HNS사고는 대규모 화재와 폭발을 수반하며, 다수의 인명사고와 주변지역에 극심한 환경오염을 야기함으로 신속한 의사결정을 통하여 광범위한 확산을 막아야 한다. 본 연구는 국내 HNS사고사례를 해상이라는 특수성이 반영된 표준코드를 바탕으로 고품질, 표준화, 디지털화된 HNS사고 데이터베이스를 구축하여 사고발생 시 신속하고 합리적인 의사결정을 지원하고, 체계적인 통합관리 및 공유가 가능한 HNS사고이력관리시스템(HATS)을 설계하고 구현하였다. 또한 개발된 시스템을 활용하여 23년간 수집된 국내 HNS사고데이터 76건에 대해 각 항목별로 통계분석을 수행하여, 국내에서는 매년 평균 3.3건의 사고가 일어나며, 주요 HNS사고요인은 춘계기간 (41%), 계류장 (51 %), 케미컬운반선 (49 %), 승무원에 의한 과실 (45 %), 자일렌류 (12 %)인 것으로 확인되었다. (괄호안 : 사고분류기준별 해당 사고요인의 퍼센트 비율임)

인터넷과 스마트폰의 보급과 함께 사람들은 관심 있는 정보를 포털사이트에서 실시간으로 검색할 수 있게 되었다. 그에 따라 빅데이터가 비정형적으로 형성되고 이를 이용하기 위한 연구 분야가 발전하고 있다. 최근 식품분야 에서도 빅데이터를 활용한 연구의 필요성이 꾸준히 제기 되고 있다. 본 연구는 국내 최대 규모의 포털 사이트인 네이버의 검색 통계를 활용하여, 사람들의 연관 검색어 빈도에 따른 식품안전 사고 원인 식품과 식중독 원인 병원 체들의 관계를 분석하였다. 특히 식중독과 관련된 식품과 식중독 원인 병원체의 포털사이트 키워드 검색 건수와 해당 원인 식품 및 병원체의 뉴스검색 건수를 분석하였으며, 최종적으로 키워드 검색 건수와 실제 식중독 발생 시기의 상관관계를 분석하였다. 분석결과, 일반적으로 식중독 발생 직후 관련 키워드 검색 건수가 증가하는 것으로 나타 났으며, 특별하게 굴과 같은 계절성 식품의 경우 키워드 검색 건수 증가 이후에 식중독 사고가 발생한 것으로 나타났다. 따라서 본 연구결과를 통해 검색 건수가 증가하는 식중독 세균이나 식품들을 식중독 사전 예방적 차원의 정보로 활용할 수 있다면 식중독 사고 발생 가능성을 낮출 수 있을 것으로 사료된다.

PURPOSES:This study aims to analyze the impact of the implementation of a school zone traffic safety improvement project on the number of accidents involving children in these zones.METHODS :To analyze the correlation between school zone traffic safety features of roads in the zone and the number of accidents involving children, we developed an occurrence probability model of traffic accidents involving children by using a binary logistic regression model with SPSS 23.0 software. Two separate models were developed for two zones: interior block and arterial road.RESULTS:The model depicted that in the case of the interior block, shorter sidewalk width, speed bump, and an elevated crosswalk were key factors affecting the occurrence of accidents involving children. In the case of arterial roads exceeding a width of 12 m, the speed limit, roadside barriers, and red paving of road surfaces were found to be the key factors.CONCLUSIONS:The results of this study can serve as the elementary research data to help improve the effectiveness of school zone traffic safety improvement projects and school zone road repair projects in future.

The purpose of this study is to investigate in-depth high school students’ strategy use in reading English texts of College Scholastic Ability Test (KSAT). This study employed a think-aloud method to look into the reading process by task types and by reading proficiency. Six high school students, three high-level and three low-level readers, were asked to perform reading tasks of three types, ‘finding a theme’, ‘filling the gap’, ‘finding an irrelevant sentence & inserting a sentence’, thinking out loud after training. The results are as follows. First, the participants used varied types of reading strategies regardless of top-down/bottom-up. ‘Guessing from the context’ and ‘paraphrasing in L1’, were most frequently used, and ‘using schema’ and ‘sensing the logical organization’ were least used.’ Second, different strategy use patterns were shown by task types: Far more strategies were used in ‘finding a theme’ than the others, especially, attending to keyword. Third, the high-level readers employed more reading strategies than the low-level counterparts. Furthermore, the strategy use pattern was very different between groups: The low-level readers seldom used ‘checking discourse markers,’ ‘synthesizing information,’ and ‘questioning’ that the high level readers commonly used.

Many industrial accidents have occurred continuously in the manufacturing industries, construction industries, and service industries of Korea. Fatal accidents have occurred most frequently in the construction industries of Korea. Especially, the trend analysis of the accident rate and fatal accident rate is very important in order to prevent industrial accidents in the construction industries systematically. This paper considers forecasting of the accident rate and fatal accident rate with static and dynamic time series analysis methods in the construction industries. Therefore, this paper describes the optimal accident rate and fatal accident rate by minimization of the sum of square errors (SSE) among regression analysis method (RAM), exponential smoothing method (ESM), double exponential smoothing method (DESM), auto-regressive integrated moving average (ARIMA) model, proposed analytic function model (PAFM), and kalman filtering model (KFM) with existing accident data in construction industries. In this paper, microsoft foundation class (MFC) soft of Visual Studio 2008 was used to predict the accident rate and fatal accident rate. Zero Accident Program developed in this paper is defined as the predicted accident rate and fatal accident rate, the zero accident target time, and the zero accident time based on the achievement probability calculated rationally and practically. The minimum value for minimizing SSE in the construction industries was found in 0.1666 and 1.4579 in the accident rate and fatal accident rate, respectively. Accordingly, RAM and ARIMA model are ideally applied in the accident rate and fatal accident rate, respectively. Finally, the trend analysis of this paper provides decisive information in order to prevent industrial accidents in construction industries very systematically.