Spatial Data Sharing on Grid

The Internet technology has already changed the Information Society in profound ways, and will continue to do so. Nowadays many people foresee that there is a similar trajectory for the next generation of Internet - Grid Technology. As an emerging computational and networking infrastructure, Grid Computing is designed to provide pervasive, uniform and reliable access to data, computational and human resources distributed in a dynamic, heterogeneous environment. On the other hand, the development of Geographic Information System （GIS） has been highly influenced by the evolution of information technology such as the Internet, telecommunications, software and various types of computing technology. In particular, in the distributed GIS domain, the development However, due to the closed and centralized has made significant impact in the past decade. legacy of the architecture and the lack of interoperability, modularity, and flexibility, current distributed GIS still cannot fully accommodate the distributed, dynamic, heterogeneous and speedy development in network and computing environments. Hence, the development of a high performance distributed GIS system is still a challenging task.
So, the development of Grid computing technology undoubtedly provides a unique opportunity for distributed GIS, and a Grid Computing based GIS paradigm becomes inevitable. This paper proposes a new computing platform based distributed GIS framework - the Grid Geographic Information System （G^2IS）.     

Program Design of Graphic Realism Displaying System Based on DXF Lathe Turning Rotational Parts

For virtually realizing the graphic realism display of DXF machine parts, in AutoCAD2007 graphic drawing environment, an interactive experimental method was taken to realize the display of graphic in DXF, which was taken as the data-exchanged interface and source. Based on depth analysis of DXF data structure, take one drawing of DXF lathe turning rotational part asthe test piece. By VC＋＋6.0 programming, part＇s geometry information could be obtained. Through data processing, 3D data of the test piece could be generated, which is based on 2D data of DXF test piece. Then, OpenGL graphic processing technologies （light, material, texture, map, et al.） were applied on the 3D display of test piece from DXF files or program modules. Finally based on the test report, results of the system functions were shared to prove the realization of system design, and the feasibility of algorithms used. In the developed software, Machine Designers could get a full view of machine parts, and do some proper modifications. The study content and results of our work have some theory and practical significance on the application of program design in the practical projects.     

Efficient maintenance of multiple-level association rules for deletion of records

Developing an efficient algorithm that can maintain discovered information as a database changes is quite important in data mining. Many proposed algorithms focused on a single level, and did not utilize previously mined information in incrementally growing databases. In the past, we proposed an incremental mining algorithm for maintenance of multiple-level association rules as new transactions were inserted. Deletion of records in databases is, however, commonly seen in real-world applications. In this paper, we thus attempt to extend our previous approach to solve this issue. The concept of pre-large itemsets is used to reduce the need for rescanning original databases and to save maintenance costs. A pre-large itemset is not truly large, but promises to be large in the future. A lower support threshold and an upper support threshold are used to realize this concept. The two user-specified upper and lower support thresholds make the pre-large itemsets act as a gap to avoid small itemsets becoming large in the updated database when transactions are deleted. A new algorithm is thus proposed based on the concept to maintain discovered multiple-level association rules for deletion of records. The proposed algorithm doesn＇t need to rescan the original database until a number of records have been deleted. It can thus save much maintenance time.     

Dm-KDE： dynamical kernel density estimation by sequences of KDE estimators with fixed number of components over data streams

In many data stream mining applications, traditional density estimation methods such as kemel density estimation, reduced set density estimation can not be applied to the density estimation of data streams because of their high computational burden, processing time and intensive memory allocation requirement. In order to reduce the time and space complexity, a novel density estimation method Dm-KDE over data streams based on the proposed algorithm m-KDE which can be used to design a KDE estimator with the fixed number of kernel components for a dataset is proposed. In this method, Dm-KDE sequence entries are created by algorithm m-KDE instead of all kemels obtained from other density estimation methods. In order to further reduce the storage space, Dm-KDE sequence entries can be merged by calculating their KL divergences. Finally, the probability density functions over arbitrary time or entire time can be estimated through the obtained estimation model. In contrast to the state-of-the-art algorithm SOMKE, the distinctive advantage of the proposed algorithm Dm-KDE exists in that it can achieve the same accuracy with much less fixed number of kernel components such that it is suitable for the scenarios where higher on-line computation about the kernel density estimation over data streams is required. We compare Dm-KDE with SOMKE and M-kernel in terms of density estimation accuracy and running time for various stationary datasets. We also apply Dm-KDE to evolving data streams. Experimental results illustrate the effectiveness of the pro- posed method.     

Performance gain with variable chunk size in GFS-like file systems

We have designed and implemented Tianwang File System（TFS）, which is a distributed file system much like Google File System（GFS）. The system has its origins in our Tianwang search engine and web mining research work. Our system has the same assumptions and the same architectures with GFS. But the key design choice that the chunk size is variable lets our system to adopt simpler system interactions which significantly improves the performance of the record append operation. In this paper, we discuss many aspects of our design which are different from GFS, and verify their pros and cons by performance experiments. The experiment results shows that the utilization ratio of our record append operation excels GFS by 25%. And the throughput of record append of TFS is also several times better.     

Twice grid colorings in steganography

A novel method of steganographic embedding is described based on vertex colorings in the grid graph, in which rainbow coloring is repeated in every block of cover signals to increase embedding efficiency. This is an improvement of the previous grid coloring method in steganography. It also outperforms LSB matching revisited method and direct sums of ternary Hamming codes. The proposed method can generate more embedding schemes which cover the range of change rates and information rates more densely.     

A classification model based on SVM and rough set theory

This paper presents a novel classification approach based on rough set theory and supporter vector machine. Sometimes, there are many attributes for classification samples and it is difficult to carry out classification. In this paper, the attributes of data set are reduction by rough set theory firstly, and then the classification is carried out using support vector machine. Finally, the classification results are obtained through the proposed model. Moreover, the proposed classification model has higher prediction accuracy by comparing with the traditional algorithm Naive Bayes algorithm and reduces the cost of calculation.     

Platform technology of Web services-oriented DCS data exchanging

To solve the problem of information interdiction among various kinds of DCS and systems of MIS and ERP, through using a kind of universal Web services object＇s encapsulation technique, a Web services-oriented DCS data exchanging platform is constructed, and the functional architecture and Key Enabling Technologies of the platform are introduced in detail. Accordingly, the enterprise information integration across different platforms and languages is realized, and an open, unified application integration environment is provided for the heterogeneous control systems and management systems.     

A study of the employment of higher institutions based on the decision tree model

The employment of the graduates is a major index to measure the achievements of higher institutions. And the academic grades of the students at school are a very important factor in obtaining employment. In this essay, a classified model of decision tree between the grades of the graduates and their employment is established, and the model is also optimized and well researched. Therefore, this model can be a scientific and rational resource for an institution when setting up the achievement goal to increase the employment rate of the students.     

On the ?2 stability of time varying linear and nonlinear discrete time MIMO systems

New conditions are derived for the l2-stability of time-varying linear and nonlinear discrete-time multiple-input multipleoutput （MIMO） systems, having a linear time time-invariant block with the transfer function F（z）, in negative feedback with a matrix of periodic/aperiodic gains A（k）, k = 0,1, 2,... and a vector of certain classes of non-monotone/monotone nonlinearities φp（-）, without restrictions on their slopes and also not requiring path-independence of their line integrals. The stability conditions, which are derived in the frequency domain, have the following features： i） They involve the positive definiteness of the real part （as evaluated on ｜z｜ = 1） of the product of Г （z） and a matrix multiplier function of z. ii） For periodic A（k）, one class of multiplier functions can be chosen so as to impose no constraint on the rate of variations A（k）, but for aperiodic A（k）, which allows a more general multiplier function, constraints are imposed on certain global averages of the generalized eigenvalues of （A（k ＋ 1）,A（k））, k = 1, 2 iii） They are distinct from and less restrictive than recent results in the literature.     

Whitening of fractional order polynomial autoregressive Non-Gaussian impulsive stable colored noise

This paper proposes a new different spectral density from power spectrum density of second order processes, thus we can get a new concept of stable white noise based on covariation function and covariation spectrum density. And a new technique is suggested for the estimation of the parameters of polynomial autoregressive （PAR） nonlinear colored noise processes with stable white noise excitations. Simultaneously, a simple whitening method is employed for polynomial autoregressive nonlinear stable colored noise.     

Context-awareness approach in game style application

By combining training content with Game AI, Game Style Training can provide a rich, interactive and engaging educational substance. It supports experiential learning-bydoing. And it can contribute to promote interest and motivation of trainees. In this paper, a Context-Awareness Approach （CAA） is put forward for earthquake rescue training by applying the concept of ambient intelligence. The CAA takes advantage of player profile to monitor player states, utilizes time sensor and location sensor to supervise environment changes. And then, a Reinforcement Learning model based on MAS is designed to update game AI system.     

Electric Power Marketing based on intelligence decision tree and artificial Neural Network

A new method of using ANN in Electric Power Marketing is introduced in this paper. Intelligence decision tree classification algorithm is used in data preprocessing to ensure data optimization, the algorithm about hidden nodes of ANN is improving and ANN computational complexity is reduced. The experiment result indicates that ANN model has good predicting effect in electric power distribution.     

The research for the key technology of Gigbit high speed serial interface IC＇s system

In high speed serial interface integrated circuit design, the design of high speed serial data recovery circuit is a troublesome task. In this paper an all-digital high speed serial data recovery circuit module for 1.5bps SATA interface implement is introduced. Without using PLL or DLL analog circuit, this circuit is an all-digital circuit made from standard cells. In contract to other design made from analog circuit, this all-digital circuit is an easily implement design and it has lower power consumption and smaller area. This circuit is being implemented in HPT183 chip which is designed and manufactured using a 0.18um CMOS process.     

Spatial data mining and visualization based on self-organizing map

Based on the traditional spatial data analysis, a novel mode of spatial data mining and visualization is proposed which integrates the self-organizing map for the actual problem. Simulations for IRIS data show that this method （computational and visual） can collaboratively discover complex pattems in large spatial datasets, in an effective and efficient way.     

Topology control for directed diffusion in wireless sensor networks

Due to severely constrained energy, storage capacity and computing power for nodes in wireless sensor network, the routing protocols have become a hot research topic. Directed diffusion is a communication paradigm for information dissemination in sensor networks based on data-centric routing. An energy efficient hybrid adaptive clustering for directed diffusion is presented in the paper. The main goal is to curb the interests flooding overhead by clustering. Hybrid of active and passive clustering creation is used to make tradeoff between maintenance cost and delay. The adaptive turning off the radio of redundant nodes and rotation of cluster heads is used to save energy. The ns-2 simulating results show that the protocol has good performances in energy consuming, delivery ratio and delay without leading to too much overhead comparing with existing directed diffusion protocols.     

Automatic analysis of textual garden path phenomenon： A computational perspective

This paper puts forward a text-circled semantic schema by which a special flow chart of cognitive alteration and processing breakdown in Machine Translation （MT） system is clearly presented. Based on the theoretical analysis of textual Garden Path Phenomenon （GPP）, we devise a formula to measure the dramatically changeable value of textual GPP. The data-provided evidence in A Farewell to Arms shows the textual GPP can motivate the development of plots and adjust the analyst＇s original horizon of expectation. Despite the limitation of incompatible, subjective and sample-restricted features involved in the theoretical framework and formula, this computational analysis makes MT system pay more attention to text-circled cognitive alteration rather than only highlight the lexical or syntactic translation, and as a result aims to make the effectiveness of machine translation of the literary text improved.     

Maximizing Networking Capacity in Multi-Channel Multi-Radio Wireless Networks

Providing each node with one or more multi-channel radios offers a promising avenue for enhancing the network capacity by simultaneously exploiting multiple non-overlapping channels through different radio interfaces and mitigating interferences through proper channel assignment. However, it is quite challenging to effectively utilize multiple channels and/or multiple radios to maximize throughput capacity. The National Natural Science Foundation of China（NSFC） Project61128005 conducted comprehensive algorithmic-theoretic and queuing-theoretic studies of maximizing wireless networking capacity in multi-channel multi-radio（MC-MR） wireless networks under the protocol interference model and fundamentally advanced the state of the art. In addition, under the notoriously hard physical interference model, this project has taken initial algorithmic studies on maximizing the network capacity, with or without power control. We expect the new techniques and tools developed in this project will have wide applications in capacity planning, resource allocation and sharing, and protocol design for wireless networks, and will serve as the basis for future algorithm developments in wireless networks with advanced features, such as multi-input multi-output（MIMO） wireless networks.