ViWoSG: A distributed scene graph of ultramassive distributed virtual environments

An ultra-massive distributed virtual environment generally consists of ultra-massive terrain data and a large quantity of objects and their attribute data, such as 2D/3D geometric models, audio/video, images, vectors, characteristics, etc. In this paper, we propose a novel method for constructing distributed scene graphs with high extensibility. Thismethod can support high concurrent interaction of clients and implement various tasks such as editing, querying, accessing and motion controlling. Some application experiments are performed to demonstrate its efficiency and soundness. Supported by the National Basic Research Program of China (Grant No. 2004CB719403), the National High-Tech Research & Development Program of China (Grant Nos. 2006AA01Z334, 2007AA01Z318, 2009AA01Z324), the National Natural Science Foundation of China (Grant Nos. 60573151, 60703062, 60833007), and the Marine 908-03-01-10 Project     

Receding horizon estimation to networked control systems with multirate scheme

This paper investigates the problem of receding horizon state estimation for networked control systems (NCSs) with random network-induced delays less than one sample period, which are formulated as multirate control systems. Based on a batch of recent past slow rate measurements in a finite horizon window, the initial state estimation in this window is solved by minimizing a receding-horizon objective function, and then the fast rate state estimations are calculated by the prediction of dynamic equation to compensate for the network-induced time delays. Furthermore, convergence results and unbiasedness properties are analyzed. An upper bound of estimation error is presented under the assumption of bounded disturbances acting on the system and measurement equations. A simulation example shows the effectiveness of the proposed method. Supported by the National Natural Science Foundation of China (Grant Nos. 60774015, 60674018, 60825302), the National High-Tech Research & Development Program of China (Grant No. 2006AA04Z173), the Specialized Research Fund for the Doctoral Program of Higher Education of China (Grant No. 20060248001), and partly by Shanghai Natural Science Foundation (Grant No. 07JC14016)     

Removing local irregularities of triangular meshes with highlight line models

The highlight line model is a powerful tool in assessing the quality of a surface. It increases the flexibility of an interactive design environment. In this paper, a method to generate a highlight line model on an arbitrary triangular mesh is presented. Based on the highlight line model, a technique to remove local shape irregularities of a triangular mesh is then presented. The shape modification is done by solving a minimization problem and performing an iterative procedure. The new technique improves not only the shape quality of the mesh surface, but also the shape of the highlight line model. It provides an intuitive and yet suitable method for locally optimizing the shape of a triangular mesh. Supported by National Science Foundation of China (Grant Nos. 60533070, 60625202), National Basic Research Program of China (Grant No. 2004CB719400), National High-Tech Research & Development Program of China (Grant No. 2007AA040401), Fok Ying Tung Education Foundation (Grant No. 111070), National Science Foundation of USA (Grant Nos. DMI-0422126, DMS-0310645), and Kentucky Science & Technology Corporation (Grant No. COMM-Fund-712)     

Min-max model predictive control for constrained nonlinear systems via multiple LPV embeddings

A min-max model predictive control strategy is proposed for a class of constrained nonlinear system whose trajectories can be embedded within those of a bank of linear parameter varying (LPV) models. The embedding LPV models can yield much better approximation of the nonlinear system dynamics than a single LTV model. For each LPV model, a parameter-dependent Lyapunov function is introduced to obtain poly-quadratically stable control law and to guarantee the feasibility and stability of the original nonlinear system. This approach can greatly reduce computational burden in traditional nonlinear predictive control strategy. Finally a simulation example illustrating the strategy is presented. Supported by the National Natural Science Foundation of China (Grant Nos. 60774015, 60825302, 60674018), the National High-Tech Research & Development Program of China (Grant No. 2007AA041403), the Specialized Research Fund for the Doctoral Program of Higher Education of China (Grant No. 20060248001), and partly by Shanghai Natural Science Foundation (Grant No. 07JC14016)     

New delay-dependent criterion for the stability of recurrent neural networks with time-varying delay

This paper is concerned with the global asymptotic stability of a class of recurrent neural networks with interval time-varying delay. By constructing a suitable Lyapunov functional, a new criterion is established to ensure the global asymptotic stability of the concerned neural networks, which can be expressed in the form of linear matrix inequality and independent of the size of derivative of time varying delay. Two numerical examples show the effectiveness of the obtained results. Supported by the National Natural Science Foundation of China (Grant Nos. 60534010, 60728307, 60774048, 60774093), the Program for Cheung Kong Scholars and Innovative Research Groups of China (Grant No. 60521003) and the National High-Tech Research & Development Program of China (Grant No. 2006AA04Z183), China Postdoctoral Sciencer Foundation (Grant No. 20080431150), and the Specialized Research Fund for the Doctoral Program of Higher Education of China (Grant No. 200801451096)     

Test-Data Generation Guided by Static Defect Detection

Software testing is an important technique to assure the quality of software systems, especially high-confidence systems. To automate the process of software testing, many automatic test-data generation techniques have been proposed. To generate e?ective test data, we propose a test-data generation technique guided by static defect detection in this paper. Using static defect detection analysis, our approach first identifies a set of suspicious statements which are likely to contain faults, then generates t...     

Demand-Driven Memory Leak Detection Based on Flow- and Context-Sensitive Pointer Analysis

We present a demand-driven approach to memory leak detection algorithm based on flow- and context-sensitive pointer analysis. The detection algorithm firstly assumes the presence of a memory leak at some program point and then runs a backward analysis to see if this assumption can be disproved. Our algorithm computes the memory abstraction of programs based on points-to graph resulting from flow- and context-sensitive pointer analysis. We have implemented the algorithm in the SUIF2 compiler infrastructure and used the implementation to analyze a set of C benchmark programs. The experimental results show that the approach has better precision with satisfied scalability as expected. This work is supported by the National Natural Science Foundation of China under Grant Nos. 60725206, 60673118, and 90612009, the National High-Tech Research and Development 863 Program of China under Grant No. 2006AA01Z429, the National Basic Research 973 Program of China under Grant No. 2005CB321802, the Program for New Century Excellent Talents in University under Grant No. NCET-04-0996, and the Hunan Natural Science Foundation under Grant No. 07JJ1011.     

A Trust-Based Approach to Estimating the Confidence of the Software System in Open Environments

Emerging with open environments, the software paradigms, such as open resource coalition and Internetware, present several novel characteristics including user-centric, non-central control, and continual evolution. The goal of obtaining high confidence on such systems is more di?cult to achieve. The general developer-oriented metrics and testing-based methods which are adopted in the traditional measurement for high confidence software seem to be infeasible in the new situation. Firstly, the software develo...     

Estimating differential quantities from point cloud based on a linear fitting of normal vectors

Estimation of differential geometric properties on a discrete surface is a fundamental work in computer graphics and computer vision. In this paper, we present an accurate and robust method for estimating differential quantities from unorganized point cloud. The principal curvatures and principal directions at each point are computed with the help of partial derivatives of the unit normal vector at that point, where the normal derivatives are estimated by fitting a linear function to each component of the normal vectors in a neighborhood. This method takes into account the normal information of all neighboring points and computes curvatures directly from the variation of unit normal vectors, which improves the accuracy and robustness of curvature estimation on irregular sampled noisy data. The main advantage of our approach is that the estimation of curvatures at a point does not rely on the accuracy of the normal vector at that point, and the normal vectors can be refined in the process of curvature estimation. Compared with the state of the art methods for estimating curvatures and Darboux frames on both synthetic and real point clouds, the approach is shown to be more accurate and robust for noisy and unorganized point cloud data. Supported in part by the National Natural Science Foundation of China (Grant Nos. 60672148, 60872120), the National High-Tech Research & Development Program of China (Grant Nos. 2006AA01Z301, 2008AA01Z301), and Beijing Municipal Natural Science Foundation (Grant No. 4062033)     

Analysis and case study on multi-dimensional scalability of the Internet architecture

This paper presents the definition of multi-dimensional scalability of the Internet architecture, and puts forward a mathematical method to evaluate Internet scalability based on a variety of constraints. Then, the method is employed to study the Internet scalability problem in performance, scale and service scalability. Based on the examples, theoretical analysis and experimental simulation are conducted to address the scalability issue. The results show that the proposed definition and evaluation method of multi-dimensional Internet scalability can effectively evaluate the scalability of the Internet in every aspect, thus providing rational suggestions and methods for evaluation of the next generation Internet architecture.     

Globally exponentially attractive sets of the family of Lorenz systems

In this paper, the concept of globally exponentially attractive set is proposed and used to consider the ultimate bounds of the family of Lorenz systems with varying parameters. Explicit estimations of the ultimate bounds are derived. The results presented in this paper contain all the existing results as special cases. In particular, the critical cases, b→ 1^＋ and a→0^＋, for which the previous methods failed, have been solved using a unified formula.     

Robust linear receivers for STBC systems with unknown co-channel interference

Focusing on space-time block code (STBC) systems with unknown co-channel interference, an oblique projection-based robust linear receiver is proposed in this paper. Based on the oblique projection, the desired signal subspace and interference-plus-noise subspace are first identified from the received signal. Then the matched filter receiver is used to decode the STBC encoded signals in the desired signal subspace. Simulation results show that the proposed linear receiver obtains significant performance improvement over conventional Capon-type receivers under finite sample-size situations and in the presence of channel estimation errors. Supported partially by the National Natural Science Foundation of China (Grant Nos. 60572046, 60502022, 60772095), and the National High-Tech Research & Development Program of China (Grant No. 2006AA01Z220)     

A 485ps 64-Bit Parallel Adder in 0.18$\mu$m CMOS

This paper presents an optimized 64-bit parallel adder. Sparse-tree architecture enables low carry-merge fan-outs and inter-stage wiring complexity. Single-rail and semi-dynamic circuit improves operation speed. Simulation results show that the proposed adder can operate at 485ps with power of 25.6mW in 0.18μm CMOS process. It achieves the goal of higher speed and lower power.     

Multivariable direct adaptive decoupling controller using multiple models and a case study

In this paper, a multivariable direct adaptive controller using multiple models without minimum phase assumption is presented to improve the transient response when the parameters of the system jump abruptly. The controller is composed of multiple fixed controller models, a free-running adaptive controller model and a re-initialized adaptive controller model. The fixed controller models are derived from the corresponding fixed system models directly. The adaptive controller models adopt the direct adaptive algorithm to reduce the design calculation. At every instant, the optimal controller is chosen out according to the switching index. The interaction of the system is viewed as the measured disturbance which is eliminated by the choice of the weighing polynomial matrix. The global convergence is obtained. Finally, several simulation examples in a wind tunnel experiment are given to show both effectiveness and practicality of the proposed method. The significance of the proposed method is that it is applicable to a non-minimum phase system, adopting direct adaptive algorithm to overcome the singularity problem during the matrix calculation and realizing decoupling control for a multivariable system. Supported by the National Natural Science Foundation of China (Grant Nos. 60504010, 60864004), the National High-Tech Research and Development Program of China (Grant No. 2008AA04Z129), the Key Project of Chinese Ministry of Education (Grant No. 208071), and the Natural Science Foundation of Jiangxi Province (Grant No. 0611006)     

Neural Network Algorithm for Designing FIR Filters Utilizing Frequency-Response Masking Technique

This paper presents a new joint optimization method for the design of sharp linear-phase finite-impulse response (FIR) digital filters which are synthesized by using basic and multistage frequency-response-masking(FRM) techniques.The method is based on a batch back-propagation neural network algorithm with a variable learning rate mode.We propose the following two-step optimization technique in order to reduce the complexity.At the first step,an initial FRM filter is designed by alternately optimizing th...     

A survey on virtual reality

Virtual reality (VR) is a scientific method and technology created during the exploration of the nature by human beings to understand, simulate, and better adapt and use the nature. Based on the analysis on the whole process of VR, this paper presents different categories of VR problems and a type of theoretical expression, and abstracts three kinds of scientific and technical problems in VR field. On the basis of foresaid content, this paper also studies current major research objectives, research results and development trend of VR in the aspects of VR modeling method, VR representation technology, human-machine interaction and devices, VR development suites and supporting infrastructure, as well as VR applications. Finally, several theoretical and technical problems that need to be further studied and solved are addressed. Supported by the National Basic Research Program of China (Grant No. 2009CB320805), the National Natural Science Foundation of China (Grant Nos. 60533070, 60503066), and the National High-Tech Research & Development Program of China (Grant Nos. 2006AA01Z333, 2006AA01Z311)     

Study and application of temporal index technology

This paper addresses the mathematical relation on a set of periods and temporal indexing constructions as well as their applications. First we introduce two concepts, i.e. the temporal connection and temporal inclusion, which are equivalence relation and preorder relation respectively. Second, by studying some basic topics such as the division of “large” equivalence classes and the overlaps of preorder relational sets, we propose a temporal data index model (TDIM) with a tree-structure consisting of a root node, equivalence class nodes and linearly ordered branch nodes. Third, we study algorithms for the temporal querying and incremental updating as well as dynamical management within the framework of TDIM. Based on a proper mathematical supporting, TDIM can be applied to researching some significant practical cases such as temporal relational and temporal XML data and so on. Supported by the National Natural Science Foundation of China (Grant Nos. 60373081, 60673135), the Natural Science Foundation of Guangdong Province (Grant No. 05003348), the Program of New Century Excellent Person Supporting of Ministery of Education of China (Grant No. NCET-04-0805)     

Recent advances on virtual human synthesis

Virtual human is a digital representation of the geometric and behavioral property of human beings in the virtual environment generated by computer. The research goal of virtual human synthesis is to generate realistic human bodymodels and natural human motion behavior. This paper introduces the development of the related researches on these two topics, and some progresses on example based human modeling and motion synthesis, and their applications in Chinese sign language teaching, computeraided sports training and public safety problem studying. Finally, some hot research topics in virtual human synthesis are presented. Supported partially by the National High-Tech Research & Development Program of China (Grant Nos. 2006AA01Z336, 2007AA01Z320), and the National Natural Science Foundation of China (Grant No. 60533070)     

Optimal iterative learning control for end-point product qualities in semi-batch process based on neural network model

An optimal iterative learning control (ILC) strategy of improving endpoint products in semi-batch processes is presented by combining a neural network model. Control affine feed-forward neural network (CAFNN) is proposed to build a model of semi-batch process. The main advantage of CAFNN is to obtain analytically its gradient of endpoint products with respect to input. Therefore, an optimal ILC law with direct error feedback is obtained explicitly, and the convergence of tracking error can be analyzed theoretically. It has been proved that the tracking errors may converge to small values. The proposed modeling and control strategy is illustrated on a simulated isothermal semi-batch reactor, and the results show that the endpoint products can be improved gradually from batch to batch. Supported by the National Natural Science Foundation of China (Grant Nos. 60404012, 60874049), the National High-Tech Research & Development Program of China (Grant No. 2007AA041402), the New Star of Science and Technology of Beijing City (Grant No. 2006A62), and the IBM China Research Lab 2008 UR-Program