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This study developed a smartphone application (app), based on user demand, for the self-care performance of patients with chronic Hepatitis B. The smartphone app was developed in five stages. In the analysis stage, we surveyed the demand for the app among 187 patients with chronic Hepatitis B, analyzed several other apps, and conducted a literature review. In the design stage, the app’s purpose was established, and the necessary functions, system interface, database, and screens were designed. In the development stage, the app was developed. In the implementation stage, the master version of the app was used by four specialists and five participants with chronic Hepatitis B. In the evaluation stage, we conducted a heuristic evaluation and a mobile app rating scale evaluation, with these nine subjects. As a result of the evaluations, 19 aspects of the system were modified to further improve the app. This smartphone app is expected to be helpful in performing self-care, serve as a disease-related knowledge source, and promote self-efficacy in chronic Hepatitis B patients.

At present, artificial intelligence has become an important part of people’s life. Meanwhile, people’s health consciousness and demands for modern leisure sports have improved. Based on the technology of artificial intelligence, this paper is to study the evaluation of leisure sports majors’ innovation ability which stays in relatively low level but with great potential. After researching and analyzing the status of leisure sports majors’ innovation ability at home and abroad, the author defined the standard of gray rates, set gray evaluation index, analyzed the gray evaluation model and concluded that students in HeBei Institute of Physical Education have good innovation abilities. This paper which laid a foundation for studies of relevant theories and practices is a pioneering work for innovation ability evaluation.

This research aims to extract Creativity-Character Elements by organic fusions of Creativity and Character by examining previous researches on the relationships between creativity and character. Based on previously related researches on the relationship between creativity and character, there are slight differences in opinions, but it appears that they are influencing mutually. Hence, the coherence of elements of creativity and those of characters was endeavored. There were totals of 36 Creativity-Character Elements extracted through this research results. This study attempted organic fusions of Creativity Elements with Character Elements based on the correlation between Creativity and Character. The results of this research would be crucial and fundamental resources for Creativity-Character Education in the educational fields.

Prime Leading organizations will use the web portal for effort monitoring and tracking. This portal is used to store and analyze the employee effort from various R&D departments. This portal provides a front end environment for employees/management of an organization to keep a track of his/her effort. It is also expected to use SharePoint advanced features such as content management, alerts, information management policies, collaboration features, reporting, and analytics services.

Vehicle License Plate Images Segmentation is a substantial stage for developing an Automatic License Plate Recognition (ALPR) system. In this paper, it is considered an efficient segmentation algorithm for extracting vehicle license plate images using Cellular Neural Networks (CNN). The learning CNN templates values are formulated as an optimization problem to achieve the desired performances which can be found by means of Adaptive Fuzzy (AF) algorithm and Neuro-Fuzzy (NF) algorithm techniques. The main objective of the paper is to compare the performances of standard CNN, Adaptive Fuzzy (AF), and Neuro-Fuzzy (NF) on real data of several vehicle license plate images of standard Indonesia License Plates. The results are then compared with ideal vehicle license plate images. Quantitative analysis between ideal vehicle license plate images and segmented vehicle license plate images is presented in terms of Peak signal-to-noise ratio (PSNR), Mean Squared Error (MSE) and Root Mean Squared Error (RMSE). From the performance analysis, the CNN template optimized by ANFIS algorithm is more recommended than the standard CNN edge detector or the CNN template optimized by Adaptive Fuzzy algorithm in vehicle license plate image segmentation. It is shown from the calculation that PSNR is 80% better than the standard CNN, and the resulted MSE and RMSE are 70% better than the standard CNN. Whereas the CNN template optimized by Adaptive Fuzzy algorithm achieves the PSNR 90% better than the standard CNN, but it yields the MSE and RMSE 40% worse than the standard CNN.

In view of the automatic solution process of the elementary school mathematics application question, this article has carried on the research to the mathematics application question teaching expert system. Firstly, this paper introduces the definition and structure of the expert system. Then the system structure and function module of the mathematics application question teaching expert system design, gives a detailed description and design of information extraction module, application of rule base, application type library and application question solving process. In this paper, the application of the problem is divided into an integer one step calculation problem, the integer two steps to calculate the application and fractional scores of three parts of the application. At the same time, according to different types of applications, the structural characteristics of the analysis. According to the information extraction model and mathematical operation rules, the overall framework and function modules of the design mathematics teaching expert system are designed. And the realization process is studied. The research results show that the system can be used to demonstrate the solution of mathematical problems in detail. Help students to understand the application of the problem solving process. Make it better learn to know how to solve the problem. And it is helpful for teachers to easily understand method and carry on the teaching process. This also means that the system has practical application value. As a bridge between mathematical theory and practice, mathematical application problems have become more and more important in the implementation of mathematical quality education. It is necessary to cultivate students' mathematics application consciousness and optimize the students' thinking quality. After leaving school, every student can still think about problems and solve the problem mathematically. In consequence, pay more attention to the teaching of application problems, make the cultivation of the consciousness of "use" of mathematics throughout the whole high school stage, and integrate training students' ability of solving mathematics application question into daily teaching, which is conductive to promote the development of students' mathematical innovation, stimulate mathematics learning interest, and improve internal drive of mathematics learning. In our country, many middle school mathematics teachers have carried on the thorough research on the mathematics application problems teaching, which also has made some progress. However, there are still a lot of mistakes in the application teaching in the daily used system. In particular, the college entrance examination still has its influences, teaching material adjustment is not in place, how to teach the application problems plays a crucial role in the overall implementation of the quality education reform.

Abstract 1. Introduction 2. Literature Review 2.1. Mobile Social Network Game (MSNG) 2.2. Attributes to Select and Continue the Msngs 3. Research Model 4. Research Methodology 5. Results 6. Conclusion References

The talented human resource demanded by companies in the knowledge-based society is the person who has creativity and upright character. Currently, there are 10 basic vocational skills commonly sought in all workers nationwide, and one of them is the problem-solving skills. One of sub-factors of problem-solving skills is creative thinking. Under these circumstances, various teaching and learning models have been developed to develop students’ creativity and upright character. However, there are not enough discussions on the optimized education programs. Customer satisfaction (CS) is defined as a condition where customers’ needs, desires, and expectations are met or exceeded to result in the repurchase of products and/or services and repeat this to continue customer loyalty. CS skills include the competencies that promptly adjust to the fast-paced environments and resolve problems creatively. However, the existing CS training is mainly focused on the attitudes or functions of services, and there is limited effort on developing the abilities to flexibly respond to various real-life issues. Therefore, CS training should be developed in order to improve students’ problem-solving skills. Additionally, the scope of CS training is expanding to the broad meaning as training for nurturing the upright character. With social demands for creativity and upright character, the purpose of this study is to develop a CS course that is based on the CPS model to develop college students’ creativity and upright character. In this study, researchers developed Creative Problem Solving (CPS) model by adapting and modifying existing CPS model, and developed CS course based on developed CPS model. The significances of developed CS course are as follow: first, it will improve the creativity and upright character of college students who have participated in a CS course that applies the CPS model. Second, it can help professors teaching CS course in colleges teach image-making course based on the CPS model in schools. Third, it is expected to suggest study directions for the development of other CS courses in addition to image-making

Service technology has gained increasing popularity in recent communication software applied in many domains. With a growing number of services that share same or similar functionalities, clustering services help improve both service composition and mashup creation. To achieve service clustering, utilizing probabilistic topic model to extract and characterize the service description documents as corresponding topics is an available scheme. However, unlike short text in social networks, the descriptions of published services possess higher dimensionality and sparse functional information. With traditional LDA (Latent Dirichlet Allocation) model to implement topic extraction makes topics unclear. To address that challenge, we conduct a context sensitive approach to generate context sensitive vector for merging the words with similar context before loading to LDA model, referred to as CV-LDA (Context Vector LDA). Through F1-Measure of clustering and topic perplexity analysis in the real-world dataset, it is shown that the proposed approach outperforms traditional LDA model in service clustering.