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Two-stage multi-item 4-dimensional transportation problem with fuzzy risk and substitution

Journal of Ambient Intelligence and Humanized Computing 2023年第7期14卷 9469-9496页

作者： Devnath, Sudeshna De, Manoranjan Mondal, Seema Sarkar Maiti, Manoranjan Department of Mathematics National Institute of Technology Durgapur Durgapur713209 India Department of Mathematics Mugberia Gangadhar Mahavidyalaya West Bengal Purba Medinipur India Department of Applied Mathematics with Oceanology and Computer Programming Vidyasagar University Midnapore721102 India

With the worldwide transport infrastructural development, there are several connecting roads between the cities for transportation. Some of these roads are smooth, and some are very rough, which invites some risks during transportation. For public distribution of some commodities, Govts. of developing countries collect those from the open markets, transport those to some warehouses for temporary storage, and from there, again transport to the fair-price shops for public distribution. With these facts, in this investigation, Govt.’s above scheme is modelled as two-stage four-dimensional transportation problems with different choices of conveyances and routes. There are some path and conveyance-wise uncertain travel risks. In fair-price shops, substitutable essential items (say rice and wheat) are sold with the necessary ones (say, mustard oil, etc.), which are sold by push-sale against some concession in an essential item (say, more rice, etc.). Thus, there is a trade-off between the ‘push-sale’ and ‘concession’, and hence an optimum decision is derived. Several models are developed depending on management’s and customers’ decisions, substitutability, push-sale, and environments. For road risk, a two-parameter (road’s roughness and distance) Mamdani-type fuzzy logic is implemented. The system’s profits for different models are maximised in both crisp and fuzzy environments and illustrated numerically using Generalised Reduced Gradient method through Lingo software. Here, the Govt.’s policy of introducing new products (termed as necessary item) among the public against a concession in an essential item has been introduced and analysed. This push-sale is effective up to a certain level, and after that, profit goes down. © 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Fuzzy logic

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Paradoxical roles of inhibitory autapse and excitatory synapse in formation of counterintuitive anticipated synchronization

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Chinese Physics B 2023年第8期32卷 499-509页

作者：丁学利古华光李玉叶贾雁兵 Department of Public Basic Education Fuyang Institute of TechnologyFuyang 236031China School of Aerospace Engineering and Applied Mechanics Tongji UniversityShanghai 200092China College of Mathematics and Computer Science Chifeng UniversityChifeng 024000China School of Mathematics and Statistics Henan University of Science and TechnologyLuoyang 471000China

Different from the common delayed synchronization(DS)in which response appears after stimulation,anticipated synchronization(AS)in unidirectionally coupled neurons denotes a counterintuitive phenomenon in which response of the receiver neuron appears before stimulation of the sender neuron,showing an interesting function of brain to anticipate the *** dynamical mechanism for the AS remains unclear due to complex dynamics of inhibitory and excitatory *** this article,the paradoxical roles of excitatory synapse and inhibitory autapse in the formation of AS are ***,in addition to the common roles such that inhibitory modulation delays and excitatory modulation advances spike,paradoxical roles of excitatory stimulation to delay spike via type-II phase response and of inhibitory autapse to advance spike are obtained in suitable parameter regions,extending the dynamics and functions of the excitatory and inhibitory ***,AS is related to the paradoxical roles of the excitatory and inhibitory modulations,presenting deep understandings to the *** autapse induces spike of the receiver neuron advanced to appear before that of the sender neuron at first,and then excitatory synapse plays a delay role to prevent the spike further advanced,resulting in the AS as the advance and delay effects realize a dynamic ***,inhibitory autapse with strong advance,middle advance,and weak advance and delay effects induce phase drift(spike of the receiver neuron advances continuously),AS,and DS,respectively,presenting comprehensive relationships between AS and other *** results present potential measures to modulate AS related to brain function.

关键词： anticipated synchronization inhibitory autapse excitatory synapse paradoxical firing

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Semi-analytical finite element method applied for characterizing micropolar fibrous composites

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applied mathematics and Mechanics(English Edition) 2024年第12期45卷 2147-2164页

作者： J.A.OTERO Y.ESPINOSA-ALMEYDA R.RODRIGUEZ-RAMOS J.MERODIO School of Engineering and Sciences Monterrey Institute of TechnologyEstado de Mexico 52926Mexico Institute of Engineering and Technology Autonomous University of Ciudad JuarezCiudad JuarezChihuahua 32310Mexico Postgraduate Program in Computational Modeling in Science and Technology Federal Fluminense UniversityRıo de Janeiro 27255-125Brazil Faculty of Mathematics and Computer Science University of HavanaLa Habana 10400Cuba Department of Mathematics Applied to ICT School of Informatics Systems EngineeringTechnical University of MadridMadrid 28031Spain

A semi-analytical finite element method(SAFEM),based on the two-scale asymptotic homogenization method(AHM)and the finite element method(FEM),is implemented to obtain the effective properties of two-phase fiber-reinforced composites(FRCs).The fibers are periodically distributed and unidirectionally aligned in a homogeneous *** framework addresses the static linear elastic micropolar problem through partial differential equations,subject to boundary conditions and perfect interface contact *** mathematical formulation of the local problems and the effective coefficients are presented by the *** local problems obtained from the AHM are solved by the FEM,which is denoted as the *** numerical results are provided,and the accuracy of the solutions is analyzed,indicating that the formulas and results obtained with the SAFEM may serve as the reference points for validating the outcomes of experimental and numerical computations.

关键词： semi-analytical approach fiber-reinforced composite(FRC) effective property finite element method(FEM) asymptotic homogenization method(AHM) micropolar elasticity

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Machine learning technique for generation of human readable rules to detect software code smells in open-source software

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Life Cycle Reliability and Safety Engineering 2024年第3期13卷 277-291页

作者： Tandon, Stuti Kumar, Vijay Singh, V.B. Amity Institute of Information Technology Amity University Uttar Pradesh Department of Mathematics Amity Institute of Applied Sciences Amity University Uttar Pradesh School of Computer and Systems Sciences Jawaharlal Nehru University

Defects entering software systems due to bad programming practice during evolution and maintenance are termed code smells. Smells impacts software at design, architectural and implementation level. These flaws report depreciation in quality of software thereby wasting human effort and time. The serious outcomes of these defects motivated researchers to study code smells. This study is conducted to determine the most daunting smell of architectural, design and implementation category of code smell. We considered 60 metrics of Apache Tomcat to analyse the quality aspects of the software. Twelve Machine Learning (ML) algorithms are applied on instances of architectural smells, implementation smells and design smells extracted from source code of 15 versions of open-source software. J48 machine learning algorithm gave 98% accurate result in code smell detection. The results are validated against tenfold cross validation and the statistical parameters: Kappa statistics, Recall, Precision, etc. used for analysing the results. Human readable classification rules are generated and validated using tenfold cross validation. Results are analysed using several Precision, Recall, F-Measure, TP Rate, FP Rate, ROC Area, Kappa statistics and accuracy performance metrics. The study also focusses on architectural category which has yet not been fully explored. © The Author(s), under exclusive licence to Society for Reliability and Safety (SRESA) 2024.

关键词： Architectural smells Design smell Implementation smell Machine learning Software metrics Static code analysis

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Optimal Lot Size and Backordered Quantity Under Carbon Tax

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International Journal of applied and Computational mathematics 2024年第4期10卷 1-16页

作者： Raiya, Geetanjali Mittal, Mandeep Department of Mathematics Amity Institute of Applied Sciences Amity University Uttar Pradesh Noida 201313 India Department of Mathematics School of Computer Science Engineering and Technology Bennett University Uttar Pradesh Greater Noida India

Researchers and industry are working together to develop low carbon inventory models that comply with carbon pricing regulations while maintaining company profits. However, this task becomes more challenging when companies also face issues related to product quality imperfections. To address this issue, a new study has developed an economic order quantity (EOQ) model that takes into account carbon emission tax, defective rates, selling prices, imperfect items, scrap items and backordering. The objective of this mathematical model is reduce overall expenses, encompassing emissions-related costs. A numerical example is come up to adorn the model, based on previous data. Sensitivity analysis has also been performed to validate the model and understand system characteristics, identifying the factors that affect total emissions. © The Author(s), under exclusive licence to Springer Nature India Private Limited 2024.

关键词： Carbon tax Defective items EOQ Optimization Shortages

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Epileptic seizure detection in EEG signals via an enhanced hybrid CNN with an integrated attention mechanism

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Mathematical Biosciences and Engineering 2025年第1期22卷 73-105页

作者： Mekruksavanich, Sakorn Phaphan, Wikanda Jitpattanakul, Anuchit Department of Computer Engineering School of Information and Communication Technology University of Phayao Phayao56000 Thailand Department of Applied Statistics Faculty of Applied Science King Mongkut’s University of Technology North Bangkok Bangkok10800 Thailand Department of Mathematics Faculty of Applied Science King Mongkut’s University of Technology North Bangkok Bangkok10800 Thailand Intelligent and Nonlinear Dynamic Innovations Research Center Science and Technology Research Institute King Mongkut’s University of Technology North Bangkok Bangkok10800 Thailand

Epileptic seizures, a prevalent neurological condition, necessitate precise and prompt identification for optimal care. Nevertheless, the intricate characteristics of electroencephalography (EEG) signals, noise, and the want for real-time analysis require enhancement in the creation of dependable detection approaches. Despite advances in machine learning and deep learning, capturing the intricate spatial and temporal patterns in EEG data remains challenging. This study introduced a novel deep learning framework combining a convolutional neural network (CNN), bidirectional gated recurrent unit (BiGRU), and convolutional block attention module (CBAM). The CNN extracts spatial features, the BiGRU captures long-term temporal dependencies, and the CBAM emphasizes critical spatial and temporal regions, creating a hybrid architecture optimized for EEG pattern recognition. Evaluation of a public EEG dataset revealed superior performance compared to existing methods. The model achieved 99.00% accuracy in binary classification, 96.20% in three-class tasks, 92.00% in four-class scenarios, and 89.00% in five-class classification. High sensitivity (89.00–99.00%) and specificity (89.63–99.00%) across all tasks highlighted the model’s robust ability to identify diverse EEG patterns. This approach supports healthcare professionals in diagnosing epileptic seizures accurately and promptly, improving patient outcomes and quality of life. © 2025 American institute of Mathematical Sciences. All rights reserved.

关键词： Electroencephalography

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Time-Consistency in Dynamic Cooperative Games with Multiple Trajectories 1

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8th International Scientific Conference on Intelligent Information Technologies for Industry, IITI 2024

作者： Li, Zekun Li, Yin Qiao, Wenwen Cheng, Wantong Department of Applied Mathematics and Process Control Saint Petersburg State University Saint Petersburg Russia School of Mathematics Harbin Institute of Technology Harbin China School of Mathematics and Computer Science Yanan University Yanan China

ISBN: (数字)9783031776885

ISBN: (纸本)9783031776878

This paper considers the time consistency of multistage cooperative games in which there are multiple optimal trajectories with complete information. In dynamic cooperative games, an important condition for the distribution of players’ payoffs is that individual rationality needs to be satisfied. If the players’ payoffs do not satisfy individual rationality as the game progresses along the cooperative trajectory, some players will deviate from the cooperative trajectory. If there are multiple optimal trajectories in the multistage game, the situation is further complicated by the fact that the players’ payoffs always satisfy individual rationality on some of the optimal trajectories, but not on others. Alternatively, players’ individual rationality conditions are quite different along different optimal trajectories. Therefore, four different scenarios of multi-stage cooperative games with multiple optimal trajectories are set up in the study and analysed for each of the four different situations. Four different Payoff Distribution Procedure (PDP) formulations are proposed to modify the players’ payoff distributions so that the game satisfies time-consistency on different optimal trajectories. Several theorems are given, and proofs are provided, with corresponding examples. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Multiple optimal trajectories Multistage cooperative games Time consistency

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Mental Health Analysis using Deep Learning of Social Media Data gathered using Chrome Extension 4

Mental Health Analysis using Deep Learning of Social Media D...

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4th International Conference for Emerging technology, INCET 2023

作者： Joshi, Manvita Mahajan, Chetashri Korgaonkar, Traividya Raul, Nataasha Naik, Meghana Sardar Patel Institute of Technology Computer Engineering Department Mumbai India Sardar Patel Institute of Technology Applied Sciences Mathematics and Humanities Department Mumbai India

ISBN: (纸本)9798350335750

Recently the topic of 'mental health' has gained high awareness, especially among younger generations. The age group that mostly gets affected by mental disorders is between 15-49 years of age. Research conducted on different social media data has found that a person with mental disorders (such as depression, anxiety, etc) tends to use social media more as compared to a mentally healthy person. Most users convey their emotional states through posting on public platforms, tweeting and accordingly watching related videos on YouTube that best describes their current mental state. It is also found that there is a difference in users' social media activities (on Facebook, Twitter, and YouTube) with a healthy mind and one with an unhealthy mind. A study conducted in 2018 found that 45% of teenagers worldwide are constantly using the internet. According to research, teenagers use the internet on average for about nine hours each day. The internet can prove to be the easiest medium to monitor a person's online activities (such as posting on social media, writing emails, watching or liking YouTube videos, commenting on YouTube videos, etc). The aforementioned activities and the internet usage time of a person can help to understand his/her mental state. The user's social media activity can be analysed for finding potential patterns in his emotions/mood. These patterns can be helpful in uncovering underlying mental health issues such as depression, stress disorders, PTSD, schizophrenia etc. These findings can be reported to the user's therapist for their monitoring record. To predict the mental state of the user by analysing their social media activities, an initiative was taken to develop an application with the objective to forewarn its users of any negative patterns regarding the state of mind that they exhibit. This application makes use of the Bidirectional LSTM algorithm, a deep learning method to identify a user's emotions (one among the 6 defined emotions) and stores

关键词： Social networking (online)

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A Review of Lightweight Security and Privacy for Resource-Constrained IoT Devices

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computers, Materials & Continua 2024年第1期78卷 31-63页

作者： Sunil Kumar Dilip Kumar Ramraj Dangi Gaurav Choudhary Nicola Dragoni Ilsun You Department of Computer Science and Engineering National Institute of Technology JamshedpurJamshedpurIndia School of Computing Science and Engineering VIT University BhopalBhopal466114India Center for Industrial Software The Maersk Mc-Kinney Moller InstituteUniversity of Southern DenmarkSonderborgOdenseDenmark Department of Applied Mathematics and Computer Science Technical University of DenmarkLyngby2800Denmark Department of Information Security Cryptologyand MathematicsKookmin UniversitySeoulSouth Korea

The widespread and growing interest in the Internet of Things(IoT)may be attributed to its usefulness in many different *** settings are probed for data,which is then transferred via linked *** are several hurdles to overcome when putting IoT into practice,from managing server infrastructure to coordinating the use of tiny *** it comes to deploying IoT,everyone agrees that security is the biggest *** is due to the fact that a large number of IoT devices exist in the physicalworld and thatmany of themhave constrained resources such as electricity,memory,processing power,and square *** research intends to analyse resource-constrained IoT devices,including RFID tags,sensors,and smart cards,and the issues involved with protecting them in such restricted *** lightweight cryptography,the information sent between these gadgets may be *** order to provide a holistic picture,this research evaluates and contrasts well-known algorithms based on their implementation cost,hardware/software efficiency,and attack resistance *** also emphasised how essential lightweight encryption is for striking a good cost-to-performance-to-security ratio.

关键词： IoT a sensor device lightweight cryptography block cipher smart card security and privacy

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An Attention Mechanism Based AVOD Network for 3D Vehicle Detection

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2023年 1-13页

作者： Yuan, Di Zhang, Haiping Shu, Xiu Liu, Qiao Chang, Xiaojun He, Zhenyu Shi, Guangming Guangzhou Institute of Technology Xidian University Xian China School of Computer Science and Cyber Engineering Guangzhou University Guangzhou China National Center for Applied Mathematics Chongqing Normal University Chongqing China Faculty of Engineering and Information Technology University of Technology Sydney Broadway New South Wales Australia School of Computer Science and Technology Harbin Institute of Technology Shenzhen China

With the continuous advancement of autonomous driving technology, 3D vehicle detection has become of widespread interest. The traditional aggregate view object detection (AVOD) framework has achieved some good results in 3D vehicle detection tasks. However, the complexity of the 3D vehicle detection scenario makes the current detection methods still not meet the actual requirements. To enhance the detection accuracy of 3D vehicle targets, we propose to equip an attention mechanism to improve the representation capability of feature maps, thereby further increasing the precision of 3D vehicle detection. Specifically, we have added the channel attention ECANet, spatial attention SANet, and mixed attention ECANet+SANet respectively into the image-based feature pyramid network of the AVOD detection framework, which can enhance the feature maps representation and improve the detection accuracy observably. The improved AVOD network is verified using the KITTI dataset. By showing the detection results of these attention mechanisms, it is found that the feature pyramid networks (FPN) module in the AVOD network based on Image has the best performance when integrating a mixed attention mechanism. In comparison to the original AVOD network, the detection results on the average precision index of the proposed method have improved by 2.29%, 2.81%, and 1.32% in the three indexes of simple, medium, and difficult, respectively. Extensive experiments have confirmed the practicality and efficacy of the AVOD network to equip the attention mechanisms for 3D vehicle detection. IEEE

关键词： Semantics

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