IEEE Access最新文献

{"title":"Intelligent Dispatch-Based Optimization of Hybrid Renewable Architectures Incorporating Electric Mobility and Hydrogen Storage for Commercial Energy Systems","authors":"Ehab S. Ali;M. H. Elkholy;Tomonobu Senjyu;Sahar M. Abd Elazim;Emad S. Hassan;Badr M. Al Faiya;Mohammed Elsayed Lotfy","doi":"10.1109/ACCESS.2026.3661790","DOIUrl":"https://doi.org/10.1109/ACCESS.2026.3661790","url":null,"abstract":"This study proposes a high-fidelity hybrid renewable energy system (HRES) designed and optimized for AEON Mall Okinawa Rycom, targeting the challenges posed by dynamic energy demand and strict reliability requirements in large commercial facilities. The proposed system integrates PV generation, wind turbines (WT), battery energy storage systems (BESS), hydrogen energy storage systems (HESS), and electric vehicles (EVs) with vehicle-to-grid (V2G) capability. A real-time energy management framework is implemented on a field-programmable gate array (FPGA), enabling deterministic control with microsecond-level response and parallel coordination of multiple energy resources. The IbI Logics Algorithm (ILA) is embedded in the FPGA to perform multi-objective energy scheduling, storage dispatch, and operating cost minimization under dynamic load and environmental conditions. Four system configurations are evaluated based on technical, economic, and environmental performance metrics. The PV–WT–BESS–HESS configuration demonstrates the most balanced overall performance, with a total annualized cost (TAC) of 3,121,900 USD. The PV–WT–BESS configuration achieves the lowest TAC of 1,422,600 USD, corresponding to a 54.4% reduction relative to the most expensive configuration, which combines EV-based storage and hydrogen systems with a TAC of 4,837,600 USD. The PV–WT–HESS configuration yields a TAC of 4,493,100 USD, representing an 8.2% reduction compared to the EV-based case. Overall, the results indicate that FPGA-based fast-response energy management enhances the robustness, scalability, and economic viability of high-fidelity HRES for modern commercial infrastructure.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"14 ","pages":"22178-22210"},"PeriodicalIF":3.6,"publicationDate":"2026-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11373164","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146175663","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":"Soil Moisture Estimation From Spire GNSS-Reflectometry Reflectivity: Semi-Empirical and Linear Regression Methods","authors":"Jiahua Zhang;Jan-Peter Weiss;John J. Braun;Ming Li;William Gullotta;Maggie Sleziak-Sallee","doi":"10.1109/ACCESS.2026.3661820","DOIUrl":"https://doi.org/10.1109/ACCESS.2026.3661820","url":null,"abstract":"This study develops semi-empirical and linear regression algorithms to estimate near-surface soil moisture (SM) using reflectivity observations of Global Navigation Satellite System reflection (GNSS-R) signals collected by Spire Global commercial satellites. The semi-empirical method employs a forward model of GNSS-R reflectivity considering soil dielectric properties, vegetation attenuation, and surface roughness effects. As direct roughness measurements are unavailable globally, we obtain effective roughness attenuation maps using Cyclone GNSS (CYGNSS) reflectivity and SMAP SM and vegetation optical depth (VOD) data. Systematic biases between Spire and CYGNSS observations are also characterized and corrected. Daily gridded corrected Spire reflectivity observations at a 36-km resolution are used to invert soil dielectric permittivity and then SM. Linear regression parameters are also determined by correlating corrected Spire reflectivity measurements to SMAP SM data for each grid. Both algorithms are applied to six months of Spire data from late Jan to Jul 2024 and evaluated over Australia. The linear regression approach achieves better overall agreement with SMAP (correlation coefficient: 0.85, root mean squared difference (RMSD): 0.05 cm3/cm3) compared to the semi-empirical method (correlation: 0.64, RMSD: 0.07 cm3/cm3). The semi-emprical method demonstrates relatively better accuracy over sparsely vegetated regions with RMSD smaller than 0.06 cm3/cm3. Both methods show degraded performance over dense vegetation. Improved characterization of vegetation and surface roughness effects is essential to enhance retrieval accuracy. This work contributes to positioning GNSS-R as a complementary technology for independent SM observations.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"14 ","pages":"22162-22177"},"PeriodicalIF":3.6,"publicationDate":"2026-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11373179","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146175686","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":"Lightweight Fault-Resilient KLEIN Cipher for IoT Encryption","authors":"Nada Maatallah;Ali Abdelli;Wajih El Hadj Youssef;Lazhar Khriji;Mohsen Machhout","doi":"10.1109/ACCESS.2026.3662133","DOIUrl":"https://doi.org/10.1109/ACCESS.2026.3662133","url":null,"abstract":"The KLEIN lightweight block cipher provides an effective encryption method suitable for IoT devices with limited computational resources, memory, and energy capacity. Despite its efficiency, the compact design of KLEIN is vulnerable to fault injection attacks, which can disrupt encryption and compromise data security. In this study, we propose a comprehensive fault detection and correction framework for KLEIN that combines parity verification, cyclic redundancy checks (CRC), and a Secure Rollback Recovery mechanism with deceptive output. This approach enables real-time fault identification, produces misleading ciphertext to thwart attackers, and restores the system to the last known correct state, ensuring uninterrupted and reliable encryption. The framework was implemented on an FPGA using Vivado 2022 and validated under various fault scenarios. Results show that the design achieves high fault coverage while maintaining efficiency, with only a 1.73% reduction in operating frequency for detection, a 1.13% hardware overhead for fault detection and a 66.28% increase in hardware area for correction. Overall, the proposed solution significantly strengthens KLEIN against fault injection threats, providing a secure and lightweight cryptographic option for resource-constrained IoT applications.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"14 ","pages":"22404-22416"},"PeriodicalIF":3.6,"publicationDate":"2026-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11373712","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146175604","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":"EV Charging and V2G Operation for Distribution System VPP Including Model Predictive Control","authors":"Rosemary E. Alden;Simone Silvestri;Malcolm McCulloch;Dan M. Ionel","doi":"10.1109/ACCESS.2026.3660975","DOIUrl":"https://doi.org/10.1109/ACCESS.2026.3660975","url":null,"abstract":"Future smart grid virtual power plants (VPPs) are considered for development based on industry communication standards for electric vehicle (EV) chargers such as Open Charge Point Protocol (OCPP), IEC 15118, and IEC 61851. To support research and development of computationally intelligent controls for distributed EV batteries, a python-based API OpenDSS VPP framework is utilized with thousands of experimental smart meter profiles, the IEEE 123 node test feeder, and hundreds of national survey-based EV modules for conventional and optimal charging and vehicle-to-grid (V2G) control development to mitigate any voltage violations and reduce peak load. A methodology is proposed for model-predictive control (MPC) optimization considering power flow calculations for physical network impacts as part of the objective function for each candidate design. It is simulated in a first approach to minimize utility cost and obtain a near-constant substation load. Within the combined experimental and synthetic neighborhood, natural disaster shark-curve type charging events and typical patterns are evaluated through the newly proposed terms of “EV hourly and daily homogeneity” to find adverse effects starting at 20% and 50%, respectively with a sensitivity study showing up to 1.45MWh increase of system losses during maximum overlap. Reductions up to 26% in cost during the VPP time window are found given assumptions for CA, USA retail rate and EV owner compensation. In the second formulation, a multi-objective problem to minimize both system losses and the substation load to a near constant with 5% tolerance and 45% reduction in system losses, i.e. 135 and 40kW respectively, shows the power saving benefits of VPP operation beyond cost reductions.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"14 ","pages":"26784-26796"},"PeriodicalIF":3.6,"publicationDate":"2026-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11372698","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146223646","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":"Evaluating MVDC and Superconducting Solutions for High-Voltage Grid Integration","authors":"Katharina Hetzenecker;Anton MeißEn;Maxim Müllender;Rik W. De Doncker;Andreas Ulbig;Matthias Schilcher","doi":"10.1109/ACCESS.2026.3662143","DOIUrl":"https://doi.org/10.1109/ACCESS.2026.3662143","url":null,"abstract":"In recent years, the integration of renewable energy sources into power grids has gained significant importance, leading to an increased demand for innovative solutions to enhance transmission and distribution infrastructure. This paper evaluates the potential of medium-voltage direct current (MVDC) and superconducting technologies to optimize high-voltage grid integration. The focus is on the economic analysis of both technologies and their characteristics in grid operation compared to conventional ac solutions. Through the examination of converter topologies, cooling requirements, and cost analyses, it becomes evident that MVDC systems offer flexible responsiveness to load changes, while superconducting cables provide benefits in urban applications due to their high current density and reduced losses. The results reveal significant differences between the investigated connection concepts, with the dc concept standing out as the only option capable of maintaining voltage compliance in all scenarios. These findings underscore the necessity for further research into the implementation of these technologies in future power grids.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"14 ","pages":"22417-22433"},"PeriodicalIF":3.6,"publicationDate":"2026-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11373537","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146175627","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":"A Two-Stage Decomposition-Grouping Strategy for Multi-Aircraft Weight and Balance Optimization of Non-ULD","authors":"Yunfei Li;Jihui Xu","doi":"10.1109/ACCESS.2026.3661795","DOIUrl":"https://doi.org/10.1109/ACCESS.2026.3661795","url":null,"abstract":"This study investigates the weight balance problem in loading non-unit load devices (non-ULDs) for multi-aircraft. A two-stage weight balance optimization model was developed for multi-aircraft non-ULDs loading. The first stage involves a two-dimensional geometric constraint model for distributing non-ULDs positions, considering their constraints, with multi-objectives of maximizing aircraft cargo hold area utilization and payload, and minimizing aircraft sorties. The second stage is a weight and balance model for adjusting non-ULDs positions, considering various aircraft constraints. Two solution strategies are designed: first, decomposing the two-stage model into a two-dimensional geometric constraint model and a weight balance constraint model via logical checks; second, a grouping strategy that combines non-ULDs in pairs to form blocks. Using Gurobi, two scenarios with different combined solution strategies were verified for the B747F aircraft. The results indicate that, for large scale instances with a given number of non-ULD, the Gurobi decomposition with grouping delivers the best balance of solution quality and solving speed. On average, cargo hold utilization is 58.59%, the number of aircraft sorties is 11.25, and solver time is 108.19 s. Directly solving with Gurobi performs worse, with cargo hold utilization of 45.04%, the number of aircraft sorties is 13.75, and solver time of 1,689.29 s. The results from the Gurobi grouping strategy are very close to those from the Gurobi decomposition with grouping strategy, with averages of 58.59% cargo hold utilization, the number of aircraft sorties is 11.25, and 76.62 s for solver time. In contrast, the Gurobi decomposition strategy yields averages of 44.95% cargo hold utilization, the number of aircraft sorties is 13.75, and 957.28 s of solver time. All methods delivered an average payload of 1,154,489 kg for 11.25 to 13.75 sorties. The proposed model can realize the loading of batch non-ULDs across multi-aircraft. Relative to the decomposition strategy, the designed grouping strategy substantially accelerates solving time while maintaining competitive solution quality.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"14 ","pages":"34493-34509"},"PeriodicalIF":3.6,"publicationDate":"2026-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11373166","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147362276","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":"Developing a High-Resolution Lane-Change Trajectory Prediction Model by Combination of Graphic Neural Network and Transformer","authors":"Wei Lei;Jiaying Zheng;Changchang Li;Yonghai He;Yanli Jiao;Mingmin Han","doi":"10.1109/ACCESS.2026.3662049","DOIUrl":"https://doi.org/10.1109/ACCESS.2026.3662049","url":null,"abstract":"Accurate vehicle trajectory prediction is critical for improving traffic safety and operational efficiency, yet remains challenging in complex traffic environments due to dynamic inter-vehicle interactions and diverse driving behaviors. This paper proposes a GCN-Transformer framework that integrates Graph Convolutional Networks (GCNs) with Transformer architectures to jointly model spatial interactions among vehicles and temporal motion dependencies. The framework adopts a two-stage strategy, in which a Temporal Enhanced Graph Attention Network (TE-GAT) is first used to infer lane-change intentions, followed by trajectory prediction that incorporates dynamic traffic and motion features. The proposed approach is evaluated on the High D dataset and real-world data collected from the Nanjing Inner Ring South Line. Quantitative results demonstrate that the proposed GCN-Transformer consistently outperforms classical and learning-based baselines across different traffic conditions, achieving a 61.7% reduction in RMSE compared with the CTRA model and a 46.1% reduction compared with CS-LSTM at a 5-s prediction horizon. In transition and congested traffic scenarios, the optimal model achieves RMSE and ADE values of 0.647 and 0.568, respectively, indicating strong robustness and generalization capability in complex traffic environments.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"14 ","pages":"22457-22473"},"PeriodicalIF":3.6,"publicationDate":"2026-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11373366","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146175629","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":"A Resilient Coordination Framework for Fresh Product Supply Chains Using Quantity Flexibility Contracts","authors":"Niloofar Abdolmaleki;Babak Javadi;Hossein Mohammadi Dolat-Abadi;Fatemeh Yazdi;Mohammad Reza Abdali","doi":"10.1109/ACCESS.2026.3660707","DOIUrl":"https://doi.org/10.1109/ACCESS.2026.3660707","url":null,"abstract":"This study presents a coordinated decision-making framework for the fresh product supply chain by leveraging a quantity flexibility (QF) contract to enhance system-wide resilience. The proposed model incorporates a backup supplier to mitigate potential disruptions and investigates optimal ordering and pricing strategies under both decentralized and coordinated settings. A Stackelberg game-theoretic approach is employed, modeling the supplier as the leader and the retailer as the follower in a hierarchical decision structure. Analytical and numerical results reveal that the coordinated model not only increases the profitability of individual entities—namely, the retailer and the backup supplier—but also improves the overall supply chain performance, particularly under low-disruption probability scenarios. This research contributes to the body of knowledge on fresh product supply chains (FPSC) by introducing a novel integration of QF contracts and resilience strategies, offering actionable insights for practitioners seeking robust coordination mechanisms in perishable goods markets.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"14 ","pages":"26812-26825"},"PeriodicalIF":3.6,"publicationDate":"2026-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11370782","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146223678","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":"Deep Q-Learning With Gradient Target Tracking","authors":"Bumgeun Park;Taeho Lee;Donghwan Lee","doi":"10.1109/ACCESS.2026.3660851","DOIUrl":"https://doi.org/10.1109/ACCESS.2026.3660851","url":null,"abstract":"This paper introduces Q-learning with gradient target tracking, a novel reinforcement learning framework that provides a learned continuous target update mechanism as an alternative to the conventional hard update paradigm. In the standard deep Q-network (DQN), the target network is a copy of the online network’s weights, held fixed for a number of iterations before being periodically replaced via a hard update. While this stabilizes training by providing consistent targets, it introduces a new challenge: the hard update period must be carefully tuned to achieve optimal performance. To address this issue, we propose two gradient-based target update methods: DQN with asymmetric gradient target tracking (AGT2-DQN) and DQN with symmetric gradient target tracking (SGT2-DQN). These methods replace the conventional hard target updates with continuous and structured updates using gradient descent, which effectively eliminates the need for manual tuning. We provide a theoretical analysis proving the convergence of these methods in tabular settings. Additionally, empirical evaluations demonstrate their advantages over standard DQN baselines, which suggest that gradient-based target updates can serve as an effective alternative to conventional target update mechanisms in Q-learning.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"14 ","pages":"29648-29673"},"PeriodicalIF":3.6,"publicationDate":"2026-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11370783","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147292795","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":"EdgeVLM as a Privacy Filter: Toward Privacy-Aware Activity Recognition From Wearable Camera Using Image Captions","authors":"Koushi Hiraoka;Yugo Nakamura;Yutaka Arakawa","doi":"10.1109/ACCESS.2026.3659343","DOIUrl":"https://doi.org/10.1109/ACCESS.2026.3659343","url":null,"abstract":"Egocentric video captured by wearable cameras offers rich contextual information for recognizing human activities in daily life. However, such video often includes sensitive personal details that must be protected from external threats. This creates a fundamental trade-off between preserving data utility and ensuring privacy, particularly in scenarios where continuous activity monitoring is required. In this study, we explore the concept of using EdgeVLM—a vision-language model designed to run entirely on edge devices—as a privacy filter for wearable camera data. We investigate the impact of caption granularity and demonstrate that our method locally transforms egocentric video into semantically rich textual image captions, enabling activity detection without transmitting raw visual content to the cloud. This edge-based processing preserves contextual cues while minimizing privacy risks through data minimization. To evaluate this approach, we conducted a quantitative user study (N = 88) that found EdgeVLM-generated captions notably decreased participants’ privacy concerns compared to raw, blurred, or cartoonized images. Critically, from a bystander’s perspective, the proposed method demonstrated privacy protection levels statistically comparable to canny edge detection. Additionally, when combined with accelerometer data, the caption-based method achieved a 77.2% accuracy in recognizing desk activities such as typing, mousing, swiping, drinking, and writing—effectively replacing pixel-level visual information with text while maintaining performance comparable to models using unfiltered visuals. These findings indicate that EdgeVLM-based image captioning is a promising privacy-conscious solution for wearable camera applications, facilitating continuous activity recognition while protecting user privacy at the edge.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"14 ","pages":"22445-22456"},"PeriodicalIF":3.6,"publicationDate":"2026-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11367700","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146175624","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}