a href="https://publications.waset.org/abstracts/search?q=state%20estimator" title=" state estimator"> state estimator</a> </p> <a href="https://publications.waset.org/abstracts/194306/state-estimator-performance-enhancement-methods-for-identifying-errors-in-modelling-and-telemetry" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/194306.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">7</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">11567</span> Optimal and Critical Path Analysis of State Transportation Network Using Neo4J</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Pallavi%20Bhogaram">Pallavi Bhogaram</a>, <a href="https://publications.waset.org/abstracts/search?q=Xiaolong%20Wu"> Xiaolong Wu</a>, <a href="https://publications.waset.org/abstracts/search?q=Min%20He"> Min He</a>, <a href="https://publications.waset.org/abstracts/search?q=Onyedikachi%20Okenwa"> Onyedikachi Okenwa</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A transportation network is a realization of a spatial network, describing a structure which permits either vehicular movement or flow of some commodity. Examples include road networks, railways, air routes, pipelines, and many more. The transportation network plays a vital role in maintaining the vigor of the nation’s economy. Hence, ensuring the network stays resilient all the time, especially in the face of challenges such as heavy traffic loads and large scale natural disasters, is of utmost importance. In this paper, we used the Neo4j application to develop the graph. Neo4j is the world's leading open-source, NoSQL, a native graph database that implements an ACID-compliant transactional backend to applications. The Southern California network model is developed using the Neo4j application and obtained the most critical and optimal nodes and paths in the network using centrality algorithms. The edge betweenness centrality algorithm calculates the critical or optimal paths using Yen's <em>k</em>-shortest paths algorithm, and the node betweenness centrality algorithm calculates the amount of influence a node has over the network. The preliminary study results confirm that the Neo4j application can be a suitable tool to study the important nodes and the critical paths for the major congested metropolitan area. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=critical%20path" title="critical path">critical path</a>, <a href="https://publications.waset.org/abstracts/search?q=transportation%20network" title=" transportation network"> transportation network</a>, <a href="https://publications.waset.org/abstracts/search?q=connectivity%20reliability" title=" connectivity reliability"> connectivity reliability</a>, <a href="https://publications.waset.org/abstracts/search?q=network%20model" title=" network model"> network model</a>, <a href="https://publications.waset.org/abstracts/search?q=Neo4j%20application" title=" Neo4j application"> Neo4j application</a>, <a href="https://publications.waset.org/abstracts/search?q=edge%20betweenness%20centrality%20index" title=" edge betweenness centrality index"> edge betweenness centrality index</a> </p> <a href="https://publications.waset.org/abstracts/127021/optimal-and-critical-path-analysis-of-state-transportation-network-using-neo4j" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/127021.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">134</span> </span> </div> </div> <ul class="pagination"> <li class="page-item disabled"><span class="page-link">&lsaquo;</span></li> <li class="page-item active"><span class="page-link">1</span></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=eco%20state%20network&page=2">2</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=eco%20state%20network&page=3">3</a></li> <li class="page-item"><a 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