Earticle

[목적] 본 연구의 목적은 골프를 더 이상 사치성 스포츠로 보기 어렵고, 현재와 같이 회원제와 대중제 골프장의 이용 료의 차이는 물론 시설에도 큰 차이가 없는 상황에서 변화된 현실에 적합한 골프장 신 분류체계와 조세체계를 제시 하기 위함에 있다. [방법] 국내 골퍼들의 선호 골프장 유형 조사를 위해 전국의 20세 이상의 남녀 골퍼 1200명으로부 터 설문지를 표집하여, 이중 결측지 200부를 제외한 1000부를 유효 표본으로 사용하였으며, 자료의 처리는 SPSS 20 을 사용하여 T-test와 ANOVA 분석을 수행하였다. [결과] 국내 골퍼들의 골프장 선호 유형은 회원과 동반자만 입장 가능한 회원제가 27.5%, 회원과 비회원 모두 예약 및 입장 가능한 준회원제가 42.7%, 대중제가 0.9%, 저가형 공공골 프장이 28.9%로 확인되었다. 선호 유형을 감안하여 신 분류체계는 일반제와 공공제로 분류 하였으며, 신 분류체계를 감안하여 신 조세체계는 일반제는 현 대중제와 동일한 세율, 공공제는 대중제의 50% 이하의 세율을 적용해야 하는 것으로 확인되었다.[결론] 따라서 신 분류체계와 신 조세체계의 적용을 통해 다양한 계층의 골프장 공급을 유도하여 진정한 골프대중화 실현이 필요할 것으로 판단된다.

[Purpose] The main purpose of this study is to present a new golf course classification system and tax system suitable for the changed situation where golf is no longer seen as a luxury sport and there is no significant difference in fees between membership and public golf courses. [Method] It surveyed 1200 male and female amateur golfers in Korea over the age of 20 and 999 samples were used as valid samples after excepting for insincere and incomplete samples. SPSS 20.0 were used to derive results. [Result] The preferred types of golf courses for domestic golfers were 27.5% for membership courses, 42.7% for semi-membership courses for both members and non-members, 0.9% for public golf courses, and 28.9% for low-cost public golf courses. In consideration of the type of preference, the new classification system was classified into general and public systems, and in consideration of the new classification system, it was confirmed that the general system should apply the same tax rate as the current public system and public system should apply less than 50% of public system. [Conclusion] Therefore, it is necessary to realize real golf popularization by the application of the new classification system and the new tax system.

본 연구는 민속춤을 본래의 연행맥락에 위치ㆍ연결시킨 데이터베이스 체계 구축 을 위한 분류 체계도를 만들기 위해 마련되었다. 연구자는 1차로 민속춤을 무속춤, 농 악춤, 탈춤, 소리춤, 허튼춤 및 모방춤 총 5가지 종목으로 나누어 각각의 민속춤에 대 한 연행맥락을 연결하고자 했다. 민속춤들은 저마다 다른 성격을 가지고 연행되었기 때문에 연행맥락의 기반 또한 이에 맞게 설정해주어야 하는데, 무속춤은 연행성격ㆍ농악춤은 연행시기ㆍ탈춤은 연행주제ㆍ소리춤은 연행시기 및 연희자ㆍ허튼춤 및 모방춤 은 연행지역 및 연희자로 맥락의 출발 지점을 설정하였다. 2차로는 춤과 좀 더 직접적 인 세부 요소(춤 설명, 무구(舞具), 무복(舞服), 무악(舞樂))를 연결했다. 이로써 각각 의 민속춤이 본래 어떤 목적에서 연행하게 된 것인지 알 수 있고, 이후 하위맥락으로 연결된 춤 또한 예술적ㆍ기능적인 측면 중심보다는 본래의 연행 의도와 역할 및 의미 를 감지하면서 파악할 수 있게 되었다고 본다. 또한 같은 종목 간의 춤 비교를 쉽게 할 수 있어 민속춤의 지역적 특성도 이해하기 편리해졌다고 할 수 있다.

This study seeks to make a classification chart due to build a database in which folk dance is placed and connected in its original Performance context. Firstly, the researcher divided folk dance into five events, including shamanism, Nongak (Instrumental music of peasants), mask dance, Sori dance, Heoteun dance and cover dance, to connect their respective feast context to folk dance. Since each of folk dances was performed in different characters, it is important to set the basis of Performance context accordingly. So shamanistic dance was set for feast character, Nongak dance for its period of time, mask dance for its theme, Sori dance for Performance period of time and performer, and finally, Heoteun dance and cover dance for Performance region and performer, as to the starting point of context. Secondly, dance was connected to more immediate, detailed elements (dance description, dancing tools, dancing costume and dance music. This would tell you about by what design each of folk dances originally became Performance and then would allow grasping dances connected in lower context by appreciating the original intent, role and meaning of Performance, not simply by focusing on artistic and functional aspects. Besides, this attempt would make it convenient to understand the regional characteristics of folk dances by enabling to compare between the same events of dance easily.

Objectives : This study aims to present a new classification system using evaluation standards to ensure the safety of transport ventilators used in Korea. Due to the rapid advancement of technology, various types of ventilators have been developed and as the range of application increases, so does demand. With quick access to information and a growing economy, the technology used in Korean hospitals is equivalent to that of other countries; however, regulatory and safety consciousness are still lagging in Korea. Methods : Based on researching overseas cases, reference data and standards for improving the current system in Korea are proposed. Results : According to the review of transport ventilator use in Korea, it was found that concerns about safety is due to the absence of a standardized classification system for evaluating the safety and effectiveness of transport ventilators. Conclusions : In order to improve the safety of patients and the quality of medical care, it is essential to establish guidelines and assessment standards guaranteeing the safety of transport ventilators in Korea. Clear definitions and classifications for devices must precede the application of such standards. In addition, effective evaluation standards should be developed in order to resolve problems and improve upon the current system through continuous validation.

몽골전통음악은 19세기 후반부터 연구되었으며, 초기 몽골전통음악을 연구한 학자들은 모두 몽골인이 아닌 외국인이었다. 몽골에서는 1950년대에 비로소 몽골전통음악 관련 연구물이 등장하기 시작하였고, 몽골국내외 전반에서 몽골음악학의 본격적인 연구는 1980년대 이후이며 지금까지도 몽골전통음악의 분류체계를 논의한 몽골 국내외 학자는 없다. 분류는 하나의 대상을 체계적으로 이해하는데 중요한 지침이 된다. 본 연구는 몽골전통음악을 연구하는 과정에서 각 지역별 혹은 학자 간에 분류 체계의 이견(異見)이 관찰되어, 이를 통합하여 하나의 시안(試案)을 마련한 것이다. 몽골전통음악의 분류체계를 논의하기 위해 몽골학계뿐만 아니라 중국학계와 서양학계의 연구결과물을 검토하면서 몇 가지 문제점을 발견하였는데, 첫째, 외국학자들에 의해 선행된 연구가 많아 외국인에 의해 명명된 학술용어를 그대로 차용하고 있는 점, 둘째, 학술용어 중 지역방언 혹은 동의어를 혼용하고 있는 점, 셋째, 하위 갈래에 대한 조사연구가 미진(未盡)한 점, 넷째, 분류체계에 대한 일관성이 다소 결여되어 문학적 분류와 음악적 분류 등을 혼용하여 복합적 분류체계를 사용하고 있는 점 등이다. 몽골전통음악의 분류는 발성기법(發聲技法), 호출(呼出)소리, 설창음악(說唱音樂), 민요(民謠), 샤먼음악(巫樂), 불교음악(佛敎音樂) 등 7가지로 통합시안을 마련해 보았으나, 학문적 분야를 막론하고 분류체계는 시세를 반영하여 지속적인 수정안이 불가피할 것이다.

Mongolian Traditional music has been researched since the late 19th century. Researchers who studied it in the early stage of the research were all foreigners, not Mongolians. It’s not until the 1950s that the music was studied in earnest in Mongolia. Full-scale research efforts have been channeled into Mongolian musicology in and outside this country since the 1980s, and no researcher has ever tried to discuss the classification system of Mongolian traditional music. Classification is one of integral elements to have a perfect, systematic understanding of things. The purpose of this study was to draw up drafts of the classification system of Mongolian traditional music, as there were disparities among regional areas or scholars in that regard. To discuss the classification system of Mongolian traditional music, the research results of Mongolian scholars were reviewed, and the research results of Chinese and Western academic communities were reviewed as well. As a result, there were several problems. First, many early studies were conducted by foreign scholars, and the technical terms made by the foreigners were intactly used. Second, some of the technical terms were mixed with regional dialects or synonyms. Third, there weren’t sufficient research efforts for the small genres. Fourth, the classification systems weren’t coherent enough. Literary and musical classification systems were mixed together, which resulted in classification of complex genres. Seven integrative drafts for the classification of Mongolian traditional music were prepared in this study, which respectively dealt with vocalization methods, onomatopoeic sound, epic narrative music, folk songs, Shaman music, and Buddhist music. But the sustained modification of classification systems will be unavoidable in every academic field.

오늘날의 공공데이터는 일상생활의 편의증진, 새로운 비즈니즈 및 일자리 창출 등의 사회․경제적 가치와 부 가적 잠재력을 지닌 중요한 국가자산으로 인식되고 있어 해외 선진국들은 공공데이터를 적극 개방하고 민간 활용을 위한 다양한 정책들을 경쟁적으로 추진하고 있으며, 우리나라 정부도 창조경제를 지원하는 새로운 정부운영 패러다 임으로 정부3.0 정책을 추진하고 있으나, 개방된 공공데이터는 공급자 관점의 분류체계로 유형화되어 있어 수요자 관점의 접근이나 정보소재 파악이 어려워 민간 활용를 확대하기에는 한계가 있다. 본 연구에서는 기존 공공데이터 개방 서비스의 분류체계에 대해 조사․분석하여 미래창조과학부 산하기관이 보유하고 있는 공공데이터를 대상으로 민 간 활용 활성화를 위한 사용자 관점의 데이터 개념을 정의하고 새로운 분류체계를 설계하여 정보관리 관점에 따른 5 개 유형과 정보활용 관점에 따른 7개 분야, 21개 세부 분야의 분류체계를 도출하였다.

Today's public sector information is considered an important national asset that has social and economic value. Hence, developed countries are competitively promoting various policies to actively promote access to public sector information and the use of such information for private purposes. The Korean government is also boosting the Government 3.0 policy as a new governmental management paradigm that supports the creative economy. Despite these governmental efforts, since open public sector information is only classified from the supplier's perspective, it is difficult to have access to information for private application from the consumer's perspective and expand private applications because of the problems in identifying the information source. In this study, the concept of data from the user's perspective for the activation of private applications was defined by focusing on public sector information obtained by affiliated organizations of the Ministry of Science, ICT and Future Planning(MSIP). The new classification system was designed by analyzing the classification system of conventional open services of public sector information through investigation.

The purpose of this study is to derive and type utilization indexes by comparing public design indicators with preceding studies related to closed school facilities, and to derive preliminary classification systems through a correlation review between indicators. Pre-research was conducted in the scope of academic papers, academic journals, research reports, and special act for promoting the utilization of closed school assets. Public design indicators were set in the scope of domestic design guidelines, the Seoul city public design assessment system, the 'Good Building' designation system, and the UK Design Quality Index (DQI). and the design review of the British architects. First of all, the research method looked at laws, procedures and utilization of closed schools, and reviewed the preceding study and domestic and international public design indicators sequentially. Next, the association was reviewed through a comparison between the preceding study and the public design indicators, and a preliminary classification system for the use of closed schools was derived from this.

매년 반복적이고 대형화된 해양사고가 발생함에 따라 해양사고 예방 및 피해 최 소화를 위한 정책개선 및 연구가 진행되고 있다. 통상 사고예방을 위해 수립되는 정 책이나 사업, 각종 연구과정에서 해양경찰청 또는 중앙해양안전심판원에서 발간하는 통계자료나 사례집을 활용하고 있는데, 이는 사고관리를 위한 정보 활용에 극히 제 한적이다. 현행 통계제공 항목의 경우 사고 위험성에 대한 깊이 있는 분석에 제약이 있고, 항목 간 연계를 통해 새로운 패턴이나 경향을 발견하기 어렵다. 본 연구의 선 행연구에서는 해양사고 안전 관련 연구, 정책수립, 의사결정에 더욱 다양한 데이터를 활용할 수 있도록 하는 ‘해양안전 정보 분류체계’를 제시하였다. 후속 연구인 이번 연구에서는 해당 분류체계를 적용하여 기존 통계자료를 활용한 연구에서 발견할 수 없는 선박사고 ‘초동대응’ 관점의 실태를 파악해보고자 한다. 이를 위해 ‘해양안전 정 보 분류체계’를 적용하여 2015-2018년 중부해역에서 발생한 선박사고 보고서에서 초 동대응과 관련 있는 데이터를 수집했다. 분석은 신고접수, 상황전파, 현장출동(도착 시간) 등 초동대응과 관련한 부문, 사고 유형별 신고 비중과 전개양상, 이에 따른 인 명피해 연관성에 대해 실시하였으며, 관서별 분석자료 활용 방안을 제시하였다.

Policy improvement and research on maritime safety prevention and damage minimization are underway due to the annually increasing number of maritime accidents that are growing in scale. Generally, statistical data or casebooks from the Korea coast guard and the Korean Maritime Safety Tribunal are utilized for policy, business, or research processes involving accident prevention. These uses demonstrate the limitations of the data utilizing process for accident prevention. There are constraints in current statistical data articles for insightful analysis of accident dangerousness, and it is difficult to discover new trends through the correlation of each article. This study proposes a ‘maritime safety information classification system’, which enables a wider variety of data to be utilized for marine accident prevention related research, policy making, and decision making. The presented research will analyze the actual conditions of boating accidents from the perspective of initial reaction by applying the classification system. This cannot be found from existing statistical data. This is implemented with boating accident reports in the central sea from 2015-2018. The analysis includes the initial reaction related parts such as the accident report, propagation of the situation, dispatch (arrival time, etc.), report ratio and development by types accident types, and human life damage correlation due to it. It will then suggest an analyzed date utilization plan by government offices.

The aim of this study was to compare the carcinogen classification systems of developed countries or global organizations with domestic system under Industrial Safety and Health Act (ISHA). We selected the representative institutions which had carcinogen classification system such as International Agency for Research on Cancer (IARC), National Toxicological Program (NTP), Environmental Protection Agency (US-EPA), American Conference of Governmental Industrial Hygienists (ACGIH), and European Union (EU). We collected the carcinogen lists issued by 5 institutions, and merged by CAS number of each chemical with Microsoft Access 7.0. We found that confirmed human carcinogens, probable human carcinogens and possible human carcinogens were 34, 179, and 252, respectively. All of the institutions classified chemicals as 2 (NTP), 3 (EU) or 5 (IARC, ACGIH, US-EPA) categories based on the weight of scientific evidences for carcinogenicity and periodically updated the carcinogen list by regular procedure. However, a total of 90 chemicals could be classified as carcinogen under ISHA in Korea. There was no procedure or system which periodically update the carcinogen lists. In addition, the status of carcinogen classification according to regulation was confused. In conclusion, these findings suggest that the carcinogen classification and management system should be amended by consideration of systems of advanced institutions and the domestic regulation system.

본 논문은 O2O쇼핑몰 플랫폼에 있는 상품 검색을 위해 딥 러닝 기반의 이미지 검색 시스템을 이용한 서비스디자인을 제안한다. 인터넷 쇼핑몰에서 판매되는 수많은 제품에 대해서 검색 이미지를 사용하여 보다 편리한 검색 서비스가 가능한 딥 러닝(Deep Learning) 기술을 구현하였다. 본 검색 시스템 구현을 위해 현재 운영 중인 쇼핑몰 업체에서 사용하고 있는 실제 데이터를 실험데이터로 사용하였다. 그러나 본 시스템에서 여러 차례의 검색 실험을 통해서 데이터 성분으로 인한 검색 성능 저하 요인을 확인하였다. 그래서 검색 성능 향상을 위해서 검색에 방해가 되는 학습 데이터를 여러 차례 수정 정리한 후에 검증 데이터를 통해서 실험 결과 값을 수치화 하였다. 이와 같은 실험 결과의 수치 값을 활용하여 본 시스템에서 구현한 서비스디자인 설계에 반영하였다.

This paper proposes a new service design which is deep learning-based image retrieval system for product search on O2O shopping mall platform. We have implemented deep learning technology that provides more convenient retrieval service for diverse images of many products that are sold in the internet shopping malls. In order to implement this retrieval system, real data used by shopping mall companies were used as experimental data. However, result from several experiments have confirmed deterioration of retrieval performance due to data components. In order to improve the performance, the learning data that interferes with the retrieval is revised several times, and then the values of experimental result are quantified with the verification data. Using the numerical values of these experiments, we have applied them to the new service design in this system.

Quality cost is used as a main rating indicator which measures evaluates validity and efficiency of quality system. Quality cost even takes up over 10~20% of overall construction cost, which shows the impact and significance on business and competitiveness of the industry. These days, among domestic construction industry, centering around major companies, the implement of quality cost system is promoting as a solution for evaluating validity and efficiency of quality system. This study structured presented quality cost item's classification system reflecting characteristics of construction works to utilize as the standard of measure evaluate quality cost for solving these problems. Evaluations were performed focusing the users, after measuring and analyzing construction works' quality cost to verify validity and efficiency of classification system of construction works' quality cost item. As the result show, measuring and analyzing quality cost, applying to established quality management system, were concluded to be easy, based on the fact of having excellent capability among all the value factors, particularly the compatability with quality management system was excelling.

Objective To evaluate the utility of using the Personal Assistance Services classification system (PAS-CS) that examines individuals with disabilities for services and government funding. To this end, this study also tests for significant differences in PAS-CS scores across disability grades and disability types.Methods A retrospective analysis was conducted using the 2014 National Survey on People with Disabilities (NSPD) data set. We selected patients with three types of disabilities (physical disabilities, brain lesions, and visual impairments). We compared the average PAS-CS scores of patients with different disability types and grades using general linear models with multiple comparisons. Results A total of 4,810 patients were included in the analysis. Patients with brain lesions had the highest average PAS-CS scores in activities of daily living (ADL) and instrumental activities of daily living (IADL) domains. Patients with visual impairments had the highest average scores in ‘Disease-specific disability’ and ‘Social-environment’ domains. For patients with physical disabilities and visual impairments, no PAS-CS domains were significantly different between patients with disability grade III and those with disability grade IV (p>0.05).Conclusion The PAS-CS scores of disability grades were not equivalent among individuals with different disability types. The Korean Ministry of Health and Welfare currently only considers certain disability grades for PAS pre-eligibility, as a result disregarding the characteristics of different disability types. Thus, the current PAS-CS requires modifications.

Purpose: The purpose of this study was to evaluate the clinical usefulness of the Critical Patient Severity Classification System (CPSCS) and Glasgow Coma Scale (GCS) for critically ill neurological patients and to determine the applicability of CPSCS and GCS in predicting their mortality. Methods: Data were collected from the medical records of 187 neurological patients who were admitted to the intensive care unit of C university hospital. The datawere analyzed through chi-square test, t test,Mann-Whitney, Kruskal-Wallis, goodness-of-fit test, and receiver operating characteristic curve. Results: In accordance with patients’ general and clinical characteristics, patient mortality turned out to be significantly different depending on intensive care unit stay, endotracheal intubation, central venous catheter, and severity by CPSCS. Hosmer-Lemeshow goodness-of-fit tests were applied to CPSCS and GCS. The results of the discrimination test using the receiver operating characteristic curve were CPSCS0, .743, GCS0 .583, CPSCS24, .734, GCS24 .612, CPSCS48, .591, GCS48 .646, CPSCS72, .622, and GCS72 .623. Logistic regression analysis showed that each point on the CPSCS score signifies a 1.034 higher likelihood of dying. Conclusion: Applied to neurologically ill patients, early CPSCS scores can be regarded as a useful tool.

정부는 연구시설장비가 과학기술의 발전을 견인하는 매우 중요한 도구이자, 수단으로 여겨지면서 국 가적으로 R&D와 연구시설장비에 대한 예산 투자를 지속적으로 확대하였다. 또한, 기 구축된 국가연구 시설장비의 효율적 운영 및 체계적 관리의 필요성이 점차 대두되면서 2010년 12월, 국가연구시설장비 표준분류체계를 개발하였다. 그러나 연구현장에서는 국가연구시설장비의 NTIS(National Science and Technology Service) 정보수집 초기단계로 누적정보 부족에 따른 표준분류체계의 과학적 검증절차 부 재와 동일계층 간 분류기준의 비일관성 문제가 여전히 한계로 제기되고 있다. 따라서 본 연구는 지난 2010년, 2015년 각 제/개정된 국가연구시설장비 표준분류체계(대분류 8개, 중 분류 25개, 소분류 410개)의 분류 정확도를 측정하고자 선형판별분석(LDA)과 분산분석(ANOVA) 기법 을 적용하여 2단계로 분석하였다. 또한, 본 연구 분석을 위해 지난 10년 동안 NTIS에 누적 등록된 정 보데이터(Big-Data) 50,271건을 수집하여 이를 활용하였다. 이는 단순히 국내외 유사 분류체계와 전문 가 의견을 토대로 만들어진 現 국가연구시설 표준분류체계를 과학적으로 실증 검증한 첫 연구 사례에 해당된다. 본 연구 결과, 대분류 이하 중분류와 소분류로 분류된 개체 수의 집단별 판별정확도는 92.2% 로 매 우 높은 수준이었고, 분산분석을 통한 사후검증에서는 대분류 8개 중 2개 집단의 변별력이 다소 낮게 나타나, 現 표준분류체계 중 일부 개선이 필요한 것으로 조사되었다. 본 연구를 통해 現 국가연구시설 장비 표준분류체계가 향후 지속적으로 개선되길 바란다.

Recently, research F&E(Facilities and Equipment) have become very important as tools and means to lead the development of science and technology. The government has been continuously expanding investment budgets for R&D and research F&E, and the need for efficient operation and systematic management of research F&E built up nationwide has increased. In December 2010, The government developed and completed a standardized classification system for national research F&E. However, accuracy and trust of information classification are suspected because information is collected by a method in which a user(researcher) directly selects and registers a classification code in NTIS. Therefore, in the study, we analyzed linearly using linear discriminant analysis(LDA) and analysis of variance(ANOVA), to measure the classification accuracy for the standardized classification system(8 major-classes, 54 sub-classes, 410 small-classes) of the national research facilities and equipment established in 2010, and revised in 2015. For the analysis, we collected and used the information data(50,271 cases) cumulatively registered in NTIS(National Science and Technology Service) for the past 10 years. This is the first case of scientifically verifying the standardized classification system of the national research facilities and equipment, which is based on information of similar classification systems and a few expert reviews in the in-outside of the country. As a result of this study, the discriminant accuracy of major-classes organized hierarchically by sub-classes and small-classes was 92.2 %, which was very high. However, in post hoc verification through analysis of variance, the discrimination power of two classes out of eight major-classes was rather low. It is expected that the standardized classification system of the national research facilities and equipment will be improved through this study.

Maize is known as one of the healthiest diets in the world, but its productivity is critically harmed by various diseases, with blight, common rust, and gray leaf spot being the most common. Early and accurate detection of these diseases is challenging. We have developed a CNN-based Sequential Model for disease classification, which aids farmers in applying appropriate treatments. Although maize is a vital global staple, its productivity is often threatened by viral leaf diseases, leading to substantial yield losses. Timely and accurate detection of these diseases is essential for effective crop management. This study introduces a deep neural network (DNN) designed to identify maize leaf diseases—specifically Blight, Gray Leaf Spot, and Common Rust—by extracting complex image features. An attention mechanism helps the model focus on critical image areas, enhancing interpretability and robustness. Validation experiments demonstrate the model's efficiency, confirming its potential as a reliable tool for precision agriculture.

Fuel structure is one of the major determinants in predicting the forest fire danger rating because it is a major factor in forest fire intensity and behavior. This study was conducted to the establishment of a fuel classification system by researching the fuel characteristics in a total of 12 study sites in Gangwon province, South Korea. There were two study sites in Yeongseo, and 10 study sites were in Yeongdong. We researched the fuel amount (kg/m2) separately in the study site by fuel structure in the forest. The fuel structure was divided into three types: surface layer (Duff, Litter, Twigs), shrub layer (the height of less than 2m), and crown layer (the height of 2m or more). As a result of this study, the fuel classification of 12 study sites was divided into three class by the K-means algorithm (Class Ⅰ: Chuncheon 1, Chuncheon 2, and Dogye-eup 1; Class Ⅱ: Jeo-dong 1, Jeo-dong 2, Yucheon-dong 1, Yucheon-dong 4, and Yucheon-dong 5; Class Ⅲ: Yucheon-dong 2, and Yucheon-dong 3).

본 연구는 화학사고를 예방하고 피해 저감 방안 마련을 위해 화학사고 분류체계를 과학적이고 활용도 높게 개선하고자 한다. 이를 위해 국내·외에서 발생한 재난 등 각종 안전사고의 분류현황을 조사하고 화학사고와 관련한 분류 항목과 방법을 적용했다. 또한, 국내에서 발생한 화학사고 사례를 바탕으로 재분석하여 분류체계의 활용성을 검증했다. 개선된 분류체계는 현재의 단편적인 분류체계에서 벗어나 한가지 화학사고를 다각도로 분류하고 심층적으로 분석하기 위해 형태, 원인, 장소, 피해, 시간, 화학물질, 사고설비, 작업내용, 위반사항에 대한 9가지 항목으로 구분했다. 또한, 9개의 대분류 항목을 64개의 중분류로 구분하고, 중분류를 60개의 소분류로 분류하여 세부원인 파악이 가능하도록 구성했다. 본 연구의 결과물을 통해 구체적인 화학사고 통계데이터를 구축할 수 있으며, 이는 화학물질 취급시설과 취급관리 강화 등과 같은 제도개선 및 화학사고 예방대책 수립을 위한 중요한 기초자료가 될 것이다.

This study has established a highly practical classification system to develop measures for reducing chemical accidents. Taxonomy for chemical accident was improved by investigating accident classification statuses domestically and internationally. And analyzed cases of chemical accidents that occurred domestically for validation. To analyze a single incident from multiple perspectives, it was categorized into 9 major classifications: type, cause, place, damage, date, substance, accident facility, work detail, and violations. The 9 items were classified into 64 categories, which were further subdivided into 60 sub-classifications to enable detailed identification of causes. This study is expected to provide important foundations for institutional improvements such as strengthening regulations on chemical handling facilities and management, as well as formulating preventice measures for chemical accidents.

This study was executed as correlation study to investigate the correla-tion between the dimensions of diaphragm movement, and respiratory functions and pressures in accordance with the Gross Motor Function Classification System (GMFCS) levels on children with cerebral palsy as the participants. Forty-three children in the age range of 5–13 years di-agnosed with cerebral palsy as the research participants were divided into three groups (levels I, II, and III) through systematic stratified ran-dom sampling in accordance with their GMFCS levels. Pearson correla-tion analysis was executed to examine the correlation between dimen-sions of diaphragm movement, and respiratory functions and pressures in accordance with the GMFCS levels of the participants. There was no significant correlation between the dimensions of diaphragm move-ment, and respiratory functions and pressures in all of the three groups in accordance with the GMFCS levels of the participants. Therefore, it is deemed that although measurement of the dimensions of diaphragm movement of children with cerebral palsy by using diagnostic ultrason-ic M-mode imaging device can be considered as auxiliary tool in pre-dicting the breathing capabilities, it cannot be used as independent measurement equipment.

Various algorithms and system development are being required to support the advanced decision making of navigation information support system because of a serious loss of lives and property accidents by officer's error like as carelessness and decision faults. Much of researchers have introduced the techniques about the systems, but they hardly consider environmental factors. In this paper, We collect the context information in order to assess the risk, which is considered the various factor of the sailing ship, then extract the features of knowledge context, which is to apply the weight of correlation coefficients among data in context information. We decide the risk after the extract features through the classification and prediction of context information, and compare the value accuracy of proposed method in order to compare efficiency of the weighted value with the non-weighted value. As a result of experience, we know that the method of weight properties effectively reflect the marine environment because the weight accurate better than the non-weighted.

An automatic speech recognition system is one of the popular research problems. There are many research groups working in this field for different language including Japanese. Japanese vowel recognition is one of important parts in the Japanese speech recognition system. The vowel classification system with the Mamdani fuzzy inference system was developed in this research. We tested our system on the blind test data set collected from one male native Japanese speaker and four male non-native Japanese speakers. All subjects in the blind test data set were not the same subjects in the training data set. We found out that the classification rate from the training data set is 95.0 %. In the speaker-independent experiments, the classification rate from the native speaker is around 70.0 %, whereas that from the non-native speakers is around 80.5 %.