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An adaptive multitasking optimization algorithm based on population distribution

Mathematical Biosciences and engineering 2024年第2期21卷 2432-2457页

作者： Li, Xiaoyu Wang, Lei Jiang, Qiaoyong Xu, Qingzheng School of Computer Science and Engineering Xi'an University of Technology Xi'an710048 China School of Electronic and Information Engineering Ankang University Ankang725000 China The Key Laboratory of Industrial Automation of Shaanxi Province Shaanxi University of Technology Hanzhong723001 China College of Information and Communication National University of Defense Technology Wuhan430019 China

Evolutionary multitasking optimization (EMTO) handles multiple tasks simultaneously by transferring and sharing valuable knowledge from other relevant tasks. How to effectively identify transferred knowledge and reduce negative knowledge transfer are two key issues in EMTO. Many existing EMTO algorithms treat the elite solutions in tasks as transferred knowledge between tasks. However, these algorithms may not be effective enough when the global optimums of the tasks are far apart. In this paper, we study an adaptive evolutionary multitasking optimization algorithm based on population distribution information to find valuable transferred knowledge and weaken the negative transfer between tasks. In this paper, we first divide each task population into K sub-populations based on the fitness values of the individuals, and then the maximum mean discrepancy (MMD) is utilized to calculate the distribution difference between each sub-population in the source task and the subpopulation where the best solution of the target task is located. Among the sub-populations of the source task, the sub-population with the smallest MMD value is selected, and the individuals in it are used as transferred individuals. In this way, the solution chosen for the transfer may be an elite solution or some other solution. In addition, an improved randomized interaction probability is also included in the proposed algorithm to adjust the intensity of inter-task interactions. The experimental results on two multitasking test suites demonstrate that the proposed algorithm achieves high solution accuracy and fast convergence for most problems, especially for problems with low relevance. © 2024 the Author(s).

关键词： Optimization

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Transfer Learning based Analysis of Chest X-rays for Accurate Lung Disease Detection and Interpretation 3

Transfer Learning based Analysis of Chest X-rays for Accurat...

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3rd International Conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics, IITCEE 2025

作者： Perla, Someswari Veledendi, Sudhakar Jaiswal, Pooja Muppidi, Satish Mandala, Jyothi Maram, Balajee Gmr Institute of Technology Department of Cse - Ai&ml Andhra Pradesh Rajam India Sr University School of Computer Science and Artificial Intelligence Warangal India Galgotias University India Gmr Institute of Technology Departnent of Computer Science and Engineering Rajam India University Department of Computer Science and Engineering Banglore India Sr University School of Computer Science and Artificial Intelligence Telangana Warangal506371 India

ISBN: (纸本)9798331515911

This is a research paper based on a transfer learning approach with a primary aim at the analysis of chest Xrays for accurate detection and interpretation of lung diseases. The proposed method relies heavily on the use of pretrained deep learning models to enhance diagnostic accuracy and reduce the time and computational resources taken during training. Applying transfer learning to a large chest X-ray dataset, the model successfully detects key patterns associated with common lung diseases, such as pneumonia and tuberculosis. The manuscript encompasses data preprocessing, model finetuning, and performance evaluation and demonstrates huge improvements over the traditional methods both in terms of accuracy and interpretability. It has been experimentally proven that the model is competent enough to provide localization of disease areas, as it can be visualized through heatmaps obtained from predictions, which might further help the radiologists perform their diagnosis tasks. This work advocates for medical imaging automation for the early and efficient detection of lung disease. © 2025 IEEE.

关键词： Lung cancer

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Guest Editorial: Special Issue on Evolutionary Computation for Games

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IEEE Transactions on Games 2023年第1期15卷 1-4页

作者： Schrum, Jacob Liu, Jialin Browne, Cameron Ekart, Aniko Gallagher, Marcus Southwestern University Department of Mathematics and Computer Science GeorgetownTX United States Southern University of Science and Technology Department of Computer Science and Engineering Shenzhen China Maastricht University Department of Data Science and Knowledge Engineering Maastricht Netherlands Aston University Department of Computer Science United Kingdom The University of Queensland School of Information Technology and Electrical Engineering Australia

The eight papers in this special section focus on applications of evolutionary computation to games to demonstrate several ways in which evolution can push boundaries and explore new areas of what is possible in the realm of games research, with a focus on game-playing, automatic agent parameter tuning, automatic game testing, and procedural content generation.

关键词： Special issues and sections Evolutionary computation Games

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Caching Techniques in Edge Computing and Challenges 3

Caching Techniques in Edge Computing and Challenges

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3rd International Conference on Advancement in Electronics and Communication engineering, AECE 2023

作者： Kumar, Sumit Dash, Yajnaseni Galgotias University Department of Computer Science & Engineering Uttar Pradesh India School of Computer Science Engineering and Technology Bennett University Uttar Pradesh India

ISBN: (纸本)9798350330724

Edge computing, a distributed computing concept, brings data processing and storage closer to endpoints or edge devices. Caching methods are crucial in edge computing environments for optimizing performance and minimizing latency and enable faster response times, efficient bandwidth utilization, and enhanced scalability. Edge computing uses caching techniques strategically based on user behaviour studies and access patterns to boost scalability and reduce network congestion. Caching techniques increase the efficacy and performance of edge computing. The parameters that influence efficacy include cache management strategies, network conditions, application features, and data access patterns. This paper presents a brief overview of the caching technologies utilized in edge computing and their challenges. © 2023 IEEE.

关键词： Internet of things

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A systematic review on non-contact methods to estimate the surface roughness 2

A systematic review on non-contact methods to estimate the s...

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2nd International Conference on Materials science and Mathematics for Advanced technology, MSMAT 2022

作者： Karegoudra, Shilpa Yendapalli, Vamsidhar Department of Computer Science and Engineering Udupi574110 India Department of Computer Science and Engineering GITAM School of Technology Bengaluru GITAM University Karnataka India

Information and Communication technology (ICT) is used in recent industries to advance into a decision-making environment in manufacturing. The objectives of this are efficiency, flexibility, innovation, quality, and cost reduction. Controlling and monitoring the machining operation is an area of interest for most researchers. Drilling is the process of making a hole by using different cutting tools and continuously removing material to create the desired feature. It often rubs against the produced surface during chip evacuation. As a result, the produced roughness is distinct from that of other machining operations like milling or turning. Surface roughness may therefore differ from the one that is predicted theoretically. In this paper, we are studying the various non-contact methods to estimate the surface roughness of the machined surfaces. © 2023 Elsevier Ltd. All rights reserved.

关键词： Cost reduction

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Maximizing the Accuracy of Time Series Analysis for the Early Detection of Rhabdomyosarcomas

Maximizing the Accuracy of Time Series Analysis for the Earl...

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2024 International Conference on Optimization Computing and Wireless Communication, ICOCWC 2024

作者： Shree, Ritu Prabhu, A. Gautam, Anupam Kumar Vivekananda Global University Department of Computer Science & Application Jaipur India Department of Computer Science and Information Technology Bangalore India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India

ISBN: (纸本)9798350383348

Rhabdomyosarcomas are a rare malignant tender tissue tumor that generally gives in younger children and teenagers. Early prognosis and remedy are essential for successful outcomes. Time collection evaluation is a valuable tool for recognizing styles and trends in medical facts, mainly for rare situations, which include Rhabdomyosarcomas. It has consequently been increasingly employed to detect early signs and symptoms of the ailment. On this look, we are conscious of investigating and optimizing techniques for time collection analysis. It is an excellent way to enhance its application and accuracy in identifying early symptoms and signs of rhabdomyosarcoma. We examine present strategies and suggest improvement techniques, along with function extraction and system mastering techniques. We further inspect the effectiveness of our strategies by conducting experiments on a dataset installed from scientific facts and literature of rhabdomyosarcoma instances. Those experiments show promising effects, indicating that our proposed strategies can considerably increase the accuracy and sensitivity of time series evaluation for the early detection of rhabdomyosarcoma and cause higher prognoses for affected sufferers. The focal point of this study is to maximize the accuracy of time series analysis for the early detection of rhabdomyosarcoma. Time collection analysis includes: • The gathering of temporal information from multiple sources. • The assessment of these records. • The interpretation of correlations between the facts points. This study aims to utilize these techniques to discover diffused adjustments in affected person information so that you can perceive the onset of the disorder in advance than would be possible with traditional techniques. The examination will expand algorithms to systematically and accurately procedure the temporal statistics and discover adjustments indicative of Rhabdomyosarcomas. In addition, the look will rent gadget learning to boost the dete

关键词： malignant recognizing Rhabdomyosarcomas strategies Time

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Improving Dynamic Behavior of Vehicular Ad Hoc Networks by Integrating Game Theory Technique 5th

Improving Dynamic Behavior of Vehicular Ad Hoc Networks by I...

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5th International Conference on Applied Technologies, ICAT 2023

作者： Tiwari, Shobhit Mani Baghel, Anurag Singh Department of Computer Science and Engineering Faculty of Engineering and Technology University of Lucknow Uttar Pradesh Lucknow India Department of Computer Science and Engineering School of ICT Gautam Buddha University Uttar Pradesh Greater Noida India

ISBN: (纸本)9783031589553

In this paper, we give the focus on the continuous advancement in the domain of Vehicular ad hoc networks (VANET’s) and that is developed as a tool for developing the base for platform intelligent mode in the communication (inter vehicle communications) and needful for enhanced improvement under the performance effect and traffic safety. Here, we have deployed the game theory method in the VANET domain and thereafter categorizes between the hop vehicle and the source vehicle. The New approach to the VANET analysis we have identified and used the social parameters and hence made it look more novel approach. "Researching vehicle ad hoc networks poses challenges due to their dynamic nature, the movement of large vehicles, unlimited energy resources, and the evolution of wireless networks. Game theory is commonly employed in wireless networks to explore the interplay between competition and cooperation. In this study, we present a system for ad hoc networks in cars, utilizing game theory to automate car groups and board elections. This approach eliminates the necessity for regular bulk updates. Furthermore, the social behavior of each car is leveraged to create clusters in the car environment. The K-means algorithm in machine learning is applied to develop social cars. The proposed system underwent testing for various characteristics, including CH lifetime, average group lifetime, average number of joins, throughput, and packet loss rate. The results demonstrate that VANET performs exceptionally well, achieving an overall performance ranging from 0.95 to 0.989". © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Heterogeneous networks

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Research on the EAP Phase Optimization Mechanism of IEEE 802.15.6 Protocol 7

Research on the EAP Phase Optimization Mechanism of IEEE 802...

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7th IEEE International Conference on computer and Communication engineering technology, CCET 2024

作者： Zhang, Chongqing Su, Lihui Zhang, Nan College of Computer Science and Engineering Shandong University of Science and Technology Qingdao China School of Mathematies and Statistics Heze University Heze China

ISBN: (纸本)9798350355673

Wireless body area networks (WBANs) are supposed to play an important role in future health care. The IEEE 802.15.6 is the standard protocol for WBANs. In order to transmit medical emergency data with high real-time and reliability requirements, the IEEE 802.15.6 specifically sets the Exclusive Access Phase (EAP) in the superframe structure. However, setting up such an EAP phase may lead to extra price. This paper studies how to optimize EAP transmission and design a mechanism utilizing Random Access Period (RAP) to replace EAP to ensure high-priority data transmission and improve resource utilization. Simulation experiments confirmed the effectiveness of the proposed mechanism. © 2024 IEEE.

关键词： Wireless local area networks (WLAN)

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Towards Efficient Video Object Detection on Embedded Devices 13

Towards Efficient Video Object Detection on Embedded Devices

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13th International Conference on computer and Knowledge engineering, ICCKE 2023

作者： Hajizadeh, Mohammad Rahmani, Adel Sabokrou, Mohammad Iran University of Science and Technology School of Computer Engineering Tehran Iran Ipm Institute for Research in Fundamental Sciences School of Computer Science Tehran Iran

ISBN: (纸本)9798350330151

The challenge of adapting various object recognition techniques from still images to videos remains unsolved. When applied to videos, methods that are specifically designed for images do not perform well due to several complications. These include blurriness, shifting or ambiguous locations, subpar quality, and other similar concerns. In addition, a lack of effective long-term memory in video object detection has yet to be addressed. It is widely recognized that consecutive frames in a video tend to produce highly similar results in most cases. Therefore, this characteristic can be exploited to improve performance. Moreover, the information contained in a series of sequential or non-consecutive frames exceeds that of a single frame. In our research, we have introduced a novel recurrent cell for feature propagation and have determined the optimal layer placement to augment the memory span. This has resulted in superior precision compared to methods presented in previous research. Furthermore, hardware constraints may exacerbate this issue. Therefore, we have focused on implementing and improving the effectiveness of these techniques on embedded devices. Our approach has yielded impressive results, with a 67.5% mAP accuracy on the real-time ImageNet VID dataset for mobile devices at a rate of 62 fps. © 2023 IEEE.

关键词： Object recognition

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Optimized Sensor Network Design for Real-Time Environmental Monitoring

Optimized Sensor Network Design for Real-Time Environmental ...

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2024 International Conference on Optimization Computing and Wireless Communication, ICOCWC 2024

作者： Harron, Syed Shukla, Gaurav Kaushik, Harshita Department of Computer Science and Information Technology Bangalore India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Vivekananda Global University Department of Computer Science & Application Jaipur India

ISBN: (纸本)9798350383348

A sensor community is a set of interconnected sensors that can degree, monitor, and report phenomena within the environment. Sensor networks have many packages consisting of actual-time environmental tracking. A good way to effectively use these networks for monitoring, an optimized network layout needs to be employed to ensure that the network can meet the necessities of its operational demands. This paper proposes a fashionable-motive sensor network design framework for real-time environmental tracking. The proposed framework gives a step-by-step technique to optimize a sensor network design for the project at hand. It begins with a version of the surroundings that the sensor community will screen, which is used to generate sensor node configurations and topologies. These configurations and topologies are then used to lay out the sensor community such that its deployment is optimized for the surroundings. The design framework makes use of a community optimization set of rules to attain a configuration that maximizes the network's performance and is capable of meeting its operational requirements. The set of rules operates with the aid of looking through the distance of all feasible sensor community topologies, looking for those that have the first-rate value-benefit ratio. The algorithm can be further progressed by way of the usage of the device, gaining knowledge of strategies, which makes it capable of managing extra complex eventualities. © 2024 IEEE.

关键词： Algorithm Community Eventualities Interconnected Requirements Sensor Strategies Value-Benefit

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