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Prediction Of Parkinson Disease Based on Feature Selection and Classification of Dopamine Transporter Scan of Brain Using Deep Learning Architectures 基于脑多巴胺转运体扫描特征选择和分类的帕金森病预测
IF 1.2 Q3 Mathematics Pub Date : 2022-05-08 DOI: 10.1142/s1793962323410210
B. Bama, Y. Jinila
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引用次数: 0
Research on the Construction of University Mental Health Education System Under Big Data 大数据下高校心理健康教育体系构建研究
IF 1.2 Q3 Mathematics Pub Date : 2022-05-08 DOI: 10.1142/s1793962323410222
Xiaochen Chen
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引用次数: 0
Dynamics of Covid-19 epidemic via two different fractional derivatives 通过两种不同的分数导数分析Covid-19的流行动态
IF 1.2 Q3 Mathematics Pub Date : 2022-05-08 DOI: 10.1142/s1793962323500071
Pushpendra Kumar, V. S. Erturk, V. Govindaraj, M. Inc., H. Abboubakar, K. Nisar
In December 2019, the novel Coronavirus, also known as 2019-nCoV or SARS-CoV-2 or COVID-19, was first recognized as a deadly disease in Wuhan, China. In this paper, we analyze two different nonclassical Coronavirus models to observe the outbreaks of this disease. Caputo and Caputo-Fabrizio (C-F) fractional derivatives are considered to simulate the given epidemic models by using two separate methods. We perform all required graphical simulations with the help of real data to demonstrate the behavior of the proposed systems. We observe that the given schemes are highly effective and suitable to analyze the dynamics of Coronavirus. We find different natures of the given model classes for both Caputo and C-F derivative sense. The main contribution of this study is to propose a novel framework of modeling to show how the fractional-order solutions can describe disease dynamics much more clearly as compared to integer-order operators. The motivation to use two different fractional derivatives, Caputo (singular-type kernel) and Caputo-Fabrizio (exponential decay-type kernel) is to explore the model dynamics under different kernels. The applications of two various kernel properties on the same model make this study more effective for scientific observations. © 2023 World Scientific Publishing Company.
2019年12月,新型冠状病毒,也被称为2019- ncov或SARS-CoV-2或COVID-19,首次在中国武汉被确认为致命疾病。本文分析了两种不同的非经典冠状病毒模型来观察该疾病的爆发。考虑用卡普托和卡普托-法布里齐奥(C-F)分数阶导数用两种不同的方法来模拟给定的流行病模型。我们在实际数据的帮助下进行了所有需要的图形模拟,以演示所提出系统的行为。我们观察到,所给出的方案是非常有效的,适合于分析冠状病毒的动力学。我们发现给定的模型类在Caputo和C-F导数意义下具有不同的性质。本研究的主要贡献是提出了一种新的建模框架,以显示分数阶解如何比整数阶算子更清楚地描述疾病动力学。使用Caputo(奇点型核)和Caputo- fabrizio(指数衰减型核)两种不同的分数阶导数的动机是探索不同核下的模型动力学。两种不同核性质在同一模型上的应用,使本研究更有效地用于科学观测。©2023世界科学出版公司。
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引用次数: 2
Deer Hunting Optimization Technique For Clustering Unsupervised Data In Data Mining 数据挖掘中无监督数据聚类的猎鹿优化技术
IF 1.2 Q3 Mathematics Pub Date : 2022-04-20 DOI: 10.1142/s1793962323410155
H. Azeez
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引用次数: 0
The effect of interference time in a predator–prey–nonprey system 捕食者-猎物-非猎物系统中干扰时间的影响
IF 1.2 Q3 Mathematics Pub Date : 2021-11-13 DOI: 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.
本文提出了一个由两个竞争物种(猎物和非猎物)和一个捕食物种组成的三物种模型。在这里,非猎物物种不包括在捕食者的食物选择中。竞争过程遵循Holling II型竞争反应对干扰时间的影响。基本结果包括系统的稳定性。首先,证明了干扰时间的增加使系统趋于稳定。其次,干扰时间对捕食者平衡密度有影响。第三,我们发展了所有物种的持久性标准。还表明,当多个稳态出现时,系统可能不是持久的。我们研究了共存平衡点的全局稳定性。为了理解分析结果,进行了数值实验。
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引用次数: 0
Spline approximation method for singularly perturbed differential-difference equation on nonuniform grids 非均匀网格上奇摄动微分-差分方程的样条逼近方法
IF 1.2 Q3 Mathematics Pub Date : 2020-12-29 DOI: 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.
研究了一类二阶奇异摄动混合位移微分-差分方程。首先,通过泰勒级数近似,将原模型简化为等价的奇摄动微分方程。然后,采用混合有限差分格式对Shishkin网格、Bakhvalov-Shishkin网格和vulanovic网格等不同类型的层适应网格进行处理。在这里,混合格式由细网格区域的三次样条近似和粗网格区域的中点迎风格式组成。误差分析表明,该方法与扰动参数无关,具有二阶收敛性。为了验证所提方案的有效性和准确性,给出了一些数值实验来支持理论结果。
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引用次数: 0
A Hybrid Multi-Scale Stacked Dilated Convolution with Attention Networks for Quality Answer Selection in Community Question Answering 基于注意网络的混合多尺度堆叠扩展卷积社区问答质量答案选择
IF 1.2 Q3 Mathematics Pub Date : 2020-11-30 DOI: 10.1142/s1793962321500161
Nivid Limbasiya, Prateek Agrawal, T. Patalia
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引用次数: 0
Author index Volume 11 (2020) 作者索引第11卷(2020)
IF 1.2 Q3 Mathematics Pub Date : 2020-11-01 DOI: 10.1142/s1793962320990019
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引用次数: 0
Author index Volume 10 (2019) 作者索引第10卷(2019)
IF 1.2 Q3 Mathematics Pub Date : 2019-11-01 DOI: 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
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引用次数: 0
Author index Volume 9 (2018) 作者索引第9卷(2018)
IF 1.2 Q3 Mathematics Pub Date : 2018-11-01 DOI: 10.1142/s2010007818990014
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引用次数: 0
期刊
International Journal of Modeling Simulation and Scientific Computing
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