检索结果-内蒙古大学图书馆

Polar codes: Encoding/decoding and rate-compatible jointly design for HARQ system

Intelligent and Converged Networks 2021年第4期2卷 334-346页

作者： Qiaoli Zeng Quan Zhou Xiangkun He Youming Sun Xiangcheng Li Haiqiang Chen School of Computer Electronics and Information and Guangxi Colleges and Universities Key Laboratory of Multimedia Communications and Information ProcessingGuangxi UniversityNanning 530004China Department of Mechanical and Aerospace Engineering Nanyang Technological UniversitySingapore 999002Singapore

Polar coding are the first class of provable capacity-achieving coding techniques for a wide range of *** an ideal recursive structure and many elegant mathematical properties,polar codes are inherently implemented with low complexity encoding and decoding *** the block length of the original polar construction is limited to powers of two,rate-compatible polar codes(RCPC)are presented to meet the flexible length/rate transmission requirements in *** RCPC codes are well-conditioned to combine with the hybrid automatic repeat request(HARQ)system,providing high throughput efficiency and such RCPC-HAPQ scheme is commonly used in delay-insensitive communication *** paper first gives a survey of both the classical and state-of-the-art encoding/decoding algorithms for polar *** the RCPC construction methods are discussed,including the puncturing,shortening,multi-kernel construction,***,we investigate several RCPC-HARQ jointly design systems and discuss their encoding gain and re-transmission diversity gain.

关键词： polar code rate compatible hybrid automatic re-transmission request polar coding/decoding

来源：评论

学校读者我要写书评

暂无评论

Dynamic Spectrum Control-Assisted Secure and Efficient Transmission Scheme in Heterogeneous Cellular Networks

引用

engineering 2022年第10期17卷 220-231页

作者： Chenxi Li Lei Guan Huaqing Wu Nan Cheng Zan Li Xuemin(Sherman)Shen State Key Laboratory of Integrated Services Networks Xidian UniversityXi’an 710071China Department of Electrical and Computer Engineering University of WaterlooWaterlooON N2L 3G1Canada Collaborative Innovation Center of Information Sensing and Understanding Xi’an 710071China

Heterogeneous cellular networks(HCNs)are envisioned as a promising architecture to provide seamless wireless coverage and increase network ***,the densified multi-tier network architecture introduces excessive intra-and cross-tier interference and makes HCNs vulnerable to eavesdropping *** this article,a dynamic spectrum control(DSC)-assisted transmission scheme is proposed for HCNs to strengthen network security and increase the network ***,the proposed DSC-assisted transmission scheme leverages the idea of block cryptography to generate sequence families,which represent the transmission decisions,by performing iterative and orthogonal sequence *** on the sequence families,multiple users can dynamically occupy different frequency slots for data transmission *** addition,the collision probability of the data transmission is analyzed,which results in closed-form expressions of the reliable transmission probability and the secrecy ***,the upper and lower bounds of network capacity are further derived with given requirements on the reliable and secure transmission *** results demonstrate that the proposed DSC-assisted scheme can outperform the benchmark scheme in terms of security ***,the impacts of key factors in the proposed DSC-assisted scheme on the network capacity and security are evaluated and discussed.

关键词： Heterogeneous cellular networks Dynamic spectrum control Transmission security Efficient data transmission

来源：评论

学校读者我要写书评

暂无评论

I Can See Your Secrets, A Way to Recognize User Pin Codes by Surveillance Camera 10

I Can See Your Secrets, A Way to Recognize User Pin Codes by...

引用

10th IEEE Smart World Congress, SWC 2024

作者： Guo, Zhenyang Cao, Jin Zan, Xiaoyong Yang, Jiawei Li, Ang Niu, Ben Sun, Zhe Yin, Lihua Li, Hui Xidian University School of Cyber Engineering Xi'an China The State Key Laboratory of Integrated Services Networks Xi'an China ByteDance Ltd Beijing China University of Maryland Department of Electrical & Computer Engineering College Park United States Institute of Information Engineering Chinese Academy of Sciences Beijing China Cyberspace Institute of Advanced Technology Guangzhou University Guangzhou China

ISBN: (纸本)9798331520861

Surveillance cameras are currently widely used in public and private places to enhance area security and reduce crime rates. However, the extensive use of surveillance cameras also poses significant threats, particularly concerning the leakage of users' private information. Surveillance cameras are often installed in the corners of areas such as hotel front desks, supermarket checkout areas, or ticket offices to observe user behavior, which can lead to shoulder-surfing attacks. In these public or private settings, when users input their personal identification number (PIN) for unlocking or payment, this process may be intentionally or unintentionally exposed and recorded. If the PIN is compromised, it can result in severe privacy breaches and financial losses for users. Existing work primarily focuses on dedicated handheld recording devices such as cameras and smartphones, lacking discussion on public surveillance cameras. In this paper, we first present an attack model for such scenarios. Based on this model, we design and implement an automated attack system for PIN recognition. Experimental results demonstrate that our proposed attack model is both feasible and effective, achieving 90 % accuracy with our system. Finally, we urge users, smartphone manufacturers, and surveillance camera manufacturers to be aware of this attack vector to prevent further harm. © 2024 IEEE.

关键词： Smartphones

来源：评论

学校读者我要写书评

暂无评论

CAT: Controllable Attribute Translation for Fair Facial Attribute Classification 17th

CAT: Controllable Attribute Translation for Fair Facial Att...

引用

17th European Conference on computer Vision, ECCV 2022

作者： Li, Jiazhi Abd-Almageed, Wael USC Ming Hsieh Department of Electrical and Computer Engineering Los Angeles United States USC Information Sciences Institute Marina del Rey United States Visual Intelligence and Multimedia Analytics Laboratory Marina del Rey United States

ISBN: (纸本)9783031250842

As the social impact of visual recognition has been under scrutiny, several protected-attribute balanced datasets emerged to address dataset bias in imbalanced datasets. However, in facial attribute classification, dataset bias stems from both protected attribute level and facial attribute level, which makes it challenging to construct a multi-attribute-level balanced real dataset. To bridge the gap, we propose an effective pipeline to generate high-quality and sufficient facial images with desired facial attributes and supplement the original dataset to be a balanced dataset at both levels, which theoretically satisfies several fairness criteria. The effectiveness of our method is verified on sex classification and facial attribute classification by yielding comparable task performance as the original dataset and further improving fairness in a comprehensive fairness evaluation with a wide range of metrics. Furthermore, our method outperforms both resampling and balanced dataset construction to address dataset bias, and debiasing models to address task bias. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Classification (of information)

来源：评论

学校读者我要写书评

暂无评论

Character-Level Street View Text Spotting Based on Deep Multisegmentation Network for Smarter Autonomous Driving

IEEE Transactions on Artificial Intelligence

引用

IEEE Transactions on Artificial Intelligence 2022年第2期3卷 297-308页

作者： Zhang, Chongsheng Tao, Yuefeng Du, Kai Ding, Weiping Wang, Bin Liu, Ji Wang, Wei Henan Provincial Key Laboratory of Big Data Analysis and Processing Laboratory of the Yellow River Cultural Heritage Henan University Kaifeng475001 China School of Information Science and Technology Nantong University Nantong226019 China School of Electrical Engineering Zhejiang University Hangzhou310058 China Big Data Lab Baidu Inc. Beijing100044 China School of Computer and Information Technology Beijing Jiaotong University Beijing100044 China

Urban scenes are full of street entities with sign boards. Therefore, in autonomous driving, street view text spotting techniques will play a significant role in the precise understanding of surrounding scenes during driving, because texts contained in the images usually provide important clues for accurate image understanding, while it is often ambiguous for existing computer vision algorithms to understand scene images without texts. In this work, we propose a Multi-Segmentation network for character-level scene Text Detection (MSTD). The MSTD introduces a densely connected atrous spatial pyramid pooling module to enlarge the receptive field of the feature extraction layer, so as to localize long as well as large-sized text instances. Moreover, it devises a double segmentation subnetwork to utilize two independent but inherently complementary losses to co-optimize the network and increase the reliability of the confidence scores in predicting the text/nontext areas. With the character instances detected by the MSTD, one can easily perform scene text spotting with classic object recognition networks such as ResNet and DenseNet. We carried out extensive experiments on nine scene text datasets to demonstrate the outstanding performance of the MSTD on character-level and line-level text instance localization and scene text recognition, where the MSTD significantly outperforms the state-of-the-art scene text detection methods and the sequence-to-sequence-learning-based scene text recognizers. © 2020 IEEE.

关键词： Character recognition

来源：评论

学校读者我要写书评

暂无评论

Weakly Supervised Invariant Representation Learning via Disentangling Known and Unknown Nuisance Factors 17th

Weakly Supervised Invariant Representation Learning via Dis...

引用

17th European Conference on computer Vision, ECCV 2022

作者： Zhu, Jiageng Xie, Hanchen Abd-Almageed, Wael USC Ming Hsieh Department of Electrical and Computer Engineering Los Angeles United States USC Information Sciences Institute Marina del Rey United States Visual Intelligence and Multimedia Analytics Laboratory Marina del Rey United States

ISBN: (纸本)9783031250842

Disentangled and invariant representations are two critical goals of representation learning and many approaches have been proposed to achieve either one of them. However, those two goals are actually complementary to each other so that we propose a framework to accomplish both of them simultaneously. We introduce a weakly supervised signal to learn disentangled representation which consists of three splits containing predictive, known nuisance and unknown nuisance information respectively. Furthermore, we incorporate contrastive method to enforce representation invariance. Experiments shows that the proposed method outperforms state-of-the-art (SOTA) methods on four standard benchmarks and shows that the proposed method can have better adversarial defense ability comparing to other methods without adversarial training. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Artificial intelligence

来源：评论

学校读者我要写书评

暂无评论

An Efficient Particle YOLO Detector for Urine Sediment Detection 4th

An Efficient Particle YOLO Detector for Urine Sediment Dete...

引用

4th International Conference on Machine Learning for Cyber Security, ML4CS 2022

作者： Chen, Zejian Hu, Rong Chen, Fukun Fan, Haoyi Ching, Fum Yew Li, Zuoyong Su, Shimei Fujian Provincial Key Laboratory of Big Data Mining and Applications School of Computer Science and Mathematics Fujian University of Technology Fujian Fuzhou350118 China School of Computer and Artificial Intelligence Zhengzhou University Henan Zhengzhou450001 China School of Computer Sciences Universiti Sains Malaysia Penang11800 Malaysia Fujian Provincial Key Laboratory of Information Processing and Intelligent Control College of Computer and Control Engineering Minjiang University Fujian Fuzhou350121 China School of Electrical Engineering Zhengzhou University Henan Zhengzhou450001 China

ISBN: (纸本)9783031201011

Urine sediment detection is an essential aid in assessing kidney health. Traditional machine learning approaches treat urine sediment particle detection as an image classification task, segmenting particles for detection based on information such as edges or thresholds. However, the segmentation of sediment particles is complex due to the low contrast and weak edge characteristics of urine sediment images. In this paper, we consider urine sediment particle detection as a object detection task and propose the YOLOv5s-CBL, a detector dedicated to particle detection. Specifically, to mitigate the impact of background noise on detection accuracy, we inherit CBAM on the YOLOv5s model to help the network filter useless noise information and find regions of interest to extract target features. Then, we expand the original three-scale feature layer to improve the sensitivity of the model to larger-scale target sediment particles. Finally, we use the BiFPN structure instead of the original PANet combined with the FPN structure, which can more effectively fuse multiple different scales of information to improve the detection performance of the model. We compared state-of-the-art methods on two real-world datasets, and the experimental results demonstrated the effectiveness of YOLOv5s-CBL. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

Logical Relation Modeling and Mining in Hyperbolic Space for Recommendation 40

Logical Relation Modeling and Mining in Hyperbolic Space for...

引用

40th IEEE International Conference on Data engineering, ICDE 2024

作者： Tan, Yanchao Lv, Hang Zhou, Zihao Guo, Wenzhong Xiong, Bo Liu, Weiming Chen, Chaochao Wang, Shiping Yang, Carl College of Computer and Data Science Fuzhou University Fuzhou China Engineering Research Center of Big Data Intelligence Ministry of Education Fuzhou China Fujian Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou University Fuzhou China Institute for Artificial Intelligence University of Stuttgart Stuttgart Germany College of Computer Science Zhejiang University Hangzhou China Emory University Department of Computer Science Atlanta United States

ISBN: (纸本)9798350317152

The sparse interactions between users and items have aggravated the difficulty of their representations in recommender systems. Existing methods leverage tags to alleviate the sparsity problem but ignore prevalent logical relations among items and tags (e.g., membership, hierarchy, and exclusion), which can be leveraged to enhance the accuracy of modeling user preferences and conducting recommendations. To this end, we propose to extract logical relations among item tags from existing tag taxonomies and exploit the individual strengths of the Poincaré and the Lorentz models in hyperbolic space for logical relation modeling towards enhanced recommendations. Moreover, we find that the logical relations directly extracted from existing tag taxonomies can be inaccurate and coarse. Therefore, we further devise innovative consistency-based and granularity-based weighting mechanisms based on user behavior patterns for data-driven logical relation mining that can be jointly optimized along with recommendations in an end-to-end fashion. Extensive experiments on four real-world benchmark datasets show drastic performance gains brought by our proposed framework, which constantly achieves an average of 8.25% improvement over state-of-the-art competitors regarding both Recall and NDCG metrics. Insightful case studies further demonstrate that our automatically refined logical relations are highly accurate and interpretable. © 2024 IEEE.

关键词： Recommender systems

来源：评论

学校读者我要写书评

暂无评论

Mathematical Modeling of a Programmable Decision Network to Simulate the Socio-Economic Environment 9

Mathematical Modeling of a Programmable Decision Network to ...

引用

9th International Conference on Mathematics and computers in Sciences and Industry, MCSI 2024

作者： Meftah, Mohammed Charaf Eddine Laouid, Abdelkader Kara, Mostefa Karampidis, Konstantinos Papadourakis, Giorgos Tampouratzis, Manolis Mastorakis, Nikos El Oued University LIAP Laboratory PO Box 789 El Oued39000 Algeria King Fahd University of Petroleum and Minerals Information and Computer Science Department Academic Belt Road Dhahran31261 Saudi Arabia Hellenic Mediterranean University Department of Electrical and Computer Engineering Crete Greece Technical University of Sofia Sofia Bulgaria Hellenic Naval Academy Piraeus Greece

ISBN: (纸本)9798350377224

Mathematical modeling of decision networks is crucial in simulating the socio-economic environment, especially as these systems grow increasingly complex. Such models allow for a structured and quantitative analysis of the myriad factors and interactions that define modern economies and societies. These models enable researchers and policymakers to predict outcomes, identify optimal strategies, and evaluate the potential impacts of various decisions. This is particularly important in addressing intricate issues such as market dynamics, social welfare, and policy implementation, where traditional analytical methods fall short. Moreover, mathematical models facilitate the testing of hypothetical scenarios, providing valuable insights into how changes in one part of the system might ripple through the entire network. This paper proposes mathematical modelling of a new programmable decision network that allows simulating the socio-economic environment as composed of dynamically interacting components and relationships. The proposed network model, thanks to its programmability, can have a more comprehensive and deeper performance than the rest of the available traditional decision networks. As a result, these models are indispensable tools for understanding and managing the complexities of contemporary economic and social landscapes, ultimately aiding in the formulation of informed, effective policies and strategies. © 2024 IEEE.

关键词： Decision network Link Mathematical modelling Node Socio-economic environment Time

来源：评论

学校读者我要写书评

暂无评论

An Improved Variable Parameter Phase-Locked Loop for Single-Carrier Underwater Acoustic Communications

An Improved Variable Parameter Phase-Locked Loop for Single-...

引用

2023 MTS/IEEE U.S. Gulf Coast, OCEANS 2023

作者： Liu, Changxin Tao, Jun Huang, Weimin School of Information Science and Engineering Southeast University Nanjing210096 China Pengcheng Laboratory Shenzhen518000 China Memorial University of Newfoundland Department of Electrical and Computer Engineering St. John'sNLA1B 3X5 Canada

ISBN: (纸本)9798218142186

A direct adaptive equalizer (DAE) coupled with a phase-locked loop (PLL) has been proved as an efficient receiver scheme for single-carrier coherent underwater acoustic (UWA) communications. Ever since its birth, numerous improvements have been proposed for the DAE. In contrast, the PLL has been somehow overlooked. A PLL with predetermined coefficients suffers performance degradation when channel conditions change, then a variable-parameter (VP) PLL designed via gradient descent (GD) method was proposed. The GD-VP-PLL is sensitive to parameter initialization though. In this paper, we propose a new VP-PLL scheme in light of the recursive Gauss-Newton (RGN) method. The resulting RGN-VP-PLL has been tested by at-sea experimental data, and showed better performance than the GD-VP-PLL and a PLL with fixed coefficients. Moreover, it is insensitive to initialization of parameters. © 2023 The Marine Technology Society (MTS).

关键词： Underwater acoustic communication

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：