Earticle

There exists the problem of low accuracy, instability and costly mobile communication positioning in GPS navigation. The vision orientation system as an auxiliary navigation method can realize the function of high precision positioning within a large range. This paper introduces a matching constraint and layer-by-layer search structure which is suitable for GPS vision navigation system, and puts forward a feature aided multi-stage matching algorithm. The algorithm firstly makes the match of the more obvious characteristics points, then the matched points information are used to determine the subsequent points general disparity range through the geometric constraints, thus improving the matching speed and accuracy. Using different types of outdoor natural topographic map matching experiments were conducted. Experimental results show that the multi-stage matching algorithm introduced in this paper is better than the basic area matching algorithm in matching accuracy and speed.

This paper presents a high performance chopper-Stabilized Two-stage operational amplifier for biomedical applications. This Two-stage is designed for low noise, low power, high PSRR and high CMRR. The Miller compensation technique (Cc) is used with a nulling active resistance (Rz) implemented using Transmission gate (TG) transistors for stable operation in feedback mode. Chopper stabilization technique has been widely used in amplifiers for flicker (1/f) noise and offsets reduction purposes using the principles of modulation and demodulation. Thus, the functionality and performance of modulation and demodulation circuits determines the realization and attainment of chopper stabilization. The operational amplifier was manufactured in a SPECTRE using GPDK 90nm CMOS technology with threshold voltages of a 0.17 V and - 0.14 V achieve a low power 2.6uW, 13.5nV /Hz at 10Hz high CMRR up to 130dB and PSRR up to 70dB at 1V power supply.

Query suggestion attracts great concern recently. It is crucial for capturing frequently asked questions in question-answering system and most popular topics in search engine. Besides these, is also used in advertising retrieval systems, e-commerce system for advertising push to get more profits. The paper gives a general review of query suggestion methods. On the whole, all the methods can be grouped into two categories: session based methods and click-through based methods. Adjacency based query suggestion, co-occurrence based query suggestion, query-flow graph based query suggestion, clustering based query suggestion, and bipartite graph based query suggestion are presented respectively in detail. Furthermore, how to evaluate the performance of query suggestion is denoted. Finally the important related issues of the area in further research are discussed.

Roadside units in Vehicular Ad hoc Networks are essential for acting as base stations that facilitate information spreading to vehicular users in the roads. Typically, vehicular nodes search for an infrastructure within their vicinity to fulfill the requested services such as internet accessing or content file handling. Due to the essentiality of the presence of roadsides as well as the high costs for installing them, determining the appropriate roadside populations is an ongoing challenge. According to the surrounding vehicular density, we aim to assure higher data throughput in order to accomplish a cooperative network. This paper considers the roadside populations as to supply vehicles’ requirements based on both a proposed algorithm and simulation results. Moreover, we study the roadside self-participation to enhance the transfer rates and achieve fair resource distribution among the requested vehicles based on coalition formation. Simulation results have proven that the variation of the roadside populations influences the data throughput. Additionally, the cooperative environment among vehicular nodes achieves higher roadside participation ratios especially in the maximum case.

Although meta-heuristic optimization algorithms have been used to solve many optimization problems, they still suffer from two main difficulties: What are the best parameters for a particular problem? How do we escape from the local optima? In this paper, a new, efficient meta-heuristic optimization algorithm inspired by wild dog packs is proposed. The main idea involves using three self-competitive parameters that are similar to the smell strength. The parameters are used to control the movement of the alpha dogs and, consequently, the movement of the whole pack. The rest of the pack is used to explore the neighboring area of the alpha dog, while the hoo procedure is used to escape from the local optima. The suggested method is applied to several unimodal and multimodal benchmark problems and is compared to five modern meta-heuristic algorithms. The experimental results show that the new algorithm outperforms other peer algorithms.

Self-validating (SEVA) pneumatic actuator is a new generation of actuator which can not only give the corresponding output according to the input control variable but also give the accuracy of the control output and status of the actuator itself and other information. A dual processor system is implemented using C8051F060 and TMS320F28335 to acquire the signals and complete fault detection, diagnosis and self-validating parameters calculating. C8051F060 is used to data acquisition and preprocessing of the actuator inner signals, and communicate with Host PC.TMS320F28335 is used to run the self-validation algorithm and fault diagnosis algorithm and transfer the self-validation outputs to C8051F060. Experimental results indicate that the sell-validating unit can acquire the actuator inner sensors data correctly in normal state and fault state. With software modification of DSP and MCU, the system can be used in data acquisition and signal processing for other actuators.

Forestry ecological projects have a huge impact on the living standard of forest farmers. Thus, information channels forest farmers choose to know about the information of these projects have great importance. The purpose of this study is to find out the main factors that influencing the adoption of these information channels of forest farmers in Western China. Rough set theory is used to solve the problem of main factors reduction. The result shows that total income from working outside, income of forestry, income of agriculture, forestry reforestation subsidy, non-commercial forest subsidy, forest seed subsidy, living expenditure and forest areas are the main factors that influencing the adoption of different channels.

This study developed a real-time remote monitoring system (RTRMS) to receive the vibration frequency of bridge pier. The system included a front station and a middle station. A multi-hop wireless routing is employed to transmit the data from the front to the middle station. The front station includes a receiver equipped to receive the vibration frequency, and a wireless sensor network to transmit the data. The middle station is designed by an embedded system for storing the data. The pressure test shows that the loss rate of received data is less than 0.6%. The consuming power of one day is 3 ampere hours in the front station and 30 ampere hours in the middle station if the 12 voltage battery is used.

With the high-speed development of China's Internet, e-commerce and network information communication make consumers on product quality of service have a more clear understanding. The competition of network sales market brought the traditional automobile sales and services the unprecedented pressure. This paper analysis the theories about customer satisfaction model both in China and abroad. All of them are expected difference theory as the core, evaluating the benefit of consumer satisfaction by perception the difference of perceived benefits and loss. On this basis, by the internet-questionnaire survey, the China internet-automobile customer satisfaction evaluation system of the bayesian model is established. From this, it can be obtained the main factors of the customer satisfaction and their influence degree.

Technological innovation talent is the core element of economic and social development. It is a symbol of a country's soft power reflected from the perspective of knowledge. Therefore it is theoretically valuable and practically significant for a country to evaluate the comprehensive level technological innovation. Based on the construction of evaluation index system of the technological innovation talents’ competitiveness, we will use BP neural network to evaluate in this paper. We determine the actual situation of the evaluation system according to the input layer, hidden layer and output layer of the model as well as the number of neurons in each layer. The number of neurons in the input layer is the number of indices of technological innovation talents evaluation. The output layer represents the comprehensive ability level and has only one neuron. However, it is difficult to figure out the number of hidden layers of BP neural networks. We use the golden section method to accurately select their layers. This can effectively avoid the problem of excessive training error due to the random selection of hidden layer. Then we illustrate the accuracy and usefulness of this algorithm with the case of the technological innovation talents of the six central provinces. Tests show that the comprehensive ability of technological innovation talents of Hubei is the most powerful in the six central provinces and is followed by Anhui. The remaining four provinces have similar levels. The actual development of technological innovation talents agree well with the experimental results.

Implementation of very large religious ceremonies in Bali demanded Hindus to be able to understand things related to Yadnya ceremony. One of the reasons why people are reluctant to participate in the Yadnya ceremony is because they does not know how to execute the ceremony. A way that can be taken is to design and make a model of the system that presented the Yadnya ceremony through Android-based information systems. The system will provide information related to activities such as execution time of Yadnya ceremony, implementation procedures, pemuput, place of ceremony, video, and images of the ceremony. Users will obtain data or information by accessing the application from the server system.

This paper took a research about the small size sample problem of the discriminant locality preserving projections method, and proposed the discriminant locality preserving projections method based on neighborhood maximum margin (NMMDLPP). Firstly, the training sample structured a weighted of K-nearest neighbor graph, and gave the weight parameter to each side of the nearest neighbor graph for obtaining the intraclass neighbors and interclass neighbors local geometry information of each point; then reduce the interval between the intraclass neighbors and increase the interval between the interclass neighbors with the result of transfer matrix, and applied the neighbor point optimal refactoring coefficient of the data to the objective function. This method chose the difference between the locality preserving between-class scatter and the locality preserving within-class scatter as the objective function to avoid of calculating the inversion of matrix. This method has conducted an experiment on the UMIST face database and Yale face database. Experimental results show that the NMMDLPP algorithm is superior to other algorithms in recognition rate. The recognition rate can reach more than 91.4%.

Cognitive method is used in this research to create portfilo of movement robot manipulator. Gradient descent (GD) fuzzy controller was used and robot’s postures and trajectory were expected in MATLAB/SIMULINK environment. Fuzzy logic controller (FLC) is an influential nonlinear controller to certain and uncertain systems which it is based on artificial intelligent and computes the required torques using the nonlinear feedback control law. Practically a large amount of systems have uncertainties accordingly this method has a challenge. Linear proportional-integral-derivative (PID) controller is a significant combination nonlinear stable-robust controller under condition of partly uncertain dynamic parameters of system. This technique is used to control of highly nonlinear systems especially in nonlinear time varient nonlinear dynamic system. To compensate for the dependence on model-free parameters, PID methodology is used. The nonlinear model dynamic formulation problem in uncertain system can be solved by using PID theorem. Proportional-Derivative-Integral (PID) theory is used to estimate the system dynamic.

After various types of emergencies, victims and rescuers will have negative psychological and mental reactions, such as stress response, psychological disorder. In this case, making the right group decision is the most important issue. It proposes the concept model of group emotional intelligence, adopts 2x2 factorial design, carries on survival experiment including 52 groups, and analyzes the influence of the group emotional intelligence on intra-group conflict, conflict management, performance, satisfaction and cohesion. Utilizes the statistical software SPSS19.0 for data analysis, and draws reliable conclusions. The conclusions offer references for enhancing emotional management capacity and problem-solving abilities of decision-making groups in emergencies environment.

Generating discernibility matrix consumes huge time and space .To solve this problem, A new Binary Discernibility Matrix (BDM) induced from information table is defined, The concept of Binary Conjunction Matrix(BCM) is then introduced, Finally A novel method for discernibility matrix using Zero-Suppressed BDDs (ZBDD) and Ordered binary decision diagrams (OBDD) is proposed in this paper, experiment is carried to compare the storage space of discernibility matrix with that of ZBDD and OBDD, results show that the new method has better storage performance and improve the attribute reduction for those information systems with more objects and features.

Robot manipulators are multi inputs-multi outputs, nonlinear and time variant system, therefore control of this system is the main challenge in robotic science. Control robot arm according to linear methodology are often having lots of problems because robotic systems are always highly nonlinear. Design accurate controller for robot manipulator is difficult because some dynamic parameters such as compliance and friction are not well understood and some robot parameters such as inertia are difficult to measure accurately and caused to variation in dynamic response. Fuzzy logic controllers have been applied in many applications. One of the important methods to solve above challenge is design adaptive controller based on fuzzy logic. In this paper, intelligent control of robot arm using Proportional-Integral-Derivative (PID) Adaptive Fuzzy Gain scheduling (PID-AFGS) is design for two degrees of robot arm.

The effects of particle size on the interface bond energy in KTa0.5Nb0.5O3/ polyimide composites were investigated using the molecular dynamics method. The composites of polyimide and the KTa0.5Nb0.5O3 nanoparticles with different size (0.4 nm, 0.5 nm, 0.6 nm, 0.8 nm, 1.2 nm, and 1.4 nm) have been established and simulated using the Forcite program package of Materials Studio software. The calculated results show that the interface bond energy is 38~150 Kcal/mol, which indicate the Van der Waals force exist between the nanoparticle and polyimide matrix. The interface bond energy of the smaller nanoparticle is greater than the lager nanaparticle due to the size effect. The introduction of the smaller nanoparticle could generate the stronger intermolecular bonding interaction between the nanoparticle and polyimide matrix.

Power function distribution is a flexible lifetime distribution that may offer a good fit to some failure data sets. In this paper, we obtain Bayesian estimators of the shape parameter of Power function distribution. For the Posterior distribution of this parameter, we consider Exponential Prior, Pareto Prior, Chi-Square Prior, Quasi Prior and Extension of Jeffrey`s Prior. The three loss functions taken up are Squared Error Loss Function (SELF), Quadratic Loss Function (QLF) and Precautionary Loss Function (PLF). The performance of an estimator is assessed on the basis of its relative Posterior risk. Monte Carlo Simulations are used to compare the performance of the estimators. It is discovered that the PLF produces the least Posterior risk when Exponential and Pareto Priors are used. SELF is the best when Chi-Square, Quasi and Extension of Jeffrey`s Priors are used.

This paper proposes a novel sliding mode control (SMC) scheme to stabilize a class of fractional-order chaotic systems. Through constructing two sliding mode variables, the control problem of n-dimensional system can be transformed to the equivalent stabilizing problem of a reduced-order system. Subsequently, on the basis of second-order sliding mode (SOSM) technique, a robust control law is designed, which strongly attenuates the chattering phenomenon inherent in traditional sliding mode controller, and guarantees the existence of sliding motion in a finite time. The stability of two sliding mode variables to the origin is proved by conventional and fractional Lyapunov theories, respectively. Finally, two numerical examples are provided to illustrate the effectiveness of the proposed approach.

The paper focus on the supply chain model with a single product in electronic and retail channel, only a supplier and a retailer in system, customers have alternatives to choose the channel that is better suited to their needs, some of them may alternatively switch to the other channel when a stock-out occurs in their preferred channel. Supplier and retailer implement one-for-one and (Q, R) ordering policies respectively to replenish their inventories. We set up the profit model of supply chain by Markov process, and study the product availability of supply chain. The result shows that the stock-out based substitution rate may increase or decrease the efficiency of decentralized supply chain; the centralized supply chain can adjust the based-stock levels timely to different stock-out based substitution rate and benefit from it, the supplier and retailer in a decentralized supply chain are more inattentive to customers’ stock-out based substitution rate, and prone to lose their benefits.

One kind of extended proportional guidance law is presented. This guidance law can be used without restriction about the motion speed of missile and target, and this is a different point with the classical proportional guidance law. In the case of random alter the tracking target curvature radius, compared with classical proportional guidance law under the proper random quantity, the normal overload of trajectory is relatively small, and has certain advantage, so the study has significant reference value in actual application. And interception time and normal overload have good performance. Tracking performance for high maneuverability target is better than the classical proportional guidance law. A target intercepting simulation based on MATLAB of the proportional coefficients and line-of-sight angular velocities is generated to analyze the trajectory properties. The effect of guidance coefficients on trajectory properties is studied. Through simulation, we simplify the problem by ignoring the actual factors so that a certain level of error is expected. The situation in practical requires more in-depth analysis and research.

At present, in the feature extraction of non-stationary vibration signals, many time-frequency analytic methods have emerged to meet the further need of non-stationary signal analysis such as Wavelet Transform (WT), Short Time Fourier Transform (STFT), Wigner-Ville Distribution (WVD), Empirical Mode Decomposition (EMD), Ensemble Empirical Mode Decomposition (EEMD) and so on. However, these time-frequency analysis methods can only be carried out on Matlab platform and the processes are of low efficiency, bringing a lot of inconvenience in signal analysis because they can not run on Windows system independently. According to the defects, a novel method of mixed programming which combines Matlab with Delphi based on COM (component Object Model) module technology is proposed to design a time-frequency analysis system for non-stationary vibration signals assembling fourteen methods. The advantages of two languages are shared with each other. In design of the system, a combined method which combines two or three analytic methods is put forward for relational analytic modules to make the analytic results more perfect and clearer, like WAVELET-FFT, EMD-WVD etc.. This paper uses the EMD-WVD combined method as an example to present the programming thoughts and processes. The effectiveness of the system is validated using a simulation signal and an experimental signal. The system can be executed separated from MATLAB environment.

In this research, we present two comparative studies; the first one is between two methods of features extraction which are the mathematical morphology, the zoning and the hybridization of these two methods. The second comparative study is between both supervised methods used in learning-classification which are the Multi-Layer Perceptron (MLP) and the Support Vector Machines (SVM) applied to cursive handwritten Tifinagh characters recognition. The obtained experimental result demonstrates that the hybrid method is most efficient and the SVM is more performing than the MLP.

The contact angle of lotus, canna, green poplar, grape and pumpkin were 150.6º, 135.5 º, 110.4 º, 101.3 º and 94.8 º respectively, five kinds of plant leaves were adhered to rectangular box by double-sided adhesive tape, which were called miniature boats. Miniature boats have super large loading capacity on water surface through the experimental measurements, loading capacity and water dimple depth increases with contact angle. Through mechanical analysis, the paper established mathematical model of loading capacity, comparing the measured values and measured values of loading capacity, the error ratio of loading capacity is about 4.0-6.1%. The loading capacity is made up of buoyancy and surface tension, percentage of buoyancy and surface tension in the loading capacity is affected by the contact angle and geometry size of miniature boats.

Waldén, Karlson, and Sun found an elegant explicit expression of backward error for the linear least squares problem. However, it is difficult to compute this quantity as it involves the minimal singular value of certain matrix. In this paper we present a simple estimation to this bound which can be easily computed especially for large problems. Numerical results demonstrate the validity of the estimation.

Over a period of time, there are different types of multipliers used to minimize cost of constructive parameters in digital FIR filter design in different forms. In these multipliers truncated multiplier design play’s an essential role. Due to multiple adders and delay elements the circuit in transpose form occupies more area and consumes power. In the proposed method effectiveness in different parameters are achieved with low cost, high speed and effective results are done by faithfully rounded truncated multipliers with operations of carry save adder. Direct form of FIR filter utilizes based on MCMAT for multiplication and accumulation operations; it will reduce the area by decreasing the number of different components like structural adders and registers. By using MCMAT operation in the digital FIR filters, optimal results can be obtained in terms of power and area specifications. The proposed 12 bit Arithmetic and Logic Unit is designed along with MCMAT based digital FIR filter for reducing area and increasing speed in real time applications.

In order to improve the detection accuracy of wavelength, the filtering and curve fitting technologies were applied in the FBG wavelength demodulation system based on tunable F-P filter. These methods could realize the accurate peak-location of output signals of the photo detector. According to the characteristics of noise, the FIR low-pass filter was designed to filter the obtained light power signals so as to provide the input signals with high SNR for the peak-detection algorithms. By analyzing and comparing several typical peak-searching algorithms, the algorithm of Gauss formula nonlinear curve fitting (L-M) was chosen to fit the digitized light power signals. The experimental results show that L-M fitting algorithm reduces the mean square error by 7.5% compared with the Gauss fitting algorithm. For the Gauss signal in the wavelength demodulation system designed in the paper, the L-M algorithm has lower mean square error than other peak-searching algorithms. This algorithm is suitable for FBG wavelength demodulation system based on tunable F-P filter. It can efficiently raise the accuracy of wavelength demodulation system.

Block matching (BM) motion estimation plays a very important role in video coding. In a BM approach, image frames in a video sequence are divided into blocks. For each block in the current frame, the best matching block is identified inside a region of the previous frame, aiming to minimize the mean square error (MSE). Unfortunately, the MSE evaluation is computationally expensive and represents the most consuming operation in the BM process. Therefore, BM motion estimation can be approached as an optimization problem, where the goal is to find the best matching block within a search space. Recently, several fast BM algorithms have been proposed to reduce the number of MSE operations by calculating only a fixed subset of search locations at the price of poor accuracy. The parallel cat swarm optimization (PCSO) & enhanced parallel cat swarm optimization (EPCSO) methods are an optimization algorithms designed to solve numerical optimization problems under the conditions of a small population size and a few iteration numbers. In this paper, a new algorithm based on Hybrid Cat Swarm Optimization (HCSO) is proposed to reduce the number of search locations in the BM process. In proposed algorithm, the computation of search locations is drastically reduced by adopting a fitness calculation strategy which indicates when it is feasible to calculate or only estimate new search locations. Conducted simulations show that the proposed method achieves the best balance over other fast BM algorithms, in terms of both estimation accuracy and computational time and find the optimal solutions in a very short time.

With the development of the computer technology, many retailers sale the products not only in the entity shop, but also in the online shop. The network channel brings a lot of convenience. However, it also produces the channel conflict. In the dual channel supply chain, the retailers are in a passive position. Therefore, they begin to use the optimal dynamical pricing strategy to determine the price of the products. At the same time, the retailers obtain the greater benefits according to reduce the inventory cost. Thereby, in this paper, considering the online channel preference, we study the inventory strategy and the pricing strategy of the products in the dual channel. And then we propose a shared inventory and a dynamical pricing strategy. In addition, we study the influence of the related parameters on the profit of the retailers. At last, the numerical analysis shows that the shared inventory and the dynamical pricing strategy can bring more profits for the retailers.