Earticle

STUKF (Strong tracking UKF) algorithm uses the time-varying fading factor to fade the past data and reduce the impact on current filter value, thus achieves the goal of adjusting the filter gain matrix in real time. But STUKF algorithm needs three UT for each filtering, and compared with the UKF filter, calculating amount of three UT increases seriously, and it is not conducive to application of engineering, therefore this paper presents an improved STUKF algorithm. Compared with the traditional STUKF filter, this new algorithm introduces the formulas of redefined fading factor. By changing the position of the fading factor, it improves the accuracy and robustness of the algorithm and reduces the computational complexity of the algorithm. Finally simulation results show that the new algorithm has higher precision and stronger robustness.

By employing a simplified bilinear method, a class of generalized fifth-order KdV (gfKdV) equations which arise in nonlinear lattice, plasma physics and ocean dynamics are inves-tigated. With the aid of symbolic computation, both solitary wave solutions and multiple-soliton solutions are obtained. These new exact solutions will extend previous results and help us explain the properties of nonlinear solitary waves in many physical models in shallow water. Parametric analysis is carried out in order to illustrate that the soliton amplitude, width and velocity are affected by the coefficient parameters in the equation.

In this paper, a new chaotic neural network model is proposed, we introduce a Bessel function as self-feedback term in this model, Compared with other chaotic neural network model, owing to the Bessel function is a nonlinear function with good nature, and it has stronger function approximation ability, so that the novel chaotic network model has stronger traversal search ability. When it is applied to solve combinatorial optimization problems, the simulation results show that the network has better ability to avoid network convergence to local minima if the appropriate coefficient of expansion and the network has been taken, so the efficiency of network optimization capability is improved.

When developing software, user interfaces are often designed with a general user in mind – which can result in applications with interfaces that are difficult to use for those with different abilities. Older adult users, for example, often encounter impairment of their physical and cognitive abilities as they age, which means they look for different features in user interfaces when compared to a younger user. Adaptive interfaces can be incredibly helpful for users in these situations – rather than being forced to conform to an application’s user interface offering, an older user can change the user interface to match what works best for them. However, the increased use of mobile devices means that users often have more than one computing device, and thus, often are running more than one instance (or a mobile and desktop instance) of a particular application. The use of cloud storage would be very beneficial in synchronizing settings from one instance of an application, across multiple devices. In doing so, we ensure that an application remains usable for an older individual across a wide variety of devices, and across platforms. In this paper, we explore the features such a cloud storage system would need to consider, in order to bring interface settings together across a variety of connected devices and keep computers up to date with the users’ preferred interface.

Aerobics has been broadly adopted in colleges and universities in our country. For aerobics can be better able to carry out, the performance prediction is very important. Aiming at the problems that the predictive model is often mismatching and difficult to solve the nonlinear optimization function of nonlinear system model of predictive control, an online support vector machine (OSVM) modeling is proposed. This proposed method builds a nonlinear model for objects using OSVM. Furthermore, we apply this method to the performance prediction of the aerobics. The results show that the online-SVM applying to the aerobics performance prediction is feasible and effective.

This paper achieves information-capture of join points by analyzing Java program with AspectJ. This information includes: method call, parameter values passed in method call, captured value of reference “this” when method is executed, the time when this references a specific type problem, and the time when the target object of the join point is a specific type.

The condition of an inaccessible gear in an operating machine can be monitored using the vibration signal of the machine measured at some convenient location and further processed to unravel the significance of these signals. Demodulation is an important issue in gearbox fault detection. Non-stationary modulating signals increase difficulties of demodulation. Though wavelet packet transform has better time–frequency localization, because of the existence of meshing frequencies, their harmonics, and coupling frequencies generated by modulation, fault detection results using wavelet packet transform alone are usually unsatisfactory. This paper proposes a fault detection method that combines Hilbert transform and machine learning method namely support vector machines (SVMs). The statistical feature vectors from Hilbert transform coefficients are classified using J48 algorithm and the predominant features were fed as input for training and testing SVM and their efficiency in classifying the faults in the Bevel Gear Box was studied.

Addressing to improve the trustworthiness of Business Process Re-engineering (BPR) system, this paper proposes a trustworthy construction approach to solve the problem mentioned above. Firstly, we analyze related literatures about the topic, we realize that main reason causing to reduce trustworthiness of BPR system is due to break of trustworthy connectivity between front configuration tools and business processes operating server. Secondly, as the primary methods composing of the construction approach, a semantic verification method is illustrated in detail based on Petri net. Finally, a case study is introduced to explain how to use the above construction approach of BPR system.

Large volumes of short reads of genomic data are generated by high-throughput sequencing instruments. The FASTQ format is widely accepted as the input format of genomic reads and has presented challenges in data storage, management, and transfer. The performance of this type of serial algorithms such as G-SQZ and DSRC is limited by the single processor and the memory in a single computer. Utilizing data parallelism, the circular dual queues of buffers, memory mapping integrated with superblocks, pipeline parallelism with multi threads, and so on, we present the parallel compression and decompression methods for DNA sequence reads in FASTQ format based on the parallel computer architectures of the cluster and the SMP. Experimental results for the parallel DSRC algorithm clearly show the efficiency of using the powerful computing resources from multi computing nodes and multi cores of each node. The speedups vary from 46 to 62 for parallel compression and vary from 40 to 58 for parallel decompression by using 10 nodes of the cluster in Tianhe-1A super computer. Test results on the SMP machine are also pleasant. The methods could be applied to any serial compressing algorithms of DNA sequence reads in FASTQ format only if they have the traits of index and superblocks.

As wind energy becomes a larger portion of the world’s energy portfolio and wind turbines become larger and more expensive, wind turbine control systems play an ever more prominent role in the design and deployment of wind turbines. The goals of traditional wind turbine control systems are maximizing energy production while protecting the wind turbine components. As more wind generation is installed there is an increasing interest in wind turbines actively controlling their power output in order to meet power set‐ points and to participate in frequency regulation for the utility grid. This capability will be beneficial for grid operators, as it seems possible that wind turbines can be more effective at providing some of these services than traditional power plants. Furthermore, establishing an ancillary market for such regulation can be beneficial for wind plant owner/operators and manufacturers that provide such services. In this tutorial paper we provide an overview of basic wind turbine control systems and highlight recent industry trends and research in wind turbine control systems for grid integration and frequency stability.

The ability to rapidly assess the loss of earthquake-stricken area after an earthquake in the absence of on-site information is of significant importance. Due to the unique geology, geomorphology, building structures as well as the social and economic situation in Yunnan, it makes the loss of building and casualties having some differences with other regions when the earthquake occurred. Based on the regional characteristics of Yunnan, this paper assesses the area of destroyed houses, economic loss, the number of earthquake deaths and number of homes lost using multiple models-a building earthquake death model, a destroyed houses model, an economic loss model and a homes lost model. This inturn allows the distribution pattern of the various losses to be displayed on a map by integrating the evaluation model and GIS technology. The value of spatial distribution is more important than simple statistical data as spatial distribution helps us understand the distribution of earthquake damage thus allowing targeted command decisions to be made for technical support of earthquake victims and earthquake-affected areas.

Recently, with the dramatic popular of geo-social networks and location based services (LBS), more and more mobile users are willing to enjoy the proximity services, which is a friend-alarm when the buddies happen to be in proximity. However, the services provider (SP) and some compromised buddies could try to steal the user’s exact location information. Hence, location privacy preserving is still a challenge question in proximity based services. Unfortunately, existing methods only consider Euclidean distance to calculate neighbors, which would bring great deviation for distance measurement in the actual terrain. To my knowledge, this article is the first time extending to the 3D surface and proposes a novel technique for the privacy-preserving proximity services. The technique utilizes simplicial triangulation decomposition on 3D surface, and the user's location is generalized with a triangular area space, then a more precise proximity distance measurement method based on the triangle fractal is proposed. Next, we design a privacy-preserving proximity query protocol, which provide complete privacy with respect to the SP and the buddies. Final, the experiments shows that our methods have practicality in the services quantity and privacy.

Friction Stir Welding (FSW) has been applied to AA5754-H111 alloy. An in-depth analysis of the influence of the process parameters has been performed using Taguchi method. Through the optimization of the process parameters it has been observed what the best process conditions for the different mechanical properties. It was observed that for tensile properties the best that lower advancing speeds and lower applied forces would be more beneficial to obtain a better tensile behavior. On the other hand, the higher advancing speeds and higher applied forces have proven to give a better bending behavior. The optimization algorithm has proven to be efficient giving welded samples with 98% efficiency, very close to the base material behavior. The corrosion testing has proven that these alloys are very resistant to corrosion although some caution should be taken regarding the “root defect”.

Computer game is a vibrant research area in artificial intelligence. Chinese chess game is an important part of computer game and it has become an important study area after chess game had reached its culmination when Deep Blue and its successors beat Kasparov. Some achievements acquired in Chinese chess game have applied into fields of medicine, economics and military. This paper presented a new method of optimizing evaluation function in Chinese-chess programming by particle swarm optimization. The process of training evaluation function is to automatically adjust these parameters in the evaluation function by self-optimizing method accomplished through competition, which is a Chinese-chess system plays against itself with different evaluation functions. The results show that the particle swarm optimization is successfully applied to optimize the evaluation function in Chinese chess and the performance of the presented program is effectively improved after many trains. We also examined the importance of the place control in the evaluation function by the comparison the optimizing results with and without the control of the place and showed the comparison result.

This paper puts forward on a fast distributed information fusion predictive control algorithm for the time-varying system with unknown stochastic system bias. It is based on the distributed fusion estimation algorithms and state-space model. The optimal information fusion rule for this algorithm is weighted by matrices, diagonal matrices and scalars. It can avoid the complicated Diophantine equation, thus obviously reduces the amount of calculation. Via the distributed information fusion algorithm, the comparison of algorithm in this paper with the local sensor, this algorithm improves stability and accuracy for the time-varying system with unknown stochastic system bias. By testing through the three-sensor target tracking control system simulation, this algorithm shows its effectiveness and correctness, and the results of simulation also show no significant difference in error between the three kinds of distributed fusion algorithm. With reduction of calculation using the scalar weighting fusion predictor, the information fusion estimation algorithm presented in this paper also improves the calculation speed and accuracy.

Recently, several chaotic based image encryption schemes have been proposed, each of them has its own strengths and limitations more or less in terms of security level and computational speed. In this paper, a novel approach for image encryption based on a 2-D Zaslavskii map and Pseudo Hadmard transform is proposed. The encryption process is composed of two stages, i.e. permutation and diffusion. The permutation is achieved by scrambling rows and columns using chaotic values. This stage substantially reduces the correlation between neighboring pixels. During diffusion, the avalanche effect is achieved with 2-D Pseudo Hadmard transforms followed by diffusion in two directions (forward and backward) with multiple additions and xor operations. This stage ensures resistance against differential attacks. The security and performance of the proposed method is analyzed thoroughly by using key-sensitivity, key-space, statistical, entropy, differential and performance analysis. The proposed scheme achieves the required level of security with only one round of encryption operation. Hence the proposed method is computationally fast.

Recently years have witnessed the development of cultural enterprises. As one of the most valuable intangible assets, goodwill valuation for cultural enterprises has gained a lot of attention. An efficient method is to use Wavelet Neural Network (WNN) model for learning the predicted value of goodwill given a set of indicators. However, there are some issues of the basic WNN model. On one hand, the randomly determination of the initial state of the neural network leads to the possibility of converging to a local optimal point. To solve this problem, we propose to employ Genetic Algorithm (GA) for optimizing the initial parameters before model training. On the other hand, the training cost of basic WNN is typically big and its convergence speed is relatively slow. To accelerate the convergence speed, we introduce Levenberg-Marquardt (LM) algorithm for training. Besides, we conduct experiment to evaluate the performance of our proposed GA-LM-WNN algorithm.

Discrete Cosine Transform (DCT) is widely used in image and video compression standards. This paper presents low-power co-ordinate rotation digital computer (CORDIC) based reconfigurable discrete cosine transform (DCT) architecture. All the computations in DCT are not equally important in generating the frequency domain output. Considering the important difference in the DCT co-efficient the number of CORDIC iterations can be dynamically changed to reduce the power of consumption with improved image quality. The proposed CORDIC based 2D DCT architecture is simulated using Modelsim and the experimental results show that our reconfigurable DCT achieves power savings with improved image quality.

As a new power transmission technology, magnetically coupled resonant wireless power transmission technology can achieve mid-range wireless power transmission with the advantage of high transmission efficiency. As known, the driving source has a significant impact on the overall performance of wireless power transmission system. With this consideration, a pulse-driven magnetically coupled resonant wireless power transmission system is proposed herein. The circuit model of the system is established on mutual inductance coupling theory. Through the analysis of its working mode the mathematical models of load power and transmission efficiency are established and the relationships among load power, transmission efficiency and driving signal frequency, duty cycle and transmission distance are revealed. Subsequently, a pulse-driven magnetically coupled resonant wireless power transmission prototype is designed and the experiment is conducted by using control variables method. The authenticity of the theory is verified as well by experiments. In the experiment, the system realizes wireless power transmission of load power 1.17W and transmission efficiency 76.13% under the condition of DC voltage 12V, driving signal frequency 94 KHz and duty cycle 15%.

Fog is a combination of two components airlight and direct attenuation, degrades the picture quality and creates a lot of problem in video surveillance, tracking and navigation. Thus, to remove it from an image, various defogging methods have been proposed in literature. Defogging can achieved using multiple images and single image fog removal method. One of the prominent methods in literature for defogging is Dark Channel Prior (DCP). This method though quite effective in removing fog from images has very high time complexity. In addition, it does not preserve edges and has halo effect. Therefore, this paper proposes a new technique which overcomes the disadvantage of DCP and at the same time preserves the picture quality. The proposed method is implemented in MATLAB-09 and the simulation results show the proposed method is quite good.

At present, quality of service (QoS) has become an important guidance in selecting a satisfactory web service when many similar web services provide overlapping or identical functionalities. Therefore people have carried out many studies on definition and standardization of QoS properties and QoS-based selecting algorithms of web service. Current web service selection usually adopt linear weighted algorithm. But it still has some limitations. This paper proposes a new QoS-based algorithm developed from traditional linear weighted algorithm for web service selection. The main improvements include removing distinction of QoS properties value tendency, selecting fixed value and a hybrid subjective-objective approach to set the weight of each QoS property. We also present the analysis of the time complexity. Finally we do a comparison experiment between our algorithm and traditional algorithm. The results show that the improvements are feasible and our algorithm has better performance.

A virtual form is an abstraction that enhances existing products and services by adding a layer to virtualize them. From a technical point of view, the current information technologies already make it possible to develop a virtual form using various techniques that represent information such as augmented reality technologies or ubiquitous display technologies. The virtual form can return a immediate feedback to a user so that it becomes a good design tool to develop games deployed in public spaces. We believe that incorporating fictional stories into virtual forms offers a new possibility for gamifying and enriching user experiences. However, only technological approaches cannot offer an ideal solution to develop attractive products and services if people do not feel values on them, and the design patterns for virtual forms is not well defined, especially, when a fictionality is incorporated. The design patterns needs to take into account a semiotic aspect of a virtual form. One key factor, in particular, is how strongly we believe in the reality of a fictional story within the virtual form from the semiotic aspect. This paper proposes some design patterns to integrate fictional stories into the real world for gamifying intelligent daily environments. The proposed design patterns cover three aspects. The first aspect is to exploit visual reality. The second aspect is to exploit ideological messages in fictional stories. The third aspect is to compose multiple fictional stories. The paper also shows a case study to motivate and gamify to join the Haiku contest by increasing the awareness of the importance of the contest, and show the effectiveness of the proposed design patterns.

The main idea of Regular Sequences of Similar Algorithm based on Sparse Linear (HR Algorithm) is to calculation the near optimal solution from the solution of sparse integer programming model. The advantages of HR algorithm are simplifying the problem of huge solution space of integer programming, reducing the number of goal constraints, and turning the problem into a simplified integer programming. The near optimal solution, which is hard to apply accurate method, can be found under limited time by using HR algorithm based on regular sequences.

This paper proposes a new clustering algorithm that combines genetic algorithm and chaotic particle swarm optimization with fuzzy C- means (GCQPSO-FCM), in order to solve the issue that the fuzzy C- mean algorithm is sensitive to the initial value. First, make full use of genetic algorithms to calculate the optimal number of clusters of sample population and select a valid criterion function as a fitness function; Furthermore, introduce chaos strategy in particle swarm algorithm to improve the algorithm global search ability, also contribute to the particles are more easily jump out of local bondage. Two speed factors are defined to accelerate the convergence, which also improves the performance of the algorithm. Experimental results show that our improved GCQPSO-FCM algorithm is better in efficiency and quality than the original algorithm.

Protection system is used to protect components against fault as fast as possible and also to minimize the area around it from fault. Nowadays because of the existence of Distributed Generation in power system, a change is needed to be implemented for protection system at distribution network in order to ensure the electricity can be supplied to the consumer safely. With the presence of distributed generation (DG) units in distribution systems, the function of relay protection is generally going to be changed. In this paper the impact of installing Dis-tributed Generation in radial system on the directional over-current protection relay, in pres-ence of a Thyristor Controlled Series Capacitor on fault courant is investigated. The relays coordination scheme was developed through analysis for three fault location scenarios. A realistic feeder system for a case study with its scheme protection is developed in Matlab software environment.

Users’ similarity mining in mobile e-commerce systems is an important field with wide applications, such as personalized recommendation and accurate advertising. Moving trajectories of e-commerce users contain much useful information, providing a very good opportunity for understanding the users’ interesting and discovering the similarity between mobile-device-holders. In this paper, we explores the problems in the existing mobile e-commerce recommendation methods, and propose a mobile users’ moving trajectories mining based user similarity discovering approach for mobile e-commerce system. We formally defines the moving trajectory and view the areas, where users stay within for a certain time, as interested regions, which reflect the preferences of mobile-device-holders. Based on the number of overlapped interested areas, a user similarity measure method is proposed. Experimental evaluation, conducted based on the publicly available datasets commendably demonstrate the effectiveness of our approach.

Cooperative communication is a fourth generation novel scheme promising significant capacity and multiplexing gain in wireless communication. This paper derives the carrier to noise interference ratio (CNIR) and average bit error rate (BER) for orthogonal frequency division multiplexing (OFDM) based amplify and forward (AF) and decode and forward (DF) scheme over Nakagami fading channels. Numerical results are provided to show the significant improvement of DF in OFDM based cooperative communication due to same frequency offset and phase noise.

The paper provides an improved evolutionary strategy (ES) of genetic algorithm (GA) on the basis of the existing literature. The ES overcomes the shortage of traditional GA whose excellent child individuals obtained in the crossover process may not survive in the process of mutation. In addition, the crossover probability and mutation probability which is hard to determine in traditional GA is removed for this proposed strategy. At the same time, it increases the number of individuals produced in process of crossover. This may increase the possibility of producing excellent individuals, thus lead to better improvement of the traditional GA. The test result of finding the optimal values of four functions using transitional GA and the proposed GA is presented in this paper. The result shows that the improved ES presented in this paper has faster calculation speed and significantly smaller number of iterations than the traditional GA. Thus, the improvement of improved ES is powerfully illustrated. Based on articles in the existing research literature, the initial population generation methods were further explored when using the genetic algorithm(GA) for solving constrained optimization problem. Through the research we present a new method about initial interior point’s generation. Firstly, construct a constraint posed by the objective function, which is based on the characteristics of constrained optimization problems. Then translate the problem of evaluating the initial interior point into a problem of solving a series of unconstrained optimization. By solving the unconstrained optimization problem, we achieve the solution of the initial interior point. Based on this idea, the research has given a method on the generation of the rest initial population individuals. In addition, through the research we concluded that the key to generate the initial population is to obtain an initial point. The production of other individuals will take less time after the initial internal point is obtained. Finally, we verified by examples that the initial population generation method given by this paper is a fast and reliable method. Thus the shortage of the GA of which the initial population is difficult to be produced in some constrained optimization problem is overcome

A new compact and wideband multi U-slotted microstrip patch antenna with improved bandwidth is presented in this paper. The antenna is resonating at the center frequency of 4.2 GHz with return loss of -40 dB. The proposed antenna provides an impedance bandwidth of 110% and VSWR ≤ 1.02 which is close to unity. The proposed antenna is excited by coaxial feed and analyzed by using HFSS software. The proposed multi U-slotted microstrip antenna is suitable for Bluetooth, Wi-Fi, WLAN, WiMax wireless communications.

In order to improve the traffic visibility in haze weathers, a Retinex algorithm based on the changing scale for haze removal with a depth map is proposed. It requires the haze image dark channel prior treatment to obtain the estimated depth map. Then it is according to the depth map to calculate Retinex scales for different parts of a hazy image. Finally a single scale Retinex transform is performed for each part of the image. Experimental results show that the algorithm can effectively improve the traffic visibility of hazy images without halo phenomena. Compared with the existing multi-scale Retinex algorithm MSR, it has the higher speed and better enhancement effect for the images that have greatly different scene depths.