Pub Date : 2025-01-09DOI: 10.1109/ACCESS.2025.3527684
Hee-Yeong Yang;Young-Shin Han;Choon-Sung Nam
Electromyography (EMG) is used to recognize user finger gestures for applications in real-time interfaces. Finger movements are classified by preprocessing to extract the features from the collected EMG data, which are then used for machine learning. The data were extracted using the overlapped segmentation method to ensure sufficient training data. The preprocessing of EMG data uses standard formulae, such as integrated EMG (IEMG) and mean absolute value (MAV). Furthermore, preprocessing involves using original data, simple moving average (SMA), and Fast Fourier transform (FFT) for feature extraction. Subsequently, these preprocessed data sets are used to train machine learning models, facilitating a comparative analysis. Four machine learning models were used: eXtreme Gradient Boost, Random Forest, k-Nearest Neighbors, and Logistic Regression. The experimental results revealed the best accuracy from preprocessing using a simple moving average followed by a Fourier transform, but classification was not possible using all nine finger movements. On the other hand, it showed more than 90% accuracy because the model learned by reducing it to a specific finger gesture. Rest movements, index finger taps, and force-taps movements achieved the highest accuracy, approximately 95%.
{"title":"Study on Finger Gesture Interface Using One-Channel EMG","authors":"Hee-Yeong Yang;Young-Shin Han;Choon-Sung Nam","doi":"10.1109/ACCESS.2025.3527684","DOIUrl":"https://doi.org/10.1109/ACCESS.2025.3527684","url":null,"abstract":"Electromyography (EMG) is used to recognize user finger gestures for applications in real-time interfaces. Finger movements are classified by preprocessing to extract the features from the collected EMG data, which are then used for machine learning. The data were extracted using the overlapped segmentation method to ensure sufficient training data. The preprocessing of EMG data uses standard formulae, such as integrated EMG (IEMG) and mean absolute value (MAV). Furthermore, preprocessing involves using original data, simple moving average (SMA), and Fast Fourier transform (FFT) for feature extraction. Subsequently, these preprocessed data sets are used to train machine learning models, facilitating a comparative analysis. Four machine learning models were used: eXtreme Gradient Boost, Random Forest, k-Nearest Neighbors, and Logistic Regression. The experimental results revealed the best accuracy from preprocessing using a simple moving average followed by a Fourier transform, but classification was not possible using all nine finger movements. On the other hand, it showed more than 90% accuracy because the model learned by reducing it to a specific finger gesture. Rest movements, index finger taps, and force-taps movements achieved the highest accuracy, approximately 95%.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"13 ","pages":"9606-9614"},"PeriodicalIF":3.4,"publicationDate":"2025-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10835803","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142993339","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}
This paper presents an innovative hybrid cable-driven shoulder joint for humanoid robotics application. A blend of a flexible central limb and three rigid lateral limbs, form a 2-degree-of-freedom (2 DOF) mechanism that connects the mobile platform to the fixed base. This design leverages both good mechanical stability and the integration of an elastic element, which mitigates vibrations up to 40% and allows the storage and release of elastic potential energy up to $1.9 ,J$ . Initially, three alternative and incremental shoulder joint designs are presented and evaluated across two distinct experiments: 1) Energy storage analysis of the parallel mechanism during single cable motion and 2) Dynamic response and vibration damping. Following these experiments, a detailed analysis is performed on the stiffness properties of the proposed prototype, as it outperforms the other two designs. The dimension of the central elastic limb, made out of Thermo-Plastic Polyurethane (TPU), is optimized using Finite Element Analysis (FEA). The kinematic behavior of the proposed mechanism is approximated as a combination of linkages equipped with two universal joints, and its motion evaluated through numerical simulations and real experiments.
{"title":"Design and Analysis of a Parallel Elastic Shoulder Joint for Humanoid Robotics Application","authors":"Sharafatdin Yessirkepov;Timur Umurzakov;Michele Folgheraiter","doi":"10.1109/ACCESS.2025.3527873","DOIUrl":"https://doi.org/10.1109/ACCESS.2025.3527873","url":null,"abstract":"This paper presents an innovative hybrid cable-driven shoulder joint for humanoid robotics application. A blend of a flexible central limb and three rigid lateral limbs, form a 2-degree-of-freedom (2 DOF) mechanism that connects the mobile platform to the fixed base. This design leverages both good mechanical stability and the integration of an elastic element, which mitigates vibrations up to 40% and allows the storage and release of elastic potential energy up to <inline-formula> <tex-math>$1.9 ,J$ </tex-math></inline-formula>. Initially, three alternative and incremental shoulder joint designs are presented and evaluated across two distinct experiments: 1) Energy storage analysis of the parallel mechanism during single cable motion and 2) Dynamic response and vibration damping. Following these experiments, a detailed analysis is performed on the stiffness properties of the proposed prototype, as it outperforms the other two designs. The dimension of the central elastic limb, made out of Thermo-Plastic Polyurethane (TPU), is optimized using Finite Element Analysis (FEA). The kinematic behavior of the proposed mechanism is approximated as a combination of linkages equipped with two universal joints, and its motion evaluated through numerical simulations and real experiments.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"13 ","pages":"8761-8778"},"PeriodicalIF":3.4,"publicationDate":"2025-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10835065","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142993677","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}
Pub Date : 2025-01-09DOI: 10.1109/ACCESS.2025.3527677
Abhiram Sharma;R. Parvathi
This paper proposes a hybrid deep learning model integrating DenseNet201 and InceptionV3 to address the challenges in achieving accurate and reliable cervical cancer classification. Current models often exhibit limitations in balancing precision and recall, which are critical for dependable clinical applications. The hybrid model leverages DenseNet201’s efficient feature reuse and InceptionV3’s capacity for handling multi-scale and hierarchical features through fine-tuning and feature fusion techniques. The methodology involves rigorous data preprocessing, including normalization, augmentation, and dataset splitting, to ensure robust training and validation. Feature extraction and dimensionality optimization are employed to identify the most critical and discriminative features for classification. The experimental setup utilizes Python, TensorFlow, and Keras within a GPU-enabled environment to handle computational demands effectively. Comprehensive evaluation metrics, including accuracy, precision, recall, and F1-score, indicate that the proposed model achieves an accuracy of 96.54%, 95.91% Presicion, 96.44% Recall and 96.17% F1 Score surpassing state-of-the-art models such as ResNet-50, DenseNet-201, InceptionV3, and Xception. Visualization tools, including high-resolution confusion matrices and ROC curves, further demonstrate the hybrid model’s capability to differentiate between cervical cancer cell classes accurately. Comparative analyses validate the model’s superior performance and its potential as a dependable tool for clinical implementation. This study presents a robust and efficient classification system that addresses the limitations of existing models. Future research will focus on further improving the system’s performance and investigating its applicability to other medical imaging tasks. The proposed model is expected to contribute significantly to early and accurate cervical cancer diagnosis, enhancing patient outcomes and supporting healthcare professionals in clinical decision-making.
{"title":"Enhancing Cervical Cancer Classification: Through a Hybrid Deep Learning Approach Integrating DenseNet201 and InceptionV3","authors":"Abhiram Sharma;R. Parvathi","doi":"10.1109/ACCESS.2025.3527677","DOIUrl":"https://doi.org/10.1109/ACCESS.2025.3527677","url":null,"abstract":"This paper proposes a hybrid deep learning model integrating DenseNet201 and InceptionV3 to address the challenges in achieving accurate and reliable cervical cancer classification. Current models often exhibit limitations in balancing precision and recall, which are critical for dependable clinical applications. The hybrid model leverages DenseNet201’s efficient feature reuse and InceptionV3’s capacity for handling multi-scale and hierarchical features through fine-tuning and feature fusion techniques. The methodology involves rigorous data preprocessing, including normalization, augmentation, and dataset splitting, to ensure robust training and validation. Feature extraction and dimensionality optimization are employed to identify the most critical and discriminative features for classification. The experimental setup utilizes Python, TensorFlow, and Keras within a GPU-enabled environment to handle computational demands effectively. Comprehensive evaluation metrics, including accuracy, precision, recall, and F1-score, indicate that the proposed model achieves an accuracy of 96.54%, 95.91% Presicion, 96.44% Recall and 96.17% F1 Score surpassing state-of-the-art models such as ResNet-50, DenseNet-201, InceptionV3, and Xception. Visualization tools, including high-resolution confusion matrices and ROC curves, further demonstrate the hybrid model’s capability to differentiate between cervical cancer cell classes accurately. Comparative analyses validate the model’s superior performance and its potential as a dependable tool for clinical implementation. This study presents a robust and efficient classification system that addresses the limitations of existing models. Future research will focus on further improving the system’s performance and investigating its applicability to other medical imaging tasks. The proposed model is expected to contribute significantly to early and accurate cervical cancer diagnosis, enhancing patient outcomes and supporting healthcare professionals in clinical decision-making.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"13 ","pages":"9868-9878"},"PeriodicalIF":3.4,"publicationDate":"2025-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10835083","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142993308","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}
As the penetration level of large-scale solar power plants (LSSPPs) in transmission systems increases, their contribution to the stability of networks cannot be overlooked. Theoretically, such resources can be considered akin to traditional power plants in preserving network stability. Moreover, diverse frequency regulation resources exert varying levels of system complexity, capacity, and response speed, thereby posing challenges to appropriate performance automatic generation control (AGC). As a remedy, a new hybrid (hierarchical/decentralized) scheme is proposed to improve the performance of traditional AGC mechanisms in the presence of LSSPPs and utilize maximum potential capability to ensure network stability. First, a new method is employed to calculate the spinning reserve for LSSPPs considering the performance of AGC for traditional power plants, the dynamics of the DC-link voltage in LSSPPs, the critical operating point related to the most severe disturbance, and the load model. Following this, the decentralized AGC system works hierarchically and in parallel with the centralized algorithm to regulate the frequency and tie lines exchange power. Furthermore, a simple and accurate index ($Delta P_{IPS_x}$ ) is provided to estimate the amount of active power changes after the disturbance in an interconnected power system (IPS). The simulation results are conducted in IEEE 39-bus and PST-16 test systems using DIgSILENT PowerFactory software. The simulation results verify the efficacy and performance of our proposed scheme to improve the AGC system performance and system stability.
{"title":"A Novel Hierarchical/Decentralized AGC Scheme for Power Systems Integrated With Large-Scale Solar Power Plants","authors":"Siavash Yari;Masood Mottaghizadeh;Innocent Kamwa;Dmitry Rimorov","doi":"10.1109/ACCESS.2025.3527920","DOIUrl":"https://doi.org/10.1109/ACCESS.2025.3527920","url":null,"abstract":"As the penetration level of large-scale solar power plants (LSSPPs) in transmission systems increases, their contribution to the stability of networks cannot be overlooked. Theoretically, such resources can be considered akin to traditional power plants in preserving network stability. Moreover, diverse frequency regulation resources exert varying levels of system complexity, capacity, and response speed, thereby posing challenges to appropriate performance automatic generation control (AGC). As a remedy, a new hybrid (hierarchical/decentralized) scheme is proposed to improve the performance of traditional AGC mechanisms in the presence of LSSPPs and utilize maximum potential capability to ensure network stability. First, a new method is employed to calculate the spinning reserve for LSSPPs considering the performance of AGC for traditional power plants, the dynamics of the DC-link voltage in LSSPPs, the critical operating point related to the most severe disturbance, and the load model. Following this, the decentralized AGC system works hierarchically and in parallel with the centralized algorithm to regulate the frequency and tie lines exchange power. Furthermore, a simple and accurate index (<inline-formula> <tex-math>$Delta P_{IPS_x}$ </tex-math></inline-formula>) is provided to estimate the amount of active power changes after the disturbance in an interconnected power system (IPS). The simulation results are conducted in IEEE 39-bus and PST-16 test systems using DIgSILENT PowerFactory software. The simulation results verify the efficacy and performance of our proposed scheme to improve the AGC system performance and system stability.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"13 ","pages":"8092-8109"},"PeriodicalIF":3.4,"publicationDate":"2025-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10835100","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142975758","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}
Pub Date : 2025-01-09DOI: 10.1109/ACCESS.2025.3527630
Jianhui Li;Jun Huang;Yahui Sun;Guoqiang Li
This work presents a novel acceleration method that achieves more efficient convergence of steady-state flow fields. This method involves conducting dynamic mode decomposition (DMD) and proper orthogonal decomposition (POD) model reduction on the field snapshots. Subsequently, the residual of the reduced-order model is optimized in the POD modal space to obtain a more accurate solution. This optimized solution is then used as the initial field, and the solver continues iterating until the residual converges. Taking full advantage of both DMD and POD, the proposed approach removes the interference of high-frequency oscillatory flow components and concentrates on the main energy components. This effectively overcomes the problems of slow convergence and residual jumps caused by system stiffness, thereby accelerating the convergence process. The results show that for linear equations, the proposed method achieves a significant acceleration, with a convergence speed five times faster than traditional numerical methods. For the nonlinear Burgers equation, the proposed method also reduces the number of convergence steps by nearly 70%. Additionally, the performance of the proposed accelerated convergence method was further validated through the complex flow around a high-dimensional dual ellipsoid.
{"title":"Accelerated Convergence Method for Flow Field Based on DMD-POD Combined Reduced-Order Optimization Model","authors":"Jianhui Li;Jun Huang;Yahui Sun;Guoqiang Li","doi":"10.1109/ACCESS.2025.3527630","DOIUrl":"https://doi.org/10.1109/ACCESS.2025.3527630","url":null,"abstract":"This work presents a novel acceleration method that achieves more efficient convergence of steady-state flow fields. This method involves conducting dynamic mode decomposition (DMD) and proper orthogonal decomposition (POD) model reduction on the field snapshots. Subsequently, the residual of the reduced-order model is optimized in the POD modal space to obtain a more accurate solution. This optimized solution is then used as the initial field, and the solver continues iterating until the residual converges. Taking full advantage of both DMD and POD, the proposed approach removes the interference of high-frequency oscillatory flow components and concentrates on the main energy components. This effectively overcomes the problems of slow convergence and residual jumps caused by system stiffness, thereby accelerating the convergence process. The results show that for linear equations, the proposed method achieves a significant acceleration, with a convergence speed five times faster than traditional numerical methods. For the nonlinear Burgers equation, the proposed method also reduces the number of convergence steps by nearly 70%. Additionally, the performance of the proposed accelerated convergence method was further validated through the complex flow around a high-dimensional dual ellipsoid.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"13 ","pages":"10340-10355"},"PeriodicalIF":3.4,"publicationDate":"2025-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10835101","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142993510","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}
Pub Date : 2025-01-09DOI: 10.1109/ACCESS.2025.3527868
Elisabeth Tchaptchet;Elie Fute Tagne;Jaime Acosta;Danda B. Rawat;Charles Kamhoua
Deepfake is an advanced technology that creates extremely realistic facial images and videos. This new technique operates under specific conditions and has a wide range of applications. For example, it can be used in the entertainment industry to create impressive visual effects or to insert actors into scenes convincingly. Similarly, in the film industry, deepfakes can help make movies by faithfully reproducing the appearance of actors who are not physically present. It is also useful for creating realistic digital avatars of people, which can be used in virtual environments, video games, or augmented reality applications. Recently, the emergence of new content generation models capable of creating impressively realistic images has been gaining momentum. Despite their advantages, they also cause significant issues when used maliciously, such as for identity theft, misinformation, and obscene depictions of well-known individuals. Therefore, it is crucial to implement effective methods to expose this generated content and thus reduce crime associated with deepfakes. This article presents a novel method for detecting fake content based on an in-depth analysis of the characteristics of eye irises. By applying a gradient map to the iris, it is possible to visualize the biological characteristics specific to eye irises, such as the round shape, identical reflections in the two irises of the same face, the size of the iris, etc. The gradient map highlights all the contours of the objects present in the iris; thus, the reflected light present in the corneas is represented by brighter pixels comparable to heat. We show that two irises of the same face are almost identical in shape, reflection, and size. Our experimental results on the Flickr-Faces-HQ (FFHQ) dataset and images obtained from StyleGAN2 demonstrate that our algorithm achieves a remarkable detection accuracy of 0.979 and 0.921 sensitivity. Furthermore, the method has a specificity of 0.937 and a precision of 0.960, thereby proving the effectiveness of the gradient map associated with the shape of the pupil in detecting Generative adversarial network (GAN) generated faces.
{"title":"Deepfakes Detection by Iris Analysis","authors":"Elisabeth Tchaptchet;Elie Fute Tagne;Jaime Acosta;Danda B. Rawat;Charles Kamhoua","doi":"10.1109/ACCESS.2025.3527868","DOIUrl":"https://doi.org/10.1109/ACCESS.2025.3527868","url":null,"abstract":"Deepfake is an advanced technology that creates extremely realistic facial images and videos. This new technique operates under specific conditions and has a wide range of applications. For example, it can be used in the entertainment industry to create impressive visual effects or to insert actors into scenes convincingly. Similarly, in the film industry, deepfakes can help make movies by faithfully reproducing the appearance of actors who are not physically present. It is also useful for creating realistic digital avatars of people, which can be used in virtual environments, video games, or augmented reality applications. Recently, the emergence of new content generation models capable of creating impressively realistic images has been gaining momentum. Despite their advantages, they also cause significant issues when used maliciously, such as for identity theft, misinformation, and obscene depictions of well-known individuals. Therefore, it is crucial to implement effective methods to expose this generated content and thus reduce crime associated with deepfakes. This article presents a novel method for detecting fake content based on an in-depth analysis of the characteristics of eye irises. By applying a gradient map to the iris, it is possible to visualize the biological characteristics specific to eye irises, such as the round shape, identical reflections in the two irises of the same face, the size of the iris, etc. The gradient map highlights all the contours of the objects present in the iris; thus, the reflected light present in the corneas is represented by brighter pixels comparable to heat. We show that two irises of the same face are almost identical in shape, reflection, and size. Our experimental results on the Flickr-Faces-HQ (FFHQ) dataset and images obtained from StyleGAN2 demonstrate that our algorithm achieves a remarkable detection accuracy of 0.979 and 0.921 sensitivity. Furthermore, the method has a specificity of 0.937 and a precision of 0.960, thereby proving the effectiveness of the gradient map associated with the shape of the pupil in detecting Generative adversarial network (GAN) generated faces.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"13 ","pages":"8977-8987"},"PeriodicalIF":3.4,"publicationDate":"2025-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10835076","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142993786","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}
Pub Date : 2025-01-09DOI: 10.1109/ACCESS.2025.3527577
Muhua Wei;Jun Wu;Huili Liu;Lin Lin;Zheng Zhang;Mayuan Sun
Currently, 6G technology is at a pivotal stage for research and standardization, with the next three to five years being crucial for achieving technological breakthroughs and fostering industrial development. 6G is anticipated to support a broader spectrum of application scenarios, lead us into a more intelligent and interconnected future. The applications and use cases of 6G serve as a vital link between technological innovation and user demands, laying the groundwork for key network performance indicators, functional design, and service capability planning, and paving the way for its future commercialization. The forward-looking exploration and identification of potential 6G use cases, particularly those with high development prospects, can offer strategic guidance for technological research and development. This study introduces an innovative 6G Use Case Potential Matrix, designed from dual perspectives of innovation and business viability. It assesses application innovation through the volume and trends of invention patents and evaluates business potential using market outlook analyses. Based on these insights, typical 6G use cases are categorized into four groups: leading use cases, use cases to be broken through, use cases to be excavated, and use cases to be cultivated. We select 23 typical 6G use cases with consensus for empirical analysis, and recommendations for the development and layout of 6G use cases are given. The findings of this research aim to offer fresh perspectives for the systematic planning of 6G applications development pathways and to support decision-making on aligning technology research directions with network requirements definitions.
{"title":"Envisioning the Potential of 6G Use Cases—A Dual Perspective of Innovation and Business","authors":"Muhua Wei;Jun Wu;Huili Liu;Lin Lin;Zheng Zhang;Mayuan Sun","doi":"10.1109/ACCESS.2025.3527577","DOIUrl":"https://doi.org/10.1109/ACCESS.2025.3527577","url":null,"abstract":"Currently, 6G technology is at a pivotal stage for research and standardization, with the next three to five years being crucial for achieving technological breakthroughs and fostering industrial development. 6G is anticipated to support a broader spectrum of application scenarios, lead us into a more intelligent and interconnected future. The applications and use cases of 6G serve as a vital link between technological innovation and user demands, laying the groundwork for key network performance indicators, functional design, and service capability planning, and paving the way for its future commercialization. The forward-looking exploration and identification of potential 6G use cases, particularly those with high development prospects, can offer strategic guidance for technological research and development. This study introduces an innovative 6G Use Case Potential Matrix, designed from dual perspectives of innovation and business viability. It assesses application innovation through the volume and trends of invention patents and evaluates business potential using market outlook analyses. Based on these insights, typical 6G use cases are categorized into four groups: leading use cases, use cases to be broken through, use cases to be excavated, and use cases to be cultivated. We select 23 typical 6G use cases with consensus for empirical analysis, and recommendations for the development and layout of 6G use cases are given. The findings of this research aim to offer fresh perspectives for the systematic planning of 6G applications development pathways and to support decision-making on aligning technology research directions with network requirements definitions.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"13 ","pages":"9831-9843"},"PeriodicalIF":3.4,"publicationDate":"2025-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10835087","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142993017","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}
Pub Date : 2025-01-09DOI: 10.1109/ACCESS.2025.3527513
Venkatesan Ramakrishnan;Dominic Savio A;Mohammad Shorfuzzaman;Waleed Mohammed Abdelfattah
The growth of Electric Vehicle (EV) technologies necessitates adequate charging infrastructure and energy storage systems for reliable operation. Conversely, vehicle-to-grid, vehicle-to-home, and vehicle-to-vehicle (V2V) technologies are being researched to enhance EV usage. V2V technology can assist EV users with convenient power sharing during emergencies. However, the conventional plug-in approach limits safety and human intervention aspects. Recent advancements in wireless power transfer (WPT) offer both convenience and reliable power exchange, making them the most suitable approach for V2V technology. WPT is a loosely coupled system, and the air gap increases leakage inductance, which weakens the coupling factor (K) and affects power transfer efficiency (PTE). In this article, the enhancement of the coupling factor is achieved by employing a reconfigurable coil between the Transmitter (Tx) coil and the Receiver (Rx) coil. This reconfigurable coil functions as a resonator, enhancing the flux generated by the Tx coil and improving PTE. Furthermore, the proposed system facilitates bidirectional power flow between two EVs. The phase shift control technique regulates the power flow between the two EVs. Improved efficient WPT conserves energy and reduces the reliance on energy storage devices. The proposed WPT system is validated with a 500W prototype model and realized efficiency of 92.6 % in aligned condition and 86.6% at 40% lateral misaligned condition.
{"title":"An Enhanced Vehicle-to-Vehicle Wireless Power Transfer System for Electric Vehicle Applications Using a Reconfigurable Coil Approach","authors":"Venkatesan Ramakrishnan;Dominic Savio A;Mohammad Shorfuzzaman;Waleed Mohammed Abdelfattah","doi":"10.1109/ACCESS.2025.3527513","DOIUrl":"https://doi.org/10.1109/ACCESS.2025.3527513","url":null,"abstract":"The growth of Electric Vehicle (EV) technologies necessitates adequate charging infrastructure and energy storage systems for reliable operation. Conversely, vehicle-to-grid, vehicle-to-home, and vehicle-to-vehicle (V2V) technologies are being researched to enhance EV usage. V2V technology can assist EV users with convenient power sharing during emergencies. However, the conventional plug-in approach limits safety and human intervention aspects. Recent advancements in wireless power transfer (WPT) offer both convenience and reliable power exchange, making them the most suitable approach for V2V technology. WPT is a loosely coupled system, and the air gap increases leakage inductance, which weakens the coupling factor (K) and affects power transfer efficiency (PTE). In this article, the enhancement of the coupling factor is achieved by employing a reconfigurable coil between the Transmitter (Tx) coil and the Receiver (Rx) coil. This reconfigurable coil functions as a resonator, enhancing the flux generated by the Tx coil and improving PTE. Furthermore, the proposed system facilitates bidirectional power flow between two EVs. The phase shift control technique regulates the power flow between the two EVs. Improved efficient WPT conserves energy and reduces the reliance on energy storage devices. The proposed WPT system is validated with a 500W prototype model and realized efficiency of 92.6 % in aligned condition and 86.6% at 40% lateral misaligned condition.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"13 ","pages":"9931-9941"},"PeriodicalIF":3.4,"publicationDate":"2025-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10835060","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142993672","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}
Pub Date : 2025-01-09DOI: 10.1109/ACCESS.2025.3527698
Bruno Branco;José Silvestre Serra Silva;Miguel Correia
s, also known as drones, are increasingly used in several applications and a variety of cyber attacks can be performed on them using several tools. Some examples of these attacks include breaking the connection between the drone and the controller with deauthentication attacks, discovering a password or cryptographic key used in a communication protocol, gaining control of the drone through command/code injection, and attacks. This paper covers drone attacks by analyzing different components of the drone, including the remote controller and communication protocols. The main purpose is to provide an overview of the possible ways in which cyber attacks can be executed. This analysis concludes that drones, designed for diverse purposes, are vulnerable to a range of cyber attacks. The paper also reviews existing penetration testing methodologies for UAVs, which provide a logical framework for their realization. This review covers the different cyber attack methods and tools used against a UAV, intending to improve defense mechanisms.
{"title":"Cyber Attacks on Commercial Drones: A Review","authors":"Bruno Branco;José Silvestre Serra Silva;Miguel Correia","doi":"10.1109/ACCESS.2025.3527698","DOIUrl":"https://doi.org/10.1109/ACCESS.2025.3527698","url":null,"abstract":"s, also known as drones, are increasingly used in several applications and a variety of cyber attacks can be performed on them using several tools. Some examples of these attacks include breaking the connection between the drone and the controller with deauthentication attacks, discovering a password or cryptographic key used in a communication protocol, gaining control of the drone through command/code injection, and attacks. This paper covers drone attacks by analyzing different components of the drone, including the remote controller and communication protocols. The main purpose is to provide an overview of the possible ways in which cyber attacks can be executed. This analysis concludes that drones, designed for diverse purposes, are vulnerable to a range of cyber attacks. The paper also reviews existing penetration testing methodologies for UAVs, which provide a logical framework for their realization. This review covers the different cyber attack methods and tools used against a UAV, intending to improve defense mechanisms.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"13 ","pages":"9566-9577"},"PeriodicalIF":3.4,"publicationDate":"2025-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10835757","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142993161","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}
Pub Date : 2025-01-09DOI: 10.1109/ACCESS.2025.3527924
Emanuel G. Muñoz;Jaime Meza;Sebastian Ventura
Recommending suitable housing implies significant challenges owing to the continuous increase in demand and the need to meet habitability standards. This document presents an innovative approach with which to address these challenges through the use of a housing recommendation method based on distances to key spatial points and the latent characteristics of the properties. The proposed method employs objective distances from the properties to points of interest, such as educational centers, medical centers, pharmacies, shops, entertainment, 911 security cameras and public transport stations. These distances are calculated on the basis of the area in which the property is located, thus providing an accurate assessment of the environment. Moreover, housing features are grouped into three correlated latent factors: Size and Value, Environment and Comfort, and Age and Safety. The recommendation system relies on fuzzy control to manage user preferences and select appropriate input data with which to test the model. A content-based filtering approach is used initially, as housing ratings are unavailable. The model predicts a percentage of membership in each cluster, which makes it possible to handle uncertainty by offering properties from different groups in a proportional manner. Euclidean distance is employed in order to measure the similarity between user preferences and housing characteristics, after which the search time is optimized by utilizing metaheuristic methods, of which the bat algorithm provides the best performance in terms of time. This algorithm selects the properties displayed to the user on the basis of natural features extracted from real estate platforms by means of web scraping techniques. The system is built with a Model-View-Controller architecture using Python, Flask, and SQLite. Personal customer data is also recorded in order to create clusters and calculate distances for new customers, thus allowing properties with high ratings to be recommended. This approach combines collaborative and content-based filtering, creating a hybrid system that improves recommendation accuracy and relevance. This analysis shows that the new recommendation method is an effective and accessible solution with which to select suitable housing.
{"title":"Fuzzy Logic Recommender Model for Housing","authors":"Emanuel G. Muñoz;Jaime Meza;Sebastian Ventura","doi":"10.1109/ACCESS.2025.3527924","DOIUrl":"https://doi.org/10.1109/ACCESS.2025.3527924","url":null,"abstract":"Recommending suitable housing implies significant challenges owing to the continuous increase in demand and the need to meet habitability standards. This document presents an innovative approach with which to address these challenges through the use of a housing recommendation method based on distances to key spatial points and the latent characteristics of the properties. The proposed method employs objective distances from the properties to points of interest, such as educational centers, medical centers, pharmacies, shops, entertainment, 911 security cameras and public transport stations. These distances are calculated on the basis of the area in which the property is located, thus providing an accurate assessment of the environment. Moreover, housing features are grouped into three correlated latent factors: Size and Value, Environment and Comfort, and Age and Safety. The recommendation system relies on fuzzy control to manage user preferences and select appropriate input data with which to test the model. A content-based filtering approach is used initially, as housing ratings are unavailable. The model predicts a percentage of membership in each cluster, which makes it possible to handle uncertainty by offering properties from different groups in a proportional manner. Euclidean distance is employed in order to measure the similarity between user preferences and housing characteristics, after which the search time is optimized by utilizing metaheuristic methods, of which the bat algorithm provides the best performance in terms of time. This algorithm selects the properties displayed to the user on the basis of natural features extracted from real estate platforms by means of web scraping techniques. The system is built with a Model-View-Controller architecture using Python, Flask, and SQLite. Personal customer data is also recorded in order to create clusters and calculate distances for new customers, thus allowing properties with high ratings to be recommended. This approach combines collaborative and content-based filtering, creating a hybrid system that improves recommendation accuracy and relevance. This analysis shows that the new recommendation method is an effective and accessible solution with which to select suitable housing.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"13 ","pages":"11380-11395"},"PeriodicalIF":3.4,"publicationDate":"2025-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10835103","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142993493","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}
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