• 대한임상독성학회지
• /
• 제19권1호
• /
• pp.24-30
• /
• 2021

Purpose: In Korea, it is predicted that the proportion of drug abusers among patients visiting the emergency room will soon increase. Several emergency medical institutions in Korea are conducting field urine screening tests for poisoning. In this study, we investigated the characteristics and usefulness of urine toxicology screening tests. Methods: The medical records of patients with positive results for tetrahydrocannabinol and methamphetamine from urine toxicology screening tests at a tertiary university hospital from August 2016 to August 2019 were reviewed retrospectively. The subjects were classified into positive and false-positive groups, and their clinical characteristics were compared and analyzed. Results: Of the 2,026 patients surveyed, 823 patients (40.6%) tested positive for one or more drugs. Among them, 12 cases (0.6%) were positive for methamphetamine and 40 cases (2.0%) were positive for tetrahydrocannabinol. The positive and the false-positive rates for methamphetamine were 66.7% and 33.3%, respectively. The positive and the false-positive rates for tetrahydrocannabinol were 2.5% and 97.5%, respectively. Conclusion: Methamphetamine showed a relatively low false-positive rate in our study. Therefore, this test seemed to assist in diagnosing methamphetamine poisoning when considered together with the present illness and physical examination results. On the other hand, the high false-positive rate for tetrahydrocannabinol tests indicates that this test was unlikely to assist in diagnosing tetrahydrocannabinol poisoning. However, considering the growing trend of illegal drug abusers in Korea, it may still be useful as a diagnostic tool for identifying drug users.

• Safety and Health at Work
• /
• 제12권1호
• /
• pp.74-95
• /
• 2021

Background: A job-exposure matrix (JEM) is an important surrogate indicator to evaluate past exposure levels. Although a Korean asbestos JEM has been constructed previously, this JEM includes only a few industrial and occupational groups. This study aimed to reconstruct the JEM by integrating the latest organized data to improve its utility. Methods: We used recent Korean standard industry and occupation codes and extracted 36 articles from a systematic literature review to initiate the reconstruction of the previous Korean asbestos JEM. The resulting data consisted of 141 combinations of industrial and occupational groups. Data from the Netherlands's JEM were also reviewed and categorized into 70 industrial and 117 occupational groups by matching with the Korean data. We also utilized Germany's data, which consisted of 10 industrial and 14 occupational groups. Results: The reconstructed Korean asbestos JEM had 141 combinations of industries and occupations. The time periods are from the 1980s to the 2000s in 10-year intervals. Most of the data were distributed between the 1990s and the 2000s. Occupations with high exposure to asbestos included knitting and weaving machine operators, automobile mechanics or assemblers, ship mechanics or assemblers, mineral ore and stone products processing mechanics, and metal casting machine operators or mold makers. Conclusions: The reconstructed Korean asbestos JEM has expanded the type and duration of the occupational groups of the previous JEM and can serve as an important reference tool for evaluating asbestos exposure and designing compensation and prevention policies in Korea.

• 한국융합학회논문지
• /
• 제12권3호
• /
• pp.35-41
• /
• 2021

본 연구는 진동을 융합한 소도구운동이 초등학교 야구선수들의 타격속도와 타격정확도에 미치는 영향을 알아보는데 목적이 있다. 주 3회 6주간 실시하였다. 실험군과 대조군 각각 20명씩으로 나누었다. 실험군은 진동을 융합한 소도구운동을 시행하였으며, 대조군은 일반적 운동을 시행하였다. 타격속도와 타격정확도를 측정하였다. 진동운동 실험군과 대조군 모두 중재 전과 후 타격속도와 타격정확도에서 군내 유의한 차이가 나타났다. 실험군과 대조군의 중재 후 군간 비교에서 타격정확도에서 유의한 차이가 나타났다. 진동을 융합한 소도구운동이 초등학교 야구선수들의 타격속도와 타격정확도를 증진시키는데 효과적인 방법이라고 사료된다. 향후 연구에서는 연령별과 스포츠 관련 질환을 가진 대상자에 대한 후속연구가 필요하다.

• 한국콘텐츠학회논문지
• /
• 제21권2호
• /
• pp.100-112
• /
• 2021

최근 빅데이터 기술시장의 성장과 함께 시각화 기술에 관한 관심은 지난 몇 년간 꾸준히 증가해왔다. 데이터 시각화는 현재 정보과학, 컴퓨터과학, 인간·컴퓨터 상호작용, 통계, 데이터마이닝, 지도학, 저널리즘 등의 광범위한 학문 분야에서 각기 조금씩 다른 의미로 사용되고 있다. 다학제적 연구가 필요한 스마트시티에서의 빅데이터 시각화는 사용자 중심의 스마트시티 서비스와 관련 정책을 전개하는데 있어 객관적이고 과학적인 접근을 가능하게 한다. 특히 공간 기반의 데이터 시각화는 도시정책 수립 과정에서 시각화 자료를 통해 다양한 이해관계자들의 효율적인 협업을 가능하게 한다. 본 논문은 선행연구를 통해 단순히 시각화 도구가 아닌 효과적인 정보전달 관점에서 공간기반의 빅데이터 시각화 표현 프로세스와 원리에 대해 고찰하였다. 데이터 시각화 모델 프로세스 및 시각화목적에 따른 시각화 표현기법, 디자인조형요소에 따른 특징과 시각화기법을 각각 도출하여 사용자 중심의 공간빅데이터 시각화 표현에 대한 방향성과 시사점을 제시하였다.

• 시스템엔지니어링학술지
• /
• 제16권2호
• /
• pp.97-109
• /
• 2020

On March 11, 2011, an earthquake followed by a tsunami caused an extended station blackout (SBO) at the Fukushima Dai-ichi NPP Units. The accident was initiated by a total loss of both onsite and offsite electrical power resulting in the loss of the ultimate heat sink for several days, and a consequent core melt in some units where proper mitigation strategies could not be implemented in a timely fashion. To enhance the plant's coping capability, the Diverse and Flexible Strategies (FLEX) were proposed to append the Emergency Operation Procedures (EOPs) by relying on portable equipment as an additional line of defense. To assess the success window of FLEX strategies, all sources of uncertainties need to be considered, using a physics-based model or system code. This necessitates conducting a large number of simulations to reflect all potential variations in initial, boundary, and design conditions as well as thermophysical properties, empirical models, and scenario uncertainties. Alternatively, data-driven models may provide a fast tool to predict the success window of FLEX strategies given the underlying uncertainties. This paper explores the applicability of Artificial Intelligence (AI) to identify the success window of FLEX strategy for extended SBO. The developed model can be trained and validated using data produced by the lumped parameter thermal-hydraulic code, MARS-KS, as best estimate system code loosely coupled with Dakota for uncertainty quantification. A Systems Engineering (SE) approach is used to plan and manage the process of using AI to predict the success window of FLEX strategies under extended SBO conditions.

• 대기
• /
• 제31권5호
• /
• pp.473-488
• /
• 2021

A new physical/statistical diagnostic downscale model has been developed for use to improve near-surface air temperature forecasts. The model includes a series of physical and statistical correction methods that account for un-resolved topographic and land-use effects as well as statistical bias errors in a low-resolution atmospheric model. Operational temperature forecasts of the Local Data Assimilation and Prediction System (LDAPS) were downscaled at 100 m resolution for three months, which were used to validate the model's physical and statistical correction methods and to compare its performance with the forecasts of the Korea Meteorological Administration Post-processing (KMAP) system. The validation results showed positive impacts of the un-resolved topographic and urban effects (topographic height correction, valley cold air pool effect, mountain internal boundary layer formation effect, urban land-use effect) in complex terrain areas. In addition, the statistical bias correction of the LDAPS model were efficient in reducing forecast errors of the near-surface temperatures. The new high-resolution downscale model showed better agreement against Korean 584 meteorological monitoring stations than the KMAP, supporting the importance of the new physical and statistical correction methods. The new physical/statistical diagnostic downscale model can be a useful tool in improving near-surface temperature forecasts and diagnostics over complex terrain areas.

• Journal of Animal Science and Technology
• /
• 제64권4호
• /
• pp.727-739
• /
• 2022

Mycotoxin contamination in pig feeds has a negative impact on growth performance, the immune system, and major body organs. Arginine (Arg) plays an important role in animals' body biochemistry and physiology. This study aimed to determine the effect of dietary Arg supplementation on mitigating the negative effects of mycotoxins in growing pigs. A total of 72 growing pigs (Landrace × Large white) with initial mean body weight (BW) = 55 ± 2.5 kg were allotted to four treatment groups with three replicates per group of six pigs per replicate in a completely randomized design. The treatments included a non-toxin diet with 1.2% Arg (NT1.2) and mycotoxin-challenged treatments supplemented with 1.2% Arg (TX1.2), 1.3% Arg (TX1.3), and 1.4% Arg (TX1.4). Statistical analysis of data included the effects of dietary level of Arg. The results indicated a significantly higher BW (p < 0.05), average daily gain (p < 0.05), and gain-to-feed ratio (p < 0.05) in the NT1.2 group than in the TX1.2, TX1.3, and TX1.4 groups. The relative weight of the liver was higher (p < 0.05) in the TX1.2 compared to that of the NT1.2 group, although it was not different from that of TX1.3 and TX1.4. The level of tumor necrosis factor-alpha was significantly up-regulated (p < 0.05) in the liver tissue of the TX1.2 group compared to that of the other treatments. Overall, dietary Arg supplementation remedied liver injury and alleviated the compromised immune system caused by mycotoxin toxicity.

• 시스템엔지니어링학술지
• /
• 제18권2호
• /
• pp.94-107
• /
• 2022

Accidents prevention and mitigation is the highest priority of nuclear power plant (NPP) operation, particularly in the aftermath of the Fukushima Daiichi accident, which has reignited public anxieties and skepticism regarding nuclear energy usage. To deal with accident scenarios more effectively, operators must have ample and precise information about key safety parameters as well as their future trajectories. This work investigates the potential of machine learning in forecasting NPP response in real-time to provide an additional validation method and help reduce human error, especially in accident situations where operators are under a lot of stress. First, a base-case SGTR simulation is carried out by the best-estimate code RELAP5/MOD3.4 to confirm the validity of the model against results reported in the APR1400 Design Control Document (DCD). Then, uncertainty quantification is performed by coupling RELAP5/MOD3.4 and the statistical tool DAKOTA to generate a large enough dataset for the construction and training of neural-based machine learning (ML) models, namely LSTM, GRU, and hybrid CNN-LSTM. Finally, the accuracy and reliability of these models in forecasting system response are tested by their performance on fresh data. To facilitate and oversee the process of developing the ML models, a Systems Engineering (SE) methodology is used to ensure that the work is consistently in line with the originating mission statement and that the findings obtained at each subsequent phase are valid.

• Journal of Korea Trade
• /
• 제25권6호
• /
• pp.105-125
• /
• 2021

Purpose - This study analyzes the effects that the response to the technical barriers to trade (TBT), which are used by various countries as means to restrict imports, exerts on exports at a time when protectionism is emerging in the face of a global economic downturn. TBT has been widely used in developed countries for the safety and protection of their people. Recently, the use of TBT as a tool of protectionism has increased considerably in developing countries as well. Therefore, this study analyzes the South Korean SMEs' response and export performance. Design/methodology - To analyze SMEs' response to TBT and their export performance, this study conducted empirical analysis through statistical analysis. To this end, the research established a theory based on previous research and designed its hypothesis and research model. To verify the hypothesis and research model, factor analysis addressing validity and reliability was performed using SPSS 25 and AMOS 26, and the structural equation model was analyzed. Findings - This study found the causal relationship between the independent variable, the mediating variable, and the dependent variable adopted against the theoretical background to have little or no effect, in contrast with previous studies. In a break from previous studies, all hypotheses were rejected for innovation strategic competencies, one of the sub-factors of the independent variable, which is believed to be a result of the lack of practical research related to TBT. Originality/value - Previous studies performed analysis using trade statistics or macro data. A number of such studies analyzed the relationship between technical regulation and trade volume. This study differs from previous studies in some respects, because it analyzed the export performance of companies by establishing a hypothesis and implementing a research model with the factors analyzed in previous studies. In addition, a new attempt has been made by classifying the TBT response factors into technology competencies, human resource competencies, and innovation strategic competencies, and utilizing technology innovation and the export support system as mediating effects.

• 대한한방부인과학회지
• /
• 제36권2호
• /
• pp.20-35
• /
• 2023

Objectives: The purpose of this study is to review clinical studies and investigate the efficacy and safety of oriental medicine on memory in menopausal women. Methods: 'menopause', 'memory', 'oriental medicine' were searched on 4 online databases (Cochrane Library, Pubmed, CNKI, OASIS). Randomized controlled trials (RCTs) that evaluated menopausal memory with oriental medicine treatment were included. The methodological quality of each RCT was assessed by using Cochrane risk of bias tool. Results: 8 RCTs were selected among 1067 articles. The overall risk of bias was evaluated as uncertain. 5 studies showed that oriental medicine alone was significant effective, but 1 long-term study with the same oriental medicine did not sustain the effect, and 2 studied were not statistically significant. Conclusions: Oriental medicine can be an effective option for improving memory in menopausal women. but considering the small number and quality of studies, inconsistent and insufficient evidence, further well-designed studies are needed to confirm the efficacy and safety of this treatment.