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basis extreme learning</title> <meta name="description" content="Search results for: orthogonal basis extreme learning"> <meta name="keywords" content="orthogonal basis extreme learning"> <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" /> 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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="orthogonal basis extreme learning"> <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> 11403</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: orthogonal basis extreme learning</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">11403</span> Orthogonal Basis Extreme Learning Algorithm and Function Approximation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ying%20Li">Ying Li</a>, <a href="https://publications.waset.org/abstracts/search?q=Yan%20Li"> Yan Li</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A new algorithm for single hidden layer feedforward neural networks (SLFN), Orthogonal Basis Extreme Learning (OBEL) algorithm, is proposed and the algorithm derivation is given in the paper. The algorithm can decide both the NNs parameters and the neuron number of hidden layer(s) during training while providing extreme fast learning speed. It will provide a practical way to develop NNs. The simulation results of function approximation showed that the algorithm is effective and feasible with good accuracy and adaptability. <p class="card-text"><strong>Keywords:</strong> <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=orthogonal%20basis%20extreme%20learning" title=" orthogonal basis extreme learning"> orthogonal basis extreme learning</a>, <a href="https://publications.waset.org/abstracts/search?q=function%20approximation" title=" function approximation"> function approximation</a> </p> <a href="https://publications.waset.org/abstracts/15129/orthogonal-basis-extreme-learning-algorithm-and-function-approximation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/15129.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">534</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">11402</span> Encryption Image via Mutual Singular Value Decomposition</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Adil%20Al-Rammahi">Adil Al-Rammahi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Image or document encryption is needed through e- government data base. Really in this paper we introduce two matrices images, one is the public, and the second is the secret (original). The analyses of each matrix is achieved using the transformation of singular values decomposition. So each matrix is transformed or analyzed to three matrices say row orthogonal basis, column orthogonal basis, and spectral diagonal basis. Product of the two row basis is calculated. Similarly the product of the two column basis is achieved. Finally we transform or save the files of public, row product and column product. In decryption stage, the original image is deduced by mutual method of the three public files. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=image%20cryptography" title="image cryptography">image cryptography</a>, <a href="https://publications.waset.org/abstracts/search?q=singular%20values%20decomposition" title=" singular values decomposition"> singular values decomposition</a> </p> <a href="https://publications.waset.org/abstracts/13714/encryption-image-via-mutual-singular-value-decomposition" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/13714.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">436</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">11401</span> Every g-Riesz Basis is a Riesz Basis</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mehdi%20Rashidi-Kouchi">Mehdi Rashidi-Kouchi</a>, <a href="https://publications.waset.org/abstracts/search?q=Asghar%20Rahimi"> Asghar Rahimi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Sun introduced a generalization of frames and showed that this includes more other cases of generalizations of frame concept and proved that many basic properties can be derived within this more general context. Another generalization of frames is frames in Hilbert C*-module. It has been proved that every g-frame in Hilbert space H respect to Hilbert space K is a frame for B(H;K) as Hilbert C*-module. We show that every g-Riesz basis for Hilbert space H respect to K by add a condition is a Riesz basis for Hilbert B(K)-module B(H;K). Also, we investigate similar result for g-orthonormal and orthogonal bases. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=frame" title="frame">frame</a>, <a href="https://publications.waset.org/abstracts/search?q=g-frame" title=" g-frame"> g-frame</a>, <a href="https://publications.waset.org/abstracts/search?q=Riesz%20basis" title=" Riesz basis"> Riesz basis</a>, <a href="https://publications.waset.org/abstracts/search?q=g-Riesz%20basis" title=" g-Riesz basis"> g-Riesz basis</a>, <a href="https://publications.waset.org/abstracts/search?q=Hilbert%20C%2A-module" title=" Hilbert C*-module"> Hilbert C*-module</a> </p> <a href="https://publications.waset.org/abstracts/17888/every-g-riesz-basis-is-a-riesz-basis" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/17888.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">471</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">11400</span> A Machine Learning-Based Approach to Capture Extreme Rainfall Events</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Willy%20Mbenza">Willy Mbenza</a>, <a href="https://publications.waset.org/abstracts/search?q=Sho%20Kenjiro"> Sho Kenjiro</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Increasing efforts are directed towards a better understanding and foreknowledge of extreme precipitation likelihood, given the adverse effects associated with their occurrence. This knowledge plays a crucial role in long-term planning and the formulation of effective emergency response. However, predicting extreme events reliably presents a challenge to conventional empirical/statistics due to the involvement of numerous variables spanning different time and space scales. In the recent time, Machine Learning has emerged as a promising tool for predicting the dynamics of extreme precipitation. ML techniques enables the consideration of both local and regional physical variables that have a strong influence on the likelihood of extreme precipitation. These variables encompasses factors such as air temperature, soil moisture, specific humidity, aerosol concentration, among others. In this study, we develop an ML model that incorporates both local and regional variables while establishing a robust relationship between physical variables and precipitation during the downscaling process. Furthermore, the model provides valuable information on the frequency and duration of a given intensity of precipitation. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=machine%20learning%20%28ML%29" title="machine learning (ML)">machine learning (ML)</a>, <a href="https://publications.waset.org/abstracts/search?q=predictions" title=" predictions"> predictions</a>, <a href="https://publications.waset.org/abstracts/search?q=rainfall%20events" title=" rainfall events"> rainfall events</a>, <a href="https://publications.waset.org/abstracts/search?q=regional%20variables" title=" regional variables"> regional variables</a> </p> <a href="https://publications.waset.org/abstracts/168878/a-machine-learning-based-approach-to-capture-extreme-rainfall-events" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/168878.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">88</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">11399</span> 3D Printing Perceptual Models of Preference Using a Fuzzy Extreme Learning Machine Approach</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Xinyi%20Le">Xinyi Le</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, 3D printing orientations were determined through our perceptual model. Some FDM (Fused Deposition Modeling) 3D printers, which are widely used in universities and industries, often require support structures during the additive manufacturing. After removing the residual material, some surface artifacts remain at the contact points. These artifacts will damage the function and visual effect of the model. To prevent the impact of these artifacts, we present a fuzzy extreme learning machine approach to find printing directions that avoid placing supports in perceptually significant regions. The proposed approach is able to solve the evaluation problem by combing both the subjective knowledge and objective information. Our method combines the advantages of fuzzy theory, auto-encoders, and extreme learning machine. Fuzzy set theory is applied for dealing with subjective preference information, and auto-encoder step is used to extract good features without supervised labels before extreme learning machine. An extreme learning machine method is then developed successfully for training and learning perceptual models. The performance of this perceptual model will be demonstrated on both natural and man-made objects. It is a good human-computer interaction practice which draws from supporting knowledge on both the machine side and the human side. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=3d%20printing" title="3d printing">3d printing</a>, <a href="https://publications.waset.org/abstracts/search?q=perceptual%20model" title=" perceptual model"> perceptual model</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20evaluation" title=" fuzzy evaluation"> fuzzy evaluation</a>, <a href="https://publications.waset.org/abstracts/search?q=data-driven%20approach" title=" data-driven approach"> data-driven approach</a> </p> <a href="https://publications.waset.org/abstracts/67233/3d-printing-perceptual-models-of-preference-using-a-fuzzy-extreme-learning-machine-approach" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/67233.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">438</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">11398</span> Applying the Extreme-Based Teaching Model in Post-Secondary Online Classroom Setting: A Field Experiment</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Leon%20Pan">Leon Pan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The first programming course within post-secondary education has long been recognized as a challenging endeavor for both educators and students alike. Historically, these courses have exhibited high failure rates and a notable number of dropouts. Instructors often lament students' lack of effort in their coursework, and students often express frustration that the teaching methods employed are not effective. Drawing inspiration from the successful principles of Extreme Programming, this study introduces an approach—the Extremes-based teaching model — aimed at enhancing the teaching of introductory programming courses. To empirically determine the effectiveness of the model, a comparison was made between a section taught using the extreme-based model and another utilizing traditional teaching methods. Notably, the extreme-based teaching class required students to work collaboratively on projects while also demanding continuous assessment and performance enhancement within groups. This paper details the application of the extreme-based model within the post-secondary online classroom context and presents the compelling results that emphasize its effectiveness in advancing the teaching and learning experiences. The extreme-based model led to a significant increase of 13.46 points in the weighted total average and a commendable 10% reduction in the failure rate. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=extreme-based%20teaching%20model" title="extreme-based teaching model">extreme-based teaching model</a>, <a href="https://publications.waset.org/abstracts/search?q=innovative%20pedagogical%20methods" title=" innovative pedagogical methods"> innovative pedagogical methods</a>, <a href="https://publications.waset.org/abstracts/search?q=project-based%20learning" title=" project-based learning"> project-based learning</a>, <a href="https://publications.waset.org/abstracts/search?q=team-based%20learning" title=" team-based learning"> team-based learning</a> </p> <a href="https://publications.waset.org/abstracts/171936/applying-the-extreme-based-teaching-model-in-post-secondary-online-classroom-setting-a-field-experiment" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/171936.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">59</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">11397</span> Least Support Orthogonal Matching Pursuit (LS-OMP) Recovery Method for Invisible Watermarking Image</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Israa%20Sh.%20Tawfic">Israa Sh. Tawfic</a>, <a href="https://publications.waset.org/abstracts/search?q=Sema%20Koc%20Kayhan"> Sema Koc Kayhan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, first, we propose least support orthogonal matching pursuit (LS-OMP) algorithm to improve the performance, of the OMP (orthogonal matching pursuit) algorithm. LS-OMP algorithm adaptively chooses optimum L (least part of support), at each iteration. This modification helps to reduce the computational complexity significantly and performs better than OMP algorithm. Second, we give the procedure for the invisible image watermarking in the presence of compressive sampling. The image reconstruction based on a set of watermarked measurements is performed using LS-OMP. <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=orthogonal%20matching%20pursuit" title=" orthogonal matching pursuit"> orthogonal matching pursuit</a>, <a href="https://publications.waset.org/abstracts/search?q=restricted%20isometry%20property" title=" restricted isometry property"> restricted isometry property</a>, <a href="https://publications.waset.org/abstracts/search?q=signal%20reconstruction" title=" signal reconstruction"> signal reconstruction</a>, <a href="https://publications.waset.org/abstracts/search?q=least%20support%20orthogonal%20matching%20pursuit" title=" least support orthogonal matching pursuit"> least support orthogonal matching pursuit</a>, <a href="https://publications.waset.org/abstracts/search?q=watermark" title=" watermark"> watermark</a> </p> <a href="https://publications.waset.org/abstracts/15820/least-support-orthogonal-matching-pursuit-ls-omp-recovery-method-for-invisible-watermarking-image" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/15820.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">338</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">11396</span> The Power of the Proper Orthogonal Decomposition Method</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Charles%20Lee">Charles Lee</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The Principal Orthogonal Decomposition (POD) technique has been used as a model reduction tool for many applications in engineering and science. In principle, one begins with an ensemble of data, called snapshots, collected from an experiment or laboratory results. The beauty of the POD technique is that when applied, the entire data set can be represented by the smallest number of orthogonal basis elements. It is the such capability that allows us to reduce the complexity and dimensions of many physical applications. Mathematical formulations and numerical schemes for the POD method will be discussed along with applications in NASA’s Deep Space Large Antenna Arrays, Satellite Image Reconstruction, Cancer Detection with DNA Microarray Data, Maximizing Stock Return, and Medical Imaging. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=reduced-order%20methods" title="reduced-order methods">reduced-order methods</a>, <a href="https://publications.waset.org/abstracts/search?q=principal%20component%20analysis" title=" principal component analysis"> principal component analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=cancer%20detection" title=" cancer detection"> cancer detection</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20reconstruction" title=" image reconstruction"> image reconstruction</a>, <a href="https://publications.waset.org/abstracts/search?q=stock%20portfolios" title=" stock portfolios"> stock portfolios</a> </p> <a href="https://publications.waset.org/abstracts/160375/the-power-of-the-proper-orthogonal-decomposition-method" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/160375.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">84</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">11395</span> Investigation on Flexural Behavior of Non-Crimp 3D Orthogonal Weave Carbon Composite Reinforcement</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sh.%20Minapoor">Sh. Minapoor</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20Ajeli"> S. Ajeli</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Non-crimp three-dimensional (3D) orthogonal carbon fabrics are one of the useful textiles reinforcements in composites. In this paper, flexural and bending properties of a carbon non-crimp 3D orthogonal woven reinforcement are experimentally investigated. The present study is focused on the understanding and measurement of the main bending parameters including flexural stress, strain, and modulus. For this purpose, the three-point bending test method is used and the load-displacement curves are analyzed. The influence of some weave's parameters such as yarn type, geometry of structure, and fiber volume fraction on bending behavior of non-crimp 3D orthogonal carbon fabric is investigated. The obtained results also represent a dataset for the simulation of flexural behavior of non-crimp 3D orthogonal weave carbon composite reinforcement. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=non-crimp%203D%20orthogonal%20weave" title="non-crimp 3D orthogonal weave">non-crimp 3D orthogonal weave</a>, <a href="https://publications.waset.org/abstracts/search?q=carbon%20composite%20reinforcement" title=" carbon composite reinforcement"> carbon composite reinforcement</a>, <a href="https://publications.waset.org/abstracts/search?q=flexural%20behavior" title=" flexural behavior"> flexural behavior</a>, <a href="https://publications.waset.org/abstracts/search?q=three-point%20bending" title=" three-point bending"> three-point bending</a> </p> <a href="https://publications.waset.org/abstracts/50505/investigation-on-flexural-behavior-of-non-crimp-3d-orthogonal-weave-carbon-composite-reinforcement" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/50505.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">297</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">11394</span> Structural Reliability Analysis Using Extreme Learning Machine</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mehul%20Srivastava">Mehul Srivastava</a>, <a href="https://publications.waset.org/abstracts/search?q=Sharma%20Tushar%20Ravikant"> Sharma Tushar Ravikant</a>, <a href="https://publications.waset.org/abstracts/search?q=Mridul%20Krishn%20Mishra"> Mridul Krishn Mishra</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In structural design, the evaluation of safety and probability failure of structure is of significant importance, mainly when the variables are random. On real structures, structural reliability can be evaluated obtaining an implicit limit state function. The structural reliability limit state function is obtained depending upon the statistically independent variables. In the analysis of reliability, we considered the statistically independent random variables to be the load intensity applied and the depth or height of the beam member considered. There are many approaches for structural reliability problems. In this paper Extreme Learning Machine technique and First Order Second Moment Method is used to determine the reliability indices for the same set of variables. The reliability index obtained using ELM is compared with the reliability index obtained using FOSM. Higher the reliability index, more feasible is the method to determine the reliability. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=reliability" title="reliability">reliability</a>, <a href="https://publications.waset.org/abstracts/search?q=reliability%20index" title=" reliability index"> reliability index</a>, <a href="https://publications.waset.org/abstracts/search?q=statistically%20independent" title=" statistically independent"> statistically independent</a>, <a href="https://publications.waset.org/abstracts/search?q=extreme%20learning%20machine" title=" extreme learning machine"> extreme learning machine</a> </p> <a href="https://publications.waset.org/abstracts/21683/structural-reliability-analysis-using-extreme-learning-machine" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/21683.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">682</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">11393</span> An Approximation Algorithm for the Non Orthogonal Cutting Problem</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=R.%20Ouafi">R. Ouafi</a>, <a href="https://publications.waset.org/abstracts/search?q=F.%20Ouafi"> F. Ouafi </a> </p> <p class="card-text"><strong>Abstract:</strong></p> We study the problem of cutting a rectangular material entity into smaller sub-entities of trapezoidal forms with minimum waste of the material. This problem will be denoted TCP (Trapezoidal Cutting Problem). The TCP has many applications in manufacturing processes of various industries: pipe line design (petro chemistry), the design of airfoil (aeronautical) or cuts of the components of textile products. We introduce an orthogonal build to provide the optimal horizontal and vertical homogeneous strips. In this paper we develop a general heuristic search based upon orthogonal build. By solving two one-dimensional knapsack problems, we combine the horizontal and vertical homogeneous strips to give a non orthogonal cutting pattern. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=combinatorial%20optimization" title="combinatorial optimization">combinatorial optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=cutting%20problem" title=" cutting problem"> cutting problem</a>, <a href="https://publications.waset.org/abstracts/search?q=heuristic" title=" heuristic"> heuristic</a> </p> <a href="https://publications.waset.org/abstracts/19497/an-approximation-algorithm-for-the-non-orthogonal-cutting-problem" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/19497.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">541</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">11392</span> Revisiting High School Students’ Learning Styles in English Subject</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Aroona%20Hashmi">Aroona Hashmi </a> </p> <p class="card-text"><strong>Abstract:</strong></p> The prime motive for this endeavor was to explore the tenth grade English class students’ preferred learning styles studying in government secondary school so that English subject teachers could tailor their pedagogical strategies in relation to their students learning needs. The further aim of this study was to identify any significance difference among the students on a gender basis, area basis and different categories of school basis. The population of this study consisting of all the secondary level schools working in the government sector and positioned in the province of Punjab. The multi-stage cluster sampling method was employed while selecting the study sample from the population. The scale used for the identification of students’ learning styles in this study was developed by Grasha-Riechmann. The data collected through learning style scale was analyzed by employing descriptive statistics technique. The results from data analysis depict that learning styles of the majority of students found to be Collaborative and Competitive. Overall, no considerable difference was surfaced between male-female, urban-rural, general-other categories of 10th grade English class students learning styles. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=learning%20style" title="learning style">learning style</a>, <a href="https://publications.waset.org/abstracts/search?q=learning%20style%20scale" title=" learning style scale"> learning style scale</a>, <a href="https://publications.waset.org/abstracts/search?q=grade" title=" grade"> grade</a>, <a href="https://publications.waset.org/abstracts/search?q=government%20sector" title=" government sector "> government sector </a> </p> <a href="https://publications.waset.org/abstracts/21672/revisiting-high-school-students-learning-styles-in-english-subject" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/21672.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">341</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">11391</span> Breast Cancer Diagnosing Based on Online Sequential Extreme Learning Machine Approach</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Musatafa%20Abbas%20Abbood%20Albadr">Musatafa Abbas Abbood Albadr</a>, <a href="https://publications.waset.org/abstracts/search?q=Masri%20Ayob"> Masri Ayob</a>, <a href="https://publications.waset.org/abstracts/search?q=Sabrina%20Tiun"> Sabrina Tiun</a>, <a href="https://publications.waset.org/abstracts/search?q=Fahad%20Taha%20Al-Dhief"> Fahad Taha Al-Dhief</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohammad%20Kamrul%20Hasan"> Mohammad Kamrul Hasan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Breast Cancer (BC) is considered one of the most frequent reasons of cancer death in women between 40 to 55 ages. The BC is diagnosed by using digital images of the FNA (Fine Needle Aspirate) for both benign and malignant tumors of the breast mass. Therefore, this work proposes the Online Sequential Extreme Learning Machine (OSELM) algorithm for diagnosing BC by using the tumor features of the breast mass. The current work has used the Wisconsin Diagnosis Breast Cancer (WDBC) dataset, which contains 569 samples (i.e., 357 samples for benign class and 212 samples for malignant class). Further, numerous measurements of assessment were used in order to evaluate the proposed OSELM algorithm, such as specificity, precision, F-measure, accuracy, G-mean, MCC, and recall. According to the outcomes of the experiment, the highest performance of the proposed OSELM was accomplished with 97.66% accuracy, 98.39% recall, 95.31% precision, 97.25% specificity, 96.83% F-measure, 95.00% MCC, and 96.84% G-Mean. The proposed OSELM algorithm demonstrates promising results in diagnosing BC. Besides, the performance of the proposed OSELM algorithm was superior to all its comparatives with respect to the rate of classification. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=breast%20cancer" title="breast cancer">breast cancer</a>, <a href="https://publications.waset.org/abstracts/search?q=machine%20learning" title=" machine learning"> machine learning</a>, <a href="https://publications.waset.org/abstracts/search?q=online%20sequential%20extreme%20learning%20machine" title=" online sequential extreme learning machine"> online sequential extreme learning machine</a>, <a href="https://publications.waset.org/abstracts/search?q=artificial%20intelligence" title=" artificial intelligence"> artificial intelligence</a> </p> <a href="https://publications.waset.org/abstracts/157482/breast-cancer-diagnosing-based-on-online-sequential-extreme-learning-machine-approach" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/157482.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">111</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">11390</span> An Extension of the Generalized Extreme Value Distribution</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Serge%20Provost">Serge Provost</a>, <a href="https://publications.waset.org/abstracts/search?q=Abdous%20Saboor"> Abdous Saboor</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A q-analogue of the generalized extreme value distribution which includes the Gumbel distribution is introduced. The additional parameter q allows for increased modeling flexibility. The resulting distribution can have a finite, semi-infinite or infinite support. It can also produce several types of hazard rate functions. The model parameters are determined by making use of the method of maximum likelihood. It will be shown that it compares favourably to three related distributions in connection with the modeling of a certain hydrological data set. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=extreme%20value%20theory" title="extreme value theory">extreme value theory</a>, <a href="https://publications.waset.org/abstracts/search?q=generalized%20extreme%20value%20distribution" title=" generalized extreme value distribution"> generalized extreme value distribution</a>, <a href="https://publications.waset.org/abstracts/search?q=goodness-of-fit%20statistics" title=" goodness-of-fit statistics"> goodness-of-fit statistics</a>, <a href="https://publications.waset.org/abstracts/search?q=Gumbel%20distribution" title=" Gumbel distribution"> Gumbel distribution</a> </p> <a href="https://publications.waset.org/abstracts/72656/an-extension-of-the-generalized-extreme-value-distribution" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/72656.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">11389</span> Sensitivity Based Robust Optimization Using 9 Level Orthogonal Array and Stepwise Regression</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=K.%20K.%20Lee">K. K. Lee</a>, <a href="https://publications.waset.org/abstracts/search?q=H.%20W.%20Han"> H. W. Han</a>, <a href="https://publications.waset.org/abstracts/search?q=H.%20L.%20Kang"> H. L. Kang</a>, <a href="https://publications.waset.org/abstracts/search?q=T.%20A.%20Kim"> T. A. Kim</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20H.%20Han"> S. H. Han</a> </p> <p class="card-text"><strong>Abstract:</strong></p> For the robust optimization of the manufacturing product design, there are design objectives that must be achieved, such as a minimization of the mean and standard deviation in objective functions within the required sensitivity constraints. The authors utilized the sensitivity of objective functions and constraints with respect to the effective design variables to reduce the computational burden associated with the evaluation of the probabilities. The individual mean and sensitivity values could be estimated easily by using the 9 level orthogonal array based response surface models optimized by the stepwise regression. The present study evaluates a proposed procedure from the robust optimization of rubber domes that are commonly used for keyboard switching, by using the 9 level orthogonal array and stepwise regression along with a desirability function. In addition, a new robust optimization process, i.e., the I2GEO (Identify, Integrate, Generate, Explore and Optimize), was proposed on the basis of the robust optimization in rubber domes. The optimized results from the response surface models and the estimated results by using the finite element analysis were consistent within a small margin of error. The standard deviation of objective function is decreasing 54.17% with suggested sensitivity based robust optimization. (Business for Cooperative R&D between Industry, Academy, and Research Institute funded Korea Small and Medium Business Administration in 2017, S2455569) <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=objective%20function" title="objective function">objective function</a>, <a href="https://publications.waset.org/abstracts/search?q=orthogonal%20array" title=" orthogonal array"> orthogonal array</a>, <a href="https://publications.waset.org/abstracts/search?q=response%20surface%20model" title=" response surface model"> response surface model</a>, <a href="https://publications.waset.org/abstracts/search?q=robust%20optimization" title=" robust optimization"> robust optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=stepwise%20regression" title=" stepwise regression"> stepwise regression</a> </p> <a href="https://publications.waset.org/abstracts/75399/sensitivity-based-robust-optimization-using-9-level-orthogonal-array-and-stepwise-regression" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/75399.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">288</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">11388</span> Influence of Precipitation and Land Use on Extreme Flow in Prek Thnot River Basin of Mekong River in Cambodia</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Chhordaneath%20Hen">Chhordaneath Hen</a>, <a href="https://publications.waset.org/abstracts/search?q=Ty%20Sok"> Ty Sok</a>, <a href="https://publications.waset.org/abstracts/search?q=Ilan%20Ich"> Ilan Ich</a>, <a href="https://publications.waset.org/abstracts/search?q=Ratboren%20Chan"> Ratboren Chan</a>, <a href="https://publications.waset.org/abstracts/search?q=Chantha%20Oeurng"> Chantha Oeurng</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The damages caused by hydrological extremes such as flooding have been severe globally, and several research studies indicated extreme precipitations play a crucial role. Cambodia is one of the most vulnerable countries exposed to floods and drought as consequences of climate impact. Prek Thnot River Basin in the southwest part of Cambodia, which is in the plate and plateau region and a part of the Mekong Delta, was selected to investigate the changes in extreme precipitation and hydrological extreme. Furthermore, to develop a statistical relationship between these phenomena in this basin from 1995 to 2020 using Multiple Linear Regression. The precipitation and hydrological extreme were assessed via the attributes and trends of rainfall patterns during the study periods. The extreme flow was defined as a dependent variable, while the independent variables are various extreme precipitation indices. The study showed that all extreme precipitations indices (R10, R20, R35, CWD, R95p, R99p, and PRCPTOT) had increasing decency. However, the number of rain days per year had a decreasing tendency, which can conclude that extreme rainfall was more intense in a shorter period of the year. The study showed a similar relationship between extreme precipitation and hydrological extreme and land use change association with hydrological extreme. The direct combination of land use and precipitation equals 37% of the flood causes in this river. This study provided information on these two causes of flood events and an understanding of expectations of climate change consequences for flood and water resources management. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=extreme%20precipitation" title="extreme precipitation">extreme precipitation</a>, <a href="https://publications.waset.org/abstracts/search?q=hydrological%20extreme" title=" hydrological extreme"> hydrological extreme</a>, <a href="https://publications.waset.org/abstracts/search?q=land%20use" title=" land use"> land use</a>, <a href="https://publications.waset.org/abstracts/search?q=land%20cover" title=" land cover"> land cover</a>, <a href="https://publications.waset.org/abstracts/search?q=Prek%20Thnot%20river%20basin" title=" Prek Thnot river basin"> Prek Thnot river basin</a> </p> <a href="https://publications.waset.org/abstracts/155816/influence-of-precipitation-and-land-use-on-extreme-flow-in-prek-thnot-river-basin-of-mekong-river-in-cambodia" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/155816.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">111</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">11387</span> Estimating The Population Mean by Using Stratified Double Extreme Ranked Set Sample</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mahmoud%20I.%20Syam">Mahmoud I. Syam</a>, <a href="https://publications.waset.org/abstracts/search?q=Kamarulzaman%20Ibrahim"> Kamarulzaman Ibrahim</a>, <a href="https://publications.waset.org/abstracts/search?q=Amer%20I.%20Al-Omari"> Amer I. Al-Omari </a> </p> <p class="card-text"><strong>Abstract:</strong></p> Stratified double extreme ranked set sampling (SDERSS) method is introduced and considered for estimating the population mean. The SDERSS is compared with the simple random sampling (SRS), stratified ranked set sampling (SRSS) and stratified simple set sampling (SSRS). It is shown that the SDERSS estimator is an unbiased of the population mean and more efficient than the estimators using SRS, SRSS and SSRS when the underlying distribution of the variable of interest is symmetric or asymmetric. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=double%20extreme%20ranked%20set%20sampling" title="double extreme ranked set sampling">double extreme ranked set sampling</a>, <a href="https://publications.waset.org/abstracts/search?q=extreme%20ranked%20set%20sampling" title=" extreme ranked set sampling"> extreme ranked set sampling</a>, <a href="https://publications.waset.org/abstracts/search?q=ranked%20set%20sampling" title=" ranked set sampling"> ranked set sampling</a>, <a href="https://publications.waset.org/abstracts/search?q=stratified%20double%20extreme%20ranked%20set%20sampling" title=" stratified double extreme ranked set sampling"> stratified double extreme ranked set sampling</a> </p> <a href="https://publications.waset.org/abstracts/25207/estimating-the-population-mean-by-using-stratified-double-extreme-ranked-set-sample" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/25207.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">456</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">11386</span> Constructing Orthogonal De Bruijn and Kautz Sequences and Applications</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yaw-Ling%20Lin">Yaw-Ling Lin</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A de Bruijn graph of order k is a graph whose vertices representing all length-k sequences with edges joining pairs of vertices whose sequences have maximum possible overlap (length k−1). Every Hamiltonian cycle of this graph defines a distinct, minimum length de Bruijn sequence containing all k-mers exactly once. A Kautz sequence is the minimal generating sequence so as the sequence of minimal length that produces all possible length-k sequences with the restriction that every two consecutive alphabets in the sequences must be different. A collection of de Bruijn/Kautz sequences are orthogonal if any two sequences are of maximally differ in sequence composition; that is, the maximum length of their common substring is k. In this paper, we discuss how such a collection of (maximal) orthogonal de Bruijn/Kautz sequences can be made and use the algorithm to build up a web application service for the synthesized DNA and other related biomolecular sequences. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=biomolecular%20sequence%20synthesis" title="biomolecular sequence synthesis">biomolecular sequence synthesis</a>, <a href="https://publications.waset.org/abstracts/search?q=de%20Bruijn%20sequences" title=" de Bruijn sequences"> de Bruijn sequences</a>, <a href="https://publications.waset.org/abstracts/search?q=Eulerian%20cycle" title=" Eulerian cycle"> Eulerian cycle</a>, <a href="https://publications.waset.org/abstracts/search?q=Hamiltonian%20cycle" title=" Hamiltonian cycle"> Hamiltonian cycle</a>, <a href="https://publications.waset.org/abstracts/search?q=Kautz%20sequences" title=" Kautz sequences"> Kautz sequences</a>, <a href="https://publications.waset.org/abstracts/search?q=orthogonal%20sequences" title=" orthogonal sequences"> orthogonal sequences</a> </p> <a href="https://publications.waset.org/abstracts/121912/constructing-orthogonal-de-bruijn-and-kautz-sequences-and-applications" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/121912.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">166</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">11385</span> Channel Estimation for Orthogonal Frequency Division Multiplexing Systems over Doubly Selective Channels Base on DCS-DCSOMP Algorithm</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Linyu%20Wang">Linyu Wang</a>, <a href="https://publications.waset.org/abstracts/search?q=Furui%20Huo"> Furui Huo</a>, <a href="https://publications.waset.org/abstracts/search?q=Jianhong%20Xiang"> Jianhong Xiang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The Doppler shift generated by high-speed movement and multipath effects in the channel are the main reasons for the generation of a time-frequency doubly-selective (DS) channel. There is severe inter-carrier interference (ICI) in the DS channel. Channel estimation for an orthogonal frequency division multiplexing (OFDM) system over a DS channel is very difficult. The simultaneous orthogonal matching pursuit algorithm under distributed compressive sensing theory (DCS-SOMP) has been used in channel estimation for OFDM systems over DS channels. However, the reconstruction accuracy of the DCS-SOMP algorithm is not high enough in the low SNR stage. To solve this problem, in this paper, we propose an improved DCS-SOMP algorithm based on the inner product difference comparison operation (DCS-DCSOMP). The reconstruction accuracy is improved by increasing the number of candidate indexes and designing the comparison conditions of inner product difference. We combine the DCS-DCSOMP algorithm with the basis expansion model (BEM) to reduce the complexity of channel estimation. Simulation results show the effectiveness of the proposed algorithm and its advantages over other algorithms. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=OFDM" title="OFDM">OFDM</a>, <a href="https://publications.waset.org/abstracts/search?q=doubly%20selective" title=" doubly selective"> doubly selective</a>, <a href="https://publications.waset.org/abstracts/search?q=channel%20estimation" title=" channel estimation"> channel estimation</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/162873/channel-estimation-for-orthogonal-frequency-division-multiplexing-systems-over-doubly-selective-channels-base-on-dcs-dcsomp-algorithm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/162873.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">95</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">11384</span> Video Text Information Detection and Localization in Lecture Videos Using Moments </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Belkacem%20Soundes">Belkacem Soundes</a>, <a href="https://publications.waset.org/abstracts/search?q=Guezouli%20Larbi"> Guezouli Larbi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents a robust and accurate method for text detection and localization over lecture videos. Frame regions are classified into text or background based on visual feature analysis. However, lecture video shows significant degradation mainly related to acquisition conditions, camera motion and environmental changes resulting in low quality videos. Hence, affecting feature extraction and description efficiency. Moreover, traditional text detection methods cannot be directly applied to lecture videos. Therefore, robust feature extraction methods dedicated to this specific video genre are required for robust and accurate text detection and extraction. Method consists of a three-step process: Slide region detection and segmentation; Feature extraction and non-text filtering. For robust and effective features extraction moment functions are used. Two distinct types of moments are used: orthogonal and non-orthogonal. For orthogonal Zernike Moments, both Pseudo Zernike moments are used, whereas for non-orthogonal ones Hu moments are used. Expressivity and description efficiency are given and discussed. Proposed approach shows that in general, orthogonal moments show high accuracy in comparison to the non-orthogonal one. Pseudo Zernike moments are more effective than Zernike with better computation time. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=text%20detection" title="text detection">text detection</a>, <a href="https://publications.waset.org/abstracts/search?q=text%20localization" title=" text localization"> text localization</a>, <a href="https://publications.waset.org/abstracts/search?q=lecture%20videos" title=" lecture videos"> lecture videos</a>, <a href="https://publications.waset.org/abstracts/search?q=pseudo%20zernike%20moments" title=" pseudo zernike moments"> pseudo zernike moments</a> </p> <a href="https://publications.waset.org/abstracts/109549/video-text-information-detection-and-localization-in-lecture-videos-using-moments" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/109549.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">151</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">11383</span> An Ontology for Smart Learning Environments in Music Education</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Konstantinos%20Sofianos">Konstantinos Sofianos</a>, <a href="https://publications.waset.org/abstracts/search?q=Michail%20Stefanidakis"> Michail Stefanidakis</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Nowadays, despite the great advances in technology, most educational frameworks lack a strong educational design basis. E-learning has become prevalent, but it faces various challenges such as student isolation and lack of quality in the learning process. An intelligent learning system provides a student with educational material according to their learning background and learning preferences. It records full information about the student, such as demographic information, learning styles, and academic performance. This information allows the system to be fully adapted to the student’s needs. In this paper, we propose a framework and an ontology for music education, consisting of the learner model and all elements of the learning process (learning objects, teaching methods, learning activities, assessment). This framework can be integrated into an intelligent learning system and used for music education in schools for the development of professional skills and beyond. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=intelligent%20learning%20systems" title="intelligent learning systems">intelligent learning systems</a>, <a href="https://publications.waset.org/abstracts/search?q=e-learning" title=" e-learning"> e-learning</a>, <a href="https://publications.waset.org/abstracts/search?q=music%20education" title=" music education"> music education</a>, <a href="https://publications.waset.org/abstracts/search?q=ontology" title=" ontology"> ontology</a>, <a href="https://publications.waset.org/abstracts/search?q=semantic%20web" title=" semantic web"> semantic web</a> </p> <a href="https://publications.waset.org/abstracts/153256/an-ontology-for-smart-learning-environments-in-music-education" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/153256.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">139</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">11382</span> Poor Cognitive Flexibility as Suggested Basis for Learning Difficulties among Children with Moderate-INTO-Severe Asthma: Evidence from WCSTPerformance</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Haitham%20Taha">Haitham Taha </a> </p> <p class="card-text"><strong>Abstract:</strong></p> The cognitive flexibility of 27 asthmatic children with learning difficulties was tested by using the Wisconsin card sorting test (WCST) and compared to the performances of 30 non-asthmatic children who have persistence learning difficulties also. The results revealed that the asthmatic group had poor performance through all the WCST psychometric parameters and especially the preservative errors one. The results were discussed in light of the postulation that poor executive functions and specifically poor cognitive flexibility are in the basis of the learning difficulties of asthmatic children with learning difficulties. Neurophysiologic framework was suggested for explaining the etiology of poor executive functions and cognitive flexibility among children with moderate into severe asthma. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=asthma" title="asthma">asthma</a>, <a href="https://publications.waset.org/abstracts/search?q=learning%20disabilities" title=" learning disabilities"> learning disabilities</a>, <a href="https://publications.waset.org/abstracts/search?q=executive%20functions" title=" executive functions"> executive functions</a>, <a href="https://publications.waset.org/abstracts/search?q=cognitive%20flexibility" title=" cognitive flexibility"> cognitive flexibility</a>, <a href="https://publications.waset.org/abstracts/search?q=WCST" title=" WCST "> WCST </a> </p> <a href="https://publications.waset.org/abstracts/13405/poor-cognitive-flexibility-as-suggested-basis-for-learning-difficulties-among-children-with-moderate-into-severe-asthma-evidence-from-wcstperformance" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/13405.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">502</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">11381</span> A Design of Active Elastic Metamaterial with Extreme Anisotropic Stiffness</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Conner%20Side">Conner Side</a>, <a href="https://publications.waset.org/abstracts/search?q=Hunter%20Pearce"> Hunter Pearce</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Traditional elastic metamaterials have difficulties in achieving independent tunable working frequency in two orthogonal directions. In this work, we proposed a pragmatic active elastic metamaterial to obtain extreme anisotropic stiffness with a tunable working frequency range. Piezoelectric patches shunted with variable conductance are properly proposed in the microstructure unit cell to manipulate the effective elastic stiffness along two principal directions at the subwavelength scale. Simulation of manipulation of wave propagation in such metamaterials is performed. An experimental study is also conducted to validate the design, and the results are in good agreement with mathematic analysis and numerical predictions. The proposed active elastic metamaterial will bring forth significant guidelines for ultrasonic imaging technique, and the results are expected to oﬀer novel and general design methodology for elastic metamaterials. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=microstructure" title="microstructure">microstructure</a>, <a href="https://publications.waset.org/abstracts/search?q=active%20elastic%20metamaterials" title=" active elastic metamaterials"> active elastic metamaterials</a>, <a href="https://publications.waset.org/abstracts/search?q=piezoelectric%20patches" title=" piezoelectric patches"> piezoelectric patches</a>, <a href="https://publications.waset.org/abstracts/search?q=experimental%20study" title=" experimental study"> experimental study</a> </p> <a href="https://publications.waset.org/abstracts/163676/a-design-of-active-elastic-metamaterial-with-extreme-anisotropic-stiffness" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/163676.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">94</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">11380</span> Artificial Intelligence-Based Detection of Individuals Suffering from Vestibular Disorder</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Dua%20Hi%C5%9Fam">Dua Hişam</a>, <a href="https://publications.waset.org/abstracts/search?q=Serhat%20%C4%B0kizo%C4%9Flu"> Serhat İkizoğlu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Identifying the problem behind balance disorder is one of the most interesting topics in the medical literature. This study has considerably enhanced the development of artificial intelligence (AI) algorithms applying multiple machine learning (ML) models to sensory data on gait collected from humans to classify between normal people and those suffering from Vestibular System (VS) problems. Although AI is widely utilized as a diagnostic tool in medicine, AI models have not been used to perform feature extraction and identify VS disorders through training on raw data. In this study, three machine learning (ML) models, the Random Forest Classifier (RF), Extreme Gradient Boosting (XGB), and K-Nearest Neighbor (KNN), have been trained to detect VS disorder, and the performance comparison of the algorithms has been made using accuracy, recall, precision, and f1-score. With an accuracy of 95.28 %, Random Forest Classifier (RF) was the most accurate model. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=vestibular%20disorder" title="vestibular disorder">vestibular disorder</a>, <a href="https://publications.waset.org/abstracts/search?q=machine%20learning" title=" machine learning"> machine learning</a>, <a href="https://publications.waset.org/abstracts/search?q=random%20forest%20classifier" title=" random forest classifier"> random forest classifier</a>, <a href="https://publications.waset.org/abstracts/search?q=k-nearest%20neighbor" title=" k-nearest neighbor"> k-nearest neighbor</a>, <a href="https://publications.waset.org/abstracts/search?q=extreme%20gradient%20boosting" title=" extreme gradient boosting"> extreme gradient boosting</a> </p> <a href="https://publications.waset.org/abstracts/162312/artificial-intelligence-based-detection-of-individuals-suffering-from-vestibular-disorder" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/162312.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">69</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">11379</span> Climate Change and Extreme Weather: Understanding Interconnections and Implications</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Johnstone%20Walubengo%20Wangusi">Johnstone Walubengo Wangusi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Climate change is undeniably altering the frequency, intensity, and geographic distribution of extreme weather events worldwide. In this paper, we explore the complex interconnections between climate change and extreme weather phenomena, drawing upon research from atmospheric science, geology, and climatology. We examine the underlying mechanisms driving these changes, the impacts on natural ecosystems and human societies, and strategies for adaptation and mitigation. By synthesizing insights from interdisciplinary research, this paper aims to provide a comprehensive understanding of the multifaceted relationship between climate change and extreme weather, informing efforts to address the challenges posed by a changing climate. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=climate%20change" title="climate change">climate change</a>, <a href="https://publications.waset.org/abstracts/search?q=extreme%20weather" title=" extreme weather"> extreme weather</a>, <a href="https://publications.waset.org/abstracts/search?q=atmospheric%20science" title=" atmospheric science"> atmospheric science</a>, <a href="https://publications.waset.org/abstracts/search?q=geology" title=" geology"> geology</a>, <a href="https://publications.waset.org/abstracts/search?q=climatology" title=" climatology"> climatology</a>, <a href="https://publications.waset.org/abstracts/search?q=impacts" title=" impacts"> impacts</a>, <a href="https://publications.waset.org/abstracts/search?q=adaptation" title=" adaptation"> adaptation</a>, <a href="https://publications.waset.org/abstracts/search?q=mitigation" title=" mitigation"> mitigation</a> </p> <a href="https://publications.waset.org/abstracts/184530/climate-change-and-extreme-weather-understanding-interconnections-and-implications" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/184530.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">64</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">11378</span> Applications of Probabilistic Interpolation via Orthogonal Matrices</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Dariusz%20Jacek%20Jak%C3%B3bczak">Dariusz Jacek Jakóbczak</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Mathematics and computer science are interested in methods of 2D curve interpolation and extrapolation using the set of key points (knots). A proposed method of Hurwitz- Radon Matrices (MHR) is such a method. This novel method is based on the family of Hurwitz-Radon (HR) matrices which possess columns composed of orthogonal vectors. Two-dimensional curve is interpolated via different functions as probability distribution functions: polynomial, sinus, cosine, tangent, cotangent, logarithm, exponent, arcsin, arccos, arctan, arcctg or power function, also inverse functions. It is shown how to build the orthogonal matrix operator and how to use it in a process of curve reconstruction. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=2D%20data%20interpolation" title="2D data interpolation">2D data interpolation</a>, <a href="https://publications.waset.org/abstracts/search?q=hurwitz-radon%20matrices" title=" hurwitz-radon matrices"> hurwitz-radon matrices</a>, <a href="https://publications.waset.org/abstracts/search?q=MHR%20method" title=" MHR method"> MHR method</a>, <a href="https://publications.waset.org/abstracts/search?q=probabilistic%20modeling" title=" probabilistic modeling"> probabilistic modeling</a>, <a href="https://publications.waset.org/abstracts/search?q=curve%20extrapolation" title=" curve extrapolation"> curve extrapolation</a> </p> <a href="https://publications.waset.org/abstracts/32599/applications-of-probabilistic-interpolation-via-orthogonal-matrices" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/32599.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">525</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">11377</span> Seismic Behaviour of Bi-Symmetric Buildings </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yogendra%20Singh">Yogendra Singh</a>, <a href="https://publications.waset.org/abstracts/search?q=Mayur%20Pisode"> Mayur Pisode</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Many times it is observed that in multi-storeyed buildings the dynamic properties in the two directions are similar due to which there may be a coupling between the two orthogonal modes of the building. This is particularly observed in bi-symmetric buildings (buildings with structural properties and periods approximately equal in the two directions). There is a swapping of vibrational energy between the modes in the two orthogonal directions. To avoid this coupling the draft revision of IS:1893 proposes a minimum separation of more than 15% between the frequencies of the fundamental modes in the two directions. This study explores the seismic behaviour of bi-symmetrical buildings under uniaxial and bi-axial ground motions. For this purpose, three different types of 8 storey buildings symmetric in plan are modelled. The first building has square columns, resulting in identical periods in the two directions. The second building, with rectangular columns, has a difference of 20% in periods in orthogonal directions, and the third building has half of the rectangular columns aligned in one direction and other half aligned in the other direction. The numerical analysis of the seismic response of these three buildings is performed by using a set of 22 ground motions from PEER NGA database and scaled as per FEMA P695 guidelines to represent the same level of intensity corresponding to the Design Basis Earthquake. The results are analyzed in terms of the displacement-time response of the buildings at roof level and corresponding maximum inter-storey drift ratios. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=bi-symmetric%20buildings" title="bi-symmetric buildings">bi-symmetric buildings</a>, <a href="https://publications.waset.org/abstracts/search?q=design%20code" title=" design code"> design code</a>, <a href="https://publications.waset.org/abstracts/search?q=dynamic%20coupling" title=" dynamic coupling"> dynamic coupling</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-storey%20buildings" title=" multi-storey buildings"> multi-storey buildings</a>, <a href="https://publications.waset.org/abstracts/search?q=seismic%20response" title=" seismic response"> seismic response</a> </p> <a href="https://publications.waset.org/abstracts/57611/seismic-behaviour-of-bi-symmetric-buildings" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/57611.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">241</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">11376</span> Study of Tribological Behaviour of Al6061/Silicon Carbide/Graphite Hybrid Metal Matrix Composite Using Taguchi's Techniques </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mohamed%20Zakaulla">Mohamed Zakaulla</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20R.%20Anwar%20Khan"> A. R. Anwar Khan </a> </p> <p class="card-text"><strong>Abstract:</strong></p> Al6061 alloy base matrix, reinforced with particles of silicon carbide (10 wt %) and Graphite powder (1wt%), known as hybrid composites have been fabricated by liquid metallurgy route (stir casting technique) and optimized at different parameters like applied load, sliding speed and sliding distance by taguchi method. A plan of experiment generated through taguchi technique was used to perform experiments based on L27 orthogonal array. The developed ANOVA and regression equations are used to find the optimum coefficient of friction and wear under the influence of applied load, sliding speed and sliding distance. On the basis of “smaller the best” the dry sliding wear resistance was analysed and finally confirmation tests were carried out to verify the experimental results. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=analysis%20of%20variance" title="analysis of variance">analysis of variance</a>, <a href="https://publications.waset.org/abstracts/search?q=dry%20sliding%20wear" title=" dry sliding wear"> dry sliding wear</a>, <a href="https://publications.waset.org/abstracts/search?q=hybrid%20composite" title=" hybrid composite"> hybrid composite</a>, <a href="https://publications.waset.org/abstracts/search?q=orthogonal%20array" title=" orthogonal array"> orthogonal array</a>, <a href="https://publications.waset.org/abstracts/search?q=Taguchi%20technique" title=" Taguchi technique "> Taguchi technique </a> </p> <a href="https://publications.waset.org/abstracts/20916/study-of-tribological-behaviour-of-al6061silicon-carbidegraphite-hybrid-metal-matrix-composite-using-taguchis-techniques" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/20916.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">11375</span> Performance Comparison of Resource Allocation without Feedback in Wireless Body Area Networks by Various Pseudo Orthogonal Sequences</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ojin%20Kwon">Ojin Kwon</a>, <a href="https://publications.waset.org/abstracts/search?q=Yong-Jin%20Yoon"> Yong-Jin Yoon</a>, <a href="https://publications.waset.org/abstracts/search?q=Liu%20Xin"> Liu Xin</a>, <a href="https://publications.waset.org/abstracts/search?q=Zhang%20Hongbao"> Zhang Hongbao</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Wireless Body Area Network (WBAN) is a short-range wireless communication around human body for various applications such as wearable devices, entertainment, military, and especially medical devices. WBAN attracts the attention of continuous health monitoring system including diagnostic procedure, early detection of abnormal conditions, and prevention of emergency situations. Compared to cellular network, WBAN system is more difficult to control inter- and inner-cell interference due to the limited power, limited calculation capability, mobility of patient, and non-cooperation among WBANs. In this paper, we compare the performance of resource allocation scheme based on several Pseudo Orthogonal Codewords (POCs) to mitigate inter-WBAN interference. Previously, the POCs are widely exploited for a protocol sequence and optical orthogonal code. Each POCs have different properties of auto- and cross-correlation and spectral efficiency according to its construction of POCs. To identify different WBANs, several different pseudo orthogonal patterns based on POCs exploits for resource allocation of WBANs. By simulating these pseudo orthogonal resource allocations of WBANs on MATLAB, we obtain the performance of WBANs according to different POCs and can analyze and evaluate the suitability of POCs for the resource allocation in the WBANs system. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=wireless%20body%20area%20network" title="wireless body area network">wireless body area network</a>, <a href="https://publications.waset.org/abstracts/search?q=body%20sensor%20network" title=" body sensor network"> body sensor network</a>, <a href="https://publications.waset.org/abstracts/search?q=resource%20allocation%20without%20feedback" title=" resource allocation without feedback"> resource allocation without feedback</a>, <a href="https://publications.waset.org/abstracts/search?q=interference%20mitigation" title=" interference mitigation"> interference mitigation</a>, <a href="https://publications.waset.org/abstracts/search?q=pseudo%20orthogonal%20pattern" title=" pseudo orthogonal pattern"> pseudo orthogonal pattern</a> </p> <a href="https://publications.waset.org/abstracts/9490/performance-comparison-of-resource-allocation-without-feedback-in-wireless-body-area-networks-by-various-pseudo-orthogonal-sequences" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/9490.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">353</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">11374</span> Optimization Based Extreme Learning Machine for Watermarking of an Image in DWT Domain</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=RAM%20PAL%20SINGH">RAM PAL SINGH</a>, <a href="https://publications.waset.org/abstracts/search?q=VIKASH%20CHAUDHARY"> VIKASH CHAUDHARY</a>, <a href="https://publications.waset.org/abstracts/search?q=MONIKA%20VERMA"> MONIKA VERMA</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we proposed the implementation of optimization based Extreme Learning Machine (ELM) for watermarking of B-channel of color image in discrete wavelet transform (DWT) domain. ELM, a regularization algorithm, works based on generalized single-hidden-layer feed-forward neural networks (SLFNs). However, hidden layer parameters, generally called feature mapping in context of ELM need not to be tuned every time. This paper shows the embedding and extraction processes of watermark with the help of ELM and results are compared with already used machine learning models for watermarking.Here, a cover image is divide into suitable numbers of non-overlapping blocks of required size and DWT is applied to each block to be transformed in low frequency sub-band domain. Basically, ELM gives a unified leaning platform with a feature mapping, that is, mapping between hidden layer and output layer of SLFNs, is tried for watermark embedding and extraction purpose in a cover image. Although ELM has widespread application right from binary classification, multiclass classification to regression and function estimation etc. Unlike SVM based algorithm which achieve suboptimal solution with high computational complexity, ELM can provide better generalization performance results with very small complexity. Efficacy of optimization method based ELM algorithm is measured by using quantitative and qualitative parameters on a watermarked image even though image is subjected to different types of geometrical and conventional attacks. <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=DWT" title=" DWT"> DWT</a>, <a href="https://publications.waset.org/abstracts/search?q=extreme%20leaning%20machine%20%28ELM%29" title=" extreme leaning machine (ELM)"> extreme leaning machine (ELM)</a>, <a href="https://publications.waset.org/abstracts/search?q=PSNR" title=" PSNR "> PSNR </a> </p> <a href="https://publications.waset.org/abstracts/4331/optimization-based-extreme-learning-machine-for-watermarking-of-an-image-in-dwt-domain" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/4331.pdf" target="_blank" class="btn 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