IEEE Open Journal of the Computer Society最新文献

筛选
英文 中文
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
{"title":"2024 List of Reviewers*","authors":"","doi":"10.1109/OJCS.2025.3527836","DOIUrl":"https://doi.org/10.1109/OJCS.2025.3527836","url":null,"abstract":"","PeriodicalId":13205,"journal":{"name":"IEEE Open Journal of the Computer Society","volume":"6 ","pages":"1-3"},"PeriodicalIF":0.0,"publicationDate":"2025-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10841813","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142975824","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
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
{"title":"New Incoming EIC Editorial","authors":"Vincenzo Piuri","doi":"10.1109/OJCS.2025.3525947","DOIUrl":"https://doi.org/10.1109/OJCS.2025.3525947","url":null,"abstract":"","PeriodicalId":13205,"journal":{"name":"IEEE Open Journal of the Computer Society","volume":"6 ","pages":"2-3"},"PeriodicalIF":0.0,"publicationDate":"2025-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10837004","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142940903","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
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
{"title":"Annual Report Text Information and Credit Rating Based on the Perspective of Readability","authors":"Yu Gong;Muhan Shi;Dongli Han","doi":"10.1109/OJCS.2024.3523699","DOIUrl":"https://doi.org/10.1109/OJCS.2024.3523699","url":null,"abstract":"The current credit rating system gives much attention to the quantitative situation of the company's finances, whereas the soft information hidden in the company's annual reports is often ignored. This study reviews the annual reports of A-share listed companies in China from 2007 to 2021 and explores the relationship between the readability of the annual reports and the credit ratings given by rating agencies. We find that the readability of annual reports significantly impacts the company's credit rating. Further heterogeneity testing reveals that this impact significantly varies across different types of companies. Therefore, credit rating agencies should pay due attention to the soft information in the annual report when rating a company to ensure accuracy in their ratings.","PeriodicalId":13205,"journal":{"name":"IEEE Open Journal of the Computer Society","volume":"6 ","pages":"403-412"},"PeriodicalIF":0.0,"publicationDate":"2024-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10818970","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143621578","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
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
相关产品
×
本文献相关产品
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信