{"title":"A New Family of Distributions with an Application to Exponentially Distribution","authors":"Layla Abdul, Jaleel Mohsin, Hazim Ghdhaib Kalt","doi":"10.52783/cana.v31.832","DOIUrl":"https://doi.org/10.52783/cana.v31.832","url":null,"abstract":"This paper introduces a new continuous distribution family called the Alpha logarithm family, which is a new modelling strategy for fitting data subject to univariate continuous distributions. This is achieved by introducing an additional parameter for greater flexibility using a single-parameter Natural logarithm transformation which can enhance some of the modeling capabilities of some Parental Continuous Distributions: This technique was applied to the exponential distribution to obtain a new two-parameter distribution, and the changes that occurred in the exponential distribution were observed. The general properties and functions of the new distribution were also derived and studied, and the estimators of the two parameters were derived. The efficiency of the estimators is verified through the simulation study. The new distribution is also applied to two sets of real data to prove the benefit of the new transformation, and we show that the proposed model is better than the asymptotic distributions with which it was compared on the selected data.","PeriodicalId":40036,"journal":{"name":"Communications on Applied Nonlinear Analysis","volume":" 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141676665","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}
Ayat Waleed Khaled, Najlae Falah, Hameed Al Saffar
{"title":"Improved Arithmetic on Koblitz Curves over Binary Field","authors":"Ayat Waleed Khaled, Najlae Falah, Hameed Al Saffar","doi":"10.52783/cana.v31.950","DOIUrl":"https://doi.org/10.52783/cana.v31.950","url":null,"abstract":"The longest process in ECC is the elliptic curve scalar multiplication. The structure of this operation involves three mathematical levels; this work aims to study issues that arise in the efficient implementation of this operation, specifically targeting the point arithmetic level for the Koblitz curve over a binary field. Theorems have been made for a speedy point doubling and point addition operation, in these theorems Jacobian coordinate modification has been considered, where these coordinates represent each point: refers to a point on a curve over . This occurs when a coordinate system represents any point on a Koblitz curve over a binary field. By choosing the right coordinate system, it is possible to speed up the elliptic curve scalar multiplication using this method.","PeriodicalId":40036,"journal":{"name":"Communications on Applied Nonlinear Analysis","volume":" 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141676745","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}
{"title":"Solving Intuitionistic Fuzzy Unconstrained Optimization Problems Using Interval Newton’s Method","authors":"S. Shilpa, Ivin Emimal, R. Hepzibah","doi":"10.52783/cana.v31.835","DOIUrl":"https://doi.org/10.52783/cana.v31.835","url":null,"abstract":"This research work studies the optimization of intuitionistic fuzzy valued functions in unconstrained problems. The Interval Newton's Method using an Intuitionistic approach addresses both single and multivariable optimization problems. The study incorporates a mathematical comprehension of interval intuitionistic fuzzy valued problems, as well as real-world examples to demonstrate their effectiveness. Furthermore, MATLAB code is provided to demonstrate the implementation of the Interval Newton's Method.","PeriodicalId":40036,"journal":{"name":"Communications on Applied Nonlinear Analysis","volume":" 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141676783","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}
{"title":"Application of the G’/G Expansion Method for Solving New Form of Nonlinear Schrödinger Equation in Bi-Isotropic Fiber","authors":"Ourahmoun Abbes","doi":"10.52783/cana.v31.951","DOIUrl":"https://doi.org/10.52783/cana.v31.951","url":null,"abstract":"Bi-isotropic media (chiral and non-reciprocal) present an outstanding challenge for the scientific community. Their characteristics have facilitated the emergence of new and remarkable applications. In this paper, we focus on the novel effect of chirality, characterized through a newly proposed formalism, to highlight the nonlinear effect induced by the magnetization vector under the influence of a strong electric field. This research work is concerned with a new formulation of constitutive relations. We delve into the analysis and discussion of the family of solutions of the nonlinear Schrödinger equation, describing the pulse propagation in nonlinear bi-isotropic media, with a novel approach to constitutive equations. We apply the extended -expansion method with varying dispersion and nonlinearity to define certain families of solutions of the nonlinear Schrödinger equation in bi-isotropic (chiral and non-reciprocal) optical fibers. This clarification aids in understanding the propagation of light with two modes of propagation: a right circular polarized wave (RCP) and a left circular polarized wave (LCP), each having two different wave vectors in nonlinear bi-isotropic media. Various novel exact solutions of bi-isotropic optical solitons are reported in this study. \u0000Introduction: The investigation of exact solutions for nonlinear partial differential equations (PDEs) holds significant importance in understanding nonlinear physical phenomena. Nonlinear waves manifest across various scientific domains, notably in optical fibers and solid-state physics. In recent years, several potent methodologies have emerged for identifying solitons and periodic wave solutions of nonlinear PDEs. These include the -expansion method [1-6], the new mapping method [9-10], the method of generalized projective Riccati equations [11-16], and the expansion method [17]. \u0000 Consequently, an original mathematical approach is proposed to evaluate nonlinear effects in bi-isotropic optical fibers, stemming from magnetization under the influence of a strong electric field [19-20]. The extended -expansion method emerges as a potent technique for deriving solution families of the nonlinear Schrödinger equation in bi-isotropic optical fibers. This method employs a perturbation expansion in powers of the dimensionless parameter and is applicable for both weak and strong nonlinearities. It accommodates varying dispersion and nonlinearity, rendering it suitable for modeling a wide array of optical fibers. \u0000Results and Conclusion: This investigate is concerned with a new formulation of constitutive relation linking to the magnetic effect, to understand rigorously the physical nature of biisotropic effects and to generalize the main macroscopic models. We inferred the nonlinear Schrodinger equation for a bi-isotropic medium term with a nonlinear term of magnetizing. In this article, the extended -expansion method is a powerful technique for determining a family of solutions of the ","PeriodicalId":40036,"journal":{"name":"Communications on Applied Nonlinear Analysis","volume":" 36","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141676840","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}
{"title":"Revolutionising Ai Deployment: Survey On Hardware Acceleration for Machine Learning Optimisation and Resilience","authors":"G. Pooja, Dr. S. Malathy","doi":"10.52783/cana.v31.855","DOIUrl":"https://doi.org/10.52783/cana.v31.855","url":null,"abstract":"This compilation of research studies holds the utmost significance in hardware acceleration for machine learning. In our current era, characterised by the exponential growth of artificial intelligence (AI) applications, these studies tackle crucial challenges in optimising neural network accelerators' performance, energy efficiency, and resilience. The importance lies in their potential to revolutionise AI implementation across various domains. Efficient hardware accelerators are a cornerstone in unlocking the full potential of AI, enabling breakthroughs in deep learning, high-speed train fault detection and isolation, and numerous other applications. By improving memory management, facts placement, bus scheduling, and fault tolerance, that research paves the way for AI structures which are both powerful and sustainable, making AI accessible and impactful in a wide variety of fields. This research is important for fostering the growth and adoption of AI, ultimately remodelling how we interact with technology and facts in our daily lives.","PeriodicalId":40036,"journal":{"name":"Communications on Applied Nonlinear Analysis","volume":"178 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141674286","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}
{"title":"Analysis of Nonlinear Schrödinger Equations with Time-Dependent Coefficients: Stability and Decay Properties","authors":"Dr. Eric Howard, Dr Nand Kumar","doi":"10.52783/cana.v31.934","DOIUrl":"https://doi.org/10.52783/cana.v31.934","url":null,"abstract":"This study investigates the stability and decay properties of solutions to nonlinear Schrödinger equations (NLSEs) with time-dependent coefficients. Employing a blend of analytical and numerical methods, we delve into how temporal variations in coefficients influence the dynamics of wave functions. Our analysis reveals that time-dependent coefficients significantly affect the stability and decay rates of solutions, uncovering conditions that lead to either enhanced stability or accelerated decay. The findings highlight the critical role of coefficient temporality in dictating the behavior of NLSE solutions. These insights not only advance our theoretical understanding of NLSEs but also bear implications for practical applications in fields modeled by these equations. Our research opens avenues for exploiting time-dependent behaviors in designing systems with desired dynamical properties.","PeriodicalId":40036,"journal":{"name":"Communications on Applied Nonlinear Analysis","volume":" 13","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141673661","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}
{"title":"Intuitionistic Fuzzy Threshold Hypergraphs and Their Role in Chasing Fugitives with Multi-Bots","authors":"Myithili.K.K","doi":"10.52783/cana.v31.826","DOIUrl":"https://doi.org/10.52783/cana.v31.826","url":null,"abstract":"In this paper, Intuitionistic Fuzzy Threshold Hypergraph (IFTHG) is described with some definitions, such as adjacency level, strength, walk, hyperpath, score values, connected and disconnected IFTHGs. IFTHGs are essential for modeling complex relationships and uncertainties in emergency response scenarios within crowed areas. Furthermore, a novel method for capturing fugitives using IFTHG model is demonstrated. The proposed system initializes robots and implements a step-by-step algorithm upon detecting any intrusion, ultimately determining the nearest robot to capture the fugitives.","PeriodicalId":40036,"journal":{"name":"Communications on Applied Nonlinear Analysis","volume":" 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141673626","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}
Mr. Jagdish Pimple, K. Vhatkar, Rachna K. Somkunwar, Mrs. Shital Wadaganve, Deepali Baghel, Dr. Rajesh Bharti, Dr. Vinod Kimbahune
{"title":"Scientific Integration of Operations Research and Machine Learning for Data Centre Optimization","authors":"Mr. Jagdish Pimple, K. Vhatkar, Rachna K. Somkunwar, Mrs. Shital Wadaganve, Deepali Baghel, Dr. Rajesh Bharti, Dr. Vinod Kimbahune","doi":"10.52783/cana.v31.948","DOIUrl":"https://doi.org/10.52783/cana.v31.948","url":null,"abstract":"In this study, we explore how to optimize data center operations by combining Operations Research (OR) and Machine Learning (ML) methodologies with Python-based categorization algorithms. Using Scikit-learn and TensorFlow, two Python libraries, we investigate how ML algorithms might be integrated with OR techniques like queuing theory and linear programming to forecast workloads and allocate resources more effectively. Problems with scheduling workloads, allocating resources, and managing energy consumption are at the heart of our research into data center optimization. The goal of this comprehensive framework is to create more effective and environmentally friendly data centre operations by systematically evaluating Python-based categorization models in response to changing workload demands and environmental circumstances. \u0000Introduction: The backbone of our digital infrastructure, data centers stand tall in the ever-changing world of contemporary technology. A vast variety of online services, including social media platforms, e-commerce websites, cloud computing, and big data analytics, rely on the servers, storage devices, networking gear, and other essential components housed in these expansive facilities. Meeting the ever-increasing demands for computational resources while simultaneously enhancing performance, efficiency, and cost-effectiveness is a daunting task for data centers, which are already struggling to keep up with the exponential growth in both the amount and complexity of digital data. \u0000Objectives: Our goal in writing this article is to delve into the ways in which data center optimization intersects with Operations Research and Machine Learning. Data center optimization presents a wide range of problems, and this course will explore the theory, methods, and best practices for using OR and ML to solve these problems. \u0000 To develop an integrated framework that combines operations research (OR) and machine learning (ML) techniques to optimize the performance, energy efficiency, and reliability of data centers. \u0000Methods: Optimization strategies that improve data center operations in terms of performance, efficiency, and sustainability. These proposed strategies make use of both OL and ML techniques. Data center operators can optimize resource allocation, workload management, temperature control, energy consumption, and anomaly detection in real-time by formally stating the optimization problem in a mathematical framework. This allows for informed decision-making, systematic analysis of trade-offs, and the implementation of adaptive control strategies. \u0000Results: The visualization depicts the projected energy usage in terms of bandwidth for both approaches, compared to the actual values. In general, although both methods demonstrate potential, additional refinement and optimization may be necessary to attain superior outcomes in real-life situations. \u0000 This discussion presents an analysis of the performance of both proc","PeriodicalId":40036,"journal":{"name":"Communications on Applied Nonlinear Analysis","volume":" 28","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141673872","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}
{"title":"On the Oscillation of a Class of Conformable Schrodinger Equations","authors":"N. Sasikala","doi":"10.52783/cana.v31.852","DOIUrl":"https://doi.org/10.52783/cana.v31.852","url":null,"abstract":"In this article, we have derived a new oscillation criteria for a class of conformable Schrodinger equations. Based on the generalized Riccati technique, the results were obtained here. Also we have extended the Hartman-Winter oscillation criteria to conformable Schrodinger equation.","PeriodicalId":40036,"journal":{"name":"Communications on Applied Nonlinear Analysis","volume":" 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141676596","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}
Shivangni Jat, R. S. Tomar, Santosh Narayankhedkar
{"title":"Graph Theoretical Models for Enhancing Highway Connectivity and Safety in Vehicular Networks","authors":"Shivangni Jat, R. S. Tomar, Santosh Narayankhedkar","doi":"10.52783/cana.v31.839","DOIUrl":"https://doi.org/10.52783/cana.v31.839","url":null,"abstract":"Vehicular networks play a crucial role in modern transportation systems, significantly impacting connectivity and safety on highways. This paper explores the application of graph theoretical models to enhance both connectivity and safety in vehicular networks. Graph theory, a branch of discrete mathematics, provides a robust framework for modeling and analyzing complex networks, including those formed by vehicles on highways. Our study begins by defining the vehicular network as a graph where nodes represent vehicles, and edges denote communication links between them. We employ various graph theoretical concepts such as connectivity, centrality, and network flow to evaluate and improve the network's performance. Key metrics, including the degree of nodes, clustering coefficients, and shortest path lengths, are utilized to quantify network connectivity and identify critical nodes and edges that influence overall network efficiency. One of the primary objectives is to ensure uninterrupted connectivity in the presence of dynamic and often unpredictable vehicular movement. To this end, we analyze the network's resilience to node failures and propose strategies to enhance robustness using redundancy and alternative routing paths. By incorporating concepts like k-connectivity and network diameter, we develop models that maintain high levels of connectivity despite the removal or failure of multiple nodes or edges. Safety is addressed through the lens of network stability and reliability. We investigate the impact of vehicular density, speed, and communication range on the network's ability to sustain reliable communication channels. Techniques such as dynamic topology management and adaptive power control are proposed to mitigate the risks associated with network fragmentation and communication delays. Furthermore, we introduce optimization algorithms that leverage graph partitioning and community detection to improve the management of vehicular clusters, facilitating efficient data dissemination and reducing the likelihood of congestion-related incidents. The proposed models are validated through simulations that mimic real-world highway conditions, demonstrating significant improvements in both connectivity and safety metrics. In conclusion, the application of graph theoretical models offers a promising approach to enhancing highway connectivity and safety in vehicular networks","PeriodicalId":40036,"journal":{"name":"Communications on Applied Nonlinear Analysis","volume":" 30","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141673799","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}