3D Model Reconstruction Based on Process Information

The traditional strategy of 3D model reconstruction mainly concentrates on orthographic projections or engineering drawings. But there are some shortcomings. Such as, only few kinds of solids can be reconstructed, the high complexity of time and less information about the 3D model. The research is extended and process card is treated as part of the 3D reconstruction. A set of process data is a superset of 2D engineering drawings set. The set comprises process drawings and process steps, and shows a sequencing and asymptotic course that a part is made from roughcast blank to final product. According to these characteristics, the object to be reconstructed is translated from the complicated engineering drawings into a series of much simpler process drawings. With the plentiful process information added for reconstruction, the disturbances such as irrelevant graph, symbol and label, etc. can be avoided. And more, the form change of both neighbor process drawings is so little that the engineering drawings interpretation has no difficulty; in addition, the abnormal solution and multi-solution can be avoided during reconstruction, and the problems of being applicable to more objects is solved ultimately. Therefore, the utility method for 3D reconstruction model will be possible. On the other hand, the feature information in process cards is provided for reconstruction model. Focusing on process cards, the feasibility and requirements of Working Procedure Model reconstruction is analyzed, and the method to apply and implement the Natural Language Understanding into the 3D reconstruction is studied. The method of asymptotic approximation product was proposed, by which a 3D process model can be constructed automatically and intelligently. The process model not only includes the information about parts characters, but also can deliver the information of design, process and engineering to the downstream applications.     

Finite Element Analysis of Steam Turbine Diaphragm

Thediaphragmofsteam turbine isoneofthemainpartsofthepassageunitfor air flowing.For studying its working conditionand performance, the three-dimensionalfinite element model（FEM）with thesoftware ANSYS10.0 isestablished according to theactualworking parameters. With the model, the deformation resultsand stress field resultsare analyzed andthe maximum displacement and stress value are calculated, meanwhile,theircorrespondingpositions are found. It provides a good foundationfor solving the problem inproduction.     

Read-write rule property research of the combined function about the confidentiality and integrality

Read-write rule about the combined function at the article function will be discussed in this paper. There are some good properties about the function, and its read-write rule is a read-write rule expansion of BLP model and Biba model by analysis in this paper.     

Study of Lyapunov exponent spectra for axial-flow compression system

The Lyapunov exponent spectra of the axial-flow compression system＇s Moore-Greitzer model was researched with chaos theory. When the parameter B of the MG model is greater （surge） or smaller （stall）, the system＇s Lyapunov exponent spectra are all （0, -）. So the compressor＇s working points are all on a limit circle, when the compressor is in the state of surge or stall. When the compressor is surge, it can come into a full limit circle, but in the stall, it can not. The conclusion was applied to detect the stall of the compressor. The numerical experimentation results demonstrate that the method can exactly detect the stage of the first stall before the start of deep rotating stall.     

Process parameters selection of fluid industry based on flexible neural trees

Fluid industry＇s production takes on high complexity, strong association, non-linear and indeterminacy. To find important parameters which influence production process, provide theoretical basis for process control of fluid industry＇s production and make the production process control more exact, we propose a flexible neural tree model in this paper. The model can be created based on predeflned information set. The structure and parameters of flexible neural tree are optimized by probabilistic incremental program evolution and simulation annealing respectively. We take production process of decomposed kiln---one of important cement＇s processes---as an example. The result indicates that the proposed model is greatly efficient.     

An efficient visual tracking method for multiple moving targets

An efficient algorithm of the edge detection according to integrating the edge gradient with the average filter is proposed, which can significantly reduce sensitivity of the background subtraction method to noise and illumination. Taking into account the features of the target such as color, size, etc., a new modified Nearest Neighbor （NN） algorithm for data association using the target features is designed. A designed Interacting Multiple Model （IMM） filter is utilized to track the maneuvering target motion, i.e. the feature point （called the centroid of the target） motion of the target. The algorithms are validated via an example with natural video sequences. The results show the algorithms are performances and validity for visual tracking. In complex environment, the algorithm can still work well.     

An adaptive image watermarking algorithm based on perceptual model

An adaptive image watermarking algorithm based on Watson＇s perceptual model is proposed in this paper. The proposed watermarking algorithm fully considers image regional characteristic. First, the cover image is divided into different smooth regions according to its gray value. Then watermark adjustment factors of those different regions are calculated respectively based on Watson＇s perceptual model. The watermark is embedded by the adjustment factors at last. Experiments show that the proposed algorithm has excellent imperceptibility and has little influence upon the eigenvalue of the cover image.     

A new theory branch for finance market study —Computational experimental finance review and synthesis

This paper provides a detailed synthesis of the computational experimental finance from four parts. （i）its theoretical basis-CAS （Complex Adaptive System） theory, （ii） the approach and method used for financial market study, （iii） research results-a number of valuable literatures review （iv） the existing problems and further research directions of this subject. Based on the challenge to the standard finance theory, the computational experimental finance is an exciting new field because it integrates CAS theory with computer technology and intends to reveal the macroscopic features of finance market from the penetration of the microscopic behaviors of investors by constructing the agent-based artificial financial market model The synthesis has prevalent meaning of guidance for new researchers allowing them to learn systematically more about the computational experimental finance.     

Smart assistive reminder for elders with memory decline

Most elders suffer from different levels of memory decline, from severe to mild. For supporting the independent living and providing the smart services to the elders, assistive reminder technology has been proposed as a promising approach to address these challenges, which are able to provide necessary help to elders in appropriate time. This paper investigates the smart assistant technique. We propose a user behavior model to describe activities of the forgetful elderly. Based on this model, we develop a smart assistive reminder, which provides reminders according to elders＇ practical needs, and avoids unnecessary notifications that will disrupt the elders＇ life. The preliminary experiments evaluate the effectiveness of our approach.     

A Multi-Agent Resource Selection Model in Manufacturing Grid Environment

A group of agents are intimately cooperated to set the assessment indices, establish the weight of each index in overall result of evaluation, collect the experts＇ scores given to each available resource, and the manufacturing resource whose overall assessment value is highest is taken as the optimal choice. Architecture of the proposed system is outlined and an example is offered to show the process of accomplishing the assessment.     

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.     

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.     

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.     

DNA-chip-based dynamic broadcast encryption scheme with constant-size ciphertexts and decryption keys

In this paper we present DNA-DBE,a DNA-chip-based dynamic broadcast encryption scheme.In our scheme,new users can join dynamically without modification of other users’decryption keys.Either the ciphertext or the decryption key is of constant-size.Backward secrecy is achieved in DNA-DBE:if new users join the system dynamically,they will not be able to retrieve past data.The security of our scheme relies on hard biological problems,which are immune to attacks of new computing technologies in the future.There exists a special feature in DNA–based cryptosystems,i.e.the set of encryption keys and the set of decryption keys have a many-to-many relationship.The implementation of more complicated DNA cryptosystems taking advantage of this special feature has been previously left as an open problem.Our DNA-DBE system is a solution to this open problem,which is also the first exploration of DNA based group-oriented encryption system.     

Solving Strategy for Repetitious Simulation of Multi-domain Physical System Based on Modelica

Repetitious simulation after modifying parameters of multi-domain physical system based on Modelica often appears in model experiment and optimization design. At present, the solvers based on Modelica need calculate all the coupled blocks during every simulation run after updating parameters. Based on discussing scale decomposition methods of simulation model, subdivision solving strategy and minimum solving strategy are put forward to improve the efficiency of repetitious simulation, by which the numerical solution of the simulation model can be achieved by only calculating the solving sequence influenced by altered parameters. A simplified model of aircraft is used to demonstrate the efficiency of the strategies presented.     

Towards the processing breakdown of syntactic garden path phenomenon： A semantic perspective of natural language expert system

Processing breakdown involved in garden path phenomenon is a special phenomenon in which the processor has to backtrack on the early understanding and create another path out to process data successfully and perfectly. From the semantic viewpoint of Natural Language Expert System, this paper puts forward a particular schema by which processing procedure of breakdown can be shown clearly and raises a special matching pattern to demonstrate the activity of noun-verb category. According to the analysis of interactive presentation of same word in which noun and verb definitions are involved, it is verified that Natural Language Expert System, only when its semantic database is activated, can clear the misunderstanding of syntactic sentences in which processing breakdown appears.     

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.     

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.     

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）.     

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.