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  • 1  Research Progress and Prospects of Network Traffic Classification
    XIONG Gang MENG Jiao CAO Zi-gang WANG Yong GUO Li FANG Bin-xing
    2012, 1(1):32-42. DOI: 10.12146/j.issn.2095-3135.201205006
    [Abstract](9968) [HTML](0) [PDF 2.32 M](29110)
    Nowadays, with the rapid development of the Internet, more and more new applications appear gradually, the scale of network expand constantly, and the architecture of network is more and more complicated. As one of the basic technologies for enhancing network controllability, traffic classification can not only provide better QoS for ISPs, but also supervise and manage network effectively, which can ensure the security of the Internet. In this paper we review the research methods and achievements in the field of traffic classification, compare these traditional methods, and point out their advantages and disadvantages. On the other hand, for the real challenges of real-time classification of high-speed network environment, encrypted traffic classification, fine-grained traffic classification, and dynamically changed protocols classification, we describe and analyze the related research progress. Finally, we look ahead the future research direction.
    2  A Scalable Hybrid Algorithm for Solving Partial Differential Equations on a Cluster of CPU/GPU
    LUO Li YANG Chao ZHAO Yu-bo CAI Xiao-chuan
    2012, 1(1):84-88. DOI: 10.12146/j.issn.2095-3135.201205013
    [Abstract](6584) [HTML](0) [PDF 3.17 M](13194)
    Several of the top ranked supercomputers are based on the hybrid architecture consisting of a large number of CPUs and GPUs. High performance has been obtained for problems with special structures, such as FFT-based imaging processing or N-body based particle calculations. However, for the class of problems described by partial differential equations (PDEs) discretized by finite difference (or other mesh based methods such as finite element) methods, obtaining even reasonably good performance on a CPU/GPU cluster is still a challenge. In this paper, we propose and test an hybrid algorithm which matches the architecture of the cluster. The scalability of the approach is implemented by a domain decomposition method, and the GPU performance is realized by using a smoothed aggregation based algebraic multigrid method. Incomplete factorization, which performs beautifully on CPU but poorly on GPU, is completely avoided in the approach. Numerical experiments are carried out by using up to 32 CPU/GPUs for solving PDE problems discretized by FDM with up to 32 millions unknowns.
    3  On the Magnetic Localization Techniques for Position and Orientation of the Capsule Endoscope
    HU Chao SONG Shuang YANG Wan-an MENG Qing-hu LI Bao-pu ZENG De-wen LI Xiao-xiao ZHU Hong-mei
    2012, 1(1):105-113. DOI: 10.12146/j.issn.2095-3135.201205017
    [Abstract](6458) [HTML](0) [PDF 9.77 M](13925)
    Wireless Capsule Endoscope (WCE) is a very promising tool for the examination of the gastrointestinal (GI) tract. However, there are some problems to be solved for the existed WCE, and one key problem is the accurate localization and tracking of the WCE. Among the possible localization methods, the magnet-based localization technique has its advantages: no need for power, not much space occupation, continuously tracking ability, and no negative effect. In this paper, we present the localization method for the magnet objective inside the WCE based on the magnetic sensor array outside the human body. Through the algorithm and system design we realize real time tracking of 3D position and 2D orientation of the magnet based on the magnetic dipole model. In order to overcome the interference of the human body movement, we propose the multi-magnets’ localization method; also, the 3D positioning and 3D orientation method is proposed, which can be used to make the 3D recovery of the GI tract and the accurate computation of the physiological tissue parameters. The real experiments show that the proposed localization system can run well and obtain the accuracy with 2~3mm for the magnet.
    4  The Current Situation and Development Trend of Service Robot Research
    SONG Zhang-jun
    2012, 1(3):1-9. DOI: 10.12146/j.issn.2095-3135.201209001
    [Abstract](6022) [HTML](0) [PDF 6.34 M](21221)
    The technology of the robot represents a national high-tech level and the degree of automation. It is helpful to develop the industry of service robots in China if we know the current situation and development trend of service robots research clearly. Recently, robotic cleaners and educational robots have been in great demand. Entertainment robots and surveillance robots are developed rapidly and the market expands quickly. Medical robots begin to enter the modern life and have played an important role in the modern surgery. To satisfy the great market and shorten the distance between China and developed countries, it is necessary to capture the development trend of the technology of service robots. R&D on service robots should focus on the integrated technologies on intelligence, modularization and network.
    5  Imaging Algorithm and System Design for Ultrasound Transient Elastography
    SHEN Yang LING Tao YAO Hui LI Yan-ming JIN Qiao-feng ZHENG Hai-rong
    2012, 1(1):93-99. DOI: 10.12146/j.issn.2095-3135.201205015
    [Abstract](5823) [HTML](0) [PDF 4.76 M](14199)
    For the advantages of noninvasive, real-time and quantitative detection, ultrasonic transient elastography has important clinical application value. This work investigates the transient elastography in a few ways and aims to design a transient imaging system. The Displacement tracking algorithm based on correlation techniques and the parabolic interpolation algorithm is proposed to improve the accuracy. A novel match filter is designed to convolute with the estimated displacement in the time direction to boost the SNR of the displacement for a better strain image mapping. The convoluted result shows the match filter can significantly improve the strain image quality and help getting more accurate Youngs modulus estimation. The Time Gain Compensation (TGC) circuit is designed to compensate the attenuated power of the ultrasound signal. And a modified polyacrylamide gel based tissue-mimicking phantom is also developed in this paper, both indentation testing and transient elastography are used to characterize the elastic properties of this phantom. The results are almost consistent with each other.
    6  An Overview of Dynamic Control for Electric Vehicles
    XU Guo-qing XU Kun LI Wei-min
    2012, 1(1):6-14. DOI: 10.12146/j.issn.2095-3135.201205002
    [Abstract](5769) [HTML](0) [PDF 1.44 M](15454)
    With the increasing concerns of global warming and resource constraints, electric vehicles (EVs) have made great progress during the past decade. The electric driving system of EVs has dinstinct advantages, such as quick response, easy measurement , and precise control of motor torque, available flexible driving architecture, and regenerative braking, etc. Such advantages can be used to improve the performance of vehicle dynamic control. This paper presents the recent research efforts on electric vehicle dynamic control in terms of parameters estimation and dyanmic control scheme and methodology, especially focusing on the tire-road friction estimaion , novel traction control methods. The lateral dynamic control including the electrical differential control, direct yaw moment control, and the integratin chassis cotrol is proposed. Several prospects for vehicle dynamic control are proposed.
    7  Status and Challenges on Data Analysis of High Throughput Sequencing
    ZHANG Wen-li
    2012, 1(3):20-24. DOI: 10.12146/j.issn.2095-3135.201209004
    [Abstract](5734) [HTML](0) [PDF 2.67 M](18726)
    Gene is the genetic material basis. All life phenomena, like disease and death, are related to Gene. Gene sequencing is a way to read life. With the development of new generation high-throughput sequencing technology, TB or more sequence data will be generated daily. It’s more difficult to interpret these big and complex data than to acquire them. Sequence data interpretation is a critical step in current biological research and has great practical significance. It’s a great challenge for current computer systems and computing models to store, process and analysis massive high throughput sequence data. With survey, especially from BGI (Beijing Genome Institute), the current status, problems and measures taken to process high throughput sequence data will be discussed. However, the challenge is too big to be solved unless more people in different fields work together in depth for a long term.
    8  Research on Brachytherapy Robotics
    XING Lei CHEN Yan GU Jia NIU Tian-ye RONG Yi WANG Le-jing WEN Ning XIE Yao-qin YU Shao-de ZHENG Bo ZHENG Guo-yan ZHOU Shou-jun
    2012, 1(2):35-39. DOI: 10.12146/j.issn.2095-3135.201207007
    [Abstract](5598) [HTML](0) [PDF 726.73 K](2734)
    Medical robotics has become a popular and cutting-edge technology, with increasing importance on the medical service market. Brachytherapy robotics integrates brachytherapy technology and image-guided therapy technology. This paper provides introduction to the brachytherapy technology and image-guided therapy, and then discusses brachytherapy robotic systems. Future perspectives are given at the end.
    9  A Dozen Essential Issues of Computing for the Masses
    XU Zhi-wei LI Guo-jie
    2012, 1(1):20-25. DOI: 10.12146/j.issn.2095-3135.201205004
    [Abstract](5507) [HTML](0) [PDF 1.54 M](10769)
    Thirty years ago, the invention and volume shipment of IBM PC significantly enlarged the user population of computing. For the next thirty years, what is the most fundamental challenge of the computing field? What paradigm shift is needed? What is the most significant industrial problem? What are the most needed scientific breakthroughs? This article addresses these questions by discussing a dozen essential issues of computing for the masses. The most fundamental challenge is the computing market’s growth stagnation. Computing for the masses is proposed to reverse this trend and should be a fundamental future direction. It has three features of value-augmenting, affordability, and sustainability. The most basic paradigm shift is human-cyber-physical ternary computing. The most significant industrial problem is the Insecta Classis paradox. Computing for the masses needs five pillars of science support, including ternary computing science, universal compute account, efficient sea-network-cloud computing platforms, information ecosystem science, and national information accounts. This article helps outline the problem space for future computer science research, with a discussion on related transformative research projects.
    10  A Comparative Analysis of Performance of Some Processing Methods in Reducing Power-Line Interference from EMG Recordings
    ZHANG Hao-shi WU Zhen-xing TIAN Lan YANG Lin LI Guang-lin
    2012, 1(1):114-118. DOI: 10.12146/j.issn.2095-3135.201205018
    [Abstract](5490) [HTML](0) [PDF 5.69 M](13262)
    Effectively reducing power line interference is always an important issue in electromyography (EMG) signal recordings and analysis. In this study, four commonly used de-noising methods, including digital notch, LMS based adaptive filter, Kalman filter and S transform, which may be suitable for the reduction of power line interference in real-time EMG recordings, were chosen and their performance in reducing the power line interference from EMG signal recordings were quantitatively analyzed and compared. The pilot results of this study showed that Kalman filter presented the best whole performance in attenuating power line interference from EMG signals and S transform de-noising method illustrated the best performance when the power line interference was severe.
    11  Scientific Computing Grid and SCE Middleware
    CHI Xue-bin XIAO Hai-li WANG Xiao-ning CAO Rong-qiang LU Sha-sha ZHANG Hong-hai
    2012, 1(1):68-76. DOI: 10.12146/j.issn.2095-3135.201205011
    [Abstract](5361) [HTML](0) [PDF 2.94 M](12409)
    This paper introduces the scientific computing grid, ScGrid, and it’s middleware SCE. ScGrid is built as one virtual supercomputer, integrating computing resource from more than 30 institutes. It provides unified,?easy to use and reliable scientific computing services. SCE is a lightweight grid middleware, which supports global job scheduling and unified data view. It provides multiple user interfaces including command line, grid portal and APIs. At present, ScGrid has been very successfully used in Chinese Academy of Sciences and widely accepted by more than 200 users.
    12  The Study and Realization of an Early Pre-impact Fall Alarm System
    LI Huiqi LIANG Ding NING Yunkun ZHANG Jing ZHAO Guoru
    2014, 3(1):46-54. DOI: 10.12146/j.issn.2095-3135.201401005
    [Abstract](5317) [HTML](0) [PDF 1.06 M](4679)
    Falls are the second leading cause of unintentional injury deaths worldwide, so how to prevent falls has become a safety and security problem for elderly people. At present, because the sensing modules of most fall alarms generally only integrate the single 3-axis accelerometer, the measurement accuracy of sensing signals is limited. They can only achieve the alarm of post-fall detection but not the early pre-impact fall recognition in real fall applications. Therefore, an early preimpact fall alarm system based on high-precision inertial sensing units was studied and developed in this paper. A multimodality sensing module embedded with the fall detection algorithm was developed for the early pre-impact fall detection. The module included a 3-axis accelerometer, a 3-axis gyroscope and a 3-axis magnetometer, which could arouse early preimpact fall warnings by a buzzer and a vibrator. Total 81 times of fall experiments from 9 healthy subjects were conducted in simulated fall conditions. The result shows that the detection sensitivity of the system combining the early warning threshold algorithm can reach 98.61% with a specificity of 98.61%, and the average pre-impact lead time is 300 ms. In the future, GPS, GSM electronic modules and wearable protected airbags will be embedded in the system, which will enhance real-time fall protections and timely treatments for the elderly people.
    13  The Prospect of Electric Vehicles: Pure Electrification, Intelligence and Human Care
    XU Guoqing XU Kun ZHANG Qi ZHENG Chunhua LIANG Jianing ZHOU Yimin
    2014, 3(1):1-17. DOI: 10.12146/j.issn.2095-3135.201401001
    [Abstract](5217) [HTML](0) [PDF 1.60 M](3303)
    In this paper, a new concept of fully electrified vehicles, based on the principle that the braking energy can be fully recovered via electrical motor and active safety control so as to improve energy efficiency greatly, was proposed. It reveals that this type of vehicles possesses the characteristics of perception for vehicle motion behaviour and the related intelligent detection methods were also introduced. At the same time, the dynamic control structure of the mechanicalelectrical decoupling in the vehicles was also discussed. Furthermore, the strategy of energy-saving, human-machine interaction, assistant driving and human care technologies were illustrated as well.
    14  Machine Translation Research and Technology
    LIU Qun
    2012, 1(1):48-54. DOI: 10.12146/j.issn.2095-3135.201205008
    [Abstract](5154) [HTML](0) [PDF 1.67 M](17891)
    This paper gives a comprehensive introduction to the status of current machine translation research and technology, and analyzes the key problems to be resolved. Finally our idea of the future trends and prospects of machine translation are put forward.
    15  Smoothed-Particle Hydrodynamics Simulation for Interactive Motion Effects
    XU Tian-chen WU En-hua
    2012, 1(1):77-83. DOI: 10.12146/j.issn.2095-3135.201205012
    [Abstract](4806) [HTML](0) [PDF 6.36 M](11970)
    In the past work for long time, since the computation required on object deformation and interaction is intensive, when fluid is interacted with rigid bodies, or especially with animating figure, the demand of real-time simulation and rendering could be hardly achieved. This paper presents a novel approach for generating effects simulated by fluid dynamics and interacted by the figure motions. In order to handle the interaction between fluid effect and deformed figure, firstly, the motion trajectory of character is tracked, and then the fluid dynamics is simulated by the model of Smoothed-Particle Hydrodynamics (SPH). Moreover, during the fluid simulation, an efficient algorithm for particle searching is also proposed, in virtue of parallel processing by GPU. Consequently, the simulation of 3D fluid effects with realistic character interaction can be rendered on a consumer-level PC in real-time.
    16  A Muti-resource Fair Scheudler of Hadoop
    MA Xiao-yan HONG Jue
    2012, 1(3):66-71. DOI: 10.12146/j.issn.2095-3135.201209012
    [Abstract](4595) [HTML](0) [PDF 2.31 M](15028)
    Hadoop job schedulers typically use a single resource abstraction and resources are allocated at the level of fixed-size partition of the nodes, called slots. These job schedulers ignore the different demands of jobs and fair allocation of multiple types of resources, leading to poor performance in throughput and average job completion time. This paper studies and implements a Muti-resource Fair Scheduler (MFS) in Hadoop. MFS adopts the idea of Dominant Resource Fairness (DRF). It uses a demand vector to describe demands for resources of a job and allocates resources to the job according to the demand vector. MFS uses resources more efficiently and satisfies multiple jobs with heterogeneous demands for resources. Experiment results show that MFS has higher throughput and shorter average job completion time compared to Hadoop slot-based Fair Scheduler and Capacity Scheduler.
    17  Current Research and Development Trend of Surface Drop Foot Stimulator
    WU Zhen ZHOU Hui LI Guang-lin
    2013, 2(4):56-60. DOI: 10.12146/j.issn.2095-3135.201307010
    [Abstract](4250) [HTML](0) [PDF 1.64 M](12328)
    Foot drop is the inability to voluntarily dorsiflex the ankle during the swing phase of gait and is usually caused by weakness and damages of the peroneal nerve. The consequences of the foot drop include the decreasing of gait quality, the limiting of mobility, the increasing of falling risk, and great increasing of energy expenditure during walking. Firstly biosignal sensors are used in the drop foot stimulator to detect foot movements. Then the surface drop foot stimulator produces a predefined stimulation profile to the peroneal nerve or tibialis anterial to elicit a dorsiflexion of the foot synchronized with the swing phase of gait to lift the foot. This paper reviewed the fundamentals and current researches of drop foot stimulators. Moreover, the development trends of the closed loop drop foot stimulator were also discussed in the paper.
    18  A Review on Deep Web Research and Prospects
    GAO Ming HUANG Zhe-xue
    2012, 1(3):47-54. DOI: 10.12146/j.issn.2095-3135.201209009
    [Abstract](4173) [HTML](0) [PDF 1.37 M](14034)
    With the rapid increase in numbers and scales of deep web sites on the Internet, search for data or information from deep web sites by submiting queries to and obtaining results from the backend databases has become a major means in information retrieval from the Web. This area has attracted many researchers to devote their efforts on development of technologies to make better use of information in th deep web. One challenge is searching for and integration of data from various databases in deep web. Since deep web is dominated by text data, research and development of technologies for text information retrieval from deep web have a broad application potential. In this paper, we review the state-of-the-art of deep web research in details and propose some future research directions.
    19  Training Method of Automatic Driving Strategy Based on Deep Reinforcement Learning
    XIA Wei LI Huiyun
    2017, 6(3):29-40. DOI: 10.12146/j.issn.2095-3135.201703003
    [Abstract](3607) [HTML](0) [PDF 1.35 M](15777)
    Automatic drive is an important application field of artificial intelligence. In this paper, a novel training strategy for self-driving vehicles was investigated based on the deep reinforcement learning model. The proposed method involves a Q-learning algorithm with filtered experience replay and pre-training with experiences from professional drivers, which accelerates the training process due to reduced exploration spaces. By resampling the input state after clustering, generalization ability of the strategy can be improved due to the individual and independent distribution of the samples. Experimental results show that, in comparison with conventional neural fitted Q-iteration algorithm, the training efficiency and controlling stability can be improved more than 90% and 30% respectively by the proposed approach. Experimental results with more complex testing tracks show that, average travel distance can be improved more than 70% in comparison with the Q-learning algorithm by the proposed method.

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