International Journal of Computers Communications & Control最新文献

Energy Saving Routing Algorithm for Wireless Sensor Networks Based on Minimum Spanning Hyper Tree 基于最小生成超树的无线传感器网络节能路由算法

4区计算机科学

International Journal of Computers Communications & Control Pub Date : 2023-10-30 DOI: 10.15837/ijccc.2023.6.5706

Hongzhang Han, Peizhong Shi

{"title":"Energy Saving Routing Algorithm for Wireless Sensor Networks Based on Minimum Spanning Hyper Tree","authors":"Hongzhang Han, Peizhong Shi","doi":"10.15837/ijccc.2023.6.5706","DOIUrl":"https://doi.org/10.15837/ijccc.2023.6.5706","url":null,"abstract":"With the rapid development of wireless sensor networks (WSNs), designing energy-efficient routing protocols has become essential to prolong network lifetime. This paper proposes a minimum spanning tree-based energy-saving routing algorithm for WSNs. First, sensor nodes are clustered using the LEACH protocol and minimum spanning trees are constructed within clusters and between cluster heads. The spanning tree edge weights are optimized considering transmission energy, residual energy, and energy consumption rate. This avoids channel competition and improves transmission efficiency. An energy-saving routing model is then built whereby deep reinforcement learning (DRL) agents calculate paths optimizing the energy utilization rate. The DRL reward function integrates network performance metrics like energy consumption, delay, and packet loss. Experiments show the proposed approach leads to 10-15W lower average switch energy consumption compared to existing methods. The throughput is high since overloaded shortest paths are avoided. The average path length is close to shortest path algorithms while maintaining energy efficiency. In summary, the proposed minimum spanning tree-based routing algorithm successfully achieves energy-saving goals for WSNs while guaranteeing network performance. It provides an efficient and adaptive routing solution for resource-constrained WSNs.","PeriodicalId":54970,"journal":{"name":"International Journal of Computers Communications & Control","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136132510","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Iot Data Processing and Scheduling Based on Deep Reinforcement Learning 基于深度强化学习的物联网数据处理与调度

4区计算机科学

International Journal of Computers Communications & Control Pub Date : 2023-10-30 DOI: 10.15837/ijccc.2023.6.5998

Yuchuan Jiang, Zhangjun Wang, ZhiXiong Jin

引用次数: 0

Automated Recognition Systems: Theoretical and Practical Implementation of Active Learning for Extracting Knowledge in Image-based Transfer Learning of Living Organisms 自动识别系统:生物图像迁移学习中主动学习提取知识的理论与实践

4区计算机科学

International Journal of Computers Communications & Control Pub Date : 2023-10-30 DOI: 10.15837/ijccc.2023.6.5728

Rodica Sobolu, Liana Stanca, Simona Aurelia Bodog

{"title":"Automated Recognition Systems: Theoretical and Practical Implementation of Active Learning for Extracting Knowledge in Image-based Transfer Learning of Living Organisms","authors":"Rodica Sobolu, Liana Stanca, Simona Aurelia Bodog","doi":"10.15837/ijccc.2023.6.5728","DOIUrl":"https://doi.org/10.15837/ijccc.2023.6.5728","url":null,"abstract":"In our research, we propose a model that leverages transfer learning and active learning techniques to accumulate knowledge and effectively solve complex problems in the field of artificial intelligence. This model operates within a parallel learning paradigm, aiming to mimic the continuous learning and improvement observed in human beings. To facilitate knowledge accumulation, we introduce a convolutional deep classification auto encoder that extracts spatially localized features from images. This enhances the model’s ability to extract relevant information. Additionally, we propose a learning classification system based on a code fragment, enabling effective representation and transfer of knowledge across different domains. Our research culminates in a theoretical and practical prototype for active learning-based knowledge extraction in various living organisms, including humans, plants, and animals. This knowledge extraction is achieved through image-based learning transfer, focusing on advancing activity recognition in image processing. Experimental results confirm that our method outperforms both baseline approaches and state-of-the-art convolutional neural network methods, underscoring its effectiveness and potential.","PeriodicalId":54970,"journal":{"name":"International Journal of Computers Communications & Control","volume":"34 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136132512","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An Improved Deeplabv3+ Model for Semantic Segmentation of Urban Environments Targeting Autonomous Driving 面向自动驾驶的城市环境语义分割改进Deeplabv3+模型

4区计算机科学

International Journal of Computers Communications & Control Pub Date : 2023-10-30 DOI: 10.15837/ijccc.2023.6.5879

Wang Wang, Hua He, Changsong Ma

引用次数: 0

Residual Generative Adversarial Adaptation Network For The Classification Of Melanoma 残差生成对抗适应网络在黑色素瘤分类中的应用

4区计算机科学

International Journal of Computers Communications & Control Pub Date : 2023-10-30 DOI: 10.15837/ijccc.2023.6.5274

None S. Gowthami, None R. Harikumar

引用次数: 0

Smart Agriculture in the Digital Age: A Comprehensive IoT-Driven Greenhouse Monitoring System 数字时代的智慧农业:物联网驱动的温室综合监测系统

4区计算机科学

International Journal of Computers Communications & Control Pub Date : 2023-10-30 DOI: 10.15837/ijccc.2023.6.6147

Attila Simo, Simona Dzitac, Amalia Duțu, Ionuț Pandelica

引用次数: 0

Transforming Financial Decision-Making: The Interplay of AI, Cloud Computing and Advanced Data Management Technologies 改变财务决策:人工智能、云计算和先进数据管理技术的相互作用

4区计算机科学

International Journal of Computers Communications & Control Pub Date : 2023-10-30 DOI: 10.15837/ijccc.2023.6.5735

Sergiu-Alexandru Ionescu, Vlad Diaconita

{"title":"Transforming Financial Decision-Making: The Interplay of AI, Cloud Computing and Advanced Data Management Technologies","authors":"Sergiu-Alexandru Ionescu, Vlad Diaconita","doi":"10.15837/ijccc.2023.6.5735","DOIUrl":"https://doi.org/10.15837/ijccc.2023.6.5735","url":null,"abstract":"Financial institutions face many challenges in managing modern financial transactions and vast data volumes. To overcome these challenges, they are increasingly harnessing advanced data man- agement technologies such as artificial intelligence and cloud computing. This paper presents a com- prehensive review of how these tools transform financial decision-making in various domains and ap- plications. We analyzed both foundational and recent advancements using a rigorous methodology based on the PRISMA 2020 guideline. Our findings indicate that many major financial institutions are adopting AI-driven solutions to potentially enhance real-time risk assessment, transactional efficiency, and predictive analytics. While they bring benefits like faster decision-making and reduced operational costs, they also pose challenges like data security and integration complexities that require further research and development. Looking ahead, we envision a more integrated, responsive, and secure financial ecosystem that leverages the convergence of AI, cloud computing, and advanced data storage. This synthesis underscores the significance of contemporary data management solutions in shaping the future of data-driven financial services, offering a guideline for stakeholders in this evolving domain.","PeriodicalId":54970,"journal":{"name":"International Journal of Computers Communications & Control","volume":"45 S1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136132511","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimizing Heterogeneity in IoT Infra Using Federated Learning and Blockchain-based Security Strategies 使用联邦学习和基于区块链的安全策略优化物联网基础设施的异构性

4区计算机科学

International Journal of Computers Communications & Control Pub Date : 2023-10-30 DOI: 10.15837/ijccc.2023.6.5890

Venkatesan Muthukumar, R. Sivakami, Vinoth Kumar Venkatesan, J. Balajee, T.R. Mahesh, E. Mohan, B. Swapna

{"title":"Optimizing Heterogeneity in IoT Infra Using Federated Learning and Blockchain-based Security Strategies","authors":"Venkatesan Muthukumar, R. Sivakami, Vinoth Kumar Venkatesan, J. Balajee, T.R. Mahesh, E. Mohan, B. Swapna","doi":"10.15837/ijccc.2023.6.5890","DOIUrl":"https://doi.org/10.15837/ijccc.2023.6.5890","url":null,"abstract":"The Internet of Things (IoT) and associated capabilities are becoming indispensable in the planning, operation, and administration of intricate systems of all sizes. High-end learning solutions that go beyond the boundaries of the problem are necessary for addressing the variety of communication concerns (compatibility, secure communication, etc.) in IoT settings. Building machine learning (ML) networks from disparate data sources is a cutting-edge practice known as Federated Learning (FL). In this article, we implement FL between edge-based servers and devices in a sparsely populated cloud to facilitate cohesive learning and the storage of critical information in smart IoT systems. FL enables collaborative training from a common model by aggregating smaller unit models via regulated edge network participants. Further, all the susceptible device’s information and sensitive message transactions are addressed via blockchain technology. Thus, a blockchain-based security mechanism is integrated to secure user privacy and facilitate widespread practical adoption. Finally, a comparison is made between the proposed model and the three best free, open-source Federated Learning models already in use (FedPD, FedProx, and FedAvg). In terms of statistical, and data heterogeneity (>70% SDI, >97% accuracy), the experimental findings suggest that the proposed model performs better than the existing techniques.","PeriodicalId":54970,"journal":{"name":"International Journal of Computers Communications & Control","volume":"45 S3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136132505","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Graph-Based PPO Approach in Multi-UAV Navigation for Communication Coverage 基于图的多无人机通信覆盖导航PPO方法

4区计算机科学

International Journal of Computers Communications & Control Pub Date : 2023-10-30 DOI: 10.15837/ijccc.2023.6.5505

Zhiling Jiang, Yining Chen, Ke Wang, Bowei Yang, Guanghua Song

引用次数: 0

Hybrid Filtering-based Physician Recommender Systems using Fuzzy Analytic Hierarchy Process and User Ratings 基于模糊层次分析法和用户评分的混合过滤医生推荐系统

4区计算机科学

International Journal of Computers Communications & Control Pub Date : 2023-10-30 DOI: 10.15837/ijccc.2023.6.5086

None V. Mani, None S. Thilagamani

{"title":"Hybrid Filtering-based Physician Recommender Systems using Fuzzy Analytic Hierarchy Process and User Ratings","authors":"None V. Mani, None S. Thilagamani","doi":"10.15837/ijccc.2023.6.5086","DOIUrl":"https://doi.org/10.15837/ijccc.2023.6.5086","url":null,"abstract":"As an emerging trend in data science, applications based on big data analytics are reshaping health informatics and medical scenarios.Currently, peoples are more cognizant and seek solutions to their healthcareproblems online. In the chorus, selecting a healthcare professional or organization is a tedious and time-consuming process. Patients may vainly spend time and meet severaldoctors until one is found that suits theirexact needs. Frequently, they do not have sufficient information on whereupon to base a decision. This has led to a dire requirementfor an efficient anddependablepatient-specific online tool to find out an appropriatedoctor in a limited time.In this paper, we propose a hybrid Physician Recommender System(PRS) by integrating various recommender approaches such asdemographic, collaborative, and content-based filtering for findingsuitabledoctors in line with the preferred choices of patients and their ratings. The proposed system resolves the problem of customization by studyingthe patient’s criteriaforchoosing a physician. It employs an adaptive algorithm to find the overall rank of the particular doctor. Furthermore, this ranking method is applied to convert patients’ preferred choices into a numerical base rating, which will ultimately be employed inour physician recommender system. The proposed system has been appraisedcarefully, and the result reveals that recommendations are rational and can satisfythe patient’s need for consistentphysician selection successfully.","PeriodicalId":54970,"journal":{"name":"International Journal of Computers Communications & Control","volume":"34 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136132513","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0