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Resolving the 'Gray sheep' Problem Using Social Network Analysis (SNA) in Collaborative Filtering (CF) Recommender Systems (소셜 네트워크 분석 기법을 활용한 협업필터링의 특이취향 사용자(Gray Sheep) 문제 해결)

  • Kim, Minsung;Im, Il
    • Journal of Intelligence and Information Systems
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    • v.20 no.2
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    • pp.137-148
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    • 2014
  • Recommender system has become one of the most important technologies in e-commerce in these days. The ultimate reason to shop online, for many consumers, is to reduce the efforts for information search and purchase. Recommender system is a key technology to serve these needs. Many of the past studies about recommender systems have been devoted to developing and improving recommendation algorithms and collaborative filtering (CF) is known to be the most successful one. Despite its success, however, CF has several shortcomings such as cold-start, sparsity, gray sheep problems. In order to be able to generate recommendations, ordinary CF algorithms require evaluations or preference information directly from users. For new users who do not have any evaluations or preference information, therefore, CF cannot come up with recommendations (Cold-star problem). As the numbers of products and customers increase, the scale of the data increases exponentially and most of the data cells are empty. This sparse dataset makes computation for recommendation extremely hard (Sparsity problem). Since CF is based on the assumption that there are groups of users sharing common preferences or tastes, CF becomes inaccurate if there are many users with rare and unique tastes (Gray sheep problem). This study proposes a new algorithm that utilizes Social Network Analysis (SNA) techniques to resolve the gray sheep problem. We utilize 'degree centrality' in SNA to identify users with unique preferences (gray sheep). Degree centrality in SNA refers to the number of direct links to and from a node. In a network of users who are connected through common preferences or tastes, those with unique tastes have fewer links to other users (nodes) and they are isolated from other users. Therefore, gray sheep can be identified by calculating degree centrality of each node. We divide the dataset into two, gray sheep and others, based on the degree centrality of the users. Then, different similarity measures and recommendation methods are applied to these two datasets. More detail algorithm is as follows: Step 1: Convert the initial data which is a two-mode network (user to item) into an one-mode network (user to user). Step 2: Calculate degree centrality of each node and separate those nodes having degree centrality values lower than the pre-set threshold. The threshold value is determined by simulations such that the accuracy of CF for the remaining dataset is maximized. Step 3: Ordinary CF algorithm is applied to the remaining dataset. Step 4: Since the separated dataset consist of users with unique tastes, an ordinary CF algorithm cannot generate recommendations for them. A 'popular item' method is used to generate recommendations for these users. The F measures of the two datasets are weighted by the numbers of nodes and summed to be used as the final performance metric. In order to test performance improvement by this new algorithm, an empirical study was conducted using a publically available dataset - the MovieLens data by GroupLens research team. We used 100,000 evaluations by 943 users on 1,682 movies. The proposed algorithm was compared with an ordinary CF algorithm utilizing 'Best-N-neighbors' and 'Cosine' similarity method. The empirical results show that F measure was improved about 11% on average when the proposed algorithm was used

    . Past studies to improve CF performance typically used additional information other than users' evaluations such as demographic data. Some studies applied SNA techniques as a new similarity metric. This study is novel in that it used SNA to separate dataset. This study shows that performance of CF can be improved, without any additional information, when SNA techniques are used as proposed. This study has several theoretical and practical implications. This study empirically shows that the characteristics of dataset can affect the performance of CF recommender systems. This helps researchers understand factors affecting performance of CF. This study also opens a door for future studies in the area of applying SNA to CF to analyze characteristics of dataset. In practice, this study provides guidelines to improve performance of CF recommender systems with a simple modification.

  • Evaluating Reverse Logistics Networks with Centralized Centers : Hybrid Genetic Algorithm Approach (집중형센터를 가진 역물류네트워크 평가 : 혼합형 유전알고리즘 접근법)

    • Yun, YoungSu
      • Journal of Intelligence and Information Systems
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      • v.19 no.4
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      • pp.55-79
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      • 2013
    • In this paper, we propose a hybrid genetic algorithm (HGA) approach to effectively solve the reverse logistics network with centralized centers (RLNCC). For the proposed HGA approach, genetic algorithm (GA) is used as a main algorithm. For implementing GA, a new bit-string representation scheme using 0 and 1 values is suggested, which can easily make initial population of GA. As genetic operators, the elitist strategy in enlarged sampling space developed by Gen and Chang (1997), a new two-point crossover operator, and a new random mutation operator are used for selection, crossover and mutation, respectively. For hybrid concept of GA, an iterative hill climbing method (IHCM) developed by Michalewicz (1994) is inserted into HGA search loop. The IHCM is one of local search techniques and precisely explores the space converged by GA search. The RLNCC is composed of collection centers, remanufacturing centers, redistribution centers, and secondary markets in reverse logistics networks. Of the centers and secondary markets, only one collection center, remanufacturing center, redistribution center, and secondary market should be opened in reverse logistics networks. Some assumptions are considered for effectively implementing the RLNCC The RLNCC is represented by a mixed integer programming (MIP) model using indexes, parameters and decision variables. The objective function of the MIP model is to minimize the total cost which is consisted of transportation cost, fixed cost, and handling cost. The transportation cost is obtained by transporting the returned products between each centers and secondary markets. The fixed cost is calculated by opening or closing decision at each center and secondary markets. That is, if there are three collection centers (the opening costs of collection center 1 2, and 3 are 10.5, 12.1, 8.9, respectively), and the collection center 1 is opened and the remainders are all closed, then the fixed cost is 10.5. The handling cost means the cost of treating the products returned from customers at each center and secondary markets which are opened at each RLNCC stage. The RLNCC is solved by the proposed HGA approach. In numerical experiment, the proposed HGA and a conventional competing approach is compared with each other using various measures of performance. For the conventional competing approach, the GA approach by Yun (2013) is used. The GA approach has not any local search technique such as the IHCM proposed the HGA approach. As measures of performance, CPU time, optimal solution, and optimal setting are used. Two types of the RLNCC with different numbers of customers, collection centers, remanufacturing centers, redistribution centers and secondary markets are presented for comparing the performances of the HGA and GA approaches. The MIP models using the two types of the RLNCC are programmed by Visual Basic Version 6.0, and the computer implementing environment is the IBM compatible PC with 3.06Ghz CPU speed and 1GB RAM on Windows XP. The parameters used in the HGA and GA approaches are that the total number of generations is 10,000, population size 20, crossover rate 0.5, mutation rate 0.1, and the search range for the IHCM is 2.0. Total 20 iterations are made for eliminating the randomness of the searches of the HGA and GA approaches. With performance comparisons, network representations by opening/closing decision, and convergence processes using two types of the RLNCCs, the experimental result shows that the HGA has significantly better performance in terms of the optimal solution than the GA, though the GA is slightly quicker than the HGA in terms of the CPU time. Finally, it has been proved that the proposed HGA approach is more efficient than conventional GA approach in two types of the RLNCC since the former has a GA search process as well as a local search process for additional search scheme, while the latter has a GA search process alone. For a future study, much more large-sized RLNCCs will be tested for robustness of our approach.

    A Study on improvement of curriculum in Nursing (간호학 교과과정 개선을 위한 조사 연구)

    • 김애실
      • Journal of Korean Academy of Nursing
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      • v.4 no.2
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      • pp.1-16
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      • 1974
    • This Study involved the development of a survey form and the collection of data in an effort-to provide information which can be used in the improvement of nursing curricula. The data examined were the kinds courses currently being taught in the curricula of nursing education institutions throughout Korea, credits required for course completion, and year in-which courses are taken. For the purposes of this study, curricula were classified into college, nursing school and vocational school categories. Courses were directed into the 3 major categories of general education courses, supporting science courses and professional education course, and further subdirector as. follows: 1) General education (following the classification of Philip H. phoenix): a) Symbolics, b) Empirics, c) Aesthetics. 4) Synthetics, e) Ethics, f) Synoptic. 2) Supporting science: a) physical science, b) biological science, c) social science, d) behavioral science, e) Health science, f) Educations 3) Professional Education; a) basic courses, b) courses in each of the respective fields of nursing. Ⅰ. General Education aimed at developing the individual as a person and as a member of society is relatively strong in college curricula compared with the other two. a) Courses included in the category of symbolics included Korean language, English, German. Chines. Mathematics. Statics: Economics and Computer most college curricula included 20 credits. of courses in this sub-category, while nursing schools required 12 credits and vocational school 10 units. English ordinarily receives particularly heavy emphasis. b) Research methodology, Domestic affair and women & courtney was included under the category of empirics in the college curricula, nursing and vocational school do not offer this at all. c) Courses classified under aesthetics were physical education, drill, music, recreation and fine arts. Most college curricula had 4 credits in these areas, nursing school provided for 2 credits, and most vocational schools offered 10 units. d) Synoptic included leadership, interpersonal relationship, and communications, Most schools did not offer courses of this nature. e) The category of ethics included citizenship. 2 credits are provided in college curricula, while vocational schools require 4 units. Nursing schools do not offer these courses. f) Courses included under synoptic were Korean history, cultural history, philosophy, Logics, and religion. Most college curricular 5 credits in these areas, nursing schools 4 credits. and vocational schools 2 units. g) Only physical education was given every Year in college curricula and only English was given in nursing schools and vocational schools in every of the curriculum. Most of the other courses were given during the first year of the curriculum. Ⅱ. Supporting science courses are fundamental to the practice and application of nursing theory. a) Physical science course include physics, chemistry and natural science. most colleges and nursing schools provided for 2 credits of physical science courses in their curricula, while most vocational schools did not offer t me. b) Courses included under biological science were anatomy, physiologic, biology and biochemistry. Most college curricula provided for 15 credits of biological science, nursing schools for the most part provided for 11 credits, and most vocational schools provided for 8 units. c) Courses included under social science were sociology and anthropology. Most colleges provided for 1 credit in courses of this category, which most nursing schools provided for 2 creates Most vocational school did not provide courses of this type. d) Courses included under behavioral science were general and clinical psychology, developmental psychology. mental hygiene and guidance. Most schools did not provide for these courses. e) Courses included under health science included pharmacy and pharmacology, microbiology, pathology, nutrition and dietetics, parasitology, and Chinese medicine. Most college curricula provided for 11 credits, while most nursing schools provide for 12 credits, most part provided 20 units of medical courses. f) Courses included under education included educational psychology, principles of education, philosophy of education, history of education, social education, educational evaluation, educational curricula, class management, guidance techniques and school & community. Host college softer 3 credits in courses in this category, while nursing schools provide 8 credits and vocational schools provide for 6 units, 50% of the colleges prepare these students to qualify as regular teachers of the second level, while 91% of the nursing schools and 60% of the vocational schools prepare their of the vocational schools prepare their students to qualify as school nurse. g) The majority of colleges start supporting science courses in the first year and complete them by the second year. Nursing schools and vocational schools usually complete them in the first year. Ⅲ. Professional Education courses are designed to develop professional nursing knowledge, attitudes and skills in the students. a) Basic courses include social nursing, nursing ethics, history of nursing professional control, nursing administration, social medicine, social welfare, introductory nursing, advanced nursing, medical regulations, efficient nursing, nursing english and basic nursing, College curricula devoted 13 credits to these subjects, nursing schools 14 credits, and vocational schools 26 units indicating a severe difference in the scope of education provided. b) There was noticeable tendency for the colleges to take a unified approach to the branches of nursing. 60% of the schools had courses in public health nursing, 80% in pediatric nursing, 60% in obstetric nursing, 90% in psychiatric nursing and 80% in medical-surgical nursing. The greatest number of schools provided 48 crudites in all of these fields combined. in most of the nursing schools, 52 credits were provided for courses divided according to disease. in the vocational schools, unified courses are provided in public health nursing, child nursing, maternal nursing, psychiatric nursing and adult nursing. In addition, one unit is provided for one hour a week of practice. The total number of units provided in the greatest number of vocational schools is thus Ⅲ units double the number provided in nursing schools and colleges. c) In th leges, the second year is devoted mainly to basic nursing courses, while the third and fourth years are used for advanced nursing courses. In nursing schools and vocational schools, the first year deals primarily with basic nursing and the second and third years are used to cover advanced nursing courses. The study yielded the following conclusions. 1. Instructional goals should be established for each courses in line with the idea of nursing, and curriculum improvements should be made accordingly. 2. Course that fall under the synthetics category should be strengthened and ways should be sought to develop the ability to cooperate with those who work for human welfare and health. 3. The ability to solve problems on the basis of scientific principles and knowledge and understanding of man society should be fostered through a strengthening of courses dealing with physical sciences, social sciences and behavioral sciences and redistribution of courses emphasizing biological and health sciences. 4. There should be more balanced curricula with less emphasis on courses in the major There is a need to establish courses necessary for the individual nurse by doing away with courses centered around specific diseases and combining them in unified courses. In addition it is possible to develop skill in dealing with people by using the social setting in comprehensive training. The most efficient ratio of the study experience should be studied to provide more effective, interesting education Elective course should be initiated to insure a man flexible, responsive educational program. 5. The curriculum stipulated in the education law should be examined.

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    A Study on Public Nuisance in Seoul, Pusan and Daegu Cities Part I. Survey on Air Pollution and Noise Level (공해(公害)에 관(關)한 조사연구(調査硏究) 제일편(第一編) : 서울, 부산(釜山), 대구(大邱) 지역(地域)의 대기오염(大氣汚染) 및 소음(騷音)에 관(關)한 비교조사(比較調査) 연구(硏究))

    • Cha, Chul-Hwan;Shin, Young-Soo;Lee, Young-Il;Cho, Kwang-Soo;Choo, Chong-Yoo;Kim, Kyo-Sung;Choi, Dug-Il
      • Journal of Preventive Medicine and Public Health
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      • v.4 no.1
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      • pp.41-64
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      • 1971
    • During the period from July 1st to the end of November 1970, a survey on air pollution and noise level was made in Seoul, Pusan and Taegu, the three largest cities in Korea. Each city was divided into 4-6 areas; the industrial area, the semi-industrial area, the commercial area, the residential area, the park area and the downtown area. Thirty eight sites were selected from each area. A. Method of Measurement : Dustfall was measured by the Deposit Gauge Method, sulfur oxides by $PbO_2$ cylinder method, suspended particles by the Digital Dust Indicator, Sulfur dioxide ($SO_2$) and Carbon Monoxide (CO) by the MSA & Kitakawa Detector and the noise levels by Rion Sound Survey meter. B. Results: 1. The mean value of dustfall in 3 cities was $30.42ton/km^2/month$, ranging from 8.69 to 95.44. 2. The mean values of dustfall by city were $33.17ton/km^2/month$ in Seoul, 32.11 in Pusan and 25.97 in Taegu. 3. The mean values of dustfall showed a trend of decreasing order of semi-industrial area, downtown area, industrial area, commercial area, residential area, and park area. 4. The mean value of dustfall in Seoul by area were $52.32ton/km^2/month$ in downtown, 50.54 in semi-industrial area, 40.37 in industrial area, 24,19 in commercial area, 16.25 in park area and 15.39 in residential area in order of concentration. 5. The mean values of dustfall in Pusan by area were $48.27ton/km^2/month$ in semi-industrial area, 36.68 in industrial area 25.31 in commercial area, and 18.19 in residential area. 6. The mean values of dustfall in Taegu by area were $36.46ton/km^2/month$ in downtown area, 33.52 in industrial area, 20.37 in commercial area and 13.55 in residential area. 7. The mean values of sulfur oxides in 3 cities were $1.52mg\;SO_3/day/100cm^2\;PbO_2$, ranging from 0.32 to 4.72. 8. The mean values of sulfur oxides by city were $1.89mg\;SO_3/day/100cm^2\;PbO_2$ in Pusan, 1.64 in Seoul and 1.21 in Taegu. 9. The mean values of sulfur oxides by area in 3 cities were $2.16mg\;SO_3/day/100cm^2\;PbO_2$ in industrial area, 1.69 in semi-industrial area, 1.50 in commercial area, 1.48 in downtown area, 1.32 in residential area and 0.94 in the park area, respectively. 10. The monthly mean values of sulfur oxides contents showed a steady increase from July reaching a peak in November. 11. The mean values of suspended particles was $2.89mg/m^3$, ranging from 1.15 to 5.27. 12. The mean values of suspended particles by city were $3.14mg/m^3$ in Seoul, 2.79 in Taegu and 2.25 in Pusan. 13. The mean values of noise level in 3 cities was 71.3 phon, ranging from 49 to 99 phon. 14. The mean values of noise level by city were 73 phon in Seoul, 72 in Pusan, and 69 in Taegu in that order. 15. The mean values of noise level by area in 3 cities showed a decrease in the order of the downtown area, commercial area, industrial area and semi-industrial area, park area and residential area. 16. The comparison of the noise levels by area in 3 cities indicated that the highest level was detected in the downtown area in Seoul and Taegu and in the industrial area in Pusan. 17. The daily average concentration of sulfur dioxides ($SO_2$) in 3 cities was 0.081 ppm, ranging from 0.004 to 0.196. 18. The daily average concentrations of sulfur dioxides by city were 0.092 ppm in Seoul, 0.089 in Pusan and 0.062 in Taegu in that order. 19. The weekly average concentration of carbon monoxides(CO) was 27.59 ppm. 20. The daily average concentrations of carbon monoxides by city were 33.37 ppm. in Seoul, 25.76 in Pusan and 23.65 in Taegu in that order. 21. The concentration of $SO_2$ and CO reaches a peak from 6 p. m. to 8 p. m. 22. About 3 times probably the daily average concentration of CO could be detected in the downtown area probably due to heavy traffic emission in comparison with that in the industial area. 23. As for daily variation of the concentration of $SO_2$ and CO it was found that the concentration maintains relatively higher value during weekdays in the industrial area and on the first part of the week in the downtown area.

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    Diagnostic Value of ADA Multiplied by Lymphocyte to Neutrophil Ratio in Tuberculous Pleurisy (결핵성 흉막염에서 ADA 활성도와 림프구/중성구 비의 곱의 진단적 유용성)

    • Jeon, Eun Ju;Kwak, Hee Won;Song, Ju Han;Lee, Young Woo;Jeong, Jae Woo;Choi, Jae Cheol;Shin, Jong Wook;Kim, Jae Yeol;Park, In Won;Choi, Byoung Whui
      • Tuberculosis and Respiratory Diseases
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      • v.63 no.1
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      • pp.17-23
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      • 2007
    • Background: Many diagnostic approaches for defining the definitive cause of pleurisy should be included due to the large variety of diseases resulting in pleural effusion. Although ADA is a useful diagnostic tool for making a differential diagnosis of pleural effusion, particularly for tuberculous pleural effusion, a definitive diagnostic cut-off value remains problematic in Korea. It was hypothesized that ADA multiplied by the Lymphocyte/Neutrophil ratio(L/N ratio) might be more powerful for making a differential diagnosis of pleural effusion. Methods: One hundred and ninety patients, who underwent thoracentesis and treatment in Chung-Ang University Hospital from January, 2005 through to February 2006, were evaluated. The clinical characteristics, radiologic data and the examination of the pleural effusion were analyzed retrospectively. Results: 1. Among the 190 patients, 59 patients (31.1%) were diagnosed with tuberculous pleurisy, 45 patients(23.7%) with parapneumonic effusion, 42 patients(22.1%) with malignant effusions, 36 patients(18.9%) with transudate, and 8 patients(4.2%) with empyema. One hundred and twenty one patients were found to have an ADA activity of 1 to 39 IU/L(63.7%). Twenty-nine were found to have an ADA activity of 40 to 75 IU/L(15.3%) and 40 were found to have an ADA activity of 75 IU/L or greater(21.0%). 2. Among the patients with tuberculous pleurisy, 5(8%), 18(30%) and 36 patients(60%) had an ADA activity ranging from 1 to 39 IU/L, 40 to 75 IU/L, and 75 IU/L or greater, respectively. In those with an ADA activitiy 40 to 75 IU/L, 18 patients(62%) had tuberculous pleurisy, 9(31%) had parapneumonic effusion and empyema, and 1(3.4%) had a malignant effusion. 3. In those with an ADA activity of 40 to 75 IU/L, there was no significant difference between tuberculous pleurisy and non-tuberculous pleural effusion(tuberculous pleurisy : 61.3 ${\pm}$ 9.2 IU/L, non-tuberculous pleural effusion : 53.3${\pm}$10.5 IU/L). 4. The mean L/N ratio of those with tuberculous pleurisy was 39.1 ${\pm}$ 44.6, which was significantly higher than nontuberculous pleural effusion patients (p<0.05). The mean ADA x L/N ratio of the tuberculous pleurisy patients was 2,445.7 ${\pm}$ 2,818.5, which was significantly higher than the non-tuberculous pleural effusion patients (level p<0.05). 5. ROC analysis showed that the ADA x L/N ratio had a higher diagnostic value than the ADA alone in the group with an ADA between 40-75 IU/L. Conclusion: The ADA multiplied by the lymphocyte-to-neutrophil ratio might provide a more definitive diagnosis of tuberculous pleurisy.

    THE EFFECT OF INTERMITTENT COMPOSITE CURING ON MARGINAL ADAPTATION (복합레진의 간헐적 광중합 방법이 변연적합도에 미치는 영향)

    • Yun, Yong-Hwan;Park, Sung-Ho
      • Restorative Dentistry and Endodontics
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      • v.32 no.3
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      • pp.248-259
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      • 2007
    • The aim of this research was to study the effect of intermittent polymerization on marginal adaptation by comparing the marginal adaptation of intermittently polymerized composite to that of continuously polymerized composite. The materials used for this study were Pyramid (Bisco Inc., Schaumburg, U.S.A.) and Heliomolar (Ivoclar Vivadent, Liechtenstein) . The experiment was carried out in class II MOD cavities prepared in 48 extracted human maxillary premolars. The samples were divided into 4 groups by light curing method: group 1- continuous curing (60s light on with no light off), group 2-intermittent curing (cycles of 3s with 2s light on & 1s light off for 90s); group 3- intermittent curing (cycles of 2s with 1s light on & 1s light off for 120s); group 4- intermittent curing (cycles of 3s with 1s light on & 2s light off for 180s). Consequently the total amount of light energy radiated was same in all the groups. Each specimen went through thermo-mechanical loading (TML) which consisted of mechanical loading (720,000 cycles, 5.0 kg) with a speed of 120 rpm for 100hours and thermocycling (6000 thermocycles of alternating water of $50^{\circ}C$ and $55^{\circ}C$). The continuous margin (CM) (%) of the total margin and regional margins, occlusal enamel (OE), vertical enamel (VE), and cervical enamel (CE) was measured before and after TML under a $\times200$ digital light microscope. Three-way ANOVA and Duncan's Multiple Range Test was performed at 95% level of confidence to test the effect of 3 variables on CM (%) of the total margin: light curing conditions, composite materials and effect of TML. In each group, One-way ANOVA and Duncan's Multiple Range Test was additionally performed to compare CM (%) of regions (OE, VE CE). The results indicated that all the three variables were statistically significant (p < 0.05). Before TML, in groups using Pyramid, groups 3 and 4 showed higher CM (%) than groups 1 and 2, and in groups using Heliomolar. groups 3 and 4 showed higher CM (%) than group 1 (p < 0.05). After TML, in both Pyramid and Heliomo)ar groups, group 3 showed higher CM (%) than group 1 (p < 0.05) CM (%) of the regions are significantly different in each group (p < 0.05). Before TML, no statistical difference was found between groups within the VE and CE region. In the OE region, group 4 of Pyramid showed higher CM (%) than group 2, and groups 2 and 4 of Heliomolar showed higher CM (%) than group 1 (p < 0.05). After TML, no statistical difference was found among groups within the VE and CE region. In the OE region, group 3 of Pyramid showed higher CM (%) than groups 1 and 2, and groups 2,3 and 4 of Heliomolar showed higher CM (%) than group 1 (p < 0.05). It was concluded that intermittent polymerization may be effective in reducing marginal gap formation.

    The Framework of Research Network and Performance Evaluation on Personal Information Security: Social Network Analysis Perspective (개인정보보호 분야의 연구자 네트워크와 성과 평가 프레임워크: 소셜 네트워크 분석을 중심으로)

    • Kim, Minsu;Choi, Jaewon;Kim, Hyun Jin
      • Journal of Intelligence and Information Systems
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      • v.20 no.1
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      • pp.177-193
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      • 2014
    • Over the past decade, there has been a rapid diffusion of electronic commerce and a rising number of interconnected networks, resulting in an escalation of security threats and privacy concerns. Electronic commerce has a built-in trade-off between the necessity of providing at least some personal information to consummate an online transaction, and the risk of negative consequences from providing such information. More recently, the frequent disclosure of private information has raised concerns about privacy and its impacts. This has motivated researchers in various fields to explore information privacy issues to address these concerns. Accordingly, the necessity for information privacy policies and technologies for collecting and storing data, and information privacy research in various fields such as medicine, computer science, business, and statistics has increased. The occurrence of various information security accidents have made finding experts in the information security field an important issue. Objective measures for finding such experts are required, as it is currently rather subjective. Based on social network analysis, this paper focused on a framework to evaluate the process of finding experts in the information security field. We collected data from the National Discovery for Science Leaders (NDSL) database, initially collecting about 2000 papers covering the period between 2005 and 2013. Outliers and the data of irrelevant papers were dropped, leaving 784 papers to test the suggested hypotheses. The co-authorship network data for co-author relationship, publisher, affiliation, and so on were analyzed using social network measures including centrality and structural hole. The results of our model estimation are as follows. With the exception of Hypothesis 3, which deals with the relationship between eigenvector centrality and performance, all of our hypotheses were supported. In line with our hypothesis, degree centrality (H1) was supported with its positive influence on the researchers' publishing performance (p<0.001). This finding indicates that as the degree of cooperation increased, the more the publishing performance of researchers increased. In addition, closeness centrality (H2) was also positively associated with researchers' publishing performance (p<0.001), suggesting that, as the efficiency of information acquisition increased, the more the researchers' publishing performance increased. This paper identified the difference in publishing performance among researchers. The analysis can be used to identify core experts and evaluate their performance in the information privacy research field. The co-authorship network for information privacy can aid in understanding the deep relationships among researchers. In addition, extracting characteristics of publishers and affiliations, this paper suggested an understanding of the social network measures and their potential for finding experts in the information privacy field. Social concerns about securing the objectivity of experts have increased, because experts in the information privacy field frequently participate in political consultation, and business education support and evaluation. In terms of practical implications, this research suggests an objective framework for experts in the information privacy field, and is useful for people who are in charge of managing research human resources. This study has some limitations, providing opportunities and suggestions for future research. Presenting the difference in information diffusion according to media and proximity presents difficulties for the generalization of the theory due to the small sample size. Therefore, further studies could consider an increased sample size and media diversity, the difference in information diffusion according to the media type, and information proximity could be explored in more detail. Moreover, previous network research has commonly observed a causal relationship between the independent and dependent variable (Kadushin, 2012). In this study, degree centrality as an independent variable might have causal relationship with performance as a dependent variable. However, in the case of network analysis research, network indices could be computed after the network relationship is created. An annual analysis could help mitigate this limitation.

    Rough Set Analysis for Stock Market Timing (러프집합분석을 이용한 매매시점 결정)

    • Huh, Jin-Nyung;Kim, Kyoung-Jae;Han, In-Goo
      • Journal of Intelligence and Information Systems
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      • v.16 no.3
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      • pp.77-97
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      • 2010
    • Market timing is an investment strategy which is used for obtaining excessive return from financial market. In general, detection of market timing means determining when to buy and sell to get excess return from trading. In many market timing systems, trading rules have been used as an engine to generate signals for trade. On the other hand, some researchers proposed the rough set analysis as a proper tool for market timing because it does not generate a signal for trade when the pattern of the market is uncertain by using the control function. The data for the rough set analysis should be discretized of numeric value because the rough set only accepts categorical data for analysis. Discretization searches for proper "cuts" for numeric data that determine intervals. All values that lie within each interval are transformed into same value. In general, there are four methods for data discretization in rough set analysis including equal frequency scaling, expert's knowledge-based discretization, minimum entropy scaling, and na$\ddot{i}$ve and Boolean reasoning-based discretization. Equal frequency scaling fixes a number of intervals and examines the histogram of each variable, then determines cuts so that approximately the same number of samples fall into each of the intervals. Expert's knowledge-based discretization determines cuts according to knowledge of domain experts through literature review or interview with experts. Minimum entropy scaling implements the algorithm based on recursively partitioning the value set of each variable so that a local measure of entropy is optimized. Na$\ddot{i}$ve and Booleanreasoning-based discretization searches categorical values by using Na$\ddot{i}$ve scaling the data, then finds the optimized dicretization thresholds through Boolean reasoning. Although the rough set analysis is promising for market timing, there is little research on the impact of the various data discretization methods on performance from trading using the rough set analysis. In this study, we compare stock market timing models using rough set analysis with various data discretization methods. The research data used in this study are the KOSPI 200 from May 1996 to October 1998. KOSPI 200 is the underlying index of the KOSPI 200 futures which is the first derivative instrument in the Korean stock market. The KOSPI 200 is a market value weighted index which consists of 200 stocks selected by criteria on liquidity and their status in corresponding industry including manufacturing, construction, communication, electricity and gas, distribution and services, and financing. The total number of samples is 660 trading days. In addition, this study uses popular technical indicators as independent variables. The experimental results show that the most profitable method for the training sample is the na$\ddot{i}$ve and Boolean reasoning but the expert's knowledge-based discretization is the most profitable method for the validation sample. In addition, the expert's knowledge-based discretization produced robust performance for both of training and validation sample. We also compared rough set analysis and decision tree. This study experimented C4.5 for the comparison purpose. The results show that rough set analysis with expert's knowledge-based discretization produced more profitable rules than C4.5.

    Open Digital Textbook for Smart Education (스마트교육을 위한 오픈 디지털교과서)

    • Koo, Young-Il;Park, Choong-Shik
      • Journal of Intelligence and Information Systems
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      • v.19 no.2
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      • pp.177-189
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      • 2013
    • In Smart Education, the roles of digital textbook is very important as face-to-face media to learners. The standardization of digital textbook will promote the industrialization of digital textbook for contents providers and distributers as well as learner and instructors. In this study, the following three objectives-oriented digital textbooks are looking for ways to standardize. (1) digital textbooks should undertake the role of the media for blended learning which supports on-off classes, should be operating on common EPUB viewer without special dedicated viewer, should utilize the existing framework of the e-learning learning contents and learning management. The reason to consider the EPUB as the standard for digital textbooks is that digital textbooks don't need to specify antoher standard for the form of books, and can take advantage od industrial base with EPUB standards-rich content and distribution structure (2) digital textbooks should provide a low-cost open market service that are currently available as the standard open software (3) To provide appropriate learning feedback information to students, digital textbooks should provide a foundation which accumulates and manages all the learning activity information according to standard infrastructure for educational Big Data processing. In this study, the digital textbook in a smart education environment was referred to open digital textbook. The components of open digital textbooks service framework are (1) digital textbook terminals such as smart pad, smart TVs, smart phones, PC, etc., (2) digital textbooks platform to show and perform digital contents on digital textbook terminals, (3) learning contents repository, which exist on the cloud, maintains accredited learning, (4) App Store providing and distributing secondary learning contents and learning tools by learning contents developing companies, and (5) LMS as a learning support/management tool which on-site class teacher use for creating classroom instruction materials. In addition, locating all of the hardware and software implement a smart education service within the cloud must have take advantage of the cloud computing for efficient management and reducing expense. The open digital textbooks of smart education is consdered as providing e-book style interface of LMS to learners. In open digital textbooks, the representation of text, image, audio, video, equations, etc. is basic function. But painting, writing, problem solving, etc are beyond the capabilities of a simple e-book. The Communication of teacher-to-student, learner-to-learnert, tems-to-team is required by using the open digital textbook. To represent student demographics, portfolio information, and class information, the standard used in e-learning is desirable. To process learner tracking information about the activities of the learner for LMS(Learning Management System), open digital textbook must have the recording function and the commnincating function with LMS. DRM is a function for protecting various copyright. Currently DRMs of e-boook are controlled by the corresponding book viewer. If open digital textbook admitt DRM that is used in a variety of different DRM standards of various e-book viewer, the implementation of redundant features can be avoided. Security/privacy functions are required to protect information about the study or instruction from a third party UDL (Universal Design for Learning) is learning support function for those with disabilities have difficulty in learning courses. The open digital textbook, which is based on E-book standard EPUB 3.0, must (1) record the learning activity log information, and (2) communicate with the server to support the learning activity. While the recording function and the communication function, which is not determined on current standards, is implemented as a JavaScript and is utilized in the current EPUB 3.0 viewer, ths strategy of proposing such recording and communication functions as the next generation of e-book standard, or special standard (EPUB 3.0 for education) is needed. Future research in this study will implement open source program with the proposed open digital textbook standard and present a new educational services including Big Data analysis.

    A Study on Recent Research Trend in Management of Technology Using Keywords Network Analysis (키워드 네트워크 분석을 통해 살펴본 기술경영의 최근 연구동향)

    • Kho, Jaechang;Cho, Kuentae;Cho, Yoonho
      • Journal of Intelligence and Information Systems
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      • v.19 no.2
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      • pp.101-123
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      • 2013
    • Recently due to the advancements of science and information technology, the socio-economic business areas are changing from the industrial economy to a knowledge economy. Furthermore, companies need to do creation of new value through continuous innovation, development of core competencies and technologies, and technological convergence. Therefore, the identification of major trends in technology research and the interdisciplinary knowledge-based prediction of integrated technologies and promising techniques are required for firms to gain and sustain competitive advantage and future growth engines. The aim of this paper is to understand the recent research trend in management of technology (MOT) and to foresee promising technologies with deep knowledge for both technology and business. Furthermore, this study intends to give a clear way to find new technical value for constant innovation and to capture core technology and technology convergence. Bibliometrics is a metrical analysis to understand literature's characteristics. Traditional bibliometrics has its limitation not to understand relationship between trend in technology management and technology itself, since it focuses on quantitative indices such as quotation frequency. To overcome this issue, the network focused bibliometrics has been used instead of traditional one. The network focused bibliometrics mainly uses "Co-citation" and "Co-word" analysis. In this study, a keywords network analysis, one of social network analysis, is performed to analyze recent research trend in MOT. For the analysis, we collected keywords from research papers published in international journals related MOT between 2002 and 2011, constructed a keyword network, and then conducted the keywords network analysis. Over the past 40 years, the studies in social network have attempted to understand the social interactions through the network structure represented by connection patterns. In other words, social network analysis has been used to explain the structures and behaviors of various social formations such as teams, organizations, and industries. In general, the social network analysis uses data as a form of matrix. In our context, the matrix depicts the relations between rows as papers and columns as keywords, where the relations are represented as binary. Even though there are no direct relations between papers who have been published, the relations between papers can be derived artificially as in the paper-keyword matrix, in which each cell has 1 for including or 0 for not including. For example, a keywords network can be configured in a way to connect the papers which have included one or more same keywords. After constructing a keywords network, we analyzed frequency of keywords, structural characteristics of keywords network, preferential attachment and growth of new keywords, component, and centrality. The results of this study are as follows. First, a paper has 4.574 keywords on the average. 90% of keywords were used three or less times for past 10 years and about 75% of keywords appeared only one time. Second, the keyword network in MOT is a small world network and a scale free network in which a small number of keywords have a tendency to become a monopoly. Third, the gap between the rich (with more edges) and the poor (with fewer edges) in the network is getting bigger as time goes on. Fourth, most of newly entering keywords become poor nodes within about 2~3 years. Finally, keywords with high degree centrality, betweenness centrality, and closeness centrality are "Innovation," "R&D," "Patent," "Forecast," "Technology transfer," "Technology," and "SME". The results of analysis will help researchers identify major trends in MOT research and then seek a new research topic. We hope that the result of the analysis will help researchers of MOT identify major trends in technology research, and utilize as useful reference information when they seek consilience with other fields of study and select a new research topic.


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