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Theoretical research progress in new-generation Internet architecture

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science in china(Series F) 2008年第11期51卷 1634-1660页

作者： WU JianPing1,2,3,LIU ying2,3 & WU Qian2,3 1 department of computer science,tsinghua university,beijing 100084,china 2 Network Research Center,tsinghua university,beijing 100084,china 3 tsinghua National Laboratory for Information science and technology(TNList) ,beijing 100084,china department of computer science Tsinghua University Network Research Center Tsinghua University tsinghua National Laboratory for Information science and technology (TNList)

Internet has become the most important information infrastructure supporting modern socio-economic development, social progress and technological Innovation. Invented 30 years ago, today Internet is facing increasingly severe technical challenges. This paper introduces the progress of the major international newgeneration Internet research plans; analyzes its basic characteristics and the principal contradictions during the development; detsiledly introduces the research carried out by 973 Project ＂Research of Future Internet Architecture＂ on the key scientific issues of new-generation Internet architecture and its latest research results; and looks to the future of the research-focus faced with the new situations of the basic research of new-generation Internet architecture as well as the new demands of innovative applications on Internet architecture.

关键词： new-generation Internet network architecture multi-dimension scalability

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一种实时视景仿真中高度场地形绘制算法

系统仿真学报 2005年第1期17卷 83-86页

作者：见英叶榛清华大学计算机科学与技术系北京100084 智能技术与系统国家重点实验室北京100084

大地形的快速实时绘制对于虚拟现实、GIS、飞行模拟、游戏制作等方面的应用都有着重要意义。这方面,国内外算法主要集中在视点相关连续LOD(Level of Detail)上面。对已有算法进行了综合及改进,实现了一个简单快速的大地形绘制算法。算法... 详细信息

大地形的快速实时绘制对于虚拟现实、GIS、飞行模拟、游戏制作等方面的应用都有着重要意义。这方面,国内外算法主要集中在视点相关连续LOD(Level of Detail)上面。对已有算法进行了综合及改进,实现了一个简单快速的大地形绘制算法。算法中,视区剪裁采用"中点分割"的思想,结合了四又树剖分过程,提高了效率。误差控制方面,引入预处理及误差反馈的思想,并对误差进行扩散,加速了绘制同时保证了对地形细节的表现。算法对裂缝拼接也做了改进。算法运行结果良好,在普通微机上即可达到较高的帧速率和较好的绘制效果。

关键词：地形绘制多分辨率视区剪裁裂缝消除

△-tame quasi-hereditary algebras

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science china Mathematics 2007年第2期50卷 240-252页

作者： Yun-ge XU & ying-bo ZHANG Faculty of Mathematics and computer science, Hubei university, Wuhan 430062, china School of Mathematics sciences, beijing Normal university, beijing 100875, china Faculty of Mathematics and computer science Hubei University Wuhan China School of Mathematics sciences Beijing Normal University Beijing China

Let (K, M,H) be an upper triangular bimodule problem. Briistle and Hille showed that the opposite algebra A of the endomorphism algebra of a projective generator P of the matrices category of (K., M, H) is quasi-hereditary, and there is an equivalence between the category of△-good modules of A and Mat(K, M). In this note, based on the tame theorem for bimodule problems, we show that if the algebra A associated with an upper triangular bimodule problem is of△-tame representation type, then the category F(△) has the homogeneous property, i.e. almost all modules in F(△) are isomorphic to their Auslander-Reiten translations. Moreover, if (K, M,H)is an upper triangular bipartite bimodule problem, then A is of△-tame representation type if and only if F(△) is homogeneous.

关键词： bimodule problem quasi-hereditary algebra △-tameness homogeneity.

Geo-Agents: Design and Implement

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Wuhan university Journal of Natural sciences 2001年第Z1期6卷 451-459页

作者： Ding Li, Qu Lei, Zhang ying, Luo ying wei, Wang Xiao lin, Xu Zhuo qun department of computer science & technology,Peking university, beijing 100871, china department of computer science & technology Peking University Beijing 100871 China

Geo Agents, a multi agent system that processes distributed geospatial information and geospatial service was presented. Firstly, the requirement for distributed geographical information process was discussed, and the architecture of Geo Agents was introduced. Then in depth discussions were raised on agent system implementation, such as the basic agent, agent advertising, message passing, and collaborating. An example was also given to explain the problem solving process.

关键词： geographical information system (GIS) multi agent system (MAS) Geo Ggents communication collaboration

Laplacian smoothing transform for face recognition

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science china(Information sciences) 2010年第12期53卷 2415-2428页

作者： GU SuiCheng, TAN ying & HE XinGui Key Laboratory of Machine Perception (MOE) department of Machine Intelligence, School of Electronics Engineering and computer science Peking university, beijing 100871, china Key Laboratory of Machine Perception (MOE) department of Machine Intelligence School of Electronics Engineering and Computer Science Peking university

In this paper, we investigate how to extract the lowest frequency features from an image. A novel Laplacian smoothing transform (LST) is proposed to transform an image into a sequence, by which low frequency features of an image can be easily extracted for a discriminant learning method for face recognition. Generally, the LST is able to be an efficient dimensionality reduction method for face recognition problems. Extensive experimental results show that the LST method performs better than other pre-processing methods, such as discrete cosine transform (DCT), principal component analysis (PCA) and discrete wavelet transform (DWT), on ORL, Yale and PIE face databases. Under the leave one out strategy, the best performance on the ORL and Yale face databases is 99.75% and 99.4%; however, in this paper, we improve both to 100% with a fast linear feature extraction method for the first time.

关键词： Laplacian smoothing transform (LST) face recognition principal component analysis (PCA) discrete cosine transform (DCT) discrete wavelet transform (DWT) linear discriminant analysis (LDA)

A malware detection model based on a negative selection algorithm with penalty factor

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science china(Information sciences) 2010年第12期53卷 2461-2471页

作者： ZHANG PengTao 1,2 , WANG Wei 1,2 & TAN ying 1,2 1 department of Machine Intelligence, School of Electronics Engineering and computer science, Peking university, beijing 100871, china 2 Key Laboratory of Machine Perception, Ministry of Education, Peking university, beijing 100871, china department of Machine Intelligence School of Electronics Engineering and Computer Science Peking University Key Laboratory of Machine Perception Ministry of Education Peking University

A malware detection model based on a negative selection algorithm with penalty factor (NSAPF) is proposed in this paper. This model extracts a malware instruction library (MIL), containing instructions that tend to appear in malware, through deep instruction analysis with respect to instruction frequency and file frequency. From the MIL, the proposed model creates a malware candidate signature library (MCSL) and a benign program malware-like signature library (BPMSL) by splitting programs orderly into various short bit strings. Depending on whether a signature matches "self", the NSAPF further divides the MCSL into two malware detection signature libraries (MDSL1 and MDSL2), and uses these as a two-dimensional reference for detecting suspicious programs. The model classifies suspicious programs as malware and benign programs by matching values of the suspicious programs with MDSL1 and MDSL2. Introduction of a penalty factor C in the negative selection algorithm enables this model to overcome the drawback of traditional negative selection algorithms in defining the harmfulness of "self" and "nonself", and focus on the harmfulness of the code, thus greatly improving the effectiveness of the model and also enabling the model to satisfy the different requirements of users in terms of true positive and false positive rates. Experimental results confirm that the proposed model achieves a better true positive rate on completely unknown malware and a better generalization ability while keeping a low false positive rate. The model can balance and adjust the true positive and false positive rates by adjusting the penalty factor C to achieve better performance.

关键词： penalty factor negative selection algorithm signature extraction artificial immune system mal- ware detection

TWO-SCALE FINITE ELEMENT GREEN'S FUNCTION APPROXIMATIONS WITH APPLICATIONS TO ELECTROSTATIC POTENTIAL COMPUTATION

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Journal of Systems science & Complexity 2010年第1期23卷 177-193页

作者： ying YANG Aihui ZHOU department of Computational science and Mathematics Guilin University of Electronic Technology Guilin 541004 China. The State Key Laboratory of Scientific and Engineering Computing Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing 100190 China.

In this paper,a two-scale finite element approach is proposed and analyzed for approximationsof Green's function in *** approach is based on a two-scale finite elementspace defined,respectively,on the whole domain with size H and on some subdomain containing singularpoints with size h (h << H).It is shown that this two-scale discretization approach is very *** particular,the two-scale discretization approach is applied to solve Poisson-Boltzmann equationssuccessfully.

关键词： Error analysis finite element Green's function Poisson-Boltzmann equation two-scale.

The Machine Recognition for Population Feature of Wheat Images Based on BP Neural Network

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Agricultural sciences in china 2002年第8期1卷 885-889页

作者： LI Shao-kun, SUO Xing-mei, BAI Zhong-ying, QI Zhi-li, Liu Xiao-hong, GAO Shi-ju and ZHAO Shuang-ning( Institute of Crop Breeding and Cultivation /Key Laboratory of Crop Genetic & Breeding, Ministry of Agriculture, ChineseAcademy of Agricultural sciences, beijing 100081 , P . R . china department of computer science and technology, Centraluniversity for Nationalities, beijing 100081 , P. R . china School of computer science and technology, beijing universityof Posts and Telecommunications, beijing 100876, P. R . china Research Center of Xinjiang Crop High-yield,Shihezi university, Shihezi 832003, P.R. china) Institute of Crop Breeding and Cultivation/Key Laboratory of Crop Genetic (ж) Breeding Ministry of Agriculture Chinese Academy of Agricultural Sciences Beijing 100081 P.R.China Research Center of Xinjiang Crop High-yield Shihezi University Shihezi 8 department of computer science and technology Central University for Nationalities Beijing 100081 P. R . China School of computer science and technology Beijing University of Posts and Telecommunications Beijing 100876 P. R . China Institute of Crop Breeding and Cultivation/Key Laboratory of Crop Genetic (ж) Breeding Ministry of Agriculture Chinese Academy of Agricultural Sciences Beijing 100081 P. R . China

Recognition and analysis of dynamic information about population images during wheat growth periods can be taken for the base of quantitative diagnosis for wheat growth. A recognition system based on self-learning BP neural network for feature data of wheat population images, such as total green areas and leaves areas was designed in this paper. In addition, some techniques to create favorable conditions for image recognition was discussed, which were as follows: (1) The method of collecting images by a digital camera and assistant equipment under natural conditions in fields. (2) An algorithm of pixel labeling was used to segment image and extract feature. (3) A high pass filter based on Laplacian was used to strengthen image information. The results showed that the ANN system was availability for image recognition of wheat population feature.

关键词： Wheat Population Leaves areas Image recognition BP neural network

Understanding adversarial attacks on observations in deep reinforcement learning

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science china(Information sciences) 2024年第5期67卷 69-83页

作者： You QIAOBEN Chengyang ying Xinning ZHOU Hang SU Jun ZHU Bo ZHANG department of computer science and technology Beijing National Research Center for Information Science and Technology Tsinghua-Bosch Joint Center for Machine Learning Institute for Artificial Intelligence Tsinghua University Peng Cheng Laboratory

Deep reinforcement learning models are vulnerable to adversarial attacks that can decrease the cumulative expected reward of a victim by manipulating its observations. Despite the efficiency of previous optimization-based methods for generating adversarial noise in supervised learning, such methods might not achieve the lowest cumulative reward since they do not generally explore the environmental ***, a framework is provided to better understand the existing methods by reformulating the problem of adversarial attacks on reinforcement learning in the function space. The reformulation approach adopted herein generates an optimal adversary in the function space of targeted attacks, repelling them via a generic two-stage framework. In the first stage, a deceptive policy is trained by hacking the environment and discovering a set of trajectories routing to the lowest reward or the worst-case performance. Next, the adversary misleads the victim to imitate the deceptive policy by perturbing the observations. Compared to existing approaches, it is theoretically shown that our adversary is strong under an appropriate noise level. Extensive experiments demonstrate the superiority of the proposed method in terms of efficiency and effectiveness, achieving state-of-the-art performance in both Atari and MuJoCo environments.

关键词： deep learning reinforcement learning adversarial robustness adversarial attack