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simulated annealing</title> <meta name="description" content="Search results for: neural simulated annealing"> <meta name="keywords" content="neural simulated annealing"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div class="container"> <nav class="navbar navbar-expand-lg navbar-light"> <a class="navbar-brand" href="https://waset.org"> <img src="https://cdn.waset.org/static/images/wasetc.png" alt="Open Science Research Excellence" title="Open Science Research Excellence" /> </a> <button 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action="https://publications.waset.org/abstracts/search"> <div id="custom-search-input"> <div class="input-group"> <i class="fas fa-search"></i> <input type="text" class="search-query" name="q" placeholder="Author, Title, Abstract, Keywords" value="neural simulated annealing"> <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> 3652</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: neural simulated annealing</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3652</span> Reconstruction of Binary Matrices Satisfying Neighborhood Constraints by Simulated Annealing</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Divyesh%20Patel">Divyesh Patel</a>, <a href="https://publications.waset.org/abstracts/search?q=Tanuja%20Srivastava"> Tanuja Srivastava</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper considers the NP-hard problem of reconstructing binary matrices satisfying exactly-1-4-adjacency constraint from its row and column projections. This problem is formulated into a maximization problem. The objective function gives a measure of adjacency constraint for the binary matrices. The maximization problem is solved by the simulated annealing algorithm and experimental results are presented. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=discrete%20tomography" title="discrete tomography">discrete tomography</a>, <a href="https://publications.waset.org/abstracts/search?q=exactly-1-4-adjacency" title=" exactly-1-4-adjacency"> exactly-1-4-adjacency</a>, <a href="https://publications.waset.org/abstracts/search?q=simulated%20annealing" title=" simulated annealing"> simulated annealing</a>, <a href="https://publications.waset.org/abstracts/search?q=binary%20matrices" title=" binary matrices"> binary matrices</a> </p> <a href="https://publications.waset.org/abstracts/8505/reconstruction-of-binary-matrices-satisfying-neighborhood-constraints-by-simulated-annealing" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/8505.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">406</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3651</span> Portfolio Risk Management Using Quantum Annealing</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Thomas%20Doutre">Thomas Doutre</a>, <a href="https://publications.waset.org/abstracts/search?q=Emmanuel%20De%20Meric%20De%20Bellefon"> Emmanuel De Meric De Bellefon</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper describes the application of local-search metaheuristic quantum annealing to portfolio opti- mization. Heuristic technics are particularly handy when Markowitz’ classical Mean-Variance problem is enriched with additional realistic constraints. Once tailored to the problem, computational experiments on real collected data have shown the superiority of quantum annealing over simulated annealing for this constrained optimization problem, taking advantages of quantum effects such as tunnelling. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=optimization" title="optimization">optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=portfolio%20risk%20management" title=" portfolio risk management"> portfolio risk management</a>, <a href="https://publications.waset.org/abstracts/search?q=quantum%20annealing" title=" quantum annealing"> quantum annealing</a>, <a href="https://publications.waset.org/abstracts/search?q=metaheuristic" title=" metaheuristic"> metaheuristic</a> </p> <a href="https://publications.waset.org/abstracts/40564/portfolio-risk-management-using-quantum-annealing" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/40564.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">3650</span> Solving the Wireless Mesh Network Design Problem Using Genetic Algorithm and Simulated Annealing Optimization Methods</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Moheb%20R.%20Girgis">Moheb R. Girgis</a>, <a href="https://publications.waset.org/abstracts/search?q=Tarek%20M.%20Mahmoud"> Tarek M. Mahmoud</a>, <a href="https://publications.waset.org/abstracts/search?q=Bahgat%20A.%20Abdullatif"> Bahgat A. Abdullatif</a>, <a href="https://publications.waset.org/abstracts/search?q=Ahmed%20M.%20Rabie"> Ahmed M. Rabie</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Mesh clients, mesh routers and gateways are components of Wireless Mesh Network (WMN). In WMN, gateways connect to Internet using wireline links and supply Internet access services for users. We usually need multiple gateways, which takes time and costs a lot of money set up, due to the limited wireless channel bit rate. WMN is a highly developed technology that offers to end users a wireless broadband access. It offers a high degree of flexibility contrasted to conventional networks; however, this attribute comes at the expense of a more complex construction. Therefore, a challenge is the planning and optimization of WMNs. In this paper, we concentrate on this challenge using a genetic algorithm and simulated annealing. The genetic algorithm and simulated annealing enable searching for a low-cost WMN configuration with constraints and determine the number of used gateways. Experimental results proved that the performance of the genetic algorithm and simulated annealing in minimizing WMN network costs while satisfying quality of service. The proposed models are presented to significantly outperform the existing solutions. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=wireless%20mesh%20networks" title="wireless mesh networks">wireless mesh networks</a>, <a href="https://publications.waset.org/abstracts/search?q=genetic%20algorithms" title=" genetic algorithms"> genetic algorithms</a>, <a href="https://publications.waset.org/abstracts/search?q=simulated%20annealing" title=" simulated annealing"> simulated annealing</a>, <a href="https://publications.waset.org/abstracts/search?q=topology%20design" title=" topology design"> topology design</a> </p> <a href="https://publications.waset.org/abstracts/11103/solving-the-wireless-mesh-network-design-problem-using-genetic-algorithm-and-simulated-annealing-optimization-methods" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/11103.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">458</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">3649</span> Hybridized Simulated Annealing with Chemical Reaction Optimization for Solving to Sequence Alignment Problem</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ernesto%20Linan">Ernesto Linan</a>, <a href="https://publications.waset.org/abstracts/search?q=Linda%20Cruz"> Linda Cruz</a>, <a href="https://publications.waset.org/abstracts/search?q=Lucero%20Becerra"> Lucero Becerra</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, a new hybridized algorithm based on Chemical Reaction Optimization and Simulated Annealing is proposed to solve the alignment sequence Problem. The Chemical Reaction Optimization is a population-based meta-heuristic algorithm based on the principles of a chemical reaction. Simulated Annealing is applied to solve a large number of combinatorial optimization problems of general-purpose. In this paper, we propose hybridization between Chemical Reaction Optimization algorithm and Simulated Annealing in order to solve the Sequence Alignment Problem. An initial population of molecules is defined at beginning of the proposed algorithm, where each molecule represents a sequence alignment problem. In order to simulate inter-molecule collisions, the process of Chemical Reaction is placed inside the Metropolis Cycle at certain values of temperature. Inside this cycle, change of molecules is done due to collisions; some molecules are accepted by applying Boltzmann probability. The results with the hybrid scheme are better than the results obtained separately. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=chemical%20reaction%20optimization" title="chemical reaction optimization">chemical reaction optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=sequence%20alignment%20problem" title=" sequence alignment problem"> sequence alignment problem</a>, <a href="https://publications.waset.org/abstracts/search?q=simulated%20annealing%20algorithm" title=" simulated annealing algorithm"> simulated annealing algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=metaheuristics" title=" metaheuristics"> metaheuristics</a> </p> <a href="https://publications.waset.org/abstracts/136324/hybridized-simulated-annealing-with-chemical-reaction-optimization-for-solving-to-sequence-alignment-problem" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/136324.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">211</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">3648</span> Optimization of Topology-Aware Job Allocation on a High-Performance Computing Cluster by Neural Simulated Annealing</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Zekang%20Lan">Zekang Lan</a>, <a href="https://publications.waset.org/abstracts/search?q=Yan%20Xu"> Yan Xu</a>, <a href="https://publications.waset.org/abstracts/search?q=Yingkun%20Huang"> Yingkun Huang</a>, <a href="https://publications.waset.org/abstracts/search?q=Dian%20Huang"> Dian Huang</a>, <a href="https://publications.waset.org/abstracts/search?q=Shengzhong%20Feng"> Shengzhong Feng</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Jobs on high-performance computing (HPC) clusters can suffer significant performance degradation due to inter-job network interference. Topology-aware job allocation problem (TJAP) is such a problem that decides how to dedicate nodes to specific applications to mitigate inter-job network interference. In this paper, we study the window-based TJAP on a fat-tree network aiming at minimizing the cost of communication hop, a defined inter-job interference metric. The window-based approach for scheduling repeats periodically, taking the jobs in the queue and solving an assignment problem that maps jobs to the available nodes. Two special allocation strategies are considered, i.e., static continuity assignment strategy (SCAS) and dynamic continuity assignment strategy (DCAS). For the SCAS, a 0-1 integer programming is developed. For the DCAS, an approach called neural simulated algorithm (NSA), which is an extension to simulated algorithm (SA) that learns a repair operator and employs them in a guided heuristic search, is proposed. The efficacy of NSA is demonstrated with a computational study against SA and SCIP. The results of numerical experiments indicate that both the model and algorithm proposed in this paper are effective. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=high-performance%20computing" title="high-performance computing">high-performance computing</a>, <a href="https://publications.waset.org/abstracts/search?q=job%20allocation" title=" job allocation"> job allocation</a>, <a href="https://publications.waset.org/abstracts/search?q=neural%20simulated%20annealing" title=" neural simulated annealing"> neural simulated annealing</a>, <a href="https://publications.waset.org/abstracts/search?q=topology-aware" title=" topology-aware"> topology-aware</a> </p> <a href="https://publications.waset.org/abstracts/160964/optimization-of-topology-aware-job-allocation-on-a-high-performance-computing-cluster-by-neural-simulated-annealing" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/160964.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">118</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">3647</span> Multi-Objective Simulated Annealing Algorithms for Scheduling Just-In-Time Assembly Lines</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ghorbanali%20Mohammadi">Ghorbanali Mohammadi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> New approaches to sequencing mixed-model manufacturing systems are present. These approaches have attracted considerable attention due to their potential to deal with difficult optimization problems. This paper presents Multi-Objective Simulated Annealing Algorithms (MOSAA) approaches to the Just-In-Time (JIT) sequencing problem where workload-smoothing (WL) and the number of set-ups (St) are to be optimized simultaneously. Mixed-model assembly lines are types of production lines where varieties of product models similar in product characteristics are assembled. Moreover, this type of problem is NP-hard. Two annealing methods are proposed to solve the multi-objective problem and find an efficient frontier of all design configurations. The performances of the two methods are tested on several problems from the literature. Experimentation demonstrates the relative desirable performance of the presented methodology. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=scheduling" title="scheduling">scheduling</a>, <a href="https://publications.waset.org/abstracts/search?q=just-in-time" title=" just-in-time"> just-in-time</a>, <a href="https://publications.waset.org/abstracts/search?q=mixed-model%20assembly%20line" title=" mixed-model assembly line"> mixed-model assembly line</a>, <a href="https://publications.waset.org/abstracts/search?q=sequencing" title=" sequencing"> sequencing</a>, <a href="https://publications.waset.org/abstracts/search?q=simulated%20annealing" title=" simulated annealing"> simulated annealing</a> </p> <a href="https://publications.waset.org/abstracts/152223/multi-objective-simulated-annealing-algorithms-for-scheduling-just-in-time-assembly-lines" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/152223.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">128</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3646</span> Solving Weighted Number of Operation Plus Processing Time Due-Date Assignment, Weighted Scheduling and Process Planning Integration Problem Using Genetic and Simulated Annealing Search Methods</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Halil%20Ibrahim%20Demir">Halil Ibrahim Demir</a>, <a href="https://publications.waset.org/abstracts/search?q=Caner%20Erden"> Caner Erden</a>, <a href="https://publications.waset.org/abstracts/search?q=Mumtaz%20Ipek"> Mumtaz Ipek</a>, <a href="https://publications.waset.org/abstracts/search?q=Ozer%20Uygun"> Ozer Uygun</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Traditionally, the three important manufacturing functions, which are process planning, scheduling and due-date assignment, are performed separately and sequentially. For couple of decades, hundreds of studies are done on integrated process planning and scheduling problems and numerous researches are performed on scheduling with due date assignment problem, but unfortunately the integration of these three important functions are not adequately addressed. Here, the integration of these three important functions is studied by using genetic, random-genetic hybrid, simulated annealing, random-simulated annealing hybrid and random search techniques. As well, the importance of the integration of these three functions and the power of meta-heuristics and of hybrid heuristics are studied. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=process%20planning" title="process planning">process planning</a>, <a href="https://publications.waset.org/abstracts/search?q=weighted%20scheduling" title=" weighted scheduling"> weighted scheduling</a>, <a href="https://publications.waset.org/abstracts/search?q=weighted%20due-date%20assignment" title=" weighted due-date assignment"> weighted due-date assignment</a>, <a href="https://publications.waset.org/abstracts/search?q=genetic%20search" title=" genetic search"> genetic search</a>, <a href="https://publications.waset.org/abstracts/search?q=simulated%20annealing" title=" simulated annealing"> simulated annealing</a>, <a href="https://publications.waset.org/abstracts/search?q=hybrid%20meta-heuristics" title=" hybrid meta-heuristics"> hybrid meta-heuristics</a> </p> <a href="https://publications.waset.org/abstracts/57629/solving-weighted-number-of-operation-plus-processing-time-due-date-assignment-weighted-scheduling-and-process-planning-integration-problem-using-genetic-and-simulated-annealing-search-methods" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/57629.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">469</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">3645</span> Model Order Reduction Using Hybrid Genetic Algorithm and Simulated Annealing</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Khaled%20Salah">Khaled Salah</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Model order reduction has been one of the most challenging topics in the past years. In this paper, a hybrid solution of genetic algorithm (GA) and simulated annealing algorithm (SA) are used to approximate high-order transfer functions (TFs) to lower-order TFs. In this approach, hybrid algorithm is applied to model order reduction putting in consideration improving accuracy and preserving the properties of the original model which are two important issues for improving the performance of simulation and computation and maintaining the behavior of the original complex models being reduced. Compared to conventional mathematical methods that have been used to obtain a reduced order model of high order complex models, our proposed method provides better results in terms of reducing run-time. Thus, the proposed technique could be used in electronic design automation (EDA) tools. <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=simulated%20annealing" title=" simulated annealing"> simulated annealing</a>, <a href="https://publications.waset.org/abstracts/search?q=model%20reduction" title=" model reduction"> model reduction</a>, <a href="https://publications.waset.org/abstracts/search?q=transfer%20function" title=" transfer function"> transfer function</a> </p> <a href="https://publications.waset.org/abstracts/97897/model-order-reduction-using-hybrid-genetic-algorithm-and-simulated-annealing" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/97897.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">143</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">3644</span> A Comparison of Sequential Quadratic Programming, Genetic Algorithm, Simulated Annealing, Particle Swarm Optimization for the Design and Optimization of a Beam Column</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Nima%20Khosravi">Nima Khosravi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper describes an integrated optimization technique with concurrent use of sequential quadratic programming, genetic algorithm, and simulated annealing particle swarm optimization for the design and optimization of a beam column. In this research, the comparison between 4 different types of optimization methods. The comparison is done and it is found out that all the methods meet the required constraints and the lowest value of the objective function is achieved by SQP, which was also the fastest optimizer to produce the results. SQP is a gradient based optimizer hence its results are usually the same after every run. The only thing which affects the results is the initial conditions given. The initial conditions given in the various test run were very large as compared. Hence, the value converged at a different point. Rest of the methods is a heuristic method which provides different values for different runs even if every parameter is kept constant. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=beam%20column" title="beam column">beam column</a>, <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=particle%20swarm%20optimization" title=" particle swarm optimization"> particle swarm optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=sequential%20quadratic%20programming" title=" sequential quadratic programming"> sequential quadratic programming</a>, <a href="https://publications.waset.org/abstracts/search?q=simulated%20annealing" title=" simulated annealing"> simulated annealing</a> </p> <a href="https://publications.waset.org/abstracts/58973/a-comparison-of-sequential-quadratic-programming-genetic-algorithm-simulated-annealing-particle-swarm-optimization-for-the-design-and-optimization-of-a-beam-column" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/58973.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">386</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">3643</span> Routing Medical Images with Tabu Search and Simulated Annealing: A Study on Quality of Service</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mej%C3%ADa%20M.%20Paula">Mejía M. Paula</a>, <a href="https://publications.waset.org/abstracts/search?q=Ram%C3%ADrez%20L.%20Leonardo"> Ramírez L. Leonardo</a>, <a href="https://publications.waset.org/abstracts/search?q=Puerta%20A.%20Gabriel"> Puerta A. Gabriel</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In telemedicine, the image repository service is important to increase the accuracy of diagnostic support of medical personnel. This study makes comparison between two routing algorithms regarding the quality of service (QoS), to be able to analyze the optimal performance at the time of loading and/or downloading of medical images. This study focused on comparing the performance of Tabu Search with other heuristic and metaheuristic algorithms that improve QoS in telemedicine services in Colombia. For this, Tabu Search and Simulated Annealing heuristic algorithms are chosen for their high usability in this type of applications; the QoS is measured taking into account the following metrics: Delay, Throughput, Jitter and Latency. In addition, routing tests were carried out on ten images in digital image and communication in medicine (DICOM) format of 40 MB. These tests were carried out for ten minutes with different traffic conditions, reaching a total of 25 tests, from a server of Universidad Militar Nueva Granada (UMNG) in Bogotá-Colombia to a remote user in Universidad de Santiago de Chile (USACH) - Chile. The results show that Tabu search presents a better QoS performance compared to Simulated Annealing, managing to optimize the routing of medical images, a basic requirement to offer diagnostic images services in telemedicine. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=medical%20image" title="medical image">medical image</a>, <a href="https://publications.waset.org/abstracts/search?q=QoS" title=" QoS"> QoS</a>, <a href="https://publications.waset.org/abstracts/search?q=simulated%20annealing" title=" simulated annealing"> simulated annealing</a>, <a href="https://publications.waset.org/abstracts/search?q=Tabu%20search" title=" Tabu search"> Tabu search</a>, <a href="https://publications.waset.org/abstracts/search?q=telemedicine" title=" telemedicine"> telemedicine</a> </p> <a href="https://publications.waset.org/abstracts/99705/routing-medical-images-with-tabu-search-and-simulated-annealing-a-study-on-quality-of-service" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/99705.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">219</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3642</span> Solving Process Planning, Weighted Earliest Due Date Scheduling and Weighted Due Date Assignment Using Simulated Annealing and Evolutionary Strategies</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Halil%20Ibrahim%20Demir">Halil Ibrahim Demir</a>, <a href="https://publications.waset.org/abstracts/search?q=Abdullah%20Hulusi%20Kokcam"> Abdullah Hulusi Kokcam</a>, <a href="https://publications.waset.org/abstracts/search?q=Fuat%20Simsir"> Fuat Simsir</a>, <a href="https://publications.waset.org/abstracts/search?q=%C3%96zer%20Uygun"> Özer Uygun</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Traditionally, three important manufacturing functions which are process planning, scheduling and due-date assignment are performed sequentially and separately. Although there are numerous works on the integration of process planning and scheduling and plenty of works focusing on scheduling with due date assignment, there are only a few works on integrated process planning, scheduling and due-date assignment. Although due-dates are determined without taking into account of weights of the customers in the literature, here weighted due-date assignment is employed to get better performance. Jobs are scheduled according to weighted earliest due date dispatching rule and due dates are determined according to some popular due date assignment methods by taking into account of the weights of each job. Simulated Annealing, Evolutionary Strategies, Random Search, hybrid of Random Search and Simulated Annealing, and hybrid of Random Search and Evolutionary Strategies, are applied as solution techniques. Three important manufacturing functions are integrated step-by-step and higher integration levels are found better. Search meta-heuristics are found to be very useful while improving performance measure. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=process%20planning" title="process planning">process planning</a>, <a href="https://publications.waset.org/abstracts/search?q=weighted%20scheduling" title=" weighted scheduling"> weighted scheduling</a>, <a href="https://publications.waset.org/abstracts/search?q=weighted%20due-date%20assignment" title=" weighted due-date assignment"> weighted due-date assignment</a>, <a href="https://publications.waset.org/abstracts/search?q=simulated%20annealing" title=" simulated annealing"> simulated annealing</a>, <a href="https://publications.waset.org/abstracts/search?q=evolutionary%20strategies" title=" evolutionary strategies"> evolutionary strategies</a>, <a href="https://publications.waset.org/abstracts/search?q=hybrid%20searches" title=" hybrid searches"> hybrid searches</a> </p> <a href="https://publications.waset.org/abstracts/67706/solving-process-planning-weighted-earliest-due-date-scheduling-and-weighted-due-date-assignment-using-simulated-annealing-and-evolutionary-strategies" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/67706.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">462</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">3641</span> Application of Simulated Annealing to Threshold Optimization in Distributed OS-CFAR System </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=L.%20Abdou">L. Abdou</a>, <a href="https://publications.waset.org/abstracts/search?q=O.%20Taibaoui"> O. Taibaoui</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20Moumen"> A. Moumen</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20Talib%20Ahmed">A. Talib Ahmed</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper proposes an application of the simulated annealing to optimize the detection threshold in an ordered statistics constant false alarm rate (OS-CFAR) system. Using conventional optimization methods, such as the conjugate gradient, can lead to a local optimum and lose the global optimum. Also for a system with a number of sensors that is greater than or equal to three, it is difficult or impossible to find this optimum; Hence, the need to use other methods, such as meta-heuristics. From a variety of meta-heuristic techniques, we can find the simulated annealing (SA) method, inspired from a process used in metallurgy. This technique is based on the selection of an initial solution and the generation of a near solution randomly, in order to improve the criterion to optimize. In this work, two parameters will be subject to such optimisation and which are the statistical order (k) and the scaling factor (T). Two fusion rules; “AND” and “OR” were considered in the case where the signals are independent from sensor to sensor. The results showed that the application of the proposed method to the problem of optimisation in a distributed system is efficiency to resolve such problems. The advantage of this method is that it allows to browse the entire solutions space and to avoid theoretically the stagnation of the optimization process in an area of local minimum. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=distributed%20system" title="distributed system">distributed system</a>, <a href="https://publications.waset.org/abstracts/search?q=OS-CFAR%20system" title=" OS-CFAR system"> OS-CFAR system</a>, <a href="https://publications.waset.org/abstracts/search?q=independent%20sensors" title=" independent sensors"> independent sensors</a>, <a href="https://publications.waset.org/abstracts/search?q=simulating%20annealing" title=" simulating annealing"> simulating annealing</a> </p> <a href="https://publications.waset.org/abstracts/22281/application-of-simulated-annealing-to-threshold-optimization-in-distributed-os-cfar-system" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/22281.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">497</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">3640</span> Fault Location Identification in High Voltage Transmission Lines </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Khaled%20M.%20El%20Naggar">Khaled M. El Naggar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper introduces a digital method for fault section identification in transmission lines. The method uses digital set of the measured short circuit current to locate faults in electrical power systems. The digitized current is used to construct a set of overdetermined system of equations. The problem is then constructed and solved using the proposed digital optimization technique to find the fault distance. The proposed optimization methodology is an application of simulated annealing optimization technique. The method is tested using practical case study to evaluate the proposed method. The accurate results obtained show that the algorithm can be used as a powerful tool in the area of power system protection. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=optimization" title="optimization">optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=estimation" title=" estimation"> estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=faults" title=" faults"> faults</a>, <a href="https://publications.waset.org/abstracts/search?q=measurement" title=" measurement"> measurement</a>, <a href="https://publications.waset.org/abstracts/search?q=high%20voltage" title=" high voltage"> high voltage</a>, <a href="https://publications.waset.org/abstracts/search?q=simulated%20annealing" title=" simulated annealing"> simulated annealing</a> </p> <a href="https://publications.waset.org/abstracts/81165/fault-location-identification-in-high-voltage-transmission-lines" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/81165.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">393</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">3639</span> Hybrid Approach for the Min-Interference Frequency Assignment</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=F.%20Debbat">F. Debbat</a>, <a href="https://publications.waset.org/abstracts/search?q=F.%20T.%20Bendimerad"> F. T. Bendimerad</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The efficient frequency assignment for radio communications becomes more and more crucial when developing new information technologies and their applications. It is consists in defining an assignment of frequencies to radio links, to be established between base stations and mobile transmitters. Separation of the frequencies assigned is necessary to avoid interference. However, unnecessary separation causes an excess requirement for spectrum, the cost of which may be very high. This problem is NP-hard problem which cannot be solved by conventional optimization algorithms. It is therefore necessary to use metaheuristic methods to solve it. This paper proposes Hybrid approach based on simulated annealing (SA) and Tabu Search (TS) methods to solve this problem. Computational results, obtained on a number of standard problem instances, testify the effectiveness of the proposed approach. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=cellular%20mobile%20communication" title="cellular mobile communication">cellular mobile communication</a>, <a href="https://publications.waset.org/abstracts/search?q=frequency%20assignment%20problem" title=" frequency assignment problem"> frequency assignment problem</a>, <a href="https://publications.waset.org/abstracts/search?q=optimization" title=" optimization"> optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=tabu%20search" title=" tabu search"> tabu search</a>, <a href="https://publications.waset.org/abstracts/search?q=simulated%20annealing" title=" simulated annealing"> simulated annealing</a> </p> <a href="https://publications.waset.org/abstracts/14250/hybrid-approach-for-the-min-interference-frequency-assignment" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/14250.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">385</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">3638</span> Mathematical Modeling and Algorithms for the Capacitated Facility Location and Allocation Problem with Emission Restriction</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sagar%20Hedaoo">Sagar Hedaoo</a>, <a href="https://publications.waset.org/abstracts/search?q=Fazle%20Baki"> Fazle Baki</a>, <a href="https://publications.waset.org/abstracts/search?q=Ahmed%20Azab"> Ahmed Azab</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In supply chain management, network design for scalable manufacturing facilities is an emerging field of research. Facility location allocation assigns facilities to customers to optimize the overall cost of the supply chain. To further optimize the costs, capacities of these facilities can be changed in accordance with customer demands. A mathematical model is formulated to fully express the problem at hand and to solve small-to-mid range instances. A dedicated constraint has been developed to restrict emissions in line with the Kyoto protocol. This problem is NP-Hard; hence, a simulated annealing metaheuristic has been developed to solve larger instances. A case study on the USA-Canada cross border crossing is used. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=emission" title="emission">emission</a>, <a href="https://publications.waset.org/abstracts/search?q=mixed%20integer%20linear%20programming" title=" mixed integer linear programming"> mixed integer linear programming</a>, <a href="https://publications.waset.org/abstracts/search?q=metaheuristic" title=" metaheuristic"> metaheuristic</a>, <a href="https://publications.waset.org/abstracts/search?q=simulated%20annealing" title=" simulated annealing"> simulated annealing</a> </p> <a href="https://publications.waset.org/abstracts/58472/mathematical-modeling-and-algorithms-for-the-capacitated-facility-location-and-allocation-problem-with-emission-restriction" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/58472.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">309</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">3637</span> Enhancement in Seebeck Coefficient of MBE Grown Un-Doped ZnO by Thermal Annealing</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=M.%20Asghar">M. Asghar</a>, <a href="https://publications.waset.org/abstracts/search?q=K.%20Mahmood"> K. Mahmood</a>, <a href="https://publications.waset.org/abstracts/search?q=F.%20Malik"> F. Malik</a>, <a href="https://publications.waset.org/abstracts/search?q=Lu%20Na"> Lu Na</a>, <a href="https://publications.waset.org/abstracts/search?q=Y-H%20Xie"> Y-H Xie</a>, <a href="https://publications.waset.org/abstracts/search?q=Yasin%20A.%20Raja"> Yasin A. Raja</a>, <a href="https://publications.waset.org/abstracts/search?q=I.%20Ferguson"> I. Ferguson</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we have reported an enhancement in Seebeck coefficient of un-doped zinc oxide (ZnO) grown by molecular beam epitaxy (MBE) on silicon (001) substrate by annealing treatment. The grown ZnO thin films were annealed in oxygen environment at 500°C – 800°C, keeping a step of 100°C for one hour. Room temperature Seebeck measurements showed that Seebeck coefficient and power factor increased from 222 to 510 µV/K and 8.8×10^-6 to 2.6×10^-4 Wm^-1K^-2 as annealing temperature increased from 500°C to 800°C respectively. This is the highest value of Seebeck coefficient ever reported for un-doped MBE grown ZnO according to best of our knowledge. This observation was related with the improvement of crystal structure of grown films with annealing temperature. X-ray diffraction (XRD) results demonstrated that full width half maximum (FWHM) of ZnO (002) plane decreased and crystalline size increased as the annealing temperature increased. Photoluminescence study revealed that the intensity of band edge emission increased and defect emission decreased as annealing temperature increased because the density of oxygen vacancy related donor defects decreased with annealing temperature. This argument was further justified by the Hall measurements which showed a decreasing trend of carrier concentration with annealing temperature. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=ZnO" title="ZnO">ZnO</a>, <a href="https://publications.waset.org/abstracts/search?q=MBE" title=" MBE"> MBE</a>, <a href="https://publications.waset.org/abstracts/search?q=thermoelectric%20properties" title=" thermoelectric properties"> thermoelectric properties</a>, <a href="https://publications.waset.org/abstracts/search?q=annealing%20temperature" title=" annealing temperature"> annealing temperature</a>, <a href="https://publications.waset.org/abstracts/search?q=crystal%20structure" title=" crystal structure"> crystal structure</a> </p> <a href="https://publications.waset.org/abstracts/6667/enhancement-in-seebeck-coefficient-of-mbe-grown-un-doped-zno-by-thermal-annealing" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/6667.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">445</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">3636</span> Resistive Switching Characteristics of Resistive Random Access Memory Devices after Furnace Annealing Processes</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Chi-Yan%20Chu">Chi-Yan Chu</a>, <a href="https://publications.waset.org/abstracts/search?q=Kai-Chi%20Chuang"> Kai-Chi Chuang</a>, <a href="https://publications.waset.org/abstracts/search?q=Huang-Chung%20Cheng"> Huang-Chung Cheng</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this study, the RRAM devices with the TiN/Ti/HfO<sub>x</sub>/TiN structure were fabricated, then the electrical characteristics of the devices without annealing and after 400 °C and 500 °C of the furnace annealing (FA) temperature processes were compared. The RRAM devices after the FA’s 400 °C showed the lower forming, set and reset voltages than the other devices without annealing. However, the RRAM devices after the FA’s 500 °C did not show any electrical characteristics because the TiN/Ti/HfO<sub>x</sub>/TiN device was oxidized, as shown in the XPS analysis. From these results, the RRAM devices after the FA’s 400 °C showed the best electrical characteristics. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=RRAM" title="RRAM">RRAM</a>, <a href="https://publications.waset.org/abstracts/search?q=furnace%20annealing%20%28FA%29" title=" furnace annealing (FA)"> furnace annealing (FA)</a>, <a href="https://publications.waset.org/abstracts/search?q=forming" title=" forming"> forming</a>, <a href="https://publications.waset.org/abstracts/search?q=set%20and%20reset%20voltages" title=" set and reset voltages"> set and reset voltages</a>, <a href="https://publications.waset.org/abstracts/search?q=XPS" title=" XPS"> XPS</a> </p> <a href="https://publications.waset.org/abstracts/58560/resistive-switching-characteristics-of-resistive-random-access-memory-devices-after-furnace-annealing-processes" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/58560.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">371</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">3635</span> Scheduling Tasks in Embedded Systems Based on NoC Architecture</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=D.%20Dorota">D. Dorota</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents a method to generate and schedule task in the architecture of embedded systems based on the simulated annealing. This method takes into account the attribute of divisibility of tasks. A proposal represents the process in the form of trees. Despite the fact that the architecture of Network-on-Chip (NoC) is an interesting alternative to a bus architecture based on multi-processors systems, it requires a lot of work that ensures the optimization of communication. This paper proposes an effective approach to generate dedicated NoC topology solving communication problems. Network NoC is generated taking into account the energy consumption and resource issues. Ultimately generated is minimal, dedicated NoC topology. The proposed solution is assumed to be a simple router design and the minimum number of lines. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Network-on-Chip" title="Network-on-Chip">Network-on-Chip</a>, <a href="https://publications.waset.org/abstracts/search?q=NoC-based%20embedded%20systems" title=" NoC-based embedded systems"> NoC-based embedded systems</a>, <a href="https://publications.waset.org/abstracts/search?q=scheduling%20task%20in%20embedded%20systems" title=" scheduling task in embedded systems"> scheduling task in embedded systems</a>, <a href="https://publications.waset.org/abstracts/search?q=simulated%20annealing" title=" simulated annealing"> simulated annealing</a> </p> <a href="https://publications.waset.org/abstracts/13048/scheduling-tasks-in-embedded-systems-based-on-noc-architecture" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/13048.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">377</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">3634</span> Solving Single Machine Total Weighted Tardiness Problem Using Gaussian Process Regression</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Wanatchapong%20Kongkaew">Wanatchapong Kongkaew</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper proposes an application of probabilistic technique, namely Gaussian process regression, for estimating an optimal sequence of the single machine with total weighted tardiness (SMTWT) scheduling problem. In this work, the Gaussian process regression (GPR) model is utilized to predict an optimal sequence of the SMTWT problem, and its solution is improved by using an iterated local search based on simulated annealing scheme, called GPRISA algorithm. The results show that the proposed GPRISA method achieves a very good performance and a reasonable trade-off between solution quality and time consumption. Moreover, in the comparison of deviation from the best-known solution, the proposed mechanism noticeably outperforms the recently existing approaches. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Gaussian%20process%20regression" title="Gaussian process regression">Gaussian process regression</a>, <a href="https://publications.waset.org/abstracts/search?q=iterated%20local%20search" title=" iterated local search"> iterated local search</a>, <a href="https://publications.waset.org/abstracts/search?q=simulated%20annealing" title=" simulated annealing"> simulated annealing</a>, <a href="https://publications.waset.org/abstracts/search?q=single%20machine%20total%20weighted%20tardiness" title=" single machine total weighted tardiness"> single machine total weighted tardiness</a> </p> <a href="https://publications.waset.org/abstracts/6433/solving-single-machine-total-weighted-tardiness-problem-using-gaussian-process-regression" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/6433.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">309</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">3633</span> Transformer Design Optimization Using Artificial Intelligence Techniques</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> </p> <p class="card-text"><strong>Abstract:</strong></p> Main objective of a power transformer design optimization problem requires minimizing the total overall cost and/or mass of the winding and core material by satisfying all possible constraints obligatory by the standards and transformer user requirement. The constraints include appropriate limits on winding fill factor, temperature rise, efficiency, no-load current and voltage regulation. The design optimizations tasks are a constrained minimum cost and/or mass solution by optimally setting the parameters, geometry and require magnetic properties of the transformer. In this paper, present the above design problems have been formulated by using genetic algorithm (GA) and simulated annealing (SA) on the MATLAB platform. The importance of the presented approach is stems for two main features. First, proposed technique provides reliable and efficient solution for the problem of design optimization with several variables. Second, it guaranteed to obtained solution is global optimum. This paper includes a demonstration of the application of the genetic programming GP technique to transformer design. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=optimization" title="optimization">optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=power%20transformer" title=" power transformer"> power transformer</a>, <a href="https://publications.waset.org/abstracts/search?q=genetic%20algorithm%20%28GA%29" title=" genetic algorithm (GA)"> genetic algorithm (GA)</a>, <a href="https://publications.waset.org/abstracts/search?q=simulated%20annealing%20technique%20%28SA%29" title=" simulated annealing technique (SA)"> simulated annealing technique (SA)</a> </p> <a href="https://publications.waset.org/abstracts/5141/transformer-design-optimization-using-artificial-intelligence-techniques" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/5141.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">583</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">3632</span> A Novel Meta-Heuristic Algorithm Based on Cloud Theory for Redundancy Allocation Problem under Realistic Condition</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=H.%20Mousavi">H. Mousavi</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20Sharifi"> M. Sharifi</a>, <a href="https://publications.waset.org/abstracts/search?q=H.%20Pourvaziri"> H. Pourvaziri</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Redundancy Allocation Problem (RAP) is a well-known mathematical problem for modeling series-parallel systems. It is a combinatorial optimization problem which focuses on determining an optimal assignment of components in a system design. In this paper, to be more practical, we have considered the problem of redundancy allocation of series system with interval valued reliability of components. Therefore, during the search process, the reliabilities of the components are considered as a stochastic variable with a lower and upper bounds. In order to optimize the problem, we proposed a simulated annealing based on cloud theory (CBSAA). Also, the Monte Carlo simulation (MCS) is embedded to the CBSAA to handle the random variable components’ reliability. This novel approach has been investigated by numerical examples and the experimental results have shown that the CBSAA combining MCS is an efficient tool to solve the RAP of systems with interval-valued component reliabilities. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=redundancy%20allocation%20problem" title="redundancy allocation problem">redundancy allocation problem</a>, <a href="https://publications.waset.org/abstracts/search?q=simulated%20annealing" title=" simulated annealing"> simulated annealing</a>, <a href="https://publications.waset.org/abstracts/search?q=cloud%20theory" title=" cloud theory"> cloud theory</a>, <a href="https://publications.waset.org/abstracts/search?q=monte%20carlo%20simulation" title=" monte carlo simulation"> monte carlo simulation</a> </p> <a href="https://publications.waset.org/abstracts/33681/a-novel-meta-heuristic-algorithm-based-on-cloud-theory-for-redundancy-allocation-problem-under-realistic-condition" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/33681.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">412</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">3631</span> Non-Population Search Algorithms for Capacitated Material Requirement Planning in Multi-Stage Assembly Flow Shop with Alternative Machines</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Watcharapan%20Sukkerd">Watcharapan Sukkerd</a>, <a href="https://publications.waset.org/abstracts/search?q=Teeradej%20Wuttipornpun"> Teeradej Wuttipornpun</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper aims to present non-population search algorithms called tabu search (TS), simulated annealing (SA) and variable neighborhood search (VNS) to minimize the total cost of capacitated MRP problem in multi-stage assembly flow shop with two alternative machines. There are three main steps for the algorithm. Firstly, an initial sequence of orders is constructed by a simple due date-based dispatching rule. Secondly, the sequence of orders is repeatedly improved to reduce the total cost by applying TS, SA and VNS separately. Finally, the total cost is further reduced by optimizing the start time of each operation using the linear programming (LP) model. Parameters of the algorithm are tuned by using real data from automotive companies. The result shows that VNS significantly outperforms TS, SA and the existing algorithm. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=capacitated%20MRP" title="capacitated MRP">capacitated MRP</a>, <a href="https://publications.waset.org/abstracts/search?q=tabu%20search" title=" tabu search"> tabu search</a>, <a href="https://publications.waset.org/abstracts/search?q=simulated%20annealing" title=" simulated annealing"> simulated annealing</a>, <a href="https://publications.waset.org/abstracts/search?q=variable%20neighborhood%20search" title=" variable neighborhood search"> variable neighborhood search</a>, <a href="https://publications.waset.org/abstracts/search?q=linear%20programming" title=" linear programming"> linear programming</a>, <a href="https://publications.waset.org/abstracts/search?q=assembly%20flow%20shop" title=" assembly flow shop"> assembly flow shop</a>, <a href="https://publications.waset.org/abstracts/search?q=application%20in%20industry" title=" application in industry"> application in industry</a> </p> <a href="https://publications.waset.org/abstracts/66991/non-population-search-algorithms-for-capacitated-material-requirement-planning-in-multi-stage-assembly-flow-shop-with-alternative-machines" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/66991.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">234</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">3630</span> Robotic Arm Control with Neural Networks Using Genetic Algorithm Optimization Approach</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Arbnor%20Pajaziti">Arbnor Pajaziti</a>, <a href="https://publications.waset.org/abstracts/search?q=Hasan%20Cana"> Hasan Cana</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, the structural genetic algorithm is used to optimize the neural network to control the joint movements of robotic arm. The robotic arm has also been modeled in 3D and simulated in real-time in MATLAB. It is found that Neural Networks provide a simple and effective way to control the robot tasks. Computer simulation examples are given to illustrate the significance of this method. By combining Genetic Algorithm optimization method and Neural Networks for the given robotic arm with 5 D.O.F. the obtained the results shown that the base joint movements overshooting time without controller was about 0.5 seconds, while with Neural Network controller (optimized with Genetic Algorithm) was about 0.2 seconds, and the population size of 150 gave best results. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=robotic%20arm" title="robotic arm">robotic arm</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=genetic%20algorithm" title=" genetic algorithm"> genetic algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=optimization" title=" optimization"> optimization</a> </p> <a href="https://publications.waset.org/abstracts/7408/robotic-arm-control-with-neural-networks-using-genetic-algorithm-optimization-approach" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/7408.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">523</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">3629</span> Application of Hybrid Honey Bees Mating Optimization Algorithm in Multiuser Detection of Wireless Communication Systems </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=N.%20Larbi">N. Larbi</a>, <a href="https://publications.waset.org/abstracts/search?q=F.%20Debbat"> F. Debbat</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Wireless communication systems have changed dramatically and shown spectacular evolution over the past two decades. These radio technologies are engaged in a quest endless high-speed transmission coupled to a constant need to improve transmission quality. Various radio communication systems being developed use code division multiple access (CDMA) technique. This work analyses a hybrid honey bees mating optimization algorithm (HBMO) applied to multiuser detection (MuD) in CDMA communication systems. The HBMO is a swarm-based optimization algorithm, which simulates the mating process of real honey bees. We apply a hybridization of HBMO with simulated annealing (SA) in order to improve the solution generated by the HBMO. Simulation results show that the detection based on Hybrid HBMO, in term of bit error rate (BER), is viable option when compared with the classic detectors from literature under Rayleigh flat fading channel. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=BER" title="BER">BER</a>, <a href="https://publications.waset.org/abstracts/search?q=DS-CDMA%20multiuser%20detection" title=" DS-CDMA multiuser detection"> DS-CDMA multiuser detection</a>, <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=hybrid%20HBMO" title=" hybrid HBMO"> hybrid HBMO</a>, <a href="https://publications.waset.org/abstracts/search?q=simulated%20annealing" title=" simulated annealing "> simulated annealing </a> </p> <a href="https://publications.waset.org/abstracts/13833/application-of-hybrid-honey-bees-mating-optimization-algorithm-in-multiuser-detection-of-wireless-communication-systems" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/13833.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">435</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">3628</span> Thermal Annealing Effects on Nonradiative Recombination Parameters of GaInAsSb/GaSb by Means of Photothermal Defection Technique</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Souha%20Bouagila">Souha Bouagila</a>, <a href="https://publications.waset.org/abstracts/search?q=Soufiene%20Ilahi"> Soufiene Ilahi</a>, <a href="https://publications.waset.org/abstracts/search?q=Noureddine%20Yacoubi"> Noureddine Yacoubi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> We have used Photothermal deflection spectroscopy PTD to investigate the impact of thermal annealing on electronics properties of GaInAsSb/GaSb.GaInAsSb used as an active layer for Vertical Cavity Surface Emitting laser (VCSEL). We have remarked that surface recombination velocity (SRV) from 7963 m / s (± 6.3%) to 1450 m / s (± 3.6) for as grown to sample annealed for 60 min. Accordingly, Force Microscopy images analyses agree well with the measure of surface recombination velocity. We have found that Root-Mean-Square Roughness (RMS) decreases as respect of annealing time. In addition, we have that the diffusion length and minority carrier mobility have been enhanced according to annealing time. However, due to annealing effects, the interface recombination velocity (IRV) is increased from 1196 m / s (± 5) to 6000 m/s (5%) for GaInAsSb in respect of annealed times. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=nonradiative%20lifetime" title="nonradiative lifetime">nonradiative lifetime</a>, <a href="https://publications.waset.org/abstracts/search?q=mobility%20of%20minority%20carrier" title=" mobility of minority carrier"> mobility of minority carrier</a>, <a href="https://publications.waset.org/abstracts/search?q=diffusion%20length" title=" diffusion length"> diffusion length</a>, <a href="https://publications.waset.org/abstracts/search?q=Surface%20and%20interface%20recombination%20velocity" title=" Surface and interface recombination velocity"> Surface and interface recombination velocity</a> </p> <a href="https://publications.waset.org/abstracts/165142/thermal-annealing-effects-on-nonradiative-recombination-parameters-of-gainassbgasb-by-means-of-photothermal-defection-technique" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/165142.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">74</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">3627</span> Characterization of Chemically Deposited CdS Thin Films Annealed in Different Atmospheres</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=J.%20Pantoja%20Enr%C3%ADquez">J. Pantoja Enríquez</a>, <a href="https://publications.waset.org/abstracts/search?q=G.%20P.%20Hern%C3%A1ndez"> G. P. Hernández</a>, <a href="https://publications.waset.org/abstracts/search?q=G.%20I.%20Duharte"> G. I. Duharte</a>, <a href="https://publications.waset.org/abstracts/search?q=X.%20Mathew"> X. Mathew</a>, <a href="https://publications.waset.org/abstracts/search?q=J.%20Moreira"> J. Moreira</a>, <a href="https://publications.waset.org/abstracts/search?q=P.%20J.%20Sebastian"> P. J. Sebastian</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Cadmium sulfide films were deposited onto glass substrates by chemical bath deposition (CBD) from a bath containing cadmium acetate, ammonium acetate, thiourea, and ammonium hydroxide. The CdS thin films were annealed in air, argon, hydrogen and nitrogen for 1 h at various temperatures (300, 350, 400, 450 and 500 °C). The changes in optical and electrical properties of annealed treated CdS thin films were analyzed. The results showed that, the band-gap and resistivity depend on the post-deposition annealing atmosphere and temperatures. Thus, it was found that these properties of the films, were found to be affected by various processes with opposite effects, some beneficial and others unfavorable. The energy gap and resistivity for different annealing atmospheres was seen to oscillate by thermal annealing. Recrystallization, oxidation, surface passivation, sublimation and materials evaporation were found the main factors of the heat-treatment process responsible for this oscillating behavior. Annealing over 400 °C was seen to degrade the optical and electrical properties of the film. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=cds" title="cds">cds</a>, <a href="https://publications.waset.org/abstracts/search?q=thin%20films" title=" thin films"> thin films</a>, <a href="https://publications.waset.org/abstracts/search?q=annealing" title=" annealing"> annealing</a>, <a href="https://publications.waset.org/abstracts/search?q=optical" title=" optical"> optical</a>, <a href="https://publications.waset.org/abstracts/search?q=electrical%20properties" title=" electrical properties"> electrical properties</a> </p> <a href="https://publications.waset.org/abstracts/31251/characterization-of-chemically-deposited-cds-thin-films-annealed-in-different-atmospheres" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/31251.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">510</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">3626</span> Preparation of CuAlO2 Thin Films on Si or Sapphire Substrate by Sol-Gel Method Using Metal Acetate or Nitrate</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Takashi%20Ehara">Takashi Ehara</a>, <a href="https://publications.waset.org/abstracts/search?q=Takayoshi%20Nakanishi"> Takayoshi Nakanishi</a>, <a href="https://publications.waset.org/abstracts/search?q=Kohei%20Sasaki"> Kohei Sasaki</a>, <a href="https://publications.waset.org/abstracts/search?q=Marina%20Abe"> Marina Abe</a>, <a href="https://publications.waset.org/abstracts/search?q=Hiroshi%20Abe"> Hiroshi Abe</a>, <a href="https://publications.waset.org/abstracts/search?q=Kiyoaki%20Abe"> Kiyoaki Abe</a>, <a href="https://publications.waset.org/abstracts/search?q=Ryo%20Iizaka"> Ryo Iizaka</a>, <a href="https://publications.waset.org/abstracts/search?q=Takuya%20Sato"> Takuya Sato</a> </p> <p class="card-text"><strong>Abstract:</strong></p> CuAlO<sub>2</sub> thin films are prepared on Si or sapphire substrate by sol-gel method using two kinds of sols. One is combination of Cu acetate and Al acetate basic, and the other is Cu nitrate and Al nitrate. In the case of acetate sol, XRD peaks of CuAlO<sub>2</sub> observed at annealing temperature of 800-950 ºC on both Si and sapphire substrates. In contrast, in the case of the films prepared using nitrate on Si substrate, XRD peaks of CuAlO<sub>2</sub> have been observed only at the annealing temperature of 800-850 ºC. At annealing temperature of 850ºC, peaks of other species have been observed beside the CuAlO<sub>2</sub> peaks, then, the CuAlO<sub>2</sub> peaks disappeared at annealing temperature of 900 °C with increasing in intensity of the other peaks. Intensity of the other peaks decreased at annealing temperature of 950 ºC with appearance of broad SiO<sub>2</sub> peak. In the present, we ascribe these peaks as metal silicide. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=CuAlO2" title="CuAlO2">CuAlO2</a>, <a href="https://publications.waset.org/abstracts/search?q=silicide" title=" silicide"> silicide</a>, <a href="https://publications.waset.org/abstracts/search?q=thin%20Films" title=" thin Films"> thin Films</a>, <a href="https://publications.waset.org/abstracts/search?q=transparent%20conducting%20oxide" title=" transparent conducting oxide"> transparent conducting oxide</a> </p> <a href="https://publications.waset.org/abstracts/52540/preparation-of-cualo2-thin-films-on-si-or-sapphire-substrate-by-sol-gel-method-using-metal-acetate-or-nitrate" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/52540.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">396</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">3625</span> Cooling-Rate Induced Fiber Birefringence Variation in Regenerated High Birefringent Fiber</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Man-Hong%20Lai">Man-Hong Lai</a>, <a href="https://publications.waset.org/abstracts/search?q=Dinusha%20S.%20Gunawardena"> Dinusha S. Gunawardena</a>, <a href="https://publications.waset.org/abstracts/search?q=Kok-Sing%20Lim"> Kok-Sing Lim</a>, <a href="https://publications.waset.org/abstracts/search?q=Harith%20Ahmad"> Harith Ahmad</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we have reported birefringence manipulation in regenerated high-birefringent fiber Bragg grating (RPMG) by using CO2 laser annealing method. The results indicate that the birefringence of RPMG remains unchanged after CO2 laser annealing followed by a slow cooling process, but reduced after the fast cooling process (~5.6×10-5). After a series of annealing procedures with different cooling rates, the obtained results show that slower the cooling rate, higher the birefringence of RPMG. The volume, thermal expansion coefficient (TEC) and glass transition temperature (Tg) change of stress applying part in RPMG during the cooling process are responsible for the birefringence change. Therefore, these findings are important to the RPMG sensor in high and dynamic temperature environment. The measuring accuracy, range and sensitivity of RPMG sensor are greatly affected by its birefringence value. This work also opens up a new application of CO2 laser for fiber annealing and birefringence modification. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=birefringence" title="birefringence">birefringence</a>, <a href="https://publications.waset.org/abstracts/search?q=CO2%20laser%20annealing" title=" CO2 laser annealing"> CO2 laser annealing</a>, <a href="https://publications.waset.org/abstracts/search?q=regenerated%20gratings" title=" regenerated gratings"> regenerated gratings</a>, <a href="https://publications.waset.org/abstracts/search?q=thermal%20stress" title=" thermal stress"> thermal stress</a> </p> <a href="https://publications.waset.org/abstracts/33331/cooling-rate-induced-fiber-birefringence-variation-in-regenerated-high-birefringent-fiber" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/33331.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">459</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">3624</span> Influence of Annealing on the Mechanical αc-Relaxation of Isotactic-Polypropylene: A Study from the Intermediate Phase Perspective</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Baobao%20Chang">Baobao Chang</a>, <a href="https://publications.waset.org/abstracts/search?q=Konrad%20Schneider"> Konrad Schneider</a>, <a href="https://publications.waset.org/abstracts/search?q=Vogel%20Roland"> Vogel Roland</a>, <a href="https://publications.waset.org/abstracts/search?q=Gert%20Heinrich"> Gert Heinrich</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this work, the influence of annealing on the mechanical αc-relaxation behavior of isotactic polypropylene (iPP) was investigated. The results suggest that the mechanical αc-relaxation behavior depends strongly on the confinement force on the polymer chains in the intermediate phase and the thickness of the intermediate phase. After quenching at 10°C, abundant crystallites with a wide size distribution are formed. The polymer chains in the intermediate phase are constrained by the crystallites, giving rise to one broad αc-relaxation peak. With an annealing temperature between 60°C~105°C, imperfect lamellae melting releases part of the constraint force, which reduces the conformational ordering of the polymer chains neighboring the amorphous phase. Consequently, two separate αc-relaxation peaks could be observed which are labeled as αc1-relaxation and αc2-relaxation. αc1-relaxation and αc2-relaxation describe the relaxation behavior of polymer chains in the region close to the amorphous phase and the crystalline phase, respectively. Both relaxation peaks shift to a higher temperature as annealing temperature increases. With an annealing temperature higher than 105°C, the new crystalline phase is formed in the intermediate phase, which enhances the constraint force on the polymer chains. αc1-relaxation peak is broadened obviously and its position shifts to a higher temperature as annealing temperature increases. Moreover, αc2-relaxation is undetectable because that the polymer chains in the region between the initial crystalline phase and the newly formed crystalline phase are strongly confined. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=annealing" title="annealing">annealing</a>, <a href="https://publications.waset.org/abstracts/search?q=%CE%B1c-relaxation" title=" αc-relaxation"> αc-relaxation</a>, <a href="https://publications.waset.org/abstracts/search?q=isotactic-polypropylene" title=" isotactic-polypropylene"> isotactic-polypropylene</a>, <a href="https://publications.waset.org/abstracts/search?q=intermediate%20phase" title=" intermediate phase"> intermediate phase</a> </p> <a href="https://publications.waset.org/abstracts/67006/influence-of-annealing-on-the-mechanical-ac-relaxation-of-isotactic-polypropylene-a-study-from-the-intermediate-phase-perspective" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/67006.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">349</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">3623</span> Thermal Stability of Hydrogen in ZnO Bulk and Thin Films: A Kinetic Monte Carlo Study</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=M.%20A.%20Lahmer">M. A. Lahmer</a>, <a href="https://publications.waset.org/abstracts/search?q=K.%20Guergouri"> K. Guergouri</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this work, Kinetic Monte Carlo (KMC) method was applied to study the thermal stability of hydrogen in ZnO bulk and thin films. Our simulation includes different possible events such as interstitial hydrogen (Hi) jumps, substitutional hydrogen (HO) formation and dissociation, oxygen and zinc vacancies jumps, hydrogen-VZn complexes formation and dissociation, HO-Hi complex formation and hydrogen molecule (H2) formation and dissociation. The obtained results show that the hidden hydrogen formed during thermal annealing or at room temperature is constituted of both hydrogen molecule and substitutional hydrogen. The ratio of this constituants depends on the initial defects concentration as well as the annealing temperature. For annealing temperature below 300°C hidden hydrogen was found to be constituted from both substitutional hydrogen and hydrogen molecule, however, for higher temperature it is composed essentially from HO defects only because H2 was found to be unstable. In the other side, our results show that the remaining hydrogen amount in sample during thermal annealing depend greatly on the oxygen vacancies in the material. H2 molecule was found to be stable for thermal annealing up to 200°C, VZnHn complexes are stable up to 350°C and HO was found to be stable up to 450°C. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=ZnO" title="ZnO">ZnO</a>, <a href="https://publications.waset.org/abstracts/search?q=hydrogen" title=" hydrogen"> hydrogen</a>, <a href="https://publications.waset.org/abstracts/search?q=thermal%20annealing" title=" thermal annealing"> thermal annealing</a>, <a href="https://publications.waset.org/abstracts/search?q=kinetic%20Monte%20Carlo" title=" kinetic Monte Carlo"> kinetic Monte Carlo</a> </p> <a href="https://publications.waset.org/abstracts/8488/thermal-stability-of-hydrogen-in-zno-bulk-and-thin-films-a-kinetic-monte-carlo-study" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/8488.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 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