Abstract: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.

Abstract:In various humanoid robot research areas such as biped walking and balance maintenance, control of Center of Mass (COM) is frequently used. However, it becomes a complex problem to directly control the COM for a high degree of freedom humanoid robot, especially in case of double feet support. In this paper, an iterative method that is easy to implement is proposed. Based on the approximated assumption that COM is fixed in local coordinate system, the control angle of the robot leg can be solved to drive the COM toward the target position. This process can be iterated to achieve high precision. Simulation tests on a NAO humanoid robot have demonstrated that the algorithm is efficient and precise.

Abstract: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.

Abstract:Recently, the Internet of Things (IoT) technology has attracted more and more attention. This is because the IoT technique can be widely used in a variety of applications, such as smart grid and intelligent transportation, healthcare, art, logistics, environmental monitoring and life. Today, the development of the IoT has been considered as one of the key technologies for improving the quality of daily activities of people. This paper firstly introduces the background and applications of the IoT and depicts the concept and architecture of the IoT. Then, this paper further presents the design and implementation of the Mushroom Networks, including the software, firmware and hardware designs. Several IoT technologies have been applied in the implementation of the mushroom node, including sensing, wireless communication and heterogeneous networking, making the Mushroom Networks to be a typical example of the IoT applied in art and culture domain.

Abstract: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.

Abstract:A novel programming interface (API) is introduced in this paper. The basic requirement is for multiple and asynchronous calling processes to capture a data stream without affecting each other. IP multicasting is the primary tool employed for this purpose. UDP is used at transport layer. The current implementation is based on the stream of web pages produced by a high performance web crawler. Along with the interface, a demo application (WordCount) is also implemented. Experiments have verified the robustness of the design, and preliminary measurement shows 1-3% data loss is observed, which is acceptable for many streaming data applications.

Abstract: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.

Abstract:With the development of the Internet technology and the changes of the situation of Internet security, we witness exponential increase of the number of malicious software and their endless variants. Traditional detection methods cannot effectively and timely deal with such mass of malicious software data, making traditional anti-virus platform running on PC client cannot satisfy current security requirements any more, thus some major Internet security venders have been launching their ‘cloud security’ program. Under such background, it is urgent to develop some new effective and efficient techniques for malware detection. In this paper, we investigate malware detection techniques based on cloud computing, including mining massive software samples, and applying new clustering models/algorithms for event sequences into malware detection, to deal with the critical issues of malware as being of large amount, fast change, high-dimension and noise-laden. Furthermore, we propose a prototype of intelligent malware detection system for cloud security.

Abstract: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.

Abstract: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.

Abstract: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.

Abstract:This paper analyzed the state of the art of computer architecture researchand development combining computing and communication. Also discussed were the requirements to processor architecture from cloud, network and terminal sides. A research direction regarding the many-core processor architecture suitable for communication applications was proposed.

Abstract: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.

Abstract:Misdiagnosis of subarachnoid hemorrhage (SAH) is as high as 25%, due to the difficulties discerning bleeding since SAH re-circulates within the subarachnoid space to make the change in grayscales of bleeding very subtle. For computer assisted diagnosis (CAD) of SAH, its state-of-the-art is reviewed: SAH can be in the form of effacement of sulci or high signal with low contrast on computed tomography (CT) images, and is difficult to be segmented using traditional segmentation methods; existing CAD system of SAH consisted of 2 steps (approximation of subarachnoid space via atlas registration or distance transformation and judging abnormalities of grayscale distribution in the approximated subarachnoid space by means of pattern recognition), and can yield erroneous conclusions when the bleeding is small or effacement of sulci occurs. Details of the algorithms are given to approximate subarachnoid space based on distance transform and to recognize SAH based on support vector machine. Possible ways to enhance the performance of CAD of SAH are pointed out: to develop new image processing methods such that high signals with low contrast as well as sulci can be well segmented and quantified.

Abstract: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.

Abstract: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.