Pub Date : 2022-05-08DOI: 10.1142/s1793962323410210
B. Bama, Y. Jinila
{"title":"Prediction Of Parkinson Disease Based on Feature Selection and Classification of Dopamine Transporter Scan of Brain Using Deep Learning Architectures","authors":"B. Bama, Y. Jinila","doi":"10.1142/s1793962323410210","DOIUrl":"https://doi.org/10.1142/s1793962323410210","url":null,"abstract":"","PeriodicalId":45889,"journal":{"name":"International Journal of Modeling Simulation and Scientific Computing","volume":"10 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2022-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76514209","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-08DOI: 10.1142/s1793962323410222
Xiaochen Chen
{"title":"Research on the Construction of University Mental Health Education System Under Big Data","authors":"Xiaochen Chen","doi":"10.1142/s1793962323410222","DOIUrl":"https://doi.org/10.1142/s1793962323410222","url":null,"abstract":"","PeriodicalId":45889,"journal":{"name":"International Journal of Modeling Simulation and Scientific Computing","volume":"77 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2022-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89552817","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-04-20DOI: 10.1142/s1793962323410155
H. Azeez
{"title":"Deer Hunting Optimization Technique For Clustering Unsupervised Data In Data Mining","authors":"H. Azeez","doi":"10.1142/s1793962323410155","DOIUrl":"https://doi.org/10.1142/s1793962323410155","url":null,"abstract":"","PeriodicalId":45889,"journal":{"name":"International Journal of Modeling Simulation and Scientific Computing","volume":"82 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2022-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79962301","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-11-13DOI: 10.1142/s1793962322500222
D. Mukherjee
In this paper, we propose a three-species model consisting of two competing (prey and nonprey) species and a predator species. Here, nonprey species are not included in the predator’s food choice. The competition process follows Holling type II competitive response to interference time. Basic results include the stability of the system. First, it is established that an increasing number of interference time stabilizes the system. Second, it is shown that the interference time has an impact on the predator equilibrium density. Third, we develop the criterion of persistence of all the species. It is also shown that the system may not be persistent when multiple steady states appear. We examine the global stability of the coexistence equilibrium point. Numerical experiments are carried out to understand the analytical outcomes.
{"title":"The effect of interference time in a predator–prey–nonprey system","authors":"D. Mukherjee","doi":"10.1142/s1793962322500222","DOIUrl":"https://doi.org/10.1142/s1793962322500222","url":null,"abstract":"In this paper, we propose a three-species model consisting of two competing (prey and nonprey) species and a predator species. Here, nonprey species are not included in the predator’s food choice. The competition process follows Holling type II competitive response to interference time. Basic results include the stability of the system. First, it is established that an increasing number of interference time stabilizes the system. Second, it is shown that the interference time has an impact on the predator equilibrium density. Third, we develop the criterion of persistence of all the species. It is also shown that the system may not be persistent when multiple steady states appear. We examine the global stability of the coexistence equilibrium point. Numerical experiments are carried out to understand the analytical outcomes.","PeriodicalId":45889,"journal":{"name":"International Journal of Modeling Simulation and Scientific Computing","volume":"16 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2021-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89636403","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-12-29DOI: 10.1142/s1793962321500057
P. Mushahary, S. R. Sahu, J. Mohapatra
In this paper, a second-order singularly perturbed differential-difference equation involving mixed shifts is considered. At first, through Taylor series approximation, the original model is reduced to an equivalent singularly perturbed differential equation. Then, the model is treated by using the hybrid finite difference scheme on different types of layer adapted meshes like Shishkin mesh, Bakhvalov–Shishkin mesh and Vulanović mesh. Here, the hybrid scheme consists of a cubic spline approximation in the fine mesh region and a midpoint upwind scheme in the coarse mesh region. The error analysis is carried out and it is shown that the proposed scheme is of second-order convergence irrespective of the perturbation parameter. To display the efficacy and accuracy of the proposed scheme, some numerical experiments are presented which support the theoretical results.
{"title":"Spline approximation method for singularly perturbed differential-difference equation on nonuniform grids","authors":"P. Mushahary, S. R. Sahu, J. Mohapatra","doi":"10.1142/s1793962321500057","DOIUrl":"https://doi.org/10.1142/s1793962321500057","url":null,"abstract":"In this paper, a second-order singularly perturbed differential-difference equation involving mixed shifts is considered. At first, through Taylor series approximation, the original model is reduced to an equivalent singularly perturbed differential equation. Then, the model is treated by using the hybrid finite difference scheme on different types of layer adapted meshes like Shishkin mesh, Bakhvalov–Shishkin mesh and Vulanović mesh. Here, the hybrid scheme consists of a cubic spline approximation in the fine mesh region and a midpoint upwind scheme in the coarse mesh region. The error analysis is carried out and it is shown that the proposed scheme is of second-order convergence irrespective of the perturbation parameter. To display the efficacy and accuracy of the proposed scheme, some numerical experiments are presented which support the theoretical results.","PeriodicalId":45889,"journal":{"name":"International Journal of Modeling Simulation and Scientific Computing","volume":"70 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2020-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90284152","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-11-30DOI: 10.1142/s1793962321500161
Nivid Limbasiya, Prateek Agrawal, T. Patalia
{"title":"A Hybrid Multi-Scale Stacked Dilated Convolution with Attention Networks for Quality Answer Selection in Community Question Answering","authors":"Nivid Limbasiya, Prateek Agrawal, T. Patalia","doi":"10.1142/s1793962321500161","DOIUrl":"https://doi.org/10.1142/s1793962321500161","url":null,"abstract":"","PeriodicalId":45889,"journal":{"name":"International Journal of Modeling Simulation and Scientific Computing","volume":"26 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2020-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78346877","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-11-01DOI: 10.1142/s1793962320990019
{"title":"Author index Volume 11 (2020)","authors":"","doi":"10.1142/s1793962320990019","DOIUrl":"https://doi.org/10.1142/s1793962320990019","url":null,"abstract":"","PeriodicalId":45889,"journal":{"name":"International Journal of Modeling Simulation and Scientific Computing","volume":"58 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90712831","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-11-01DOI: 10.1142/s1793962319990010
Ahmad, B., see Javidi, M. 5 (2019) 1950033 Ahmed, S., see Khan, N. A. 4 (2019) 1950026 Ahmedou Bamba, S. and Ellabib, A., Simulation and computational heat transfer in the human eye with Dirichlet–Neumann domain decomposition approximation 6 (2019) 1950041 Al-Omari, A. I. and Haq, A., Novel entropy estimators of a continuous random variable 2 (2019) 1950004 Alagoz, B. B., Tepljakov, A., Ates, A., Petlenkov, E. and Yeroglu, C., Time-domain identification of One Noninteger Order Plus Time Delay models from step response measurements 1 (2019) 1941011 Aleroev, T. S. and Erokhin, S., Some solutions of the nonhomogeneous Bagley–Torvik equation 1 (2019) 1941002 Aleroev, T., Aleroeva, H. and Kirianova, L., One method for the boundary value problem eigenvalues calculating for a second-order differential equation with a fractional derivative 1 (2019) 1941004 Aleroeva, H., see Aleroev, T. 1 (2019) 1941004 Altun, E., Weighted-exponential regression model: An alternative to the gamma regression model 6 (2019) 1950035 Amine, K., An energy-degree evaluation metric for clustering purposes in mobile ad hoc networks 2 (2019) 1950005 Anand Kumar, G. and Sridevi, P. V., Deep learning network with Euclidean similarity factor for Brain MR Tumor segmentation and volume estimation 6 (2019) 1950039 Ananthula, V. R., see Ram Mohan, Ch. 3 (2019) 1950014 Araki, F., see Matsuoka, D. 3 (2019) 1950018 Arshad, S., Baleanu, D., Defterli, O. and Shumaila, A numerical framework for the approximate solution of fractional tumor-obesity model 1 (2019) 1941008 Ates, A., see Alagoz, B. B. 1 (2019) 1941011 Badshah, N., see Murad, D. 2 (2019) 1950006 Baleanu, D., see Arshad, S. 1 (2019) 1941008
Ahmed, B.， see Javidi, M. 5 (2019) 1950033 Ahmed, S.， see Khan, N. A. 4 (2019) 1950026 Ahmedou Bamba, S.和Ellabib, A.，人眼中的模拟和计算传热与Dirichlet-Neumann域分解近似6 (2019)1950041 Al-Omari, a.i.和Haq, A.，连续随机变量的新熵估计2 (2019)1950004 Alagoz, b.b.， Tepljakov, A.， Ates, A.， Petlenkov, E.和Yeroglu, C.，Aleroev, t.s.和Erokhin, S.，非齐次Bagley-Torvik方程的一些解1 (2019)1941002 Aleroev, T.， Aleroeva, H.和Kirianova, L.，一种计算二阶分数阶导数微分方程边值问题特征值的方法1 (2019)1941004 Aleroeva, H.，参见Aleroev, T. 1 (2019) 1941004 Altun, E.，加权指数回归模型:gamma回归模型的替代方案6 (2019)1950035 Amine, K.，移动自组织网络中用于聚类目的能量度评估指标2 (2019)1950005 Anand Kumar, G.和Sridevi, P. V.，脑MR肿瘤分割和体积估计的欧氏相似因子深度学习网络6 (2019)1950039 Ananthula, V. R.， see Ram Mohan, Ch. 3 (2019) 1950014 Araki, F.， see Matsuoka, D. 3 (2019) 1950018 Arshad, S.， Baleanu, D.， Defterli, O.和Shumaila，一个分数型肿瘤-肥胖模型近似解的数值框架[1](2019)1941008 .刘建军，刘建军，刘建军，等。1(2019)1941011。2 (2019)1950006
{"title":"Author index Volume 10 (2019)","authors":"","doi":"10.1142/s1793962319990010","DOIUrl":"https://doi.org/10.1142/s1793962319990010","url":null,"abstract":"Ahmad, B., see Javidi, M. 5 (2019) 1950033 Ahmed, S., see Khan, N. A. 4 (2019) 1950026 Ahmedou Bamba, S. and Ellabib, A., Simulation and computational heat transfer in the human eye with Dirichlet–Neumann domain decomposition approximation 6 (2019) 1950041 Al-Omari, A. I. and Haq, A., Novel entropy estimators of a continuous random variable 2 (2019) 1950004 Alagoz, B. B., Tepljakov, A., Ates, A., Petlenkov, E. and Yeroglu, C., Time-domain identification of One Noninteger Order Plus Time Delay models from step response measurements 1 (2019) 1941011 Aleroev, T. S. and Erokhin, S., Some solutions of the nonhomogeneous Bagley–Torvik equation 1 (2019) 1941002 Aleroev, T., Aleroeva, H. and Kirianova, L., One method for the boundary value problem eigenvalues calculating for a second-order differential equation with a fractional derivative 1 (2019) 1941004 Aleroeva, H., see Aleroev, T. 1 (2019) 1941004 Altun, E., Weighted-exponential regression model: An alternative to the gamma regression model 6 (2019) 1950035 Amine, K., An energy-degree evaluation metric for clustering purposes in mobile ad hoc networks 2 (2019) 1950005 Anand Kumar, G. and Sridevi, P. V., Deep learning network with Euclidean similarity factor for Brain MR Tumor segmentation and volume estimation 6 (2019) 1950039 Ananthula, V. R., see Ram Mohan, Ch. 3 (2019) 1950014 Araki, F., see Matsuoka, D. 3 (2019) 1950018 Arshad, S., Baleanu, D., Defterli, O. and Shumaila, A numerical framework for the approximate solution of fractional tumor-obesity model 1 (2019) 1941008 Ates, A., see Alagoz, B. B. 1 (2019) 1941011 Badshah, N., see Murad, D. 2 (2019) 1950006 Baleanu, D., see Arshad, S. 1 (2019) 1941008","PeriodicalId":45889,"journal":{"name":"International Journal of Modeling Simulation and Scientific Computing","volume":"13 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78936270","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-11-01DOI: 10.1142/s2010007818990014
{"title":"Author index Volume 9 (2018)","authors":"","doi":"10.1142/s2010007818990014","DOIUrl":"https://doi.org/10.1142/s2010007818990014","url":null,"abstract":"","PeriodicalId":45889,"journal":{"name":"International Journal of Modeling Simulation and Scientific Computing","volume":"35 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77839788","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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