Earticle

We turn to statistical-based methods and propose a statistical inference approach by using Dynamic Bayesian Network, which is able to learn automatically from data set. By soccer video analysis is as an example, the proposed method is verified by experiment. We extract the color, shape and other low-level features from the video, to detect and identify 5 kinds of high-level semantic events using dynamic Bayesian network model. The experimental results show that our method is effective.

This paper is an in-depth study on the positive effects of the consciousness of lifelong education among university students. This research found the following results. First, the consciousness of lifelong education among university students has a positive effect on their life core competencies. Second, it increases everyday creativity, leadership, and cognitive learning competency of students. Third, it promotes the life core competencies for students. Fourth, it also advances the mediating effect between consciousness of lifelong education and life core competencies. In other words, the consciousness of lifelong education of university students influences their everyday creativity, leadership, cognitive learning competency and their life core competencies positively as well.

The emergence of cloud computing has changed the software development and deployment, providing users with great convenience. But even in the cloud computing environment, software development efficiency is particularly low. In order to improve the efficiency of software development, and make software release easier, we designed a layered service computing platform. With the help of basic services, the platform makes software development and publishing simple and efficient. To demonstrate our platform, we described the process of building a simple WebGIS system in this paper. This process represents the software development process in our platform. Experiment shows that our work is not only available but also simplifies the process of software development.

Capability-Based requirements management and planning thoughts and methods have gone increasingly deep into the development of Weapon System-of-Systems (WSoS). In the traditional top-to-bottom capability requirement planning (CRP) methods, the constraints among different capabilities indexes acquired from the tasks decomposition are neglected, which leads to the irrationalities and conflicts between different WSoS capability requirement indexes. Based on the analysis and description of capability requirements planning problem, the constraints are divided into five types and extracted from WSoS according multiple views thoughts. In addition, Interval Weighted Constraint Network (IWCN) is introduced and a consistency detection algorithm and a conflicts elimination strategy are proposed to achieve a capabilities requirement plan satisfying the tasks requirements and the capabilities indexes constraints. Finally, the practical applicability within a Joint Operations System of Systems (JOSoS) based on the space force capability requirement scheme planning is demonstrated, which proves the validation of the method built in this study.

Financial information systems operated by financial institutions are based on various customers’ information. If leaked for illegal and vicious purposes, financial information can bring a lot of damages, including financial damages. Therefore, continuous demands on IT compliance related to financial information systems have risen as financial policy institutions suggest integrated plans for improvement on clarity of financial information service and reinforcement on safety of information systems operation. In order to meet such demands, financial institutions invested efforts and capital to prevent illegal leaks of financial information outside of barriers, however, it happens that not only do information leaks caused by external factors, but also ones caused by internal information system users occur quite frequently. Therefore, financial information systems must be operated and managed by authorized internal users. For that, this study analyzes various authentication technologies and compliances as advanced research then suggests a new authentication model for financial information system users. Through this model, we expect that the system will be able to secure safety in operation and management of financial information system hence, to deal with illegal leaks of financial information.

This paper aims at solving existing problems in enterprise human resource management through measurement and analysis of enterprise human resource management capability. It proposes a measurement model for human resource management capability based on ideal domain of grey correlation. First, an improved measurement and analysis system for enterprise human resource management capability is proposed; then, positive and negative ideal domains for enterprise human resource management capability are constructed, and the management capability is measured and analyzed based on grey correlation analysis method to obtain the grey correlation coefficients and grey correlation degrees between the object-under-examination and positive and negative ideal domains respectively. Next, on the basis of comprehensive grey correlation, a human resource management capability model is proposed to measure human resource management capability. Finally, case study is carried out to examine the feasibility of the proposed model.

The purpose of this study is to develop a scale for measuring the “selective attributes” or characteristics that influence distance continuing education learners’ decision-making in selecting an academic institution; it also presents practical implications for marketing by estimating how the factors that are classified through factor analysis form clusters. As a result of the exploratory factor analysis to develop a scale for measuring the selective attributes which that are influential factors in selecting an academic institution, the attributes were categorized as “academic curriculum and convenience of facilities,” “ease of obtaining the degree,” “faculty and course quality,” and “tuition discount and scholarship.” As a result of the cluster analysis using factor scores, cluster types were classified as “tuition and scholarship group,” “diverse purpose group,” and “academic curriculum and convenience of facilities group.” Multivariate analysis of variance (MANOVA) was performed to verify the validity of the cluster types, and each cluster was determined to carry statistical significance.

To overcome the deficiencies of the existing literatures to describe the function of recovery quantity, it was necessary to construct a new function, in which recovery quantity connected with buy-back price and sale quantity. This paper analyzed the optimal decision of the manufacturer and competing retailers under the following three cases: two retailers participated in the recycle, one retailer participated in the recycle and the manufacturer collected directly. The results show that: when the saving cost (cost between new products and reused products) is large enough, the manufacturer tends to collect used products in the consumer market through the competing retailers. And when the saving cost is small, the manufacturer collects herself or chooses one of the competing retailers to collect the used products, which depends on the market size, the attract coefficient and the switching coefficient. Moreover, the improvement of the consumers’ environmental awareness is beneficial to the manufacturer, consumers and social environment. The results of this paper provide a basis for the manufacturer on its channel selection.

A dynamic robust optimization model is established based on the objective of profit maximization to deal with the uncertainty of the problem through formulating a robust linear programming model. An equivalent robust optimization model using duality theory and auxiliary problem principle is obtained which allows the solutions to be derived more efficiently. Following the numerical simulation and sensitivity analysis is presented. The numerical simulation shows that the robust optimization mode can reduce the risk and uncertainty of reverse logistics operation process and the environment of demand uncertainty, which verifies the effectiveness of the approach.

This paper investigates determinants of increases in elderly populations by utilizing econometric models such as panel data analysis. All the results support stylized fact in the relationship between elderly populations, fertility, and GDP per capita in the long run. However, bi-directional channels are found to exist regarding changes in elderly populations, signifying that the primary determinants of increases in elderly populations come from demographic aspects rather than social aspects in the short run. Regarding care of the elderly, social aspects therefore appear to be quite vulnerable. It could be asserted that social systems should be carefully developed to suit aging societies.

This study aims to identify how the perception of trustworthiness and website atmosphere influences customer trust and website image to enhance stickiness, as well as the extent to which gender moderates the relationships between the constructs. Appropriate measures were developed and tested on 203 respondents in east provinces in China with a cross-sectional questionnaire survey. The path relationships of the research model were analyzed by structural equation modeling (SEM) using AMOS 18.0. The results confirmed that trustworthiness and website atmosphere have positive impacts on customer trust and website image. Customer trust and website image have positive impacts on stickiness. Meanwhile, the moderating effects of gender in the relationships between trustworthiness, website atmosphere and customer trust are significant. Thus, the managers should focus on trustworthiness and website atmosphere to improve stickiness through customer trust and website image.

A design of in-transit logistics remote video monitoring system is proposed based on cotex-A8 processor hardware and Android software systems platform, by the terminal USB infrared camera driver transplant, video streaming H.264 codec, and 3G wireless transmission network, the in-transit logistics remote video monitoring real-time display is achieved, which can prevent the loss of goods and cargo in logistics process and be served as the evidence for the responsibility distinguishing in the event of goods damage. Managers and customers can track the transport status of goods by computer or mobile phone in real-time, and provide better service to customer, therefore enhance the competitiveness of logistics enterprises.

Based on the perspective of innovation ecosystem, the paper studies the relationships between openness and absorptive capacity of leading firms’, and how they make effects on innovation performance. Based on a survey of 126 high-tech firms’ in China, we found both the openness and absorptive capacity have a positive impact on innovation performance. A finding shows that the scope of openness is wider, the knowledge acquisition capability contributes more to the innovation performance; also, the depth of openness is deeper, the knowledge exploitation capability is more helpful to improve the innovation performance.

In this study, we developed a visualization tool that shows learners’ interactive activities graphically during virtual reality (VR) education. Current VR system only shows learning content. However, we need to recognize learners’ interaction and information exchanges for increasing effectiveness of learning; also we need to show it effectively. Therefore, we developed visualization tool for VR learning based on web 2.0, and this tool helps teachers and students to monitor and percept the interaction activities among students, and thus it facilitates their interaction and learning in VR education environment. For experiments, 68 students participated in VR learning. The result shows that the interaction and the perception of effectiveness of learning are significant differences between VR system and web 2.0 VR system. Furthermore, for verify availability of usage, TAM (Technology acceptance model) analysis about the system is supported. This result will be basic material for constructing of future VR learning environment.

This paper studied optimal order quantity and advertising level of newsvendor. According to the concepts of unit opportunity shortage penalty and unit opportunity expected excess loss, analyzed the relationship between optimal order quantity and the loss aversion coefficient. On this basis, from two aspects of the impact of advertising on the market, we studied the retailer optimal advertising and order quantity decision problems, got the optimal level of advertising and the optimal order quantity, finally examples have shown the impacts of advertising on the retailer.

This paper proposed an algorithm for 3D hands tracking on the learned hierarchical latent variable space, which employs a Hierarchical Gaussian Process Latent Variable Model(HGPLVM) to learn the hierarchical latent space of hands motion and the nonlinear mapping from the hierarchical latent space to the pose space simultaneously. Nonlinear mappings from the hierarchical latent space to the space of hand images are constructed using radial basis function interpolation method. With these mappings, particles can be projected into hand images and measured in the image space directly. Particle filters with fewer particles are used to track the hand on the learned hierarchical low-dimensional space. Then the Hierarchical Conditional Random Field, which can capture extrinsic class dynamics and learn the relationship between motions of hand parts and different hand gestures simultaneously, is presented to model the continuous hand gestures. Experimental results show that our proposed method can track articulated hand robustly and approving recognition performance has also been achieved on the user-defined hand gesture dataset.

In this paper, we identify the industrial characteristics of portal sites by using stochastic frontier analysis and to bit regression. As a result of the analyses, the study proposed that market share and an appropriate level of fixed assets, not human resources, have a positive impact on the efficiency of portal sites. It also revealed that portal sites are no longer an innovative industry, but are showing characteristics more similiar to a traditional industry.

With the rapid development of the Internet, for-profit site need to analyze the user's behavior and provide more satisfactory service. Therefore, the classification of network behavior analysis and the further research based on it are more and more urgent on the agenda. In this paper, a method based on similar aggregation user behavior analysis algorithm is proposed. Addressing the recommendation of personalized books problems is solved by this method. Firstly, the user behavior is analyzed by using the RFM model. Secondly, the Apriori algorithm based on weight increment is applied to mining association rules between users in line with the recent habits of users. Similarity is calculated by Apriori algorithm with using VSM model. In this paper, readers’ browsing history of e-library which is provided by Harbin University of Science and Technology is used as experimental data. This method is compared with the method which does not use the weight increment and similar aggregation. Comparison of results showed that the method of our paper can meet the requirements of the Book Recommendation system.

With the development of information construction and the abundance of network information resources, the load of sports information resources in the network becomes distribution, variety, great capacity, and then influences people to have fast and accurate access to online information. Network information resource is important in prison, because prison police is a very special social groups, therefore strengthening the prison sports is particularly important. In this paper, we test the prison sport based on network information resources, using a questionnaire survey of 200 prison police and make statistics analysis. The main purpose of this research is to understand the status and problem of prison sports, and provide related suggestions in order to promote prison sports activities, thereby contributing to sports development in prisons system.

The traditional K-nearest neighbor algorithm existences of the risk of miscarriage of justice, for its shortage a speech emotion recognition algorithm based on fuzzy K-nearest neighbors is proposed. By introducing the fuzzy membership concept, different characteristic parameters for the different contribution of emotion recognition are calculated, and the weighted Euclidean distance is used in speech emotion recognition. The experimental results show the effectiveness of the algorithm.

Reputable brands play a significant role on the long-term performance of a company and sustainable customer perceptions.Investors need toregard brand valuation reports like Korea Best Brands as important information. This study uses the event study methodology toinvestigatethe announcement effectof Korea Best Brands. The results of this study are as follows. Korea Best brands announcement have positive impacts on listed companies in the first year, it was not seen consistentsince that time. Also,fallen and ascended group in brand valueshave no effects before the event daybut have a negative effect after the event day. Significant increasing in brand value prevents a negative effect of unusual falling.

To effectively evaluate and analyze assimilability scheme of complex product, an improved evaluation method is proposed. It sets up three levels in the evaluation: scheme level, craft level and component level, giving evaluation indexes that can influence assimilability of complex product at every level. A corresponding evaluation index system is established. Based on the calculation of fuzzy distances and fuzzy nearness between different evaluation indexes, weighs of information entropy of indexes are gained. Then the levels of current complex product assembling scheme can be acquired. At last, specific project example is conducted to analyze and verify the model and the algorithm. The effectiveness and feasibility of the model and the algorithm are proven.

We fully study the various factor indexes involved, use the AHP to build an integrated-assessed mathematic model of hierarchy of good distinct and structure of high efficiency and calculate the weight assessment indicator of each hierarchy. This paper uses AHP to build the general objective function of the designing scheme of students practice property. By the statistical analysis of the tip of various property indexes of mass property data, we choose the corresponding subordinating degree functions in the fuzzy mathematic field to determine the appropriate subjection function, calculate the relevant degree of membership, and finally conduct the integrated assessment of mathematic model of the design of remote students practice system. The paper uses C# language in the developing environment of VS2010 to develop the fuzzy-comprehensive-assessment software system of the designing scheme of students, and, we also use the software to analysis the systematic reliability of this scheme by living example. Through this work, we could offer a scientific and rational theory of technology to students for the support of remote Students practice projects research department.

The purpose of this study is to analyze the effect of national cultural dimension and type of alliance orientation (scanning alliance, utilization alliance) on alliance performance. To analyze this objective, we conducted a survey in target companies which signed partnership and international business. This study reviews various literatures and developed a research model. To examine the research model, we collected data from international companies with partnerships. The study results showed that national culture and type of alliance orientation have a significant effect on the alliance performance. Moreover, it can provide a very meaningful implication where international firms achieve better performance identifying the core competencies between cultural characteristics and alliance orientation suitable for the partnership.

This paper addresses the problem of adaptive trajectory tracking control for the wheeled mobile robot (WMR) based on cascade-design method. The condition is considered that there is a distance between the mass center of the robot and the geometrical center. The tracking error system is divided into two subsystems: the position error system and the orientation error system. In order to deal with the circumstance with the unknown parameters, an adaptive tracking control law is proposed. Simulation results illustrate the effectiveness of the proposed control methods.

This study investigated the development of an educational prevention program for smartphone addiction and how it can affect smartphone addiction, knowledge and attitudes after education for nursing students and staff comprising of experimental groups (26 nursing students) and control group (27 nursing students) in a university. The experimental group was given prevention education, while the control group was given nothing. SPSS 21.0 program was used to compare the before and after smartphone addiction, knowledge and attitude scores along with the t-test to analyze the differences. The average smartphone addiction (t=-2.41, p=.016) and knowledge scores (t=4.56, p=0.002) of the experimental group statistically significantly increased, while the attitude score (t=1.24, p=.321) of experimental group did not significantly increase. This study demonstrates that a prevention education program can be effective for smartphone addiction and knowledge of nursing students and staff in a university.

Introduce the basic ideas, principle and modeling approach of the analytic hierarchy process and take examples of post selection and decision of graduates, making specific demonstration about the utilization of AHP to prove the scientificity and practicability of AHP for multi-attribute decision-making problems.

In the modern supply chain management, optimizing supply chain can reduce the cost of the enterprise. In the optimization of supply chain, the inventory optimization is a very important part. Through forecasting the inventory amount, we can reduce the cost of the inventory. And we also can optimize the supply chain. Because the supply chain network is complex, we use the chaos theory to study and predict the inventory. In this paper, we put forward a chaotic forecasting method which is based on the BP neural and genetic algorithm. This new method is BP-GA chaos prediction algorithm. We use the method to predict the inventory amount. The experiment shows that the method has achieved good forecasting effect.