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Double-averaged Turbulence Characteristics Over Hemispherical Rough Bed 1

26th International Conference on Hydraulics, Water Resources and Coastal Engineering, HYDRO 2021

作者： Shounda, Jaynata Barman, Krishnendu Department of Applied Mathematics With Oceanology and Computer Programming Vidyasagar University West Bengal Midnapore721102 India

ISBN: (数字)9789811991516

ISBN: (纸本)9789811991509

This study characterized the double-averaged (time and space) turbulence parameters and local flow distributions through the experimental measurement over fully submerged artificially made hemispherical rough bed. Three different directional components of velocity data were collected by 3D micro-acoustic Doppler velocimeter (ADV) with a Reynolds number 62000. The changes of spatially averaged mean velocity profiles into specific flow layers on this rough bed were discussed corresponding with the smooth bed data. In the bottom wall region, double-averaged negative velocity components indicate the flow separation and strong recirculation zone. However, results from the double-averaged turbulent-kinetic-energy (TKE) flux and form-induced TKE flux were shown the upward and downward TKE transport throughout the flow depth. Also, TKE budgets terms turbulence production, diffusion and dissipation attain their peaks at the interfacial sub-layer of this rough bed flow. The production and dissipation rates of TKE have reached their maximum points at just above the lower extremity of form-induced sub-layer and within the interfacial sub-layer, respectively. The interfacial sub-layer has been treated as the losing zone of TKE pressure energy distribution and the zone of turbulence spreading. Moreover, the lower boundary of form-induced sub-layer shows as the energy access region. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Turbulence

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Pricing Policy with the Effect of Fairness Concern, Imprecise Greenness, and Prices in Imprecise Market for a Dual Channel

Pricing Policy with the Effect of Fairness Concern, Imprecis...

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International Conference on Nonlinear Applied Analysis and Optimization, ICNAAO-2021

作者： Ganguly, Sanchari Das, Pritha Maiti, Manoranjan Department of Mathematics Indian Institute of Engineering Science and Technology Shibpur WB Howrah711103 India Department of Applied Mathematics Oceanology and Computer Programming Vidyasagar University WB Midnapore721102 India

ISBN: (纸本)9789819905966

Fairness concern behavior, a well-known cognitive bias, refers to a person’s attitude of dissatisfaction for unequal pay-offs in someone’s favor. Against environmental pollution, many firms are focused on green manufacturing to maintain sustainable development. The adoption of online shopping by customers around the globe has altered the dynamics of competitiveness in the retail supply chain (SC). Considering the above facts, the effect of fairness concern on optimal prices and channel members’ profits in a two-level dual channel SC is investigated. Here, we consider an SC comprising a green manufacturer and a fair-minded retailer where the manufacturer produces and sells the green product through both offline and online channels to consumers. Due to uncertainty in the real world, the fuzziness is associated with market demand, price elasticity, and the coefficient of greenness. The fuzzy objectives and constraints are reduced to crisp ones using expectation and possibility measures, respectively. Both centralized and decentralized models (with and without cognitive bias) are formulated and solved by the Stackelberg game for the optimal prices and product greenness level. The models’ optimal solutions are analyzed and compared with the deterministic models numerically. The effects of the fairness concern coefficient on the optimal prices, product greenness level, and channel members’ profits are investigated. The sensitivity analyses are presented to study the effects of the fuzzy degree of customers’ sensitivity toward greenness on channel members’ profits. Retailer’s fairness is harmful to the manufacturer but beneficial for her own profit. Finally, some conclusions and managerial insights are presented. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Game theory

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Soft Matrix Game: A Hesitant Fuzzy MCDM Approach

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American Journal of Mathematical and Management Sciences 2021年第2期40卷 107-119页

作者： Jana, Jishu Kumar Roy, Sankar Department of Applied Mathematics with Oceanology and Computer Programming Vidyasagar University MidnaporeWest Bengal India

Soft set theory has emerged recently as a new mathematical tool to handle uncertainty. Sometimes decision makers are not sure about the decision-making criteria, where soft set theory provides an idea to deal with such uncertainties. Multi-criteria decision making (MCDM) involves choosing the best from several alternatives. MCDM methods such as TOPSIS and VIKOR depend on an aggregating function for presenting "closeness to the ideal" which arises due to the compromise solution. The VIKOR method of compromise ranking describes a compromise solution, providing a maximum for the "maximizing player" and minimum for the "opponent", which is an effective approach in an MCDM game. TOPSIS method presents a solution with the shortest distance to the positive ideal solution (PIS) and largest distance from the negative ideal solution (NIS). Also, hesitant fuzzy soft set is an appropriate tool to tackle the imprecise parameters introduced in MCDM problems by the decision maker (DM). In this paper, we extend the VIKOR and TOPSIS methods for solving MCDM game problems with hesitant fuzzy soft payoffs to determine the optimal strategies. Finally, a numerical example is incorporated to verify the extended VIKOR approach and the results are compared with those for the TOPSIS method. The paper ends with conclusions and outlooks. © 2020 Taylor & Francis Group, LLC.

关键词： Numerical methods

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Sustainable Manufacturing Model with Considering Greenhouse Gas Emission and Screening Process of Imperfect Items Under Stochastic Environment

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International Journal of Applied and Computational mathematics 2022年第3期8卷 1-21页

作者： Dolai, Madhusudan Manna, Amalesh Kumar Mondal, Shyamal Kumar Department of Applied Mathematics with Oceanology and Computer Programming Vidyasagar University West Bengal Midnapore 721102 India Department of Mathematics C. V. Raman Global University Bhubaneswar 752054 India

In this work, a production model with screening of imperfect product and green house gas emission has been developed. Here, it has been considered that the manufacturing process transfer from in-control situation to out-of-control situation after an uncertain time, which is a random variable. In the out-of-control situation, a part of produced items are imperfect. For this reason, the manufacturer decides to check each item through screening process before sale the perfect items to the market. The screening and production rates are not equal and new type of screening process has been considered here. The imperfect rate depends on the length of out-of-control situation and its random nature. Also, the manufacturer sales the imperfect items by reducing the selling price. The greenhouse gas (GHG) emission tax has been considered here and its rate depends on the production rate. The objective of this study is to find the optimal business and production period, optimal production rate which maximizes the expected average profit of the model. Two numerical examples have been considered to illustrate the feasibility of the model. Finally, the sensitivity analysis have been carried out to get the effect of some important parameters on the optimization problem related to the proposed model. © 2022, The Author(s), under exclusive licence to Springer Nature India Private Limited.

关键词： Greenhouse gas emission Imperfect production Price discount Screening

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α-Reliable Shortest Path Problem in Uncertain Time-Dependent Networks

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International Journal of Applied and Computational mathematics 2022年第4期8卷 1-12页

作者： Biswal, Sagarika Ghorai, Ganesh Mohanty, S.P. Department of Mathematics Nimapara Autonomous College Nimapara Puri 752106 India Department of Applied Mathematics With Oceanology and Computer Programming Vidyasagar University West Bengal Midnapore 721102 India Department of Mathematics Siksha ‘O’ Anusandhan University (SOA) Bhubaneswar 751030 India

In a congested road network, it is always desirable to find a reliable shortest path so far as travel time is concerned. Physical distance and travel time are invariably uncertain due to large-scale maintenance work, natural disaster, heavy accident, weather conditions, etc. Many researchers considered travel time to be stochastic where the Bellman’s principle of optimality is not preserved. Also, any sub-path of a shortest path is not necessarily shortest. Some researchers find non-dominated paths under different variants as a multi-objective optimization problem. Moreover, in the absence of sample data, probability theory cannot be used. In this work, the travel time is considered to be uncertain variable, where no sample data is required and it is established that Bellman’s principle of optimality is preserved. So, in contrast to the stochastic environment, classical dynamic approach can be used to find the α-reliable shortest path using uncertainty theory. © 2022, The Author(s), under exclusive licence to Springer Nature India Private Limited.

关键词： Dijkstra’s algorithm Non-dominated path Pre-trip planning Reliable shortest path Travel time Uncertain variable

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A Comprehensive Study on m-Polar Picture Fuzzy Graphs and Its Application

Journal of Uncertain Systems

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Journal of Uncertain Systems 2025年第1期18卷

作者： Khatun, Jasminara Amanathulla, S. Pal, Madhumangal Department of Applied Mathematics with Oceanology and Computer Programming Vidyasagar University Midnapore 721102 India Department of Mathematics Raghunathpur College Raghunathpur 723133 India

In real-life problems, information collected from multiple agents often exhibits "multipolar information," which cannot be accurately modeled by existing graph models. This paper introduces the m-polar picture fuzzy graph (mPPFG) as a more efficient model for such problems. The mPPFG offers a precise, flexible and comparable system compared to other graph models. The paper defines the mPPFG model and introduces new terms and properties such as order, degree, weighted arithmetic average (WAA) order, WAA degree, complement, homomorphism, isomorphism, eccentricity, radius, diameter and more. It also explores the concepts of m-polar antipodal picture fuzzy graphs, eccentric mPPFG, self-centered mPPFG and self-median mPPFG, highlighting their definitions and properties. The m-polar antipodal picture fuzzy graph represents a graph where each vertex is associated with an m-polar antipodal picture fuzzy set. The eccentric mPPFG focuses on highly eccentric vertices, while the self-centered mPPFG considers central vertices. The self-median mPPFG represents median vertices in the graph. The study of these graph types and their isomorphism properties contributes to a deeper understanding of the structural variations within mPPFGs. Furthermore, the paper proposes an application of the mPPFG model in evaluating the performance of ministers in India during their tenure. An algorithm is also developed for computing the performance of ministers. © 2024 World Scientific. All rights reserved.

关键词： complement diameter isomorphism m-polar antipodal PFG mPPFG Picture fuzzy graphs

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Quadripartitioned Neutrosophic Graph Structures

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Neutrosophic Sets and Systems 2022年 51卷 269-294页

作者： Hussain, S. Satham Rashmonlou, Hossein Mofidnakhaei, F. Hussain, R Jahir Sahoo, Sankar Broumi, Said PG & Research Department of Mathematics Jamal Mohamed College Tamilnadu Trichy India Department of Mathematics University of Mazandarn Babolsar Iran Department of Physics Sari Branch Islamic Azad University Sari Iran Department of Applied Mathematics with Oceanology and Computer Programming Vidyasagar University Midnapore India Laboratory of Information Processing Faculty of Science Ben M’Sik University Hassan II Casablanca Morocco

The quadripartitioned neutrosophic set is the partition of indeterminacy function of the neutrosophic set into contradiction part and ignorance part. In this work, the concept of quadripartitioned neutrosophic graph structures and its properties are invented. The strong, tree, Φ − permutation and Φ − complement of quadripartitioned neutrosophic graph structure are investigated. The operations like Cartesian Product, cross product, lexicographic product, composition in graph structures and join operations are established. © 2022, Neutrosophic Sets and Systems. All Rights Reserved.

关键词： Graphic methods

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Bi-level programming for Stackelberg Game with Intuitionistic Fuzzy Number: a Ranking Approach

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Journal of the Operations Research Society of China 2021年第1期9卷 131-149页

作者： Sumit Kumar Maiti Sankar Kumar Roy School of Applied Sciences and Humanities Haldia Institute of TechnologyPurba MidnaporeWB 721657India Department of Applied Mathematics with Oceanology and Computer ProgrammingVidyasagar UniversityMidnaporeWB 721102India

This paper introduces a ranking function procedure on a bi-level programming for Stackelberg game involving intuitionistic fuzzy *** fuzzy num-ber is considered in many real-life situations,so it makes perfect sense to address decision-making problem by using some specified intuitionistic fuzzy *** this paper,intuitionistic fuzziness is characterized by a normal generalized triangular intuitionistic fuzzy number.A defuzzification method is introduced based on the pro-portional probability density function associated with the corresponding membership function,as well as the complement of non-membership *** the proposed ranking technique,a methodology is presented for solving bi-level programming for Stackelberg *** application example is provided to demonstrate the applica-bility of the proposed methodology,and the achieved results are compared with the existing methods.

关键词： Bi-levelprogramming Triangular intuitionistic fuzz ynumber Ranking function Nonlinear programming Optimal solution

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Two-Level Supply Chain Inventory Model for Perishable Goods with Fuzzy Lead-Time and Shortages

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International Journal of Applied and Computational mathematics 2021年第5期7卷 1-18页

作者： Mallick, Rabin Kumar Manna, Amalesh Kumar Shaikh, Ali Akbar Mondal, Shyamal Kumar Department of Applied Mathematics With Oceanology and Computer Programming Vidyasagar University Midnapore 721102 West Bengal India Department of Mathematics The University of Burdwan Burdwan 713104 India

This study deals with a supplier-retailer supply chain system for perishable goods under fuzzy lead-time and fully backlogged shortages. In this proposed model, a supplier collects the deteriorating goods and fulfills the retailer's demand. Also, two different cases are considered. In the first case, retailer's fully backlogged shortages are incorporated whereas in the second case, retailer's shortages are not allowed. Lead-time of the system is considered as fuzzy in nature. In the first case, the integrated average profit of the supply chain system is obtained in fuzzy nature and the centroid method is used for defuzzification. The aim of this study is to maximize the integrated average profit by optimizing retailer's reorder level and business period. Three numerical examples are considered and solved for justification of the proposed model. Finally, the sensitivity analyses are performed with respect to the values of different system parameters. © 2021, The Author(s), under exclusive licence to Springer Nature India Private Limited.

关键词： Fuzzy lead-time Perishable goods Shortages Supply chain

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Analyzing the impact of machine learning and artificial intelligence and its effect on management of lung cancer detection in covid-19 pandemic

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Materials Today: Proceedings 2022年 56卷 2213-2216页

作者： Boddu, Raja Sarath Kumar Karmakar, Partha Bhaumik, Ankan Nassa, Vinay Kumar Vandana Bhattacharya, Sumanta Department of CSE Lenora College of Engineering Andhra Pradesh Rampachodavaram India Government of West Bengal Bikash Bhawan Salt Lake W.B. Kolkata India Dept. of Applied Mathematics With Oceanology and Computer Programming Vidyasagar University Midnapore India Department of Computer Science Engineering South Point Group of Institutions Sonepat Haryana India Department of Mathematics Dasmesh Khalsa College Zirakpur India Department of Science and Technology and Biotechnology MAKAUT India

Cancer victims, particularly those with lung cancer, are more susceptible and at higher danger of COVID-19 and associated consequences as a result of their compromised immune systems, which makes them particularly sensitive. Because of a variety of circumstances, cancer patients' diagnosis, treatment, and aftercare are very complicated and time-consuming during an epidemic. In such circumstances, advances in artificial intelligence (AI) and machine learning algorithms (ML) offer the capacity to boost cancer sufferer diagnosis, therapy, and care via the use of cutting technologies. For example, using clinical and imaging data combined with machine learning methods, the researchers may be able to distinguish among lung alterations induced by corona virus and those produced by immunotherapy and radiation. During this epidemic, artificial intelligence (AI) may be utilized to guarantee that the appropriate individuals are recruited in cancer clinical trials more quickly and effectively than in the past, which was done in a conventional and complicated manner. In order to better care for cancer patients and find novel and more effective therapies, It is critical that we move beyond traditional research methods and use artificial intelligence (AI) and machine learning to update our research (ML). Artificial intelligence (AI) and machine learning (ML) are being utilised to help with several aspects of the COVID-19 epidemic, such as epidemiology, molecular research and medication development, medical diagnosis and treatment, and socioeconomics. The use of artificial intelligence (AI) and machine learning (ML) in the diagnosis and treatment of COVID-19 patients is also being investigated. The combination of artificial intelligence and machine learning in COVID-19 may help to identify positive patients more quickly. In order to understand the dynamics of an epidemic that is relevant to artificial intelligence, when used in different patient groups, AI-based algorithms can quic

关键词： COVID-19

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