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Automated Disassembly Sequence Prediction for Industry 4.0 Using Enhanced Genetic Algorithm

computers, Materials & Continua 2021年第11期69卷 2531-2548页

作者： Anil Kumar Gulivindala M.V.A.Raju Bahubalendruni R.Chandrasekar Ejaz Ahmed Mustufa Haider Abidi Abdulrahman Al-Ahmari Department of Mechanical Engineering Industrial Robotics and Manufacturing Automation LaboratoryNational Institute of TechnologyKariakal609609India Department of Computer Science Engineering National Institute of TechnologyKariakal609609India Raytheon Chair for Systems Engineering Advanced Manufacturing InstituteKing Saud UniversityRiyadh11421Saudi Arabia Industrial Engineering Department College of EngineeringKing Saud UniversityRiyadh11421Saudi Arabia

The evolution of Industry 4.0 made it essential to adopt the Internet of Things(IoT)and Cloud Computing(CC)technologies to perform activities in the new age of *** technologies enable collecting,storing,and retrieving essential information from the manufacturing *** collected at sites are shared with others where execution automatedly *** obtained information must be validated at manufacturing to avoid undesirable data losses during the de-manufacturing ***,information sharing from the assembly level at the manufacturing stage to disassembly at the product end-of-life state is a major *** current research validates the information optimally to offer a minimum set of activities to complete the disassembly *** optimal disassembly sequence plan(DSP)can possess valid information to organize the necessary actions in ***,finding an optimal DSP is complex because of its combinatorial *** genetic algorithm(GA)is a widely preferred artificial intelligence(AI)algorithm to obtain a near-optimal solution for the DSP *** converging nature at local optima is a limitation in the traditional *** study improvised the GA workability by integrating with the proposed priori crossover *** optimality function is defined to reduce disassembly effort by considering directional changes as *** enhanced GA method is tested on a real-time product to evaluate the *** obtained results reveal that diversity control depends on the operators employed in the disassembly *** proposed method’s solution can be stored in the cloud and shared through IoT devices for effective resource allocation and disassembly for maximum recovery of the *** effectiveness of the proposed enhanced GA method is determined by making a comparative assessment with traditional GA and other AI methods at different population sizes.

关键词： Automation internet of things disassembly sequence planning priori cross over operator enhanced GA disassembly predicates

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Enhancing Mobile Crowdsensing Efficiency: A Coverage-aware Resource Allocation Approach

arXiv

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arXiv 2025年

作者： Fu, Yaru Zhang, Yue Shi, Zheng Guo, Yongna Liu, Yalin School of Science and Technology Hong Kong Metropolitan University Hong Kong Department of Electronic and Information Engineering Shantou University China School of Intelligent Systems Science and Engineering Jinan University China School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden

In this study, we investigate the resource management challenges in next-generation mobile crowdsensing networks with the goal of minimizing task completion latency while ensuring coverage performance, i.e., an essential metric to ensure comprehensive data collection across the monitored area, yet it has been commonly overlooked in existing studies. To this end, we formulate a weighted latency and coverage gap minimization problem via jointly optimizing user selection, subchannel allocation, and sensing task allocation. The formulated minimization problem is a non-convex mixed-integer programming issue. To facilitate the analysis, we decompose the original optimization problem into two subproblems. One focuses on optimizing sensing task and subband allocation under fixed sensing user selection, which is optimally solved by the Hungarian algorithm via problem reformulation. Building upon these findings, we introduce a time-efficient two-sided swapping method to refine the scheduled user set and enhance system performance. Extensive numerical results demonstrate the effectiveness of our proposed approach compared to various benchmark strategies. Copyright © 2025, The Authors. All rights reserved.

关键词： Integer programming

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Biomechanical models in the lower-limb exoskeletons development: A review

TechRxiv

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TechRxiv 2023年

作者： Firouzi, Vahid Seyfarth, Andre Song, Seungmoon Von Stryk, Oskar Sharbafi, Maziar Ahmad Lauflabor Locomotion Laboratory Institute of Sport Science TU Darmstadt Germany Simulation Systems Optimization and Robotics Group Department of Computer Science TU Darmstadt Germany Mechanical and Industrial Engineering Northeastern University United States

Lower limb exoskeletons serve multiple purposes, like supporting and augmenting movement. Biomechanical models are practical tools to understand human movement, and motor control. This review explores the applications of biomechanical gait models in the development of lower-limb exoskeletons. Biomechanical models can be broadly categorized as conceptual and detailed models. Biomechanical models can be used for the design, control, and assessment of exoskeletons. Also, these models can be used to estimate unmeasurable or hard-to-measure variables, which is also useful within the aforementioned applications. The analysis of applications and research areas aims to inspire further advancements in this field and contribute to the development of more effective exoskeletons. We highlight validating simulation studies, improving the accuracy and fidelity of biomechanical models, and benefiting from exoskeletons to enhance or validate biomechanical models as future research areas related to biomechanical models. We also emphasize the exploration of model-based design and control approaches for exoskeletons targeting pathological gait, and utilizing biomechanical models for diverse design objectives of exoskeletons. Also, increasing the availability of open-source resources accelerates exoskeleton and biomechanical model advancement. Our review reveals existing needs and cracks new perspectives for the development of more usable and human-compatible exoskeletons based on biomechanical models. © 2023, CC BY.

关键词： Exoskeleton (robotics)

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Machine Learning Models for Monitoring Salinity in River Estuaries: A Case Study of the Po River

Machine Learning Models for Monitoring Salinity in River Est...

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IEEE International Workshop on Metrology for the Sea;Learning to Measure Sea Health Parameters (MetroSea)

作者： Leonardo Saccotelli Giorgia Verri Alessandro De Lorenzis Carla Cherubini Giovanni Dimauro Giovanni Coppini Rosalia Maglietta CMCC Foundation - Euro-Mediterranean Center on Climate Change Lecce Italy Department of Computer Science University of Bari Bari Italy Institute of Intelligent Industrial Technologies and Systems for Advanced Manufacturing CNR-STIIMA Bari Italy

ISBN: (数字)9798350379006

ISBN: (纸本)9798350379013

Saltwater intrusion into river estuaries is a pressing environmental and socio-economic concern, posing a threat to freshwater ecosystems, agriculture, and coastal communities' water resources. Despite this, estuaries remain inadequately monitored today. The present study propose a multi-branch machine learning approach to predict the estuaries' salinity. A comprehensive learning dataset was constructed using an unstructred grid model, named SHYFEM, focusing on the Po River branches and spanning the year 2018. Machine learning algorithms including Support Vector Machine (SVM) and Random Forest (RF) were chosen as the primary models for analysis. SVM emerged has top-performing model, with an RMSE of 0.976 psu, MAE of 0.576 psu and an R2 score of 0.925. The proposed methodology provides valuable insights for monitoring and managing salinity intrusion in Po River region. However, its applicability extends beyond the Po River to other areas facing similar natural and anthropogenic conditions.

关键词： Support vector machines Salinity (geophysical) Sea measurements Estuaries Vectors Rivers Socioeconomics Monitoring Water resources Random forests

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Solving Colored Traveling Salesman Problem via Multi-neighborhood Simulated Annealing Search 18

Solving Colored Traveling Salesman Problem via Multi-neighbo...

引用

18th IEEE International Conference on Networking, Sensing and Control, ICNSC 2021

作者： Zhou, Yangming Xu, Wenqiang Fu, Zhang-Hua Zhou, Mengchu East China University of Science and Technology Department of Computer Science and Engineering Shanghai200237 China Macau Institute of Systems Engineering Macau University of Science and Technology 999078 China Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen518172 China Institute of Robotics and Intelligent Manufacturing The Chinese University of Hong Kong Shenzhen Shenzhen518172 China New Jersey Institute of Technology Department of Electrical and Computer Engineering NewarkNJ07102 United States Department of Cyber-Physical Systems St. Petersburg State Marine Technical University St. Petersburg198262 Russia

ISBN: (纸本)9781665440486

A colored traveling salesman problem (CTSP) is an important variant of the well-known multiple traveling salesman problem, which uses colors to differentiate salesmen's accessibility to individual cities to be visited. As a highly useful model for some complex scheduling problems, CTSP is NP-hard. A Multi-neighborhood Simulated Annealing Search (MSAS) approach is proposed to solve it in this paper. Starting from an initial solution, it iterates through two complementary neighborhoods: intra-route and inter-route neighborhoods. Experiments on three groups of 60 widely-used benchmark instances show that it achieves highly competitive performance compared to state-of-the-art algorithms. Moreover, MSAS can be integrated into other search methods to further improve performance, which is demonstrated by using a recently proposed iterated two-phase local search. © 2021 IEEE.

关键词： Traveling salesman problem

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A Multi-Token Coordinate Descent Method for Semi-Decentralized Vertical Federated Learning

arXiv

引用

arXiv 2023年

作者： Valdeira, Pedro Chi, Yuejie Soares, Cláudia Xavier, João CMU IST United States CMU United States NOVA IST Department of Electrical and Computer Engineering Carnegie Mellon University United States Institute for Systems and Robotics Instituto Superior Técnico Portugal Department of Computer Science NOVA School of Science and Technology Portugal

Communication efficiency is a major challenge in federated learning (FL). In client-server schemes, the server constitutes a bottleneck, and while decentralized setups spread communications, they do not necessarily reduce them due to slower convergence. We propose Multi-Token Coordinate Descent (MTCD), a communication-efficient algorithm for semi-decentralized vertical federated learning, exploiting both client-server and client-client communications when each client holds a small subset of features. Our multi-token method can be seen as a parallel Markov chain (block) coordinate descent algorithm and it subsumes the client-server and decentralized setups as special cases. We obtain a convergence rate of O(1/T) for nonconvex objectives when tokens roam over disjoint subsets of clients and for convex objectives when they roam over possibly overlapping subsets. Numerical results show that MTCD improves the state-of-the-art communication efficiency and allows for a tunable amount of parallel communications. © 2023, CC BY.

关键词： Efficiency

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Data-driven Optimal Cooperative Output Regulation of Unknown Linear Discrete-time Multi-agent systems

Data-driven Optimal Cooperative Output Regulation of Unknown...

引用

第35届中国控制与决策会议

作者： Dong Liang Yi Dong Chaoli Wang Engang Tian Department of Control Science and Engineering School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology College of Electronic and Information Engineering Shanghai Research Institute for Intelligent Autonomous Systems Tongji University

The cooperative output regulation problem has been extensively studied on the basis of the distributed observer ***,the majority of the existing research assumes that the dynamics is known *** remove this condition,the cooperative output regulation problem is further solved via the data-driven framework where the dynamics of the plant is ***,a data-driven distributed observer is established to estimate the state of the leader with unknown dynamics subject to external ***,the unknown regulator equations are solved using the iterative recurrent neural network ***,the state-based data-driven distributed control law is synthesized to solve the *** optimal gains are derived by solving convex optimization problems using input and state ***,a numerical example is presented to verify the feasibility of the proposed framework.

关键词： Linear systems multi-agent systems cooperative output regulation data-driven control optimal control

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Fundus Image Quality Assessment and Enhancement: a Systematic Review

arXiv

引用

arXiv 2025年

作者： Li, Heng Li, Haojin Ou, Mingyang Yu, Xiangyang Zhang, Xiaoqing Niu, Ke Fu, Huazhu Liu, Jiang Research Institute of Trustworthy Autonomous Systems SUSTech Shenzhen China Department of Computer Science and Engineering SUSTech Shenzhen China Center for High Performance Computing and Shenzhen Key Laboratory of Intelligent Bioinformatics Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China Computer School Beijing Information Science and Technology University Beijing China Singapore

As an affordable and convenient eye scan, fundus photography holds the potential for preventing vision impairment, especially in resource-limited regions. However, fundus image degradation is common under intricate imaging environments, impacting following diagnosis and treatment. Consequently, image quality assessment (IQA) and enhancement (IQE) are essential for ensuring the clinical value and reliability of fundus images. While existing reviews offer some overview of this field, a comprehensive analysis of the interplay between IQA and IQE, along with their clinical deployment challenges, is lacking. This paper addresses this gap by providing a thorough review of fundus IQA and IQE algorithms, research advancements, and practical applications. We outline the fundamentals of the fundus photography imaging system and the associated interferences, and then systematically summarize the paradigms in fundus IQA and IQE. Furthermore, we discuss the practical challenges and solutions in deploying IQA and IQE, as well as offer insights into potential future research directions. Copyright © 2025, The Authors. All rights reserved.

关键词： Photography

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Learning layer-wise equivariances automatically using gradients 23

Learning layer-wise equivariances automatically using gradie...

引用

Proceedings of the 37th International Conference on Neural Information Processing systems

作者： Tycho F.A. van der Ouderaa Alexander Immer Mark van der Wilk Department of Computing Imperial College London United Kingdom Department of Computer Science ETH Zurich Switzerland and Max Planck Institute for Intelligent Systems Tübingen Germany Department of Computing Imperial College London United Kingdom and Department of Computer Science University of Oxford United Kingdom

Convolutions encode equivariance symmetries into neural networks leading to better generalisation performance. However, symmetries provide fixed hard constraints on the functions a network can represent, need to be specified in advance, and can not be adapted. Our goal is to allow flexible symmetry constraints that can automatically be learned from data using gradients. Learning symmetry and associated weight connectivity structures from scratch is difficult for two reasons. First, it requires efficient and flexible parameterisations of layer-wise equivariances. Secondly, symmetries act as constraints and are therefore not encouraged by training losses measuring data fit. To overcome these challenges, we improve parameterisations of soft equivariance and learn the amount of equivariance in layers by optimising the marginal likelihood, estimated using differentiable Laplace approximations. The objective balances data fit and model complexity enabling layer-wise symmetry discovery in deep networks. We demonstrate the ability to automatically learn layer-wise equivariances on image classification tasks, achieving equivalent or improved performance over baselines with hard-coded symmetry.

关键词：

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Personnel selection under Intuitionistic Fuzzy Multi-Criteria Decision Analysis evaluation 28th

Personnel selection under Intuitionistic Fuzzy Multi-Criteri...

引用

28th International Conference on Knowledge Based and intelligent information and Engineering systems, KES 2024

作者： Augusciak, Izabela Wieckowski, Jakub Salabun, Wojciech University of WSB Merito ul. Sniadeckich 3 Szczecin70-224 Poland National Institute of Telecommunications ul. Szachowa 1 Warsaw04-894 Poland Research Team on Intelligent Decision Support Systems Department of Artificial Intelligence and Applied Mathematics Faculty of Computer Science and Information Technology West Pomeranian University of Technology Szczecin ul. Zolnierska 49 Szczecin71-210 Poland

Decision-making involves various aspects of daily life, encompassing routine tasks, complex business strategies, and resource management. With problems often including multiple criteria, detailed analysis becomes imperative to ensure a reliable assessment. Consequently, diverse tools have emerged to aid decision-makers in making well-informed choices, with Multi-Criteria Decision Analysis (MCDA) methods standing out for structured evaluations and adaptable processes. MCDA methods accommodate both crisp and fuzzy data, handling uncertainties inherent in decision problems. However, the abundance of methods poses a challenge in selecting the most suitable approach. Comparative analyses underscore the variability in outcomes, emphasizing the importance of employing multiple techniques for robust decision-making. Within resource management, MCDA methods offer versatile solutions, integrating expert knowledge and fuzzy logic to enhance reliability. As technological advancements introduce novel tools, empirical validation becomes crucial. Fuzzy ranking emerges as a promising approach, offering comprehensive insights into decision stability and robustness. This study applies selected MCDA methods within an Intuitionistic Fuzzy (IF) environment to personnel selection, analyzing multiple criteria with the participation of decision-makers. Through Monte Carlo simulation and fuzzy ranking, the study validates the efficacy of fuzzy ranking in practical multi-criteria decision-making scenarios, offering insights into decision robustness and stability. The proposed research provides a comprehensive approach to personnel selection, producing reliable and robust recommendations under changing input conditions. © 2024 The Authors.

关键词： Resource allocation

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