检索结果-内蒙古大学图书馆

Sparse Nonnegative Matrix Factorization for Multiple-Local-Community detection

IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS 2020年第5期7卷 1220-1233页

作者： Kamuhanda, Dany Wang, Meng He, Kun Huazhong Univ Sci & Technol Sch Comp Sci & Technol Wuhan 430074 Peoples R China

Local community detection consists of finding a group of nodes closely related to the seeds, a small set of nodes of interest. Such groups of nodes are densely connected or have a high probability of being connected internally than their connections to other clusters in the network. Existing local community detection methods focus on finding either one local community that all seeds are most likely to be in or finding a single community for each of the seeds. However, a seed member usually belongs to multiple local overlapping communities. In this work, we present a novel method of detecting multiple local communities to which a single-seed member belongs. The proposed method consists of three key steps: 1) local sampling with Personalized PageRank (PPR);2) using the sparseness generated by a sparse nonnegative matrix factorization (SNMF) to estimate the number of communities in the sampled subgraph;and 3) using SNMF soft community membership vectors to assign nodes to communities. The proposed method shows favorable accuracy performance and a good conductance compared with state-of-the-art community detection methods by experiments using a combination of artificial and real-world networks.

关键词： Task analysis Sparse matrices detection algorithms Social network services Encoding Metadata Image edge detection Clustering local community detection nonnegative matrix factorization (NMF) social networks sparseness

来源：评论

学校读者我要写书评

暂无评论

Real-Time Fall detection Using Uncalibrated Fisheye Cameras

引用

IEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL SYSTEMS 2020年第3期12卷 588-600页

作者： Kottari, Konstantina N. Delibasis, Konstantinos K. Maglogiannis, Ilias G. Univ Thessaly Sch Sci Comp Sci & Biomed Informat Dept Lamia 35131 Greece Univ Piraeus Sch Informat & Commun Technol Digital Syst Dept Piraeus 18534 Greece

In this article, we describe an approach for the problem of fall detection among the several other everyday activities in indoor environment, using three uncalibrated fisheye cameras. The proposed methodology requires the input segmented silhouettes from the three simultaneously acquired frames, and it is capable of detecting fall events in every location of the imaged environment. The presented algorithm uses the model of fisheye image formation that is based on the spherical projection followed by central projection. Under this model, vertical structures are imaged as straight lines passing through the center of field of view, by a camera with approximately vertical optical axis. The main advantages of this article are the simplicity of the detecting rule, the speed of execution, and the utilization of heterogeneous omnidirectional cameras that allows simultaneous imaging along any direction. The proposed algorithm is designed and parameterized using an extensive data set of synthetic frames. The results from the real videos are presented using the frame statistics and the event-based statistics. The proposed algorithm correctly detects the fall events within standing or walking, as well as other nonfalling activities.

关键词： Cameras Calibration Feature extraction Three-dimensional displays detection algorithms Hidden Markov models Head Computer vision fall detection event fisheye cameras multicamera feature extraction rule-based recognition

来源：评论

学校读者我要写书评

暂无评论

Jumping-At-Air: Jumping without Touching the Ground in Virtual Reality

Jumping-At-Air: Jumping without Touching the Ground in Virtu...

引用

Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW), IEEE Conference on

作者： Liuyang Chen Gaoqi He Changbo Wang NetEase (Hangzhou) Network Co. Ltd East China Normal University

ISBN: (数字)9798331514846

ISBN: (纸本)9798331525637

We propose Jumping-At-Air, where the avatar jumps in the virtual world and lands at a higher air while the user jumps in the real world, then jumps again from the air. The core idea is to first create a pair of pressure-sensing shoes based on the ESP32 chip, equipped with pressure sensors in the soles, to accurately detect the jumping stage. Then, through a carefully designed equation with two adjustable parameters, the user’s jump trajectory in the real world is redirected to drive the jumps of the avatar in the virtual world. The redirected jumping curve is differentiable and continuous throughout its domain and conforms to the definition of a parabola.

关键词： Human computer interaction Pressure sensors Three-dimensional displays Avatars Footwear Games User experience Hardware Trajectory detection algorithms

来源：评论

学校读者我要写书评

暂无评论

Malicious User detection for Cooperative Mobility Tracking in Autonomous Driving

引用

IEEE INTERNET OF THINGS JOURNAL 2020年第6期7卷 4922-4936页

作者： Pi, Wang Yang, Pengtao Duan, Dongliang Chen, Chen Cheng, Xiang Yang, Liuqing Li, Hang Peking Univ Sch Elect Engn & Comp Sci Dept Elect State Key Lab Adv Opt Commun Syst & Networks Beijing 100871 Peoples R China Univ Wyoming Dept Elect & Comp Engn Laramie WY 82071 USA Colorado State Univ Dept Elect & Comp Engn Ft Collins CO 80523 USA Shenzhen Res Inst Big Data Data Driven Intelligent Informat Syst Lab Shenzhen 518172 Peoples R China

The mobility status of self and surrounding vehicles provides important information to various tasks in autonomous driving (AD) and intelligent transportation system (ITS). Accordingly, a precise, stable, and robust mobility tracking framework is essential. Compared with self-tracking that relies only on mobility observations from onboard sensors [e.g., global positioning system (GPS), inertial measurement unit (IMU), and camera], cooperative tracking markedly increases the precision and reliability of the mobility information by integrating observations from roadside units (RSUs) and nearby vehicles through vehicle-to-everything (V2X) communications in the Internet of Vehicles (IoV). Nevertheless, cooperative tracking can be quite vulnerable if there are malicious users sending bogus observations in the cooperative network. In this article, we present a malicious user detection framework, which includes two sequential detection algorithms and a secure mobility data exchange and fusion model to detect and remove bogus mobility information and integrate proposed detection algorithms with previous data fusion algorithms, which secures the cooperative mobility tracking in AD, ITS. Simulations validate the effectiveness and robustness of the proposed framework under different types of attacks.

关键词： detection algorithms Heuristic algorithms Internet of Things Sensors Data models Vehicle dynamics Global Positioning System Autonomous driving (AD) cooperative mobility tracking intelligent transportation system (ITS) Internet of Vehicles (IoV) malicious user detection sequential detection

来源：评论

学校读者我要写书评

暂无评论

Research on Fault detection Algorithm of Pantograph Based on Edge Computing Image Processing

引用

IEEE ACCESS 2020年 8卷 84652-84659页

作者： Li, Hongsheng Huanghuai Univ Intelligent Mfg Inst Zhumadian 463000 Peoples R China

Traditional pantograph detection technology has installed a large number of various types of sensors on the pantograph, which is not conducive to the flow characteristics of the pantograph. Traditional detection technology can neither monitor the operation status of the pantograph in real time, nor guarantee the safe operation of the entire train. The existing schemes are only manual solutions, and intelligent real-time monitoring is performed without error, and a lot of labor costs are required. Focusing on the shortcomings of traditional pantographs in sliding plate wear and sliding plate crack detection, an improved mean filtering algorithm is proposed to optimize the image of pantograph, and the adaptive Canny edge detection technology is used to accurately calculate the skateboard wear. Firstly, the improved image algorithm is used to pre-treat the pantograph slide wear and crack length, then the improved mean filtering algorithm is combined with adaptive Canny operator for image optimization detection, and finally the edge calculation is used for crack identification. An optimized real-time on-line detection technology is proposed, which can accurately measure the wear and tear of skateboards and cracks. For different experimental environments, the optimization algorithm proposed in this paper is used to detect pantographs in real time. The experimental results show that, compared with the traditional detection algorithm, the detection accuracy of sliding plate wear can reach 0.5 mm, and and that of sliding plate cracks can reach 0.4 mm. The crack recognition accuracy of skates is as high as 93 & x0025;.

关键词： Image edge detection Filtering algorithms Real-time systems detection algorithms Filtering Sensors Monitoring Adaptive canny edge monitoring dynamic calibration filtering pantograph failure detection second generation curve wave edge computing

来源：评论

学校读者我要写书评

暂无评论

A 2.92-Gb/s/W and 0.43-Gb/s/MG Flexible and Scalable CGRA-Based Baseband Processor for Massive MIMO detection

引用

IEEE JOURNAL OF SOLID-STATE CIRCUITS 2020年第2期55卷 505-519页

作者： Peng, Guiqiang Liu, Leibo Zhou, Sheng Yin, Shouyi Wei, Shaojun Tsinghua Univ Inst Microelect Beijing 100084 Peoples R China Tsinghua Univ Dept Elect Engn Beijing 100084 Peoples R China

Communication systems' development requires service customization in aspects, such as standards, multiple-input multiple-output (MIMO) scales, and algorithms. The existing hardware designs for massive MIMO detection have difficulty in achieving both high flexibility and scalability with high hardware efficiency. This article proposes a baseband processor based on a dynamic coarse-grained reconfigurable array (CGRA) for massive MIMO detection. To efficiently support various algorithm features and requirements, three optimization techniques are proposed to achieve high flexibility and scalability. First, an on-demand matrix-vector systolic array is proposed to enable flexible and scalable matrix and vector operations, reducing memory accesses by 82. Second, distributed multi-interaction data storage is designed for flexible data access and reusability. Finally, a continuable adaptive context information format is proposed to support different bit widths, operations, and extensions of MIMO systems, reducing context information by 67. These techniques achieve the improvements of 1.33 $\times $ , 1.34 $\times $ , and 1.29 $\times $ in energy efficiency and 1.21 $\times $ , 1.18 $\times $ , and 1.18 $\times $ in area efficiency, evaluated by removing one technique at a time from the proposed architecture. Fabricated in a 28-nm CMOS technology, the chip achieves high flexibility and scalability in supporting various detection algorithms;various MIMO scales, such as $4\,\,\times $ 4, 32 $\times $ 32, and 128 $\times $ 8;and baseband processing tasks, such as filtering and fast Fourier transformation. When benchmarked on various detection algorithms, the processor achieves 1.64-2.92-Gb/s/W energy efficiency and 0.25-0.43-Gb/s/MG area efficiency, which are 2.78-28.54 $\times $ and 2.05-14.43 $\times $ those of state-of-the-art programmable designs, respectively. To our knowledge, this is the first flexible and scalable CGRA-based baseband processor for massive MIMO detection.

关键词： Computer architecture Scalability detection algorithms Baseband Context Coarse-grained reconfigurable architecture (CGRA) energy and area efficiencies flexibility and scalability massive multiple-input multiple-output (MIMO) detection reconfigurable baseband processor

来源：评论

学校读者我要写书评

暂无评论

An Efficient ECG Classification System Using Resource-Saving Architecture and Random Forest

引用

IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS 2021年第6期25卷 1904-1914页

作者： Kung, Bo-Han Hu, Po-Yuan Huang, Chiu-Chang Lee, Cheng-Che Yao, Chia-Yu Kuan, Chieh-Hsiung Natl Taiwan Univ Grad Inst Biomed Elect & Bioinformat Taipei 10617 Taiwan Natl Taiwan Univ Grad Inst Elect Engn Taipei 10617 Taiwan Natl Taiwan Univ Sci & Technol Dept Elect Engn Taipei 10607 Taiwan

This paper presents a resource-saving system to extract a few important features of electrocardiogram (ECG) signals. In addition, real-time classifiers are proposed as well to classify different types of arrhythmias via these features. The proposed feature extraction system is based on two delta-sigma modulators adopting 250 Hz sampling rate and three wave detection algorithms to analyze outputs of the modulators. It extracts essential details of each heartbeat, and the details are encoded into 68 bits data that is only 1.48% of the other comparable methods. To evaluate our classification, we use a novel patient-specific training protocol in conjunction with the MIT-BIH database and the recommendation of the AAMI to train the classifiers. The classifiers are random forests that are designed to recognize two major types of arrhythmias. They are supraventricular ectopic beats (SVEB) and ventricular ectopic beats (VEB). The performance of the arrhythmia classification reaches to the F1 scores of 81.05% for SVEB and 97.07% for VEB, which are also comparable to the state-of-the-art methods. The method provides a reliable and accurate approach to analyze ECG signals. Additionally, it also possesses time-efficient, low-complexity, and low-memory-usage advantages. Benefiting from these advantages, the method can be applied to practical ECG applications, especially wearable healthcare devices and implanted medical devices, for wave detection and arrhythmia classification.

关键词： Electrocardiography Feature extraction detection algorithms Bioinformatics Heart Quantization (signal) Modulation Electrocardiogram (ECG) delta-sigma modulator random forest (RF) ECG classification

来源：评论

学校读者我要写书评

暂无评论

Vulnerability detection on Android Apps-Inspired by Case Study on Vulnerability Related With Web Functions

引用

IEEE ACCESS 2020年 8卷 106437-106451页

作者： Qin, Jiawei Zhang, Hua Guo, Jing Wang, Senmiao Wen, Qiaoyan Shi, Yijie Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China Coordinat Ctr China Natl Comp Network Emergency Response Tech Team Beijing 100029 Peoples R China

Nowadays, people's lifestyle is more and more dependent on mobile applications (Apps), such as shopping, financial management and surfing the internet. However, developers mainly focus on the implementation of Apps and the improvement of user experience while ignoring security issues. In this paper, we perform the comprehensive study on vulnerabilities caused by misuse of APIs and form a methodology for this type of vulnerability analysis. We investigate the security of three types of Android Apps including finance, shopping and browser which are closely related to human life. And we analyze four vulnerabilities including Improper certificate validation(CWE-295:ICV), WebView bypass certificate validation vulnerability(CVE-2014-5531:WBCVV), WebView remote code execution vulnerability(CVE-2014-1939:WRCEV) and Alibaba Cloud OSS credential disclosure vulnerability(CNVD-2017-09774:ACOCDV). In order to verify the effectiveness of our analysis method in large-scale Apps on the Internet, we propose a novel scalable tool - VulArcher, which is based on heuristic method and used to discover if the above vulnerabilities exist in Apps. We download a total of 6114 of the above three types of samples in App stores, and we use VulArcher to perform the above vulnerability detection for each App. We perform manual verification by randomly selecting 100 samples of each vulnerability. We find that the accuracy rate for ACOCDV can reach 100%, the accuracy rate for WBCVV can reach 95%, and the accuracy rate for the other two vulnerabilities can reach 87%. And one of vulnerabilities detected by VulArcher has been included in China National Vulnerability Database (CNVD) ID(CNVD-2017-23282). Experiments show that our tool is feasible and effective. For the convenience of researchers in related communities, We make our data and tool available at https://***/blog/2020/01/03/vularcher-site-launched.

关键词： Androids Humanoid robots Security Tools Servers Manuals Java Static analysis vulnerability mobile agents security application software detection algorithms

来源：评论

学校读者我要写书评

暂无评论

Focus First: Coarse-to-Fine Traffic Sign detection With Stepwise Learning

引用

IEEE ACCESS 2020年 8卷 171170-171183页

作者： Liu, Liman Wang, Yuntao Li, Kunqian Li, Jie South Cent Univ Nationalities Sch Biomed Engn Wuhan 430074 Peoples R China Ocean Univ China Coll Engn Qingdao 266100 Peoples R China Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan 430074 Peoples R China

Traffic sign detection is a very important part of intelligent assisted driving system. However, with the interference of various target sizes, geometric distortion, occlusion and motion blur, fast and accurate detection on large-size car camera image is extremely hard. To achieve both high efficient and accurate detection, we present a traffic sign detection method within a coarse-to-fine framework, which sequentially detects the targets in grid-level and image-level. We demonstrate that focusing first is a more effective detection strategy for small targets in wide detection space. We propose a target grid prediction network, which is a fully convolutional network for binary classification, to realize rapid coarse localization of the target and effectively guide the clipping and scaling of the target area. With the flexible potential target region extracting strategy, the detecting space can be significantly reduced. At the same time, the correctly extracted local areas for the targets can further facilitate the accurate detection of the subsequent traffic sign detector. In the experiments, our method achieves impressive performance in terms of both efficiency and accuracy. On the challenging Tsinghua-Tencent 100K (TT100K) dataset, our method achieves 20.9 FPS detection speed for 1600 x 1600 images and the F-1-score of the proposed method for all-scale targets is 91.55.

关键词： Object detection Task analysis Convolutional neural networks Feature extraction Detectors Roads detection algorithms Traffic sign detection Single Shot MultiBox~Detector convolutional neural network

来源：评论

学校读者我要写书评

暂无评论

Deep Learning-Aided Tabu Search detection for Large MIMO Systems

引用

IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2020年第6期19卷 4262-4275页

作者： Nguyen, Nhan Thanh Lee, Kyungchun Seoul Natl Univ Sci & Technol Dept Elect & Informat Engn Seoul 01811 South Korea Seoul Natl Univ Sci & Technol Res Ctr Elect & Informat Technol Seoul 01811 South Korea

In this study, we consider the application of deep learning (DL) to tabu search (TS) detection in large multiple-input multiple-output (MIMO) systems. First, we propose a deep neural network (DNN) architecture for symbol detection, termed the fast-convergence sparsely connected detection network (FS-Net), which is obtained by optimizing the prior detection networks called DetNet and ScNet. Then, we propose the DL-aided TS algorithm, in which the initial solution is approximated by the proposed FS-Net. Furthermore, in this algorithm, an adaptive early termination (ET) algorithm and a modified searching process are performed based on the predicted approximation error, which is determined from the FS-Net-based initial solution, so that the optimal solution can be reached earlier. The simulation results show that the proposed algorithm achieves approximately 90% complexity reduction for a 32 x 32 MIMO system with QPSK with respect to the existing TS algorithms, while maintaining almost the same performance.

关键词： Complexity theory MIMO communication Prediction algorithms Receiving antennas Approximation algorithms detection algorithms Wireless communication MIMO deep learning deep neural network tabu search

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：