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Design and implementation of a kind of EUPS for mobile service

Journal of information and Computational Science 2010年第11期7卷 2248-2257页

作者： Zhang, Xiaodan Zhang, Degan Qiao, Xiaodong Liang, Bing Peng, Hongtao Institute of Scientific and Technical Information of China Beijing 100038 China Tianjin Key Lab. of Intelligent Computing and Novel software Technology Tianjin University of Technology Tianjin 300191 China Key Laboratory of Computer Vision and System Ministry of Education Tianjin University of Technology Tianjin 300191 China Beijing Petroleum Managers Training Institute Beijing 100096 China

In order to support mobile service of long-distance monitoring and controlling UPS based on Web, a kind of design and implementation solution of embedded UPS (EUPS) system is brought forward in this paper. The design and implementation of system is based on ATmega161 and RTL8019AS with TCP/IP protocol suite for communication. In the EUPS system, an embedded file system is designed and implemented which can store the data and index information on a serial EEPROM chip in structured way and communicate with MCU through I2C bus. By embedding the file system into UPS system or other information appliances, users can browse and manipulate local data on the web client side. Based on our experimental tests, the performance of EUPS can meet the requirements of Web-based mobile services. © 2010 Binary information Press.

关键词： Websites

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SliceProp: A Slice-Wise Bidirectional Propagation Model for Interactive 3D Medical Image Segmentation 1

SliceProp: A Slice-Wise Bidirectional Propagation Model for ...

引用

1st IEEE International Conference on Medical Artificial Intelligence, MedAI 2023

作者： Xu, Xin Lu, Wenjing Lei, Jiahao Qiu, Peng Shen, Hong-Bin Yang, Yang Shanghai Jiao Tong University Key Lab. of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Department of Computer Science and Engineering Shanghai200240 China Shanghai Ninth People's Hospital Shanghai Jiao Tong University School of Medicine Department of Vascular Surgery China Shanghai Jiao Tong University Institute of Image Processing and Pattern Recognition Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China

ISBN: (纸本)9798350358780

Interactive medical image segmentation methods have become increasingly popular in recent years. These methods combine manual lab.ling and automatic segmentation, reducing the workload of annotation while maintaining high accuracy. However, most current interactive segmentation frameworks are limited to 2D image data, and are not suitable for 3D image data due to the large size and high complexity of 3D data, as well as the challenges posed by information asymmetry and sparse annotation. In this paper, we propose SliceProp, an interactive segmentation framework that implements slice-wise lab.l Bidirectional Propagation (LBP) for 3D medical image segmentation. SliceProp extends the interactive 2D image segmentation algorithm to 3D image segmentation, and can handle 3D data with large size and high complexity. Moreover, equipped with a Backtracking Feedback Check (BFC) module, SliceProp effectively addresses the issues of information asymmetry and spatial sparse annotation in 3D medical image segmentation. Additionally, we adopt an uncertainty-based criterion to pri-oritize the slices to be refined interactively, which enhances the efficiency of the interaction process by enabling the model to focus on the regions with the most unreliable predictions. SliceProp is evaluated on two datasets and achieves promising results compared to state-of-the-art methods. © 2023 IEEE.

关键词： Medical imaging

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Ultra-Compact Magnetoelectric Sensors for Femto-Tesla Vlf Signal Reception

SSRN

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SSRN 2024年

作者： Dong, Cunzheng Sun, Changxing Chen, Lei He, Yifan Liu, Yisi Luo, Bin Sun, Nian-Xiang Department of Electrical and Computer Engineering Northeastern University BostonMA02115 United States State Key Laboratory of Reliability and Intelligence of Electrical Equipment Hebei University of Technology Tianjin300130 China Key Lab of Computer Vision and Intelligent Information System Chongqing University of Arts and Sciences Chongqing402160 China

Very low-frequency (VLF) electromagnetic waves can penetrate dense conductive media, such as earth and saltwater, with minimal attenuation, allowing for long-distance signal transmission via ionospheric reflection. These characteristics make VLF waves ideal for applications in submarine navigation, subterranean mapping, underground communication, and ionospheric remote sensing. Conventional VLF signal reception has relied on magnetic loop antennas due to their low noise performance;however, their large size and reduced sensitivity due to low quality factors (Q) limit their use in portable and compact applications, particularly in underwater and underground environments. To address these challenges, we propose an ultra-compact room-temperature extremely sensitive femto-tesla magnetic sensor based on a strain-mediated high-Q Metglas/Quartz magnetoelectric (ME) resonator operating at its electromechanical resonance (EMR) at 24.55 kHz for VLF signal reception. The Metglas/Quartz ME sensor demonstrates a sensitivity and magnetic noise performance enhancement by an order of magnitude compared to conventional Metglas/PZT ME sensors, achieving an ultra-low equivalent magnetic noise level of 5 fT/Hz1/2, owing to high magnetic permeability and magnetostriction of Metglas and the high-quality factor of Quartz at EMR. Moreover, the Metglas/Quartz ME VLF receiver exhibits overwhelming near-field and far-field VLF signal reception capability, realizing a successful reception of VLF signal 400 km away from the NAA VLF Transmitter Cutler. The demonstrated ultra-compact high-Q Metglas/Quartz ME sensor capable of femto-tesla VLF signal reception shows significant improvements in magnetic sensing capability, size, power consumption, and cost compared to traditional magnetic loop antennas, making it a promising solution for portable VLF signal reception in challenging environments. © 2024, The Authors. All rights reserved.

关键词： Loop antennas

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MapDistill: Boosting Efficient Camera-based HD Map Construction via Camera-LiDAR Fusion Model Distillation

arXiv

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arXiv 2024年

作者： Hao, Xiaoshuai Li, Ruikai Zhang, Hui Li, Dingzhe Yin, Rong Jung, Sangil Park, Seung-In Yoo, ByungIn Zhao, Haimei Zhang, Jing Samsung R&D Institute China Beijing China State Key Lab of Intelligent Transportation System Beihang University China Institute of Information Engineering Chinese Academy of Sciences China Computer Vision TU SAIT SEC Korea Republic of The University of Sydney Australia

Online high-definition (HD) map construction is an important and challenging task in autonomous driving. Recently, there has been a growing interest in cost-effective multi-view camera-based methods without relying on other sensors like LiDAR. However, these methods suffer from a lack of explicit depth information, necessitating the use of large models to achieve satisfactory performance. To address this, we employ the Knowledge Distillation (KD) idea for efficient HD map construction for the first time and introduce a novel KD-based approach called MapDistill to transfer knowledge from a high-performance camera-LiDAR fusion model to a lightweight camera-only model. Specifically, we adopt the teacher-student architecture, i.e., a camera-LiDAR fusion model as the teacher and a lightweight camera model as the student, and devise a dual BEV transform module to facilitate cross-modal knowledge distillation while maintaining cost-effective camera-only deployment. Additionally, we present a comprehensive distillation scheme encompassing cross-modal relation distillation, dual-level feature distillation, and map head distillation. This approach alleviates knowledge transfer challenges between modalities, enabling the student model to learn improved feature representations for HD map construction. Experimental results on the challenging nuScenes dataset demonstrate the effectiveness of MapDistill, surpassing existing competitors by over 7.7 mAP or 4.5× speedup. Copyright © 2024, The Authors. All rights reserved.

关键词： Cost effectiveness

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Robust Multi-Exposure Image Fusion: A Structural Patch Decomposition Approach

Robust Multi-Exposure Image Fusion: A Structural Patch Decom...

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作者： Ma, Kede Li, Hui Yong, Hongwei Wang, Zhou Meng, Deyu Zhang, Lei Department of Electrical and Computer Engineering University of Waterloo WaterlooONN2L 3G1 Canada Department of Computing Hong Kong Polytechnic University Hong Kong Hong Kong Department of Computing. Hong Kong Polytechnic University Hong Kong Hong Kong Institute for Information and System Sciences and Ministry of Education Key Laboratory of Intelligent Networks and Network Security Xi'an Jiaotong University Xi'an710049 China Inst. for Info. and Syst. Sci. and Min. of Educ. Key Lab. of Intelligent Networks and Netwk. Secty. Xi'an Jiaotong University Xi'an710049 China

We propose a simple yet effective structural patch decomposition approach for multi-exposure image fusion (MEF) that is robust to ghosting effect. We decompose an image patch into three conceptually independent components: signal strength, signal structure, and mean intensity. Upon fusing these three components separately, we reconstruct a desired patch and place it back into the fused image. This novel patch decomposition approach benefits MEF in many aspects. First, as opposed to most pixel-wise MEF methods, the proposed algorithm does not require post-processing steps to improve visual quality or to reduce spatial artifacts. Second, it handles RGB color channels jointly, and thus produces fused images with more vivid color appearance. Third and most importantly, the direction of the signal structure component in the patch vector space provides ideal information for ghost removal. It allows us to reliably and efficiently reject inconsistent object motions with respect to a chosen reference image without performing computationally expensive motion estimation. We compare the proposed algorithm with 12 MEF methods on 21 static scenes and 12 deghosting schemes on 19 dynamic scenes (with camera and object motion). Extensive experimental results demonstrate that the proposed algorithm not only outperforms previous MEF algorithms on static scenes but also consistently produces high quality fused images with little ghosting artifacts for dynamic scenes. Moreover, it maintains a lower computational cost compared with the state-of-The-Art deghosting schemes.11The MATlab.code of the proposed algorithm will be made availab.e online. Preliminary results of Section III-A [1] were presented at the IEEE International Conference on Image Processing, Canada, 2015. © 1992-2012 IEEE.

关键词： Image fusion

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A Review of Generalized Zero-Shot Learning Methods

arXiv

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arXiv 2020年

作者： Pourpanah, Farhad Abdar, Moloud Luo, Yuxuan Zhou, Xinlei Wang, Ran Lim, Chee Peng Wang, Xi-Zhao Jonathan Wu, Q.M. The Centre for Computer Vision and Deep Learning Department of Electrical and Computer Engineering University of Windsor WindsorONN9B 3P4 Canada Deakin University Australia The Department of Computer Science City University of Hong Kong Hong Kong The College of Mathematics and Statistics Shenzhen Key Lab. of Advanced Machine Learning and Applications Shenzhen University Shenzhen518060 China The College of Computer Science and Software Engineering Guangdong Key Lab. of Intelligent Information Processing Shenzhen University Shenzhen518060 China

Generalized zero-shot learning (GZSL) aims to train a model for classifying data samples under the condition that some output classes are unknown during supervised learning. To address this challenging task, GZSL leverages semantic information of the seen (source) and unseen (target) classes to bridge the gap between both seen and unseen classes. Since its introduction, many GZSL models have been formulated. In this review paper, we present a comprehensive review on GZSL. Firstly, we provide an overview of GZSL including the problems and challenges. Then, we introduce a hierarchical categorization for the GZSL methods and discuss the representative methods in each category. In addition, we discuss the availab.e benchmark data sets and applications of GZSL, along with a discussion on the research gaps and directions for future investigations. Copyright © 2020, The Authors. All rights reserved.

关键词： Zero-shot learning

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WISERNet: Wider Separate-then-reunion Network for Steganalysis of Color Images

arXiv

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arXiv 2018年

作者： Zeng, Jishen Tan, Shunquan Liu, Guangqing Li, Bin Huang, Jiwu Guangdong Key Laboratory of Intelligent Information Processing National Engineering Laboratory for Big Data System Computing Technology Shenzhen University Shenzhen518060 China College of Computer Science and Software Engineering Shenzhen University Guangdong Key Lab. of Intelligent Info. Processing and Shenzhen Key Laboratory of Media Security Shenzhen University Shenzhen518060 China Peng Cheng Laboratory Shenzhen518052 China

Until recently, deep steganalyzers in spatial domain have been all designed for gray-scale images. In this paper, we propose WISERNet (the wider separate-then-reunion network) for steganalysis of color images. We provide theoretical rationale to claim that the summation in normal convolution is one sort of "linear collusion attack" which reserves strong correlated patterns while impairs uncorrelated noises. Therefore in the bottom convolutional layer which aims at suppressing correlated image contents, we adopt separate channel-wise convolution without summation instead. Conversely, in the upper convolutional layers we believe that the summation in normal convolution is beneficial. Therefore we adopt united normal convolution in those layers and make them remarkably wider to reinforce the effect of "linear collusion attack". As a result, our proposed wide-and-shallow, separate-then-reunion network structure is specifically suitable for color image steganalysis. We have conducted extensive experiments on color image datasets generated from BOSSBase raw images and another large-scale dataset which contains 100,000 raw images, with di_erent demosaicking algorithms and downsampling algorithms. The experimental results show that our proposed network outperforms other state-of-the-art color image steganalytic models either hand-crafted or learned using deep networks in the literature by a clear margin. Specifically, it is noted that the detection performance gain is achieved with less than half the complexity compared to the most advanced deeplearning steganalyzer as far as we know, which is scarce in the literature. Copyright © 2018, The Authors. All rights reserved.

关键词： Steganography

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Research of deep packet inspection system based on the MapReduce

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Journal of Computational information systems 2013年第7期9卷 2587-2594页

作者： Wang, Jinsong Wei, Jun Lin, Sheng Huang, Wei Tianjin Key Lab. of Intelligent Computing and Novel Software Technology Tianjin University of Technology Tianjin 300384 China Key Laboratory of Computer Vision and System Ministry of Education Tianjin University of Technology Tianjin 300384 China

In this paper, we propose a deep packet inspection system based on the MapReduce. The MapReduce which is a parallel distributed programming model developed by Google applies the technology of deep packet inspection. Network protocol analysis technique is invoked to realize detect, effectively reducing the packet number to be matched. Furthermore, cache technology is adopted to store attack signature from database in order to reduce the frequency of reading the rules from library file which improved the detection efficiency. Experimental results show that effectiveness of the proposed system with the high-speed network traffic. Copyright © 2013 Binary information Press.

关键词： MapReduce

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Abnormal network traffic detection approach based on alive entropy

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Tongxin Xuebao/Journal on Communications 2013年第SUPPL.2期34卷 51-57页

作者： Mu, Xiang-Kun Wang, Jin-Song Xue, Yu-Feng Huang, Wei Tianjin Key Lab. of Intelligent Computing and Novel Software Technology Tianjin University of Technology Tianjin 300384 China Key Laboratory of Computer Vision and System Ministry of Education Tianjin University of Technology Tianjin 300384 China

A novel alive entropy-based detection approach was proposed, which detects the abnormal network traffic based on the values of alive entropies. The alive entropies calculated based on the NetFlow data coming from the network traffic of input and output of a whole system, which is essentially a monitored network. In order to decrease false positive rate of abnormal network traffic, different scales are selected to compute the values of alive entropies in different sizes of network traffic. With the low false positive rate of abnormal network traffic, the abnormal network traffic can be effectively detected. Experiments carried out on a real campus network were used to evaluate the effectiveness of the proposed approach. A comparative study illustrates that the proposed approach may easily detect the abnormal network traffic with random characteristics in comparison with some "conventional" approaches reported in the literatures.

关键词： Entropy

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A Many-Objective Evolutionary Algorithm Assisted by Ideal Hyperplane

SSRN

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SSRN 2022年

作者： Zhang, Zhixia Wen, Jie Wang, Hui Cai, Xingjuan Cui, Zhihua Zhang, Wensheng School of Computer Science and Technology Taiyuan University of Science and Technology China School of Information Engineering Nanchang Institute of Technology Nanchang330099 China State Key Laboratory of Intelligent Control and Management of Complex System Institute of Automation Chinese Academy of Sciences China State Key Lab. for Novel Software Technology Nanjing University China

In many-objective optimization problems (MaOPs), it is a difficult task for evolutionary algorithms to balance convergence and diversity while rapidly converging to the Pareto front. As the number of objectives increases, the difficulty of evolutionary algorithms increases with individual selection pressure. To address above problems, we propose a many-objective evolution algorithm assisted by an ideal hyperplane (MaOEA-IH). Firstly, the ideal hyperplane as a reference surface to guide the individual to search the Pareto front, which is established from the extremum of each dimension of the objective space. Secondly, a parallel p -norm mating selection strategy is proposed to improve convergence. In addition, two factors are considered in this strategy: 1) different p -norm are used to measure different spatial scales;2) individual selection uncertainty is defined by incorporating a probabilistic perturbation mechanism. Thirdly, the improved shift-based density estimation strategy is used as the evaluation criterion for environmental selection to improve the convergence and diversity of solution sets and enhance selection pressure. To verify the effectiveness of the proposed algorithm, MAOEA-IH is compared with seven excellent algorithms in three benchmark sets (DTLZ, WFG and MaF). The results show that the proposed MAOEA-IH is highly competitive in solving MaOPs. © 2022, The Authors. All rights reserved.

关键词： Geometry

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