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Effect of random movement and cooperative hunting in the prey-predator system:A dynamical approach

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International Journal of Biomathematics 2024年第3期17卷 211-240页

作者： Shivam teekam singh Mukesh Kumar Department of Mathematics Graphic Era Deemed to be University 566/6 Bell RoadSociety AreaClenent Town DehradunUttarakhand 248002India Department of Computer Science and Engineering Graphic Era Deemed to be University 566/6 Bell RoadSociety AreaClement Town DehradunUttarakhand 248002India

Self-diffusion prerequisite is obtained as the spreading approach of biological *** hunting is a common behavior in predator populations that promotes predation and the coexistence of the prey-predator *** the other side,the Allee effect among prey may cause the system to become *** this paper,a difusive prey predator system with cooperative hunting and the weak Allee effect in prey populations is *** linear stability and Hopf-bifurcation analysis had been used to examine the system's *** the spatial stability of the system,the conditions for Turing instability have been *** multiple-scale analysis has been used to derive the amplitude equations of the *** stability analysis of these amplitude equations leads to the formation of Turing ***,numerical simulations are used to analyze spatial patterns forming in 1-D and *** studies indicate that the model can generate a complex pattern structure and that self-diffusion has a drastic impacton species distribution.

关键词： Prey predator system hunting cooperation Allee effect Hopf-bifurcation diffusive instability amplitudeequation

Ordering Cost Depletion in Inventory Policy with Imperfect Products and Backorder Rebate

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Computers, Materials & Continua 2021年第3期66卷 2343-2357页

作者： Sandeep Kumar teekam singh Kamaleldin Abodayeh Wasfi Shatanawi Department of Mathematics Graphic Era Hill UniversityDehradun248002India Department of Mathematics Graphic Era Deemed UniversityDehradun248002India Department of Mathematics and General Sciences Prince Sultan UniversityRiyadh11586Saudi Arabia China Medical University Hospital China Medical UniversityTaichung40402Taiwan Department of Mathematics Hashemite UniversityZarqa13133Jordan

This study presents an inventory model for imperfect products with depletion in ordering costs and constant lead time where the price discount in the backorder is *** imperfect products are refused or modified or if they reached to the customer,returned and thus some extra costs are *** some of the researchers explicitly present on the significant association between size of lot and quality *** practical situations,the unsatisfied demands increase the period of lead time and decrease the *** control customers'problems and losses,the supplier provides a price discount in backorders during ***,an order’s policies may result in including some imperfect products in arrival lots.A discount on price may be offered by the supplier on the out-of-stock products to manage the backorder *** study aims to develop a model with imperfect products by permitting the price discount in backorders,and the cost of ordering is considered a decision ***,it is assumed that the demand for lead time is followed by a normal distribution and then stops it and assumed that the first two moments of demand for lead time are ***,the minimax distribution method is used to solve this model,and a separate algorithm is *** this study,two models are discussed with and without a normally distributed rate of *** current study verified with the help of some numerical examples over various model parameters.

关键词： Inventory ordering cost imperfect product lead time backorder

Detection of Behavioral Patterns Employing a Hybrid Approach of Computational Techniques

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Computers, Materials & Continua 2022年第7期72卷 2015-2031页

作者： Rohit Raja Chetan Swarup Abhishek Kumar Kamred Udham singh teekam singh Dinesh Gupta Neeraj Varshney Swati Jain Department of Information Technology Guru Ghasidas VishwavidyalayaBilaspur495009India Department of Basic Science College of Science&Theoretical StudiesSaudi Electronic University13316Saudi Arabia Department of Computer Science&IT JAIN(Deemed to be University)Bangalore560069India Computer Science and Information Science Cheng Kung University621301Taiwan School of Computer Science University of Petroleum and Energy StudiesDehradun248007India Department of CSE I K Gujral Punjab Technical UniversityJalandhar144603India Department of Computer Engineering and Applications GLA UniversityMathura281406India Department of Computer Science Government J Yoganandam Chhattisgarh CollegeRaipur492001India

As far as the present state is concerned in detecting the behavioral pattern of humans(subject)using morphological image processing,a considerable portion of the study has been conducted utilizing frontal vision data of human *** present research work had used a side vision of human-face data to develop a theoretical framework via a hybrid analytical model *** this example,hybridization includes an artificial neural network(ANN)with a genetic algorithm(GA).We researched the geometrical properties extracted from side-vision human-face *** additional study was conducted to determine the ideal number of geometrical characteristics to pick while *** close vicinity ofminimum distance measurements is done for these clusters,mapped for proper classification and decision process of behavioral *** identify the data acquired,support vector machines and artificial neural networks are utilized.A method known as an adaptiveunidirectional associative memory(AUTAM)was used to map one side of a human face to the other side of the same *** behavioral pattern has been detected based on two-class problem classification,and the decision process has been done using a genetic algorithm with best-fit *** developed algorithm in the present work has been tested by considering a dataset of 100 subjects and tested using standard databases like FERET,Multi-PIE,Yale Face database,RTR,CASIA,*** complexity measures have also been calculated under worst-case and best-case situations.

关键词： Adaptive-unidirectional-associative-memory technique artificial neural network genetic algorithm hybrid approach

Prediction of Cardiovascular Disease Using Machine Learning Technique—A Modern Approach

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Computers, Materials & Continua 2022年第4期71卷 855-869页

作者： Visvasam Devadoss Ambeth Kumar Chetan Swarup Indhumathi Murugan Abhishek Kumar Kamred Udham singh teekam singh Ramu Dubey Department of Computer Science&Engineering Panimalar Engineering CollegeAnna UniversityChennai600123India Department of Basic Science College of Science&Theoretical StudiesSaudi Electronic UniversityRiyadh-Male Campus 13316Saudi Arabia Department of Computer Science&IT JAIN(Deemed to be University)Bangalore560069India Department of Computer Science and Information Engineering National Cheng Kung UniversityTainan 701Taiwan Department of Mathematics Graphic Era Hill UniversityDehradun248002India Department of Mathematics J.C.Bose University of Science&TechnologyYMCAFaridabad121006India

Cardio Vascular disease(CVD),involving the heart and blood vessels is one of the most leading causes of death throughout the *** are several risk factors for causing heart diseases like sedentary lifestyle,unhealthy diet,obesity,diabetes,hypertension,smoking and consumption of alcohol,stress,hereditary factory *** cardiovascular disease and improving and treating the risk factors at an early stage are of paramount importance to save the precious life of a human *** present,the highly stressful life with bad lifestyle activities causes heart disease at a very young *** main aim of this research is to predict the premature heart disease based on machine learning *** paper deals with a novel approach using the machine learning algorithm for predicting the cardiovascular disease at the premature stage *** Vector Machine(SVM)is used for segregating the CVD patients based on their symptoms and medical *** experimentation results by using the proposed method will facilitate the medical practitioners to provide suitable treatment for the patients on time.A sophisticated model has been developed with the current approach to examine the various stages of CVD and the performance metrics used have given effective and fruitful results as compared to other machine learning techniques.

关键词： Machine learning support vector machine classification cardiovascular disease