Earticle

In present research, the image feature based on adaptive wavelet has been widely used in the content-based image retrieval field. However, there is a common problem in these methods, which is to describe different query images with the same wavelet basis. In order to improve the adaptability of the image retrieval technology, we design different image basis for different query images, to achieve characterizing the feature-changing of different image categories with the adjustable distance measure. We also use the approximate Taylor expansion to reduce the seeking time of the characterization image and the characterization derivative image. As the experimental results have shown that, the new image retrieval technology with high adaptability can improve the retrieval performance greatly.

Particle swarm optimization (PSO) is an artificial intelligence (AI) technique that can be used to find approximate solutions to extremely difficult or impossible numeric maximization and minimization problems. Particle swarm optimization is an optimization method. It is an optimization algorithm, which is based on swarm intelligence. Optimization problems are widely used in different fields of science and technology. Sometimes such problems can be complex due to its practical nature. Particle swarm optimization (PSO) is a stochastic algorithm used for optimization. It is a very good technique for the optimization problems. But still there is a drawback that it gets stuck in local minima. To improve the performance of PSO, the researchers have proposed some variants of PSO. Some researchers try to improve it by improving the initialization of swarm. Some of them introduced new parameters like constriction coefficient and inertia weight. Some define different methods of the inertia weight to improve performance of PSO and some of them work on the global and local best. This paper transplants some of the parameters used to enhance the performance of Particle Swarm Optimization technique.

In most previously reported studies on pseudonoise (PN) code acquisition, independent additive noises have been assumed in various noise environments. The use of an independent observation model may cause considerable performance degradation in modern high data-rate communication systems. In these studies, only additive noise model is considered. In this paper, a new detector for PN code acquisition in multiplicative and weakly dependent non-Gaussian noises is proposed. Modeling the acquisition problem as a hypothesis testing problem, the test statistical is derived for multiplicative and weakly dependent non-Gaussian noises, based on the locally optimum detection technique. Numerical results show that the proposed detector can offer substantial performance improvement over the conventional schemes in multiplicative and weakly dependent non-Gaussian noises.

In order to promote the overall innovation efficiency and running effect of the equipment manufacturing industry effectively which we focus on cultivating and developing strategic in China, overall innovation efficiency and running effect of sampling data is completely evaluated and analyzed by establishing the data analysis of the DEA model and using the Malmquist index analysis method based on the representative data samples of some equipment manufacturing industries in Heilongjiang province in China in 2003-2012.Analysis result shows the overall innovation efficiency characteristics of the equipment manufacturing industry in Heilongjiang province, illustrates the related factors which influence the improvement of the innovation ability and incensement of its growth rate of the equipment manufacturing industry in Heilongjiang province. The study provides the necessary theoretical basis for clarifying the development state of equipment manufacturing industry in Heilongjiang province, points out the strategic development of the development of equipment manufacturing industry and the development direction of overall innovation.

Testing is the one of the crucial phase that is performed during software development. It is done to validate the quality of the software testing using minimal cost, efforts and to generate high quality test cases. It is impossible to test software with all the possible inputs. Hence there is a need to select and reduce test cases that will find as many faults as possible. This paper will describe a method for optimizing software testing Using hybrid meta-heuristics that is by the combination of particle Swarm optimization technique and genetic algorithm, an algorithm has been

In recent years, with the rapid development of China's nuclear power industry, nuclear generator has also been actively developed. Because the unit capacity of the generator is increasing, so working life and operational reliability of the generator are also being tested. Among them, transient thermal running ability of the generator is one of the key factors affecting working life and operational reliability of the generator. This paper mainly analyzed the negative sequence current and the transient negative sequence component of the generator during asymmetric operation, and elaborates the principle of the generator negative sequence component harmonic. The paper has reference value for in-depth study of the generator negative sequence component.

The dielectric constant of the thin films of CdS nanoparticles grown in polymer matrix (PVA) deposited on Si substrates has been studied at room temperature as a function of frequency under vacuum (10-3 Torr). The samples of CdS nanoparticles have been prepared with different particle sizes and dispersibilities (η) by varying the chemical bath deposition temperature. The room temperature dielectric constants of the CdS-PVA composites lie in the range 120 to 255 at high frequency range (>1 kHz) which are much higher than that of only PVA having dielectric constant ~28 and CdS having dielectric constant 8.9. The dielectric constant of the films increases with the decrease of particle size.

Emergency response is a complicated process that requires substantial knowledge, information support and multi-subject collaboration. This paper focuses on the analysis and design of a system for emergency responders in charge of task planning, coordinating and controlling the actions in crisis response. Based on system science theory, we analysed the characteristics of emergency decision-making in times of disaster and discussed the process and internal architecture of the resulting system for developing an emergency plan. We also provide a basic analysis framework for multi-layer, multi-subject and multi-task emergency planning in times of disaster. We designed the structure and process of an emergency planning system. Consistent data standards are critical for such a system, and many analyses of crisis response reveal that the lack of such standards hinders efficient critical information flow among incident responders. Therefore, using a team collaborative perspective for emergency planning, we developed an emergency information and plan model for general emergency planning based on the hazard emergency domain and plan ontology concepts. This is a basic utilitarian model for the hierarchical collaborative emergency plan process. We also developed a prototype system and tested its validity for multi-subject task planning.

In present research work the effect of insert nose radius and machining parameters including cutting speed, feed rate and depth of cut on surface roughness(Ra) and material removal rate(MRR) in a turning of HSS(M2) are investigated using the Taguchi method and ANOVA. A three level, four parameter design of experiment,L9 orthogonal array using Minitab 14 software, the signal-to-noise (S/N) ratio is employed to study the performance characteristics in the turning of HSS(M2) by taking nose radius of Tin coated carbide inserts tool of 0.4,0.8 and 1.2 mm on CNC turning centre. The analysis of variance (ANOVA) is applied to study the percentage contribution of each machining parameters while CNCturning of HSS (M2) material. The all experimental trials are conducted in dry machining environment and at a constant spindle speed 2800 rpm.The results are verified by taking confirmation experiments. The present investigation indicates that feed rate and nose radius are the most significant factors in case of material removal rate and surface roughness for turning of HSS (M2) material.

Water samples were collected from two sites (Urdana Nala and Moti Nala) in Jabalpur city, were analyzed for their physio- chemical characteristics. This analysis result was compared with the WHO & United State Sanility labolatory standards of irrigation/drinking water quality parameters with the following water quality parameters namely pH, Electrical conductivity, Cu, Cr, SO4, Fe, NO3, Chloride, TH, TA, Na. The statistical analysis like Factor Analysis (FA) and Principle Component Analysis (PCA) of obtained data were carried out. The PCA extract and to define the parameters responsible for the main variability in water quality variance for Jabalpur city. Moti Nala and Urdana Nala water constrains high Na ions. But Cu, Cr, SO4, Fe, NO3, Cl, TH are within limits. TA is higher in most of the samples. The PCA produced more important parameter NO3, Cr, Fe, TH, Na, EC, SO4, Na in Urdana Nala site. NO3, Cu, Na, Fe, TA, pH, SO4, TH, Cr in Moti Nala site. Finally the results of PCA reflect a good look on the water quality monitoring and interpretation of the surface water.

In the field of information security, chaos algorithm and its application in hardware encryption have important significance. The paper here takes a normally used Lorenz chaotic system as an example and introduces its FPGA hardware circuit design; generation and download method, then, statistical tests and instrument test are done. Through the test, it is demonstrated that the chaotic sequence generated by the circuit has good statistical properties and chaotic characteristics. By this way, researchers can easily and quickly get and test chaotic sequences in experimental environment.

Word sense disambiguation is important for many applications in natural language processing fields including machine translation, information retrieval and automatic summarization. In this paper, left word unit and right word unit are extracted for improving the quality of word sense disambiguation (WSD) starting from the target polysemous word. Their semantic knowledge is mined from Tongyici Cilin which is a Chinese semantic lexicon. A new method of word sense disambiguation is proposed with semantic information of left word unit and right word unit. The classifier of word sense disambiguation is built based on bayesian model. SemEval-2007: Task#5 is used as training corpus and test corpus. Experimental results show that the disambiguation classifier’s precision is improved and demonstrate the effectiveness of the method.

In this paper, we applied Sumudu decomposition method coupled with the Taylors series to solve linear and non-linear Advection problems. It is observed that the proposed method is highly suitable for such problems and overcomes some of the basic deficiencies of traditional decomposition method. Several examples are given to re-confirm the efficiency of the suggested algorithm.

Voting algorithm is an important indispensable part of the redundancy design in redundant systems. This paper presented an improved majority voting algorithm, and compared the algorithm with the standard majority voting algorithm and the median voting algorithm through experiments, it is proved that the improved algorithm achieves a compromise between the result selection capabilities of the median voting algorithm and the safety features of the majority voting algorithm.

Energy efficient clustering is well known optimization problem which has been studied widely to extend lifetime of wireless sensor networks (WSNs). Grid computing, enable different entities to share computational, memory, and data resources using a flexible and secure framework. These resources enable users to run computational jobs that exceed the capabilities of available sensor at any single location. The algorithm presented here is to create a virtual cluster within established clusters in wireless sensor network to share individual sensor resources, which permits the wireless sensor network to gain extra cluster resources to run resource consuming applications with private resource control policies. According to the power issue and the unpredictable wireless network characteristics, it is possible that applications running on the sensor nodes might fail due to sensor energy termination, hence, using Cuckoo Search Optimization (CSO) algorithm is necessary as inspired nature technique to improve the availability of sensor nodes by electing the optimum sensor node from each cluster according to precise constrains applied by network specifications. The motivation for this virtual cluster is to create a virtual cluster environment with heterogeneous resources from clusters with homogeneous nodes when a critical event take place and need a service might requires several sensors resources which make it necessary to arrange these resources to achieve the required service.

In order to improve the problem of premature convergence and computational efficiency of traditional differential evolution algorithm in solving high-dimensional problems, an improved differential evolution (HMSDE) algorithm based on combing elite synergy strategy, multi-population strategy and dynamic adaptive strategy is proposed in this paper. In the proposed HMSDE algorithm, the population is dynamically divided into multi-populations in order to keep the diversity of the population, elite synergy strategy is used to achieve information exchange among different sub-populations, and dynamic adaptive strategy is used to dynamically control the parameter values of scaling factor and crossover factor in order to improve the stability and robustness of the HMSDE algorithm. In order to test the performance of the HMSDE algorithm, a set of 10 benchmark functions are selected in here. The results show that the HMSDE algorithm takes on remarkable optimized ability, faster convergence speed and higher search accuracy. And the HMSDE algorithm can avoid the premature convergence and outperforms several state-of-the-art performances.

Shadow detection for single image is difficult but has wide applications. This paper proposes a novel and fast shadow detection method based on the Tricolor Attenuation Model [1]. In this study, we analyze the spectral property of outdoor light sources to estimate the parameters of TAM. Then our shadow detection method is proposed by integrate the TAM feature and intensity information. Our method can extract shadows for a single and uncalibrated image without any prior knowledge, even for complex scenes. Experimental results show the effectiveness of the proposed method.

To improve the response to customers’ demand and the efficiency & quality of product design in the networked collaborated environment, a new modeling framework of the product design platform based on the Internet of Things (IoT) is put forward. In accordance with the requirements of collaborative product design among the supply chain partners, the design platform established on the IoT is given to optimize and carry out the design process through the network. The fundamental structure, feasibilities, functions and key technologies of this platform are described in detail. Further more, a set of key issues are raised in this architecture, and the techniques employed in the solution are presented. All of these researches would provide significant practical references for enterprises to build the related product design platform.

By using model-driven architecture (MDA), most of errors can be discovered and solved at the early stage of system design. AADL lacks formal semantics which are essential for real-time embedded systems with high safety requirements. In this paper, we design and implementation the AADL Interpreter based on K semantics framework, and this lays a solid foundation for formal analysis and verification of AADL model.

This paper presents a Hybrid NC Control System for Automatic line based on Cyber-Physical-System (CPS) technology. Firstly, this paper describes the overall system hierarchical structure, which uses a variety of techniques, such as sensors, smart computing, and heterogeneous network integration. In order to improve the practical value, we study and solve some technical problems, such as heterogeneous systems integration, data storage, and real-time simulation. Finally, the prototype system is developed, which has been applied in a large State-owned enterprise in Wuxi, China.

In this study, we used three popular data mining techniques (decision trees, artificial neural networks and support vector machine) to analyze the risk factors of medical expense of patients with hepatitis A in Guangdong Province in 2008. We compared the three methods to find out an effective method to predict medical expense and extract main influence factors of the medical expense. The results showed that support vector machine is the most accurate predictor.

The utilization of modern information technology in the delivery of healthcare is to enhance the availability and reliability of improved healthcare services to patients at a reduced cost. The alternative in this context is to outsource the computing storage resources with the help of cloud infrastructure. The drastic reduction in the cost of healthcare services, utilization of resources, maintainability and the adoption of new technologies are some of the benefits that healthcare centers in rural areas can get from cloud-based medical information system. Also, new prospects such as easy and ever-present access to medical records and the chances to make use of services of physicians that are not readily available in the rural areas are some of the opportunities offered by a cloud-based medical information system. This paper proposes and implements a cloud-based electronic medical record (CloudeMR) system to improve the delivery of healthcare system in the rural communities of Nigeria.

The mobile game is experiencing a rapid development and one of the favorite mobile applications. This article focuses on Chinese mobile game market and conducts an empirical research on the factors of the user adoption of mobile game. The research results show that perceived usefulness, perceived entertainment, economic cost and subject norm significantly affect the attitude of use, which results in behavior intention to adopt the mobile game, while the perceived ease of use, similarity and brand trust, which proposed to affect the user adoption in related literatures insignificantly affect use adoption of mobile game .

With the application of ITIL in IT services of small and medium-sized commercial banks, whether the improvement of IT service has been fulfilled is the key to successful introduction of ITIL. However, the mature IT services index evaluation system and methods for the small and medium-sized commercial banks have not been established. This research aims to establish the stakeholders’ satisfaction evaluation system of ITIL project based on KPI of ITIL management, which has strong pertinence and operability. The author has utilized the BP network based on GA optimization to conduct evaluation because the types of indicators are numerous and some of them are difficult to be quantized. Firstly, the author gains the precious model by means of the selected indicators and results of evaluation within 10 small and medium-sized commercial banks and GA-BP model. Afterwards, the indicator evaluation results of four of them are tested. The results of evaluation perfectly fit the expert evaluation results and the precision and convergence speed of the model are higher than that of the random BP, therefore, it is applicable to obtain stakeholder satisfaction of ITIL projects via GA-BP model and commendably satisfy the demands for evaluation of ITIL on basis of IT service level of small and medium-sized commercial banks.

How to manage the component library is important to the component reuse. The description mechanism of components is the basic on the component retrieval, which make users better understand the component. In general, we deal with three issues in semantic search, namely, usability, scalability and retrieval performance. In this paper, we propose a novel keyword-based semantic retrieval approach. Furthermore, the tradition component library exist heterogeneity because of the different company have their own standard. So the proposed methodology in the paper is fulfilled with the component management framework in the basic of the ontological feature model based on ontology and multiple agent system .The feature model is distinguish the tradition feature model, which describe the component form three different dimensions. Also the semantic retrieval model of component and the disturbed calling of component based on the multiple agents are researched which will help to improve the component reuse. The result indicates the effectiveness of the proposed framework.

In rural area, it is very important for peasants to get the information efficiently. In this essay, peasant’s interpersonal communication is studied. Using data of 98 rural households from 3 villages in Fujian Province, their social networks are painted, with the application of Burt’s structural hole theory. The structure of peasant’s social networks is analyzed and the key nodes in the network are identified. According to the results, we sum up some general characteristics of the key node of peasants in their social networks, and put forward suggestions to improve the communication of information among peasants.

With the explosive growth of the information on the Internet, the number of web pages is also expanding rapidly. A common web page typically contains many different blocks. Unfortunately, apart from the main content blocks, it usually has such blocks as navigation bars, copyright, and advertisements, which are known as noise. Studies have shown that these noisy blocks can do harm to Web mining, search engine performance, and Web page clustering and classification. It is a significant work to effectively clean these noises up and extract main content blocks from the Web pages. In this paper, we propose a method of automatic template detection and noise elimination based on an new idea defining two sorts of templates called Style Template and Content Template relatively. There is a basic observation that, the Web pages from the same site are always similar in presentation style and contents, however, the main content blocks are always different in contents. Therefore, we design an algorithm to detect the two kind of templates from the samplings from a particular site, and extract the main content out of the noises using the template. We apply our method to template problem, and the result shows that our methods performs very well, and has a remarkable advantage on time consumption over previous methods.

For decades, Image enhancement techniques have been pushing the envelope of image processing applications. The aim of image enhancement is to recover the information perception contained in the image for human eyes besides delivering the best input for image processing systems. Fingerprint system is one of the most popular image processing system, The performance of any fingerprint system highly depends on the fingerprint image quality; therefore, fingerprint image enhancement is an essential stage in fingerprint systems. Gabor filtering has been widely used to facilitate various fingerprint applications. Meanwhile, enhancement using Gabor filter still has several drawbacks. In the present enhancement approach, we propose an active hybrid contextual module used for image enhancement. In order to prove the efficiency and effectiveness the proposed algorithm applied to fingerprint image. The proposed filter methodology includes eight stages, each one designed for a particular image defect, which can much improve the clarity and continuity of ridge structures, link broken ridges and reduce the false minutia. The experimental results show that the enhanced image quality by using our algorithm has higher performance, robustness and versatility. Presented approach might be useful for many applications related to digital image processing, computer vision.