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unconstrained bed sensing method</title> <meta name="description" content="Search results for: unconstrained bed sensing method"> <meta name="keywords" content="unconstrained bed sensing method"> <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 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method="get" 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="unconstrained bed sensing method"> <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> 19795</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: unconstrained bed sensing method</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19795</span> Development of Scratching Monitoring System Based on Mathematical Model of Unconstrained Bed Sensing Method</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Takuya%20Sumi">Takuya Sumi</a>, <a href="https://publications.waset.org/abstracts/search?q=Syoko%20Nukaya"> Syoko Nukaya</a>, <a href="https://publications.waset.org/abstracts/search?q=Takashi%20Kaburagi"> Takashi Kaburagi</a>, <a href="https://publications.waset.org/abstracts/search?q=Hiroshi%20Tanaka"> Hiroshi Tanaka</a>, <a href="https://publications.waset.org/abstracts/search?q=Kajiro%20Watanabe"> Kajiro Watanabe</a>, <a href="https://publications.waset.org/abstracts/search?q=Yosuke%20Kurihara"> Yosuke Kurihara</a> </p> <p class="card-text"><strong>Abstract:</strong></p> We propose an unconstrained measurement system for scratching motion based on mathematical model of unconstrained bed sensing method which could measure the bed vibrations due to the motion of the person on the bed. In this paper, we construct mathematical model of the unconstrained bed monitoring system, and we apply the unconstrained bed sensing method to the system for detecting scratching motion. The proposed sensors are placed under the three bed feet. When the person is lying on the bed, the output signals from the sensors are proportional to the magnitude of the vibration due to the scratching motion. Hence, we could detect the subject’s scratching motion from the output signals from ceramic sensors. We evaluated two scratching motions using the proposed system in the validity experiment as follows: First experiment is the subject’s scratching the right side cheek with his right hand, and; second experiment is the subject’s scratching the shin with another foot. As the results of the experiment, we recognized the scratching signals that enable the determination when the scratching occurred. Furthermore, the difference among the amplitudes of the output signals enabled us to estimate where the subject scratched. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=unconstrained%20bed%20sensing%20method" title="unconstrained bed sensing method">unconstrained bed sensing method</a>, <a href="https://publications.waset.org/abstracts/search?q=scratching" title=" scratching"> scratching</a>, <a href="https://publications.waset.org/abstracts/search?q=body%20movement" title=" body movement"> body movement</a>, <a href="https://publications.waset.org/abstracts/search?q=itchy" title=" itchy"> itchy</a>, <a href="https://publications.waset.org/abstracts/search?q=piezoceramics" title=" piezoceramics"> piezoceramics</a> </p> <a href="https://publications.waset.org/abstracts/1382/development-of-scratching-monitoring-system-based-on-mathematical-model-of-unconstrained-bed-sensing-method" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/1382.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">411</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">19794</span> Classification Method for Turnover While Sleeping Using Multi-Point Unconstrained Sensing Devices</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=K.%20Shiba">K. Shiba</a>, <a href="https://publications.waset.org/abstracts/search?q=T.%20Kobayashi"> T. Kobayashi</a>, <a href="https://publications.waset.org/abstracts/search?q=T.%20Kaburagi"> T. Kaburagi</a>, <a href="https://publications.waset.org/abstracts/search?q=Y.%20Kurihara"> Y. Kurihara</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Elderly population in the world is increasing, and consequently, their nursing burden is also increasing. In such situations, monitoring and evaluating their daily action facilitates efficient nursing care. Especially, we focus on an unconscious activity during sleep, i.e. turnover. Monitoring turnover during sleep is essential to evaluate various conditions related to sleep. Bedsores are considered as one of the monitoring conditions. Changing patient’s posture every two hours is required for caregivers to prevent bedsore. Herein, we attempt to develop an unconstrained nocturnal monitoring system using a sensing device based on piezoelectric ceramics that can detect the vibrations owing to human body movement on the bed. In the proposed method, in order to construct a multi-points sensing, we placed two sensing devices under the right and left legs at the head-side of an ordinary bed. Using this equipment, when a subject lies on the bed, feature is calculated from the output voltages of the sensing devices. In order to evaluate our proposed method, we conducted an experiment with six healthy male subjects. Consequently, the period during which turnover occurs can be correctly classified as the turnover period with 100% accuracy. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=turnover" title="turnover">turnover</a>, <a href="https://publications.waset.org/abstracts/search?q=piezoelectric%20ceramics" title=" piezoelectric ceramics"> piezoelectric ceramics</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-points%20sensing" title=" multi-points sensing"> multi-points sensing</a>, <a href="https://publications.waset.org/abstracts/search?q=unconstrained%20monitoring%20system" title=" unconstrained monitoring system"> unconstrained monitoring system</a> </p> <a href="https://publications.waset.org/abstracts/75765/classification-method-for-turnover-while-sleeping-using-multi-point-unconstrained-sensing-devices" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/75765.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">194</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19793</span> A New Family of Globally Convergent Conjugate Gradient Methods</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=B.%20Sellami">B. Sellami</a>, <a href="https://publications.waset.org/abstracts/search?q=Y.%20Laskri"> Y. Laskri</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20Belloufi"> M. Belloufi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Conjugate gradient methods are an important class of methods for unconstrained optimization, especially for large-scale problems. Recently, they have been much studied. In this paper, a new family of conjugate gradient method is proposed for unconstrained optimization. This method includes the already existing two practical nonlinear conjugate gradient methods, which produces a descent search direction at every iteration and converges globally provided that the line search satisfies the Wolfe conditions. The numerical experiments are done to test the efficiency of the new method, which implies the new method is promising. In addition the methods related to this family are uniformly discussed. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=conjugate%20gradient%20method" title="conjugate gradient method">conjugate gradient method</a>, <a href="https://publications.waset.org/abstracts/search?q=global%20convergence" title=" global convergence"> global convergence</a>, <a href="https://publications.waset.org/abstracts/search?q=line%20search" title=" line search"> line search</a>, <a href="https://publications.waset.org/abstracts/search?q=unconstrained%20optimization" title=" unconstrained optimization"> unconstrained optimization</a> </p> <a href="https://publications.waset.org/abstracts/40381/a-new-family-of-globally-convergent-conjugate-gradient-methods" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/40381.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">410</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">19792</span> A Conjugate Gradient Method for Large Scale Unconstrained Optimization</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mohammed%20Belloufi">Mohammed Belloufi</a>, <a href="https://publications.waset.org/abstracts/search?q=Rachid%20Benzine"> Rachid Benzine</a>, <a href="https://publications.waset.org/abstracts/search?q=Badreddine%20Sellami"> Badreddine Sellami</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Conjugate gradient methods is useful for solving large scale optimization problems in scientific and engineering computation, characterized by the simplicity of their iteration and their low memory requirements. It is well known that the search direction plays a main role in the line search method. In this paper, we propose a search direction with the Wolfe line search technique for solving unconstrained optimization problems. Under the above line searches and some assumptions, the global convergence properties of the given methods are discussed. Numerical results and comparisons with other CG methods are given. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=unconstrained%20optimization" title="unconstrained optimization">unconstrained optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=conjugate%20gradient%20method" title=" conjugate gradient method"> conjugate gradient method</a>, <a href="https://publications.waset.org/abstracts/search?q=strong%20Wolfe%20line%20search" title=" strong Wolfe line search"> strong Wolfe line search</a>, <a href="https://publications.waset.org/abstracts/search?q=global%20convergence" title=" global convergence"> global convergence</a> </p> <a href="https://publications.waset.org/abstracts/40028/a-conjugate-gradient-method-for-large-scale-unconstrained-optimization" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/40028.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">422</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">19791</span> A New Conjugate Gradient Method with Guaranteed Descent</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=B.%20Sellami">B. Sellami</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20Belloufi"> M. Belloufi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Conjugate gradient methods are an important class of methods for unconstrained optimization, especially for large-scale problems. Recently, they have been much studied. In this paper, we propose a new two-parameter family of conjugate gradient methods for unconstrained optimization. The two-parameter family of methods not only includes the already existing three practical nonlinear conjugate gradient methods, but also has other family of conjugate gradient methods as subfamily. The two-parameter family of methods with the Wolfe line search is shown to ensure the descent property of each search direction. Some general convergence results are also established for the two-parameter family of methods. The numerical results show that this method is efficient for the given test problems. In addition, the methods related to this family are uniformly discussed. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=unconstrained%20optimization" title="unconstrained optimization">unconstrained optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=conjugate%20gradient%20method" title=" conjugate gradient method"> conjugate gradient method</a>, <a href="https://publications.waset.org/abstracts/search?q=line%20search" title=" line search"> line search</a>, <a href="https://publications.waset.org/abstracts/search?q=global%20convergence" title=" global convergence"> global convergence</a> </p> <a href="https://publications.waset.org/abstracts/41734/a-new-conjugate-gradient-method-with-guaranteed-descent" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/41734.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">452</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">19790</span> A New Class of Conjugate Gradient Methods Based on a Modified Search Direction for Unconstrained Optimization</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Belloufi%20Mohammed">Belloufi Mohammed</a>, <a href="https://publications.waset.org/abstracts/search?q=Sellami%20Badreddine"> Sellami Badreddine</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Conjugate gradient methods have played a special role for solving large scale optimization problems due to the simplicity of their iteration, convergence properties and their low memory requirements. In this work, we propose a new class of conjugate gradient methods which ensures sufficient descent. Moreover, we propose a new search direction with the Wolfe line search technique for solving unconstrained optimization problems, a global convergence result for general functions is established provided that the line search satisfies the Wolfe conditions. Our numerical experiments indicate that our proposed methods are preferable and in general superior to the classical conjugate gradient methods in terms of efficiency and robustness. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=unconstrained%20optimization" title="unconstrained optimization">unconstrained optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=conjugate%20gradient%20method" title=" conjugate gradient method"> conjugate gradient method</a>, <a href="https://publications.waset.org/abstracts/search?q=sufficient%20descent%20property" title=" sufficient descent property"> sufficient descent property</a>, <a href="https://publications.waset.org/abstracts/search?q=numerical%20comparisons" title=" numerical comparisons"> numerical comparisons</a> </p> <a href="https://publications.waset.org/abstracts/41725/a-new-class-of-conjugate-gradient-methods-based-on-a-modified-search-direction-for-unconstrained-optimization" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/41725.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">405</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19789</span> Co-Evolutionary Fruit Fly Optimization Algorithm and Firefly Algorithm for Solving Unconstrained Optimization Problems</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=R.%20M.%20Rizk-Allah">R. M. Rizk-Allah</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents co-evolutionary fruit fly optimization algorithm based on firefly algorithm (CFOA-FA) for solving unconstrained optimization problems. The proposed algorithm integrates the merits of fruit fly optimization algorithm (FOA), firefly algorithm (FA) and elite strategy to refine the performance of classical FOA. Moreover, co-evolutionary mechanism is performed by applying FA procedures to ensure the diversity of the swarm. Finally, the proposed algorithm CFOA- FA is tested on several benchmark problems from the usual literature and the numerical results have demonstrated the superiority of the proposed algorithm for finding the global optimal solution. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=firefly%20algorithm" title="firefly algorithm">firefly algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=fruit%20fly%20optimization%20algorithm" title=" fruit fly optimization algorithm"> fruit fly optimization algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=unconstrained%20optimization%20problems" title=" unconstrained optimization problems"> unconstrained optimization problems</a> </p> <a href="https://publications.waset.org/abstracts/15923/co-evolutionary-fruit-fly-optimization-algorithm-and-firefly-algorithm-for-solving-unconstrained-optimization-problems" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/15923.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">536</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">19788</span> A Modified Nonlinear Conjugate Gradient Algorithm for Large Scale Unconstrained Optimization Problems</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Tsegay%20Giday%20Woldu">Tsegay Giday Woldu</a>, <a href="https://publications.waset.org/abstracts/search?q=Haibin%20Zhang"> Haibin Zhang</a>, <a href="https://publications.waset.org/abstracts/search?q=Xin%20Zhang"> Xin Zhang</a>, <a href="https://publications.waset.org/abstracts/search?q=Yemane%20Hailu%20Fissuh"> Yemane Hailu Fissuh</a> </p> <p class="card-text"><strong>Abstract:</strong></p> It is well known that nonlinear conjugate gradient method is one of the widely used first order methods to solve large scale unconstrained smooth optimization problems. Because of the low memory requirement, attractive theoretical features, practical computational efficiency and nice convergence properties, nonlinear conjugate gradient methods have a special role for solving large scale unconstrained optimization problems. Large scale optimization problems are with important applications in practical and scientific world. However, nonlinear conjugate gradient methods have restricted information about the curvature of the objective function and they are likely less efficient and robust compared to some second order algorithms. To overcome these drawbacks, the new modified nonlinear conjugate gradient method is presented. The noticeable features of our work are that the new search direction possesses the sufficient descent property independent of any line search and it belongs to a trust region. Under mild assumptions and standard Wolfe line search technique, the global convergence property of the proposed algorithm is established. Furthermore, to test the practical computational performance of our new algorithm, numerical experiments are provided and implemented on the set of some large dimensional unconstrained problems. The numerical results show that the proposed algorithm is an efficient and robust compared with other similar algorithms. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=conjugate%20gradient%20method" title="conjugate gradient method">conjugate gradient method</a>, <a href="https://publications.waset.org/abstracts/search?q=global%20convergence" title=" global convergence"> global convergence</a>, <a href="https://publications.waset.org/abstracts/search?q=large%20scale%20optimization" title=" large scale optimization"> large scale optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=sufficient%20descent%20property" title=" sufficient descent property"> sufficient descent property</a> </p> <a href="https://publications.waset.org/abstracts/102625/a-modified-nonlinear-conjugate-gradient-algorithm-for-large-scale-unconstrained-optimization-problems" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/102625.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">206</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">19787</span> Automatic Extraction of Water Bodies Using Whole-R Method</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Nikhat%20Nawaz">Nikhat Nawaz</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20Srinivasulu"> S. Srinivasulu</a>, <a href="https://publications.waset.org/abstracts/search?q=P.%20Kesava%20Rao"> P. Kesava Rao</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Feature extraction plays an important role in many remote sensing applications. Automatic extraction of water bodies is of great significance in many remote sensing applications like change detection, image retrieval etc. This paper presents a procedure for automatic extraction of water information from remote sensing images. The algorithm uses the relative location of R-colour component of the chromaticity diagram. This method is then integrated with the effectiveness of the spatial scale transformation of whole method. The whole method is based on water index fitted from spectral library. Experimental results demonstrate the improved accuracy and effectiveness of the integrated method for automatic extraction of water bodies. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=feature%20extraction" title="feature extraction">feature extraction</a>, <a href="https://publications.waset.org/abstracts/search?q=remote%20sensing" title=" remote sensing"> remote sensing</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20retrieval" title=" image retrieval"> image retrieval</a>, <a href="https://publications.waset.org/abstracts/search?q=chromaticity" title=" chromaticity"> chromaticity</a>, <a href="https://publications.waset.org/abstracts/search?q=water%20index" title=" water index"> water index</a>, <a href="https://publications.waset.org/abstracts/search?q=spectral%20library" title=" spectral library"> spectral library</a>, <a href="https://publications.waset.org/abstracts/search?q=integrated%20method" title=" integrated method "> integrated method </a> </p> <a href="https://publications.waset.org/abstracts/2097/automatic-extraction-of-water-bodies-using-whole-r-method" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/2097.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">19786</span> Application of Compressed Sensing Method for Compression of Quantum Data</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=M.%20Kowalski">M. Kowalski</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20%C5%BByczkowski"> M. Życzkowski</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20Karol"> M. Karol</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Current quantum key distribution systems (QKD) offer low bit rate of up to single MHz. Compared to conventional optical fiber links with multiple GHz bitrates, parameters of recent QKD systems are significantly lower. In the article we present the conception of application of the Compressed Sensing method for compression of quantum information. The compression methodology as well as the signal reconstruction method and initial results of improving the throughput of quantum information link are presented. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=quantum%20key%20distribution%20systems" title="quantum key distribution systems">quantum key distribution systems</a>, <a href="https://publications.waset.org/abstracts/search?q=fiber%20optic%20system" title=" fiber optic system"> fiber optic system</a>, <a href="https://publications.waset.org/abstracts/search?q=compressed%20sensing" title=" compressed sensing"> compressed sensing</a> </p> <a href="https://publications.waset.org/abstracts/9234/application-of-compressed-sensing-method-for-compression-of-quantum-data" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/9234.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">694</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">19785</span> Fusion of Shape and Texture for Unconstrained Periocular Authentication</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=D.%20R.%20Ambika">D. R. Ambika</a>, <a href="https://publications.waset.org/abstracts/search?q=K.%20R.%20Radhika"> K. R. Radhika</a>, <a href="https://publications.waset.org/abstracts/search?q=D.%20Seshachalam"> D. Seshachalam</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Unconstrained authentication is an important component for personal automated systems and human-computer interfaces. Existing solutions mostly use face as the primary object of analysis. The performance of face-based systems is largely determined by the extent of deformation caused in the facial region and amount of useful information available in occluded face images. Periocular region is a useful portion of face with discriminative ability coupled with resistance to deformation. A reliable portion of periocular area is available for occluded images. The present work demonstrates that joint representation of periocular texture and periocular structure provides an effective expression and poses invariant representation. The proposed methodology provides an effective and compact description of periocular texture and shape. The method is tested over four benchmark datasets exhibiting varied acquisition conditions. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=periocular%20authentication" title="periocular authentication">periocular authentication</a>, <a href="https://publications.waset.org/abstracts/search?q=Zernike%20moments" title=" Zernike moments"> Zernike moments</a>, <a href="https://publications.waset.org/abstracts/search?q=LBP%20variance" title=" LBP variance"> LBP variance</a>, <a href="https://publications.waset.org/abstracts/search?q=shape%20and%20texture%20fusion" title=" shape and texture fusion"> shape and texture fusion</a> </p> <a href="https://publications.waset.org/abstracts/68833/fusion-of-shape-and-texture-for-unconstrained-periocular-authentication" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/68833.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">279</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19784</span> Capacity Optimization in Cooperative Cognitive Radio Networks</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mahdi%20Pirmoradian">Mahdi Pirmoradian</a>, <a href="https://publications.waset.org/abstracts/search?q=Olayinka%20Adigun"> Olayinka Adigun</a>, <a href="https://publications.waset.org/abstracts/search?q=Christos%20Politis"> Christos Politis</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Cooperative spectrum sensing is a crucial challenge in cognitive radio networks. Cooperative sensing can increase the reliability of spectrum hole detection, optimize sensing time and reduce delay in cooperative networks. In this paper, an efficient central capacity optimization algorithm is proposed to minimize cooperative sensing time in a homogenous sensor network using OR decision rule subject to the detection and false alarm probabilities constraints. The evaluation results reveal significant improvement in the sensing time and normalized capacity of the cognitive sensors. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=cooperative%20networks" title="cooperative networks">cooperative networks</a>, <a href="https://publications.waset.org/abstracts/search?q=normalized%20capacity" title=" normalized capacity"> normalized capacity</a>, <a href="https://publications.waset.org/abstracts/search?q=sensing%20time" title=" sensing time"> sensing time</a> </p> <a href="https://publications.waset.org/abstracts/25670/capacity-optimization-in-cooperative-cognitive-radio-networks" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/25670.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">634</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">19783</span> Image Reconstruction Method Based on L0 Norm</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jianhong%20Xiang">Jianhong Xiang</a>, <a href="https://publications.waset.org/abstracts/search?q=Hao%20Xiang"> Hao Xiang</a>, <a href="https://publications.waset.org/abstracts/search?q=Linyu%20Wang"> Linyu Wang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Compressed sensing (CS) has a wide range of applications in sparse signal reconstruction. Aiming at the problems of low recovery accuracy and long reconstruction time of existing reconstruction algorithms in medical imaging, this paper proposes a corrected smoothing L0 algorithm based on compressed sensing (CSL0). First, an approximate hyperbolic tangent function (AHTF) that is more similar to the L0 norm is proposed to approximate the L0 norm. Secondly, in view of the "sawtooth phenomenon" in the steepest descent method and the problem of sensitivity to the initial value selection in the modified Newton method, the use of the steepest descent method and the modified Newton method are jointly optimized to improve the reconstruction accuracy. Finally, the CSL0 algorithm is simulated on various images. The results show that the algorithm proposed in this paper improves the reconstruction accuracy of the test image by 0-0. 98dB. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=smoothed%20L0" title="smoothed L0">smoothed L0</a>, <a href="https://publications.waset.org/abstracts/search?q=compressed%20sensing" title=" compressed sensing"> compressed sensing</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20processing" title=" image processing"> image processing</a>, <a href="https://publications.waset.org/abstracts/search?q=sparse%20reconstruction" title=" sparse reconstruction"> sparse reconstruction</a> </p> <a href="https://publications.waset.org/abstracts/155598/image-reconstruction-method-based-on-l0-norm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/155598.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">116</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">19782</span> Development of an Optimization Method for Myoelectric Signal Processing by Active Matrix Sensing in Robot Rehabilitation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Noriyoshi%20Yamauchi">Noriyoshi Yamauchi</a>, <a href="https://publications.waset.org/abstracts/search?q=Etsuo%20Horikawa"> Etsuo Horikawa</a>, <a href="https://publications.waset.org/abstracts/search?q=Takunori%20Tsuji"> Takunori Tsuji</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Training by exoskeleton robot is drawing attention as a rehabilitation method for body paralysis seen in many cases, and there are many forms that assist with the myoelectric signal generated by exercise commands from the brain. Rehabilitation requires more frequent training, but it is one of the reasons that the technology is required for the identification of the myoelectric potential derivation site and attachment of the device is preventing the spread of paralysis. In this research, we focus on improving the efficiency of gait training by exoskeleton type robots, improvement of myoelectric acquisition and analysis method using active matrix sensing method, and improvement of walking rehabilitation and walking by optimization of robot control. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=active%20matrix%20sensing" title="active matrix sensing">active matrix sensing</a>, <a href="https://publications.waset.org/abstracts/search?q=brain%20machine%20interface%20%28BMI%29" title=" brain machine interface (BMI)"> brain machine interface (BMI)</a>, <a href="https://publications.waset.org/abstracts/search?q=the%20central%20pattern%20generator%20%28CPG%29" title=" the central pattern generator (CPG)"> the central pattern generator (CPG)</a>, <a href="https://publications.waset.org/abstracts/search?q=myoelectric%20signal%20processing" title=" myoelectric signal processing"> myoelectric signal processing</a>, <a href="https://publications.waset.org/abstracts/search?q=robot%20rehabilitation" title=" robot rehabilitation"> robot rehabilitation</a> </p> <a href="https://publications.waset.org/abstracts/64589/development-of-an-optimization-method-for-myoelectric-signal-processing-by-active-matrix-sensing-in-robot-rehabilitation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/64589.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">19781</span> Effect of Using a Mixture of Al2O3 Nanoparticles and 3-Aminopropyltriethoxysilane as the Sensing Membrane for Polysilicon Wire on pH Sensing</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=You-Lin%20Wu">You-Lin Wu</a>, <a href="https://publications.waset.org/abstracts/search?q=Zong-Xian%20Wu"> Zong-Xian Wu</a>, <a href="https://publications.waset.org/abstracts/search?q=Jing-Jenn%20Lin"> Jing-Jenn Lin</a>, <a href="https://publications.waset.org/abstracts/search?q=Shih-Hung%20Lin"> Shih-Hung Lin</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this work, a polysilicon wire (PSW) coated with a mixture of 3-aminopropyltriethoxysilane (r-APTES) and Al2O3 nanoparticles as the sensing membrane prepared with various Al2O3/r-APTES and dispersing agent/r-APTES ratios for pH sensing is studied. The r-APTES and dispersed Al2O3 nanoparticles mixture was directly transferred to PSW surface by solution phase deposition (SPD). It is found that using a mixture of Al2O3 nanoparticles and r-APTES as the sensing membrane help in improving the pH sensing of the PSW sensor and a 5 min SPD deposition time is the best. Dispersing agent is found to be necessary for better pH sensing when preparing the mixture of Al2O3 nanoparticles and r-APTES. The optimum condition for preparing the mixture is found to be Al2O3/r-APTES ratio of 2% and dispersing agent/r-APTES ratio of 0.3%. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=al2o3%20nanoparticles" title="al2o3 nanoparticles">al2o3 nanoparticles</a>, <a href="https://publications.waset.org/abstracts/search?q=ph%20sensing" title=" ph sensing"> ph sensing</a>, <a href="https://publications.waset.org/abstracts/search?q=polysilicon%20wire%20sensor" title=" polysilicon wire sensor"> polysilicon wire sensor</a>, <a href="https://publications.waset.org/abstracts/search?q=r-aptes" title=" r-aptes"> r-aptes</a> </p> <a href="https://publications.waset.org/abstracts/31242/effect-of-using-a-mixture-of-al2o3-nanoparticles-and-3-aminopropyltriethoxysilane-as-the-sensing-membrane-for-polysilicon-wire-on-ph-sensing" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/31242.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">414</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">19780</span> Fe-Doped Graphene Nanoparticles for Gas Sensing Applications </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Shivani%20A.%20Singh">Shivani A. Singh</a>, <a href="https://publications.waset.org/abstracts/search?q=Pravin%20S.%20More"> Pravin S. More</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In the present inspection, we indicate the falsification of Fe-doped graphene nanoparticles by modified Hummers method. Structural and physiochemical properties of the resulting pallets were explored with the help of ultraviolet-visible spectroscopy (UV-Vis), Fourier transform infrared spectroscopy (FTIR), X-ray powder diffraction (XRD) and scanning electron microscopy (SEM), Photoluminescence spectroscopy (PL) for graphene sample exhibits absorption peaks ~248nm. Pure graphene shows PL peak at 348 nm. After doping of Fe with graphene the PL peak shifted from 348 nm to 332 nm. The oxidation degree, i.e. the relative amount of oxygen functional groups was estimated from the relative intensities of the oxygen related bands (ORB) in the FTIR measurements. These analyses show that this modified material can be useful for gas sensing applications and to be used in diverse areas. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=chemical%20doping" title="chemical doping">chemical doping</a>, <a href="https://publications.waset.org/abstracts/search?q=graphene" title=" graphene"> graphene</a>, <a href="https://publications.waset.org/abstracts/search?q=gas%20sensing" title=" gas sensing"> gas sensing</a>, <a href="https://publications.waset.org/abstracts/search?q=sensing" title=" sensing"> sensing</a> </p> <a href="https://publications.waset.org/abstracts/79785/fe-doped-graphene-nanoparticles-for-gas-sensing-applications" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/79785.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">218</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19779</span> Genetic Algorithm and Multi Criteria Decision Making Approach for Compressive Sensing Based Direction of Arrival Estimation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ekin%20Nurba%C5%9F">Ekin Nurbaş</a> </p> <p class="card-text"><strong>Abstract:</strong></p> One of the essential challenges in array signal processing, which has drawn enormous research interest over the past several decades, is estimating the direction of arrival (DOA) of plane waves impinging on an array of sensors. In recent years, the Compressive Sensing based DoA estimation methods have been proposed by researchers, and it has been discovered that the Compressive Sensing (CS)-based algorithms achieved significant performances for DoA estimation even in scenarios where there are multiple coherent sources. On the other hand, the Genetic Algorithm, which is a method that provides a solution strategy inspired by natural selection, has been used in sparse representation problems in recent years and provides significant improvements in performance. With all of those in consideration, in this paper, a method that combines the Genetic Algorithm (GA) and the Multi-Criteria Decision Making (MCDM) approaches for Direction of Arrival (DoA) estimation in the Compressive Sensing (CS) framework is proposed. In this method, we generate a multi-objective optimization problem by splitting the norm minimization and reconstruction loss minimization parts of the Compressive Sensing algorithm. With the help of the Genetic Algorithm, multiple non-dominated solutions are achieved for the defined multi-objective optimization problem. Among the pareto-frontier solutions, the final solution is obtained with the multiple MCDM methods. Moreover, the performance of the proposed method is compared with the CS-based methods in the literature. <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=direction%20of%20arrival%20esitmation" title=" direction of arrival esitmation"> direction of arrival esitmation</a>, <a href="https://publications.waset.org/abstracts/search?q=multi%20criteria%20decision%20making" title=" multi criteria decision making"> multi criteria decision making</a>, <a href="https://publications.waset.org/abstracts/search?q=compressive%20sensing" title=" compressive sensing"> compressive sensing</a> </p> <a href="https://publications.waset.org/abstracts/154971/genetic-algorithm-and-multi-criteria-decision-making-approach-for-compressive-sensing-based-direction-of-arrival-estimation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/154971.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">147</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">19778</span> Doped and Co-doped ZnO Based Nanoparticles and their Photocatalytic and Gas Sensing Property</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Neha%20Verma">Neha Verma</a>, <a href="https://publications.waset.org/abstracts/search?q=Manik%20Rakhra"> Manik Rakhra</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Statement of the Problem: Nowadays, a tremendous increase in population and advanced industrialization augment the problems related to air and water pollutions. Growing industries promoting environmental danger, which is an alarming threat to the ecosystem. For safeguard, the environment, detection of perilous gases and release of colored wastewater is required for eutrophication pollution. Researchers around the globe are trying their best efforts to save the environment. For this remediation advanced oxidation process is used for potential applications. ZnO is an important semiconductor photocatalyst with high photocatalytic and gas sensing activities. For efficient photocatalytic and gas sensing properties, it is necessary to prepare a doped/co-doped ZnO compound to decrease the electron-hole recombination rates. However, lanthanide doped and co-doped metal oxide is seldom studied for photocatalytic and gas sensing applications. The purpose of this study is to describe the best photocatalyst for the photodegradation of dyes and gas sensing properties. Methodology & Theoretical Orientation: Economical framework has to be used for the synthesis of ZnO. In the depth literature survey, a simple combustion method is utilized for gas sensing and photocatalytic activities. Findings: Rare earth doped and co-doped ZnO nanoparticles were the best photocatalysts for photodegradation of organic dyes and different gas sensing applications by varying various factors such as pH, aging time, and different concentrations of doping and codoping metals in ZnO. Complete degradation of dye was observed only in min. Gas sensing nanodevice showed a better response and quick recovery time for doped/co-doped ZnO. Conclusion & Significance: In order to prevent air and water pollution, well crystalline ZnO nanoparticles were synthesized by rapid and economic method, which is used as photocatalyst for photodegradation of organic dyes and gas sensing applications to sense the release of hazardous gases from the environment. <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=photocatalyst" title=" photocatalyst"> photocatalyst</a>, <a href="https://publications.waset.org/abstracts/search?q=photodegradation%20of%20dye" title=" photodegradation of dye"> photodegradation of dye</a>, <a href="https://publications.waset.org/abstracts/search?q=gas%20sensor" title=" gas sensor"> gas sensor</a> </p> <a href="https://publications.waset.org/abstracts/142117/doped-and-co-doped-zno-based-nanoparticles-and-their-photocatalytic-and-gas-sensing-property" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/142117.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">155</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19777</span> Efficient Ground Targets Detection Using Compressive Sensing in Ground-Based Synthetic-Aperture Radar (SAR) Images</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Gherbi%20Nabil">Gherbi Nabil</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Detection of ground targets in SAR radar images is an important area for radar information processing. In the literature, various algorithms have been discussed in this context. However, most of them are of low robustness and accuracy. To this end, we discuss target detection in SAR images based on compressive sensing. Firstly, traditional SAR image target detection algorithms are discussed, and their limitations are highlighted. Secondly, a compressive sensing method is proposed based on the sparsity of SAR images. Next, the detection problem is solved using Multiple Measurements Vector configuration. Furthermore, a robust Alternating Direction Method of Multipliers (ADMM) is developed to solve the optimization problem. Finally, the detection results obtained using raw complex data are presented. Experimental results on real SAR images have verified the effectiveness of the proposed algorithm. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=compressive%20sensing" title="compressive sensing">compressive sensing</a>, <a href="https://publications.waset.org/abstracts/search?q=raw%20complex%20data" title=" raw complex data"> raw complex data</a>, <a href="https://publications.waset.org/abstracts/search?q=synthetic%20aperture%20radar" title=" synthetic aperture radar"> synthetic aperture radar</a>, <a href="https://publications.waset.org/abstracts/search?q=ADMM" title=" ADMM"> ADMM</a> </p> <a href="https://publications.waset.org/abstracts/191958/efficient-ground-targets-detection-using-compressive-sensing-in-ground-based-synthetic-aperture-radar-sar-images" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/191958.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">20</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">19776</span> Optimal Sensing Technique for Estimating Stress Distribution of 2-D Steel Frame Structure Using Genetic Algorithm</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jun%20Su%20Park">Jun Su Park</a>, <a href="https://publications.waset.org/abstracts/search?q=Byung%20Kwan%20Oh"> Byung Kwan Oh</a>, <a href="https://publications.waset.org/abstracts/search?q=Jin%20Woo%20Hwang"> Jin Woo Hwang</a>, <a href="https://publications.waset.org/abstracts/search?q=Yousok%20Kim"> Yousok Kim</a>, <a href="https://publications.waset.org/abstracts/search?q=Hyo%20Seon%20Park"> Hyo Seon Park</a> </p> <p class="card-text"><strong>Abstract:</strong></p> For the structural safety, the maximum stress calculated from the stress distribution of a structure is widely used. The stress distribution can be estimated by deformed shape of the structure obtained from measurement. Although the estimation of stress is strongly affected by the location and number of sensing points, most studies have conducted the stress estimation without reasonable basis on sensing plan such as the location and number of sensors. In this paper, an optimal sensing technique for estimating the stress distribution is proposed. This technique proposes the optimal location and number of sensing points for a 2-D frame structure while minimizing the error of stress distribution between analytical model and estimation by cubic smoothing splines using genetic algorithm. To verify the proposed method, the optimal sensor measurement technique is applied to simulation tests on 2-D steel frame structure. The simulation tests are performed under various loading scenarios. Through those tests, the optimal sensing plan for the structure is suggested and verified. <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=optimal%20sensing" title=" optimal sensing"> optimal sensing</a>, <a href="https://publications.waset.org/abstracts/search?q=optimizing%20sensor%20placements" title=" optimizing sensor placements"> optimizing sensor placements</a>, <a href="https://publications.waset.org/abstracts/search?q=steel%20frame%20structure" title=" steel frame structure"> steel frame structure</a> </p> <a href="https://publications.waset.org/abstracts/25426/optimal-sensing-technique-for-estimating-stress-distribution-of-2-d-steel-frame-structure-using-genetic-algorithm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/25426.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">531</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">19775</span> Cooperative Spectrum Sensing Using Hybrid IWO/PSO Algorithm in Cognitive Radio Networks</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Deepa%20Das">Deepa Das</a>, <a href="https://publications.waset.org/abstracts/search?q=Susmita%20Das"> Susmita Das</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Cognitive Radio (CR) is an emerging technology to combat the spectrum scarcity issues. This is achieved by consistently sensing the spectrum, and detecting the under-utilized frequency bands without causing undue interference to the primary user (PU). In soft decision fusion (SDF) based cooperative spectrum sensing, various evolutionary algorithms have been discussed, which optimize the weight coefficient vector for maximizing the detection performance. In this paper, we propose the hybrid invasive weed optimization and particle swarm optimization (IWO/PSO) algorithm as a fast and global optimization method, which improves the detection probability with a lesser sensing time. Then, the efficiency of this algorithm is compared with the standard invasive weed optimization (IWO), particle swarm optimization (PSO), genetic algorithm (GA) and other conventional SDF based methods on the basis of convergence and detection probability. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=cognitive%20radio" title="cognitive radio">cognitive radio</a>, <a href="https://publications.waset.org/abstracts/search?q=spectrum%20sensing" title=" spectrum sensing"> spectrum sensing</a>, <a href="https://publications.waset.org/abstracts/search?q=soft%20decision%20fusion" title=" soft decision fusion"> soft decision fusion</a>, <a href="https://publications.waset.org/abstracts/search?q=GA" title=" GA"> GA</a>, <a href="https://publications.waset.org/abstracts/search?q=PSO" title=" PSO"> PSO</a>, <a href="https://publications.waset.org/abstracts/search?q=IWO" title=" IWO"> IWO</a>, <a href="https://publications.waset.org/abstracts/search?q=hybrid%20IWO%2FPSO" title=" hybrid IWO/PSO"> hybrid IWO/PSO</a> </p> <a href="https://publications.waset.org/abstracts/9362/cooperative-spectrum-sensing-using-hybrid-iwopso-algorithm-in-cognitive-radio-networks" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/9362.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">467</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">19774</span> Reliability Factors Based Fuzzy Logic Scheme for Spectrum Sensing</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Tallataf%20Rasheed">Tallataf Rasheed</a>, <a href="https://publications.waset.org/abstracts/search?q=Adnan%20Rashdi"> Adnan Rashdi</a>, <a href="https://publications.waset.org/abstracts/search?q=Ahmad%20Naeem%20Akhtar"> Ahmad Naeem Akhtar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The accurate spectrum sensing is a fundamental requirement of dynamic spectrum access for deployment of Cognitive Radio Network (CRN). To acheive this requirement a Reliability factors based Fuzzy Logic (RFL) Scheme for Spectrum Sensing has been proposed in this paper. Cognitive Radio User (CRU) predicts the presence or absence of Primary User (PU) using energy detector and calculates the Reliability factors which are SNR of sensing node, threshold of energy detector and decision difference of each node with other nodes in a cooperative spectrum sensing environment. Then the decision of energy detector is combined with Reliability factors of sensing node using Fuzzy Logic. These Reliability Factors used in RFL Scheme describes the reliability of decision made by a CRU to improve the local spectrum sensing. This Fuzzy combining scheme provides the accuracy of decision made by sensornode. The simulation results have shown that the proposed technique provide better PU detection probability than existing Spectrum Sensing Techniques. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=cognitive%20radio" title="cognitive radio">cognitive radio</a>, <a href="https://publications.waset.org/abstracts/search?q=spectrum%20sensing" title=" spectrum sensing"> spectrum sensing</a>, <a href="https://publications.waset.org/abstracts/search?q=energy%20detector" title=" energy detector"> energy detector</a>, <a href="https://publications.waset.org/abstracts/search?q=reliability%20factors" title=" reliability factors"> reliability factors</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20logic" title=" fuzzy logic"> fuzzy logic</a> </p> <a href="https://publications.waset.org/abstracts/77586/reliability-factors-based-fuzzy-logic-scheme-for-spectrum-sensing" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/77586.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">486</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">19773</span> Mapping of Arenga Pinnata Tree Using Remote Sensing</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Zulkiflee%20Abd%20Latif">Zulkiflee Abd Latif</a>, <a href="https://publications.waset.org/abstracts/search?q=Sitinor%20Atikah%20Nordin"> Sitinor Atikah Nordin</a>, <a href="https://publications.waset.org/abstracts/search?q=Alawi%20Sulaiman"> Alawi Sulaiman</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Different tree species possess different and various benefits. Arenga Pinnata tree species own several potential uses that is valuable for the economy and the country. Mapping vegetation using remote sensing technique involves various process, techniques and consideration. Using satellite imagery, this method enables the access of inaccessible area and with the availability of near infra-red band; it is useful in vegetation analysis, especially in identifying tree species. Pixel-based and object-based classification technique is used as a method in this study. Pixel-based classification technique used in this study divided into unsupervised and supervised classification. Object based classification technique becomes more popular another alternative method in classification process. Using spectral, texture, color and other information, to classify the target make object-based classification is a promising technique for classification. Classification of Arenga Pinnata trees is overlaid with elevation, slope and aspect, soil and river data and several other data to give information regarding the tree character and living environment. This paper will present the utilization of remote sensing technique in order to map Arenga Pinnata tree species <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Arenga%20Pinnata" title="Arenga Pinnata">Arenga Pinnata</a>, <a href="https://publications.waset.org/abstracts/search?q=pixel-based%20classification" title=" pixel-based classification"> pixel-based classification</a>, <a href="https://publications.waset.org/abstracts/search?q=object-based%20classification" title=" object-based classification"> object-based classification</a>, <a href="https://publications.waset.org/abstracts/search?q=remote%20sensing" title=" remote sensing"> remote sensing</a> </p> <a href="https://publications.waset.org/abstracts/13681/mapping-of-arenga-pinnata-tree-using-remote-sensing" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/13681.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">380</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">19772</span> Linear Frequency Modulation-Frequency Shift Keying Radar with Compressive Sensing</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ho%20Jeong%20Jin">Ho Jeong Jin</a>, <a href="https://publications.waset.org/abstracts/search?q=Chang%20Won%20Seo"> Chang Won Seo</a>, <a href="https://publications.waset.org/abstracts/search?q=Choon%20Sik%20Cho"> Choon Sik Cho</a>, <a href="https://publications.waset.org/abstracts/search?q=Bong%20Yong%20Choi"> Bong Yong Choi</a>, <a href="https://publications.waset.org/abstracts/search?q=Kwang%20Kyun%20Na"> Kwang Kyun Na</a>, <a href="https://publications.waset.org/abstracts/search?q=Sang%20Rok%20Lee"> Sang Rok Lee</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, a radar signal processing technique using the LFM-FSK (Linear Frequency Modulation-Frequency Shift Keying) is proposed for reducing the false alarm rate based on the compressive sensing. The LFM-FSK method combines FMCW (Frequency Modulation Continuous Wave) signal with FSK (Frequency Shift Keying). This shows an advantage which can suppress the ghost phenomenon without the complicated CFAR (Constant False Alarm Rate) algorithm. Moreover, the parametric sparse algorithm applying the compressive sensing that restores signals efficiently with respect to the incomplete data samples is also integrated, leading to reducing the burden of ADC in the receiver of radars. 24 GHz FMCW signal is applied and tested in the real environment with FSK modulated data for verifying the proposed algorithm along with the compressive sensing. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=compressive%20sensing" title="compressive sensing">compressive sensing</a>, <a href="https://publications.waset.org/abstracts/search?q=LFM-FSK%20radar" title=" LFM-FSK radar"> LFM-FSK radar</a>, <a href="https://publications.waset.org/abstracts/search?q=radar%20signal%20processing" title=" radar signal processing"> radar signal processing</a>, <a href="https://publications.waset.org/abstracts/search?q=sparse%20algorithm" title=" sparse algorithm"> sparse algorithm</a> </p> <a href="https://publications.waset.org/abstracts/51309/linear-frequency-modulation-frequency-shift-keying-radar-with-compressive-sensing" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/51309.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">483</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">19771</span> Performance of Nakagami Fading Channel over Energy Detection Based Spectrum Sensing</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=M.%20Ranjeeth">M. Ranjeeth</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20Anuradha"> S. Anuradha</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Spectrum sensing is the main feature of cognitive radio technology. Spectrum sensing gives an idea of detecting the presence of the primary users in a licensed spectrum. In this paper we compare the theoretical results of detection probability of different fading environments like Rayleigh, Rician, Nakagami-m fading channels with the simulation results using energy detection based spectrum sensing. The numerical results are plotted as P_f Vs P_d for different SNR values, fading parameters. It is observed that Nakagami fading channel performance is better than other fading channels by using energy detection in spectrum sensing. A MATLAB simulation test bench has been implemented to know the performance of energy detection in different fading channel environment. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=spectrum%20sensing" title="spectrum sensing">spectrum sensing</a>, <a href="https://publications.waset.org/abstracts/search?q=energy%20detection" title=" energy detection"> energy detection</a>, <a href="https://publications.waset.org/abstracts/search?q=fading%20channels" title=" fading channels"> fading channels</a>, <a href="https://publications.waset.org/abstracts/search?q=probability%20of%20detection" title=" probability of detection"> probability of detection</a>, <a href="https://publications.waset.org/abstracts/search?q=probability%20of%20false%20alarm" title=" probability of false alarm"> probability of false alarm</a> </p> <a href="https://publications.waset.org/abstracts/15800/performance-of-nakagami-fading-channel-over-energy-detection-based-spectrum-sensing" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/15800.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">532</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">19770</span> A New Framework for ECG Signal Modeling and Compression Based on Compressed Sensing Theory</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Siavash%20Eftekharifar">Siavash Eftekharifar</a>, <a href="https://publications.waset.org/abstracts/search?q=Tohid%20Yousefi%20Rezaii"> Tohid Yousefi Rezaii</a>, <a href="https://publications.waset.org/abstracts/search?q=Mahdi%20Shamsi"> Mahdi Shamsi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The purpose of this paper is to exploit compressed sensing (CS) method in order to model and compress the electrocardiogram (ECG) signals at a high compression ratio. In order to obtain a sparse representation of the ECG signals, first a suitable basis matrix with Gaussian kernels, which are shown to nicely fit the ECG signals, is constructed. Then the sparse model is extracted by applying some optimization technique. Finally, the CS theory is utilized to obtain a compressed version of the sparse signal. Reconstruction of the ECG signal from the compressed version is also done to prove the reliability of the algorithm. At this stage, a greedy optimization technique is used to reconstruct the ECG signal and the Mean Square Error (MSE) is calculated to evaluate the precision of the proposed compression method. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=compressed%20sensing" title="compressed sensing">compressed sensing</a>, <a href="https://publications.waset.org/abstracts/search?q=ECG%20compression" title=" ECG compression"> ECG compression</a>, <a href="https://publications.waset.org/abstracts/search?q=Gaussian%20kernel" title=" Gaussian kernel"> Gaussian kernel</a>, <a href="https://publications.waset.org/abstracts/search?q=sparse%20representation" title=" sparse representation"> sparse representation</a> </p> <a href="https://publications.waset.org/abstracts/31469/a-new-framework-for-ecg-signal-modeling-and-compression-based-on-compressed-sensing-theory" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/31469.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">19769</span> Steepest Descent Method with New Step Sizes</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Bib%20Paruhum%20Silalahi">Bib Paruhum Silalahi</a>, <a href="https://publications.waset.org/abstracts/search?q=Djihad%20Wungguli"> Djihad Wungguli</a>, <a href="https://publications.waset.org/abstracts/search?q=Sugi%20Guritman"> Sugi Guritman</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Steepest descent method is a simple gradient method for optimization. This method has a slow convergence in heading to the optimal solution, which occurs because of the zigzag form of the steps. Barzilai and Borwein modified this algorithm so that it performs well for problems with large dimensions. Barzilai and Borwein method results have sparked a lot of research on the method of steepest descent, including alternate minimization gradient method and Yuan method. Inspired by previous works, we modified the step size of the steepest descent method. We then compare the modification results against the Barzilai and Borwein method, alternate minimization gradient method and Yuan method for quadratic function cases in terms of the iterations number and the running time. The average results indicate that the steepest descent method with the new step sizes provide good results for small dimensions and able to compete with the results of Barzilai and Borwein method and the alternate minimization gradient method for large dimensions. The new step sizes have faster convergence compared to the other methods, especially for cases with large dimensions. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=steepest%20descent" title="steepest descent">steepest descent</a>, <a href="https://publications.waset.org/abstracts/search?q=line%20search" title=" line search"> line search</a>, <a href="https://publications.waset.org/abstracts/search?q=iteration" title=" iteration"> iteration</a>, <a href="https://publications.waset.org/abstracts/search?q=running%20time" title=" running time"> running time</a>, <a href="https://publications.waset.org/abstracts/search?q=unconstrained%20optimization" title=" unconstrained optimization"> unconstrained optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=convergence" title=" convergence"> convergence</a> </p> <a href="https://publications.waset.org/abstracts/29734/steepest-descent-method-with-new-step-sizes" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/29734.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">540</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">19768</span> Rb-Modified Few-Layered Graphene for Gas Sensing Application</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Vasant%20Reddy">Vasant Reddy</a>, <a href="https://publications.waset.org/abstracts/search?q=Shivani%20A.%20Singh"> Shivani A. Singh</a>, <a href="https://publications.waset.org/abstracts/search?q=Pravin%20S.%20More"> Pravin S. More</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In the present investigation, we demonstrated the fabrication of few-layers of graphene sheets with alkali metal i.e. Rb-G using chemical route method. The obtained materials were characterized by means of chemical, structural and electrical techniques, using the ultraviolet-visible spectroscopy (UV-Vis), Fourier transform infrared spectroscopy (FTIR), X-ray powder diffraction (XRD), scanning electron microscopy (SEM) and 4 points probe, respectively. The XRD studies were carried out to understand the phase of the samples where we found a sharp peak of Rb-G at 26.470. UV-Spectroscopy of Graphene and Rb-modified graphene samples shows the absorption peaks at ~248 nm and ~318 nm respectively. These analyses show that this modified material can be useful for gas sensing applications and to be used in diverse areas. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=chemical%20route" title="chemical route">chemical route</a>, <a href="https://publications.waset.org/abstracts/search?q=graphene" title=" graphene"> graphene</a>, <a href="https://publications.waset.org/abstracts/search?q=gas%20sensing" title=" gas sensing"> gas sensing</a>, <a href="https://publications.waset.org/abstracts/search?q=UV-spectroscopy" title=" UV-spectroscopy"> UV-spectroscopy</a> </p> <a href="https://publications.waset.org/abstracts/79789/rb-modified-few-layered-graphene-for-gas-sensing-application" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/79789.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">269</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">19767</span> Radio-Frequency Technologies for Sensing and Imaging</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Cam%20Nguyen">Cam Nguyen</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Rapid, accurate, and safe sensing and imaging of physical quantities or structures finds many applications and is of significant interest to society. Sensing and imaging using radio-frequency (RF) techniques, particularly, has gone through significant development and subsequently established itself as a unique territory in the sensing world. RF sensing and imaging has played a critical role in providing us many sensing and imaging abilities beyond our human capabilities, benefiting both civilian and military applications - for example, from sensing abnormal conditions underneath some structures’ surfaces to detection and classification of concealed items, hidden activities, and buried objects. We present the developments of several sensing and imaging systems implementing RF technologies like ultra-wide band (UWB), synthetic-pulse, and interferometry. These systems are fabricated completely using RF integrated circuits. The UWB impulse system operates over multiple pulse durations from 450 to 1170 ps with 5.5-GHz RF bandwidth. It performs well through tests of various samples, demonstrating its usefulness for subsurface sensing. The synthetic-pulse system operating from 0.6 to 5.6 GHz can assess accurately subsurface structures. The synthetic-pulse system operating from 29.72-37.7 GHz demonstrates abilities for various surface and near-surface sensing such as profile mapping, liquid-level monitoring, and anti-personnel mine locating. The interferometric system operating at 35.6 GHz demonstrates its multi-functional capability for measurement of displacements and slow velocities. These RF sensors are attractive and useful for various surface and subsurface sensing applications. This paper was made possible by NPRP grant # 6-241-2-102 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=RF%20sensors" title="RF sensors">RF sensors</a>, <a href="https://publications.waset.org/abstracts/search?q=radars" title=" radars"> radars</a>, <a href="https://publications.waset.org/abstracts/search?q=surface%20sensing" title=" surface sensing"> surface sensing</a>, <a href="https://publications.waset.org/abstracts/search?q=subsurface%20sensing" title=" subsurface sensing"> subsurface sensing</a> </p> <a href="https://publications.waset.org/abstracts/73251/radio-frequency-technologies-for-sensing-and-imaging" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/73251.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">316</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19766</span> A New Modification of Nonlinear Conjugate Gradient Coefficients with Global Convergence Properties</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ahmad%20Alhawarat">Ahmad Alhawarat</a>, <a href="https://publications.waset.org/abstracts/search?q=Mustafa%20Mamat"> Mustafa Mamat</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohd%20Rivaie"> Mohd Rivaie</a>, <a href="https://publications.waset.org/abstracts/search?q=Ismail%20Mohd"> Ismail Mohd</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Conjugate gradient method has been enormously used to solve large scale unconstrained optimization problems due to the number of iteration, memory, CPU time, and convergence property, in this paper we find a new class of nonlinear conjugate gradient coefficient with global convergence properties proved by exact line search. The numerical results for our new βK give a good result when it compared with well-known formulas. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=conjugate%20gradient%20method" title="conjugate gradient method">conjugate gradient method</a>, <a href="https://publications.waset.org/abstracts/search?q=conjugate%20gradient%20coefficient" title=" conjugate gradient coefficient"> conjugate gradient coefficient</a>, <a href="https://publications.waset.org/abstracts/search?q=global%20convergence" title=" global convergence"> global convergence</a> </p> <a href="https://publications.waset.org/abstracts/1392/a-new-modification-of-nonlinear-conjugate-gradient-coefficients-with-global-convergence-properties" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/1392.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 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