This paper relates the distribution trend of the information skills for students based on Visual Analog Scale (VAS) and Likert scale (LS). The data are collected from 40 subjects. They were invited to answer LS questionnaires first, and then to answer VAS questionnaires a week later. To apply the same evaluation criteria, VAS data and LS data are transformed to ratio scales value (i.e. 0.00 to 1.00) and the subjective evaluation distribution based on LS and VAS are calculated. The experiment result shows that there exists unintended bias between LS data and VAS data. This fact is supported by the published articles. Therefore, it can be considered again that the presence of bias is affected by the difference of questionnaire. To obtain reliable conclusions, it is necessary to try this method on the results of feature study and do more investigation.

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The purpose of this paper is to investigate the involvement with others in the nursing student, it is to clarify the characteristics of reflective students. Subjects were 111 nursing students of vocational school. The contents of the questionnaire were questionnaires about emotional intelligence (J-ESCQ), reflection (J-RRQ), and involvement with others (i.e., agent) in the daily of the subjects. Each grade was no significant difference in the mean scores of J-ESCQ and J-RRQ (p<0.01). Homeroom teacher and Faculty members of the agent were most selected by Third grade students than the First-grade or Second-grade students. However, The agent also did not have an extreme bias in each grade. Mean scores of two-scales was used in the cluster analysis by Ward method. We were comparing the difference between the Mean score of J-RRQ of two clusters. As a result, two clusters were as follows: Low-Reflection Group (Low-RG) and High-Reflection Group (High-RG). Results of the comparison of the agent between the two groups, Agent of Low-RG was senior students and/or a member of part-time job. On the other hand, agent of the High-RG has been many selected faculty and/or students of other school. It was suggested that the involvement of the faculty is more important to the reflection of the students.

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Recently, people are collecting regional information using the Internet. Also, the SNS and blog are important tools to transfer information such as regional information and internet user's experience. The development of information and communication technology has enabled to disseminate information easily. Therefore, to write personal experiences on "word of mouth" has a significant public influence. In this study, we collect local information from the big data on the Internet. We focused on Twitter that can transmit information easily. Our objective is to collect regional information from Twitter, and to acquire knowledge information by analyzing.

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A major cause of Acute Coronary Syndrome (ACS) is a blood clot generated by a rupture of plaque in the coronary artery. For a diagnosis of ACS, it becomes important to characterize accurately the tissue of coronary plaque. Several methods to characterize the tissue of coronary plaque have been proposed so far. They are not however always useful due to the limitation of the performance of the features selected. In this study, we propose a new method to use sparse modeling of the 2D ultrasound signal reflected from the target tissue of plaque. The effectiveness of the proposed method has been verified by comparing the characterization results by the proposed method to those by the conventional methods for the real intravascular ultrasound data obtained from the human coronary arteries.

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