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algorithms</title> <meta name="description" content="Search results for: genetic algorithms"> <meta name="keywords" content="genetic algorithms"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div class="container"> <nav class="navbar navbar-expand-lg navbar-light"> <a class="navbar-brand" href="https://waset.org"> <img src="https://cdn.waset.org/static/images/wasetc.png" alt="Open Science Research Excellence" title="Open Science Research Excellence" /> </a> <button class="d-block d-lg-none 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action="https://publications.waset.org/abstracts/search"> <div id="custom-search-input"> <div class="input-group"> <i class="fas fa-search"></i> <input type="text" class="search-query" name="q" placeholder="Author, Title, Abstract, Keywords" value="genetic algorithms"> <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> 3424</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: genetic algorithms</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3274</span> Estimating Estimators: An Empirical Comparison of Non-Invasive Analysis Methods</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yan%20Torres">Yan Torres</a>, <a href="https://publications.waset.org/abstracts/search?q=Fernanda%20Simoes"> Fernanda Simoes</a>, <a href="https://publications.waset.org/abstracts/search?q=Francisco%20Petrucci-Fonseca"> Francisco Petrucci-Fonseca</a>, <a href="https://publications.waset.org/abstracts/search?q=Freddie-Jeanne%20Richard"> Freddie-Jeanne Richard</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The non-invasive samples are an alternative of collecting genetic samples directly. Non-invasive samples are collected without the manipulation of the animal (e.g., scats, feathers and hairs). Nevertheless, the use of non-invasive samples has some limitations. The main issue is degraded DNA, leading to poorer extraction efficiency and genotyping. Those errors delayed for some years a widespread use of non-invasive genetic information. Possibilities to limit genotyping errors can be done using analysis methods that can assimilate the errors and singularities of non-invasive samples. Genotype matching and population estimation algorithms can be highlighted as important analysis tools that have been adapted to deal with those errors. Although, this recent development of analysis methods there is still a lack of empirical performance comparison of them. A comparison of methods with dataset different in size and structure can be useful for future studies since non-invasive samples are a powerful tool for getting information specially for endangered and rare populations. To compare the analysis methods, four different datasets used were obtained from the Dryad digital repository were used. Three different matching algorithms (Cervus, Colony and Error Tolerant Likelihood Matching - ETLM) are used for matching genotypes and two different ones for population estimation (Capwire and BayesN). The three matching algorithms showed different patterns of results. The ETLM produced less number of unique individuals and recaptures. A similarity in the matched genotypes between Colony and Cervus was observed. That is not a surprise since the similarity between those methods on the likelihood pairwise and clustering algorithms. The matching of ETLM showed almost no similarity with the genotypes that were matched with the other methods. The different cluster algorithm system and error model of ETLM seems to lead to a more criterious selection, although the processing time and interface friendly of ETLM were the worst between the compared methods. The population estimators performed differently regarding the datasets. There was a consensus between the different estimators only for the one dataset. The BayesN showed higher and lower estimations when compared with Capwire. The BayesN does not consider the total number of recaptures like Capwire only the recapture events. So, this makes the estimator sensitive to data heterogeneity. Heterogeneity in the sense means different capture rates between individuals. In those examples, the tolerance for homogeneity seems to be crucial for BayesN work properly. Both methods are user-friendly and have reasonable processing time. An amplified analysis with simulated genotype data can clarify the sensibility of the algorithms. The present comparison of the matching methods indicates that Colony seems to be more appropriated for general use considering a time/interface/robustness balance. The heterogeneity of the recaptures affected strongly the BayesN estimations, leading to over and underestimations population numbers. Capwire is then advisable to general use since it performs better in a wide range of situations. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=algorithms" title="algorithms">algorithms</a>, <a href="https://publications.waset.org/abstracts/search?q=genetics" title=" genetics"> genetics</a>, <a href="https://publications.waset.org/abstracts/search?q=matching" title=" matching"> matching</a>, <a href="https://publications.waset.org/abstracts/search?q=population" title=" population"> population</a> </p> <a href="https://publications.waset.org/abstracts/99825/estimating-estimators-an-empirical-comparison-of-non-invasive-analysis-methods" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/99825.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">143</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3273</span> Genomic Diversity of Clostridium perfringens Strains in Food and Human Sources</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Asma%20Afshari">Asma Afshari</a>, <a href="https://publications.waset.org/abstracts/search?q=Abdollah%20Jamshidi"> Abdollah Jamshidi</a>, <a href="https://publications.waset.org/abstracts/search?q=Jamshid%20Razmyar"> Jamshid Razmyar</a>, <a href="https://publications.waset.org/abstracts/search?q=Mehrnaz%20Rad"> Mehrnaz Rad</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Clostridium perfringens is a serious pathogen which causes enteric diseases in domestic animals and food poisoning in humans. Spores can survive cooking processes and play an important role in the possible onset of disease. In this study RAPD-PCR and REP-PCR were used to examine the genetic diversity of 49isolates ofC. Perfringens type A from 3 different sources. The results of RAPD-PCR revealed the most genetic diversity among poultry isolates, while human isolates showed the least genetic diversity. Cluster analysis obtained from RAPD_PCR and based on the genetic distances split the 49 strains into five distinct major clusters (A, B, C, D, and E). Cluster A and C were composed of isolates from poultry meat, cluster B was composed of isolates from human feces, cluster D was composed of isolates from minced meat, poultry meat and human feces and cluster E was composed of isolates from minced meat. Further characterization of these strains by using (GTG) 5 fingerprint repetitive sequence-based PCR analysis did not show further differentiation between various types of strains. To our knowledge, this is the first study in which the genetic diversity of C. perfringens isolates from different types of meats and human feces has been investigated. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=C.%20perfringens" title="C. perfringens">C. perfringens</a>, <a href="https://publications.waset.org/abstracts/search?q=genetic%20diversity" title=" genetic diversity"> genetic diversity</a>, <a href="https://publications.waset.org/abstracts/search?q=RAPD-PCR" title=" RAPD-PCR"> RAPD-PCR</a>, <a href="https://publications.waset.org/abstracts/search?q=REP-PCR" title=" REP-PCR"> REP-PCR</a> </p> <a href="https://publications.waset.org/abstracts/35846/genomic-diversity-of-clostridium-perfringens-strains-in-food-and-human-sources" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/35846.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">492</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">3272</span> Performance of Non-Deterministic Structural Optimization Algorithms Applied to a Steel Truss Structure</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ersilio%20Tushaj">Ersilio Tushaj</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The efficient solution that satisfies the optimal condition is an important issue in the structural engineering design problem. The new codes of structural design consist in design methodology that looks after the exploitation of the total resources of the construction material. In recent years some non-deterministic or meta-heuristic structural optimization algorithms have been developed widely in the research community. These methods search the optimum condition starting from the simulation of a natural phenomenon, such as survival of the fittest, the immune system, swarm intelligence or the cooling process of molten metal through annealing. Among these techniques the most known are: the genetic algorithms, simulated annealing, evolution strategies, particle swarm optimization, tabu search, ant colony optimization, harmony search and big bang crunch optimization. In this study, five of these algorithms are applied for the optimum weight design of a steel truss structure with variable geometry but fixed topology. The design process selects optimum distances and size sections from a set of commercial steel profiles. In the formulation of the design problem are considered deflection limitations, buckling and allowable stress constraints. The approach is repeated starting from different initial populations. The design problem topology is taken from an existing steel structure. The optimization process helps the engineer to achieve good final solutions, avoiding the repetitive evaluation of alternative designs in a time consuming process. The algorithms used for the application, the results of the optimal solutions, the number of iterations and the minimal weight designs, will be reported in the paper. Based on these results, it would be estimated, the amount of the steel that could be saved by applying structural analysis combined with non-deterministic optimization methods. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=structural%20optimization" title="structural optimization">structural optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=non-deterministic%20methods" title=" non-deterministic methods"> non-deterministic methods</a>, <a href="https://publications.waset.org/abstracts/search?q=truss%20structures" title=" truss structures"> truss structures</a>, <a href="https://publications.waset.org/abstracts/search?q=steel%20truss" title=" steel truss"> steel truss</a> </p> <a href="https://publications.waset.org/abstracts/74250/performance-of-non-deterministic-structural-optimization-algorithms-applied-to-a-steel-truss-structure" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/74250.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">230</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">3271</span> BeamGA Median: A Hybrid Heuristic Search Approach</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ghada%20Badr">Ghada Badr</a>, <a href="https://publications.waset.org/abstracts/search?q=Manar%20Hosny"> Manar Hosny</a>, <a href="https://publications.waset.org/abstracts/search?q=Nuha%20Bintayyash"> Nuha Bintayyash</a>, <a href="https://publications.waset.org/abstracts/search?q=Eman%20Albilali"> Eman Albilali</a>, <a href="https://publications.waset.org/abstracts/search?q=Souad%20Larabi%20Marie-Sainte"> Souad Larabi Marie-Sainte</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The median problem is significantly applied to derive the most reasonable rearrangement phylogenetic tree for many species. More specifically, the problem is concerned with finding a permutation that minimizes the sum of distances between itself and a set of three signed permutations. Genomes with equal number of genes but different order can be represented as permutations. In this paper, an algorithm, namely BeamGA median, is proposed that combines a heuristic search approach (local beam) as an initialization step to generate a number of solutions, and then a Genetic Algorithm (GA) is applied in order to refine the solutions, aiming to achieve a better median with the smallest possible reversal distance from the three original permutations. In this approach, any genome rearrangement distance can be applied. In this paper, we use the reversal distance. To the best of our knowledge, the proposed approach was not applied before for solving the median problem. Our approach considers true biological evolution scenario by applying the concept of common intervals during the GA optimization process. This allows us to imitate a true biological behavior and enhance genetic approach time convergence. We were able to handle permutations with a large number of genes, within an acceptable time performance and with same or better accuracy as compared to existing algorithms. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=median%20problem" title="median problem">median problem</a>, <a href="https://publications.waset.org/abstracts/search?q=phylogenetic%20tree" title=" phylogenetic tree"> phylogenetic tree</a>, <a href="https://publications.waset.org/abstracts/search?q=permutation" title=" permutation"> permutation</a>, <a href="https://publications.waset.org/abstracts/search?q=genetic%20algorithm" title=" genetic algorithm"> genetic algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=beam%20search" title=" beam search"> beam search</a>, <a href="https://publications.waset.org/abstracts/search?q=genome%20rearrangement%20distance" title=" genome rearrangement distance"> genome rearrangement distance</a> </p> <a href="https://publications.waset.org/abstracts/73026/beamga-median-a-hybrid-heuristic-search-approach" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/73026.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">265</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">3270</span> Etude 3D Quantum Numerical Simulation of Performance in the HEMT</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=A.%20Boursali">A. Boursali</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20Guen-Bouazza"> A. Guen-Bouazza</a> </p> <p class="card-text"><strong>Abstract:</strong></p> We present a simulation of a HEMT (high electron mobility transistor) structure with and without a field plate. We extract the device characteristics through the analysis of DC, AC and high frequency regimes, as shown in this paper. This work demonstrates the optimal device with a gate length of 15 nm, InAlN/GaN heterostructure and field plate structure, making it superior to modern HEMTs when compared with otherwise equivalent devices. This improves the ability to bear the burden of the current density passes in the channel. We have demonstrated an excellent current density, as high as 2.05 A/m, a peak extrinsic transconductance of 0.59S/m at VDS=2 V, and cutting frequency cutoffs of 638 GHz in the first HEMT and 463 GHz for Field plate HEMT., maximum frequency of 1.7 THz, maximum efficiency of 73%, maximum breakdown voltage of 400 V, leakage current density IFuite=1 x 10-26 A, DIBL=33.52 mV/V and an ON/OFF current density ratio higher than 1 x 1010. These values were determined through the simulation by deriving genetic and Monte Carlo algorithms that optimize the design and the future of this technology. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=HEMT" title="HEMT">HEMT</a>, <a href="https://publications.waset.org/abstracts/search?q=silvaco" title=" silvaco"> silvaco</a>, <a href="https://publications.waset.org/abstracts/search?q=field%20plate" title=" field plate"> field plate</a>, <a href="https://publications.waset.org/abstracts/search?q=genetic%20algorithm" title=" genetic algorithm"> genetic algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=quantum" title=" quantum"> quantum</a> </p> <a href="https://publications.waset.org/abstracts/39443/etude-3d-quantum-numerical-simulation-of-performance-in-the-hemt" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/39443.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">3269</span> A Survey in Techniques for Imbalanced Intrusion Detection System Datasets</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Najmeh%20Abedzadeh">Najmeh Abedzadeh</a>, <a href="https://publications.waset.org/abstracts/search?q=Matthew%20Jacobs"> Matthew Jacobs</a> </p> <p class="card-text"><strong>Abstract:</strong></p> An intrusion detection system (IDS) is a software application that monitors malicious activities and generates alerts if any are detected. However, most network activities in IDS datasets are normal, and the relatively few numbers of attacks make the available data imbalanced. Consequently, cyber-attacks can hide inside a large number of normal activities, and machine learning algorithms have difficulty learning and classifying the data correctly. In this paper, a comprehensive literature review is conducted on different types of algorithms for both implementing the IDS and methods in correcting the imbalanced IDS dataset. The most famous algorithms are machine learning (ML), deep learning (DL), synthetic minority over-sampling technique (SMOTE), and reinforcement learning (RL). Most of the research use the CSE-CIC-IDS2017, CSE-CIC-IDS2018, and NSL-KDD datasets for evaluating their algorithms. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=IDS" title="IDS">IDS</a>, <a href="https://publications.waset.org/abstracts/search?q=imbalanced%20datasets" title=" imbalanced datasets"> imbalanced datasets</a>, <a href="https://publications.waset.org/abstracts/search?q=sampling%20algorithms" title=" sampling algorithms"> sampling algorithms</a>, <a href="https://publications.waset.org/abstracts/search?q=big%20data" title=" big data"> big data</a> </p> <a href="https://publications.waset.org/abstracts/149498/a-survey-in-techniques-for-imbalanced-intrusion-detection-system-datasets" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/149498.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">327</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">3268</span> 3D Quantum Simulation of a HEMT Device Performance</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Z.%20Kourdi">Z. Kourdi</a>, <a href="https://publications.waset.org/abstracts/search?q=B.%20Bouazza"> B. Bouazza</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20Khaouani"> M. Khaouani</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20Guen-Bouazza"> A. Guen-Bouazza</a>, <a href="https://publications.waset.org/abstracts/search?q=Z.%20Djennati"> Z. Djennati</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20Boursali"> A. Boursali</a> </p> <p class="card-text"><strong>Abstract:</strong></p> We present a simulation of a HEMT (high electron mobility transistor) structure with and without a field plate. We extract the device characteristics through the analysis of DC, AC and high frequency regimes, as shown in this paper. This work demonstrates the optimal device with a gate length of 15 nm, InAlN/GaN heterostructure and field plate structure, making it superior to modern HEMTs when compared with otherwise equivalent devices. This improves the ability to bear the burden of the current density passes in the channel. We have demonstrated an excellent current density, as high as 2.05 A/mm, a peak extrinsic transconductance of 590 mS/mm at VDS=2 V, and cutting frequency cutoffs of 638 GHz in the first HEMT and 463 GHz for Field plate HEMT., maximum frequency of 1.7 THz, maximum efficiency of 73%, maximum breakdown voltage of 400 V, DIBL=33.52 mV/V and an ON/OFF current density ratio higher than 1 x 1010. These values were determined through the simulation by deriving genetic and Monte Carlo algorithms that optimize the design and the future of this technology. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=HEMT" title="HEMT">HEMT</a>, <a href="https://publications.waset.org/abstracts/search?q=Silvaco" title=" Silvaco"> Silvaco</a>, <a href="https://publications.waset.org/abstracts/search?q=field%20plate" title=" field plate"> field plate</a>, <a href="https://publications.waset.org/abstracts/search?q=genetic%20algorithm" title=" genetic algorithm"> genetic algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=quantum" title=" quantum"> quantum</a> </p> <a href="https://publications.waset.org/abstracts/30552/3d-quantum-simulation-of-a-hemt-device-performance" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/30552.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">476</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">3267</span> Linear Array Geometry Synthesis with Minimum Sidelobe Level and Null Control Using Taguchi Method</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Amara%20Prakasa%20Rao">Amara Prakasa Rao</a>, <a href="https://publications.waset.org/abstracts/search?q=N.%20V.%20S.%20N.%20Sarma"> N. V. S. N. Sarma</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper describes the synthesis of linear array geometry with minimum sidelobe level and null control using the Taguchi method. Based on the concept of the orthogonal array, Taguchi method effectively reduces the number of tests required in an optimization process. Taguchi method has been successfully applied in many fields such as mechanical, chemical engineering, power electronics, etc. Compared to other evolutionary methods such as genetic algorithms, simulated annealing and particle swarm optimization, the Taguchi method is much easier to understand and implement. It requires less computational/iteration processing to optimize the problem. Different cases are considered to illustrate the performance of this technique. Simulation results show that this method outperforms the other evolution algorithms (like GA, PSO) for smart antenna systems design. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=array%20factor" title="array factor">array factor</a>, <a href="https://publications.waset.org/abstracts/search?q=beamforming" title=" beamforming"> beamforming</a>, <a href="https://publications.waset.org/abstracts/search?q=null%20placement" title=" null placement"> null placement</a>, <a href="https://publications.waset.org/abstracts/search?q=optimization%20method" title=" optimization method"> optimization method</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%20method" title=" Taguchi method"> Taguchi method</a>, <a href="https://publications.waset.org/abstracts/search?q=smart%20antenna%20system" title=" smart antenna system"> smart antenna system</a> </p> <a href="https://publications.waset.org/abstracts/14589/linear-array-geometry-synthesis-with-minimum-sidelobe-level-and-null-control-using-taguchi-method" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/14589.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">394</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">3266</span> Investigation of Genetic Diversity in Bread Wheat by RAPD and SSR Markers </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mohammad%20Sadegh%20Khavarinejad">Mohammad Sadegh Khavarinejad</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this study, genetic diversity of 10 bread wheat genotypes by SSR and RAPD markers was evaluated. 11 primers were used included 6 RAPD primers and 5 SSR primers. RAPDs and SSRs could find 33 and 17 polymorphism respectively. In RAPDs, primers UBC 350 and UBC 109 and in SSRs, Primers Xgwm 469-6D and Xgwm120-2B showed genetic diversity among genotypes more than others. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=wheat" title="wheat">wheat</a>, <a href="https://publications.waset.org/abstracts/search?q=molecular%20markers" title=" molecular markers"> molecular markers</a>, <a href="https://publications.waset.org/abstracts/search?q=SSR" title=" SSR"> SSR</a>, <a href="https://publications.waset.org/abstracts/search?q=RAPD" title=" RAPD "> RAPD </a> </p> <a href="https://publications.waset.org/abstracts/21379/investigation-of-genetic-diversity-in-bread-wheat-by-rapd-and-ssr-markers" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/21379.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">433</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">3265</span> Optimization of Steel Moment Frame Structures Using Genetic Algorithm</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mohammad%20Befkin">Mohammad Befkin</a>, <a href="https://publications.waset.org/abstracts/search?q=Alireza%20Momtaz"> Alireza Momtaz</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Structural design is the challenging aspect of every project due to limitations in dimensions, functionality of the structure, and more importantly, the allocated budget for construction. This research study aims to investigate the optimized design for three steel moment frame buildings with different number of stories using genetic algorithm code. The number and length of spans, and height of each floor were constant in all three buildings. The design of structures are carried out according to AISC code within the provisions of plastic design with allowable stress values. Genetic code for optimization is produced using MATLAB program, while buildings modeled in Opensees program and connected to the MATLAB code to perform iterations in optimization steps. In the end designs resulted from genetic algorithm code were compared with the analysis of buildings in ETABS program. The results demonstrated that suggested structural elements by the code utilize their full capacity, indicating the desirable efficiency of produced code. <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=structural%20analysis" title=" structural analysis"> structural analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=steel%20moment%20frame" title=" steel moment frame"> steel moment frame</a>, <a href="https://publications.waset.org/abstracts/search?q=structural%20design" title=" structural design"> structural design</a> </p> <a href="https://publications.waset.org/abstracts/166927/optimization-of-steel-moment-frame-structures-using-genetic-algorithm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/166927.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">118</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3264</span> Development of Microsatellite Markers for Genetic Variation Analysis in House Cricket, Acheta domesticus</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yash%20M.%20Gupta">Yash M. Gupta</a>, <a href="https://publications.waset.org/abstracts/search?q=Kittisak%20Buddhachat"> Kittisak Buddhachat</a>, <a href="https://publications.waset.org/abstracts/search?q=Surin%20Peyachoknagul"> Surin Peyachoknagul</a>, <a href="https://publications.waset.org/abstracts/search?q=Somjit%20Homchan"> Somjit Homchan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The house cricket, Acheta domesticus is one of the commonly found species of field crickets. Although it is very commonly used as food and feed, the genomic information of house cricket is still missing for genetic investigation. DNA sequencing technology has evolved over the decades, and it has also revolutionized the molecular marker development for genetic analysis. In the present study, we have sequenced the whole genome of A. domesticus using illumina platform based HiSeq X Ten sequencing technology for searching simple sequence repeats (SSRs) in DNA to develop polymorphic microsatellite markers for population genetic analysis. A total of 112,157 SSRs with primer pairs were identified, 91 randomly selected SSRs used to check DNA amplification, of which nine primers were polymorphic. These microsatellite markers have shown cross-amplification with other three species of crickets which are Gryllus bimaculatus, Gryllus testaceus and Brachytrupes portentosus. These nine polymorphic microsatellite markers were used to check genetic variation for forty-five individuals of A. domesticus, Phitsanulok population, Thailand. For nine loci, the number of alleles was ranging from 5 to 15. The observed heterozygosity was ranged from 0.4091 to 0.7556. These microsatellite markers will facilitate population genetic analysis for future studies of A. domesticus populations. Moreover, the transferability of these SSR makers would also enable researchers to conduct genetic studies for other closely related species. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=cross-amplification" title="cross-amplification">cross-amplification</a>, <a href="https://publications.waset.org/abstracts/search?q=microsatellite%20markers" title=" microsatellite markers"> microsatellite markers</a>, <a href="https://publications.waset.org/abstracts/search?q=observed%20heterozygosity" title=" observed heterozygosity"> observed heterozygosity</a>, <a href="https://publications.waset.org/abstracts/search?q=population%20genetic" title=" population genetic"> population genetic</a>, <a href="https://publications.waset.org/abstracts/search?q=simple%20sequence%20repeats" title=" simple sequence repeats"> simple sequence repeats</a> </p> <a href="https://publications.waset.org/abstracts/109733/development-of-microsatellite-markers-for-genetic-variation-analysis-in-house-cricket-acheta-domesticus" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/109733.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">140</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">3263</span> A Pipeline for Detecting Copy Number Variation from Whole Exome Sequencing Using Comprehensive Tools</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Cheng-Yang%20Lee">Cheng-Yang Lee</a>, <a href="https://publications.waset.org/abstracts/search?q=Petrus%20Tang"> Petrus Tang</a>, <a href="https://publications.waset.org/abstracts/search?q=Tzu-Hao%20Chang"> Tzu-Hao Chang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Copy number variations (CNVs) have played an important role in many kinds of human diseases, such as Autism, Schizophrenia and a number of cancers. Many diseases are found in genome coding regions and whole exome sequencing (WES) is a cost-effective and powerful technology in detecting variants that are enriched in exons and have potential applications in clinical setting. Although several algorithms have been developed to detect CNVs using WES and compared with other algorithms for finding the most suitable methods using their own samples, there were not consistent datasets across most of algorithms to evaluate the ability of CNV detection. On the other hand, most of algorithms is using command line interface that may greatly limit the analysis capability of many laboratories. We create a series of simulated WES datasets from UCSC hg19 chromosome 22, and then evaluate the CNV detective ability of 19 algorithms from OMICtools database using our simulated WES datasets. We compute the sensitivity, specificity and accuracy in each algorithm for validation of the exome-derived CNVs. After comparison of 19 algorithms from OMICtools database, we construct a platform to install all of the algorithms in a virtual machine like VirtualBox which can be established conveniently in local computers, and then create a simple script that can be easily to use for detecting CNVs using algorithms selected by users. We also build a table to elaborate on many kinds of events, such as input requirement, CNV detective ability, for all of the algorithms that can provide users a specification to choose optimum algorithms. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=whole%20exome%20sequencing" title="whole exome sequencing">whole exome sequencing</a>, <a href="https://publications.waset.org/abstracts/search?q=copy%20number%20variations" title=" copy number variations"> copy number variations</a>, <a href="https://publications.waset.org/abstracts/search?q=omictools" title=" omictools"> omictools</a>, <a href="https://publications.waset.org/abstracts/search?q=pipeline" title=" pipeline"> pipeline</a> </p> <a href="https://publications.waset.org/abstracts/43020/a-pipeline-for-detecting-copy-number-variation-from-whole-exome-sequencing-using-comprehensive-tools" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/43020.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">319</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">3262</span> Dual Band Antenna Design with Compact Radiator for 2.5/5.2/5.8 Ghz Wlan Application Using Genetic Algorithm</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ramnath%20Narhete">Ramnath Narhete</a>, <a href="https://publications.waset.org/abstracts/search?q=Saket%20Pandey"> Saket Pandey</a>, <a href="https://publications.waset.org/abstracts/search?q=Puran%20Gour"> Puran Gour</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents of dual-band planner antenna with a compact radiator for 2.4/5.2/5.8 proposed by optimizing its resonant frequency, Bandwidth of operation and radiation frequency using the genetic algorithm. The antenna consists L-shaped and E-shaped radiating element to generate two resonant modes for dual band operation. The above techniques have been successfully used in many applications. Dual band antenna with the compact radiator for 2.4/5.2/5.8 GHz WLAN application design and radiator size only width 8mm and a length is 11.3 mm. The antenna can we used for various application in the field of communication. Genetic algorithm will be used to design the antenna and impedance matching network. <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=dual-band%20E" title=" dual-band E"> dual-band E</a>, <a href="https://publications.waset.org/abstracts/search?q=dual-band%20L" title=" dual-band L"> dual-band L</a>, <a href="https://publications.waset.org/abstracts/search?q=WLAN" title=" WLAN"> WLAN</a>, <a href="https://publications.waset.org/abstracts/search?q=compact%20radiator" title=" compact radiator"> compact radiator</a> </p> <a href="https://publications.waset.org/abstracts/28512/dual-band-antenna-design-with-compact-radiator-for-255258-ghz-wlan-application-using-genetic-algorithm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/28512.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">579</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">3261</span> Credit Risk Assessment Using Rule Based Classifiers: A Comparative Study</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Salima%20Smiti">Salima Smiti</a>, <a href="https://publications.waset.org/abstracts/search?q=Ines%20Gasmi"> Ines Gasmi</a>, <a href="https://publications.waset.org/abstracts/search?q=Makram%20Soui"> Makram Soui</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Credit risk is the most important issue for financial institutions. Its assessment becomes an important task used to predict defaulter customers and classify customers as good or bad payers. To this objective, numerous techniques have been applied for credit risk assessment. However, to our knowledge, several evaluation techniques are black-box models such as neural networks, SVM, etc. They generate applicants’ classes without any explanation. In this paper, we propose to assess credit risk using rules classification method. Our output is a set of rules which describe and explain the decision. To this end, we will compare seven classification algorithms (JRip, Decision Table, OneR, ZeroR, Fuzzy Rule, PART and Genetic programming (GP)) where the goal is to find the best rules satisfying many criteria: accuracy, sensitivity, and specificity. The obtained results confirm the efficiency of the GP algorithm for German and Australian datasets compared to other rule-based techniques to predict the credit risk. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=credit%20risk%20assessment" title="credit risk assessment">credit risk assessment</a>, <a href="https://publications.waset.org/abstracts/search?q=classification%20algorithms" title=" classification algorithms"> classification algorithms</a>, <a href="https://publications.waset.org/abstracts/search?q=data%20mining" title=" data mining"> data mining</a>, <a href="https://publications.waset.org/abstracts/search?q=rule%20extraction" title=" rule extraction"> rule extraction</a> </p> <a href="https://publications.waset.org/abstracts/82645/credit-risk-assessment-using-rule-based-classifiers-a-comparative-study" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/82645.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">181</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">3260</span> Mutual Information Based Image Registration of Satellite Images Using PSO-GA Hybrid Algorithm </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Dipti%20Patra">Dipti Patra</a>, <a href="https://publications.waset.org/abstracts/search?q=Guguloth%20Uma"> Guguloth Uma</a>, <a href="https://publications.waset.org/abstracts/search?q=Smita%20Pradhan"> Smita Pradhan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Registration is a fundamental task in image processing. It is used to transform different sets of data into one coordinate system, where data are acquired from different times, different viewing angles, and/or different sensors. The registration geometrically aligns two images (the reference and target images). Registration techniques are used in satellite images and it is important in order to be able to compare or integrate the data obtained from these different measurements. In this work, mutual information is considered as a similarity metric for registration of satellite images. The transformation is assumed to be a rigid transformation. An attempt has been made here to optimize the transformation function. The proposed image registration technique hybrid PSO-GA incorporates the notion of Particle Swarm Optimization and Genetic Algorithm and is used for finding the best optimum values of transformation parameters. The performance comparision obtained with the experiments on satellite images found that the proposed hybrid PSO-GA algorithm outperforms the other algorithms in terms of mutual information and registration accuracy. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=image%20registration" title="image registration">image registration</a>, <a href="https://publications.waset.org/abstracts/search?q=genetic%20algorithm" title=" genetic algorithm"> genetic algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=particle%20swarm%20optimization" title=" particle swarm optimization"> particle swarm optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=hybrid%20PSO-GA%20algorithm%20and%20mutual%20information" title=" hybrid PSO-GA algorithm and mutual information"> hybrid PSO-GA algorithm and mutual information</a> </p> <a href="https://publications.waset.org/abstracts/9683/mutual-information-based-image-registration-of-satellite-images-using-pso-ga-hybrid-algorithm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/9683.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">407</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3259</span> Solving Process Planning and Scheduling with Number of Operation Plus Processing Time Due-Date Assignment Concurrently Using a Genetic Search</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Halil%20Ibrahim%20Demir">Halil Ibrahim Demir</a>, <a href="https://publications.waset.org/abstracts/search?q=Alper%20Goksu"> Alper Goksu</a>, <a href="https://publications.waset.org/abstracts/search?q=Onur%20Canpolat"> Onur Canpolat</a>, <a href="https://publications.waset.org/abstracts/search?q=Caner%20Erden"> Caner Erden</a>, <a href="https://publications.waset.org/abstracts/search?q=Melek%20Nur"> Melek Nur</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Traditionally process planning, scheduling and due date assignment are performed sequentially and separately. High interrelation between these functions makes integration very useful. Although there are numerous works on integrated process planning and scheduling and many works on scheduling with due date assignment, there are only a few works on the integration of these three functions. Here we tested the different integration levels of these three functions and found a fully integrated version as the best. We applied genetic search and random search and genetic search was found better compared to the random search. We penalized all earliness, tardiness and due date related costs. Since all these three terms are all undesired, it is better to penalize all of them. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=process%20planning" title="process planning">process planning</a>, <a href="https://publications.waset.org/abstracts/search?q=scheduling" title=" scheduling"> scheduling</a>, <a href="https://publications.waset.org/abstracts/search?q=due-date%20assignment" title=" due-date assignment"> due-date assignment</a>, <a href="https://publications.waset.org/abstracts/search?q=genetic%20algorithm" title=" genetic algorithm"> genetic algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=random%20search" title=" random search"> random search</a> </p> <a href="https://publications.waset.org/abstracts/68612/solving-process-planning-and-scheduling-with-number-of-operation-plus-processing-time-due-date-assignment-concurrently-using-a-genetic-search" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/68612.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">375</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">3258</span> A Cognitive Approach to the Optimization of Power Distribution across an Educational Campus</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mrinmoy%20Majumder">Mrinmoy Majumder</a>, <a href="https://publications.waset.org/abstracts/search?q=Apu%20Kumar%20Saha"> Apu Kumar Saha</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The ever-increasing human population and its demand for energy is placing stress upon conventional energy sources; and as demand for power continues to outstrip supply, the need to optimize energy distribution and utilization is emerging as an important focus for various stakeholders. The distribution of available energy must be achieved in such a way that the needs of the consumer are satisfied. However, if the availability of resources is not sufficient to satisfy consumer demand, it is necessary to find a method to select consumers based on factors such as their socio-economic or environmental impacts. Weighting consumer types in this way can help separate them based on their relative importance, and cognitive optimization of the allocation process can then be carried out so that, even on days of particularly scarce supply, the socio-economic impacts of not satisfying the needs of consumers can be minimized. In this context, the present study utilized fuzzy logic to assign weightage to different types of consumers based at an educational campus in India, and then established optimal allocation by applying the non-linear mapping capability of neuro-genetic algorithms. The outputs of the algorithms were compared with similar outputs from particle swarm optimization and differential evolution algorithms. The results of the study demonstrate an option for the optimal utilization of available energy based on the socio-economic importance of consumers. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=power%20allocation" title="power allocation">power allocation</a>, <a href="https://publications.waset.org/abstracts/search?q=optimization%20problem" title=" optimization problem"> optimization problem</a>, <a href="https://publications.waset.org/abstracts/search?q=neural%20networks" title=" neural networks"> neural networks</a>, <a href="https://publications.waset.org/abstracts/search?q=environmental%20and%20ecological%20engineering" title=" environmental and ecological engineering"> environmental and ecological engineering</a> </p> <a href="https://publications.waset.org/abstracts/19462/a-cognitive-approach-to-the-optimization-of-power-distribution-across-an-educational-campus" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/19462.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">478</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">3257</span> Analytical Study of CPU Scheduling Algorithms</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Keshav%20Rathi">Keshav Rathi</a>, <a href="https://publications.waset.org/abstracts/search?q=Aakriti%20Sharma"> Aakriti Sharma</a>, <a href="https://publications.waset.org/abstracts/search?q=Vinayak%20R.%20Dinesh"> Vinayak R. Dinesh</a>, <a href="https://publications.waset.org/abstracts/search?q=Irfan%20Ramzan%20Parray"> Irfan Ramzan Parray</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Scheduling is a basic operating system function since practically all computer resources are scheduled before use. The CPU is one of the most important computer resources. Central Processing Unit (CPU) scheduling is vital because it allows the CPU to transition between processes. A processor is the most significant resource in a computer; the operating system can increase the computer's productivity. The objective of the operating system is to allow as many processes as possible to operate at the same time in order to maximize CPU utilization. The highly efficient CPU scheduler is based on the invention of high-quality scheduling algorithms that meet the scheduling objectives. In this paper, we reviewed various fundamental CPU scheduling algorithms for a single CPU and showed which algorithm is best for the particular situation. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=computer%20science" title="computer science">computer science</a>, <a href="https://publications.waset.org/abstracts/search?q=Operating%20system" title=" Operating system"> Operating system</a>, <a href="https://publications.waset.org/abstracts/search?q=CPU%20scheduling" title=" CPU scheduling"> CPU scheduling</a>, <a href="https://publications.waset.org/abstracts/search?q=cpu%20algorithms" title=" cpu algorithms"> cpu algorithms</a> </p> <a href="https://publications.waset.org/abstracts/194885/analytical-study-of-cpu-scheduling-algorithms" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/194885.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">6</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">3256</span> Reliability Improvement of Power System Networks Using Adaptive Genetic Algorithm</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Alireza%20Alesaadi">Alireza Alesaadi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Reliability analysis is a powerful method for determining the weak points of the electrical networks. In designing of electrical network, it is tried to design the most reliable network with minimal system shutting down, but it is usually associated with increasing the cost. In this paper, using adaptive genetic algorithm, a method was presented that provides the most reliable system with a certain economical cost. Finally, the proposed method is applied to a sample network and results will be analyzed. <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=adaptive%20genetic%20algorithm" title=" adaptive genetic algorithm"> adaptive genetic algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=electrical%20network" title=" electrical network"> electrical network</a>, <a href="https://publications.waset.org/abstracts/search?q=communication%20engineering" title=" communication engineering"> communication engineering</a> </p> <a href="https://publications.waset.org/abstracts/6512/reliability-improvement-of-power-system-networks-using-adaptive-genetic-algorithm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/6512.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">508</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">3255</span> A Preliminary Study for Design of Automatic Block Reallocation Algorithm with Genetic Algorithm Method in the Land Consolidation Projects</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Tayfun%20%C3%87ay">Tayfun Çay</a>, <a href="https://publications.waset.org/abstracts/search?q=Yasar%20%C4%B0nceyol"> Yasar İnceyol</a>, <a href="https://publications.waset.org/abstracts/search?q=Abdurrahman%20%C3%96zbeyaz"> Abdurrahman Özbeyaz</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Land reallocation is one of the most important steps in land consolidation projects. Many different models were proposed for land reallocation in the literature such as Fuzzy Logic, block priority based land reallocation and Spatial Decision Support Systems. A model including four parts is considered for automatic block reallocation with genetic algorithm method in land consolidation projects. These stages are preparing data tables for a project land, determining conditions and constraints of land reallocation, designing command steps and logical flow chart of reallocation algorithm and finally writing program codes of Genetic Algorithm respectively. In this study, we designed the first three steps of the considered model comprising four steps. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=land%20consolidation" title="land consolidation">land consolidation</a>, <a href="https://publications.waset.org/abstracts/search?q=landholding" title=" landholding"> landholding</a>, <a href="https://publications.waset.org/abstracts/search?q=land%20reallocation" title=" land reallocation"> land reallocation</a>, <a href="https://publications.waset.org/abstracts/search?q=optimization" title=" optimization"> optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=genetic%20algorithm" title=" genetic algorithm"> genetic algorithm</a> </p> <a href="https://publications.waset.org/abstracts/28036/a-preliminary-study-for-design-of-automatic-block-reallocation-algorithm-with-genetic-algorithm-method-in-the-land-consolidation-projects" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/28036.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">430</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">3254</span> Performance Analysis of Artificial Neural Network with Decision Tree in Prediction of Diabetes Mellitus</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=J.%20K.%20Alhassan">J. K. Alhassan</a>, <a href="https://publications.waset.org/abstracts/search?q=B.%20Attah"> B. Attah</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20Misra"> S. Misra</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Human beings have the ability to make logical decisions. Although human decision - making is often optimal, it is insufficient when huge amount of data is to be classified. medical dataset is a vital ingredient used in predicting patients health condition. In other to have the best prediction, there calls for most suitable machine learning algorithms. This work compared the performance of Artificial Neural Network (ANN) and Decision Tree Algorithms (DTA) as regards to some performance metrics using diabetes data. The evaluations was done using weka software and found out that DTA performed better than ANN. Multilayer Perceptron (MLP) and Radial Basis Function (RBF) were the two algorithms used for ANN, while RegTree and LADTree algorithms were the DTA models used. The Root Mean Squared Error (RMSE) of MLP is 0.3913,that of RBF is 0.3625, that of RepTree is 0.3174 and that of LADTree is 0.3206 respectively. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=artificial%20neural%20network" title="artificial neural network">artificial neural network</a>, <a href="https://publications.waset.org/abstracts/search?q=classification" title=" classification"> classification</a>, <a href="https://publications.waset.org/abstracts/search?q=decision%20tree%20algorithms" title=" decision tree algorithms"> decision tree algorithms</a>, <a href="https://publications.waset.org/abstracts/search?q=diabetes%20mellitus" title=" diabetes mellitus"> diabetes mellitus</a> </p> <a href="https://publications.waset.org/abstracts/35949/performance-analysis-of-artificial-neural-network-with-decision-tree-in-prediction-of-diabetes-mellitus" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/35949.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">408</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">3253</span> Using Greywolf Optimized Machine Learning Algorithms to Improve Accuracy for Predicting Hospital Readmission for Diabetes</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Vincent%20Liu">Vincent Liu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Machine learning algorithms (ML) can achieve high accuracy in predicting outcomes compared to classical models. Metaheuristic, nature-inspired algorithms can enhance traditional ML algorithms by optimizing them such as by performing feature selection. We compare ten ML algorithms to predict 30-day hospital readmission rates for diabetes patients in the US using a dataset from UCI Machine Learning Repository with feature selection performed by Greywolf nature-inspired algorithm. The baseline accuracy for the initial random forest model was 65%. After performing feature engineering, SMOTE for class balancing, and Greywolf optimization, the machine learning algorithms showed better metrics, including F1 scores, accuracy, and confusion matrix with improvements ranging in 10%-30%, and a best model of XGBoost with an accuracy of 95%. Applying machine learning this way can improve patient outcomes as unnecessary rehospitalizations can be prevented by focusing on patients that are at a higher risk of readmission. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=diabetes" title="diabetes">diabetes</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=30-day%20readmission" title=" 30-day readmission"> 30-day readmission</a>, <a href="https://publications.waset.org/abstracts/search?q=metaheuristic" title=" metaheuristic"> metaheuristic</a> </p> <a href="https://publications.waset.org/abstracts/181586/using-greywolf-optimized-machine-learning-algorithms-to-improve-accuracy-for-predicting-hospital-readmission-for-diabetes" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/181586.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">61</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">3252</span> Multiclass Support Vector Machines with Simultaneous Multi-Factors Optimization for Corporate Credit Ratings</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hyunchul%20Ahn">Hyunchul Ahn</a>, <a href="https://publications.waset.org/abstracts/search?q=William%20X.%20S.%20Wong"> William X. S. Wong</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Corporate credit rating prediction is one of the most important topics, which has been studied by researchers in the last decade. Over the last decade, researchers are pushing the limit to enhance the exactness of the corporate credit rating prediction model by applying several data-driven tools including statistical and artificial intelligence methods. Among them, multiclass support vector machine (MSVM) has been widely applied due to its good predictability. However, heuristics, for example, parameters of a kernel function, appropriate feature and instance subset, has become the main reason for the critics on MSVM, as they have dictate the MSVM architectural variables. This study presents a hybrid MSVM model that is intended to optimize all the parameter such as feature selection, instance selection, and kernel parameter. Our model adopts genetic algorithm (GA) to simultaneously optimize multiple heterogeneous design factors of MSVM. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=corporate%20credit%20rating%20prediction" title="corporate credit rating prediction">corporate credit rating prediction</a>, <a href="https://publications.waset.org/abstracts/search?q=Feature%20selection" title=" Feature selection"> Feature selection</a>, <a href="https://publications.waset.org/abstracts/search?q=genetic%20algorithms" title=" genetic algorithms"> genetic algorithms</a>, <a href="https://publications.waset.org/abstracts/search?q=instance%20selection" title=" instance selection"> instance selection</a>, <a href="https://publications.waset.org/abstracts/search?q=multiclass%20support%20vector%20machines" title=" multiclass support vector machines"> multiclass support vector machines</a> </p> <a href="https://publications.waset.org/abstracts/44856/multiclass-support-vector-machines-with-simultaneous-multi-factors-optimization-for-corporate-credit-ratings" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/44856.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">294</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">3251</span> Seismic Retrofitting of Structures Using Steel Plate Slit Dampers Based on Genetic Algorithm</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mohamed%20Noureldin">Mohamed Noureldin</a>, <a href="https://publications.waset.org/abstracts/search?q=Jinkoo%20Kim"> Jinkoo Kim</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this study, a genetic algorithm was used to find out the optimum locations of the slit dampers satisfying a target displacement. A seismic retrofit scheme for a building structure was presented using steel plate slit dampers. A cyclic loading test was used to verify the energy dissipation capacity of the slit damper. The seismic retrofit of the model structure using the slit dampers was compared with the retrofit with enlarging shear walls. The capacity spectrum method was used to propose a simple damper distribution scheme proportional to the inter-story drifts. The validity of the simple story-wise damper distribution procedure was verified by comparing the results of the genetic algorithm. It was observed that the proposed simple damper distribution pattern was in a good agreement with the optimum distribution obtained from the genetic algorithm. Acknowledgment: This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2017R1D1A1B03032809). <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=slit%20dampers" title="slit dampers">slit dampers</a>, <a href="https://publications.waset.org/abstracts/search?q=seismic%20retrofit" title=" seismic retrofit"> seismic retrofit</a>, <a href="https://publications.waset.org/abstracts/search?q=genetic%20algorithm" title=" genetic algorithm"> genetic algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=optimum%20design" title=" optimum design"> optimum design</a> </p> <a href="https://publications.waset.org/abstracts/86061/seismic-retrofitting-of-structures-using-steel-plate-slit-dampers-based-on-genetic-algorithm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/86061.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">223</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">3250</span> Applications of AFM in 4D to Optimize the Design of Genetic Nanoparticles</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hosam%20Abdelhady">Hosam Abdelhady</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Filming the behaviors of individual DNA molecules in their environment when they interact with individual medicinal nano-polymers in a molecular scale has opened the door to understand the effect of the molecular shape, size, and incubation time with nanocarriers on optimizing the design of robust genetic Nano molecules able to resist the enzymatic degradation, enter the cell, reach to the nucleus and kill individual cancer cells in their environment. To this end, we will show how we applied the 4D AFM as a guide to finetune the design of genetic nanoparticles and to film the effects of these nanoparticles on the nanomechanical and morphological profiles of individual cancer cells. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=AFM" title="AFM">AFM</a>, <a href="https://publications.waset.org/abstracts/search?q=dendrimers" title=" dendrimers"> dendrimers</a>, <a href="https://publications.waset.org/abstracts/search?q=nanoparticles" title=" nanoparticles"> nanoparticles</a>, <a href="https://publications.waset.org/abstracts/search?q=DNA" title=" DNA"> DNA</a>, <a href="https://publications.waset.org/abstracts/search?q=gene%20therapy" title=" gene therapy"> gene therapy</a>, <a href="https://publications.waset.org/abstracts/search?q=imaging" title=" imaging"> imaging</a> </p> <a href="https://publications.waset.org/abstracts/157876/applications-of-afm-in-4d-to-optimize-the-design-of-genetic-nanoparticles" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/157876.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">73</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3249</span> A Versatile Algorithm to Propose Optimized Solutions to the Dengue Disease Problem</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Fernando%20L.%20P.%20Santos">Fernando L. P. Santos</a>, <a href="https://publications.waset.org/abstracts/search?q=Luiz%20G.%20Lyra"> Luiz G. Lyra</a>, <a href="https://publications.waset.org/abstracts/search?q=Helenice%20O.%20Florentino"> Helenice O. Florentino</a>, <a href="https://publications.waset.org/abstracts/search?q=Daniela%20R.%20Cantane"> Daniela R. Cantane</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Dengue is a febrile infectious disease caused by a virus of the family Flaviridae. It is transmitted by the bite of mosquitoes, usually of the genus Aedes aegypti. It occurs in tropical and subtropical areas of the world. This disease has been a major public health problem worldwide, especially in tropical countries such as Brazil, and its incidence has increased in recent years. Dengue is a subject of intense research. Efficient forms of mosquito control must be considered. In this work, the mono-objective optimal control problem was solved for analysing the dengue disease problem. Chemical and biological controls were considered in the mathematical aspect. This model describes the dynamics of mosquitoes in water and winged phases. We applied the genetic algorithms (GA) to obtain optimal strategies for the control of dengue. Numerical simulations have been performed to verify the versatility and the applicability of this algorithm. On the basis of the present results we may recommend the GA to solve optimal control problem with a large region of feasibility. <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=dengue" title=" dengue"> dengue</a>, <a href="https://publications.waset.org/abstracts/search?q=Aedes%20aegypti" title=" Aedes aegypti"> Aedes aegypti</a>, <a href="https://publications.waset.org/abstracts/search?q=biological%20control" title=" biological control"> biological control</a>, <a href="https://publications.waset.org/abstracts/search?q=chemical%20control" title=" chemical control"> chemical control</a> </p> <a href="https://publications.waset.org/abstracts/15232/a-versatile-algorithm-to-propose-optimized-solutions-to-the-dengue-disease-problem" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/15232.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">3248</span> Nurse’s Role in Early Detection of Breast Cancer through Mammography and Genetic Screening and Its Impact on Patient's Outcome</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Salwa%20Hagag%20Abdelaziz">Salwa Hagag Abdelaziz</a>, <a href="https://publications.waset.org/abstracts/search?q=Dorria%20Salem"> Dorria Salem</a>, <a href="https://publications.waset.org/abstracts/search?q=Hoda%20Zaki"> Hoda Zaki</a>, <a href="https://publications.waset.org/abstracts/search?q=Suzan%20Atteya"> Suzan Atteya</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Early detection of breast cancer saves many thousands of lives each year via application of mammography and genetic screening and many more lives could be saved if nurses are involved in breast care screening practices. So, the aim of the study was to identify nurse's role in early detection of breast cancer through mammography and genetic screening and its impact on patient's outcome. In order to achieve this aim, 400 women above 40 years, asymptomatic were recruited for mammography and genetic screening. In addition, 50 nurses and 6 technologists were involved in the study. A descriptive analytical design was used. Five tools were utilized: sociodemographic, mammographic examination and risk factors, women's before, during and after mammography, items relaying to technologists, and items related to nurses were also obtained. The study finding revealed that 3% of women detected for malignancy and 7.25% for fibroadenoma. Statistically, significant differences were found between mammography results and age, family history, genetic screening, exposure to smoke, and using contraceptive pills. Nurses have insufficient knowledge about screening tests. Based on these findings the present study recommended involvement of nurses in breast care which is very important to in force population about screening practices. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=mammography" title="mammography">mammography</a>, <a href="https://publications.waset.org/abstracts/search?q=early%20detection" title=" early detection"> early detection</a>, <a href="https://publications.waset.org/abstracts/search?q=genetic%20screening" title=" genetic screening"> genetic screening</a>, <a href="https://publications.waset.org/abstracts/search?q=breast%20cancer" title=" breast cancer"> breast cancer</a> </p> <a href="https://publications.waset.org/abstracts/22557/nurses-role-in-early-detection-of-breast-cancer-through-mammography-and-genetic-screening-and-its-impact-on-patients-outcome" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/22557.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">562</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">3247</span> Computational Analyses of Persian Walnut Genetic Data: Notes on Genetic Diversity and Cultivar Phylogeny</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Masoud%20Sheidaei">Masoud Sheidaei</a>, <a href="https://publications.waset.org/abstracts/search?q=Melica%20Tabasi"> Melica Tabasi</a>, <a href="https://publications.waset.org/abstracts/search?q=Fahimeh%20Koohdar"> Fahimeh Koohdar</a>, <a href="https://publications.waset.org/abstracts/search?q=Mona%20Sheidaei"> Mona Sheidaei</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Juglans regia L. is an economically important species of edible nuts. Iran is known as a center of origin of genetically rich walnut germplasm and expected to be found a large diversity within Iranian walnut populations. A detailed population genetic of local populations is useful for developing an optimal strategy for in situ conservation and can assist the breeders in crop improvement programs. Different phylogenetic studies have been carried out in this genus, but none has been concerned with genetic changes associated with geographical divergence and the identification of adaptive SNPs. Therefore, we carried out the present study to identify discriminating ITS nucleotides among Juglans species and also reveal association between ITS SNPs and geographical variables. We used different computations approaches like DAPC, CCA, and RDA analyses for the above-mentioned tasks. We also performed population genetics analyses for population effective size changes associated with the species expansion. The results obtained suggest that latitudinal distribution has a more profound effect on the species genetic changes. Similarly, multiple analytical approaches utilized for the identification of both discriminating DNA nucleotides/ SNPs almost produced congruent results. The SNPs with different phylogenetic importance were also identified by using a parsimony approach. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Persian%20walnut" title="Persian walnut">Persian walnut</a>, <a href="https://publications.waset.org/abstracts/search?q=adaptive%20SNPs" title=" adaptive SNPs"> adaptive SNPs</a>, <a href="https://publications.waset.org/abstracts/search?q=data%20analyses" title=" data analyses"> data analyses</a>, <a href="https://publications.waset.org/abstracts/search?q=genetic%20diversity" title=" genetic diversity"> genetic diversity</a> </p> <a href="https://publications.waset.org/abstracts/148098/computational-analyses-of-persian-walnut-genetic-data-notes-on-genetic-diversity-and-cultivar-phylogeny" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/148098.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">129</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">3246</span> Tuning Fractional Order Proportional-Integral-Derivative Controller Using Hybrid Genetic Algorithm Particle Swarm and Differential Evolution Optimization Methods for Automatic Voltage Regulator System</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Fouzi%20Aboura">Fouzi Aboura</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The fractional order proportional-integral-derivative (FOPID) controller or fractional order (PIλDµ) is a proportional-integral-derivative (PID) controller where integral order (λ) and derivative order (µ) are fractional, one of the important application of classical PID is the Automatic Voltage Regulator (AVR).The FOPID controller needs five parameters optimization while the design of conventional PID controller needs only three parameters to be optimized. In our paper we have proposed a comparison between algorithms Differential Evolution (DE) and Hybrid Genetic Algorithm Particle Swarm Optimization (HGAPSO) ,we have studied theirs characteristics and performance analysis to find an optimum parameters of the FOPID controller, a new objective function is also proposed to take into account the relation between the performance criteria’s. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=FOPID%20controller" title="FOPID controller">FOPID controller</a>, <a href="https://publications.waset.org/abstracts/search?q=fractional%20order" title=" fractional order"> fractional order</a>, <a href="https://publications.waset.org/abstracts/search?q=AVR%20system" title=" AVR system"> AVR system</a>, <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=optimization" title=" optimization"> optimization</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=HGAPSO" title=" HGAPSO"> HGAPSO</a> </p> <a href="https://publications.waset.org/abstracts/164900/tuning-fractional-order-proportional-integral-derivative-controller-using-hybrid-genetic-algorithm-particle-swarm-and-differential-evolution-optimization-methods-for-automatic-voltage-regulator-system" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/164900.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">90</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">3245</span> Genetic-Environment Influences on the Cognitive Abilities of 6-to-8 Years Old Twins</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Annu%20Panghal">Annu Panghal</a>, <a href="https://publications.waset.org/abstracts/search?q=Bimla%20Dhanda"> Bimla Dhanda</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This research paper aims to determine the genetic-environment influences on the cognitive abilities of twins. Using the 100 pairs of twins from two districts, namely: Bhiwani (N = 90) and Hisar (N = 110) of Haryana State, genetic and environmental influences were assessed in twin study design. The cognitive abilities of twins were measured using the Wechsler Intelligence Scale for Children (WISC-R). Home Observation for Measurement of the Environment (HOME) Inventory was taken to examine the home environment of twins. Heritability estimate was used to analyze the genes contributing to shape the cognitive abilities of twins. The heritability estimates for cognitive abilities of 6-7 years old twins in Hisar district were 74% and in Bhiwani District 76%. Further the heritability estimates were 64% in the twins of Hisar district and 60 in Bhiwani district % in the age group of 7-8 years. The remaining variations in the cognitive abilities of twins were due to environmental factors namely: provision for Active Stimulation, paternal involvement, safe physical environment. The findings provide robust evidence that the cognitive abilities were more influenced by genes than the environmental factors and also revealed that the influence of genetic was more in the age group 6-7 years than the age group 7-8 years. The conclusion of the heritability estimates indicates that the genetic influence was more in the age group of 6-7 years than the age group of 7-8 years. As the age increases the genetic influence decreases and environment influence increases. Mother education was strongly associated with the cognitive abilities of twins. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=genetics" title="genetics">genetics</a>, <a href="https://publications.waset.org/abstracts/search?q=heritability" title=" heritability"> heritability</a>, <a href="https://publications.waset.org/abstracts/search?q=twins" title=" twins"> twins</a>, <a href="https://publications.waset.org/abstracts/search?q=environment" title=" environment"> environment</a>, <a href="https://publications.waset.org/abstracts/search?q=cognitive%20abilities" title=" cognitive abilities"> cognitive abilities</a> </p> <a href="https://publications.waset.org/abstracts/113491/genetic-environment-influences-on-the-cognitive-abilities-of-6-to-8-years-old-twins" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/113491.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> <ul class="pagination"> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=genetic%20algorithms&page=5" rel="prev">&lsaquo;</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=genetic%20algorithms&page=1">1</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=genetic%20algorithms&page=2">2</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=genetic%20algorithms&page=3">3</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=genetic%20algorithms&page=4">4</a></li> <li class="page-item"><a class="page-link" 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