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A Study on the Utilization Level of Traditional Medicine by Residents - On the basis of Use of Folk Medical Techniques - (주민(住民)의 전통의술(傳統醫術) 이용도(利用度) 조사연구(調査硏究) - 민속요법(民俗療法) 이용(利用)을 중심(中心) 으로 -)

  • Kim, Jin-Soon
    • Journal of agricultural medicine and community health
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    • v.13 no.1
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    • pp.3-18
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    • 1988
  • The general objective of this research is to study behavioral pattern of health care utilization and to measure the level of utilization of the traditional medicine. The specific objective is to study utilization pattern and content of folk medicine which is the indegenous medical technology recognized part of traditional medicine. This research was under taken to generate valid information that will provide basis data for formulating general direction for health education activities and for designing service package for general population. A social survey method was employed to obtain required information for the research activities, The survey field team consisted of 20 surveyors who all participated is an intensive 2 day training course. A total of 3091 households were visited and interviewed by the field team during the period 7 September to 6 October 1987. The major findings obtained from the information collected by the field survey are as follows ; 1) General characteristics of the study households 2562 households out of 3091 households visited were selected for final data process, 80.2 of the selected households were nuclear families ; 17.4%, extended families ; others 2.4%. Only 4.3 percent of the study population in the urban households indicated "no schooling" whereas 14.2% of the rural household members falls within this category. Study population in the urban areas are more protected against diseases by the national medical insurance system than those in rural areas. In their self appraisal of living standard, those who responded with low group are 39.6% and 50.3% respectively by urban and rural households. 2) Morbidity status Period prevalence rate for all diseases during the preceding 15 days before the date of the household interview v as 243,0 per 1,000 study population. For cases with the illness duration of within 15 days, the initial points of medical entry were diversied ; 56.9%, drug stores ; 30.9%, clinics and hospitals ; 4.6% folk medicine ; 1.7% clinics of Korean oriental medicine. Among the chronic case; with illness duration of over 90 days, 34.6% of these people utilized clinics and hospitals of modern medicine ; 31.6%, drug stores ; 18.6% clinics of Korean oriental medicine ; 6.8% folk medical techniques. Noticeable is the almost ten fold increase from the mere 0.9% in the utilization of Korean oriental medicine, whereas in the utilization of folk medicine, it is short of two-fold increase. 3) Folk medicine and its utilization Households that use folk medicine for relief and care of signs and symptoms commonly encountered in daily life, number 1969 households, which accounts for 76.9% of all the study households. This rather high level use of folk medicine is not different from rural to urban areas. The order of frequency of utilizing folk medicine among the study people are : the highest 14.3% for the relief of indigestion ; 8.6% for burns ; 5.1% for common cold ; 4.7% for hiccough ; and 4.2% for hordeolum. A present various procedures of folk medicine is being used to relieve all kinds of symptoms. 192 symptoms are identified at present. The most frequently used procedures of folk medicine appear to be based either on principles of the Korean oriental medicine or of scientific knowledge. Based on these survey findings, proposals for utilizing folk medicine are as follows First, this survey's findings will be feed back to both on the job training and on the spot guidance of community health practitioners, public health nurses and other peripheral work force in the health field, who are in daily contacts with community. This feed back will assure that the health personnel carry out their health education and information activities that are based on the utilization pattern of folk medicine as found in the survey result. Second, studies will be soon implemented that are designed to measure the efficiency and potency of these procedures and to improve these procedures of folk medicine were most frequently used by the community. Third, studies will continue to systematize medicinal plants and skills of Korean oriental medicine that are easily available at minimal cost in daily life for the prevention of diseases and management of emergency cases.

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Comparison of Association Rule Learning and Subgroup Discovery for Mining Traffic Accident Data (교통사고 데이터의 마이닝을 위한 연관규칙 학습기법과 서브그룹 발견기법의 비교)

  • Kim, Jeongmin;Ryu, Kwang Ryel
    • Journal of Intelligence and Information Systems
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    • v.21 no.4
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    • pp.1-16
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    • 2015
  • Traffic accident is one of the major cause of death worldwide for the last several decades. According to the statistics of world health organization, approximately 1.24 million deaths occurred on the world's roads in 2010. In order to reduce future traffic accident, multipronged approaches have been adopted including traffic regulations, injury-reducing technologies, driving training program and so on. Records on traffic accidents are generated and maintained for this purpose. To make these records meaningful and effective, it is necessary to analyze relationship between traffic accident and related factors including vehicle design, road design, weather, driver behavior etc. Insight derived from these analysis can be used for accident prevention approaches. Traffic accident data mining is an activity to find useful knowledges about such relationship that is not well-known and user may interested in it. Many studies about mining accident data have been reported over the past two decades. Most of studies mainly focused on predict risk of accident using accident related factors. Supervised learning methods like decision tree, logistic regression, k-nearest neighbor, neural network are used for these prediction. However, derived prediction model from these algorithms are too complex to understand for human itself because the main purpose of these algorithms are prediction, not explanation of the data. Some of studies use unsupervised clustering algorithm to dividing the data into several groups, but derived group itself is still not easy to understand for human, so it is necessary to do some additional analytic works. Rule based learning methods are adequate when we want to derive comprehensive form of knowledge about the target domain. It derives a set of if-then rules that represent relationship between the target feature with other features. Rules are fairly easy for human to understand its meaning therefore it can help provide insight and comprehensible results for human. Association rule learning methods and subgroup discovery methods are representing rule based learning methods for descriptive task. These two algorithms have been used in a wide range of area from transaction analysis, accident data analysis, detection of statistically significant patient risk groups, discovering key person in social communities and so on. We use both the association rule learning method and the subgroup discovery method to discover useful patterns from a traffic accident dataset consisting of many features including profile of driver, location of accident, types of accident, information of vehicle, violation of regulation and so on. The association rule learning method, which is one of the unsupervised learning methods, searches for frequent item sets from the data and translates them into rules. In contrast, the subgroup discovery method is a kind of supervised learning method that discovers rules of user specified concepts satisfying certain degree of generality and unusualness. Depending on what aspect of the data we are focusing our attention to, we may combine different multiple relevant features of interest to make a synthetic target feature, and give it to the rule learning algorithms. After a set of rules is derived, some postprocessing steps are taken to make the ruleset more compact and easier to understand by removing some uninteresting or redundant rules. We conducted a set of experiments of mining our traffic accident data in both unsupervised mode and supervised mode for comparison of these rule based learning algorithms. Experiments with the traffic accident data reveals that the association rule learning, in its pure unsupervised mode, can discover some hidden relationship among the features. Under supervised learning setting with combinatorial target feature, however, the subgroup discovery method finds good rules much more easily than the association rule learning method that requires a lot of efforts to tune the parameters.

Measures of International Standardization in Korean Landscape Drawing Practice (한국 조경제도의 국제표준화 방안)

  • Kim, Min-Soo
    • Journal of the Korean Institute of Landscape Architecture
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    • v.37 no.4
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    • pp.52-63
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    • 2009
  • WTO/TBT aims to reduce impediments to trade resulting from differences between national regulations and standards. Where international standards exist or their completion is imminent, the Code of Good Practice says that standardizing bodies should use them, or the relevant parts of them, as a basis for any standards they develop. Drawing is a formal and precise way of communicating information about the shape, size and, features. In addition, drawing is a part of the universal language of engineering. However there are many differences between international landscape drawing standard ISO 11091 and Korean landscape drawing practice(KLDP). The result of a comparison of ISO 11091 with KLDP and suggestions for international standardization of KLDP are summarized as follows. First, Among the 33 kinds of conventions from ISO 11091, 2 similar kinds and 15 different kinds from KLDP and 16 kinds of conventions which exist only in ISO 11091 appeared-for the international standardization of KLDP, it is necessary to make an extensive alteration of KLDP. Second, Europe Unity countries accepted ISO 11091 and are using it as their national standard for landscape drawing. Even Japan has accepted ISO 11091 on their civil engineering drawings and is using it as their national standard. Therefore, we need to hasten KS standard enactment based on ISO 1091. Third, For the KS standard of construction drawings, the degree of international standardization is rising even though there are still differences from the ISO standard. Therefore, since the burden on the international standardization of KLDP is expected to be weighed, preparations should be quickly brought about in the practice fields. Fourth, Since in the landscape planting ordinances of local independent governments is the standard presented by categorizing trees into evergreen and deciduous, such parts should be modified and introduced when enacting the KS standard based on ISO 11091. Fifth, For the enactment of the KS standard for landscape drawings, a wide range of opinions should be collected by the relevant landscape organization by installing a committee, and based on its recommendation, an application for the KS standard enactment of landscape drawing should be made to the chief of Ministry of Knowledge Economy.

An Evaluation Model for Software Usability using Mental Model and Emotional factors (정신모형과 감성 요소를 이용한 소프트웨어 사용성 평가 모델 개발)

  • 김한샘;김효영;한혁수
    • Journal of KIISE:Software and Applications
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    • v.30 no.1_2
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    • pp.117-128
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    • 2003
  • Software usability is a characteristic of the software that is decided based on learnability, effectiveness, and satisfaction when it is evaluated. The usability is a main factor of the software quality. A software has to be continuously improved by taking guidelines that comes from the usability evaluation. Usability factors may vary among the different software products and even for the same factor, the users may have different opinions according to their experience and knowledge. Therefore, a usability evaluation process must be developed with the consideration of many factors like various applications and users. Existing systems such as satisfaction evaluation and performance evaluation only evaluate the result and do not perform cause analysis. And also unified evaluation items and contents do not reflect the characteristics of the products. To address these problems, this paper presents a evaluation model that is based on the mental model of user and the problems, this paper presents a evaluation model that is based on the mental model of user and the emotion of users. This model uses evaluation factors of the user task which are extracted by analyzing usage of the target product. In the mental model approach, the conceptual model of designer and the mental model of the user are compared and the differences are taken as a gap also reported as a part to be improved in the future. In the emotional factor approach, the emotional factors are extracted for the target products and evaluated in terms of the emotional factors. With this proposed method, we can evaluate the software products with customized attributes of the products and deduce the guidelines for the future improvements. We also takes the GUI framework as a sample case and extracts the directions for improvement. As this model analyzes tasks of users and uses evaluation factors for each task, it is capable of not only reflecting the characteristics of the product, but exactly identifying the items that should be modified and improved.

A Study on Reported Status and Management Plan of Marine Facilities in Korea 2. On the Basis of Region and Type of Facilities (국내 해양시설의 신고 현황과 관리 방안에 관한 연구 2. 지역별 및 시설종류별 현황을 중심으로)

  • Kim, Kwang-Soo
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.16 no.3
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    • pp.275-285
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    • 2010
  • Present state of nationwide marine facilities reported to 12 regional maritime affairs and port offices of MLTM in Korea for two years 2008 and 2009 was analyzed based on region and type of facilities, and national management plan was proposed in this study. As of the end of 2009, 8 types of marine facilities were reported to Yeosu regional maritime affairs and port office, while only 3 types of facilities were reported to Pohang, Daesan and Jeju regional offices, respectively. Oil and noxious liquid substances storage facilities belonged in the type of facility which was reported to all of 12 regional offices, and ranged from 11 facilities reported to Pyeongtaek regional office to the respective 38 facilities to Yeosu and Masan regional offices. In pollutants storage facilities, 4 facilities were reported to Masan regional office, 2 facilities to Donghae and Mokpo regional offices, respectively, 1 facility to Yeosu, Gunsan and Pyeongtaek regional offices, respectively, and none of facilities to the other regional offices. Ship construction, repair and scrap facilities belonged in the type of facility which was reported to all of 12 regional offices, and 45% of the facilities were concentrated in Southeastern Sea of Korea centering around Busan and Masan. In cargo handling facilities, 3 facilities were reported to Busan and Masan regional offices, respectively, 1 facility to Daesan regional office, and none of facilities to the other regional offices. In wastes storage facilities, 5 facilities were reported to Ulsan regional office, 4 facilities to Gunsan regional office, 2 facilities to Incheon regional office, 1 facility to Yeosu regional office, and none of facilities to the other regional offices. 65% of nationwide water intake and drainage facilities were concentrated in the areas of Pohang and Mokpo, and 78% of nationwide fishing spots at play were concentrated in the area of Masan. In other marine facilities, 4 facilities were reported to Donghae regional office, 3 facilities to Masan regional office, 2 facilities to Yeosu and Pyeongtaek regional offices, respectively, 1 facility to Incheon and Ulsan regional offices, respectively, and none of facilities to the other regional offices. In integrated marine science base facilities, 3 facilities were reported to Jeju regional office, 1 facility to Yeosu, Ulsan and Gunsan regional offices, respectively, and none of facilities to the other regional offices. The management based on the circumstances of regional offices, the management based on the characteristics of the type of facilities, the amendment of the relevant rules and regulations, facility owner's full knowledge and observance of the relevant rules and regulations with regard to the relevant type of facilities, and positive management actions from national point of view were proposed for national management plans of marine facilities.

Implementing a Cervical Cancer Awareness Program in Low-income Settings in Western China: a Community-based Locally Affordable Intervention for Risk Reduction

  • Simayi, Dilixia;Yang, Lan;Li, Feng;Wang, Ying-Hong;Amanguli, A.;Zhang, Wei;Mohemaiti, Meiliguli;Tao, Lin;Zhao, Jin;Jing, Ming-Xia;Wang, Wei;Saimaiti, Abudukeyoumu;Zou, Xiao-Guang;Maimaiti, Ayinuer;Ma, Zhi-Ping;Hao, Xiao-Ling;Duan, Fen;Jing, Fang;Bai, Hui-Li;Liu, Zhao;Zhang, Lei;Chen, Cheng;Cong, Li;Zhang, Xi;Zhang, Hong-Yan;Zhan, Jin-Qiong;Zhang, Wen Jie
    • Asian Pacific Journal of Cancer Prevention
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    • v.14 no.12
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    • pp.7459-7466
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    • 2013
  • Background: Some 60 years after introduction of the Papanicolaou smear worldwide, cervical cancer remains a burden in developing countries where >85% of world new cases and deaths occur, suggesting a failure to establish comprehensive cervical-cancer control programs. Effective interventions are available to control cervical cancer but are not all affordable in low-income settings. Disease awareness saves lives by risk-reduction as witnessed in reducing mortality of HIV/AIDS and smoking-related cancers. Subjects and Methods: We initiated a community-based awareness program on cervical cancer in two low-income Muslim Uyghur townships in Kashi (Kashgar) Prefecture, Xinjiang, China in 2008. The education involved more than 5,000 women from two rural townships and awareness was then evaluated in 2010 and 2011, respectively, using a questionnaire with 10 basic knowledge questions on cervical cancer. Demographic information was also collected and included in an EpiData database. A 10-point scoring system was used to score the awareness. Results: The effectiveness and feasibility of the program were evaluated among 4,475 women aged 19-70 years, of whom >92% lived on/below US$1.00/day. Women without prior education showed a poor average awareness rate of 6.4% (164/2,559). A onetime education intervention, however, sharply raised the awareness rate by 4-fold to 25.5% (493/1,916). Importantly, low income and illiteracy were two reliable factors affecting awareness before or after education intervention. Conclusions: Education intervention can significantly raise the awareness of cervical cancer in low-income women. Economic development and compulsory education are two important solutions in raising general disease awareness. We propose that implementing community-based awareness programs against cervical cancer is realistic, locally affordable and sustainable in low-income countries, which may save many lives over time and, importantly, will facilitate the integration of comprehensive programs when feasible. In this context, adopting this strategy may provide one good example of how to achieve "good health at low cost".

An Intelligent Intrusion Detection Model Based on Support Vector Machines and the Classification Threshold Optimization for Considering the Asymmetric Error Cost (비대칭 오류비용을 고려한 분류기준값 최적화와 SVM에 기반한 지능형 침입탐지모형)

  • Lee, Hyeon-Uk;Ahn, Hyun-Chul
    • Journal of Intelligence and Information Systems
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    • v.17 no.4
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    • pp.157-173
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    • 2011
  • As the Internet use explodes recently, the malicious attacks and hacking for a system connected to network occur frequently. This means the fatal damage can be caused by these intrusions in the government agency, public office, and company operating various systems. For such reasons, there are growing interests and demand about the intrusion detection systems (IDS)-the security systems for detecting, identifying and responding to unauthorized or abnormal activities appropriately. The intrusion detection models that have been applied in conventional IDS are generally designed by modeling the experts' implicit knowledge on the network intrusions or the hackers' abnormal behaviors. These kinds of intrusion detection models perform well under the normal situations. However, they show poor performance when they meet a new or unknown pattern of the network attacks. For this reason, several recent studies try to adopt various artificial intelligence techniques, which can proactively respond to the unknown threats. Especially, artificial neural networks (ANNs) have popularly been applied in the prior studies because of its superior prediction accuracy. However, ANNs have some intrinsic limitations such as the risk of overfitting, the requirement of the large sample size, and the lack of understanding the prediction process (i.e. black box theory). As a result, the most recent studies on IDS have started to adopt support vector machine (SVM), the classification technique that is more stable and powerful compared to ANNs. SVM is known as a relatively high predictive power and generalization capability. Under this background, this study proposes a novel intelligent intrusion detection model that uses SVM as the classification model in order to improve the predictive ability of IDS. Also, our model is designed to consider the asymmetric error cost by optimizing the classification threshold. Generally, there are two common forms of errors in intrusion detection. The first error type is the False-Positive Error (FPE). In the case of FPE, the wrong judgment on it may result in the unnecessary fixation. The second error type is the False-Negative Error (FNE) that mainly misjudges the malware of the program as normal. Compared to FPE, FNE is more fatal. Thus, when considering total cost of misclassification in IDS, it is more reasonable to assign heavier weights on FNE rather than FPE. Therefore, we designed our proposed intrusion detection model to optimize the classification threshold in order to minimize the total misclassification cost. In this case, conventional SVM cannot be applied because it is designed to generate discrete output (i.e. a class). To resolve this problem, we used the revised SVM technique proposed by Platt(2000), which is able to generate the probability estimate. To validate the practical applicability of our model, we applied it to the real-world dataset for network intrusion detection. The experimental dataset was collected from the IDS sensor of an official institution in Korea from January to June 2010. We collected 15,000 log data in total, and selected 1,000 samples from them by using random sampling method. In addition, the SVM model was compared with the logistic regression (LOGIT), decision trees (DT), and ANN to confirm the superiority of the proposed model. LOGIT and DT was experimented using PASW Statistics v18.0, and ANN was experimented using Neuroshell 4.0. For SVM, LIBSVM v2.90-a freeware for training SVM classifier-was used. Empirical results showed that our proposed model based on SVM outperformed all the other comparative models in detecting network intrusions from the accuracy perspective. They also showed that our model reduced the total misclassification cost compared to the ANN-based intrusion detection model. As a result, it is expected that the intrusion detection model proposed in this paper would not only enhance the performance of IDS, but also lead to better management of FNE.

Evaluation of Web Service Similarity Assessment Methods (웹서비스 유사성 평가 방법들의 실험적 평가)

  • Hwang, You-Sub
    • Journal of Intelligence and Information Systems
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    • v.15 no.4
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    • pp.1-22
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    • 2009
  • The World Wide Web is transitioning from being a mere collection of documents that contain useful information toward providing a collection of services that perform useful tasks. The emerging Web service technology has been envisioned as the next technological wave and is expected to play an important role in this recent transformation of the Web. By providing interoperable interface standards for application-to-application communication, Web services can be combined with component based software development to promote application interaction and integration both within and across enterprises. To make Web services for service-oriented computing operational, it is important that Web service repositories not only be well-structured but also provide efficient tools for developers to find reusable Web service components that meet their needs. As the potential of Web services for service-oriented computing is being widely recognized, the demand for effective Web service discovery mechanisms is concomitantly growing. A number of techniques for Web service discovery have been proposed, but the discovery challenge has not been satisfactorily addressed. Unfortunately, most existing solutions are either too rudimentary to be useful or too domain dependent to be generalizable. In this paper, we propose a Web service organizing framework that combines clustering techniques with string matching and leverages the semantics of the XML-based service specification in WSDL documents. We believe that this is one of the first attempts at applying data mining techniques in the Web service discovery domain. Our proposed approach has several appealing features : (1) It minimizes the requirement of prior knowledge from both service consumers and publishers; (2) It avoids exploiting domain dependent ontologies; and (3) It is able to visualize the semantic relationships among Web services. We have developed a prototype system based on the proposed framework using an unsupervised artificial neural network and empirically evaluated the proposed approach and tool using real Web service descriptions drawn from operational Web service registries. We report on some preliminary results demonstrating the efficacy of the proposed approach.

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A Study on Automatic Classification Model of Documents Based on Korean Standard Industrial Classification (한국표준산업분류를 기준으로 한 문서의 자동 분류 모델에 관한 연구)

  • Lee, Jae-Seong;Jun, Seung-Pyo;Yoo, Hyoung Sun
    • Journal of Intelligence and Information Systems
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    • v.24 no.3
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    • pp.221-241
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    • 2018
  • As we enter the knowledge society, the importance of information as a new form of capital is being emphasized. The importance of information classification is also increasing for efficient management of digital information produced exponentially. In this study, we tried to automatically classify and provide tailored information that can help companies decide to make technology commercialization. Therefore, we propose a method to classify information based on Korea Standard Industry Classification (KSIC), which indicates the business characteristics of enterprises. The classification of information or documents has been largely based on machine learning, but there is not enough training data categorized on the basis of KSIC. Therefore, this study applied the method of calculating similarity between documents. Specifically, a method and a model for presenting the most appropriate KSIC code are proposed by collecting explanatory texts of each code of KSIC and calculating the similarity with the classification object document using the vector space model. The IPC data were collected and classified by KSIC. And then verified the methodology by comparing it with the KSIC-IPC concordance table provided by the Korean Intellectual Property Office. As a result of the verification, the highest agreement was obtained when the LT method, which is a kind of TF-IDF calculation formula, was applied. At this time, the degree of match of the first rank matching KSIC was 53% and the cumulative match of the fifth ranking was 76%. Through this, it can be confirmed that KSIC classification of technology, industry, and market information that SMEs need more quantitatively and objectively is possible. In addition, it is considered that the methods and results provided in this study can be used as a basic data to help the qualitative judgment of experts in creating a linkage table between heterogeneous classification systems.

Analysis of Integrated Oceanic Current Maps in Science and Earth Science Textbooks of Secondary School Based on 2015 Revised Curriculum (2015 개정 교육과정 기반 중등학교 과학 및 지구과학 교과서의 통합 해류도 분석)

  • Park, Kyung-Ae;Lee, Jae Yon;Park, Jae-Jin;Lee, Eunil;Byun, Do-Seong;Kang, Boon-Soon;Jeong, Kwang-Yeong
    • Journal of the Korean earth science society
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    • v.41 no.3
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    • pp.248-260
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    • 2020
  • Oceanic current maps introduced in science and earth science textbooks can offer a valuable opportunity for students to learn about rapid climate change and the role of currents associated with the global energy balance problem. Previously developed oceanic current maps in middle and high school textbooks under the 2007 and 2009-revised national curriculum contained various errors in terms of scientific accuracy. To resolve these problems, marine experts have constructed a unified oceanographic map of the oceans surrounding the Korean Peninsula. Since 2010, this process has involved a continuous, long-term consultation procedure. By extensively gathering opinions and through verification process, a representative and scientific oceanic current map was eventually constructed. Based on this, the educational oceanic current maps, targeting the comprehension of middle and high school students, were developed. These maps were incorporated into middle and high school textbooks in accordance with the revised 2015 curriculum. In this study, we analyzed the oceanic current maps of five middle school science textbooks and six earth science textbooks that were published in high school in 2019. Although all the oceanic current maps in the textbooks were unified based on the proposed scientific oceanic current maps, there were problems such as the omission of certain oceanic currents or the use of a combination of dotted and solid lines. Moreover, several textbooks were found to be using incorrect names for oceanic currents. This study suggests that oceanic current maps, produced by integrating scientific knowledge, should be visually accurate and utilized appropriately to avoid students' misconception.