• Health Policy and Management
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• v.18 no.2
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• pp.86-106
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• 2008

This research analyzed. knowledge structure and its effect factor by analysis of co-author and keyword network in Korea's health policy and administration sector. The data was extracted from 339 articles listed in the Korean Journal of Health Policy and Administration, and was transformed into a co-author and keyword matrix. In this matrix the existence of a link was defined by impact factors which were calculated by the weight value of what the role was and the rate of how many authors contributed. We demonstrated that the research achievement was dependent on the author's status and network index. Analysis methods were neighborhood degree, correspondence analysis, multiple regression and the difference of weight distribution by research fields. Co-author networks were developed as closeness centrality as well as degree centrality by a few high productivity researchers. In particular, power law distribution was discovered in impact factor and research productivity. 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. Especially, this journal shared its major researchers who had a licensed physician with the Journal of Preventive Medicine and Public Health. Therefore, social scientists were likely to be small co-author network differently from natural scientists. It was so called 'two cultures' phenomenon. This study showed how can we verified academic research structure existed in the unit of journal like as citation networks. The co-author networks in the field of health policy and administration had more differentiated and clustered than preventive medicine and epidemiology fields.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.12
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• pp.2607-2613
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• 2012

The results of inherent knowledge based generic summarization are influenced by the composition of sentence in document set. In order to resolve the problem, this papser propses a new generic document summarization which uses clustering of semantic feature of document and coherence of document cluster. The proposed method clusters sentences using semantic feature deriving from NMF(non-negative matrix factorization), which it can classify document topic group because inherent structure of document are well represented by the sentence cluster. In addition, the method can improve the quality of summarization because the importance sentences are extracted by using coherence of sentence cluster and the cluster refinement by re-cluster. The experimental results demonstrate appling the proposed method to generic summarization achieves better performance than generic document summarization methods.

• Journal of The Korean Association For Science Education
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• v.29 no.8
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• pp.812-823
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• 2009

The purpose of this study is to search effective assessments methods by using the Fusion model of Cognitive diagnosis theory. Attributes are skills or cognitive processes that are required to perform correctly on a particular item. After test items were developed, item's attributes were decided and Q-matrix about item's attributes was made. After testing, the result was analyzed according to gender and achievement level. The results of the analysis showed that students mastered 'Interpreting data' best, and 'synthesizing' worst among the five attributes. Female students showed higher ability than male students in 'recalling.' Students of high achievement level mastered more scientific attributes than students of low achievement level. Conventional assessments only provided a single summary score but Cognitive diagnosis modeling provided useful information by estimating individual knowledge states by assessing whether an examinee has mastered specific attributes measured by the science test. The skill profiles can offer a skill level of strong, weak, or mixed for each student for each skill. Therefore, the skill profiles will provide useful diagnostic information in addition to single overall scores.

• Solar Energy
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• v.12 no.2
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• pp.43-50
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• 1992

This study has been conducted to provide fundamental knowledge of the characteristics of pressure drop through porous metal by experimental investigation. Pressure drop of air passing through porous metal was measured. The influences of porosity and flow velocity on pressure drop were investigated and in view of friction factor, the experimental data was compared with theorical equation as known to Ergun's equation concerning unconsolid packed bed. The result of this study are as follows. The pressure drop was increased with increasing the flow velocity and at the same flow velocity with decreasing the porosity(decreasing the particle diameter), In Particular, the experimental equation for the pressure drop was derived using the particle diameter, matrix diameter and matrix thickness. The experimental data were correlated well(mean deviation ${\pm}15%$ )with the present empirical dimensionless equation.

• Journal of Gifted/Talented Education
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• v.26 no.4
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• pp.677-697
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• 2016

This study analyzed the difference in evaluation results in evaluating identical products by applying two different types of evaluating scales, Creative Product Analysis Matrix (CPAM) and Creative Product Semantic Scale (CPSS) by O'Quin and Bessember (1989). As a result, evaluation based on explicit knowledge scored lower than evaluation based on implicit knowledge, implying that the evaluation becomes stricter. When evaluated with CPSS, which as relatively more segmentalized grading criteria, all sub-dimensions of creativity showed low scores, and it show that when evaluator's first impression or personal evaluation standard on the products is firm, they may not be evaluated by the evaluation tools. Gifted education teachers were giving similar evaluations as experts in creative product evaluation, and understanding the product evaluation tool fully in advance before teaching or evaluating products may lead to the generation of newer, more useful and appropriate, and highly creative product with high solvability.

• Composites Research
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• v.25 no.3
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• pp.76-81
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• 2012

Atmospheric pressure plasma treatment on carbon nanotube (CNT) surfaces was performed to modify reinforcement effect and interfacial adhesion of carbon fiber reinforced CNT-phenolic composites. The surface changes occurring on CNT treated with plasma were analyzed by using Fourier transform infrared spectroscope (FT-IR). The significant improvement of wettability on CNT was confirmed by static contact angle test after plasma treatment. Such plasma treatment resulted in a decrease in the advancing contact angle from $118^{\circ}$ to $60^{\circ}$. The interfacial adhesion between carbon fiber and CNT-phenolic composites increased by plasma treatment based on apparent modulus test results during quasi-static tensile strength. Furthermore, the proposed database offers valuable knowledge for evaluating interfacial shear strength (IFSS).

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.8
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• pp.3917-3941
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• 2019

The recent interest in artificial intelligence and machine learning has partly contributed to an interest in the use of such approaches for hyperspectral remote sensing (HRS) imagery classification, as evidenced by the increasing number of deep framework with deep convolutional neural networks (CNN) structures proposed in the literature. In these approaches, the assumption of obtaining high quality deep features by using CNN is not always easy and efficient because of the complex data distribution and the limited sample size. In this paper, conventional handcrafted learning-based multi features based on expert knowledge are introduced as the input of a special designed CNN to improve the pixel description and classification performance of HRS imagery. The introduction of these handcrafted features can reduce the complexity of the original HRS data and reduce the sample requirements by eliminating redundant information and improving the starting point of deep feature training. It also provides some concise and effective features that are not readily available from direct training with CNN. Evaluations using three public HRS datasets demonstrate the utility of our proposed method in HRS classification.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.23 no.2
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• pp.109-132
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• 2012

This study examines the social network of scholars in the field of communication by using author cocitation data. A matrix containing the number of cocited documents between pairs of authors is created for social network analysis of scholars who are on the editorial board of Journal of Communication, and the networked map of the scholars is used to visualize the knowledge structure of the field by identifying groups of authors who are more central than others. In addition, the study compares the previous analysis performed in 2008 and the current analysis on the editorial board of the journal, which increased from 146 to 254 scholars in numbers. Author cocitation data was collected using Social Science Citation Index (SSCI) through the Web of Science database, and UCInet was used to create and visualize the author cocitation network and to analyze the correlation between the cocitation network and the factors that may have affected the structure of the cocitation network.

• Journal of Preventive Medicine and Public Health
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• v.41 no.6
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• pp.365-372
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• 2008

Objectives : There are very few researches on North Korea's academic activities. Furthermore, it is doubtful that the available data are reliable. This study investigated research activities and knowledge structure in the field of Preventive Medicine in North Korea with a network analysis using co-authors and keywords. Methods : The data was composed of the North Korean Journal of preventive medicine ranged from Vol. 1 of 1997 to Vol. 4 of 2006. It was the matrix of 1,172 articles by 1,567 co-authors. We applied R procedure for keywords abstraction, and then sought for the outcome of network forms by spring-KK and shrinking network. Results : To comprehend the whole networks explicitly demonstrated that the academic activities in North Korea s preventive medicine were predisposed to centralization as similar as South Korea's, but on the other aspect they were prone to one-off intermittent segmentation. The principal co-author networks were formulated around some outstanding medical universities seemingly in addition to possible intervention by major researchers. The knowledge structure of network was based on experimentation judging from keywords such as drug, immunity, virus detection, infection, bacteria, anti-inflammation, etc. Conclusions : Though North Korea is a socialist regime, there were network of academic activities, which were deemed the existence of inducive mechanism affordable for free research. Article keywords has laid greater emphasis on experiment-based bacterial defection, sustainable immune system and prevention of infection. The kind of trend was a consistent characteristic in preventive medicine of North Korea haying close correlation with Koryo medical science.

• 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.