bluuebunny/crossref_metadata_2025 huggingface dataset:
Design of Moving Target Detection System Based on FPGA
Authors: Yu Yan Xin , Wang Chun Yang , Chen Yu , Sun Hong Yan
Published: October 2014

This paper puts forward a kind of radar moving target detection system based on single chip of field programmable gate array (FPGA), including the input buffer, string and transformation, window function, Doppler filter group, the constant false alarm and output caching function modules. Doppler filter group is 16 point FIR filter direct filtering method, constant false alarm circuit adopts alarm circuit which choose larger in the average of adjacent cells. The experimental results show that the moving target detection system can effectively detect targets. Compared with traditional system performance this method is more stable and has stronger anti-interference ability.
Group Decision Making Method Based on Composite Linguistic Expressions
Authors: Dai Wen Zhan , Li Yun
Published: October 2014

When decision makers are hesitant among different linguistic terms, the traditional use of one single linguistic term will restrict the accuracy of personal preference expressed by experts, it is necessary to use composite linguistic term which contains both the one single linguistic terms and the comparative linguistic expressions. Firstly, with the use of context-free grammars, two-tuple linguistic representation model and hesitant fuzzy linguistic term sets, the linguistic expressions of the preference relations provided by experts are transformed into judgment matrix, then the suitable aggregation operators will be selected to obtain a best solution to the problem. Finally, a new group decision making model based on composite linguistic expressions has been proposed and a practical example has been analyzed to verify the reasonability and feasibility of the approach.
Pile-Up Pulse Separation Technology Research Based on MATLAB
Authors: Wang Ya Fei , Liu Bing Qi , Cao Xu
Published: October 2014

The way of energy spectrum acquisition aimed at nuclear signal, putting forward a kind of pile-up pulse separation technology research based on MATLAB. It takes MATLAB as processing platform, adopts graphical user interface (GUI) as design tools, establishs pile-up pulse signal simulation module, in order for nuclear accumulation of signal pulse which can be used in many cases to provide initial data for further research. Through the proposed platform, researching on the way and theory of pile-up pulse separation, and programming to achieve processing method, combining the separation results from different pile up pulse cases and to make an analysis, giving the best processing method and suggestion on treatment scheme, so as to provide basis for the improvement of digital nuclear spectrum system.
Study on the Optimal Distribution Strategy of Multi-Firepower Units Based on Markov Model
Authors: Ai Di Ming , Liu Xiao Guang , Kong Ling Jie , Zhao Jun Yan
Published: October 2014

Under the circumstances of informationized war, how to distribute firepower units in the most economic manner to maximize the performance of combat system as a whole has become the hot topic with which the combat agent is concerned. The conventional static method based on linear programming intends to distribute firepower units to the enemy targets under certain restrictions as possible as it can , when the number of enemy targets is more than that of the firepower units, there will be multiple firepower units acting to the same enemy target, the effectiveness of combat will be greatly reduced oppositely while the invasion intensity of enemy targets is becoming larger and stronger suddenly. The threat intensity of coming enemy target is included into performance indices for distribution by Markov random target dynamic distribution strategy. based on the original static distribution strategy proposed by this paper, and the weapons will be redistributed to other targets when one weapon finishes its shooting with no more targets distributed, and the less efficient weapons will be replaced with those more efficient ones. Thus, the system can still redistribute firepower units to enemy targets that haven’t been destroyed according to the current status of weapon system's firepower units, even though no new targets arrive or no new instructions of dynamic firepower targets’ distribution decisions are given. All these can help minimize the whole threatening intensity of enemy group, in order to realize the maximum of weapon system’s average economic benefit of combat in the long term.
Practical Criteria for H-Matrices
Authors: Zhang Ming Da
Published: October 2014

Generalized strictly diagonally dominant matrix is very important in computing mathematics and matrix theory, many articles are searching simple and practical identification of generalized strictly diagonally dominant matrix. In this paper, using the concept of diagonal dominance, some sufficient conditions for generalized strictly diagonally dominant matrices are given.
Research on Parallel Computation of Semantic Similarity in Linked Data
Authors: Jin Xiao , Zhang Xing Jin , Zheng Zhi Yun , Li Quan Min , Lu Li Ping
Published: October 2014

This paper proposes a novel parallel computing method of semantic similarity in linked data to solve such problems as low efficiency and data dispersion.It combines the existing similarity calculation method with MapReduce parallel computation framework to design the appropriate parallel computing method of similarity. First, three typical similarity computing methods and the parallel programming models are introduced. Then according to the MapReduce programming techniques of cloud computing, the parallel computation of similarity in linked data is proposed. The experimental results show that, compared with the traditional platforms, the parallel computing method of similarity on the Hadoop cluster not only improves the capacity and efficiency in the processing massive data, but also has a better speed-up ratio and augmentability.
Visual Plant Sticks Growth Model and Three-Dimensional Visualization
Authors: Yin Ying Ying , Chen Li Fei
Published: October 2014

For the aim that describing the growth process of plant sticks with a effective model, presented a new method based on plant physiological characteristics, it also considered plant weight and light comprehensively. The model can reflect parallel growing of plants continually and dynamically, and the relationship between plant morphology and growing physiology is also be reflected at the same time. The simulation results show that the model is directly and provides a practical method for the research of virtual plant, especially for the plant sticks.
Research on Prediction of CAAC Flight Incident 10000-Hour-Rate Based on Single Regression Model
Authors: Gan Xu Sheng , Gao Wen Ming , Zhao Hai Tao
Published: October 2014

To assist the aviation safety management and decision-making, it is important to effectively predict the flight incident 10000-hour-rate for preventing the aviation accidents. For improvement of prediction level, a simple regression model is proposed. The prediction result obtained in actual example indicates that the proposed single regression model has a good prediction on CAAC flight incident 10000-hour-rate.
An Improved Bat Algorithm and its Application in Permutation Flow Shop Scheduling Problem
Authors: Zhang Jian Jun , Li Yue Guang
Published: October 2014

Permutation flow shop scheduling problem is a complicated global optimum problem. In this paper, according to the characteristics of permutation flow shop scheduling problem, an improved bat algorithm was used to solve permutation flow shop scheduling problem. The algorithm was experimented and the experimental results show that the improved bat algorithm has better feasibility and validity for solving permutation flow shop scheduling problem.
An Improved Quantum Ant Colony Algorithm of Solving Nonlinear Equation Groups
Authors: Xia Yue Hua , Li Yue Guang
Published: October 2014

In this paper, according to the characteristics of nonlinear equations. A new algorithm, Quantum Ant Colony Algorithm (QACA) is proposed. The core is that Q-bit and quantum rotation gate adopted in QEA are introduced into ACS to represent and update the pheromone respectively, so it has better diversity and global search capacity. The experimental result demonstrates that QACA can get better solutions to nonlinear equations.
The Research and Application of Time Series Prediction Model
Authors: Zhao Yue Ling , Cao Li Ying , Ma Li , Chen Gui Fen
Published: October 2014

The idea of using time series analysis to predict product is not new. At present, there are many food resources prediction and evaluation, and in the agricultural research it is prediction good method of international popular food like method, remote sensing prediction method, multiple regression and other methods to predict yield. In this paper, the main production data is used in Jilin province in recent decades, the application of time series analysis method of comparative study, in order to serve agriculture and choose a more accurate prediction of time series model in recent years of maize yield in Jilin province. The results showed that ARIMA (2,1,1) could correctly simulate and forecast the products of maize, providing an important method for accurately predicting the yield in formation of agricultural products.
Study on the Prediction of Shanghai Composite Index Based on a Fusion Model of RBF Neural Network, Markov Chain and GA
Authors: Zhu Wei Hua , Yang Jing
Published: October 2014

From numerous approaches studying the prediction of stock price, this paper proposed a new approach which was the combination of RBF neural network and Markov chain to forecast the stock closing price of the Shanghai composite index. Markov chain was aimed at making the error between the actual price and predicted price obtained by RBF neural network correct. Besides, for higher prediction accuracy, genetic algorithm was used to optimize the state division of Markov chain. The experimental result confirmed its effectiveness and superiority in comparison with the other two methods in some time interval.
MOEAs Based on Dynamic Chaotic Mutation
Authors: Ding Xue , Zhao Chuan Xin , Yang Hong Hong , Chen Bin
Published: October 2014

In reality, there are varieties of practical problems which are all optimizing many objectives at the same time. Meanwhile, these problems are usually highly complex, which are called multi-objective optimization problem. Multi-Objective Evolutionary Algorithms, shorted as MOEAs, is very suitable for solving this kind of problem. Chaos is defined as a random phenomenon with a sensitive dependence on initial conditions, which is produced by deterministic system. It covers almost each branch of both natural science and social science. The main work of this paper is to analyze and make conclusion about the dynamic chaotic mutation and MOEAs. Based on it, this paper proves the convergence of dynamic chaos multi-objective optimization, and proposes MOEAs based on dynamic chaotic mutation.
Calculation of Semantic Similarity Property Based on Generalized Semantic Weak Incomplete Information System
Authors: Ding Xue , Yang Hong Hong , Zhang Ren
Published: October 2014

Each object has its own specific properties, objects can be uniquely identified by its properties. "Properties" are properties of all the main features of the concept only, property values ​​are often given a certain amount of semantics, in the calculation of similarity among the different attributes if only to consider the type of calculation is obviously not complete [1]. For example: blue and blue, the similarity calculation in the property type, we can not determine its degree of similarity, but it is the same type of semantic expression under the different languages. Another example: domperidone and domperidone, which is the same type of drugs. Therefore, we attribute value in the calculation of the time, but also taking into account the semantic similarity.
Maritime Search and Rescue Capability Evaluation Algorithm Based on Cloud Model
Authors: Xu Zhi Yuan , Wu Zhao Lin , Yao Jie , Ren Yu Qing
Published: October 2014

Maritime search and rescue is important for the maritime traffic safety. A maritime search and rescue capability evaluation algorithm based on cloud model is proposed in this paper. Firstly, we established the evaluation system; Secondly, we determined the expert evaluation cloud model according the scoring; Thirdly, we calculated the evaluation result by the comprehensive cloud; Finally, we used the digital characteristics to restore the cloud chart. The experimental result shows that our method is objective and accurate.
A Fair Virtual Network Embedding Algorithm
Authors: Wang Cong , Yuan Ying , Wan Cong
Published: October 2014

Efficient network resource utilization is crucial in Virtual Network Embedding (VNE) problem. The diversity of virtual topologies belong to various services providers (SPs) severely affects the efficiency of VNE algorithms and fairness between SPs. This paper proposes a fair VNE algorithm with a topological transformation mechanism. Such mechanism will transform virtual topology to reduce complexity. Then the algorithm will felicitously map the virtual network onto substrate network through a Disperse Particle Swarm Optimization (DPSO) based process. Simulation results show that due to the topological transformation procedure the algorithm can achieve more fairness than traditional VNE algorithms.
Network System Reliability and Unit Probability Importance Based on Monte Carlo Method
Authors: Bin Rao
Published: October 2014

The network system reliability research contains a number of problems, such as: Reliability analysis and reliability design, reliability, maintenance and a lot of problems so on. The calculation of reliability of the network is the important area of network reliability analysis, State enumeration method and principle of a class, don't pay the product and method, the factor decomposition method is a classic accurate algorithm of computing network reliability. Due to the difficulty of precise calculation, in the method, appeared and bound method, Monte carol method, the reliability of the approximate algorithm. Compared with the accurate algorithm, approximate algorithm is still under development. So far, no recognized classic algorithms, so the method to improve calculation accuracy, reduce the complexity of the target of the researchers.
Study on Maize Yield Prediction Using Time Series Analysis
Authors: Zhao Yue Ling , Han Hai Yan , Cao Li Ying , Chen Gui Fen
Published: October 2014

In order to predict the maize yield of changes in the following years for our managers and framers, we have applied a statistical model based on time series analysis. Nowadays, there is a variety of methods on yield prediction in agricultural .In order to prove the accuracy of prediction models, more than prediction model can be used. In the paper, the establishment of ARIMA (2, 1, 1) model was been established by using the timing sequence analysis on yield data. The partition results can not only guide farmer, provide an important method for accurately predicting in agricultural products, and can be used to implement variable input and precise fertilization recommendation.
Improving Image Classification Quality Using Multi-View Learning
Authors: Sun Cheng Jian , Zhu Song Hao , Shi Zhe
Published: October 2014

This paper proposes a novel multi-view learning framework which leverages the information contained in pseudo-labeled images to improve the prediction performance of image classification using multiple views of an image. In the training process, labeled images are first adopted to train view-specific classifiers independently using uncorrelated and sufficient views, and each view-specific classifier is then iteratively re-trained using initial labeled samples and additional pseudo-labeled samples based on a measure of confidence. In the classification process, the maximum entropy principle is utilized to assign appropriate category label to each unlabeled image using optimally trained view-specific classifiers. Experimental results on a general-purpose image database demonstrate the effectiveness and efficiency of the proposed multi-view semi-supervised scheme.
Research of Object Tracking Algorithm Based on BRISK
Authors: Guo Shi Xu , Chen Jia Xin , Peng Bo
Published: October 2014

In view of the problems that high complexity, large calculation and the difficulty to apply to real-time systems in the current moving target tracking algorithm, this paper introduce the BRISK feature extraction algorithm, and proposed the object tracking algorithm based on BRISK. Set up the background model and use the background difference method to detect the moving target template. Then match in the next frame and track the target. In order to reduce the search feature matching area, further improve the real-time of the algorithm, we also introduce the kalman filter algorithm to estimate the target motion trajectory. The experimental result show that comparing with the SURF, SIFT feature tracking algorithm, the algorithm of this paper has greatly improved in real-time.
Research on Random Algorithm of English Test Paper Composition
Authors: Qu Wei Wei
Published: October 2014

English, as one of the most important information carriers, has become the most widely used language worldwide, and its importance is increasingly prominent in each field of our society. Examinations are an important means of evaluating the level of English language learning and teaching outcomes. For the problems existed in traditional English exam, this paper research English online examination system intelligent test paper based on random algorithm. First, the design test paper constraints, including the question amount constraint, questions type constraints, knowledge point constraints, difficulty constraints, answer time constraints and so on; Then, using the linear congruence generator study of a random number generation, list recursive formula and describe parameters; Finally, using flow diagram to study random test paper process, for each step describing in detail. Advantages of random algorithm are easy to use, the disadvantage is not retrospective, applies to the number of exam papers and extraction requirements are relatively few cases.
Body Sensor Network Processing Mechanism for Micro-Data Security Publishing
Authors: Li Na
Published: October 2014

Individuals’ privacy protection when publishing data for research has recently put great attention on data mining and information resources sharing fields. Privacy preservation is an important and challenging problem in micro-data publishing. This paper aimed to find an available directly way protect patient privacy. Processing numeric values which got from body sensor network (BSN). Firstly, we analyze the characteristics of medical data which collected from BSN, and then the records will be grouped according to the Quasi-identifier. The last step is to inspect the diversity of sensitive attributes.
Pretreatment of Wastewater Using a Combined Coagulation and Fenton Oxidation Process
Authors: Linghu Wen Sheng , Sun Chun Yan
Published: October 2014

The effectiveness of combined coagulation and Fenton oxidation to pharmaceutical plant wastewater was investigated under different operational conditions such as pH, dosage, coagulants and ratio of Fe2+to H2O2. Among the nonionic polyacrylamide, cationic polyacrylamide, anionic polyacrylamide, polyaluminum chloride and polymeric ferric sulfate, anionic polyacrylamide showed the best efficiency of coagulation for the pharmaceutical plant wastewater. The results also showed that after the combined coagulation and Fenton oxidation treatment, the COD and color were reduced by 69.9% and 78.9%, respectively. The BOD5/ COD ratio increased from 0.09 in initial to 0.22 after treatment. The wastewater of outlet was easier for the sequent biological process.
Using Prior Knowledge for Community Detection by Label Propagation Algorithm
Authors: Wang Yi Bo , Wang Wen Jun , Liu Dong , Liu Xiao , Jiao Peng Fei
Published: October 2014

Community detection is an important approach to analyze and understand the organization or unit structure of the complex networks. By comparing the existing community detection algorithms, the label propagation algorithm (LPA) shows prominent operation speed and qualifies near linear time complexity. However, original LPA algorithm only uses the topological structure to guide the community detection process, failing to improve the quality of community detection when extra information offered. In this paper, we combine the prior information with topological structure to guide the community detection process. During the label propagation process, we proposed a new label update principle, making a node absorb its neighbor label information depending on the label distribution. The experimental results both on real networks and artificial networks show that the improved algorithm not only inherits the characteristic of rapid speed, but also improves the quality of community detection. Moreover, the improved algorithm still has the feature of near linear time complexity.
Object Tracking with Robust Kalman Filter Based on Convex Optimization
Authors: Feng Bao , Qin Chuan Bo , Wu Fei
Published: October 2014

Tracking moving objects with high accuracy is an important problem in fields of robot vision, video signal processing and pattern recognition. One of the widely used object tracking methods is Kalman filter. Conventional Kalman filter has a basic assumption that the noise obeys Gaussian distribution. However, in practice, the observed data also suffers from non-stationary sparse noise, which may cause performance deterioration for conventional Kalman filter. In this paper, we propose a robust Kalman filter based on convex optimization to remove not only the Gaussian noise but also such kind of sparse noise. Formulated as a convex optimization problem, the robust Kalman filter can be solved efficiently by Interior Point Method. Numerical results show that the proposed method is robust against sparse noise and achieves better performance while tracking objects under sparse noisy condition.
Recent Advance in Green Catalytic Oxidation of Alcohols to Aldehydes and Ketones with Hydrogen Peroxide as Oxidant
Authors: Tang Xuan , Fang Li Li , Huang Feng Lin
Published: October 2014

. New developments in green catalytic oxidations of alcohols with H2O2 as oxidant in last decade are reviewed. Emphasis is placed on introducing the heterogeneous catalysts supported on different material in various of reactions, mechanism features are discussed as well.
Analyzing Functions of the Influence in Decision by Ballot Using Statistical Methods
Authors: Duan Wen Xi
Published: October 2014

The methods for quantity of the influence coefficient are put forward in this paper. The effect of the influence coefficient in voting actions is also explained. However, the simple means of the voting results such as evaluation, calculation, operation and control are introduced in the article.
The Comparison of the Estimator of the Variance in the Cox Proportional Hazards Model
Authors: Li Yong
Published: October 2014

The Cox model is commonly used to model survival data as a function of covariates. In this paper we compare the three methods to estimate the variance of the parameters in Cox model and presents the simulation result.
Cluster Analysis of Seismic Data Based on Region Scalable Fitting Model
Authors: Lu Wen Jia , Wu Qing Qiang , Lin Dong Yun
Published: October 2014

In order to analysis seismic data, we propose a cluster analysis method based on region scalable fitting model which aims to adapt the image segmentation algorithm to cluster analysis. The method can be divided into 4 parts: dimension reduction, data segmentation, feature extraction, and feature cluster. Finally, we do cluster validity evaluation. The validity evaluation results show that the computational complexity of the new algorithm is relatively lower than the ordinary ones and the inhomogeneous data of high dimension can be analyzed effectively by our model. In this paper, the RSF model was applied in the high-dimensional space. Since the original sample quantity is dramatically reduced by the new algorithm, our model can be incorporated into the algorithms which have strict requirements for the size of sample.
A Novel Text Data Mining Method Based on Neural Network and its Application
Authors: Liu Lei , Wang Shao Qiang , Gao Quan Bao
Published: October 2014

Data mining aims to excavate new knowledge from existing information. When it comes to test mining, a better way is to take the context into account In this study we present text mining procedures based on a neural network framework in order to identify indicative factors in the form of keywords within the medical record narratives. These keywords and their weight/value suggest an innovative way for justifying a CT scan request. Our purpose is to extend the reach of diagnosis beyond traditional processing of clinical data towards an efficient utilization of the narratives in medical records.
Image Fusion Based on Adaptive Coefficient Gauss Wavelet
Authors: Li Yong , Miao Zhuang
Published: October 2014

According to CT and MR image features, we presented the medical image fusion algorithm based on adaptive Gaussian wavelet, which uses gray level co-occurrence matrix to modify space coefficients adaptively. Compared with other wavelet algorithm by simulation, the results proved that the proposed algorithm obtained valid information in a highly automated manner, and without human intervention or prior information.
Recurrent Wavelet Neural Network Based on Immune Evolving Algorithm and its Application in Nonlinear Modeling
Authors: Luo Xiang Jie , Wei Cheng Kai , Gao Hai Long
Published: October 2014

To improve the modeling performance of Recurrent Wavelet Neural Network (RWNN), a training algorithm based on Immune Evolving Algorithm (IEA) is proposed. In the process of RWNN training, IEA is mainly used to optimize the connection weight, translating and scaling parameter. The experiment result on Duffing chaotic time series shows that the proposed RWNN training algorithm has a good prediction capability in the field of nonlinear modeling.
An Improve Firefly Algorithm and its Application in Nonlinear Equation Groups
Authors: Zhang Yan Feng , Li Yue Guang
Published: October 2014

In this paper, according to the characteristics of nonlinear equations. A Novel Firefly Algorithm was used to solve the nonlinear equations problem, the algorithm was experimented and the experimental results show that the new algorithm to be successful in locating multiple solutions and better accuracy. The experimental result demonstrates that the Improve firefly algorithm can get better solutions to nonlinear equations.
MSRM Based Object Extraction Method for Image Sequences
Authors: Yu Wen Ting , Wang Jing Ling , Ye Long
Published: October 2014

Object extraction, which aims to accurately separate a foreground object from its background in still images, plays an important role in many computer vision applications. An interactive object extraction method based on MSRM (maximal similarity based region merging) is presented in this paper. We can manually mark the target and background only one time in any one image of the image sequence to obtain the object extraction result of the image sequence. Compared to currently used method based on graph cut algorithm that manually marks the target and background on all the images one by one to get the object extraction result, our method is more efficient and the result is as precious as with other methods.
Logistics Distribution Route Optimization Based on Chaotic Cuckoo Algorithm
Authors: Li Juan
Published: October 2014

In order to efficiently solve the routing optimization problem of logistics distribution vehicle, a new chaotic cuckoo optimization algorithm have been put forward, first, the algorithm is used for seeking optimization, chaotic perturbation operator is added in the parasitic nest position in the iteration, thereby the population diversity is expanded and the algorithm accuracy is improved. The simulation experiment is carried out for this algorithm; the result shows that the algorithm is to seek the optimal solution, the average solution, and find the optimal solution frequency and time, which all has obvious effects.
Non-Stationary Signal Analysis Based on Hilbert-Huang Transform and Median Filter
Authors: Wang Xiao Li , Wang Dian Hong
Published: October 2014

The Hilbert-Huang Transform (HHT) is a new time-frequency analysis with adaptability and orthogonality, but it is rather weak in terms of noise resistance, even low noise can disturb the HHT result greatly. The paper launches an investigation on how noises affect the HHT result and proposes the method to solve the problem. The analytic framework for HHT is first introduced, the feature of the test signal is extracted by HHT. Median filter is adopted to reduce the frequency leakage of certain signal component caused by white noise. The method proposed is experimentally simulated and the results demonstrate its effectiveness.
Research on Blurred Image Restoration Quality Evaluation Method
Authors: Zhang Jian Hua , Kong Fan Tao , Wu Jian Zhai , Zhu Meng Shuai , Zhao Pu , Wang Sheng Wei
Published: October 2014

Accurate evaluation of image quality is always being a problem. With blurry cotton images as samples, using variance methods, average gradient method, gray prediction error statistics method and information entropy method, this research evaluated restoration quality of 4 kinds of images from the perspective of grayscale contrast, sharpness, contrast and ambiguity. The results show that the 4 image restoration algorithms all improved image quality, and Wiener algorithm improved image quality best comparing with other 3 algorithms, Reg second, Blind algorithm and K-L algorithm were worse.
An Improved AdaBoost Algorithm
Authors: Liao Shao Wen , Chen Yong
Published: October 2014

In view of the higher mistaken-detection rate problem of the human face detection in complex conditions, we put forward an improved algorithm. This article Proposes one kind of the method Which unifies the level of difference between the threshold and the feature value of the weak classifier with the weak classifier's overall error rate. Compared to the method which only based on the overall classification error rate to update the weights, this method can achieve higher detection rate while reduces the mistaken-detection rate. This article redefines the training error which is caused When we train the weak classifier, and Proposes MCE-AdaBoost algorithm. The new definition of training error will pay more attention to the error Which erroneously estimates the face Sample as non-face sample; this much more conforms to face detection of this special target detection issue. The experimental results show that MCE-AdaBoost algorithm can effectively improve the detection Performance of the final classifier.
Effects of Rare Earths on Inclusions Distribution and Modality of 8Cr4MoV Cold Work Roll Cast Steel
Authors: Wu Guo Sheng , Fu Zhi Yun , Wang Zhong
Published: October 2014

A study of rare earth effects on inclusion modality of 8Cr4MoV cold work roll steels was carried out in the laboratory, the steels smelting by a 50kg vacuum induction furnace, atmospheric casting, processing sample after annealing, then inspecting the steels’microstructure, inclusion modality and composition; The results showed that the steels’ microstructure fine, micro-hardness increased with increasing rare earth content, while the average size of inclusions decreased significantly, also the morphology and composition of inclusions significantly changed from the angular black manganese sulfide to the ball white sulfur oxides of rare earth, and thus played roles of deoxidation, desulfurization, purification and deterioration of liquid steel , it will help improving the fatigue performance of the work roll.
An Adaptive Power Control Algorithm in RFID Systems
Authors: Long Jing , Li Jian Cheng , Zheng Li Ming
Published: October 2014

Nowadays, RFID technology has been widely spread in various fields. However, the situation of the reader-to-reader collision, caused by movements of readers, is becoming more and more prominent. To solve this problem, this paper proposes an adaptive power control algorithm based on the SNR-measurements method, which uses the Kalman filtering algorithm to estimate the wireless channel characteristic at first, and then adjusts the transmission power of the reader variously according to both channel estimated results and SNR histories, which determines the step size. As shown in simulation results, the algorithm proposed could avoid reader-collision effectively. The algorithm not only provides improvements on real-time ability as well as reliability, but also improves the throughput and precision of identifying tags.
Design & Implementation of Real-Time Broadcast System of Urban Public Transport Crowding Index Based on the Internet of Things
Authors: Zhang Si Jun , Chen Shu Yan
Published: October 2014

Real-time broadcast system of public transport crowding index belongs to the broadcast system of urban public transport environment in ITS. The remaining seats and vehicle weight of the bus can effectively reflect the current crowding of public transport. This paper proposes a real-time broadcast system about the crowding index in public transport based on the Internet of things. The system can be divided into four submodules: wireless sensor network node, Sink node, terminal analysis and evaluation system and site display platform.Operating datas in public transport collected by wireless sensor networking node are sent to terminal analysis and evaluation system by GPRS wireless communication mode. This system can help people choose the best travel route. It may be helpful for managers to make a better traffic assignment.
Vegas-f: Adaptive Growth Rate of Slow Start for TCP Vegas in Large Bandwidth-Delay Network
Authors: Hou Pei Dong , Tang Bi Hua , Liu Fang , Liu Yuan An , Liu Kai Ming , Xie Gang
Published: October 2014

TCP Vegas has the problem that it stops slow start too early, and it is more obvious in the large delay-bandwidth network. This phenomenon can cause a very long linear growth after entering congestion avoidance phase, and it will reduce the transmission efficiency. This paper analyzes that the reasons for this phenomenon is due to the exponential growth of slow start itself, then puts forward a dynamic growth algorithms of slow start, we call it Vegas-f. Improved algorithms can dynamically adjust the growth rate of slow start, so as to improve the transmission efficiency and competitiveness in mixing network. Simulation results show that the improved algorithm has completely solved the problem and the performance is improved significantly.
Interference Localization via Direction of Arrival Estimation for Satellite with Planar Array
Authors: Qiu Xiao Feng , Zhang Xiao Fei
Published: October 2014

This paper presents the model of satellite planar array, and interference localization via direction of arrival (DOA) estimation. We derive a dimension reduction DOA estimaton algorithm therein. The proposed algorithm, which only requires a one-dimensional local searching, can avoid the high computational cost within two-dimensional multiple signal classification (2D-MUSIC) algorithm. We illustrate that the proposed algorithm has better angle estimation performance than estimation method of signal parameters via rotational invariance technique (ESPRIT) algorithm, and has very close angle estimation performance to 2D-MUSIC algorithm. Furthermore, our algorithm requires no extra pairing. Simulation results present the usefulness of our algorithm.
Mixed Communication Method on the Grid-Based for Wireless Sensor Networks
Authors: Dai Jing Guo , Yuan Hui Yong
Published: October 2014

When senors transmit their data to the sink via multi-hop communication, the sensors closer to the sink are burdened with heavy relay traffic and tend to die early. On the contrary, if all sensors transmit datas to the sink via single-hop communication, the sensors further from the sink will die much more quickly than those closer to the sink. In this paper, we first develop an analytical model to derive the optimal cluster radius. Then we propose a mixed communication method on grid-based where the sensors can transmit data to the sink in either single-hop or multi-hop. Finally, we conduct extensive experiments and show that our method outperforms LEACH and HEED in terms of network lifetime by balancing energy consumption.
Application and Research of Data Interface Synchronization on Web Maintenance
Authors: Liu Xiao Yang , Zhao Jian Ping , Li Qing Mei , Wang Wei , Ding Ran , Zhao Jian Hui
Published: October 2014

To adapt to the changing requirement of task data interface under the situation of far distance, multiple segment, multiple circle, multiple satellite and multi-station visibility for satellite misson in transfer orbit segment, the web incremental maintenance system based on materialized view was achieved through applying incremental maintenance principle, database technology, synchronization mechanism and maintenance proxy, and realizing the synchronization and consistency of data interface about the distributed experiment information surveillance software system. The result shows that web incremental maintenance system can ensure the real-time and consistency of data processing and transmission.
Private Set Intersection via Searchable Encryption against Malicious Adversaries
Authors: Shao Zhi Yi , Yang Bo
Published: October 2014

Shao et al. proposed a novel method for computing private set intersection based on searchable encryption. Compared with the traditional protocols, their technique requires much less computation for the client to obtain the intersection. Concretely, the client only computes m (the cardinality of the client’s input set) multiplications, m hashes, and one modular exponentiation. However, their protocol only satisfies security against semi-honest behaviors. In this paper, we aim to promote the security of Shao et al.’s protocol. Our solution woks in the CRS model, and is based on the non-interactive zero knowledge proof and the succinct non-interactive argument. The proposed protocol satisfies security against malicious adversaries and needs only one round interaction.
Research on GNSS/SINS Tightly Coupled Integrated Navigation System
Authors: Chang Yao Wei , Chen Shuai
Published: October 2014

When a missile runs under the complex situation such as high dynamic flying, receiver signal being blocked and so on, the GNSS receiver sometimes gets less than four satellites. For the loosely coupled system, the navigation accuracy will decrease over time. In this paper ,tightly coupled integrated navigation system which is based on pseudo range and pseudo range rate dynamically adjusts the dimension of the system according to the number of visible satellites, in order to achieve seamlessly navigation; a multiple step optimum precision factor satellite selection algorithm is proposed, an error compensation method which is based on the state transition is designed and implemented. Experiments show that when the number of visible satellites changes, tightly coupled system can seamlessly switch, when more than four satellites are received, the multiple step optimum precision factor selection algorithm can provide a combination of high precision satellites, by applying the error compensation method to calibrating the system, high-precision navigation can be achieved.
Design and Implementation of Configurable RFID Middleware for Mobile Devices
Authors: Xu Da Wei , Yang Li Ping , Chen Xiao Ming
Published: October 2014

RFID middleware for massive data focused on the performance of server-side processing to bring pressure on the issue, a new for mobile devices can be flexibly configured RFID middleware (SMM). SMM can be used for mobile devices, has a better platform independence , can be deployed with multiple operating systems ; abstract objects by device , user via the user interface (UI) and a standard Web interface to control and manage a variety of mobile devices . Meanwhile, SMM also provides data synchronization. Experimental results show that, SMM has low energy consumption; high efficiency advantages can effectively reduce server stress and improve system performance.
Analysis and Design of Mount Tai Tourism E-Commerce Service Platform
Authors: Liu Ke , Ren Xiang , Jiang Huan Jun
Published: October 2014

In response to the Tai'an City to seize new opportunities, "building strong economic and cultural city, to create an international tourist city," the goal, to contribute to economic development in Tai'an City, combined with the current actual situation Mountain Tai tourism industry, the paper constructed Mountain Tai tourism e-commerce service platform, and to promote e-commerce operations in the country. This article fully and semi positioned Walks Walks consumer groups, unlike Ctrip, the way cattle and other typical third-party e-commerce platform, Mountain Tai tourism e-commerce service platform can be used as a third-party e-commerce platform consignment of various travel services, but also independent Tarzan become tourist attractions, the official website of Mountain Tai tourism hub, is a full range of travel e-commerce platform.
A Research of Dynamic Message Routing Based on Load Balance in ESB
Authors: Cao Min , Di Xiao Li
Published: October 2014

By analyzing the advantages and disadvantages of the existing dynamic message routing model in ESB,propose a new dynamic message routing model based on load balance. This paper applied the message routing components in the Enterprise Integration Patterns to the routing model of ESB.By using abstract routing table and real-time service monitoring and load balance strategy,the system efficiency has been improved.The experimental results demonstrate the effectiveness of this model.
The Distribution of Interests in the Course of Urbanization of Land Requisition: Problems and Countermeasures
Authors: Zhu Hong , Liu Jia Peng , Tang Xiao Ling , Yi Rong Hua
Published: October 2014

In cities and towns across the country the current movement is carried out like a raging fire, we often can see many from all kinds of news media in the land expropriation unfair now. The author collected the first-hand information by investigation, the analysis of relevant data. Considering the limitations of the data collected, this paper on the basis of the existing theory, discusses the interest distribution problems of local government, the village committee and the farmers whose land has been expropriated between these three subjects. Through the study of the subject, combined with the reality of research results, the reason the farmers' interests for farmers' cognition of the value of the land is not complete, relevant legal deficiencies, asymmetric information and government compulsory treatment. Then put forward the following 5 measures, use simple language and real data to put forward suggestions for perfecting the land requisition system.
Construction of Interactive Interpretation Study Website Based on WebRTC Technology
Authors: Wang Yue
Published: October 2014

According to interpretation learning theory and skills, this paper constructs a platform of interactive interpretation study on website, aiming at building an open, systematic and interactive training platform for users to practice interpreting without time or space limitation. The web is consisted of five modules, listening and comprehension, memory, figures conversion, language reconstruction and interpreting, which constitute the fundamental steps of acquiring interpreting skills based on the skill-centered theory. Moreover, with Web Real Time Communication (WebRTC) technology and HTML5 development platform, interactive study function on the web enabling users to practice together can be finally realized.
LTE Downlink Channel Estimation Base on DCT
Authors: Wang Yong , Wu Pan Fei , Xiong Guo Qing
Published: October 2014

The long term evolution (LTE) system is a high data rate transmission system. And the channel estimation is critical to it. In this paper, a novel channel estimator on the basis of Discrete Cosine Transform (DCT) method is presented for LTE. It can mitigate the aliasing error caused by spectral leakage well and is applicable for non-integer sampled channel because DCT can reduce the high frequency component. Its performance is much better than LS method and close to LMMSE method, and the complexity is much simpler than LMMSE. The simulation results show that the DCT-based method is superior to the traditional channel estimation algorithm in the multi-path Rayleigh fading channel which is a available and effective channel estimation method.
Performance Analysis of Synchronization Detection Algorithms in TD-LTE Cell Search
Authors: Wang Yong , Xiong Guo Qing , Wu Pan Fei
Published: October 2014

This paper mainly studies the TD-LTE cell search synchronization process. The synchronization process is mainly divided into the Primary Synchronization and the secondary synchronization detection process synchronization process. This paper present a mixed-correlation primary synchronization detection algorithm and Non-coherent secondary synchronization detection algorithm. Mixed-related synchronization detection algorithm can reduce the impact of frequency offset and multipath effects of detection. Non-coherent detection algorithm can reduce computation complexity so that it can improve the secondary synchronous detection rate.
Multi-Node Cooperative Transmission over Content Centric Networking
Authors: Ding Li , Zhu Ming , Wang Jin Lin
Published: October 2014

In this paper, we present our implementation and evaluation of multi-node transmission over Content Centric Networking, which is realized by CCNx project. As there are no client-server connections in CCN, it offers the possibility to transfer data from multiple nodes as well as multiple links in parallel. However, in the current strategy of CCNx, even if there are many nodes who store the video files the client needs, the CCNx may choose one node to transfer the resource at one point, resulting the waste of other links .Thus we try to split video files into fragments. Multi-nodes will cooperate together to transfer the fragments As there are more than one nodes transferring the different fragments at the same time, each link can be made fully used and the transfer performance can be improved in some ways.
Application of Machine Vision in ARM Based on OpenCV and Qt
Authors: Yin Shun Jian , Xia Ding Chun , Ma Jun
Published: October 2014

Based on the research of Linux kernel file system and embeded development environment, to build the Linux root file system from the bottom, to complete the development environment of Qt and Opencv dynamic library transplantation, through the efficient development platform and streamlined building the file system, realize the use of fewer resources to complete the application of machine vision in the ARM development board, make contributions to the future development of intelligent mobile terminal.
Build a Fully Distributed Hadoop Cluster Based on VM Scene
Authors: Zhang Yun , Yao Yu Xia , Yang Ji
Published: October 2014

Hadoop learners is limited by practical problems such as hardware devices, the paper intends to solve the multi-machine build Hadoop distributed cluster in VMWare virtual environment. In this paper, three hosts as an example, the research includes the design of the node and network topology, the installation and configuration of the virtual machine, SSH free password login, installation, configuration and management of Hadoop.