IEEE Access最新文献_第7页

Robust Optimal Control for a Microbial Batch Culture Processes: Incorporating Free Terminal Time and Sensitivity Analysis 微生物间歇培养过程的鲁棒优化控制：结合自由终端时间和灵敏度分析

IF 3.6 3区计算机科学

IEEE Access Pub Date : 2025-07-24 DOI: 10.1109/ACCESS.2025.3592428

Yang Qi;Zheng Shijin;Xie Suzhen;Feng Enmin

{"title":"Robust Optimal Control for a Microbial Batch Culture Processes: Incorporating Free Terminal Time and Sensitivity Analysis","authors":"Yang Qi;Zheng Shijin;Xie Suzhen;Feng Enmin","doi":"10.1109/ACCESS.2025.3592428","DOIUrl":"https://doi.org/10.1109/ACCESS.2025.3592428","url":null,"abstract":"This paper focuses on the robust optimal control problem of an enzymatic-catalytic dynamic system in batch culture with uncertain parameters. To enhance the productivity of 1,3-propanediol (1,3-PD) in batch culture, we define the initial concentrations of biomass and glycerol as well as the terminal time of the fermentation process as control variables. By considering the nonlinear characteristics of the enzymatic-catalytic system as a primary constraint, we formulate a robust optimal control model that simultaneously evaluates the production efficiency of 1,3-PD and its sensitivity to uncertain parameters. The main objective of this model is to identify an optimal control strategy that not only strengthens the robustness of the system but also maximizes the yield of 1,3-PD. Given that the terminal time of this robust optimal control problem is unfixed and non-standard terms exist in the optimal control formulation, we adopt the time-scale transformation method and introduce an auxiliary dynamic system for calculating system sensitivity. Subsequently, we develop an improved particle swarm optimization algorithm to solve this equivalent problem. Finally, the trade-off between production efficiency and process robustness is systematically assessed through numerical simulations. The results demonstrate that sacrificing a marginal 3.9% of 1,3-PD production efficiency can lead to a 25.3% enhancement in system robustness. The primary contribution of this study lies in proposing a novel control strategy that effectively addresses the uncertainty of system parameters, while enhancing the production efficiency of 1,3-PD and the stability of the production process. The innovation of this control strategy resides in its comprehensive consideration of the impacts of multiple variables on system robustness, providing valuable theoretical support for practical applications.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"13 ","pages":"131303-131313"},"PeriodicalIF":3.6,"publicationDate":"2025-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11095677","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144725290","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}

引用次数: 0

Voltage-Based Load Recognition and Its Integration Into an Application Use Case 基于电压的负载识别及其应用实例集成

IF 3.6 3区计算机科学

IEEE Access Pub Date : 2025-07-24 DOI: 10.1109/ACCESS.2025.3592476

Henning Schlachter;Stefan GeißEndörfer;Holger Behrends;Karsten Von Maydell;Carsten Agert

{"title":"Voltage-Based Load Recognition and Its Integration Into an Application Use Case","authors":"Henning Schlachter;Stefan GeißEndörfer;Holger Behrends;Karsten Von Maydell;Carsten Agert","doi":"10.1109/ACCESS.2025.3592476","DOIUrl":"https://doi.org/10.1109/ACCESS.2025.3592476","url":null,"abstract":"The expansion of renewable energies, the growing number of consumers, e.g., in e-mobility, and their connection to low voltage grids pose new challenges for grid operation, particularly regarding voltage control and energy losses. In this context, comprehensive knowledge about the surrounding grid facilitates the intelligent control of photovoltaic (PV)-battery systems, creating a need to observe grid participants. In that regard, a previously developed load recognition method is successfully applied in a use case to recognize two electric vehicles and a heat pump in a simulative grid environment, yielding an accuracy of around 96%. Considering to couple that method with a subsequent control algorithm, an approach is developed to estimate a virtual voltage signal, which represents the grid voltage without the impact of control actions. It is validated that this enables the effective application of load recognition in control conditions. Finally, it is demonstrated how to integrate the load recognition method into a control setup using the virtual voltage concept. The corresponding control algorithm manages the power flow between a PV-battery system and the grid in conjunction with a static Q(U) algorithm. It leverages the information about active loads with the objectives of maintaining a stable and balanced grid voltage and optimizing energy consumption in the example use case. Thereby, the voltage deviation is reduced by around 26% and the grid unbalance by approximately 38%, compared to only using the Q(U) algorithm without a battery. It can be concluded that the load recognition method can successfully gather information from the surroundings of a grid node even in control applications.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"13 ","pages":"134423-134440"},"PeriodicalIF":3.6,"publicationDate":"2025-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11095713","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144758342","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}

引用次数: 0

Adaptive Passivity-Based Control for DC Motor Speed Regulation in DC-DC Converter-Fed Systems 基于自适应无源控制的直流-直流变换器-馈电系统直流电机调速

IF 3.6 3区计算机科学

IEEE Access Pub Date : 2025-07-24 DOI: 10.1109/ACCESS.2025.3592594

Diego Montoya Acevedo;Ignacio Parraguez-Garrido;Walter Gil-González;Oscar Danilo Montoya;Catalina González-Castaño

{"title":"Adaptive Passivity-Based Control for DC Motor Speed Regulation in DC-DC Converter-Fed Systems","authors":"Diego Montoya Acevedo;Ignacio Parraguez-Garrido;Walter Gil-González;Oscar Danilo Montoya;Catalina González-Castaño","doi":"10.1109/ACCESS.2025.3592594","DOIUrl":"https://doi.org/10.1109/ACCESS.2025.3592594","url":null,"abstract":"This paper presents a unified adaptive passivity-based control strategy using incremental modeling to regulate the angular speed of a DC series motor driven by DC-DC converters operating in both buck and boost configurations. The proposed approach leverages an incremental port-Hamiltonian framework to design control laws that ensure the global asymptotic stability of the closed-loop system. To address the challenge posed by unknown load torques, a nonlinear disturbance observer is incorporated, allowing for the real-time estimation required for an accurate computation of equilibrium points and reference tracking. These theoretical developments are validated through experimental implementation and compared against an inverse optimal control (IOC) strategy. The results show that the proposed IDA-PBC significantly outperforms the IOC in terms of transient response, tracking accuracy, and disturbance rejection. In the buck configuration, the IDA-PBC reduces the rise time by up to 50.24% and completely eliminates the overshoot. Similarly, in the boost configuration, the rise time is improved by 20.63%, with enhanced stability and lower phase lag under sinusoidal tracking. These findings confirm the robustness and effectiveness of the proposed control strategy for real-time applications in electromechanical systems.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"13 ","pages":"131957-131966"},"PeriodicalIF":3.6,"publicationDate":"2025-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11095674","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144725152","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}

引用次数: 0

A Review of Vehicle Dynamics and Control Approaches for Mitigating Motion Sickness in Autonomous Vehicles 自动驾驶汽车动力学与运动病控制方法综述

IF 3.6 3区计算机科学

IEEE Access Pub Date : 2025-07-24 DOI: 10.1109/ACCESS.2025.3592407

Ilhan Yunus;Georgios Papaioannou;Jenny Jerrelind;Lars Drugge

{"title":"A Review of Vehicle Dynamics and Control Approaches for Mitigating Motion Sickness in Autonomous Vehicles","authors":"Ilhan Yunus;Georgios Papaioannou;Jenny Jerrelind;Lars Drugge","doi":"10.1109/ACCESS.2025.3592407","DOIUrl":"https://doi.org/10.1109/ACCESS.2025.3592407","url":null,"abstract":"This study highlights the challenge of motion sickness (MS) in autonomous vehicles (AVs), providing a comprehensive review of assessing, predicting, and preventing this issue with a special focus on vehicle dynamics and control-based approaches. Unlike previous studies, this review bridges the gap between MS prediction models and vehicle dynamics-based mitigation strategies by presenting an integrated perspective. Effective mitigation requires accurate and reliable prediction. In this context, motion-based prediction approaches, recognised for their practicality, cost-effectiveness, and promising results, are examined in detail with particular focus on ISO-based methods and sensory conflict theory-based models. The importance of identifying MS triggers and validating these models experimentally is also emphasised, alongside recent trends in customised approaches addressing individual variability in MS susceptibility. The study then investigates mitigation strategies centred on vehicle dynamics and control systems, due to their potential for directly controlling motion triggers, calling for tailored and integrated approaches. Furthermore, the critical role of trajectory planning and tracking algorithms in mitigating MS is reviewed, emphasising their potential through optimal control and the incorporation of MS metrics into cost functions. Additionally, integrating trajectory planning with active chassis systems is identified as a promising direction for reducing MS. The study concludes by underscoring the importance of optimised, personalised, integrated and connected vehicle dynamics and control-based methods to effectively mitigate MS in AVs. Finally, a future horizons approach, supported by a vision roadmap, is introduced as a means to address current challenges, define research directions, and ultimately advance the adoption of AVs with minimum MS.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"13 ","pages":"132990-133024"},"PeriodicalIF":3.6,"publicationDate":"2025-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11095669","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144750797","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}

引用次数: 0

Robust Prediction of Wildfire Spread in Australia 澳大利亚野火蔓延的可靠预测

IF 3.6 3区计算机科学

IEEE Access Pub Date : 2025-07-24 DOI: 10.1109/ACCESS.2025.3592124

Michael Palk;Katharina Knappmann;Stefan Voss;Raka Jovanovic

{"title":"Robust Prediction of Wildfire Spread in Australia","authors":"Michael Palk;Katharina Knappmann;Stefan Voss;Raka Jovanovic","doi":"10.1109/ACCESS.2025.3592124","DOIUrl":"https://doi.org/10.1109/ACCESS.2025.3592124","url":null,"abstract":"Wildfires can have devastating effects on urban infrastructure and natural ecosystems, making wildfire management an important, but yet complex and difficult task. The systematic collection of data, increased computing power, and the development of physical models made it possible to get an understanding of the dynamics of wildfire spread. As exact computational simulations of wildfires are not feasible yet, several subtasks such as the estimation of the spread rate were analyzed with various methods in the literature. In this paper, different types of predictive models are evaluated to forecast the spread of wildfires on a daily and weekly basis in a comparative study. These models are tested on real-world data of wildfires from the seven Australian regions New South Wales, Northern Territory, Queensland, South Australia, Tasmania, Victoria, and Western Australia from 2005 to 2020, including weather, vegetation, and land cover class data, in a univariate and multivariate setting. Furthermore, relevant features are identified and discussed which can have an important influence on wildfire spread. We find that robust models, which are less sensitive to outliers, capture the dynamics of wildfire spread most accurately.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"13 ","pages":"132703-132723"},"PeriodicalIF":3.6,"publicationDate":"2025-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11095684","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144751110","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}

引用次数: 0

Edge Computing Application-Specific Integrated Circuit With Two Serial Communication Protocols and a Backpropagation Neural Network 具有两个串行通信协议和反向传播神经网络的边缘计算专用集成电路

IF 3.6 3区计算机科学

IEEE Access Pub Date : 2025-07-24 DOI: 10.1109/ACCESS.2025.3592315

Guo-Ming Sung;Sachin D. Kohale;Chao-Yu Chen;Ying-Tzu Lai

{"title":"Edge Computing Application-Specific Integrated Circuit With Two Serial Communication Protocols and a Backpropagation Neural Network","authors":"Guo-Ming Sung;Sachin D. Kohale;Chao-Yu Chen;Ying-Tzu Lai","doi":"10.1109/ACCESS.2025.3592315","DOIUrl":"https://doi.org/10.1109/ACCESS.2025.3592315","url":null,"abstract":"This study developed an edge computing application-specific integrated circuit (ASIC) with two serial communication protocols, adjustable weights, and a backpropagation neural network (BPNN) for edge computing. The serial peripheral interface and I2C serial communication protocols are used in the developed ASIC to ensure its communication reliability. Moreover, adjustable weights are employed to achieve high edge computing performance and minimize the computational load. An Arduino development board captures sensing data and sends them to the designed ASIC through the I2C communication protocol. A 25LC640 EEPROM memory microchip is mounted externally on the ASIC and stores the BPNN model, training data, and adjustable weights. The BPNN model is constructed using the inverse transfer algorithm, and this model’s training process is optimized by employing the stochastic gradient descent method. This approach not only ensures a high learning rate but also leads to relatively few iterations. Once the training procedure is complete, the obtained weights are stored in the EEPROM. Moreover, the BPNN model can be trained on a computer or other external device and then loaded into the plug-in EEPROM directly. This design not only enhances the tunability of the model but also facilitates migration and application of the learning results among devices. The designed ASIC was fabricated through the 90-nm cell-based complementary metal–oxide–semiconductor process of Taiwan Semiconductor Manufacturing Company. According to the simulation results, the proposed ASIC has a gate count of 85526, a chip area of <inline-formula> <tex-math>$0.896times 0.896$ </tex-math></inline-formula> mm2, and power consumption of 0.7459 mW at a voltage of 1.0 V and frequency of 20 MHz.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"13 ","pages":"134529-134540"},"PeriodicalIF":3.6,"publicationDate":"2025-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11095715","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144756759","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}

引用次数: 0

Machine Learning Approach to Aerodynamic Analysis of NACA0005 Airfoil: ANN and CFD Integration NACA0005翼型气动分析的机器学习方法：ANN和CFD集成

IF 3.6 3区计算机科学

IEEE Access Pub Date : 2025-07-24 DOI: 10.1109/ACCESS.2025.3592338

Taiba Kouser;Dilek Funda Kurtulus;Srikanth Goli;Abdulrahman Aliyu;Imil Hamda Imran;Luai M. Alhems;Azhar M. Memon

{"title":"Machine Learning Approach to Aerodynamic Analysis of NACA0005 Airfoil: ANN and CFD Integration","authors":"Taiba Kouser;Dilek Funda Kurtulus;Srikanth Goli;Abdulrahman Aliyu;Imil Hamda Imran;Luai M. Alhems;Azhar M. Memon","doi":"10.1109/ACCESS.2025.3592338","DOIUrl":"https://doi.org/10.1109/ACCESS.2025.3592338","url":null,"abstract":"This study presents a machine learning approach to predict the unsteady aerodynamic performance of a NACA0005 airfoil. Data generated by computational fluid dynamics (CFD) is used to train the model for Reynolds numbers <inline-formula> <tex-math>$Re in [{1000-5000}]$ </tex-math></inline-formula> and angles of attack ranging from 9° to 11°. A robust Scaled Conjugate Gradient (SCG) algorithm is employed for efficient training of data. The ANN has a two-layer architecture, with 9 fixed neurons in the first hidden layer and a varying number of neurons in the second layer to achieve optimal performance. The model yielded coefficients of determination (<inline-formula> <tex-math>$R^{2}$ </tex-math></inline-formula>) of 0.994 (Coefficient of lift (<inline-formula> <tex-math>$C_{l}$ </tex-math></inline-formula>)) and 0.9615 (Coefficient of drag (<inline-formula> <tex-math>$C_{d}$ </tex-math></inline-formula>)) for training, and 0.9563 (<inline-formula> <tex-math>$C_{l}$ </tex-math></inline-formula>) and 0.9085 (<inline-formula> <tex-math>$C_{d}$ </tex-math></inline-formula>) for testing. Overall mean errors are found to be less than 1%. It offers a powerful surrogate modeling approach for aerodynamic studies at ultra-low Reynolds numbers. Moreover, it provides rapid and reliable alternatives to traditional CFD simulations in aerodynamic analysis for unseen cases.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"13 ","pages":"131088-131101"},"PeriodicalIF":3.6,"publicationDate":"2025-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11095683","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144725280","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}

引用次数: 0

PHILDER: Lightweight Framework for Intelligent Phishing Detection on Resource-Limited Devices 资源有限设备上智能网络钓鱼检测的轻量级框架

IF 3.6 3区计算机科学

IEEE Access Pub Date : 2025-07-24 DOI: 10.1109/ACCESS.2025.3592541

Guilherme Dantas Bispo;César Augusto Borges de Andrade;Gabriela Mayumi Saiki;Raquel Valadares Borges;André Luiz Marques Serrano;Geraldo Pereira Rocha Filho;Vinícius Pereira Gonçalves

{"title":"PHILDER: Lightweight Framework for Intelligent Phishing Detection on Resource-Limited Devices","authors":"Guilherme Dantas Bispo;César Augusto Borges de Andrade;Gabriela Mayumi Saiki;Raquel Valadares Borges;André Luiz Marques Serrano;Geraldo Pereira Rocha Filho;Vinícius Pereira Gonçalves","doi":"10.1109/ACCESS.2025.3592541","DOIUrl":"https://doi.org/10.1109/ACCESS.2025.3592541","url":null,"abstract":"The increasing sophistication of phishing attacks represents a significant challenge to cybersecurity, particularly in the context of fraudulent emails crafted to deceive users and steal confidential information. This paper proposes a deep learning-based approach for the automatic detection of phishing in emails, the PHILDER (PHishing Intelligent Lightweight DEtection on Resource-limited devices) model. The study employs a dataset composed of real emails extracted from PhishTank and the SpamAssassin Public Corpus, spanning both legitimate and fraudulent samples. To address the natural imbalance between spam and phishing emails, two strategies were applied: undersampling, which reduces the number of legitimate emails to balance the classes, and oversampling using SMOTE (Synthetic Minority Over-sampling Technique) to generate new synthetic samples of the minority class. Five models (ALBERT, DistilBERT, MobileBERT, MiniLM, and TinyBERT) were trained: one using the original dataset, one with undersampling, and a third with oversampling. The experimental results show that the oversampling approach had to be discarded due to computational cost issues, the tendency to overfit, and inferior performance compared to the other two approaches. The main contributions of this paper include the application of computational efficiency metrics for model evaluation, which not only consider traditional metrics but also enable assessment in real-world applications under hardware computational constraints, and the exploration of different data composition strategies for training. The use of PHILDER (TinyBERT combined with data balancing techniques) demonstrates a promising approach for the automatic detection of phishing in emails, contributing to strengthening digital security against social engineering attacks.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"13 ","pages":"131967-131979"},"PeriodicalIF":3.6,"publicationDate":"2025-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11095665","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144751060","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}

引用次数: 0

Encoding Holographic Data Into Synthetic Video Streams for Enhanced Microplastic Detection 将全息数据编码为合成视频流以增强微塑性检测

IF 3.6 3区计算机科学

IEEE Access Pub Date : 2025-07-24 DOI: 10.1109/ACCESS.2025.3592323

Paolo Russo;Fabiana Di Ciaccio;Pasquale Santaniello;Teresa Cacace;Pierluigi Carcagnì;Marco del Coco;Melania Paturzo

{"title":"Encoding Holographic Data Into Synthetic Video Streams for Enhanced Microplastic Detection","authors":"Paolo Russo;Fabiana Di Ciaccio;Pasquale Santaniello;Teresa Cacace;Pierluigi Carcagnì;Marco del Coco;Melania Paturzo","doi":"10.1109/ACCESS.2025.3592323","DOIUrl":"https://doi.org/10.1109/ACCESS.2025.3592323","url":null,"abstract":"This study presents a novel deep learning pipeline for the detection and classification of microplastics using digital holography, with a focus on synthetic microfibers released during laundry. We introduce HMPD 2.0, an enhanced version of the Holography MicroPlastic Dataset featuring 24 amplitude and phase channels per sample, obtained through varying spatial filtering, numerical aberration correction, and propagation. To reduce input dimensionality, we propose a pseudo-RGB compression technique that groups grayscale channels into synthetic frames, which are then interpreted as a video sequence. This allows the use of transformer-based video architectures, particularly TimeSformer, for spatiotemporal modeling. Experimental results demonstrate that TimeSformer achieves a classification accuracy of up to 97.91%, with compressed 8-frame inputs maintaining high performance while significantly reducing inference time (from 42 ms to 16 ms per sample). These findings validate the effectiveness and efficiency of our approach, which supports real-time deployment on edge devices.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"13 ","pages":"132680-132692"},"PeriodicalIF":3.6,"publicationDate":"2025-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11095714","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144758345","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}

引用次数: 0

Performance Enhancement of Dual-Input Frequency-Periodic Load Modulated Power Amplifier at 1–5.7-GHz Bandwidth With Co-Designed Biasing Network 协同设计偏置网络对1 - 5.7 ghz双输入频率周期负载调制功率放大器性能的增强

IF 3.6 3区计算机科学

IEEE Access Pub Date : 2025-07-24 DOI: 10.1109/ACCESS.2025.3592238

Takuma Torii;Yuji Komatsuzaki;Shintaro Shinjo;Ryo Ishikawa

{"title":"Performance Enhancement of Dual-Input Frequency-Periodic Load Modulated Power Amplifier at 1–5.7-GHz Bandwidth With Co-Designed Biasing Network","authors":"Takuma Torii;Yuji Komatsuzaki;Shintaro Shinjo;Ryo Ishikawa","doi":"10.1109/ACCESS.2025.3592238","DOIUrl":"https://doi.org/10.1109/ACCESS.2025.3592238","url":null,"abstract":"This study proposes a novel dual input power amplifier (PA) with a frequency-periodic load modulated output matching network supported by a broadband biasing network. The output matching network consists of two transmission lines which enable the dual-input PA to operate in Doherty or outphasing modes depending on the frequency. The proposed broadband biasing network simply consists of a short stub circuit that cooperates with the output matching network. The biasing network not only provides a bias to PA, but also improves the bandwidth in the back-off operation over the broadband characteristic of 145%. The two independent input signals are utilized to optimize the operation of Doherty and outphasing mode. The dual-input PA is implemented using a <inline-formula> <tex-math>$0.15~mu $ </tex-math></inline-formula> m GaN HEMT process. The fabricated PA shows a saturated output power of 35.2 dBm to 38.1 dBm with a power added efficiency (PAE) of 36.6% to 62% for the broadband 1 GHz to 5.7 GHz. The fabricated PA demonstrated an averaged output power of 27.7 dBm to 31.8 dBm, a PAE of 35% to 56.2% and an adjacent channel power Ratio (ACPR) of -41 to -55 dBc.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"13 ","pages":"131856-131868"},"PeriodicalIF":3.6,"publicationDate":"2025-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11095680","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144725153","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}

引用次数: 0