IEEE Open Journal of the Computer Society最新文献_第10页

Hybrid POF-VLC Systems: Recent Advances, Challenges, Opportunities, and Future Directions 混合POF-VLC系统：最新进展、挑战、机遇和未来方向

IEEE Open Journal of the Computer Society Pub Date : 2025-01-28 DOI: 10.1109/OJCS.2025.3535663

Rola Abdallah;Mohamed Atef;Nasir Saeed

{"title":"Hybrid POF-VLC Systems: Recent Advances, Challenges, Opportunities, and Future Directions","authors":"Rola Abdallah;Mohamed Atef;Nasir Saeed","doi":"10.1109/OJCS.2025.3535663","DOIUrl":"https://doi.org/10.1109/OJCS.2025.3535663","url":null,"abstract":"Hybrid Polymer Optical Fiber and Visible Light Communication (POF-VLC) systems are emerging as a promising solution for high-speed, interference-free connectivity, especially in environments where traditional RF communication is constrained. This paper investigates key nonlinear impairments in POF-VLC systems, such as chromatic dispersion (CD), self-phase modulation (SPM), cross-phase modulation (XPM), four-wave mixing (FWM), and stimulated scattering, which severely degrade signal quality and limit transmission range. We review advanced modulation techniques like Orthogonal Frequency Division Multiplexing (OFDM) and Discrete Multitone Modulation (DMT), alongside traditional methods like Non-Return-to-Zero (NRZ) and On-Off Keying (OOK), evaluating their effectiveness in overcoming these challenges. Furthermore, the application of machine learning, particularly neural network-based equalizers like Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs), is highlighted for their potential to enhance signal quality and system performance. This review emphasizes the transformative role these advanced strategies can play in optimizing hybrid POF-VLC systems, paving the way for their integration into high-demand communication environments. Moreover, this paper presents several promising research directions, such as optimizing training algorithms, exploring deeper neural network architectures, and integrating POF-VLC systems with emerging technologies like beyond 5G, improving energy efficiency, and addressing scalability and complexity in real-time adaptive POF-VLC systems.","PeriodicalId":13205,"journal":{"name":"IEEE Open Journal of the Computer Society","volume":"6 ","pages":"317-335"},"PeriodicalIF":0.0,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10856321","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143480810","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Quantum Computing-Accelerated Kalman Filtering for Satellite Clusters: Algorithms and Comparative Analysis 量子计算加速卡尔曼滤波的卫星簇：算法和比较分析

IEEE Open Journal of the Computer Society Pub Date : 2025-01-27 DOI: 10.1109/OJCS.2025.3535081

Shreyan Prakash;Raj Bhattacherjee;Sainath Bitragunta;Ashutosh Bhatia;Kamlesh Tiwari

{"title":"Quantum Computing-Accelerated Kalman Filtering for Satellite Clusters: Algorithms and Comparative Analysis","authors":"Shreyan Prakash;Raj Bhattacherjee;Sainath Bitragunta;Ashutosh Bhatia;Kamlesh Tiwari","doi":"10.1109/OJCS.2025.3535081","DOIUrl":"https://doi.org/10.1109/OJCS.2025.3535081","url":null,"abstract":"The increasing demand for high-precision real-time data processing in satellite clusters requires efficient algorithms to manage inherent uncertainties in space-based systems. We propose an innovative framework that integrates Quantum Neural Network (QNN) architecture into Kalman filtering processes, specifically tailored for Low Earth Orbit satellite clusters. Our quantum computing-based approach achieves a significant improvement in prediction accuracy and a reduction in mean absolute error compared to classical Kalman filtering techniques. These advances significantly improve computational efficiency and error handling, making the method highly scalable under varying noise levels. A comparative analysis demonstrates the superior performance of the Quantum Kalman Filter in processing speed, resource utilization, and prediction accuracy, all evaluated within the constraints of LEO satellite constellations. These findings highlight the potential of quantum computing to optimize data processing strategies for future missions, including deep space explorations.","PeriodicalId":13205,"journal":{"name":"IEEE Open Journal of the Computer Society","volume":"6 ","pages":"307-316"},"PeriodicalIF":0.0,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10855618","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143403867","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

UVtrack: Multi-Modal Indoor Seamless Localization Using Ultra-Wideband Communication and Vision Sensors UVtrack：使用超宽带通信和视觉传感器的多模态室内无缝定位

IEEE Open Journal of the Computer Society Pub Date : 2025-01-20 DOI: 10.1109/OJCS.2025.3531442

Yi Xu;Zhigang Chen;Ming Zhao;Fengxiao Tang;Yangfan Li;Jiaqi Liu;Nei Kato

{"title":"UVtrack: Multi-Modal Indoor Seamless Localization Using Ultra-Wideband Communication and Vision Sensors","authors":"Yi Xu;Zhigang Chen;Ming Zhao;Fengxiao Tang;Yangfan Li;Jiaqi Liu;Nei Kato","doi":"10.1109/OJCS.2025.3531442","DOIUrl":"https://doi.org/10.1109/OJCS.2025.3531442","url":null,"abstract":"High precision and robust indoor positioning system has a broad range of applications in the area of mobile computing. Due to the advancement of image processing algorithms, the prevalence of surveillance ambient cameras shows promise for offering sub-meter accuracy localization services. The tracking performance in dynamic contexts is still unreliable for ambient camera-based methods, despite their general ability to pinpoint pedestrians in video frames at fine-grained levels. Contrarily, ultra-wideband-based technology can continuously track pedestrians, but they are frequently susceptible to the effects of non-line-of-sight (NLOS) errors on the surrounding environment. We see a chance to combine these two most viable approaches in order to get beyond the aforementioned drawbacks and return to the pedestrian localization issue from a different angle. In this article, we propose UVtrack, a localization system based on UWB and ambient cameras that achieves centimeter accuracy and improved reliability. The key innovation of UVtrack is a well-designed particle filter which adopts UWB and vision results in the weight update of the particle set, and an adaptive distance variance weighted least squares method (DVLS) to improve UWB sub-system robustness. We take UVtrack into use on common smartphones and test its effectiveness in three different situations. The results demonstrated that UVtrack attains an outstanding localization accuracy of 7 cm.","PeriodicalId":13205,"journal":{"name":"IEEE Open Journal of the Computer Society","volume":"6 ","pages":"272-281"},"PeriodicalIF":0.0,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10845877","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143107126","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

2024 List of Reviewers* 2024 年审查员名单*

IEEE Open Journal of the Computer Society Pub Date : 2025-01-14 DOI: 10.1109/OJCS.2025.3527836

引用次数: 0

New Incoming EIC Editorial 新到来的EIC社论

IEEE Open Journal of the Computer Society Pub Date : 2025-01-10 DOI: 10.1109/OJCS.2025.3525947

Vincenzo Piuri

引用次数: 0

Comparative Analysis of Traditional and Modern NLP Techniques on the CoLA Dataset: From POS Tagging to Large Language Models 传统与现代自然语言处理技术在CoLA数据集上的比较分析：从词性标注到大型语言模型

IEEE Open Journal of the Computer Society Pub Date : 2025-01-07 DOI: 10.1109/OJCS.2025.3526712

Abdessamad Benlahbib;Achraf Boumhidi;Anass Fahfouh;Hamza Alami

{"title":"Comparative Analysis of Traditional and Modern NLP Techniques on the CoLA Dataset: From POS Tagging to Large Language Models","authors":"Abdessamad Benlahbib;Achraf Boumhidi;Anass Fahfouh;Hamza Alami","doi":"10.1109/OJCS.2025.3526712","DOIUrl":"https://doi.org/10.1109/OJCS.2025.3526712","url":null,"abstract":"The task of classifying linguistic acceptability, exemplified by the CoLA (Corpus of Linguistic Acceptability) dataset, poses unique challenges for natural language processing (NLP) models. These challenges include distinguishing between subtle grammatical errors, understanding complex syntactic structures, and detecting semantic inconsistencies, all of which make the task difficult even for human annotators. In this article, we compare a range of techniques, from traditional methods such as Part-of-Speech (POS) tagging and feature extraction methods like CountVectorizer with Term Frequency-Inverse Document Frequency (TF-IDF) and N-grams, to modern embeddings such as FastText and Embeddings from Language Models (ELMo), as well as deep learning architectures like transformers and Large Language Models (LLMs). Our experiments show a clear improvement in performance as models evolve from traditional to more advanced approaches. Notably, state-of-the-art (SOTA) results were obtained by fine-tuning GPT-4o with extensive hyperparameter tuning, including experimenting with various epochs and batch sizes. This comparative analysis provides valuable insights into the relative strengths of each technique for identifying morphological, syntactic, and semantic violations, highlighting the effectiveness of LLMs in these tasks.","PeriodicalId":13205,"journal":{"name":"IEEE Open Journal of the Computer Society","volume":"6 ","pages":"248-260"},"PeriodicalIF":0.0,"publicationDate":"2025-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10829978","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143106179","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Quantitative Cybersecurity Analysis Framework for Cyber Physical Systems: A Conceptual Approach 网络物理系统的定量网络安全分析框架：概念方法

IEEE Open Journal of the Computer Society Pub Date : 2025-01-06 DOI: 10.1109/OJCS.2024.3520315

Alhassan Abdulhamid;Sohag Kabir;Ibrahim Ghafir;Ci Lei;Khalil El Hindi;Mohammad Hammoudeh

{"title":"Quantitative Cybersecurity Analysis Framework for Cyber Physical Systems: A Conceptual Approach","authors":"Alhassan Abdulhamid;Sohag Kabir;Ibrahim Ghafir;Ci Lei;Khalil El Hindi;Mohammad Hammoudeh","doi":"10.1109/OJCS.2024.3520315","DOIUrl":"https://doi.org/10.1109/OJCS.2024.3520315","url":null,"abstract":"Cyber-physical systems (CPS) are indispensable in various sectors, enabling convenient and efficient processes in today's rapidly evolving technological landscape. However, the integration of internet-enabled components with physical processes exposes CPS to numerous security threats, rendering them susceptible to potential cyber-attacks. This paper presents a quantitative analysis framework for evaluating the security attributes of CPS conceptual design. Focusing on CPS design architecture, the framework models and quantifies security attributes by considering various dimensions. The paper demonstrates the integration of qualitative expert inputs into a fuzzy logic system to address the challenges and uncertainties associated with vulnerability data in CPS security quantification. Additionally, it examines the statistical dependence of basic attack steps (BASs) and their impact on the overall system security analysis, taking into account the intricate connectivity of CPS and the vulnerabilities that attackers could exploit. The novelty of the proposed framework lies in its integrated approach to modelling and quantifying cybersecurity attributes in the CPS environment while considering uncertainties in vulnerability data and dependencies between security events. The computation of statistical and stochastic dependencies among BASs is achieved by mapping the attack tree (AT) to a higher statistical model of the Bayesian network (BN) model. The application of this framework was demonstrated using an intelligent glucose monitoring and insulin administration system (IGMIAS). The framework's general nature makes it adaptable for quantifying cybersecurity behaviours in any CPS environment.","PeriodicalId":13205,"journal":{"name":"IEEE Open Journal of the Computer Society","volume":"6 ","pages":"613-626"},"PeriodicalIF":0.0,"publicationDate":"2025-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10829501","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144073183","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimizing Energy Efficiency in UPA-Assisted SWIPT Massive MIMO Systems Over Rician Fading Channels upa辅助SWIPT大规模MIMO系统在衰落信道上的能源效率优化

IEEE Open Journal of the Computer Society Pub Date : 2025-01-03 DOI: 10.1109/OJCS.2025.3525519

Mohammad Hassan Adeli;Dariush Abbasi-Moghadam;Hossein Fotouhi;S. Mohammad Razavizadeh

{"title":"Optimizing Energy Efficiency in UPA-Assisted SWIPT Massive MIMO Systems Over Rician Fading Channels","authors":"Mohammad Hassan Adeli;Dariush Abbasi-Moghadam;Hossein Fotouhi;S. Mohammad Razavizadeh","doi":"10.1109/OJCS.2025.3525519","DOIUrl":"https://doi.org/10.1109/OJCS.2025.3525519","url":null,"abstract":"Massive Multiple Input Multiple Output (mMIMO) is a promising solution for enabling green communication in next-generation wireless networks. Integrating mMIMO with Simultaneous Wireless Information and Power Transfer (SWIPT) technology can further enhance the system efficiencies in terms of Energy Efficiency (EE) and spectral efficiency. This article studies the feasibility and energy-efficient design of a uniform planar antenna (UPA)-assisted mMIMO-enabled SWIPT system. The downlink transmission of the SWIPT mMIMO system over the Rician fading channels is investigated with terminals harvesting energy based on a nonlinear energy harvesting model. We derive approximate expressions for signal-to-interference-plus-noise Ratio (SINR) and harvested power. Additionally, we formulate an EE optimization problem considering user-level quality of service and total transmit power constraints. To solve this nonconvex problem, we jointly optimize the allocated power and Power Splitting (PS) ratios by exploiting the fractional programming and convex-concave procedure approaches. Results demonstrate the superiority of our proposed design compared to the conventional scenarios with equal power allocation and fixed PS ratio algorithms with about 2 to 5 times EE improvements. The Results also indicate a considerably higher growth rate on EE by increasing the number of antennas and Rician factors compared to the two other methods.","PeriodicalId":13205,"journal":{"name":"IEEE Open Journal of the Computer Society","volume":"6 ","pages":"236-247"},"PeriodicalIF":0.0,"publicationDate":"2025-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10820514","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143107127","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Leveraging Deep Learning and Multimodal Large Language Models for Near-Miss Detection Using Crowdsourced Videos 利用深度学习和多模态大语言模型使用众包视频进行近靶检测

IEEE Open Journal of the Computer Society Pub Date : 2025-01-03 DOI: 10.1109/OJCS.2025.3525560

Shadi Jaradat;Mohammed Elhenawy;Huthaifa I. Ashqar;Alexander Paz;Richi Nayak

{"title":"Leveraging Deep Learning and Multimodal Large Language Models for Near-Miss Detection Using Crowdsourced Videos","authors":"Shadi Jaradat;Mohammed Elhenawy;Huthaifa I. Ashqar;Alexander Paz;Richi Nayak","doi":"10.1109/OJCS.2025.3525560","DOIUrl":"https://doi.org/10.1109/OJCS.2025.3525560","url":null,"abstract":"Near-miss traffic incidents, positioned just above \"unsafe acts\" on the safety triangle theory, offer crucial predictive insights for preventing crashes. However, these incidents are often underrepresented in traffic safety research, which tends to focus primarily on actual crashes. This study introduces a novel AI-based framework designed to detect and analyze near-miss and crash events in crowdsourced dashcam footage. The framework consists of two key components: a deep learning model to segment video streams and identify potential near-miss or crash incidents and a multimodal large language model (MLLM) to further analyze and extract narrative information from the identified events. We evaluated three deep learning models—CNN, Vision Transformers (ViTs), and CNN+LSTM—on a dataset specifically curated for three-class classification (crashes, near-misses, and normal driving events). CNN achieved the highest accuracy (90%) and F1-score (89%) at the frame level. At the event level, ViTs delivered a strong performance with a test accuracy of 77.27% and an F1-score of 67.37%, while CNN+LSTM, although lower in overall performance, demonstrated significant potential with a test accuracy of 78.1% and an F1-score of 68.69%. For a deeper analysis, we applied GPT-4o to process critical safety events (near-misses and crashes), utilizing both zero-shot and few-shot learning for narrative generation and feature extraction. The zero-shot learning method performed better, achieving an accuracy of 81.2% and an F1-score of 81.9%. This study underscores the potential of combining deep learning with MLLMs to enhance traffic safety analysis by integrating near-miss data as a key predictive layer. Our approach highlights the importance of leveraging near-miss incidents to proactively enhance road safety, thereby reducing the likelihood of crashes through early intervention and better event understanding.","PeriodicalId":13205,"journal":{"name":"IEEE Open Journal of the Computer Society","volume":"6 ","pages":"223-235"},"PeriodicalIF":0.0,"publicationDate":"2025-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10820995","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143106743","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Annual Report Text Information and Credit Rating Based on the Perspective of Readability 基于可读性视角的年度报告文本信息与信用评级

IEEE Open Journal of the Computer Society Pub Date : 2024-12-31 DOI: 10.1109/OJCS.2024.3523699

Yu Gong;Muhan Shi;Dongli Han

引用次数: 0