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IEEE International Conference on Systems, Man and Cybernetics

作者： Jia Chen Xin Luo MengChu Zhou School of Cyber Science and Technology Beihang University Beijing China Chongqing Key Lab. of Big Data and Intelligent Computing and the Chongqing Engineering Research Center of Big Data Application for Smart Cities Chongqing Institute of Green and Intelligent Technology Chongqing School University of Chinese Academy of Sciences Chongqing China New Jersey Institute of Technology Newark NJ USA

ISBN: (纸本)9781665442084

A stochastic-gradient-descent-based Latent Factor Analysis (LFA) model is highly efficient in representative learning of a High-Dimensional and Sparse (HiDS) matrix. Its learning rate adaptation is vital in ensuring its efficiency. Such adaptation can be realized with an evolutionary computing algorithm. However, a resultant model tends to suffer from two issues: a) the pre-mature convergence of the swarm of learning rates as caused by an adopted evolution algorithm, and b) the pre-mature convergence of the LFA model as caused jointly by evolution-based learning rate adaptation and an optimization algorithm. This paper focuses on the methods to address such issues. A Hierarchical Particle-swarm-optimization-incorporated Latent factor analysis (HPL) model with a two-layered structure is proposed, where the first layer pre-trains desired latent factors with a position-transitional particle-swarm-optimization-based LFA model, and the second layer performs latent factor refining with a newly-proposed mini-batch particle swarm optimizer. With such design, an HPL model can well handle the pre-mature convergence, which is supported by the positive experimental results achieved on HiDS matrices from industrial applications.

关键词： Adaptation models Analytical models Computational modeling Refining Predictive models Sparse matrices Particle swarm optimization

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Improving Chinese Storing Text Retrieval Systems' Security via a Novel Maximal Prefix Coding

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International Journal of Computer Processing of Languages 2002年第4期15卷 379-393页

作者： D. Y. LONG W. J. JIA P. O. AU M. LI Department of Computer Science Zhongshan University Guangzhou 510275 PRC State Key Lab. of Information Security Chinese Academy of Science Beijing 100080 PRC Department of Computer Engineering and Information Technology City University of Hong Kong 83 Tat Chee Avenue Kowloon Hong Kong SAR PRC School of Computing National University of Singapore Singapore

We have seen that Huffman coding has been widely used in data, image, and video compression. In this paper novel maximal prefix coding is introduced. Relationship between the Huffman coding and the optimal maximal prefix coding are discussed. We show that all Huffman coding schemes are optimal maximal prefix coding schemes and that conversely the optimal maximal prefix coding schemes need not be the Huffman coding schemes. Moreover, it is proven that, for any maximal prefix code C, there exists an information source I = (∑ P) such that C is exactly a Huffman code for I. Therefore, it is essential to show that the class of Huffman codes is coincident with one of the maximal prefix codes. A case study of data compression is also given. Comparing the Huffman coding, the maximal prefix coding is used not only for statistical modeling but also for dictionary methods. It is also good at applying to a large information retrieval system and improving its security.

关键词： Coding Data Compression Huffman Coding Maximal Prefix Coding

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Grip force prediction based on changes in Brachioradialis Muscle Impedance

Grip force prediction based on changes in Brachioradialis Mu...

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IEEE MTT-S International Microwave Bio Conference ((IMBIOC)

作者： Pan Xu Xudong Yang Hongli Yan Ž eljka Luč ev Vasić Mario Cifrek Yueming Gao College of Physics and Information Engineering Fuzhou University Fuzhou China Fujian Province Key Lab. of Medical Instrumentation and Pharmaceutical Technology Fuzhou University Fuzhou China School of Advanced Manufacturing Fuzhou University Fuzhou China Faculty of Electrical Engineering and Computing University of Zagreb Zagreb Croatia

ISBN: (数字)9781665423403

ISBN: (纸本)9781665423410

Grip force prediction plays an important role in biomechanical research, sports medicine, and clinical rehabilitation. Most of the current studies in this area only focuses on the characteristic input of surface Electromyography (sEMG) signals, but the acquisition and processing of sEMG are complicated and vulnerable to electromagnetic interference. The impedance signal has the advantages of easy acquisition and processing, strong anti-interference, non-invasive detection, and are widely used in the treatment of neuromuscular diseases. In this paper, impedance technique is introduced into grip force prediction. A single-frequency, low-intensity alternating current (AC) signal is injected into the brachioradialis muscle, and the change in muscle impedance is detected through the electrical effect of the electromagnetic field on biological tissue. Then, the correlation between impedance parameters and grip force changes is discussed, and the Long Short-Term Memory (LSTM) grip force prediction model is established with resistance (R) and phase (P) as feature inputs. The results show that the $r^{2}\_score$ of the grip force prediction model is greater than 0.94 and the mean square error (MSE) is lower than 0.7. This paper restores the actual grip force based on the LSTM prediction model and provides a new implementation idea for grip force prediction.

关键词： Training Analytical models Surface impedance Correlation Biological system modeling Force Muscles

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Secrecy Analysis of UAV Control Information Transmission via NOMA

Secrecy Analysis of UAV Control Information Transmission via...

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IEEE Conference on Wireless Communications and Networking

作者： Zhaoxin Feng Huabing Lu Nan Zhao Zhaoyuan Shi Yunfei Chen Xianbin Wang School of Information and Communication Engineering Dalian University of Technology Dalian China Key Lab. of Intelligent Perception and Computing of Anhui Province Anqing Normal University Anqing China Department of Engineering University of Durham Durham UK Department of Electrical and Computer Engineering Western University London ON Canada

ISBN: (数字)9798350303582

ISBN: (纸本)9798350303599

Unmanned aerial vehicle (UAV) assisted wireless communication is essential for the next-generation mobile networks. In coping with the increased dynamics in UAV networks, the design of control information transmission is essential, requiring ultra reliability, low latency, and high security. In this paper, considering both the large-scale path loss and the Nakagami-m small-scale fading, we investigate the secrecy performance of UAV control information transmission in a NOMA ground-air network with an external flying eavesdropper. A spherical secrecy protection zone is set, and the closed-form expressions for average secure BLER and average achievable secrecy throughput are derived. After that, the asymptotic performance in the high SNR regime is analyzed to get more insights. Ultimately, simulation results verify the accuracy of analysis.

关键词： Wireless communication NOMA Accuracy Simulation Information processing Autonomous aerial vehicles Throughput

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Finite element modeling and experimental analysis of bladder volume body surface monitoring method

Finite element modeling and experimental analysis of bladder...

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IEEE MTT-S International Microwave Bio Conference ((IMBIOC)

作者： Hongli Yan Xudong Yang Xu Li Yueming Gao Ž eljka Luč ev Vasić Mario Cifrek College of Physics and Information Engineering Fuzhou University Fuzhou China Fujian Provincial Key Lab. of Medical Instrument and Pharmaceutical Technology Fuzhou University Fuzhou China School of Advanced Manufacturing Fuzhou University Fuzhou China Faculty of Electrical Engineering and Computing University of Zagreb Zagreb Croatia

ISBN: (数字)9781665423403

ISBN: (纸本)9781665423410

Bladder dysfunction seriously affects people's quality of life. The accumulation of urine volume in the bladder changes the bladder volume, which changes the impedance of the hypogastrium. This paper constructs a finite element model of the hypogastrium and bladder, and the impedance of the hypogastrium at different volumes of the bladder is obtained by simulation. It also explains the causes of bladder impedance changes based on the current density distribution and designs the impedance acquisition circuit to carry out experimental data measurements on the subjects. The results show that changes in bladder volume affect the amplitude and phase of impedance in the hypogastrium. The model proposed in this paper can provide a theoretical basis for bladder urine volume body surface monitoring.

关键词： Surface impedance Solid modeling Impedance measurement Wearable computers Bladder Finite element analysis Impedance

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Detection of low back muscle state based on electrical impedance myography

Detection of low back muscle state based on electrical imped...

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IEEE MTT-S International Microwave Bio Conference ((IMBIOC)

作者： Jingting Shi Yanyan Liu Hongli Yan Yueming Gao Ž eljka Luč ev Vasić Mario Cifrek The College of Physics and Information Engineering Fuzhou University Fuzhou China Fujian province Key Lab. of medical Instrument and Pharmaceutical technology Fuzhou University Fuzhou China School of Advanced Manufacturing Fuzhou University Fuzhou China The Faculty of Electrical Engineering and Computing University of Zagreb Zagreb Croatia

ISBN: (数字)9781665423403

ISBN: (纸本)9781665423410

In the prevention and rehabilitation stage of low back diseases, it is necessary to detect the state of muscles to avoid excessive fatigue and injury caused by continuous exertion of lumbar muscles. In this paper, an in vivo experimental platform for measuring low back muscle impedance was established in order to detect the different force states of muscle and study the corresponding relationship between muscle force state and muscle impedance. In the experiment, Biering-Sorensen (BS) test was used to make the low back muscle contract continuously, and different weights (5 kg, 2.5 kg, 0 kg) were used to distinguish the force state of muscle. The impedance analyzer was used to measure the muscle impedance parameters under different load in the subject's low back muscle for studying the electrical impedance characteristics of different low back muscle states. The results showed that the relative resistance $R^{\prime}$ of EIM was a downward trend with time and the 5 kg load had the fastest decline; The relative reactance $X_{c}^{\prime}$ of EIM was an upward trend with time, the 5 kg load also had the fastest rise. The slope $k$ of the fitting curve of $R^{\prime}$ and $X_{c}^{\prime}\text{were}-5.8\times 10^{-4}$ and $8.76 \times 10^{-4}$ respectively. Therefore, EIM can effectively detect the state of low back muscles.

关键词： In vivo Impedance measurement Force Fitting Muscles Back Market research

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The Characterization of Multi-source Multicast with Network Coding

The Characterization of Multi-source Multicast with Network ...

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2012 IEEE 14th International Conference on Communication technology

作者： Hanxu Hou Hui Li Shenzhen Key Lab of Cloud Computing Technology & Application Shenzhen Graduate SchoolPeking University Shenzhen Eng.Lab of Converged Network Tech.Shenzhen Graduate SchoolPeking University

ISBN: (纸本)9781467321006

The capacity region of the single-source multicast network coding has an explicit Max-flow Min-cut *** for multi-source multicast networks the problem is still *** this paper,we mainly discuss the case of independent encoding multi-source multicast network using inter-session network *** propose a multi-source independent encoding theorem for this problem which characterizes the admissible coding rate region of independent encoding for relevant multiple *** theorem is proposed by the paper according to the strongly typical sequences and random *** also point out the connections between our theorem and the general multi- source network coding problem,of which the results are computable and can be used to design the multi-source network coding algorithm.

关键词： network coding multi-source multicast correlated data computable

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Privacy-Aware UAV Flights through Self-Configuring Motion Planning

Privacy-Aware UAV Flights through Self-Configuring Motion Pl...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Yixing Luo Yijun Yu Zhi Jin Yao Li Zuohua Ding Yuan Zhou Yang Liu Key Lab. of High Confidence of Software Technologies(MoE) Peking University Beijing China School of Computing and Communications The Open University Milton Keynes UK School of Information Science and Technology Zhejiang Sci-Tech University Hangzhou China School of Computer Science and Engineering Nanyang Technological University Singapore

ISBN: (数字)9781728173955

ISBN: (纸本)9781728173962

During flights, an unmanned aerial vehicle (UAV) may not be allowed to move across certain areas due to soft constraints such as privacy restrictions. Current methods on self-adaption focus mostly on motion planning such that the trajectory does not trespass predetermined restricted areas. When the environment is cluttered with uncertain obstacles, however, these motion planning algorithms are not flexible enough to find a trajectory that satisfies additional privacy-preserving requirements within a tight time budget during the flights. In this paper, we propose a privacy risk aware motion planning method through the reconfiguration of privacy-sensitive sensors. It minimises environmental impact by re-configuring the sensor during flight, while still guaranteeing the safety and energy hard constraints such as collision avoidance and timeliness. First, we formulate a model for assessing privacy risks of dynamically detected restricted areas. In case the UAV cannot find a feasible solution to satisfy both hard and soft constraints from the current configuration, our decision making method can then produce an optimal reconfiguration of the privacy-sensitive sensor with a more efficient trajectory. We evaluate the proposal through various simulations with different settings in a virtual environment and also validate the approach through real test flights on DJI Matrice 100 UAV.

关键词： Privacy Planning Cameras Sensors Trajectory Safety Unmanned aerial vehicles

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iSplit LBI: Individualized partial ranking with ties via split LBI

arXiv

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arXiv 2019年

作者： Xu, Qianqian Sun, Xinwei Yang, Zhiyong Cao, Xiaochun Huang, Qingming Yao, Yuan Key Lab. of Intelligent Information Processing Institute of Computing Technology CAS Microsoft Research Asia State Key Laboratory of Information Security Institute of Information Engineering CAS School of Cyber Security University of Chinese Academy of Sciences School of Computer Science and Tech. University of Chinese Academy of Sciences Key Laboratory of Big Data Mining and Knowledge Management CAS Peng Cheng Laboratory Department of Mathematics Hong Kong University of Science and Technology Hong Kong

Due to the inherent uncertainty of data, the problem of predicting partial ranking from pairwise comparison data with ties has attracted increasing interest in recent years. However, in real-world scenarios, different individuals often hold distinct preferences. It might be misleading to merely look at a global partial ranking while ignoring personal diversity. In this paper, instead of learning a global ranking which is agreed with the consensus, we pursue the tie-aware partial ranking from an individualized perspective. Particularly, we formulate a unified framework which not only can be used for individualized partial ranking prediction, but also be helpful for abnormal user selection. This is realized by a variable splitting-based algorithm called iSplitLBI. Specifically, our algorithm generates a sequence of estimations with a regularization path, where both the hyperparameters and model parameters are updated. At each step of the path, the parameters can be decomposed into three orthogonal parts, namely, abnormal signals, personalized signals and random noise. The abnormal signals can serve the purpose of abnormal user selection, while the abnormal signals and personalized signals together are mainly responsible for individual partial ranking prediction. Extensive experiments on simulated and real-world datasets demonstrate that our new approach significantly outperforms state-of-the-art alternatives. The code is now availiable at https://***/qianqianxu010/ NeurIPS2019-iSplitLBI. Copyright © 2019, The Authors. All rights reserved.

关键词： Forecasting

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Expander Code: A Scalab.e Erasure-Resilient Code to Keep up with Data Growth in Distributed Storage

Expander Code: A Scalable Erasure-Resilient Code to Keep up ...

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IEEE International Performance computing and Communication Conference

作者： Guangping Xu Sheng Lin Hua Zhang Xing Guo Kai Shit Computer and Communication Engineering School Tianjin University of Technology Tianjin China 300384 Tianjin Key Lab. of Intelligence Computing and New Software Technology Tianjin China 300384

ISBN: (纸本)9781479932153

To ensure high reliability and storage efficiency, erasure codes are preferred in storage systems. With the prevalent of distributed storage systems such as clouds storage, how to design a scalab.e and efficient erasure-resilient code is challenging. We propose a scalab.e binary linear code to keep up with data growth which has the following properties. Given the group size k and the code block length n, the proposed code corrects any two bit erasures among the n bits. The redundancy overhead of the code is 2/(k + 2), and each data bit affects exactly 2 parity bits. As results of these properties, if a data bit is changed or added, only two parity bits need to be updated;and the recovery of an erasured bit requires accessing at most k other bits and the recovery of two erasured bits requires at most 2k other bits. We give the construction algorithm by the order expansion of regular graphs;moreover, we optimize the failure resilience during the construction procedure. Compared with existing codes, our proposed code has notable benefits in storage scalab.lity, redundancy overhead and I/O bandwidth. The deployment of the proposed code in distributed storage systems can be simple and practical.

关键词： Storage systems Erasure codes Scalab.lity Fault-tolerance Graph expansion

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