bluuebunny/crossref_metadata_2025 huggingface dataset:
Temperature and Humidity Measurement Based on Wireless Sensor Network Technology
Authors: Chen Xiao
Published: June 2010

To overcome the shortcomings of wired temperature and humidity measurement system, a temperature and humidity measuremet system based on wireless sensor networks was designed. the components of the system and its working principle were described in detail. Its nodes use a digital temperature and humidity sensor SHT15 for data collection, wireless transmission chip CC1100e for data short-range wireless transceiver and the wireless network, and AT89S52 microcontroller for controlling core. Nodes communicate with the background host through serial interfaces. The system can achieve environmental temperature and humidity dynamically and comprehensive real-time monitoring. Node has a dual function as terminals and routers, in addition to data processing, but also for other nodes to forward the temperature and humidity data storage, management, and integration, and taking in collaboration with other nodes to complete some specific tasks. The system has some advantages such as low cost, low power consumption and small size, which has a good application prospects.
Research on System Safety Assessment Based on Optimized BP Network
Authors: Xia Jin Hua , Liu Dong Rong
Published: June 2010

The safety assessment of the production process can provide scientific basis for management decisions. The application of neural network theory in system safety assessment can overcome some traditional deficiencies of traditional safety assessment methods and arrive at accurate assessment result. The paper introduced Genetic Algorithm (GA) into the optimization of BP algorithm, which use GA to optimize the weight and threshold of BP and then utilize BP network to seek for exact solution, so that the target of global optimization and fast efficiency can be achieved. Based on this, the GA optimized neural network was applied in the system safety assessment, and the assessment model based on the algorithm was proposed. The example to verify the effectiveness of GA optimized BP algorithm was also provided.
A Kind of Hierarchical K-Means Web Log Clustering Algorithm
Authors: Liu Li Xia , Zhuang Yi Qi
Published: June 2010

Clustering techniques are often used in Web log mining to analyze user’s interest on the web pages. Based on the analysis of advantages and disadvantages of the application of classic clustering algorithm in Web log data mining, the paper brought out a kind of hierarchical K-means Web log clustering algorithm, which integrated K-means clustering algorithm and cohesion-based hierarchical clustering algorithm and overcame shortcoming of high time complexity of hierarchical clustering algorithm. The clustering effect of the algorithm is better than K-means clustering and fit for clustering process of large amount data. The result analysis of practical Web log data clustering also proves the validity of the algorithm.
An Embedded Multi-Phase Tactic of Scheduling Autoimmunization for Complex Correlated Production System
Authors: Luo Ya Bo , Tang Ming Chun
Published: June 2010

The schedule for job shop system involving the complex correlated constraints is a complex combinatorial optimization problem, for which currently there is no a methodology claiming to have capability to find the optimum solution. Current research concentrate on the search of acceptable feasible solutions. This research proposes an embedded multi-phase methodology to find the acceptable feasible solutions in a higher efficiency. The thinking of the methodology is to decompose the complex optimization problem into two sub problems of the operation sequence and the machine allocation to lower the complexity of the scheduling system and improve the searching efficiency. The two sub problems are solved orderly respectively, and the results of the first sub problem are embedded into the second sub problem as the original values of design variables. Thus these two sub optimization problems are integrated into a searching loop to ensure the feasibility of solution and improve the searching efficiency in the complex correlated system.
Assessment on Logistics Outsourcing Risk Based on Rough Set Theory and Unascertained Measure Model
Authors: Jiang Hua , Zhao Shuang Lin
Published: June 2010

In recent years, logistics outsourcing has gained increasing importance and today is used by a large number of firms across virtually all industries worldwide. However, while logistics outsourcing brings enterprises economic benefits, it also brings in a lot of potential risks. It has an utmost significance to strengthen the identification and assessment of logistics outsourcing risks. The paper applies unascertained measure model to analyze and assess logistics outsourcing risks, which provides a new way to assess the risks of logistics outsourcing and is helpful for enterprises’ decision-making. Lastly, according to analysis results, the paper proposed aversion strategies for logistics outsourcing risks.
Environmental Influence Assessment of Thermal Power Plant Based on Entropy and Fuzzy Optimal Model
Authors: Huang Yuan Sheng , Shi Xiu Fen , Yuan Li Ming
Published: June 2010

The prevention of environmental pollution is an important work and an assessment indicator for thermal power enterprises,it is also the key factor for sustainable development.This paper presents a new qualitative analysis method for thermal power enterprises to analyze its environmental impact. It takes four thermal power units for example, uses entropy method to determine the weight values of indicators, and filter the indicators based on the size of the values. For the characteristic matrix of the remaining evaluation indexes, it uses multi-objective fuzzy optimization model to transform the absolute amount of the indicator values into the relative amount ones, then it calculates the positive ideal distance and negative ideal distance of each evaluation object, and ranks them based on the plus menbership grade maximal principle. The positive analysis result shows that this method has a strong practical significance, it provides a more reliable evaluation method for environmental protectors.
Discrete Differential Evolution Strategy and its Numerical Application
Authors: Zhang Ming Ming , Zhao Shu Guang , Wang Xu
Published: June 2010

Differential evolution is a simple but powerful parallel global search optimization algorithm, which has been successfully used to solve single-objective optimization problems. In this paper, a novel discrete differential evolution strategy (D2E) is proposed to enhance the ability of solving the numerical optimization problems. D2E adopts the difference information from the binary evolutionary individuals and self-adaptive parameter adjustment to effectively explore the global solution space. The results of numerical simulations demonstrate that the proposed strategy is feasible and efficient, has the better metrics performances.
Target Detection and Tracking Based on Ship Borne Infrared Imagery
Authors: Hu Wen Hua , Xu Kai Yu , Shi Chao Jian
Published: June 2010

A novel automatic target detection and tracking algorithm for tracking targets based on ship borne infrared imagery is proposed in this paper. The algorithm has two modes: detection and tracking. In detection mode, the proposed algorithm utilized difference between the consecutive frames and top-hat filter to determine the target position. In tracking mode, the Intensity Variation Function (IVF) is utilized. Before tracking and location the new position, the algorithm should determine the IVF whether reliable. If unreliable, the mode turns to detection. Experimental results by using real-life infrared image sequence are shown to validate the robustness of the proposed technique.
A Novel Defect Evaluation Method for Concrete Structures in Infrared Based on ANN and PSO Algorithm
Authors: Liang Ben Liang , Tian Ye
Published: June 2010

Abstract: The defect of concrete structures on material level can be expressed by defect depth and defect range. Infrared thermal imaging technology of concrete material defect detection is actually an inverse problem of heat transfer. On the basis of the current research achievements, infrared thermal imaging methods used in concrete structure defects was deduced to a multi-objective function optimization problem. Considering the traditional optimization algorithm slow convergence speed and local minima faults, this paper introduce particle swarm optimization algorithm (PSO) and the BP neural network to detect concrete material defect depth and range.PSO algorithm was used to optimize neural networks connection weights between layers and the network topology. The simulation test results are in good agreement with the experiment results and verify the validity of this method.
An Improved Ant Colony System Based on Negative Biased
Authors: Yang Jin Qiu , Yang Jian Gang , Chen Gen Lang
Published: June 2010

Ant System (AS) was the first Ant Colony Optimization (ACO) algorithm, which converged too slowly and consumed huge computation. Among the variants of AS, Ant Colony System (ACS) was one of the most successful algorithms. But ACS converged so rapidly that it always was in early stagnation. An improved Ant Colony System based on Negative Biased (NBACS) was introduced in the paper to overcome the early stagnation of the ACS. Experiments for Traveling Salesman Problem (TSP) showed that better solutions were obtained at the same time when the convergence rate accelerated more rapidly.
Tested and Modeled Relationship between Curing Time and Cube Compressive Strength of Recycled Aggregate Concrete
Authors: Zhang Zheng Wen , Wang Wei , Ma Li Sha , Wang Huan Li , Pan Gao Jie , Zhang Shuai
Published: June 2010

Abstract. Recently, more and more concrete structures are demolished and rebuild, and a large amount of demolished concretes are reused as materials for recycled aggregate concrete (RAC). It is very important to correctly describe time-dependent compressive strength of RAC before the design of corresponding RAC structures. In this paper, compressive strength tests of RAC with different curing times are conducted, and a new three-parameter mathematical model for time-strength curve is presented according to exponent function. Approaches to determine parameters of the proposed model are presented based on characterized points of tested time-strength curve. Finally, good agreements have been found between tested data and new model fittings. The result of this paper is helpful to the numerical analysis and practical engineering design of RAC structures.
Agricultural Policy-Oriented Ontology-Based Semantic Information Retrieval
Authors: Zhu Hong Mei , Liang Yong Quan , Tian Qi Jia , Ji Shu Juan
Published: June 2010

Research on architecture of ontology-based information semantic representation and Retrieval is done. As a case study, a prototype for agricultural policy-oriented ontology-based semantic information retrieval system (APOSIRS) is established. Ontology plays a role that providing a shared terminology and supporting for the retrieval process. The architecture allows APOSIRS-based applications to perform automatic semantic information Retrieval of agricultural policy text at more length: automatic and dynamic semantic annotation of unstructured and semi-structured content, semantically-enabled information extraction, indexing, retrieval, as well as ontology management, such as querying and modifying the underlying ontology and knowledge bases. Main components of this architecture have been implemented and their results are reported.
Research and Exploration of Volterra Series on Nonlinear System Identification and Modeling
Authors: Chen Y.
Published: June 2010

With the development of analysis and identification way to nonlinear dynamic system, people uses many different method to build up mathematics model to simulate nonlinear dynamic system. This paper introduces some important nonlinear system identification ways and a kind of Volterra series expression type in detail. This kind of way adopts Hilbert reproducing kernel method to build up nonlinear dynamic system model. Hilbert space provides a kind of effective expression type for Fourier series and transfer based on anyorthogonal polynomial. Volterra series function has very strict theory basic, which can be applied into many nonlinear dynamic system analysis and identification filed, and has broad practicality and application prospect.
A New Chaos Optimization Algorithm and its Application
Authors: Lu Li Fen , Xiu Chun Bo
Published: June 2010

In order to avoid blind searching before reducing the searching space of optimized variable and enhance searching efficiency in chaos optimization algorithm, a new mutative scale chaos optimization algorithm, Probability Chaos Optimization Algorithm (PCOA) was proposed. The current searching space is searched according to large probability and the origin space is searched according to small probability. Though the searching space is shrunk prematurely, the global optimal point can be found because the origin space is still searched according to small probability, which can overcome the shortcoming of losing the global optimal points owing to prematurely shrinking the searching space of the optimized variables in conventional mutative scale chaos optimization algorithm. The simulation results prove the validity of the algorithm.
Design of RBF Neural Networks Based on Adjustable Radius
Authors: Liu Xiao Yong
Published: June 2010

In this paper, a new RBF neural network (RBFNN) algorithm, called ar-RBFNN, is presented. In traditional RBFNNs based on clustering algorithm, called oRBFNN in this paper, the width of the basis function-Gaussian function, or called radius, ignored the effect of numbers in different clusters, or density of data points. New algorithm considers radius is effect to performance of algorithms in problem of function approximation. Mean Square Error is used to evaluate performances of two algorithms, oRBFNN and ar-RBFNN algorithms. Several experiments in function approximation show ar-RBFNN is better than oRBFNN.
An Improved Model for OD and Object Description in Fieldbus Intelligent Instruments Based on Object-Oriented Design
Authors: Liang Geng , Li Wen , Bai Yan
Published: June 2010

At present, objects dictionary (OD) and object descriptions used in fieldbus intelligent instruments are based on variable-sized storage and constant property values, which constrains the flexibility and portability in data access and modularization and encapsulation in system design. In this paper, a kind of universal data structure for object description in OD was presented. Universal management of object description with different types could be realized with the proposed structure. Based on principle and methodology of Object-Oriented Design (OOD), an improved model for object description was proposed. In the improved model, constant value used in object code field of object description is replaced by function pointer pointing to object instance handler for data process of object instances belonging to the same class. Universal function structure is used for all class object instance handlers for different classes but instances belonging to different classes are manipulated differently with their own handlers. The improved model for OD and object description was proven effective and efficient by the practice of development and design of intelligent instruments in distributed control network.
Fault Diagnosis of Rotating Machinery Based on Empirical Mode Decomposition and Fractal Feature Parameter Classification
Authors: Huang Jiang Tao , Cao Xiao Wen , Li Wu Jin
Published: June 2010

Rolling bearings are vital elements in rotating machinery and vibration signal is a kind of effective mean to characterize the status of rolling bearing fault. This paper presents a novel intelligent method for fault diagnosis based on empirical mode decomposition, fractal feature parameter extracting and orthogonal quadratic discriminant function classifier. The new method consists of three steps. Firstly, with investigating the feature of impact fault in vibration signals, the raw vibration signals are decomposed into intrinsic mode functions by empirical mode decomposition. Secondly, using the method of time sequences fractal dimension calculating, fractal feature parameters are extracted from intrinsic mode functions. Then, each raw signal sample has a feature set. Finally, training set and testing set are inputted into the orthogonal quadratic discriminant function model in the classification phase to identify different abnormal cases. The proposed method is applied to the fault diagnosis of rolling element bearing, and the test results indicate that the novel intelligent diagnosis method is sensitive to fault severity and capable of fault detection and fault diagnosis.
Recovering one Missing Element at a Time in SFM under Occlusion
Authors: Wang Jia Zhuo
Published: June 2010

When there is occlusion, the measurement matrix collecting trajectories of features points in SFM would be incomplete. In this paper, we have presented a method to recover missing elements in an incomplete measurement matrix one by one. We also discussed the concept of Relevance between a target missing element and its relevant known elements, and a measurement matrix transformation process, utilizing in determining the order of the recovery of missing elements. Experiments on both synthetic and real data showed that our method work efficiently.
Fractal Properties of Financial Time Series
Authors: Zhang Hong , Dong Ke Qiang
Published: June 2010

In this paper, we analyze the stock of Nanjing Panda Electronics Co Ltd for the 44-year period, from May 2, 1996, to October 9, 2009, a total of 3200 trading days. Using the Box-counting dimension method, we find that the financial data have different power law exponents in the plot for the number of box and diameter of box, which indicates the multifractality exist in the time series. In order to investigate the latent properties in the data, the width and maximum of the singular spectrum are calculated. The results show the strong degree of multifractality in the time series.
Study on Numerical Methods for Acoustic Radiation of Open Structure
Authors: Li Li Jun , Gang Xian Yue , Li Hong Yan , Chai Shan , Xu Ying Zi
Published: June 2010

For acoustic radiation of open thin-walled structure, it was difficult to analyze directly by analytical method. The problem could be solved by several numerical methods. This paper had studied the basic theory of the numerical methods as FEM (Finite Element Method), BEM (Boundary Element Method) and IFEM (Infinite Element Method), and the numerical methods to solve open structure radiation problem. Under the premise of structure-acoustic coupling, this paper analyzed the theory and flow of the methods on acoustic radiation of open structure, including IBEM (Indirect Boundary Element Method), DBEM (Direct Boundary Element Method) coupling method of interior field and exterior field, FEM and BEM coupling method, FEM and IFEM coupling method. This paper took the open structure as practical example, and applied the several methods to analyze it, and analyzed and compared the several results to get relevant conclusions.
A New Similitude Analysis Method for a Scale Model Test
Authors: Gang Xian Yue , Wang Deng Feng , Su Xue Jun
Published: June 2010

The scale models are usually tested to study the dynamic characteristics of large structures or micro-electromechanical systems. Dimensional analysis, as a classical similitude analysis method, because of the uncertainty of the basic vector of solutions, is a trial-and-error approach greatly depended on experience. Based on the finite element method (FEM) and frequency response function (FRF) analysis, a new method was proposed to quantitatively analyze the similitude of the model parameters and the FRF between the full size model and its scale model. And the load scale rules were established to predict the static or dynamic response characteristics of the actual structure.
Networked Optimal Decision Support System for Cutting Parameters
Authors: Yan Chun Ping , Zhou Qing Hua , Wang Qi Feng , Liu Fei
Published: June 2010

The real-time, the consistency and the accuracy of information transmission in cutting process are poor, and it is hard for manufacturing enterprises to enhance the machining efficiency and quality. Consequently, based on the real-time dynamic environment of cutting system and oriented to first-line production and operating workers, a networked optimal decision support system for cutting parameters was constructed; its system structure and function structure were described and its running mode was analyzed likewise. On the basis of research on the normative description of cutting process knowledge, an ontology-based description method of cutting process knowledge was proposed.
Using ANP to Do the Information Personnel Evaluation
Authors: Wei Jin Yu , Li Xin , Bi Ran
Published: June 2010

Information technology develops faster and faster, while the information talent have become more important than ever. The Analytic Network Process (ANP) was used in the paper for evaluation of the information personnel. ANP is a feedback and interdependence process developed on the basis of AHP and the SD software was used to calculate the ANP model. Evaluation results obtained in the paper can give suggestions to decision makers.
Evaluation of the Environmental Logistics Performance Based on the Analytic Network Process
Authors: Wei Jin Yu , Yuan Ting , Bi Ran
Published: June 2010

Environmental logistics was paid great attention as the results of the rapid developments of society and economy, and threats of the materials and environment. Many experts have studied the environmental logistics, but few of them do evaluation on it. This paper built a reasonable index system and used the decision-making method ANP to improve the traditional evaluation method. The ANP is a method with dependence and feedback and was done in the paper by using the Super Decisions software, the report of which can do a favor for the related decision-makers.
The Research on Human Resource Management Based on Fuzzy ANP
Authors: Wei Jin Yu , Li Xin , Bi Ran
Published: June 2010

Human resource management's objective, is to maximize the return on investment from the organization's human capital and minimize financial risk. The position of it is more and more important in modern society. This study introduced an effective method to evaluate factors that effect on human resource management. Fuzzy ANP method was introduced in detail, and it was used to compute the weights of each factor of the model.
The Application of ANP in the Trust Relationship in Supply Chain Partnership
Authors: Wei Jin Yu , Yan Xiao Min , Bi Ran
Published: June 2010

Companies set the highest standards of working together throughout the supply chain to create value and sustainable competitive advantage. Trust plays a most important role in the cooperation of supply chain. This study provided an effective method to evaluate the priorities on factors for partnership in supply chain. The factors which affect the trust partnership were setup and an evaluation model was built. Analytic Network Process was used to compute the priority of factors.
An Analysis on the Relationship between R&D Input and Patent Output in Chinese Software Firms
Authors: Ye Tao , Qing Zhou
Published: June 2010

The relation between R&D input and patent output in Chinese software firms is empirically analyzed. Estimations from both time series data and cross-section data show that there is a significantly causal and quantitative relation between the R&D input and the patent output in Chinese software firms, and the R&D input has leg effects on the patent output. By calculating the output elasticity it is found that Chinese software firms have stepped into the era of knowledge economy, but their human capital remains homogenous. From the composition of the source of R&D capital input it is inferred that in the macro level market-demand has become a major source of these firms’ technological innovations.
Channel Estimation Based on Interpolation in OFDM System
Authors: Cui Yue Hua , Ye Shuang , Wu Qiu Rui , Liu Jian Hua , Dai Yan
Published: June 2010

OFDM（Orthogonal Frequency Division Multiplexing）is a new modulation technology, which can reduce multi-pass interference efficiently. It splits a high-rate data stream into a number of lower-rate data streams which can be transmitted simultaneously over a number of subcarriers. It brings high spectral efficiency. In this paper, we first introduce the channel estimation algorithm based on comb-pilot in OFDM system, and emphasis on analysis and comparison of the three kinds of interpolation methods: linear interpolation, low-pass interpolation and transform-domain interpolation. We use MATLAB to carry out the system simulation, and its results indicate that: The performance of low-pass interpolation is the best ,but it’s hard to carry out; transform-domain interpolation’s performance and complexity are both between above two methods.
A New Congestion Controller for Multilayer Networked Control Systems with Persistent Disturbances
Authors: Liu Peng
Published: June 2010

In this paper, a new congestion controller is developed to obtain a feedforward and feedback optimal control for networked control systems (NCS) with persistent disturbances. The disturbances have known dynamic characteristics but unknown initial conditions. The disturbance observer is proposed to make the feedforward control law realizable physically. In the approach only the non-linear compensating term, solution of a sequence of adjoint vector differential equations, is required iteration. By taking the finite iteration of non-linear compensating term of optimal solution sequence, a suboptimal control law for NCS with time delay can be obtained.
A Hybrid Model of Neural Network and Grey Theory for Air Traffic Passenger Volume Forecasting
Authors: Zhang Yan , Zhang Jun
Published: June 2010

Chinese air traffic passenger volumes have experienced phenomenal growth during the past years. The air traffic volume prediction plays a key role in air traffic flow management system. This paper develops a hybrid model of Neural and Grey Theory for air traffic passenger volume forecasting. The Grey theory is adopted to fit the air traffic data patterns and make the data a higher regularity, and Radical basis function is combined to raise the forecasting accuracy. The model is tested with the Chinese civil aviation passenger volume data from 1998 to 2007 and the result shows that the model is feasible for practical implementations.
A Circular Interpolation Algorithm for NC Machining Trace Control Based on Angle Approximation Theorem
Authors: Chen Shu Fa , Li Zong Ling , Han Fu Shan
Published: June 2010

. DDA（Digital Differential Analyzer）circular interpolation algorithm is often applied to NC（Numerical Control） machining trace control, due to the greater error accumulation in DDA interpolation algorithm, the maximum feed speed of machine tool is limited, and the interpolation algorithm is hardly satisfied with the requirements for high-precision and high-speed machining. To solve this problem, a new circular interpolation algorithm based on the angular approximation method was proposed, the fundamental rule, calculation program and calculating process were introduced, and then, this interpolation algorithm was compared with the other DDA interpolation algorithm in error accumulation. It is concluded from comparative analysis and practical application that the new interpolation algorithm does not exist any accumulative error in the speed and outline, the interpolation error is little, the algorithm is simple and easy to be realized as well.
FEM Simulation of the Effects of Residual Stress on Deformation of Gyroscope Frame
Authors: Zhan Jun , Chen Gui Min , Liu Xiao Fang , Liu Qing Jie , Zhang Qian
Published: June 2010

Gyroscope is the core of an inertia system and made by machining process. Machining process imports large residual stress. The residual stress will be released and induces large deformation of gyroscope frame. In this paper, the effects of residual stress on deformation of gyroscope frame were simulated by finite element method. Different stress distribution leads different deformation. Compressive stress can make sample long and tensile stress make sample short. The stress released in deformation process which reduced about 90%.
Long-Term Power Load Forecast Based on Improved BP Neural Network
Authors: Li Shuang Chen , Yuan Di
Published: June 2010

This article proposed the improvement BP algorithm which solved the neural network to restrain slow and easy well to fall into the partial minimum the question, through setup time sequence forecast model made the long-term power forecast, and made a comparison with the traditional BP natural network.
Parameter Identification of Heavy Commercial Vehicle Rollover Prediction Model
Authors: Zhu Tian Jun , Zong Chang Fu
Published: June 2010

This paper presents the parameter identification technology of heavy commercial vehicle rollover prediction. In this study, a nonlinear truck model has been established for the rollover threat prediction. In order to achieve valid and representative truck model as close to the target real truck as possible, a set of key parameters are identified from experiment data collected from real truck ground test. At the last, the vehicle prediction model simulation results compared with the experimental results, it is shown that the prediction model can be accurately predicted the rollover dangerous state.
Idle Users Management for Improved BitTorrent Performance
Authors: Zhang Ming , Yang Jin Qiu
Published: June 2010

In the past few years, there have been tremendous interest in the peer-to-peer(P2P) content delivery. This communication paradigm dramatically increases the traffic over inter-ISP links. In particular, BitTorrent(BT), the most popular P2P application, generates a huge amount of traffic on the Internet.
BitTorrent’s performance is limited by the fact that typical internet users have much lower upload bandwidths than download bandwidths. This results in the overall average download speed of a BitTorrent-like file download system to be bottle-necked by the much lower upload capacity. We think about to utilize idle users’ spare upload capacity to largely improve the download speed beyond what can be achieved in a conventional BitTorrent network. In this paper, we design a system that is completely compatible with the already existing clients who conform to the BitTorrent protocol, at the same time, we analyze this system’s steady-state performance and present simulation results.
Parallel Fast Multipole BEM of Strip Cold Rolling Process
Authors: Gui Hai Lian , Huang Qing Xue
Published: June 2010

In order to improve the efficient and accuracy, parallel algorithm of fast multipole boundary element method (FM-BEM) was presented. Combined with sparse approximate inverse preconditioning (SPAI), GMRES(m) was used to solve the equation system of FM-BEM. The parallel FM-BEM was applied to strip cold rolling process, the results obtained from parallel FM-BEM was similar with the experimental measurements. The parallel FM-BEM has more efficient and accuracy than traditional FM-BEM. This method is benefit for solving precision engineering problem.
An Efficient Searching Scheme in Unstructured P2P Networks
Authors: Zhang Ming , Yang Jin Qiu
Published: June 2010

Unstructured peer-to-peer (P2P) systems，due to their excellent support for content lookup and sharing，are creating a large proportion of network traffic in today’s Internet. A P2P system typically involves thousands or millions of live peers in the network. In this paper, we propose and evaluate an efficient searching scheme in unstructured P2P networks. This scheme proposes a local adaptive routing protocol. This routing protocol adopts a simple scheme which driven by query interest among peers. We analyze this scheme’s performance and present simulation results. Our simulation results demonstrated the benefits of the proposed system and show that the approach is able to dynamically group nodes in clusters containing peers with shared interests, at the same time, and organized into a community network.
An Adaptive Partitioned Algorithm Based on Mean Coding and Vector Quantization
Authors: Gu Mei Hua , Yu N.M. , Wang De Fa
Published: June 2010

A hybrid algorithm based on mean coding and vector quantization is presented in this paper. The smooth image block is coded with the mean coding algorithm, which can reduce the vector quantization (VQ) search computation and improve the compression ratio effectively, and this method is called the basic blended algorithm (BBA). On this base, an adaptive partitioned algorithm (APA) algorithm based on 16×16 pixels image block is proposed, the optional image block sizes are 16×8, 8×16, 8×8, 8×4, 4×8, 4×4 pixels, the image is coded adaptively at different levels. The size of mean coding is chosen adaptively according to the size of the smooth image block, the Not-smooth 4×4 pixels image block is coded by VQ. In addition, the improved APA (IAPA) is also given in this paper. Simulations show that the APA and IAPA proposed in this paper are proven to have great performance for different kinds of images, especially significant for those have large areas of static background and little details. Compared with BBA, the compression ratio of APA and IAPA can be improved by 416% and 512%, the PSNR of APA and IAPA is reduced only 2.4% and 3.6%, the complexity can be reduced significantly, which is of advantage to hardware implementation.
Change Detection of the Eastern Reserve Wetlands after the Yellow River Resumed its Normal Runoff
Authors: Liu Yan Fen , Zhang Jie , Ma Yi , Kai Shan , Jin Xiao Hua
Published: June 2010

In this paper, wetlands landscape pattern dynamic changes were investigated in the eastern Yellow River Delta National Nature Reserve by the combination use of satellite remote sensing and geographic information systems. The main objective of this study was to determine the variation characteristics and reasons of the reserve wetlands since the Yellow River resumed its normal runoff from 2001 to 2008. Results showed that the reserve wetlands were mainly composed of the natural wetlands and the constructed wetlands, while the proportion of the later was very less. The amount of the wetlands increased 91.510 km2 in total from 2001 to 2008, although there was a little decrease about 7.569 km2 from 2001 to 2004. Among these types of wetlands the bare muddy tidal flat, the estuarine waters and the palustrine wetlands had a relatively significant change. Through transformation analysis between the above three types and the others, we can conclude that there are two major factors affecting the reserve wetlands landscapes: Firstly, the changing condition of Yellow River water and sediment, and secondly, the increasing human activities.
The Decription of a Sort of Two-Directional Biorthogonal Trivariate Wavelet Packets with Finite Support
Authors: Chen Qing Jiang , Yan Lie Ya
Published: June 2010

The advantages of wavelets and their promising features in various application have attracted a lot of interest and effort in recent years. In this article, the notion of two-directional biorthogonal finitely supported trivariate wavelet packets with multiscale is developed. Their properties is investigated by virtue of algebra theory, time-frequency analysis method and functional analysis method. In the final, new Riesz bases of space are constructed from these wavelet packets. Three biorthogonality formulas regarding these wavelet packets are established
Characters of Two-Directional Compactly Supported Bivariate Wavelet Packets
Authors: Sheng Zong Sheng , Du Shu De
Published: June 2010

Wavelet analysis has been a powerful tool for exploring and solving many complicated problems in natural science and engineering computation. In this article, the notion of biorthogonal two-direction compactly supported bivariate wavelet packets with polyscale is developed. Their properties is investigated by algebra theory, means of time-frequency analysis methodand, operator theory. The direct decomposition relationship is provided. In the final, new Riesz bases of space are constructed from these wavelet packets. Three biorthogonality formulas regarding these wavelet packets are established.
Key Factors Effect on Vehicle Braking Performance Based on Nonlinear 3DOF Vehicle Dynamic Model
Authors: Zhang Li Jun , Wang Rui
Published: June 2010

3DOF nonlinear braking dynamic model considering tire-road adhesion characteristics was established, and non-dimensional equations were gained from the above mathematic models by using braking torque coefficient, front and rear axle equivalent inertia coefficients and braking force distribution coefficient. Based on the numerical calculation in Matlab-Simulink software, the effect of key factors, (including vehicle mass and vehicle gravity center position variation, frontal and rear braking force distribution coefficient, and frontal and rear axle inertial variation caused by driven mode) on vehicle braking performance, such as braking distance and wheel lockup status, was investigated and summarized. Several 3D visualizations of the simulation results show that variation of vehicle center of gravity, vehicle mass, braking moment distribution, wheel equivalent inertia due to driveline, can cause quite complex effect. It can be assumed that the gained results in this study can help to improve vehicle braking performance and enhance braking stability.
Effect of Heat Modification and Biofilm on Zeolite Adsorption Properties
Authors: Long Hong , Zuo Jin Long
Published: June 2010

In order to improve ammonia removal capability from wastewater, zeolite was modified with heat and biofilm in this paper. The results showed that the adsorption capacity of heat modified zeolite could be reach mean value of 120.18meq/100g, which was 1.55 times than virgin zeolite. The results of bench scale experiments also showed that the data in the experiments were in line with Langmuir isotherms for ammonium ion absorbed onto heat modified zeolite. Moreover the biofilm which attached on the surface of heat modified zeolite only modified the surface feature of modified zeolite, while ion-exchange and diffusion procedure were not affected.
Reliable Guaranteed Cost Control for Uncertain Time-Lag Systems of Actuator Failures
Authors: Lu Wang Ping , Xu Hai Dong , Li Shao Yi , Tao Ling
Published: June 2010

Focusing on a type of uncertain continual time-lag systems, study on the designing problems of law in reliable guaranteed cost feedback control when actuators are in fault condition of continuous-gain. Apply of the processing method of linear matrix inequality, derived out the condition that reliable guaranteed cost exist, and give out the parameterized representation of all the reliable guaranteed cost control law. In this foundation, we can further obtained the designing method of optimal reliable guaranteed cost control law.
Research on Reactive Power Compensation Algorithm Based on Game Theory in Wind Farm
Authors: Xu Xiang Zheng , Chen Qi
Published: June 2010

In current, constant speed of asynchronous generator system has been used wind farm in China areas. But because of that abilities of reactive power control helpless, reactive power have been provided by grid. In view of the above situation, the feasible measures are adopted in the wind dynamic reactive power compensation devices. The asynchronous machine transient process used reactive power to keeping voltage of machine has been provided. This article introduced the Game Theory in economics to the area of reactive power compensation. This new method of the share of reactive power in wind farm, will improve wind farm reactive power compensation too vague to efficient in the moment. In the meantime, the share of reactive power algorithm analysis process have bee bullied in this paper. For the research in the future, it proposed supplementary opinions.
Research on Harmonic Suppression of Electric Railway Based on Hybrid Active Power Filter
Authors: Xu Xiang Zheng , Chen Bai Chao
Published: June 2010

According to the specific property of traction supply system, a novel hybrid active power filter (HAPF) is designed in this paper. The new HAPF topology is that, after the impedance of fundamental wave is in parallel with the active power filter (APF), it is series connected passive filter. The kinds of structure can reduce the VA rating of the APF greatly. The small rating active power filter is used to improve filtering characteristics of the passive filter and suppress possible resonance between the traction supply system impedance and the passive filter. Through MATLAB simulation, it shows that the control strategy of power quality is apparently effective, and it plays an important role in enhancing the reliability of transformer station and the operating security of electric railway.
Design of Hierarchically Porous Materials for Bone Tissue Regeneration
Authors: Yun Hui Suk
Published: June 2010

Mesoporous materials synthesized using a polymer templating route have attracted considerable attention in the field of bone tissue regeneration because their unique pore textural properties (high specific surface area, pore volume and controllable mesopore structure) can promote rapid bone formation. In addition, their potential use as a drug delivery system has been highlighted. The scaffolds in bone tissue regeneration should contain 3D interconnected pores ranging in size from 10 to 1000 μm for successful cell migration, nutrient delivery, bone in-growth and vascularization. Meso-sized pores are too small to carry out these roles, even though mesoporous materials have attractive functionalities for bone tissue regeneration. Therefore, a technique linking mesoporous materials with the general scaffolds is required. This paper reviews recent studies relating the development of new porous scaffolds containing mesopores for using in bone tissue regeneration. All the suggested methods, such as a combination of polymer templating methods and rapid prototyping technique can provide hierarchically 3D porous bioactive scaffolds with well interconnected pore structures in the nano to macro size range, good molding capability, biocompatibility, and bioactivity. The new fabrication techniques suggested can potentially be used to design ideal scaffolds in bone tissue regeneration.
Calcium Phosphate Ceramics as Bone Drug-Combined Devices
Authors: Verron Elise , Bouler Jean Michel
Published: June 2010

The use of bone grafts is constantly increasing, their employ is principally linked to bone trauma, prosthesis revision surgery, and arthrodesis applications. In the case of biological bone grafts and depending on the origin of the graft, these grafts are classified as autografts, allografts, or xenografts. The autograft is the most commonly used and corresponds to a fresh bone graft harvesting taken from a second operating site, i.e. iliac crest, parietal bone, tibial plateaux or the fibula. The autograft has many advantages in terms of biotolerance and osteogenic potential, which justify its widespread utilization in reconstructive surgery[1]. From a practical point of view, sampling and grafting take place during the same surgical session. However, the longer exposure to the anesthetic and the surgical operation per se increases the risk of complications. For example, this procedure results in sever post-operation pain, iliac hernias, or even haemorrhages[2]. Furthermore, the volume of the bone graft taken is generally limited to 20 cm3. In the case of allografts, it generally leads to an acute inflammatory reaction which participates to the resorption/substitution process. Xenografts are less used since it involves a donor and a recipient from different species.
Dendritic Macromolecules: New Possibilities for Advanced Bioceramics
Authors: González Blanca , López de Laorden Carlos , Colilla Montserrat , Vallet-Regí Maria
Published: June 2010

Dendrimers are a relatively new class of molecules that display a variety of potentially useful architecture-induced properties. In this chapter, we firstly present a general description of this interesting class of macromolecules, making special emphasis in their current biomedical applications. The combination of dendrimers with ceramics, traditionally used in the biomedical field, provides synergistic features and functions to the resulting hybrid materials. After the dendrimers introduction, an overall description of mesoporous silicas, iron oxide nanoparticles and carbon nanotubes bioceramics, is presented. Finally, recent research examples of dendrimer-functionalized ceramics, both from the synthetic and biomedical applicative points of view, are reviewed.
Biomineralization of Polymer Scaffolds
Authors: Katsanevakis Eleni , Wen Xue Jun , Shi Dong Lu , Zhang Ning
Published: June 2010

Bioceramics are an important subclass of inorganic, non-metallic biomaterials. Attributing to their bioactivity and the ability to form bonds with native bone, bioceramics are increasingly used in medical implants, especially for bone repair and regeneration. With chemical composition similar to that of native bone, hydroxyapatite (HAp), a type of bioceramics, may impart to biomaterial implants biocompatibility, osteoconductivity, as well as surface properties that are germane to osteointegration at the bone-implant interface. However, porous bioceramics are very brittle and have low fracture toughness and compressive strength, which limits their uses as bulk materials for orthopedic implants. Increasing their mechanical strength by reducing the porosity may prevent tissue infiltration, therefore, bone regeneration. In comparison, polymers may mimic the mechanical properties of native bone, however, may lack the appropriate surface properties to seamlessly integrate with natural bone. There is a critical need to combine the bulk properties of polymers with the surface properties of bioceramics in the design of functional scaffolds for bone tissue engineering. There are several ways to incorporate bioceramics on scaffold surfaces, including plasma spraying, sputter coating, physical adsorption, laser deposition, and biomineralization. Biomineralization, which allows easy fabrication of bioceramics under physiological conditions, provides an effective means to produce bonelike minerals, e.g., HAp, on scaffold surfaces. By following the cascade of biological mineralization in vivo, biomineralization in vitro on polymers may be achieved using several different methods, including immersion in simulated body fluid (SBF), alternative soaking in calcium and phosphate solutions, urea-mediated solution mineralization, enzymatic method, and direct incorporation of HAp nanoparticles into polymers. The uniformity, structure, and composition of the bioceramic coatings can be fine-tuned by governing bimineralization parameters such as composition and concentration of the immersion solution, immersion time, temperature, and agitation. A variety of surface modification techniques can be chosen to functionalize/activate polymer surfaces to facilitate biomineralization. In this review, the mechanism for biomineralization in vivo, different mechanisms and methods for biomineralization in vitro, surface modifications for enhanced biomineralization, polymers for biomineralization, and biomineralization for drug delivery will be discussed in details.
Functionalized Calcium Phosphate Nanoparticles for Biomedical Application
Authors: Epple Matthias , Kovtun Anna
Published: June 2010

Calcium phosphate is a natural biomineral and therefore possesses an excellent biocompatibility due to its chemical similarity to human hard tissue (bone and teeth). Calcium phosphate nanoparticles can be precipitated under controlled conditions and used as carrier in biological systems, e.g. to transfer nucleic acids or drugs. Such nanoparticles can also be suitably functionalized with fluorescing dyes, polymeric agents, pro-drugs or activators. The small monodisperse nanoparticles only mildly influence the intracellular calcium level and therefore are not toxic for cells.