Computers & Electrical Engineering最新文献

{"title":"A swarm intelligence approach to minimum weight independent dominating set problem","authors":"Mohd Danish Rasheed ,&nbsp;Alok Singh ,&nbsp;Rammohan Mallipeddi","doi":"10.1016/j.compeleceng.2025.110222","DOIUrl":"10.1016/j.compeleceng.2025.110222","url":null,"abstract":"<div><div>The minimum weight independent dominating set (MWIDS) problem is a challenging problem in graph theory with diverse practical applications. In this paper, we propose a novel approach to tackle the MWIDS problem efficiently using the Artificial Bee Colony (ABC) algorithm, a metaheuristic optimization technique inspired by the foraging behavior of honeybees. Our approach integrates six heuristics tailored as per the characteristics of the MWIDS problem within the ABC algorithm to generate high-quality solutions by effectively exploring the solution space. We have conducted extensive experiments on standard benchmark instances to evaluate the effectiveness of our proposed approach. The experimental results demonstrate the competitiveness of our approach in comparison to the state-of-the-art for finding high quality solutions highlighting its potential for practical applications in real-world scenarios.</div></div>","PeriodicalId":50630,"journal":{"name":"Computers & Electrical Engineering","volume":"123 ","pages":"Article 110222"},"PeriodicalIF":4.0,"publicationDate":"2025-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143579150","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimal day-ahead scheduling and reconfiguration of active distribution systems considering energy hubs, residential demand response aggregators, and electric vehicle parking lot aggregators","authors":"Hashmatollah Nourizadeh,&nbsp;Mehrdad Setayesh Nazar","doi":"10.1016/j.compeleceng.2025.110227","DOIUrl":"10.1016/j.compeleceng.2025.110227","url":null,"abstract":"<div><div>This paper presents the optimal day-ahead scheduling and reconfiguration of an active distribution system considering energy hubs, residential demand response aggregators, and electric vehicle parking lot aggregators. The main contribution of this paper is that it introduces a three-level framework for scheduling and reconfiguring active distribution systems and modeling the competition among residential demand response aggregators in the day-ahead horizon.This framework examines the flexible integrated demand response program for smart residential consumers and multi-carrier energy hubs. The study evaluates the impacts of power exchange by consumers on the profits and costs of stakeholders while minimizing operational costs, maximizing power exchange profits, and ensuring residential comfort levels. Additionally, optimal scheduling and reconfiguration of the active distribution system have been proposed. In the first level, the optimization process focuses on the residential demand response aggregators and electric vehicle parking lots, incorporating Cournot-based competition among residential aggregators and prioritizing carbon emissions reduction and fuel savings. In the second level, self-scheduling of multi-carrier energy hubs is performed to determine profits and costs. In the third level, the proposed procedure considers the contribution of lower-level agents that can be utilized for scheduling and reconfiguring the active distribution system. The effectiveness of the model was assessed using a modified IEEE 123 bus system. The simultaneous implementation of the proposed demand response program and optimal reconfiguration reduced operational costs by 5.28%. Furthermore, competition among residential demand response aggregators and the implementation of the proposed demand response program increased profits by $75.49 and $61.03, respectively.</div></div>","PeriodicalId":50630,"journal":{"name":"Computers & Electrical Engineering","volume":"123 ","pages":"Article 110227"},"PeriodicalIF":4.0,"publicationDate":"2025-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143579149","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An adaptive feature fusion framework of CNN and GNN for histopathology images classification","authors":"Linhao Li ,&nbsp;Min Xu ,&nbsp;Shuai Chen ,&nbsp;Baoyan Mu","doi":"10.1016/j.compeleceng.2025.110186","DOIUrl":"10.1016/j.compeleceng.2025.110186","url":null,"abstract":"<div><div>This study introduces an Adaptive Feature Fusion Classification Network (AFFC<img>Net) designed for cancer detection in histopathology images. AFFC<img>Net leverages Convolutional Neural Network (CNN) and Graph Neural Network (GNN) as parallel feature extractors, significantly improving the ability to capture complex histopathological features. The network includes an adaptive feature fusion module that weights and fuses features from the two branches using adaptive scaling factor and attention mechanisms. The fused features are subsequently utilized to construct a graph structure. The global feature aggregation unit then performs sampling and aggregation on this graph to extract high-level semantic features. Experimental results demonstrate the effectiveness of AFFC<img>Net. On the BRACS dataset, a breast cancer subtype pathology image dataset containing 4391 images, the model achieved an F1-score of 67.23 %, representing a 2.83 % improvement over previous methods. On the LC25000 dataset, a pathology image dataset of lung and colon tissues containing 25,000 images, it achieved Precision, Recall, Specificity, Accuracy, and F1-score of 99.84 %, 99.84 %, 99.96 %, 99.84 %, and 99.84 %, respectively, showing improvements of 1.36 %, 0.37 %, 0.34 %, 0.45 %, and 0.52 % compared to existing approaches. These results highlight AFFC<img>Net's capability to leverage advanced semantic features and achieve competitive performance compared to state-of-the-art methods.</div></div>","PeriodicalId":50630,"journal":{"name":"Computers & Electrical Engineering","volume":"123 ","pages":"Article 110186"},"PeriodicalIF":4.0,"publicationDate":"2025-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143579147","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AI-driven dynamic trust management and blockchain-based security in industrial IoT","authors":"Rajesh Kumar,&nbsp;Rewa Sharma","doi":"10.1016/j.compeleceng.2025.110213","DOIUrl":"10.1016/j.compeleceng.2025.110213","url":null,"abstract":"<div><div>The Industrial Internet of Things (IIoT) revolutionizes industrial operations through real-time data exchange and analytics but introduces significant security and trust challenges particularly in dynamic and distributed IIoT environments. We hypothesize that integrating an AI-driven Trust Management System (TMS) with blockchain technology can address these issues effectively. This paper proposes a framework combining an AI-driven Dynamic TMS (AI-DTMS) with a private blockchain. AI-DTMS evaluates the reliability of the device and data using machine learning, achieving 96.31% accuracy with minimal false positives. The blockchain module ensures secure authentication, achieving nearly 100% success. It mitigates critical threats, including spoofing, Sybil, node-capturing, replay, and DDoS attacks, ensuring robust security in IIoT environments. Performance evaluations demonstrate 35% improvement in response time and up to 97.8% reduction in latency, underscoring scalability and efficiency. By integrating AI-DTMS with blockchain, the framework enhances trust, security, and performance in dynamic IIoT environments, offering a scalable and robust solution.</div></div>","PeriodicalId":50630,"journal":{"name":"Computers & Electrical Engineering","volume":"123 ","pages":"Article 110213"},"PeriodicalIF":4.0,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143562577","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Q-learning-based hierarchical routing protocol in underwater acoustic sensor networks","authors":"Amir Masoud Rahmani ,&nbsp;Jawad Tanveer ,&nbsp;Abdulmohsen Mutairi ,&nbsp;May Altulyan ,&nbsp;Entesar Gemeay ,&nbsp;Mahfooz Alam ,&nbsp;Mohammad Sadegh Yousefpoor ,&nbsp;Efat Yousefpoor ,&nbsp;Mehdi Hosseinzadeh","doi":"10.1016/j.compeleceng.2025.110211","DOIUrl":"10.1016/j.compeleceng.2025.110211","url":null,"abstract":"<div><div>In order to guarantee a reliable data forwarding process, underwater acoustic sensor networks (UASNs), which are widely used in water environments like oceans and seas, need efficient routing protocols. Because sensor nodes are expensive to deploy in underwater environments and have limited energy capacities, energy optimization is a significant and practical issue, particularly for extending network lifetime. Today, various energy-efficient routing strategies have been suggested by combining opportunistic routing (OR) and reinforcement learning (RL). However, this subject deals still with different challenges. This paper introduces a Q-learning-based hierarchical routing protocol (QHRP) in UASNs. This approach builds a Q-learning-based routing tree, which contains a state set filtered by a two-step filtering process. It effectively increases the convergence speed of the Q-learning algorithm and lowers delay due to the tree construction process. In QHRP, the reward function considers network conditions and is obtained based on four metrics, namely remaining energy, strategic depth, the size of the state set, and successful transmission probability. Moreover, QHRP solves the void area problem in the routing tree by redefining the set of states and reward function. To evaluate QHRP compared to the three routing methods, namely RLOR, EE-DBR, and MURAO, various experiments are performed in terms of packet delivery rate (PDR), end-to-end delay (EED), data integrity, consumed energy, and the number of hops in the forwarding routes. These results show that QHRP improves PDR, delay, data integrity, energy consumption, and the number of hops by 9.068%, 9.03%, 9.84%, 15.61%, and 10.31%, respectively.</div></div>","PeriodicalId":50630,"journal":{"name":"Computers & Electrical Engineering","volume":"123 ","pages":"Article 110211"},"PeriodicalIF":4.0,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143562475","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-load parity-time symmetry wireless power transmission system with active directional energy transmission","authors":"Biao-Biao Xu,&nbsp;You-Long Wen,&nbsp;Xing-Yu Zhang,&nbsp;Xiao-San Ma,&nbsp;Mu-Tian Cheng","doi":"10.1016/j.compeleceng.2024.109980","DOIUrl":"10.1016/j.compeleceng.2024.109980","url":null,"abstract":"<div><div>A novel multi-load Parity-Time (PT) wireless power transmission (WPT) system with active directional energy transmission is designed. Firstly, we utilize a variable capacitor array to achieve selective mutual coupling between a single transmitting coil and multiple receiving coils. Then, under the action of the control circuit, the system can prioritize charging low-capacity batteries and automatically switch charging modes after the load is charged. Furthermore, different from the existing multi-load PT-WPT system, the DC-DC converter is added to the receiving device in this design. The DC-DC converter ensures that the system can provide constant current (CC) or constant voltage (CV) charging modes depending on the load requirements. Through the above design, we have constructed a new multi-stage charging mode in the multi-load PT-WPT system. The experimental results show that the system can achieve active directional energy transfer and provide different charging modes according to the needs of the loads. Moreover, the system also exhibits features such as a wide coupling and actively switching charging modes. The use of a multi-load PT-WPT system with active directional energy transmission can provide efficient charging strategies for wireless sensor networks with multiple loads.</div></div>","PeriodicalId":50630,"journal":{"name":"Computers & Electrical Engineering","volume":"123 ","pages":"Article 109980"},"PeriodicalIF":4.0,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143562474","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Design of a low-power intelligent system for optimizing railway tunnel settlement data stream processing using TinyMLt","authors":"Baihang Lv ,&nbsp;Lei Wang ,&nbsp;Xing Liu ,&nbsp;Bin Liu ,&nbsp;Bo Liu ,&nbsp;Ziwen Zhang ,&nbsp;Yang Li ,&nbsp;Fangzhe Shi","doi":"10.1016/j.compeleceng.2025.110197","DOIUrl":"10.1016/j.compeleceng.2025.110197","url":null,"abstract":"<div><div>The advancement of TinyML technologies has opened new avenues for designing low-power intelligent systems, significantly enhancing the processing capabilities of embedded devices in critical infrastructure. To overcome these limitations, we propose a Dynamic Geomechanical Prediction Framework (DGPF) integrated with a novel Adaptive Learning-Informed Simulation (ALIS) strategy. The DGPF combines physics-informed simulations with data-driven corrections, leveraging finite element modeling and machine learning techniques to capture intricate soil-tunnel interactions. The ALIS strategy enhances model adaptability and efficiency by incorporating real-time monitoring data, adaptive parameter calibration, and multi-fidelity modeling. This study introduces a low-power intelligent framework for railway tunnel settlement prediction, leveraging TinyML to enhance scalability and energy efficiency. By integrating physics-informed simulations with data-driven corrections through a Dynamic Geomechanical Prediction Framework (DGPF), the proposed approach addresses the nonlinear complexities of settlement processes. The framework achieves a 35% reduction in prediction errors and a 50% improvement in computational efficiency compared to traditional methods. Experimental results demonstrate its practical applicability for real-time settlement monitoring in safety-critical geotechnical engineering scenarios.</div></div>","PeriodicalId":50630,"journal":{"name":"Computers & Electrical Engineering","volume":"123 ","pages":"Article 110197"},"PeriodicalIF":4.0,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143562477","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"On-chip kernel-based spatial filter for CMOS image sensor","authors":"Bárbaro Maykel López-Portilla Vigil ,&nbsp;Wladimir Valenzuela ,&nbsp;Payman Zarkesh-Ha ,&nbsp;Miguel Figueroa","doi":"10.1016/j.compeleceng.2025.110218","DOIUrl":"10.1016/j.compeleceng.2025.110218","url":null,"abstract":"<div><div>The Internet of Things is transforming our interactions with the world. CMOS Image Sensors are crucial components in multimedia applications for the Internet of Things. They allow IoT devices to perceive, interpret, and respond to the physical world, improving efficiency, safety, and convenience across various industries. The images captured by these sensors are sent to an external digital device for processing. This data flow can result in high power consumption, limit the frame rate, and restrict the parallelization of algorithm data. This paper introduces a new CMOS Smart Imaging Sensor architecture that performs kernel-based spatial filtering at the pixel level, overcoming the drawbacks above. The design proposal enables spatial filtering using a single kernel, two different kernels on the same image, or two cascaded kernels. The circuit calculates the absolute value of the single convolution in parallel at each pixel using simple arithmetic operations within a neighborhood during photocurrent integration. This process is repeated when the filter requires more than one kernel. We designed a 128 × 128-pixel imager in a <span><math><mrow><mn>0</mn><mo>.</mo><mn>35</mn><mspace></mspace><mi>μ</mi><mi>m</mi></mrow></math></span> CMOS process and validated it through post-layout simulations. According to these simulations, the kernel-based spatial filter circuit is integrated into the imager, which processes images at frame rates ranging from 746 to 752 fps. Our CMOS implementation outperforms state-of-the-art circuits in denoising, with the best result: a Mean Squared Error of 0.90, Peak Signal Noise Ratio of 48.55 dB, and Structural Similarity Index Metric of 0.99 configured as the mean filter. Additionally, it demonstrates comparable performance in edge detection to state-of-the-art circuits. The best results were achieved with a Mean Squared Error of 4.68, a Peak Signal to Noise Ratio of 41.42 dB, and a Structural Similarity Index Metric of 0.97, using the y-direction Robert filter. Our proposed circuit demonstrated good edge-location accuracy, with a value of 0.99 for the Sobel filter, which is one of the best results according to the Pratt Figure of Merit.</div></div>","PeriodicalId":50630,"journal":{"name":"Computers & Electrical Engineering","volume":"123 ","pages":"Article 110218"},"PeriodicalIF":4.0,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143562476","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dynamic multiphase DDoS attack identification and mitigation framework to secure SDN-based fog-empowered consumer IoT Networks","authors":"Pooja Chaudhary ,&nbsp;A.K. Singh ,&nbsp;B.B. Gupta","doi":"10.1016/j.compeleceng.2025.110226","DOIUrl":"10.1016/j.compeleceng.2025.110226","url":null,"abstract":"<div><div>The rapid growth of Consumer-Internet-of-Things (CIoT) devices has introduced critical vulnerabilities, making them susceptible to Distributed Denial-of-Service (DDoS) attacks. This paper proposes a multi-phase framework for detecting and mitigating DDoS attacks in Software-Defined Networking (SDN)-based fog-enabled IoT networks (SD-FCIoT). The framework combines entropy-based anomaly detection with machine learning for accurate and timely attack identification. Dynamic thresholding using Chebyshev’s inequality ensures adaptability to network changes, while an attribute selection algorithm using symmetrical uncertainty and k-means clustering enhances classification accuracy. Experiments conducted in a simulated SD-FCIoT environment and with the BoT-IoT dataset demonstrate the framework’s effectiveness. Random Forest (RF) achieved 98.71% accuracy for binary classification and excelled in multi-class attack detection, including Ping Flood and TCP-SYN Flood attacks. The attribute selection algorithm improved detection accuracy by 1.22% and reduced false positives. Furthermore, the fog-enabled architecture lowered response time by 35% compared to centralized systems. These results highlight the framework’s scalability and efficiency in securing CIoT networks against diverse DDoS attacks.</div></div>","PeriodicalId":50630,"journal":{"name":"Computers & Electrical Engineering","volume":"123 ","pages":"Article 110226"},"PeriodicalIF":4.0,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143547125","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"FIDO-enabled universal authenticator with Web usability and privacy preservation","authors":"Wen-Wei Li ,&nbsp;Kuo-Hui Yeh ,&nbsp;Yan-Sing Ji ,&nbsp;Shi-Cho Cha","doi":"10.1016/j.compeleceng.2025.110201","DOIUrl":"10.1016/j.compeleceng.2025.110201","url":null,"abstract":"<div><div>More and more organizations adopt strong authentication schemes, such as multi-factor authentication (MFA) and hardware-based means, to enhance application security instead of ID/password. When using the hardware-based authentication methods, users are required to carry hardware authenticators. Then, application systems communicate with the authenticators to authenticate their owners with the credentials stored in the authenticators or the authenticators themselves. For Web-based applications, people may need to install extra components for application servers to communicate with user authenticators. In this case, W3C and Fido alliances have issued the WebAuthn specifications. Therefore, application servers can communicate with user authenticators through the Bluetooth, near-field communication (NFC), or other standard means via web browsers without additional components. However, the current WebAuthn specification does not consider the scenario of using personal identification cards. While some researchers have proposed enhancements by incorporating additional software, these solutions can decrease usability and increase complexity. This study focuses on the scenario that uses personal identification cards as authenticators to access Web applications. In light of this, this study proposes a means to implement WebAuthn and FIDO specifications in personal identification cards called FIDO-enabled universal authenticator. With the support of WebAuthn, Web applications adopt strong authentication schemes to authenticate users without installing extra software. However, the existing WebAuthn specification lacks provisions for scenarios involving personal identification cards. To address privacy concerns, the proposed system adopts a one-time verifiable identity for identity providers to preserve user privacy. Additionally, we demonstrate the feasibility of implementing the dedicated authenticator with an NFC-based smart card corresponding with FIDO-supported Web applications.</div></div>","PeriodicalId":50630,"journal":{"name":"Computers & Electrical Engineering","volume":"123 ","pages":"Article 110201"},"PeriodicalIF":4.0,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143562473","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}