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

作者： Varun Somanna, M.N. Yadav, Rakesh Kumar Inzimam 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

This study aimed to quantify the temporal capabilities of radiotherapy facts from sufferers with Hodgkin lymphoma (HL) and correlate those functions with time collection evaluation (TSA) measures to perceive potential temporal relationships with early analysis of HL. Excessive-decision 3-dimensional computed tomography (CT) scans of HL sufferers have been analyzed using batch-clever TSA methods to derive the temporal collection that characterizes the radiotherapy facts. In the end, a set of temporal features from the measured temporal series have been extracted and correlated with HL's medical and laboratory analysis. The outcomes showed that the derived temporal capabilities had undoubtedly correlated with the analysis, indicating a capability for using radiotherapy information to diagnose HL early. The mean and general deviation of the temporal collection in the radiotherapy curves from HL sufferers has been notably one-of-a-kind from wholesome patients. Furthermore, the temporal series of radiotherapy statistics from HL sufferers showed notably better peaks in the temporal capabilities than healthful patients, indicating an elevated stage of radiotherapy for HL sufferers. The effects of this observation recommend that TSA may be a viable tool for early analysis of HL, presenting a more comprehensive view of the temporal traits of radiotherapy data for HL sufferers. © 2024 IEEE.

关键词： capabilities evaluation radiotherapy relationships tomography

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A Robust Ensemble Learning Approach for Medical Image Segmentation with Transfer Learning

A Robust Ensemble Learning Approach for Medical Image Segmen...

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

作者： Shree, Ritu Kavitha, R. Singh, Shweta 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

This paper proposes a robust ensemble mastering approach for clinical picture segmentation. The proposed technique combines a convolution neural community (CNN) with a switch studying-based totally ensemble model. The CNN is pre-educated with a dataset containing clinical photo modalities, particularly Magnetic Resonance Imaging (MRI) and computed tomography (CT)., a weight-averaged ensemble model is acquired between the two scientific photograph modalities. This version is an initial way to the clinical image segmentation problem. Eventually, the ensemble model is great-tuned with additional imaging statistics from an unmarried modality to improve the segmentation accuracy. The proposed technique is evaluated on a range of datasets, and the effects display that it achieves competitive performance compared to the country of the artwork. Moreover, the experiments reveal that combining the transfer gaining knowledge of-based totally ensemble mastering approach with extra imaging information enhances the accuracy of medical picture segmentation. © 2024 IEEE.

关键词： additional convolution learning state subsequently

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ICCG:low-cost and efficient consistency with adaptive synchronization for metadata replication

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Frontiers of computer science 2025年第1期19卷 53-70页

作者： Chenhao ZHANG Liang WANG Jing SHANG Zhiwen XIAO Limin XIAO Meng HAN Bing WEI Runnan SHEN Jinquan WANG State Key Laboratory of Software Development Environment Beihang UniversityBeijing 100191China School of Computer Science and Engineering Beihang UniversityBeijing 100191China School of Cyberspace Security Hainan UniversityHaikou 570228China China Mobile Information Technology Center Beijing 100033China

The rapid growth in the storage scale of wide-area distributed file systems (DFS) calls for fast and scalable metadata management. Metadata replication is the widely used technique for improving the performance and scalability of metadata management. Because of the POSIX requirement of file systems, many existing metadata management techniques utilize a costly design for the sake of metadata consistency, leading to unacceptable performance overhead. We propose a new metadata consistency maintenance method (ICCG), which includes an incremental consistency guaranteed directory tree synchronization (ICGDT) and a causal consistency guaranteed replica index synchronization (CCGRI), to ensure system performance without sacrificing metadata consistency. ICGDT uses a flexible consistency scheme based on the state of files and directories maintained through the conflict state tree to provide an incremental consistency for metadata, which satisfies both metadata consistency and performance requirements. CCGRI ensures low latency and consistent access to data by establishing a causal consistency for replica indexes through multi-version extent trees and logical time. Experimental results demonstrate the effectiveness of our methods. Compared with the strong consistency policies widely used in modern DFSes, our methods significantly improve the system performance. For example, in file creation, ICCG can improve the performance of directory tree operations by at least 36.4 times.

关键词： metadata management metadata replication consistency directory tree replica index

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Mapping between baseband units and remote radio heads based on channel prediction in CRAN

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International Journal of Wireless and Mobile Computing 2022年第2期22卷 167-178页

作者： Odwa, Lilly Abau Yosia Chen, Yueyun School of Computer and Communication Engineering University of Science and Technology Beijing Haidian District Beijing China

In cloud radio access networks, it is difficult to efficiently use the baseband unit resources. To improve resource utilisation, this paper proposes the Predictive Borrow and Lend method, which maps between baseband units and remote radio heads based on channel prediction. The channel state is predicted based on regularised particle filters, and multiple remote radio heads are mapped to a single baseband unit depending on baseband unit capacity. The proposed method aims at maximising the number of busy baseband units, by combining remote radio heads to a single baseband unit. When baseband unit utilisation exceeds the upper limit, the remote radio heads are switched to another baseband unit with low resource usage. The delay is also reduced;and the spectral and energy efficiency of the proposed method are improved, compared to borrow and lend method. Copyright © 2022 Inderscience Enterprises Ltd.

关键词： Energy efficiency

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Evaluation and Inference of a Proposed, Improved and Efficient W Model for Software Testing 15

Evaluation and Inference of a Proposed, Improved and Efficie...

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Velan, Senthil S. Velan, Sivaranjani Senthil Rubini, P. Sudhakar, K. Information Science and Engineering CMR Institute of Technology Bengaluru India Computer Science and Engineering MVJ College of Engineering Bengaluru India School of Engineering and Technology CMR University Bengaluru India Artificial Intelligence and Data Science NITTE Meenakshi Institute of Technology Bengaluru India

ISBN: (纸本)9798350370249

Software Testing is an important and measured/outcome-oriented field that requires an in-depth analysis for developing new methodologies. This enables the development of high-quality end product resulting in fewer maintenance schedules. Several models have been proposed by research teams of different companies leading to improved development and testing schedules. Even with the availability of these models, a significant allocation of the budget has been dedicated purely on the maintenance of software developed by the IT industry. In order to address this need for improved process models of testing, a new exclusive and efficient W model has been proposed and explained in this paper. This model can improve the quality of end product, namely the high-quality software and further reduce the cost involved for the maintenance. Based on the quantitative measurement the proposed W software testing model, it was found the small scale software developed by adopting this method produces high-quality software with 50% less errors/faults compared to development using classical life cycle model. ©2024 IEEE.

关键词： computer software selection and evaluation

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Prediction of Reliability of Data in Underwater Communication Network Using Fuzzy Logic

Prediction of Reliability of Data in Underwater Communicatio...

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

作者： Yadav, Surendra Gobi, N. Yadav, Rakesh 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

This paper uses fuzzy logic to propose a reliability prediction set of rules for the underwater communication community. The set of rules uses fixed fuzzy rules to expect communication reliability among nodes in an underwater environment. Those fuzzy rules are derived from a reliability model based on the characteristics of an ordinary underwater conversation system, such as physical and environmental elements. The algorithm is then examined using accurate statistics from an underwater communication test. The effects imply that this approach is promising in predicting the reliability of the community. It has also been discovered that reliability prediction accuracy can be advanced if the bushy guidelines include extra factors, the sign channel's records rate, and the machine's performance parameters. This study offers a practical approach to improving the performance and reliability of underwater communique networks. © 2024 IEEE.

关键词： algorithm communication environmental fuzzy logic

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Thermal coupling analysis and improved dynamic temperature control algorithm for 3D-LSI

Thermal coupling analysis and improved dynamic temperature c...

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2023 International Technical Conference on Circuits/Systems, computers, and Communications, ITC-CSCC 2023

作者： Wang, Songxiang Usami, Kimiyoshi Graduate School of Engineering and Science Shibaura Institute of Technology Tokyo Japan Shibaura Institute of Technology Department of Computer Science and Engineering Tokyo Japan

ISBN: (纸本)9798350326413

3D-LSI techniques are proven to be effective in improving performance without miniaturization of transistors. However, 3D-LSI have problems in heat dissipation, especially in 3D-LSI without TSV. An example is the stacked chips where communication among chips is done wirelessly. It is difficult to dissipate the heat generated by layers not connected to the substrate or the cooler. This is because thermal conduction through TSVs becomes impossible. Therefore, thermal management technology is necessary in the TSV-less 3D stacked chips. In this paper, we investigate the effect of multiple heating sources on each other by simulation. Based on the simulation results, we considered the distance between multiple high heat- sources in the proposed method to further reduce the highest temperature in the chip. In addition, we also designed a task migration algorithm when heat source cross-layer migration is allowed. This improved algorithm can select better task migration targets to reduce the generation of hotspots without changing the overall performance of the chip. Simulation verification was conducted using a commercial thermal analysis software. The results show that our approach can reduce the maximum temperature in the chip by 3-7°C when only intra-layer migration is allowed, and by more than 30°C when cross-layer migration of tasks is allowed. © 2023 IEEE.

关键词： Temperature control

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An elastic framework construction method based on task migration in edge computing

An elastic framework construction method based on task migra...

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作者： Pu, Yonglin Li, Ziyang Yu, Jiong Lu, Liang Guo, Binglei School of Software Nanjing University of Information Science and Technology Nanjing China School of Software Xinjiang University Urumqi China College of Computer Science and Technology Civil Aviation University of China Tianjin China School of Computer Engineering Hubei University of Arts and Science Xiangyang China

Edge computing (EC) serves as an effective technology, empowering end-users to attain high bandwidth and low latency by offloading tasks with high computational demands from mobile devices to edge servers. However, a major challenge arises when the processing load fluctuates continuously, leading to a performance bottleneck due to the inability to rescale edge node (EN) resources. To address this problem, the approach of task migration is introduced, and EN load prediction model, the resource constrained model, optimal communication overhead model, optimal task migration model, and energy consumption model are built to form a theoretical foundation from which to propose a task migration based resilient framework construction method in EC. With the aid of the domino effect and the combined effect of task migration, a dynamic node-growing algorithm (DNGA) and a dynamic node-shrinking algorithm (DNSA), both based on the task migration strategy, are proposed. Specifically, the DNGA smoothly expands the EN scale when the processing load increases, while the DNSA shrinks the EN scale when the processing load decreases. The experimental results show that for standard benchmarks deployed on an elastic framework, the proposed method realizes a smooth scaling mechanism in the EC, which reduces the latency and improves the reliability of data processing. © 2023 John Wiley & Sons, Ltd.

关键词： Energy utilization

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Enhancing Human Action Recognition with Adaptive Hybrid Deep Attentive Networks and Archerfish Optimization

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computers, Materials & Continua 2024年第9期80卷 4791-4812页

作者： Ahmad Yahiya Ahmad Bani Ahmad Jafar Alzubi Sophers James Vincent Omollo Nyangaresi Chanthirasekaran Kutralakani Anguraju Krishnan Department of Accounting and Finance Faculty of BusinessMiddle East UniversityAmman11831Jordan Faculty of Engineering Al-Balqa Applied UniversitySalt19117Jordan Department of Mathematics Kongunadu College of Engineering and Technology(Autonomous)TholurpattiTrichy621215India Department of Computer Science and Software Engineering Jaramogi Oginga Odinga University of Science and TechnologyBondo210-40601Kenya Department of Electronics and Communication Engineering Saveetha School of EngineeringSaveetha Institute of Medical and Technical SciencesChennai602105India Department of Electronics and Communication Engineering Saveetha Engineering College(Autonomous)Chennai602105India Department of Computer Science and Engineering Kongunadu College of Engineering and Technology(Autonomous)TholurpattiTrichy621215India

In recent years,wearable devices-based Human Activity Recognition(HAR)models have received significant *** developed HAR models use hand-crafted features to recognize human activities,leading to the extraction of basic *** images captured by wearable sensors contain advanced features,allowing them to be analyzed by deep learning algorithms to enhance the detection and recognition of human *** lighting and limited sensor capabilities can impact data quality,making the recognition of human actions a challenging *** unimodal-based HAR approaches are not suitable in a real-time ***,an updated HAR model is developed using multiple types of data and an advanced deep-learning ***,the required signals and sensor data are accumulated from the standard *** these signals,the wave features are *** the extracted wave features and sensor data are given as the input to recognize the human *** Adaptive Hybrid Deep Attentive Network(AHDAN)is developed by incorporating a“1D Convolutional Neural Network(1DCNN)”with a“Gated Recurrent Unit(GRU)”for the human activity recognition ***,the Enhanced Archerfish Hunting Optimizer(EAHO)is suggested to fine-tune the network parameters for enhancing the recognition *** experimental evaluation is performed on various deep learning networks and heuristic algorithms to confirm the effectiveness of the proposed HAR *** EAHO-based HAR model outperforms traditional deep learning networks with an accuracy of 95.36,95.25 for recall,95.48 for specificity,and 95.47 for precision,*** result proved that the developed model is effective in recognizing human action by taking less ***,it reduces the computation complexity and overfitting issue through using an optimization approach.

关键词： Human action recognition multi-modal sensor data and signals adaptive hybrid deep attentive network enhanced archerfish hunting optimizer 1D convolutional neural network gated recurrent units

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Providing an Intelligent Hybrid Routing Method in Wireless Sensor Networks 23th

Providing an Intelligent Hybrid Routing Method in Wireless S...

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23rd International Conference on Intelligent Systems Design and Applications, ISDA 2023

作者： Hosseinabadi, Ali Asghar Rahmani Mirkamali, Seyedsaeid Hajiabadi, Mahdi Rohani Abraham, Ajith Department of Computer Science University of Regina Regina Canada Department of Computer Engineering and IT Payame Noor University Tehran Iran Faculty of Computer and Information Technology Engineering Islamic Azad University Qazvin Qazvin Iran School of Computer Science Engineering and Technology Bennett University Uttar Pradesh Greater Noida India

ISBN: (纸本)9783031647758

Optimal energy consumption in Wireless Sensor Networks (WSNs) is important. Previous research has shown that by organizing network nodes into a number of clusters, one can achieve greater energy efficiency leading to longer network life. The WSN is made up of a very large number of sensor nodes that communicate with each other to perform specific tasks. These nodes have limited energy, processing power, and memory. Because the lifetime of the network depends on the brightness of the nodes, the energy consumption of each node is very important. Therefore, we need to find solutions to reduce the energy consumption of the nodes. One way to reduce energy consumption is clustering, many algorithms have been introduced in this field. In this paper, we optimize Particle Swarm Optimization (PSO) algorithm based on fuzzy logic and PSO algorithm. The fitting criterion will be based on the minimum energy consumed by the nodes of the network during each operation period, It leads to a balance in the energy consumption of the headers and, as a consequence, a lengthening of the life of the network. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Fuzzy logic

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