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Bright Optical Solitons for the Concatenation Model with Power-Law Nonlinearity: Laplace-Adomian Decomposition 具有幂律非线性的协合模型的明亮光学孤子:拉普拉斯-阿多米分解
IF 0.3 Q3 MATHEMATICS Pub Date : 2023-12-13 DOI: 10.37256/cm.4420233705
O. González-Gaxiola, A. Biswas, Y. Yıldırım, A. Alshomrani
This paper is a numerical study of the bright optical solitons that emerge from the concatenation model which is considered with power-law nonlinearity. The Laplace-Adomian decomposition scheme is the integration methodology adopted in the paper. The surface plots are exhibited for a range of values of the power-law parameter.
本文是对幂律非线性协整模型中出现的亮光孤子的数值研究。本文采用的积分方法是拉普拉斯-阿多米分解方案。表面图显示了一系列幂律参数值。
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引用次数: 0
Surjective Isometries of Multiplication Operators and Weighted Composition Operators on nth Weighted-Type Banach Spaces of Analytic Functions 第 n 次加权型解析函数巴拿赫空间上乘法运算符和加权合成运算符的投射等分线
IF 0.3 Q3 MATHEMATICS Pub Date : 2023-12-12 DOI: 10.37256/cm.4420232472
Shams Alyusof
This paper is to characterize isometries of multiplication operators and weighted composition operators on the nth weighted-type Banach spaces {Vn : n ∈ N} of analytic functions on the open unit disk of which the Bloch space and the Zygmund space are particular cases at n = 1, 2. We give characterizations of the symbols ψ and φ for which the multiplication operator Mψ and the weighted composition operator Wψ,φ are surjective isometries. Moreover, we show that generalized weighted composition operators are not isometric on Vn.
本文旨在表征开单位圆盘上解析函数的第 n 个加权型巴拿赫空间 {Vn : n∈ N} 上的乘法算子和加权合成算子的等距性,其中布洛赫空间和齐格蒙空间是 n = 1, 2 时的特例。我们给出了符号 ψ 和 φ 的特征,对于这两个符号,乘法算子 Mψ 和加权合成算子 Wψ,φ 是投射等距。此外,我们还证明了广义加权合成算子在 Vn 上不是等距的。
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引用次数: 0
Differential Transform Method for Solving Volterra q-Integral Equations 求解 Volterra q 积分方程的微分变换法
IF 0.3 Q3 MATHEMATICS Pub Date : 2023-12-12 DOI: 10.37256/cm.4420232549
A. Bhat, H. A. Rizvi, J. Ganie, Faiza A. Sulaiman, D. K. Jain
In this paper, Volterra q-integral equations are solved by using the method of q-differential transformation. Exact solutions of linear and nonlinear q-integral equations have been investigated. To illustrate the method, several problems are discussed for the effectiveness and performance of the proposed method.
本文利用 q 微分变换的方法求解 Volterra q 积分方程。研究了线性和非线性 q 积分方程的精确解。为了说明该方法,讨论了几个问题,以证明所提方法的有效性和性能。
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引用次数: 0
Identity and Access Control Techniques for Enhanced Data Communication in Cloud 增强云计算数据通信的身份和访问控制技术
IF 0.3 Q3 MATHEMATICS Pub Date : 2023-12-10 DOI: 10.37256/cm.5120243721
Rashmi Dixit, K. Ravindranath
The preservation of sensitive data and prevention of unauthorized access are critical objectives in cloud computing environments, necessitating the implementation of robust security measures. The present study delves into the amalgamation of the Hierarchical Role Based Access Control Model (HR-ACM), Composikey, a composite key encryption algorithm, and Interactive Tree Based zero knowledge protocol (ITZKP) to construct a robust security framework for cloud security. This study presents an investigation into the viability and efficacy of integrating HRACM, Composikey, and ITZKP as a means of augmenting security measures and reducing potential hazards in cloudbased systems. The execution times comparison of the Composikey, IBPRE, and KPRE models were compared for different filesizes (1 KB to 2 GB) to evaluate the performance of the HRACM method. As roles increase, RBAC a execution time increases significantly. The HRACM Method takes 0.001 to 0.002 seconds to implement across all role counts. The results show that the HRACM Method is more efficient and time-effective than the RBAC Method. The response time measured in microseconds for the existing ZKP and Libra systems for different file sizes, ranging from 1KB to 1 GB. The results reveal that the verifier time for the ITZKP system aligns closely with the existing systems, demonstrating its ability to perform efficient verification processes. These findings collectively demonstrate the potential of the integrated security framework in enhancing cloud security.
保护敏感数据和防止未经授权的访问是云计算环境中的关键目标,因此必须实施强有力的安全措施。本研究将基于角色的分级访问控制模型(HR-ACM)、复合密钥加密算法 Composikey 和基于树的交互式零知识协议(ITZKP)结合起来,为云安全构建一个强大的安全框架。本研究探讨了将 HRACM、Composikey 和 ITZKP 集成为增强安全措施和减少云系统潜在危害的一种手段的可行性和有效性。比较了 Composikey、IBPRE 和 KPRE 模型在不同文件大小(1 KB 至 2 GB)下的执行时间,以评估 HRACM 方法的性能。随着角色的增加,RBAC 的执行时间也大幅增加。在所有角色数中,HRACM 方法的执行时间为 0.001 至 0.002 秒。结果表明,HRACM 方法比 RBAC 方法更高效、更省时。以微秒为单位测量现有 ZKP 和 Libra 系统对不同文件大小(从 1KB 到 1GB)的响应时间。结果表明,ITZKP 系统的验证时间与现有系统非常接近,这表明它有能力执行高效的验证流程。这些发现共同证明了集成安全框架在增强云安全方面的潜力。
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引用次数: 0
A CRITIC-TOPSIS MCDM Technique under the Neutrosophic Environment with Application on Aircraft Selection 中性环境下的一种 CRITIC-TOPSIS MCDM 技术在飞机选型中的应用
IF 0.3 Q3 MATHEMATICS Pub Date : 2023-12-01 DOI: 10.37256/cm.4420232963
Gurpreet Kaur, Aishwarya Dhara, Arunava Majumder, Balvinder Singh Sandhu, Avinandan Puhan, Manoj Singh Adhikari
This paper develops a CRITIC-TOPSIS ''multi-criteria decision-making'' method under a neutrosophic environment. The neutrosophic set is a generalized version of the fuzzy and ''intuitionistic fuzzy set''. The purpose of this paper is the extension of the CRITIC-TOPSIS method using neutrosophic sets to create a more accurate and efficient decision support system for selecting a very light business jet (Bizjet). It provides the ranking to the selected number of Bizjets based on some pre-defined criteria under the neutrosophic CRITIC-TOPSIS method. The results of this study are obtained from the extended version of the previous study on decision-making for the selection of Bizjets. This study obtains results under the neutrosophic environment with a more realistic scenario.
本文提出了一种中性环境下的critical - topsis“多准则决策”方法。中性集是模糊和“直觉模糊集”的广义形式。本文的目的是扩展critical - topsis方法,使用中性集来创建一个更准确和有效的决策支持系统,用于选择非常轻的公务机(Bizjet)。它根据一些预先定义的标准,在中性的critical - topsis方法下,对选定数量的Bizjets进行排名。本研究的结果来自于前人关于商业飞机选择决策研究的扩展版。本研究在中性粒细胞环境下获得了更为真实的结果。
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引用次数: 0
Efficacy of the Single Server Markovian Two-Phase Symmetric Queue with Encouraged Stationary-Queue-Size Analysis 单服务器马尔可夫两相对称队列的效率与鼓励固定队列规模分析
IF 0.3 Q3 MATHEMATICS Pub Date : 2023-11-28 DOI: 10.37256/cm.4420233505
R. Jeyachandhiran, P. Rajendran
The efficacy of the Markovian single server symmetric queue is examined in this paper together with the suggested encouraged stationary queue-size analysis. First, we propose the stochastic Markov renewal process with encouraged arrival see time averages and encouraged arrival-stationary-queue-size analysis. The server takes further vacations after two extra service phases or until the server discovers a new set of clients in the service. Finally, we discuss the utility of the Bernoulli two-vacation symmetric queue, and it is clearly shown that the degree of efficiency rises when the encouraged arrival is taken into account.
本文研究了马尔可夫单服务器对称队列的有效性,并提出了鼓励静止队列规模分析的建议。首先,我们提出了随机马尔可夫更新过程与鼓励到达时间平均和鼓励到达-静态队列规模分析。服务器在两个额外的服务阶段后或直到服务器在服务中发现一组新的客户时,会进一步休假。最后,我们讨论了伯努利双休假对称队列的效用,结果清楚地表明,当考虑到鼓励性到达时,效率会提高。
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引用次数: 0
Computing Topological Indices of 3-Layered Artificial Neural Network 计算三层人工神经网络的拓扑指标
IF 0.3 Q3 MATHEMATICS Pub Date : 2023-11-24 DOI: 10.37256/cm.4420233502
Gayathiri V, Manimaran A
Let η be a network graph with vertex and edge sets P(η) and E(η), respectively. This study aims to find the expected value (obtained during training and testing data) for Artificial Neural Networks (ANN) through indices. A three-layer artificial neural network is considered here, which we call ANN(m, n, o). Moreover, a comparison is given between the topological indices (TI) of ANN with topological indices (TI) of the Probabilistic Neural Network (PNN). By comparing the indices, we can assess the effect of network structure on ANN model accuracy. The comparison between the two approaches helps us understand the accuracy and performance of ANN and PNN models. We can also gain insights into the differences between ANN and PNN in terms of their ability to learn and generalize.
假设 η 是一个网络图,其顶点和边集分别为 P(η) 和 E(η)。本研究旨在通过指数找到人工神经网络(ANN)的预期值(在训练和测试数据期间获得)。这里考虑的是三层人工神经网络,我们称之为 ANN(m、n、o)。此外,我们还将 ANN 的拓扑指数 (TI) 与概率神经网络 (PNN) 的拓扑指数 (TI) 进行了比较。通过比较这些指数,我们可以评估网络结构对 ANN 模型准确性的影响。这两种方法之间的比较有助于我们了解 ANN 和 PNN 模型的准确性和性能。我们还可以深入了解 ANN 和 PNN 在学习和泛化能力方面的差异。
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引用次数: 0
Analysis of Deep Learning Methods for Healthcare Sector - Medical Imaging Disease Detection 医疗保健领域的深度学习方法分析 - 医学影像疾病检测
IF 0.3 Q3 MATHEMATICS Pub Date : 2023-11-17 DOI: 10.37256/cm.4420232496
Hemlata Sahu, Ramgopal Kashyap, Surbhi Bhatia, B. Dewangan, Nora A. Alkhaldi, Samson Anosh Babu, Senthilkumar Mohan
In this paper, artificial intelligence (AI) and the ideas of machine learning (ML) and deep learning (DL) are introduced gradually. Applying ML techniques like deep neural network (DNN) models has grown in popularity in recent years due to the complexity of healthcare data, which has been increasing. To extract hidden patterns and some other crucial information from the enormous amount of health data, which traditional analytics are unable to locate in a fair amount of time, ML approaches offer cost-effective and productive models for data analysis. We are encouraged to pursue this work because of the quick advancements made in DL approaches. The idea of DL is developing from its theoretical foundations to its applications. Modern ML models that are widely utilized in academia and industry, mostly in image classification and natural language processing, including DNN. Medical imaging technologies, medical healthcare data processing, medical disease diagnostics, and general healthcare all stand to greatly benefit from these developments. We have two goals: first, to conduct a survey on DL techniques for medical pictures, and second, to develop DL-based approaches for image classification. This paper is mainly targeted towards understanding the feasibility and different processes that could be adopted for medical image classification; for this, we perform a systematic literature review. A review of various existing techniques in terms of medical image classification indicates some shortcomings that have an impact on the performance of the whole model. This study aims to explore the existing DL approaches, challenges, brief comparisons, and applicability of different medical image processing are also studied and presented. The adoption of fewer datasets, poor use of temporal information, and reduced classification accuracy all contribute to the lower performance model, which is addressed. The study provides a clear explanation of contemporary developments, cutting-edge learning tools, and platforms for DL techniques.
本文将逐步介绍人工智能(AI)以及机器学习(ML)和深度学习(DL)的思想。近年来,由于医疗数据的复杂性不断增加,应用深度神经网络(DNN)模型等 ML 技术越来越受欢迎。要从海量医疗数据中提取传统分析方法无法在短时间内找到的隐藏模式和其他一些关键信息,ML 方法为数据分析提供了具有成本效益且富有成效的模型。由于 DL 方法的快速发展,我们深受鼓舞地开展了这项工作。DL 的理念正在从理论基础向应用发展。现代 ML 模型在学术界和工业界得到广泛应用,主要用于图像分类和自然语言处理,包括 DNN。医学成像技术、医疗保健数据处理、医疗疾病诊断和普通医疗保健都将从这些发展中受益匪浅。我们有两个目标:第一,对医学图像的 DL 技术进行调查;第二,开发基于 DL 的图像分类方法。本文的主要目标是了解医学图像分类的可行性和可采用的不同流程;为此,我们进行了系统的文献综述。对现有各种医学影像分类技术的回顾表明,这些技术存在一些缺点,会影响整个模型的性能。本研究旨在探讨现有的 DL 方法、挑战、简要比较以及不同医学图像处理的适用性。采用较少的数据集、对时间信息的利用不佳以及分类准确性的降低都是造成模型性能较低的原因,本研究对此进行了探讨。本研究清楚地解释了 DL 技术的当代发展、前沿学习工具和平台。
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引用次数: 0
On Nontriviality of a Product in the Classical Adams Spectral Sequence 论经典亚当斯谱序列中积的非琐碎性
IF 0.3 Q3 MATHEMATICS Pub Date : 2023-11-17 DOI: 10.37256/cm.4420232994
Linan Zhong, Hao Zhao
Let p ≥ 11 be an odd prime and q = 2(p − 1). Suppose that n ≥ 1 with n ≠ 5. Let 0 ≤ s < p − 4 and t = s + 2 + t = s + 2 + (s + 2)p + (s + 3)p2 + (s +4)p3 + pn . This paper shows that the product element δs+4h0bn−1 ∈ ExtAs+7,tq+s (Z/p,Z/p) is a nontrivial permanent cycle in the classical Adams spectral sequence, where δs+4 denotes the 4th Greek letter element.
设 p ≥ 11 为奇数素数,q = 2(p - 1)。假设 n ≥ 1,n≠5。设 0≤s < p - 4,且 t = s + 2 + t = s + 2 + (s + 2)p + (s + 3)p2 + (s + 4)p3 + pn。本文证明了乘积元素 δs+4h0bn-1∈ ExtAs+7,tq+s (Z/p,Z/p) 是经典亚当斯谱序列中的一个非小永久循环,其中 δs+4 表示第 4 个希腊字母元素。
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引用次数: 0
Error Analysis Using Three and Four Stage Eighth Order Embedded Runge-Kutta Method for Sixth Order Ordinary Differential Equation vvi(u)=f(u,v,v',v'',v''',viv) 六阶常微分方程 vvi(u)=f(u,v,v',v'',v''',viv) 的三阶和四阶嵌入式 Runge-Kutta 方法误差分析
IF 0.3 Q3 MATHEMATICS Pub Date : 2023-11-15 DOI: 10.37256/cm.4420232610
Manpreet Kaur, Sangeet Kumar, J. Bhatti
The present paper aims at providing an insight to embedded Runge-Kutta sixth order (RKSD) ordinary differential equation method for solving the initial value problem of order six of type vvi(u) = f(u, v, v', v'',v''',viv). The concept of order conditions for the three and four stages up to the eighth and ninth orders, respectively, is designed and evaluated; furthermore, the zero-stability of the proposed method is proved. Comparisons are made between these orders with the help of a mathematical example, and global and local truncated error norms are evaluated.
本文旨在深入探讨嵌入式 Runge-Kutta 六阶(RKSD)常微分方程方法,用于求解 vvi(u) = f(u, v, v', v'',v''',viv) 类型的六阶初值问题。设计并评估了三阶和四阶直至八阶和九阶的阶次条件概念;此外,还证明了所提方法的零稳定性。借助一个数学实例对这些阶数进行了比较,并评估了全局和局部截断误差规范。
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引用次数: 0
期刊
Contemporary Mathematics
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