{"title":"Mixed Time/Event-Triggered Model Predictive Tracking Control for Networked Mobile Robots","authors":"Huixin Liu;Yonghua Lai;Hongsong Lian;Guobin Wang;Dongsheng Zheng","doi":"10.1109/ACCESS.2025.3589791","DOIUrl":"https://doi.org/10.1109/ACCESS.2025.3589791","url":null,"abstract":"Focusing on the tracking control challenges in networked mobile robot systems, this research formulates a mixed time/event-triggered model predictive control (MPC) method. The method integrates time-triggered and event-triggered mechanisms, where the time-triggered module improves the performance of the MPC, and the event-triggered module reduces the resource consumption without sacrificing the control performance. The MPC algorithm is developed based on the auxiliary optimization problem (OP), which is constrained by linear matrix inequalities. The feasibility of the auxiliary OP is evaluated, and the mean square stability of the closed-loop system is investigated. The research results are expected to save network resources while ensuring the performance of networked mobile robots and provide strong support for practical applications of networked mobile robots.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"13 ","pages":"128582-128591"},"PeriodicalIF":3.4,"publicationDate":"2025-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11082117","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144705005","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}
IEEE AccessPub Date : 2025-07-16DOI: 10.1109/ACCESS.2025.3589778
Marek Vaško;Adam Herout
{"title":"LossFIQA: A Shortcut Solution to Image Quality Assessment Using Loss for Faces and Beyond","authors":"Marek Vaško;Adam Herout","doi":"10.1109/ACCESS.2025.3589778","DOIUrl":"https://doi.org/10.1109/ACCESS.2025.3589778","url":null,"abstract":"We introduce a novel approach to model-based quality assessment of input images. Our approach is very simple, and we demonstrate experimentally that it is not limited to a single domain (typically face recognition in the literature). Our approach generates per-sample quality pseudo-labels directly from the objective function used during the training of the target model. We evaluate the proposed method on eight large and respected datasets (from the face recognition on LFW, CALFW, CPLFW, XQLFW, CFP-FP, AgeDB, IJB-C, and retinopathy detection domain on EyePACS dataset) and using multiple state-of-the-art models (AdaFace, MagFace, ArcFace, ElasticFace, and CuricularFace). Compared to state-of-the-art methods for face quality assessment that are considerably more complex, our solution yields competitive results while being much simpler and not limited to one application.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"13 ","pages":"126915-126924"},"PeriodicalIF":3.4,"publicationDate":"2025-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11082134","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144705008","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}
IEEE AccessPub Date : 2025-07-16DOI: 10.1109/ACCESS.2025.3589884
Kuang-Hsuan Huang;Yen-Sheng Chen
{"title":"Broadband Low-Cost Microstrip Arrays for Water-Level Radar With Frequency-Stable Beams and Side-Sector Sidelobe Suppression","authors":"Kuang-Hsuan Huang;Yen-Sheng Chen","doi":"10.1109/ACCESS.2025.3589884","DOIUrl":"https://doi.org/10.1109/ACCESS.2025.3589884","url":null,"abstract":"Water-level radar systems often rely on horn or lens antennas to achieve narrow-beam coverage and high gain, but scaling these designs for bistatic setups significantly increases size and installation complexity. This paper addresses these challenges by introducing a single-layer microstrip patch array, fabricated on a standard printed circuit board (PCB) substrate and fed by only uniform excitations, for bistatic water-level radar. The key novelty lies in systematically comparing two widely used feed architectures—series-fed and planar-fed—while demonstrating that the planar-fed structure not only avoids the beam steering observed in series-fed arrays but also achieves side-sector sidelobe suppression without complex amplitude tapers. A <inline-formula> <tex-math>$16times 16$ </tex-math></inline-formula> planar-fed prototype demonstrates wide impedance and 3-dB gain bandwidths, near-constant beamwidth across its operational range, and suppressed side-sector sidelobes, marking a clear improvement over earlier microstrip arrays that rely on amplitude tapers or show frequency-dependent beam steering. These results confirm that uniform excitation is sufficient for maintaining broadside radiation and controlling sidelobes, offering a compact, broadband, and low-cost alternative to large horn assemblies. This work thus provides an effective solution that bridges theoretical array concepts and real-world radar deployment, meeting the stringent needs of water-level monitoring.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"13 ","pages":"125348-125358"},"PeriodicalIF":3.4,"publicationDate":"2025-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11082113","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144687727","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}
IEEE AccessPub Date : 2025-07-16DOI: 10.1109/ACCESS.2025.3589572
Le Nam Pham;Quoc Dung Phan;Nho-van Nguyen
{"title":"Simplified Carrier-Based SVDPWM Methods Using Reduced Common Mode Voltage Vector Redundancy for Improving Output Current Ripple in Four-Level NPC Inverter","authors":"Le Nam Pham;Quoc Dung Phan;Nho-van Nguyen","doi":"10.1109/ACCESS.2025.3589572","DOIUrl":"https://doi.org/10.1109/ACCESS.2025.3589572","url":null,"abstract":"In this article, new fast and Three-level reduced common-mode voltage (RCMV) space vector Discontinuous pulse width modulation (SVDPWM) strategies are proposed to achieve high performance in four-level neutral point clamped (4L-NPC) inverters. Redundant reduced common-mode voltage (RCMV) vectors in the space vector diagram (SVD) of the Four-level inverter are utilized to design three discontinuous pulse width modulation (DPWM) control strategies with Three-level CMV (3L-CMV) characteristic, SVDPWM0, SVDPWM1 and HSVDPWM. The last and best one is deduced based on harmonic flux and harmonic distortion factor (HDF) analysis, to improve the output current ripple. For analysis and easy implementation, the SVPWM of the four-level inverter will be solved in the two-level SVD. A simple carrier-based PWM implementation of the RCMV SVDPWM methods will be developed to reduce the computational burden. The proposed 3L-CMV methods significantly reduce harmonic distortion compared to both Two-level CMV (2L-CMV) and Four-level CMV (4L-CMV) SVPWM methods. They exhibit a reduction in peak-to-peak CMV from approximately 40% to 60% and a lower CMV magnitude in the sampling frequency component compared to the 4L-CMV methods. As a result, the proposed system exhibits a considerable reduction in RMS leakage current. Additionally, they can achieve a reduction in switching loss up to 40% in specific conditions, offering improved efficiency compared to continuous PWM schemes.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"13 ","pages":"124962-124978"},"PeriodicalIF":3.4,"publicationDate":"2025-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11082150","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144680813","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}
IEEE AccessPub Date : 2025-07-16DOI: 10.1109/ACCESS.2025.3589882
Sun Jiandong;Chen Jiabei;Gong Songtao;Xu Zhiwei;You Shixun
{"title":"Dynamic Efficiency Analysis of Airborne Cross-Eye Jamming Operations","authors":"Sun Jiandong;Chen Jiabei;Gong Songtao;Xu Zhiwei;You Shixun","doi":"10.1109/ACCESS.2025.3589882","DOIUrl":"https://doi.org/10.1109/ACCESS.2025.3589882","url":null,"abstract":"Cross-eye jamming represents an effective angle deception technique against monopulse seekers, capable of electromagnetic jamming against precision-guided weapons deployed on airborne platforms. While existing research primarily concentrates on minimizing the amplitude and phase tolerance of cross-eye jamming to enhance jammer performance, it often overlooks in-depth analysis of its practical combat application, leading to fragmented and nonspecific evaluations of its combat effectiveness. This study decouples the amplitude and phase error composition characteristics of an airborne retrodirective cross-eye jamming prototype by conducting a thorough analysis of its system architecture and jamming signal generation principles. Additionally, it introduces a vector guidance algorithm incorporating physical constraints to model and assess the combat effectiveness of cross-eye jamming in dynamic operational scenarios. To validate the scientific robustness of the research findings, a comprehensive verification framework is established, integrating numerical simulations and air interface experiments. Through the systematic combination of diverse experimental configurations, this research summarizes and proposes a methodology for analyzing the hardware specifications and combat effectiveness baseline of cross-eye jamming systems.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"13 ","pages":"125982-125992"},"PeriodicalIF":3.4,"publicationDate":"2025-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11082118","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144687627","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}
IEEE AccessPub Date : 2025-07-16DOI: 10.1109/ACCESS.2025.3589957
Natan de Souza Rodrigues;Célia Ghedini Ralha
{"title":"A Flexible and Configurable System to Author Name Disambiguation","authors":"Natan de Souza Rodrigues;Célia Ghedini Ralha","doi":"10.1109/ACCESS.2025.3589957","DOIUrl":"https://doi.org/10.1109/ACCESS.2025.3589957","url":null,"abstract":"Author Name Disambiguation (AND) is critical in maintaining the integrity of bibliographic databases, especially under data sparsity and large-scale ambiguity. This paper introduces a configurable and scalable AND system that combines transformer-based embeddings (MiniLM), Graph Convolutional Networks (GCN), and hierarchical clustering. The framework enables fine-grained parameterization of GCN depth, training epochs, and embedding models to adapt to datasets with varying structural and semantic complexity. Extensive evaluations on three benchmark datasets, including AMiner-12, DBLP, and LAGOS-AND, demonstrate consistent improvements over state-of-the-art baselines. On DBLP, our system achieves a pF1 of 0.878 and a K-Metric of 0.976, outperforming prior work by over 15% and 20%, respectively. On AMiner-12, despite sparse metadata, the method attains a 13.8% gain in average cluster purity and 10.1% in K-Metric. On the large-scale LAGOS-AND dataset, the system reaches a B-cubed F1-score of 0.908, surpassing the best-reported baseline by more than 9%. These results validate the system’s ability to integrate semantic and relational signals for robust and accurate AND across diverse contexts.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"13 ","pages":"125606-125617"},"PeriodicalIF":3.4,"publicationDate":"2025-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11082132","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144687726","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}
{"title":"3D-Printed Lightweight Metamaterial Absorber Using Rectangular Perforations","authors":"Junhyuk Ahn;Heeju Jwa;Minjun Kim;Yongwoo Cho;Kyounghwan Kim;Prabhakar Jepiti;Sungjoon Lim","doi":"10.1109/ACCESS.2025.3589588","DOIUrl":"https://doi.org/10.1109/ACCESS.2025.3589588","url":null,"abstract":"Metamaterial absorbers (MMAs) are designed to achieve near-total absorption of electromagnetic radiation. In radio-frequency fields, MMAs exhibit absorption behavior that stems from RF resonance. Thus, MMAs are useful in fields such as stealth coatings. However, the use of MMA unit cells for stealth applications is limited due to their heavy weight. In this paper, we demonstrate that a weight reduction of up to 61.31% and a 66.22% decrease in PLA volume can be achieved in a Jerusalem Cross MMA unit cell, with minimal impact on key absorptive properties such as resonant frequency and absorptivity. This was accomplished by selectively removing material from the corners and near-edge regions of the dielectric layer within the unit cell. The simulation results were verified with an array consisting of <inline-formula> <tex-math>$12times 12$ </tex-math></inline-formula> MMA unit cells, where resonant behavior was observed at 10.33 GHz with an absorptivity of 99.84%. Polylactic acid was used as the dielectric material for 3D printing, and the conductive surfaces were fabricated using silver paste. The results of this study demonstrate the feasibility of lightweight MMA designs for real-life applications.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"13 ","pages":"126299-126306"},"PeriodicalIF":3.4,"publicationDate":"2025-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11082148","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144687706","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}
IEEE AccessPub Date : 2025-07-16DOI: 10.1109/ACCESS.2025.3589619
Md. Nasif Safwan;Souhardo Rahman;Mahamodul Hasan Mahadi;Md Iftekharul Mobin;Taharat Muhammad Jabir;Zeyar Aung;M. F. Mridha
{"title":"T3SSLNet: Triple-Method Self-Supervised Learning for Enhanced Brain Tumor Classification in MRI","authors":"Md. Nasif Safwan;Souhardo Rahman;Mahamodul Hasan Mahadi;Md Iftekharul Mobin;Taharat Muhammad Jabir;Zeyar Aung;M. F. Mridha","doi":"10.1109/ACCESS.2025.3589619","DOIUrl":"https://doi.org/10.1109/ACCESS.2025.3589619","url":null,"abstract":"Classification of brain tumors from MRI images is crucial for early diagnosis and effective treatment planning. However, there are still obstacles to overcome, including low image quality, sparsely labeled data, and variability in tumor characteristics. In this study, we explored the use of self-supervised learning techniques to improve the classification performance for brain tumors. Specifically, we tested three SSL approaches SimCLR, MoCo, and BYOL, with ResNet-50 as the backbone architecture on a newly constructed dataset created by combining five public datasets. We further extended our work by integrating EfficientNet to evaluate its computational efficiency, demonstrating its feasibility for low-processor systems. We introduce T3SSLNet, a novel framework consisting of four key components: the imaging spectrum enhancement block for data augmentation, the Frozen Feature Extractor block for hierarchical feature extraction, Neural Representation Projection Learning block for contrastive-positive pair learning, and Unfrozen Classification block for tumor classification. Our experimental results paired with ResNet-50 indicate that, without fine-tuning, MoCo achieved the highest accuracy at 95.76%, followed by SimCLR at 92.25% and BYOL at 81.80%. Following fine-tuning, BYOL showed a significant improvement, reaching 96.42%, while MoCo and SimCLR reached 96.87% and 97.02%, respectively.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"13 ","pages":"127852-127867"},"PeriodicalIF":3.4,"publicationDate":"2025-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11082144","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144704930","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}
{"title":"pwnobd: Offensive Cybersecurity Toolkit for Vulnerability Analysis and Penetration Testing of OBD-II Devices","authors":"Roberto Gesteira-Miñarro;Ignacio Gutiérrez;Rafael Palacios;Gregorio López","doi":"10.1109/ACCESS.2025.3589867","DOIUrl":"https://doi.org/10.1109/ACCESS.2025.3589867","url":null,"abstract":"The research field of vehicle cybersecurity has experienced a significant growth in interest due to the attack surface that the information systems comprising a vehicle provides and the ever-expanding body of regulations that provide special focus on cybersecurity on vehicular systems. Of particular interest is the attack surface exposed by OBD dongles, wireless devices that connect to the vehicle’s diagnostic port, whose access to the vehicle’s CAN buses could potentially be exploited by adversaries. However, acquiring a vehicle for use in the security assessment of these devices may not be possible for the researcher. In this article, we propose a software tool, <monospace>pwnobd</monospace>, that assists in developing proof-of-concept attacks seeking to take advantage of the found vulnerabilities, alongside an architecture for a research and demonstration platform that provides a testbed for vulnerability analysis and penetration testing for attacks towards these devices. A small battery of tests is then performed on several diagnostic devices using this platform, along with a focused study on one such device, proving the potential benefit of such platform for security researchers.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"13 ","pages":"126925-126934"},"PeriodicalIF":3.4,"publicationDate":"2025-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11082116","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144704905","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}
IEEE AccessPub Date : 2025-07-16DOI: 10.1109/ACCESS.2025.3589175
Norah A. Al-Johany;Fathy E. Eassa;Sanaa A. Sharaf;Eynas H. Balkhair;Sara M. Assiri
{"title":"Defect Detection and Correction in OpenMP: A Static Analysis and Machine Learning-Based Solution","authors":"Norah A. Al-Johany;Fathy E. Eassa;Sanaa A. Sharaf;Eynas H. Balkhair;Sara M. Assiri","doi":"10.1109/ACCESS.2025.3589175","DOIUrl":"https://doi.org/10.1109/ACCESS.2025.3589175","url":null,"abstract":"Concurrency defects such as race conditions, deadlocks, and improper synchronization remain a critical challenge in developing reliable OpenMP-based parallel applications. Traditional static analysis tools often focus only on defect detection, offering limited or no automated correction capabilities. This paper presents a novel static analysis tool designed to detect and automatically correct concurrency-related defects in OpenMP programs. The tool performs lexical and syntactic analysis to extract OpenMP constructs, verify directive usage, and identify incorrect synchronization patterns. A rule-based correction engine is employed to repair detected defects through minimally invasive code transformations, such as inserting critical sections, correcting directive placement, and adjusting data-sharing clauses. To enhance predictive accuracy, the tool incorporates machine learning classifiers—Naive Bayes (NB), Decision Tree (DT), Random Forest (RF), and Linear Support Vector Machine (LSVM)—trained on various feature combinations, including Abstract Features (AF), Halstead Features (HF), and Semantic Features (SF). Evaluation results show that NB and LSVM achieved up to 99% accuracy with simple feature sets, while DT and RF exhibited lower performance across all combinations. The tool was validated on a curated dataset of annotated OpenMP programs, achieving a 99.15% correction rate with minimal execution overhead. These results confirm the effectiveness and practicality of the proposed solution in improving the correctness and maintainability of OpenMP applications. This work bridges the gap between static defect detection and automated correction, contributing a scalable and intelligent approach to reliable parallel software development.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"13 ","pages":"125499-125525"},"PeriodicalIF":3.4,"publicationDate":"2025-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11082155","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144687645","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}