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Multi-attribute Group Decision-making Based on Hesitant Bipolar-valued Fuzzy Information and Social Network

computer Systems Science & engineering 2023年第3期44卷 1939-1950页

作者： Dhanalakshmi R Sovan Samanta Arun Kumar Sivaraman Jeong Gon Lee Balasundaram A Sanamdikar Sanjay Tanaji Priya Ravindran Department of Computer Science and Engineering KCG College of TechnologyChennai600097Tamil NaduIndia Department of Mathematics Tamralipta MahavidyalayaWest Bengal721636India School of Computer Science and Engineering Vellore Institute of TechnologyChennai600127Tamil NaduIndia Division of Applied Mathematics Wonkwang UniversityIksan-SiJeonbuk54538Korea School of Computer Science and Engineering Center for Cyber Physical SystemsVellore Institute of TechnologyChennai600127Tamil NaduIndia Department of Instrumentation Engineering PDEAs College of EngineeringManjari412307PuneIndia Engineering and Research Services HCL TechnologiesChennai600119India

Fuzzy sets have undergone several expansions and generalisations in the literature,including Atanasov’s intuitionistic fuzzy sets,type 2 fuzzy sets,and fuzzy multisets,to name a *** can be regarded as fuzzy multisets from a formal standpoint;nevertheless,their interpretation differs from the two other approaches to fuzzy multisets that are currently *** fuzzy sets(HFS)are very useful if consultants have hesitation in dealing with group decision-making problems between several possible ***,these possible memberships can be not only crisp values in[0,1],but also interval values during a practical evaluation *** bipolar valued fuzzy set(HBVFS)is a generalization of *** paper aims to introduce a general framework of multi-attribute group decision-making using social *** propose two types of decision-making processes:Type-1 decision-making process and Type-2 decision-making *** the Type-1 decision-making process,the experts’original opinion is proces for thefinal ranking of *** Type-2 decision making processs,there are two major aspects we ***,consistency tests and checking of consensus models are given for detecting that the judgments are logically ***,the framework demands(partial)decision-makers to review their ***,the coherence and consensus of several HBVFSs are established forfinal ranking of *** proposed framework is clarified by an example of software packages selection of a university.

关键词： Group decision-making aggregation operators hesitant bipolar-valued fuzzy set

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Semantic and spatial‐spectral feature fusion transformer network for the classification of hyperspectral image

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CAAI Transactions on Intelligence Technology 2023年第4期8卷 1308-1322页

作者： Erxin Xie Na Chen Jiangtao Peng Weiwei Sun Qian Du Xinge You Hubei Key Laboratory of Applied Mathematics Faculty of Mathematics and StatisticsHubei UniversityWuhanChina Department of Geography and Spatial Information Techniques Ningbo UniversityNingboChina Department of Electrical and Computer Engineering Mississippi State UniversityMississippi StateMississippiUSA School of Electronic Information and Communications Huazhong University of Science and TechnologyWuhanChina

Recently,transformer‐based networks have been introduced for the classification of hyperspectral image(HSI).Although transformer‐based methods can well capture spectral sequence information,their ability to fuse different types of information contained in HSI is still *** exploit rich spectral,spatial and semantic information in HSI,a novel semantic and spatial‐spectral feature fusion transformer(S3FFT)network is proposed in this *** the proposed S3FFT method,spatial attention and efficient channel attention(ECA)modules are employed for the extraction of shallow spatialspectral ***,a transformer‐based module is designed to extract advanced fused features and to produce the pseudo‐label and class probability of each pixel for semantic feature ***,the semantic,spatial and spectral features are combined by the transformer for *** with traditional deep learning methods and recently transformer‐based methods,the proposed S3FFT shows relatively better results on three HSI datasets.

关键词： image classification machine learning

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Delayed excitatory self-feedback-induced negative responses of complex neuronal bursting patterns

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Chinese Physics B 2021年第5期30卷 236-246页

作者： Ben Cao Huaguang Gu Yuye Li School of Aerospace Engineering and Applied Mechanics Tongji UniversityShanghai 200092China College of Mathematics and Computer Science Chifeng UniversityChifeng 024000China Institute of Applied Mathematics Chifeng UniversityChifeng 024000China

In traditional viewpoint,excitatory modulation always promotes neural firing *** contrary,the negative responses of complex bursting behaviors to excitatory self-feedback mediated by autapse with time delay are acquired in the present *** representative bursting patterns which are identified respectively to be“Fold/Big Homoclinic”bursting and“Circle/Fold cycle”bursting with bifurcations are *** both burstings,excitatory modulation can induce less spikes per burst for suitable time delay and strength of the self-feedback/autapse,because the modulation can change the initial or termination phases of the *** the former bursting composed of quiescent state and burst,the mean firing frequency exhibits increase,due to that the quiescent state becomes much shorter than the ***,for the latter bursting pattern with more complex behavior which is depolarization block lying between burst and quiescent state,the firing frequency manifests decrease in a wide range of time delay and strength,because the duration of both depolarization block and quiescent state becomes ***,the decrease degree of spike number per burst is larger than that of the bursting period,which is the cause for the decrease of firing *** reduced bursting activity is explained with the relations between the bifurcation points of the fast subsystem and the bursting *** present paper provides novel examples of paradoxical phenomenon that the excitatory effect induces negative responses,which presents possible novel modulation measures and potential functions of excitatory self-feedback/autapse to reduce bursting activities.

关键词： bifurcation bursting excitatory autapse time delay

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Green Algorithms for Energy-Efficient Distributed Flow-Shop Manufacturing Problem

Green Algorithms for Energy-Efficient Distributed Flow-Shop ...

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2023 International Symposium on Green Technologies and Applications, ISGTA 2023

作者： Sayah, Achraf Aqil, Said Lahby, Mohamed Laboratory of Applied Mathematics and Computer Sciences Higher Normal School Hassan II University of Casablanca Morocco Laboratory of Artificial Intelligence and Complex Systems Engineering National Higher School of Arts And Crafts Hassan II University of Casablanca Morocco

Minimizing energy consumption is one of the most interesting issues in recent industrial production. Energy-efficient scheduling is a promising approach to reducing energy consumption in manufacturing systems. However, energy-efficient scheduling is a problem of great interest, especially for the Distributed permutation Flow-Shop Manufacturing Problem (DPFSMP). This paper addresses the critical challenge of energy efficiency in the industry of DPFSMP optimization, where task processing times depend closely on their position in the production line. The objective is to minimize the total energy consumption (TEC) for all machines in distributed workshops. To solve this problem, we propose two efficient constructive algorithms for energy-efficient scheduling of this type of problem with speed-dependent tasks: the Nawaz Enscore and Ham (NEH) based algorithm and the Greedy Random Adaptive Search Procedure (GRASP) based algorithm. We evaluate the performance of the two proposed algorithms on a set of benchmark problems to identify the one with the best performance. The results show that the (NEH) algorithm outperforms the GRASP algorithm in terms of energy efficiency and solution quality. In fact, the proposed algorithms can be used by manufacturers to reduce energy consumption in their production systems. This can help manufacturers save money, reduce environmental impact and improve overall sustainability. © 2024 The Authors. Published by ELSEVIER B.V.

关键词： Energy utilization

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Enhancing Deep Reinforcement Learning with Scenario-Based Modeling

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SN computer Science 2023年第2期4卷 1-13页

作者： Yerushalmi, Raz Amir, Guy Elyasaf, Achiya Harel, David Katz, Guy Marron, Assaf Department of Computer Science and Applied Mathematics Weizmann Institute of Science Rehovot 76100 Israel School of Computer Science and Engineering The Hebrew University of Jerusalem Jerusalem 91904 Israel Software and Information Systems Engineering Ben-Gurion University of the Negev Beer-Sheva 8410501 Israel

Deep reinforcement learning agents have achieved unprecedented results when learning to generalize from unstructured data. However, the “black-box” nature of the trained DRL agents makes it difficult to ensure that they adhere to various requirements posed by engineers. In this work, we put forth a novel technique for enhancing the reinforcement learning training loop, and specifically—its reward function, in a way that allows engineers to directly inject their expert knowledge into the training process. This allows us to make the trained agent adhere to multiple constraints of interest. Moreover, using scenario-based modeling techniques, our method allows users to formulate the defined constraints using advanced, well-established, behavioral modeling methods. This combination of such modeling methods together with ML learning tools produces agents that are both high performing and more likely to adhere to prescribed constraints. Furthermore, the resulting agents are more transparent and hence more maintainable. We demonstrate our technique by evaluating it on a case study from the domain of internet congestion control, and present promising results. © 2023, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.

关键词： Deep reinforcement learning Domain expertise Machine learning Rule-based specifications Scenario-based modeling

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Use of Polygram Substitution in Spotting the Swindler in Secret Sharing 11th

Use of Polygram Substitution in Spotting the Swindler in Sec...

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11th International Conference on Intelligent Computing and Applications, ICRTC 2023

作者： Yadav, Poonam Satheesh Kumar, S. Muthukumaran, V. Sandeep Kumar, Mathivanan Radhika, E.K. Department of Computer Science School of Applied Sciences Reva University Bangalore India Department of Mathematics College of Engineering and Technology SRM Institute of Science and Technology Tamil Nadu Kattankulathur 603203 India School of Computer Science and Engineering Galgotias University Uttar Pradesh Greater Noida203201 India Department of Computer Science and Applications Sindhi College Bangalore560024 India

ISBN: (纸本)9789819717231

In the polygram substitution, one set of characters is replaced by another set based on algorithm. The model is proposed for calculating and estimating secure online secret shares, where dynamic modification in any of the shares will be identified if number of the shares are more than specified threshold value. The security is based on the intractability of factoring as it uses Lagrange polynomial function. This is further enhanced by a graphical masking and unmasking technique;it includes two phases: encryption of the individual secrets and sharing of the data. The generation of the shares is done by masking using Polygram substitution, and the shares are regenerated and unmasking of the qualified shares is done to find original secret. Masking is done on original secret, then shares are generated. Each encrypted share contains information which is different than original secret. Masking by Polygram substitution gives additional protection of secret data on the Internet. Moreover, we achieve efficient recovery of the original secret data. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Polynomials

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The Role of Predictive Maintenance Optimization Techniques in Enhancing Industrial Productivity 10

The Role of Predictive Maintenance Optimization Techniques i...

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10th International Conference on Optimization and Applications, ICOA 2024

作者： Er-Ratby, Mohamed Kobi, Abdessamad Sadraoui, Youssef Kadiri, Moulay Saddik National School of Applied Sciences Sultan Moulay Slimane University LASTI Laboratory of Science and Engineering Techniques Khouribga Morocco Polytech Angers University of Angers LARIS Angevin Laboratory for Systems Engineering Research Angers France National School of Applied Sciences Sultan Moulay Slimane University LIPIM Laboratory of Process Engineering Computer Science and Mathematics Khouribga Morocco

ISBN: (纸本)9798350387353

The convergence between advanced technology and industrial production holds significant potential to enhance operational efficiency, reduce maintenance costs, and minimize unexpected disruptions. Artificial intelligence, in particular, plays a crucial role in predicting machine failures, thereby contributing to the optimization of operational performance and maximizing overall company output. However, current challenges in maintenance and production are numerous. High maintenance costs are often a major concern for companies, as they can significantly eat into profit margins. Unexpected downtime, caused by sudden machine failures, leads to substantial production losses, affecting not only revenue but also customer satisfaction and the company's reputation. Furthermore, the increasing complexity of industrial systems makes the management of maintenance and production even more difficult, necessitating more advanced and integrated solutions. This article explores the various applications of artificial intelligence in the manufacturing industry, highlighting its impact on business performance. It also examines the steps necessary for implementing predictive maintenance, from data collection and processing to the establishment of predictive models. The ultimate goal is to improve equipment availability, optimize operational performance, and maximize overall company output. © 2024 IEEE.

关键词： Predictive maintenance

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Construction and application of high-quality genome-scale metabolic model of Zymomonas mobilis to guide rational design of microbial cell factories

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Synthetic and Systems Biotechnology 2023年第3期8卷 498-508页

作者： Yalun Wu Qianqian Yuan Yongfu Yang Defei Liu Shihui Yang Hongwu Ma State Key Laboratory of Biocatalysis and Enzyme Engineering School of Life SciencesHubei UniversityWuhan430062HubeiChina Biodesign Center Key Laboratory of Systems Microbial BiotechnologyTianjin Institute of Industrial BiotechnologyChinese Academy of SciencesTianjin300308China Hubei Key Laboratory of Applied Mathematics Faculty of Mathematics and StatisticsHubei UniversityWuhan430062HubeiChina Artificial Intelligence and Knowledge Engineering Lab School of Computer Science and Information EngineeringHubei UniversityWuhan430062HubeiChina

High-quality genome-scale metabolic models(GEMs)could play critical roles on rational design of microbial cell factories in the classical Design-Build-Test-Learn cycle of synthetic biology *** of the constant establishment and update of GEMs for model microorganisms such as Escherichia coli and Saccharomyces cerevisiae,high-quality GEMs for non-model industrial microorganisms are still *** mobilis *** ZM4 is a non-model ethanologenic microorganism with many excellent industrial characteristics that has been developing as microbial cell factories for biochemical *** five GEMs of *** have been constructed,these models are either generating ATP incorrectly,or lacking information of plasmid genes,or not providing standard format *** this study,a high-quality GEM iZM516 of *** ZM4 was *** information from the improved genome annotation,literature,datasets of Biolog Phenotype Microarray studies,and recently updated Gene-Protein-Reaction information was combined for the curation of ***,516 genes,1389 reactions,1437 metabolites,and 3 cell compartments are included in iZM516,which also had the highest MEMOTE score of 91%among all published GEMs of *** growth was then predicted by iZM516,which had 79.4%agreement with the experimental results of the substrate *** addition,the potential endogenous succinate synthesis pathway of *** ZM4 was proposed through simulation and analysis using ***,metabolic engineering strategies to produce succinate and 1,4-butanediol(1,4-BDO)were designed and then simulated under anaerobic condition using *** results indicated that 1.68 mol/mol succinate and 1.07 mol/mol 1,4-BDO can be achieved through combinational metabolic engineering strategies,which was comparable to that of the model species *** study thus not only established a high-quality GEM iZM516 to help understand and design microbial cell fac

关键词： Genome-scale metabolic models(GEMSs) Non-model industrial microorganism Zymomonas mobilis Biolog phenotype microarray Succinate 1,4-Butanediol

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A spatiotemporal datamining approach for road profile estimation using low-cost device 26

A spatiotemporal datamining approach for road profile estima...

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26th International Conference on Knowledge-Based and Intelligent Information and engineering Systems, KES 2022

作者： Taktak, Mariem Triki, Slim Higher Institute of Applied Sciences and Technologies of Sousse Department of Computer Science and Applied Mathematics Sousse Tunisia National Engineering School of Sfax Tunisia

In this paper, we address the problem of the spatiotemporal data mining in the field of the road conditions estimation. We demonstrate that road condition estimation can be defined as a problem of dynamic discovering of different classes of road profile during training phase. We focus on the road profile classification from time series data collected by a low-cost inertial sensor embedded into smartphone devices. Data used in this work are composed of three datasets which treat real asphalt pavement problems. The first, called Asphalt-obstacle, address the identification problem of obstacles in the pavement where data are collected. The second, called Asphalt pavement-type, aims at identifying three types of pavements namely flexible pavement, cobblestone street and dirt roads. The third and final dataset, called Asphalt pavement-regularity, treat the pavement quality effect on the driver comfortability. In order to estimate the road conditions, we conduct an evaluation of four spatiotemporal algorithms which combine concepts from machine learning and data-driven. With uniform parameters setting and on-line implementation property, we find that Markov spatiotemporal dynamic model achieve the best average classification accuracy of 90.5% ± 0.01 in 4-class Asphalt obstacles, 84% ± 0.006 in 3-class Asphalt pavement-type and 94.9%±0.005 in 2-class Asphalt pavement-regularity. © 2022 The Authors. Published by Elsevier B.V.

关键词： Smartphones

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Langevin Equation in Heterogeneous Landscapes: How to Choose the Interpretation

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Physical Review Letters 2024年第6期133卷 067102-067102页

作者： Adrian Pacheco-Pozo Michał Balcerek Agnieszka Wyłomanska Krzysztof Burnecki Igor M. Sokolov Diego Krapf Department of Electrical and Computer Engineering and School of Biomedical Engineering Faculty of Pure and Applied Mathematics Hugo Steinhaus Center Institut für Physik and IRIS Adlershof

The Langevin equation is a common tool to model diffusion at a single-particle level. In nonhomogeneous environments, such as aqueous two-phase systems or biological condensates with different diffusion coefficients in different phases, the solution to a Langevin equation is not unique unless the interpretation of stochastic integrals involved is selected. We analyze the diffusion of particles in such systems and evaluate the mean, the mean square displacement, and the distribution of particles, as well as the variance of the time-averaged mean-square displacements. Our analytical results provide a method to choose the interpretation parameter from single-particle tracking experiments.

关键词： Brownian motion Diffusion Random walks Stochastic processes Liquid-liquid interfaces Langevin equation Stochastic differential equations

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