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arXiv 2021年

作者： Liu, A-Ming Guo, W. Safonova, Inna N. Skiba, Alexander N. School of Science Hainan University Haikou570228 China Department of Applied Mathematics and Computer Science Belarusian State University Minsk220030 Belarus Department of Mathematics and Technologies of Programming Francisk Skorina Gomel State University Gomel246019 Belarus

Let F be a class of group and G a finite group. Then a set Σ of subgroups of G is called a G-covering subgroup system for the class F if G ∈ F whenever Σ ⊆ F. We prove that: If a set of subgroups Σ of G contains at least one supplement to each maximal subgroup of every Sylow subgroup of G, then Σ is a G-covering subgroup system for the classes of all σ-soluble and all σ-nilpotent groups, and for the class of all σ-soluble P σT -groups. This result gives positive answers to questions 19.87 and 19.88 from the Kourovka *** Codes 20D10 © 2021, CC BY.

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A multiobjective multi-item inventory control problem in fuzzy-rough environment using soft computing techniques

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Advances in Decision Sciences 2014年 2014卷

作者： Jana, Dipak Kumar Maity, K. Maiti, M. Roy, T.K. Department of Engineering Science Haldia Institute of Technology Haldia West Bengal 721657 India Department of Mathematics Mugberia Gangadhar Mahavidyalaya Mugberia Purba Medinipur West Bengal 721425 India Department of Applied Mathematics with Oceanology and Computer Programming Vidyasagar University Medinipur West Bengal 721 102 India Department of Mathematics Bengal Engineering and Science University Shibpur Howrah West Bengal 711103 India

The optimal production and advertising policies for an inventory control system of multi-item multiobjective problem under a single management are formulated as an optimal control problem with resource constraints under inflation and discounting in fuzzy rough (Fu-Ro) environment. The objectives and constraints in Fu-Ro are made deterministic using fuzzy rough expected values method (EVM). Here, the production and advertisement rates are unknown and considered as control (decision) variables. The production, advertisement, and demand rates are functions of time t. Maximization of the total proceed from perfect and imperfect units and minimization of the total cost consisting of production, holding, and advertisement costs are formulated as optimal control problems and solved directly using multiobjective genetic algorithm (MOGA). In another method for solution, membership functions of the objectives are derived and the multi-objective problems are transformed to a single objective by the convex combination of the membership functions and then the problem is solved by generalized reduced gradient (GRG) method. Finally, numerical experiment and graphical representation are provided to illustrate the system. © 2014 Dipak Kumar Jana et al.

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Fuzzy vs neural network models for environmental decision support system implementation aiming to standardise the multiparametric decision in a Drinking Water Plant with Electrodialysis Reversal 8

Fuzzy vs neural network models for environmental decision su...

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8th International Congress on Environmental Modelling and Software - Environmental Modelling and Software for Supporting a Sustainable Future, iEMSs 2016

作者： Dalmau, Montse Monclús, Hèctor Espasa, Joan Atanasova, Natasa Poch, Manel Emiliano, Pere Capdevila, Oriol González, Santiago Valero, Fernando Institute of the Environment University of Girona Girona CataloniaE-17003 Spain Logic and Programming Research Group Department of Computer Science Applied Mathematics and Statistics University of Girona Girona CataloniaE-17003 Spain ATLL-Concessionària de la Generalitat de Catalunya Sant Martí de l'Erm 30 Sant Joan Despí Barcelona CataloniaE08970 Spain

ISBN: (纸本)9788890357459

The development of an environmental decision support system (EDSS) by means of two different aims to support the operators' decisions in the drinking water treatment plant (DWTP), equipped with the biggest electrodialysis reversal (EDR) in the world. A fuzzy artificial neural network (ANN) modelling and adaptive network-based fuzzy inference system (ANFIS) have been compared for optimizing the decision: how to manage water blending ratios from EDR and conventional treatment of the drinking water plant, evaluating Llobregat River characteristics (inlet DWTP), current operating conditions of DWTP, weather conditions and distribution requirements on-line. This tool has been tested among 4,5 months in the facility, showing better tendencies regarding the ANFIS model in comparison to the ANN model. A further application of the ANN and ANFIS process models, tested and validated, will be integrated into a process-controlled architecture of the EDSS. © 2016 Environmental Modelling and Software for Supporting a Sustainable Future, Proceedings - 8th International Congress on Environmental Modelling and Software, iEMSs 2016. All rights reserved.

关键词： Fuzzy inference

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Speaker's Emotions Recognition Module Based on the GoogleLeNet Neural Network

Speaker's Emotions Recognition Module Based on the GoogleLeN...

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2022 International Conference on Smart Information Systems and Technologies, SIST 2022

作者： Tereikovskyi, Ihor Tereikovska, Liudmyla Kryvoruchko, Olena Tereikovskyi, Oleh Tyshchenko, Dmytro Franchuk, Tamara National Technical University Of Ukraine Igor Sikorsky Kyiv Polytechnic Institute Dept. Of System Programming And Specialized Computer Systems Kyiv Ukraine Kyiv National University Of Construction And Architecture Dept. Of Information Technology For Design And Applied Mathematics Kyiv Ukraine Kyiv National University Of Trade And Economics Dept. Of Software Engineering And Cyber Security Kyiv Ukraine National Technical University Of Ukraine Igor Sikorsky Kyiv Polytechnic Institute Dept. Of Department Of Computer Engineering Kyiv Ukraine

ISBN: (数字)9781665467902

ISBN: (纸本)9781665467902

The article is devoted to the development of means for recognition of the emotions of the speaker, based on the neural network analysis of fixed fragments of the voice signal. The possibility of improving recognition tools through the use of a convolutional neural network of the GoogLeNet type is shown. The expediency of training the network on the examples of the TESS database is determined. A procedure for representing a voice signal in the form of a square grayscale image has been developed. Based on the use of the specified database, the modification of the GoogLeNet network was carried out. The architecture and software implementation of the recognition module have been developed. With the help of computer experiments, it has been established that after 150 epochs of training on a fairly limited training sample, the modified GoogLeNet makes it possible to achieve an accuracy of recognition of the speaker's emotions of approximately 0.97 on test examples. The obtained accuracy is comparable to the accuracy of the best modern systems of this purpose and confirms the promise of using neural network models like GoogLeNet for emotion recognition based on voice signal analysis. The need for further research aimed at reducing the resource intensity of the neural network model is shown. © 2022 IEEE.

关键词： Emotion Recognition

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Location–allocation problem for green efficient two-stage vehicle-based logistics system: A type-2 neutrosophic multi-objective modeling approach

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Expert Systems with Applications 2024年 238卷

作者： Das, Soumen Kumar Yu, Vincent F. Roy, Sankar Kumar Weber, Gerhard Wilhelm Department of Pure and Applied Sciences Midnapore City College Kuturia West Bengal Bhadutala721129 India Department of Applied Mathematics with Oceanology and Computer Programming Vidyasagar University West Bengal Midnapore721102 India Department of Industrial Management National Taiwan University of Science and Technology Taipei Taiwan Center for Cyber-Physical System Innovation National Taiwan University of Science and Technology Taipei Taiwan Faculty of Engineering Management Poznan University of Technology Poznan Poland IAM METU Ankara Turkey

In recent decades, global climate change has become one of the most critical environmental issues, leading to increased environmental and social concerns about the sustainability of logistics networks. This study proposes a novel multi-objective, multi-facility location–allocation model for a two-stage solid logistics network that supports green practices. To account for uncertainty in real-world problems, some parameters of the model are represented as triangular type-2 neutrosophic numbers to deal with hesitant situations. The fuzzy model is then converted into a deterministic one using a new ranking approach. Three conflicting objective functions – minimizing total financial costs, maximizing customers’ satisfaction levels, and ensuring sustainable and effective conveyances – are simultaneously optimized using the ϵ-constraint approach. The proposed model and solution approach are tested with two numerical examples. A comparative study is also presented, comparing the proposed approach with other Pareto-based multi-objective approaches, such as the global criterion approach, multi-objective fuzzy programming, and weighted Chebychev programming. Finally, the paper concludes with some remarks. © 2023

关键词： Sustainable development

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Correction to: Multi-item two-stage fixed-charge 4DTP with hybrid random type-2 fuzzy variable

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Soft Computing 2021年第1期26卷 463-463页

作者： Devnath, Sudeshna Giri, Pravash Kumar Mondal, Seema Sarkar Maiti, Manoranjan Department of Mathematics National Institute of Technology Durgapur Durgapur India Department of Mathematics Government General Degree College Kashmuli India Department of Applied Mathematics with Oceanology and Computer Programming Vidyasagar University Midnapore India

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Sports programming as a Tool for Regional Development of the Digital Industry and Higher Education

Sports Programming as a Tool for Regional Development of the...

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Technology Enhanced Learning in Higher Education (TELE), International Conference on

作者： Alexander Galkin Artem Miroshnikov Daniil Sapronov Elena Skarzhinskaya Faculty of Automation and Computer Science Lipetsk State Technical University Lipetsk Russia Department of Applied Mathematics Lipetsk State Technical University Lipetsk Russia Lipetsk branch of the Russian Federation of Sports Programming Lipetsk Russia Department of Cybersport Moscow Financial and Industrial University “Synergy” Moscow Russia

ISBN: (数字)9798350353532

ISBN: (纸本)9798350353549

Abstract-The article presents the history of the development of sports programming as a sport in Russia. The main stages of the formation of the legislative basis for this sport are given. The rationale and description of the process of training athletes in higher education institutions are given - possible traj ectories in the disciplines of “algorithmic programming” and “product programming”, the influence of the development of sports programming on improving the quality of IT education. As an example, the organization of training students in the discipline of “algorithmic programming” at the Lipetsk State Technical University is given. The activities of the Lipetsk regional branch of the All- Russian Sports Federation to popularize this sport including among students are also described.

关键词： Training Industries Organizations History programming profession Sports

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Correction to: Fully fuzzy multi-item two-stage fixed charge four-dimensional transportation problems with flexible constraints

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Granular Computing 2021年第4期7卷 799-799页

作者： Devnath, Sudeshna Giri, Pravash Kumar Sarkar Mondal, Seema Maiti, Manoranjan Department of Mathematics National Institute of Technology Durgapur Durgapur India Department of Mathematics Government General Degree College Dantan-II Kashmuli India Department of Applied Mathematics with Oceanology and Computer Programming Vidyasagar University Midnapore India

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Thank You to Our Peer Reviewers in 2024

Journal of Geophysical Research: Machine Learning and Comput...

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Journal of Geophysical Research: Machine Learning and Computation 2025年第1期2卷

作者： Enrico Camporeale Raffaele Marino Thomas Berger Yangkang Chen Doris Folini Geoffrey Fox Xiaofeng Li Donald Lucas Steve Tobias Markus Reichstein John Rundle Chaopeng Shen Renata Wentzcovitch Yixin Wen School of Physical and Chemical Sciences Queen Mary University of London London UK Space Weather Technology Research and Education Center University of Colorado Boulder Boulder CO USA Laboratoire de Mécanique des Fluides et d'Acoustique CNRS - École Centrale de Lyon Écully France Jackson School of Geosciences The University of Texas at Austin Austin TX USA ETH Zurich Institute for Atmospheric and Climate Science Zurich Switzerland Department of Computer Science Biocomplexity Institute University of Virginia Charlottesville VA USA Chinese Academy of Sciences Institute of Oceanology Qingdao China Lawrence Livermore National Laboratory Livermore CA USA Department of Applied Mathematics University of Leeds Leeds UK Max-Planck-Institute for Biogeochemistry Jena Germany Department of Physics and Astronomy University of California – Davis Davis CA USA Department of Civil and Environmental Engineering The Pennsylvania State University University Park PA USA Department of Earth and Environmental Sciences Columbia University New York NY USA Lamont Doherty Earth Observatory Columbia University Palisades NY USA Department of Geography University of Florida Gainesville FL USA

On behalf of AGU, the scientific community, and the editorial team of Journal of Geophysical Research: Machine Learning and Computation, we extend our sincere gratitude to the reviewers who dedicated their time and expertise to evaluating manuscripts for us in 2024. Scientific research can now be communicated in various ways, yet peer review remains the cornerstone of scholarly publishing. We deeply appreciate the reviewers who devoted hours to reading and providing insightful feedback. The high quality of our published papers is a testament to their commitment to this vital community service. The editors thank the 2024 peer reviewers In 2024, we received 368 submissions, with 518 reviewers contributing a total of 885 reviews. These numbers have exceeded our expectations, reflecting the scientific community's trust in our newly established journal and the significance of this editorial initiative. We are truly grateful for this support and, as an editorial board, remain committed to upholding the highest standards in our future publications.

关键词： editorial peer review

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Minimum 2-Tuple Dominating Set of an Interval Graph

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International Journal of Combinatorics 2011年第1期2011卷

作者： Tarasankar Pramanik Sukumar Mondal Madhumangal Pal Department of Applied Mathematics with Oceanology and Computer Programming Vidyasagar University Midnapore 721102 Indiavidyasagar.ac.in Department of Mathematics Raja N. L. Khan Women′s College Vidyasagar University Midnapore 721102 India

The k -tuple domination problem, for a fixed positive integer k , is to find a minimum size vertex subset such that every vertex in the graph is dominated by at least k vertices in this set. The case when k = 2 is called 2-tuple domination problem or double domination problem. In this paper, the 2-tuple domination problem is studied on interval graphs from an algorithmic point of view, which takes O ( n 2 ) time, n is the total number of vertices of the interval graph.

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