IEEE Access最新文献

{"title":"Exploring Frontal Lobe Brain Activity and Cardiovascular Health Benefits of Reusi Dat Ton: A Neurophysiological and Cardiovascular Assessment","authors":"Kittichai Tharawadeepimuk;Ampika Nanbancha;Weerawat Limroongreungrat;Nuchanath Leelawapa;Yodchanan Wongsawat;Watchara Sroykham","doi":"10.1109/ACCESS.2024.3471642","DOIUrl":"https://doi.org/10.1109/ACCESS.2024.3471642","url":null,"abstract":"This study explored the neurophysiological and cardiovascular benefits of Reusi Dat Ton, focusing on its effects on frontal lobe brain activity and cardiovascular health. Forty-five participants (21 males, 24 females; mean age: 35.73 years; mean BMI: 23.49; mean MMSE score: 27.00) participated in a 20-minute Reusi Dat Ton session. The session comprised five exercises, each performed five times, with 1-minute rest intervals between sets. Cardiovascular health was assessed using a cardiac health monitor, while a 32-channel EEG cap recorded brain activity during a 5-minute eyes-closed resting state, both before and after the session. The findings revealed that Reusi Dat Ton significantly reduced delta wave (0.5-4 Hz) activity in the frontal lobe (\u0000<inline-formula> <tex-math>$p~lt 0.001$ </tex-math></inline-formula>\u0000) and substantially increased alpha wave (8.5-13 Hz) activity in specific frontal lobe regions (\u0000<inline-formula> <tex-math>$p~lt 0.01$ </tex-math></inline-formula>\u0000). Additionally, beta wave (13.5-30 Hz) activity increased in the frontal lobe (\u0000<inline-formula> <tex-math>$p~lt 0.05$ </tex-math></inline-formula>\u0000), and theta wave (4.5-8 Hz) activity increased in other regions (\u0000<inline-formula> <tex-math>$p~lt 0.05$ </tex-math></inline-formula>\u0000). Reusi Dat Ton contribute to cardiovascular health by lowering the heart rate (\u0000<inline-formula> <tex-math>$p~lt 0.001$ </tex-math></inline-formula>\u0000) and improving arterial elasticity, arterial type, and arterial score. These outcomes are consistent with the positive effects of various yoga practices on the heart rate, blood pressure, heart rate variability, and arterial stiffness. This study highlights the potential of Reusi Dat Ton as a holistic practice to enhance both mental and physical health.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"12 ","pages":"145522-145529"},"PeriodicalIF":3.4,"publicationDate":"2024-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10703057","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142408751","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":"Solar Irradiance Forecasting Using a Hybrid Quantum Neural Network: A Comparison on GPU-Based Workflow Development Platforms","authors":"Ying-Yi Hong;Dylan Josh Domingo Lopez;Yun-Yuan Wang","doi":"10.1109/ACCESS.2024.3472053","DOIUrl":"https://doi.org/10.1109/ACCESS.2024.3472053","url":null,"abstract":"Modern renewable power operations can be enhanced by integrating deep neural networks, particularly for forecasting solar irradiance. Recent advancements in quantum computing have shown potential improvements in classical deep neural networks. However, current challenges with quantum hardware, such as susceptibility to noise and decoherence, pose risks to its practicality. Hybrid quantum neural networks (HQNNs) are found to mitigate these issues, especially when integrated with graphics processing unit (GPU)-based pipelines. This paper presents a comparative study of different software platforms for developing HQNNs, using multi-location very short-term solar irradiance forecasting as an example. A classical benchmark model is initially designed based on statistical analysis of a 10-minute resolution solar irradiance dataset, with its parameters further optimized using Bayesian Optimization. The experimental design of this paper includes a loss comparison between classical neural networks and HQNNs across different seasons and a performance comparison between Pennylane, Torchquantum, and CUDA Quantum (CUDA-Q) as HQNN development platforms. Experimental results show that HQNNs achieve up to a 92.30% improvement in testing loss compared to classical neural networks. Regarding HQNN development platforms, Pennylane shows an 81.54% testing loss reduction from classical models, Torchquantum shows a 90.34% improvement, and CUDA-Q shows a 92.30% improvement in testing loss. Implementing hardware acceleration libraries for GPU-based state vector simulation demonstrates an approximate 275% speedup in average latency per epoch, a 218% speedup in inference time, and a 10.20% improvement in testing loss compared to CPU-based simulations. CUDA-Q achieves a training time 2.7 times shorter and an inference time 2.9 times shorter compared to Pennylane, while it is 32.3 times faster in training and 31 times faster in inference compared to Torchquantum.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"12 ","pages":"145079-145094"},"PeriodicalIF":3.4,"publicationDate":"2024-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10703035","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142408813","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":"Don’t Stop Believin’: A Unified Evaluation Approach for LLM Honeypots","authors":"Simon B. Weber;Marc Feger;Michael Pilgermann","doi":"10.1109/ACCESS.2024.3472460","DOIUrl":"https://doi.org/10.1109/ACCESS.2024.3472460","url":null,"abstract":"The research area of honeypots is gaining new momentum, driven by advancements in large language models (LLMs). The chat-based applications of generative pretrained transformer (GPT) models seem ideal for the use as honeypot backends, especially in request-response protocols like Secure Shell (SSH). By leveraging LLMs, many challenges associated with traditional honeypots – such as high development costs, ease of exposure, and breakout risks – appear to be solved. While early studies have primarily focused on the potential of these models, our research investigates the current limitations of GPT-3.5 by analyzing three datasets of varying complexity. We conducted an expert annotation of over 1,400 request-response pairs, encompassing 230 different base commands. Our findings reveal that while GPT-3.5 struggles to maintain context, incorporating session context into response generation improves the quality of SSH responses. Additionally, we explored whether distinguishing between convincing and non-convincing responses is a metrics issue. We propose a paraphrase-mining approach to address this challenge, which achieved a macro F1 score of 77.85% using cosine distance in our evaluation. This method has the potential to reduce annotation efforts, converge LLM-based honeypot performance evaluation, and facilitate comparisons between new and previous approaches in future research.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"12 ","pages":"144579-144587"},"PeriodicalIF":3.4,"publicationDate":"2024-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10703029","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142408918","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":"Realization of Game Mechanics in Virtual Reality for Amblyopia Treatment","authors":"Vishwas G. Kini;Shonraj Ballae Ganeshrao;P. C. Siddalingaswamy","doi":"10.1109/ACCESS.2024.3472217","DOIUrl":"https://doi.org/10.1109/ACCESS.2024.3472217","url":null,"abstract":"The number of Amblyopia cases has been constantly rising in the recent times. Difficulty in regular clinical visits for therapy has created a need for a monitored engaging home-based amblyopia treatment. In this regard, various technological designs are proposed of which gamified VR amblyopia treatment has showcased positive outcomes over time. However in this work, we identify a need to understand and improvise the gamified VR amblyopia treatment in terms of attentional & engaging elements for better engageability and ensure correlation of stimulus in the virtual environment to the real world for test efficacy. Additionally, correlating the distance and stimulus parameters in VR to the real world is showcased as a design guideline for which the visual acuity test yielded a positive correlation (r =0.845, p =0.002 at \u0000<inline-formula> <tex-math>$alpha =0.01$ </tex-math></inline-formula>\u0000, N =10). To identify the XR interaction game mechanics promoting engagement and motivation in users for regular treatment, a user based study is conducted. The identified game mechanics with a cognitive task load (NASA TLX, M =12.26) are later mapped with the recognised amblyopia characteristics to propose a prototype of XR amblyopic game mechanics. The prototype is evaluated for motivational and engagement factors through Octalysis (Score =332). System Usability Scale and Nielsen’s Heuristic Evaluation are further used to evaluate the design by the experts. Results obtained (SUS, M =72.8 & Heuristics, M >60% and N =10) demonstrate the potential usability of the prototype as home-based gamified amblyopia treatment.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"12 ","pages":"145018-145037"},"PeriodicalIF":3.4,"publicationDate":"2024-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10703065","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142409041","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":"Comparative Analysis of A3C and PPO Algorithms in Reinforcement Learning: A Survey on General Environments","authors":"Alberto del Rio;David Jimenez;Javier Serrano","doi":"10.1109/ACCESS.2024.3472473","DOIUrl":"https://doi.org/10.1109/ACCESS.2024.3472473","url":null,"abstract":"This research article presents a comparison between two mainstream Deep Reinforcement Learning (DRL) algorithms, Asynchronous Advantage Actor-Critic (A3C) and Proximal Policy Optimization (PPO), in the context of two diverse environments: CartPole and Lunar Lander. DRL algorithms are widely known for their effectiveness in training agents to navigate complex environments and achieve optimal policies. Nevertheless, a methodical assessment of their effectiveness in various settings is crucial for comprehending their advantages and disadvantages. In this study, we conduct experiments on the CartPole and Lunar Lander environments using both A3C and PPO algorithms. We compare their performance in terms of convergence speed and stability. Our results indicate that A3C typically achieves quicker training times, but exhibits greater instability in reward values. Conversely, PPO demonstrates a more stable training process at the expense of longer execution times. An evaluation of the environment is needed in terms of algorithm selection, based on specific application needs, balancing between training time and stability. A3C is ideal for applications requiring rapid training, while PPO is better suited for those prioritizing training stability.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"12 ","pages":"146795-146806"},"PeriodicalIF":3.4,"publicationDate":"2024-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10703056","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142447039","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":"DGFusion: A Novel Infrared and Visible Image Fusion Method Based on Diffusion and Generative Adversarial Networks","authors":"Zhiguang Yang;Hanqin Qin;Shan Zeng;Bing Li;Yuanyan Tang","doi":"10.1109/ACCESS.2024.3472479","DOIUrl":"https://doi.org/10.1109/ACCESS.2024.3472479","url":null,"abstract":"In current deep learning-based infrared and visible image fusion algorithms, the image processing step involves converting the RGB channels of visible image into luminance channels. These methods usually pay more attention to the texture details in the image and neglect the equally important color information, which contradicts human vision. Color information, a crucial role in human visual perception, is one of the most intuitive evaluation metrics for image fusion. In order to restore the color of fused images, researchers have made many attempts, such as enhancing brightness or contrast. but the fusion results are not satisfied. Dif-Fusion compensates for the lack of color information by creating a multi-channel data distribution. However, the balance of the multi-channel data distribution still poses a problem. Based on Dif-Fusion, we propose an enhanced algorithm named DGFusion. Firstly, we change the Information input mechanism to balance the weights of infrared image features and visible image, which can enhance the expression of infrared information. Meanwhile, for obtain deep-level features, UNet++ replaces the original U-Net structure of the diffusion model. Furthermore, we introduce a discriminator in the fusion network for superior texture detail preservation. We conducted comparative experiments and ablation studies, which shows that the DGFusion yields superior fusion results. Ablation experiments show that DGFusion improves on most metrics compared to the unmodified method, validating the effectiveness of our approach. Comparison experiments show that our method outperforms several state-of-the-art fusion methods in terms of metrics and visual effects.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"12 ","pages":"147051-147064"},"PeriodicalIF":3.4,"publicationDate":"2024-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10703051","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142447018","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 4D Entangled Memristor Hyperchaotic System and Its New Predefined-Time Sliding Mode Synchronization Control","authors":"Shixiang Zhu;Qingke Lu;Yuming Feng;Dongfang Yan","doi":"10.1109/ACCESS.2024.3472123","DOIUrl":"https://doi.org/10.1109/ACCESS.2024.3472123","url":null,"abstract":"In this paper, a four-dimensional cosine entangled hyperchaotic system with memristor is presented. Through dynamical behavior analysis, including bifurcation diagrams and Lyapunov exponent spectra, we delve deeply into the characteristics of this system’s dynamics. The exploration uncovers the system’s rich dynamic behavior. Subsequently, we design a model circuit for this system to verify its feasibility for implementation. The comparison between experimental results and numerical simulations demonstrates a high level of consistency. Further, a new Lyapunov function is proposed, which satisfies the predetermined time stability condition. On this basis, we design a predetermined time sliding mode controller for synchronizing two chaotic systems. With this controller, the state of the error system can be stabilized within the specified time range. Simulation results show that the proposed control method has excellent anti-interference performance and fast convergence speed. In terms of communication security, the method is able to recover valuable information quickly and accurately, further confirming its excellent performance.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"12 ","pages":"145483-145495"},"PeriodicalIF":3.4,"publicationDate":"2024-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10703030","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142408808","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":"Demand Forecasting in Supply Chain Management for Rossmann Stores Using Weather Enhanced Deep Learning Model","authors":"Nameer Ul Haq Qureshi;Salman Javed;Kamran Javed;Syed Meesam Raza Naqvi;Ali Raza;Zubair Saeed","doi":"10.1109/ACCESS.2024.3472499","DOIUrl":"https://doi.org/10.1109/ACCESS.2024.3472499","url":null,"abstract":"Demand forecasting is one of the essential aspects of supply chain management, as it is linked with the financial performance of the organization. In the retail industry, it is essential to have more accurate forecasts to make suitable decisions. Therefore, the selection of the right forecasting method is considered vital and ideal to meet customer needs. More precisely, this research paper focuses on developing forecasting model for 1115 Rossmann stores located in Europe. Although, previously researchers have been working on developing models to forecast sales demand and to improve accuracy. However, it has been observed that few of the necessary conditions or situations were not being catered for in sales demand forecasting. Such as most researchers used univariate data of total sales for forecasting demand. The internal and external factors such as weather, promotional activity, location of the store, and holidays also play one of the primary roles when it comes to sales demand to forecast. Therefore, it is not specifically a univariate problem but a multivariate problem which have been analyzed in this research. In this research, multivariate dataset including weather variables, other important features have been used in predicting sales demand in supply chain management which helped to achieve better and reliable results. An enhanced deep learning model for sales Demand Forecasting using Weather Data (SDFW) is proposed using Gated Recurrent Unit (GRU) with Grid search. The proposed approach GRU with Grid search showed better performances as compared to previously suggested Long Short Term Memory (LSTM) model. Moreover, Gated Recurrent Unit (GRU) with Grid Search showed significant improvement in sales demand forecasting accuracy when considering weather-related data subsets. These findings will help the Rossmann retail industry in predicting the upcoming sales demand in a more efficient way, which will also optimize their inventory records.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"12 ","pages":"145570-145581"},"PeriodicalIF":3.4,"publicationDate":"2024-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10703040","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142408968","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":"An Improved Quadratic Spline Model Using Curvature Tip Compression—Particle Swarm Optimization to Forecast Accurately the Nonlinear Fluid Calibration Curve","authors":"Jalu A. Prakosa;Norma Alias;Purwowibowo Purwowibowo;Abeer D. Algarni;Naglaa F. Soliman","doi":"10.1109/ACCESS.2024.3472312","DOIUrl":"https://doi.org/10.1109/ACCESS.2024.3472312","url":null,"abstract":"Calibration costs of fluid quantity are not only expensive but also take time, particularly if calibrator facilities are limited. Sometimes, calibrated measuring points do not match the needs of measuring instruments in the field, so forecasts require to be made. Further, the quadratic spline is the simplest non-linear spline model, which vows better accuracy than other linear spline and non-linear regression. For those reasons, we propose a method that minimizes the curvature tip of the quadratic spline model with the popular particle swarm optimization (PSO) technique. This research aims to enhance the accuracy of the quadratic spline prediction model on the calibration curve with a PSO-based curvature tip compression strategy. We want to reduce the effect of oscillations on forming the quadratic spline model. Experimental validation results and comparison of proposed and common methods of quadratic spline interpolation showed that our novel approach, curvature tip compression-PSO, was superior and increased accuracy of 12.18 times from the ordinary quadratic spline and 3.14 times from the linear spline. The proposed method had more minor errors and measurement uncertainties than other ordinary prediction models, thus proving its excellence in predicting unkown values. Calibration curve of turbine flowmeters and salinometers were implemented to this application of the predictive model.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"12 ","pages":"144519-144532"},"PeriodicalIF":3.4,"publicationDate":"2024-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10702592","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142408714","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":"Characterizing the 80 GHz Channel in Static Scenarios: Diffuse Reflection, Scattering, and Transmission Through Trees Under Varying Weather Conditions","authors":"Radek Zavorka;Tomas Mikulasek;Josef Vychodil;Jiri Blumenstein;Aniruddha Chandra;Hussein Hammoud;Jan M. Kelner;Cezary Ziółkowski;Thomas Zemen;Christoph Mecklenbräuker;Ales Prokes","doi":"10.1109/ACCESS.2024.3472003","DOIUrl":"https://doi.org/10.1109/ACCESS.2024.3472003","url":null,"abstract":"The deployment of wireless systems in millimeter wave relies on a thorough understanding of electromagnetic wave propagation under various weather conditions and scenarios. In this study, we characterize millimeter wave propagation effects from measurement data, utilizing channel impulse response analysis with a focus on root mean square delay spread and Rician K-factor. The obtained results highlight the significant influence of weather conditions and foliage on propagation, including diffuse reflection, scattering, and absorption. Particularly, we observed a notable increase in scattering from deciduous trees with leaves, in comparison with bare trees or ones covered by snow or ice. The attenuation of the signal propagated through a tree with foliage is 2.16dB/m higher compared to a bare tree. Our validation measurements within a semi-anechoic chamber confirmed these observations and aided in quantifying the differences. These findings offer valuable insights into the dynamics of millimeter-wave signals that are important for advancing wireless communication technologies.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"12 ","pages":"144738-144749"},"PeriodicalIF":3.4,"publicationDate":"2024-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10703038","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142408727","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}