• Journal of Information Science Theory and Practice
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• v.4 no.1
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• pp.21-29
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• 2016

Given the difference in research performance in various scientific fields, this study aims to weight and valuate current indicators used for evaluation of scientific productions (publications), in order to adjust these indicators in comparison to each other and make possible a more precise evaluation of scientific productions. This is a scientometrics study using documentary, evaluative, and survey techniques. The statistical population consisted of 106 top Iranian researchers, scientists, and scientific and research managers. Then their research résumé information was gathered and analyzed based on research questions. In order to compare values, the data gathered from research production performance of the population was weighted using Shannon entropy method. Also, the weights of each scientific production importance according to expert opinions (extracted from other works) was analyzed and after adjustment the final weight of each scientific production was determined. A pairwise matrix was used in order to determine the ratios. According to the results, in the area of engineering sciences, patents (0.142) in the area of science, international articles (0.074) in the area of humanities and social sciences, books (0.174), and in the area of medical sciences, international articles (0.111) had the highest weight compared to other information formats. By dividing the weights for each type of publication, the value of each scientific production compared to other scientific productions in the same field and productions of other fields was calculated. Validation of the results in the studied population resulted in very high credibility for all investigated indicators in all four fields. By using these values and normalized ratios of publication indicators it is possible to achieve precise and adjusted results, making it possible to feasibly use these results in realistic policy making.

• Journal of Preventive Medicine and Public Health
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• v.41 no.1
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• pp.1-9
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• 2008

Objectives : This study evaluated knowledge structure and its effect factor by analysis of co-author and keyword networks in Korea's preventive medicine sector. Methods : The data was extracted from 873 papers listed in the Journal of Preventive Medicine and Public Health, and was transformed into a co-author and keyword matrix where the existence of a 'link' was judged by impact factors calculated by the weight value of the role and rate of author participation. Research achievement was dependent upon the author's status and networking index, as analyzed by neighborhood degree, multidimensional scaling, correspondence analysis, and multiple regression. Results : Co-author networks developed as randomness network in the center of a few high-productivity researchers. In particular, closeness centrality was more developed than degree centrality. Also, power law distribution was discovered in impact factor and research productivity by college affiliation. In multiple regression, the effect of the author's role was significant in both the impact factor calculated by the participatory rate and the number of listed articles. However, the number of listed articles varied by sex. Conclusions : This study shows that the small world phenomenon exists in co-author and keyword networks in a journal, as in citation networks. However, the differentiation of knowledge structure in the field of preventive medicine was relatively restricted by specialization.

• International Journal of Knowledge Content Development & Technology
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• v.7 no.1
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• pp.57-78
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• 2017

There are several statistical classification algorithms available for land use/land cover classification. However, each has a certain bias or compromise. Some methods like the parallel piped approach in supervised classification, cannot classify continuous regions within a feature. On the other hand, while unsupervised classification method takes maximum advantage of spectral variability in an image, the maximally separable clusters in spectral space may not do much for our perception of important classes in a given study area. In this research, the output of an ANN algorithm was compared with the Possibilistic c-Means an improvement of the fuzzy c-Means on both moderate resolutions Landsat8 and a high resolution Formosat 2 images. The Formosat 2 image comes with an 8m spectral resolution on the multispectral data. This multispectral image data was resampled to 10m in order to maintain a uniform ratio of 1:3 against Landsat 8 image. Six classes were chosen for analysis including: Dense forest, eucalyptus, water, grassland, wheat and riverine sand. Using a standard false color composite (FCC), the six features reflected differently in the infrared region with wheat producing the brightest pixel values. Signature collection per class was therefore easily obtained for all classifications. The output of both ANN and FCM, were analyzed separately for accuracy and an error matrix generated to assess the quality and accuracy of the classification algorithms. When you compare the results of the two methods on a per-class-basis, ANN had a crisper output compared to PCM which yielded clusters with pixels especially on the moderate resolution Landsat 8 imagery.

• The Journal of Korean Society for School & Community Health Education
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• v.12 no.3
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• pp.1-15
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• 2011

Objectives: We describe the development of a smoking and drinking prevention program for adolescents, using intervention mapping. Methods: The study sample consisted of 1,000 high school second-grade students from 6 high schools in Seoul. The PRECEDE model was applied for the needs assessment. We carried out a social diagnosis by assessing the factors such as the quality of life, happiness level, and satisfaction with school life; an epidemiological diagnosis on the perceived health status, stress levels, and priority of health issues; a behavioral diagnosis on the smoking and drinking rate and the intention to smoke and drink; and an educational diagnosis on knowledge, beliefs, attitudes, self-efficacy, outcome expectations, social norms and life skills. Results: The development process included a needs assessment, identifying factors that influence smoking and drinking among adolescents. Intention, knowledge, perceived norms, perceived benefit, perceived cost, perceived susceptibility, self-efficacy, and life skills were identified as determinants. Three performance objectives were formulated to describe what an individual needs to do in order to avoid smoking and drinking. Subsequently, we constructed an intervention matrix by crossing the performance objectives with the selected determinants. Each cell describes the learning objectives of the smoking and drinking prevention program. The program used methods from the transtheoretical model, such as consciousness raising, outcome expectations, self-reevaluation, self-liberation, counterconditioning, environmental reevaluation, and stimulus control. The program deals with the effects of smoking and drinking, self-improvement, decision making, understanding advertisements, communication skills, social relationships, and assertiveness. Conclusions: By using the process of intervention mapping, the program developer was able to ensure a systematical incorporation of empirical and new data and theories to guide the intervention design. Programs targeting other health-related behavior and other methods or strategies can also be developed using this intervention mapping process.

• Journal of the Korea Society of Computer and Information
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• v.10 no.4 s.36
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• pp.1-16
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• 2005

When Web-based special retrieval systems for scientific field extremely restrict the expression of user's information request, the process of the information content analysis and that of the information acquisition become inconsistent. Accordingly, this study suggests the re-ranking retrieval model which reflects the content based similarity between user's inquiry terms and index words by grasping the document knowledge structure. In order to accomplish this, the former constructs a thesaurus and similarity relation matrix to provide the subject analysis mechanism and the latter propose the algorithm which establishes a search model such as query expansion in order to analyze the user's demands. Therefore, the algorithm that this study suggests as retrieval utilizing the information structure of a retrieval system can be content-based retrieval mechanism to establish a 2-step search model for the preservation of recall and improvement of accuracy which was a weak point of the previous fuzzy retrieval model.

• Communications of Mathematical Education
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• v.36 no.3
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• pp.439-467
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• 2022

The future society requires not only knowledge but also various competencies, including creativity, cooperative spirit and integrated thinking. This research develops a program for integrating mathematics and information science to enhance important mathematical competencies such as problem-solving and communication. This program does not require much prior knowledge, can be motivated using everyday language and easy-to-access tools, and is based on creative problem-solving activities with multilateral cooperation. The usefulness and rigor of mathematics are emphasized as the number of participants increases in the activities, and theoretical principles stem from the matrix theory over finite fields. Moreover, the activity highlights a connection with error-correcting codes, an important topic in information science. We expect that the real-world contexts of this program contribute to enhancing mathematical communication competence and providing an opportunity to experience the values of mathematics and that this program to be accessible to teachers since coding is not included.

• The Journal of Society for e-Business Studies
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• v.12 no.2
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• pp.47-74
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• 2007

This research purpose to improve the qualification items for electronic commerce manager. Former qualification system for the electronic commerce manager was executed 11 times from year 2000 to 2005. To improve the standard for test questions and contents of qualification items, we reviewed literatures about job analysis for electronic commerce manager, electronic commerce curriculum, e-Business market and other countries' similar qualification systems and items. We also analysed the job related knowledge, skill, and abilities using job analysis by DACUM method, subject matter experts interview and workshop committee for development and validation of qualification items. Based on the results of job analysis and DACUM workshop, we derived a job model for electronic commerce manager and then validated it through field survey and additional expert review. Finally we developed and suggested an alternated qualification items using matrix analysis between categorized job knowledge and job tasks.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.647-653
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• 2022

Data mining is a technique that explores knowledge such as relationships and patterns between data by exploring and analyzing data. Data that occurs in the real world includes a temporal attribute. Temporal data mining research to find useful knowledge from data with temporal properties can be effectively utilized for predictive judgment that can predict the future. In this paper, we propose an algorithm using time-unit grouping to classify the database into regular time period units and discover frequent pattern itemsets in time units. The proposed algorithm organizes the transaction and items included in the time unit into a matrix, and discovers frequent items in the time unit through grouping. In the experimental results for the performance evaluation, it was found that the execution time was 1.2 times that of the existing algorithm, but more than twice the frequent pattern itemsets were discovered.

• Restorative Dentistry and Endodontics
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• v.24 no.1
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• pp.88-99
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• 1999

The purpose of this study was to investigate the physical properties of experimental composite resins made with the spherical and crushed fillers. The 14 experimental composite resins containing 0, 5, 10, 15, 20 and 25%(w/w) in spherical filler group and 0, 10, 20, 30, 40, 50, 60 and 70%(w/w) in crushed filler group, incorporated in a Bis-GMA matrix (Aldrich Co., USA), were made with 1% ${\gamma}$-methoxy silane treated fillers. The polymer matrix was made by dissolving 0.7%(w/w) of benzoyl peroxide(Janssen Chemical Co. Japan) in methacrylate monomer, whereupon 0.7%(v/v) N,N-dimethyl-p-toluidine(Tokyo Kasei Co. Japan) was added to the monomer. The weight percentage of each specific particle size distribution could be determined from a knowledge of the specific gravity, the weight(w/w), and corresponding volume %(v/v) of the filler sample in resin monomer. In crushed silica group and spherical silica group, the diametral tensile strengths and compressive strengths were measured with Instron Testing Machine(No.4467), and analyzed in 14 experimental composite resins made by filler fractions. The shear bond strength of 14 experimental composite resins to bovine enamel was measured with universal testing machine(Instron No.4467). The fracture surfaces were sputter-coated with a gold film and investigated by SEM. The results were as follows; 1. The diametral tensile strength was tendency to increase in crushed silica group, but not in spherical silica group. The highest diametral tensile strength was found in 20% filler fractions of two groups. 2. The compressive strength was higher in 15%(w/w) and 20%(w/w) in spherical silica group than in crushed silica group, but not in spherical silica group. 3. The significant correlation was noticed in increase in shear bond strength in crushed silica group, but not in spherical silica group. 4. The significantly highest shear bond strength was noticed in 50% filler concentration in crushed silica group, and in 15% filler concentration in spherical silica group, it was not significant in relation. 5. In crushed silica group, cut surface of resin matrix and the interface between resin and filler is obvious. In spherical silica group, fractures that occurred through the filler particles were round in shape.

• The Journal of the Korea Contents Association
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• v.10 no.2
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• pp.462-480
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• 2010

Patent analysis is the extracting knowledge which is needed for the company's research and development strategy through accumulated worldwide patent database. In order to set the future direction of corresponding technology which is scheduled to be developed, the technology trends and deployment processes are identified by analyzing results of present patent applications. The patent analysis provides the required results for analyzing present patent applications. In this paper, we will carry out technology classification for related patent analysis methods and systems. Moreover we will investigate and analyze related domestic patents, U.S. patents and IEEE papers. Due to the characteristics of technology sector, not only patents are applied but also research papers are released actively about patent analysis system. We will analyze patents according to the technology classification by using the final searching results which come from the selected search words in this study. To find necessary niche technology which is needed for patent analysis system, matrix analysis was performed to all of valid patents and papers. Identifying the technology development trends of registered patent analysis systems, and presenting the future direction of technology development which is related to patent analysis system. To figure out the technology which is developed relatively weak based on domestic patents, U.S patent and research papers by analyzing the valid patents and papers with statistical test and self-organizing map quantitatively. Then, presenting the necessity of this technology development.