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IEEE International Symposium on Defect and Fault Tolerance in VLSI Systems

作者： Yu Xie Chen Yang Chuang-An Mao He Chen Yi-Zhuang Xie Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology Beijing China

As soft errors become a significant threat to modern electronic systems, the first priority of protection against soft errors should be decreasing resource consumption. This brief proposes a novel low-overhead fault tolerant FFT design, combining modified reduced precision redundancy (RPR) method and error correction codes (ECCs). RPR can lower the hardware overhead when compared with traditional full-precision redundancy techniques, especially when resource of the original design is huge. ECCs are cost-efficient for achieving fault tolerance on our parallel-pipelined FFT. As an example, an FPGA implementation of a four-channel 16K-point FFT is presented, which demonstrates that the proposed scheme can further reduce the overhead of fault tolerance designs.

关键词： Redundancy Fault tolerant systems Program processors Field programmable gate arrays Error correction codes Tunneling magnetoresistance

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Optimization and Verification of OpenV PX-Based 10Gbps Interconnection

Optimization and Verification of OpenV PX-Based 10Gbps Inter...

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2017 17th IEEE International Conference on Communication technology (ICCT 2017)

作者： Rongrong Ben Xingming Li Shanqing Hu Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology Tsinghua University

As serial date rates migrate to 10Gbps and beyond, the list of signal integrity(SI) concerns and pitfalls grows. This paper focuses the design of SI of 10G serial link on OpenVPX system, and the research of the corresponding design and optimization methods based on passive design of 10Gbps high speed serial link. Combined pre-emphasis and equalization, the design enhances the quality of full link, reduces the bit error rate, and ensures accurate transmission of 10Gbps serial signal, with margin left for system operation. With simulation and testing, the methods are verified to be accurate and feasible in this paper.

关键词： OpenVPX 10Gbps signal integrity simulation

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An optimal density peak algorithm based on data field and information entropy 17

An optimal density peak algorithm based on data field and in...

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2017 International Conference on Data Mining, Communications and information technology, DMCIT 2017

作者： Tao, Ling Li, Wenjie Jin, Yu College of Computer Science and Technology Wuhan University of Science and Technology Wuhan China Hubei Province Key Laboratory of Intelligent Information Processing Real-time Industrial System Wuhan China

ISBN: (纸本)9781450352185

The manual selection of threshold dc and cluster centers are the big limitations of the clustering by fast search and find of density peaks algorithm (DPC). In this paper, the data field theory was introduced to adaptively select the threshold dc. The selection of cluster centers was regarded as the segmentation of the dataset that contains positive and negative samples. The information entropy was calculated to measure the purity of the dataset after each segmentation. Segmentation with the maximum entropy reduction divided all the cluster centers into the positive sample set, thus avoiding the errors cause by operating the Decision Graph manually. Comparison of clustering results on the artificial datasets shows that the proposed method (F-DPC) can choose the threshold dc reasonably according to the distribution of datasets and is robust to noise. Evaluating indicators in the real-life experiments exhibit that the proposed method can accurately determine the number of clusters and gain higher clustering accuracy. © 2017 Association for Computing Machinery.

关键词： Clustering algorithms

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Research on Multi-Model of Computer Organization for System Capability

Research on Multi-Model of Computer Organization for System ...

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2018 3rd International Conference on Education,Sports,Arts and Management Engineering(ICESAME 2018)

作者： Li HUANG Wei HU Kai ZHANG Jianhua LU College of Computer Science and Technology Wuhan University of Science and Technology Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan University of Science and Technology National Computer Experimental Teaching Demonstration Center (Wuhan University of Science and Technology)

This paper studies the lack of systematic, teaching content and the obsolete teaching mode of the principle of computer composition in most colleges and universities in China. Proposed system-oriented teaching methods and modes. This paper expounds the teaching goal of cultivating system competence based on classroom teaching system, supported by gradient experiment teaching, combining MOOC platform and SPOC teaching mode, and taking the second class as the teaching implementation system expanded.

关键词： system capability multiple teaching mode computer organization

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Dense dilated network with probability regularized walk for vessel detection

arXiv

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arXiv 2019年

作者： Mou, Lei Chen, Li Cheng, Jun Gu, Zaiwang Zhao, Yitian Liu, Jiang School of Computer Science and Technology Wuhan University of Science and Technology Wuhan430081 China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan University of Science and Technology Wuhan430081 China Cixi Institute of Biomedical Engineering Chinese Academy of Sciences Zhejiang315201 China UBTech Research UBTech Robotics Corp Ltd Guangdong518055 China Department of Computer Science and Engineering Southern University of Science and Technology Guangdong518055 China Cixi Institute of Biomedical Engineering Ningbo Institute of Industrial Technology Chinese Academy of Sciences Zhejiang315201 China

The detection of retinal vessel is of great importance in the diagnosis and treatment of many ocular diseases. Many methods have been proposed for vessel detection. However, most of the algorithms neglect the connectivity of the vessels, which plays an important role in the diagnosis. In this paper, we propose a novel method for retinal vessel detection. The proposed method includes a dense dilated network to get an initial detection of the vessels and a probability regularized walk algorithm to address the fracture issue in the initial detection. The dense dilated network integrates newly proposed dense dilated feature extraction blocks into an encoder-decoder structure to extract and accumulate features at different scales. A multi-scale Dice loss function is adopted to train the network. To improve the connectivity of the segmented vessels, we also introduce a probability regularized walk algorithm to connect the broken vessels. The proposed method has been applied on three public data sets: DRIVE, STARE and CHASE_DB1. The results show that the proposed method outperforms the state-of-the-art methods in accuracy, sensitivity, specificity and also area under receiver operating characteristic curve. Copyright © 2019, The Authors. All rights reserved.

关键词： Diagnosis

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Duplicate checking Strategies for Selecting Topics for Graduation Thesis Based on Maximum Public Sequence

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IOP Conference Series: Earth and Environmental Science 2019年第3期267卷

作者： Guorui Yu Li Huang Jiewen Sun Shangchun Liao School of Computer Science and Technology Wuhan University of Science and Technology phone:*** Intelligent Information Processing and Hubei Real-time Industrial Systems Laboratory. Key Laboratory of Metallurgical Equipment and Control Technology Wuhan University of Science and Technology Ministry of Education.

The system is based on the undergraduate thesis management system as the practice platform, focusing on the realization of the thesis topic check function. The current check-up detection system is based on the entire contents of the query, and does not meet the requirements for an undergraduate thesis query. According to the characteristics of the thesis, the system first divides the keywords into the topic, selects the irrelevant parts, then removes the irrelevant words, and finally checks the keywords in the topic, and realizes the efficient and accurate check for inspection.

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Adaptive feature representation for visual tracking

arXiv

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arXiv 2017年

作者： Han, Yuqi Deng, Chenwei Zhang, Zengshuo Li, Jiatong Zhao, Baojun Beijing Key Laboratory of Embedded Real-time Information Processing Technique Beijing Institute of Technology Beijing100081 China

Robust feature representation plays significant role in visual tracking. However, it remains a challenging issue, since many factors may affect the experimental performance. The existing method which combine different features by setting them equally with the fixed weight could hardly solve the issues, due to the different statistical properties of different features across various of scenarios and attributes. In this paper, by exploiting the internal relationship among these features, we develop a robust method to construct a more stable feature representation. More specifically, we utilize a co-training paradigm to formulate the intrinsic complementary information of multi-feature template into the efficient correlation filter framework. We test our approach on challenging sequences with illumination variation, scale variation, deformation etc. Experimental results demonstrate that the proposed method outperforms state-of-the-art methods favorably. Copyright © 2017, The Authors. All rights reserved.

关键词： Machine learning

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Image classification algorithm based on LTS-HD multi instance multi label RBF 12

Image classification algorithm based on LTS-HD multi instanc...

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12th IEEE Conference on Industrial Electronics and Applications, ICIEA 2017

作者： Min, Jie Zhang, Hong Wuhan University of Science and Technology Institute of Computer Science and Technology Wuhan China Wuhan University of Science and Technology Hubei Prov. Key Laboratory of Intelligent Information Processing and Real Time Industrial System Wuhan China

ISBN: (纸本)9781538621035

In order to improve the accuracy of image classification and the robustness of the algorithm, this paper proposes a Image classification algorithm based on LTS-HD(Least Trimmed Square Hausdorff) multi instance multi label RBF. The image classification algorithm based on the traditional Hausdorff distance has poor stability, and the classification results are quite different. Therefore, the image classification algorithm based on the LTS Hausdorff overcomes the problems existing in the traditional algorithm. In this paper, an improved K-Means clustering algorithm which combines Canopy algorithm and K-Means algorithm not only optimizes the initial clustering center of K-Means algorithm, but also reduces the time complexity of traditional K-Means algorithm. The experimental results show that the proposed algorithm can effectively resist the influence of noise and improve the accuracy of classification. © 2017 IEEE.

关键词： Image classification

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Design and optimization of a divider in pipelined processors based on quotient-Try 12

Design and optimization of a divider in pipelined processors...

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12th IEEE Conference on Industrial Electronics and Applications, ICIEA 2017

作者： Yu, Zhang Chunqiang, Li Wei, Hu Huan, Shen Jing, Liu College of Computer Science and Technology Wuhan University of Science and Technology Wuhan Hubei430065 China Hubei Province Key Laboratory of Intelligent Information Processing and Real-Time Industrial System Wuhan Hubei430065 China

ISBN: (纸本)9781538621035

Pipeline is an effective approach to improve the performance of the processors, and the bottleneck of the pipelined devices is its longest execution path. In classical five-stage pipeline, division instruction takes up more clock cycles than the other general instructions because of its complex operations. In this paper, we proposed a design of optimized divider based on quotient-Try. When DIV instruction is being executed, divisor and dividend are transmitted to the divider, while quotient and remainder are determined by using the highest bit of dividend minus divisor. This divider has been tested on simulation environment. The experiment results showed that this divider could reduce the complexity of circuit design and accelerate the speed of operating compared with the divider which was based on reciprocal-multiply. © 2017 IEEE.

关键词： Field programmable gate arrays (FPGA)

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Adaptive Clustering SOFC Image Segmentation Based on Particle Swarm Optimization

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Journal of Physics: Conference Series 2019年第1期1229卷

作者： Xuefei Yang Xiaowei Fu Xi Li College of Computer Science and Technology Wuhan University of Science and Technology Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan China 430065 State Key Laboratory of Materials Processing and Die & Mould Technology Huazhong University of Science and Technology Wuhan China 430074 College of Automation Huazhong University of Science and Technology Wuhan China 430074

Microstructural parameters are important for analyzing the chemistry and performance of solid oxide fuel cells (SOFCs). Aiming at the YSZ / Ni anode optical microscopy (OM) image of SOFC, in this paper, particle swarm intelligent optimization algorithm is used to improve the fuzzy C-means clustering algorithm for image segmentation. Particle swarm optimization is used to adaptively search the initial clustering center, helping to avoid local optimization and preserve more image detail. The experimental results show that the proposed method can improve the segmentation accuracy of images. At the same time, it can accurately segment the SOFC three-phase and provide effective image segmentation results for the microstructure parameters.

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