• Explosives and Blasting
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• v.40 no.3
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• pp.19-32
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• 2022

Hydrogen is a fuel having the highest energy compared with other common fuels. This means hydrogen is a clean energy source for the future. However, using hydrogen as a fuel has implication regarding carrier and storage issues, as hydrogen is highly inflammable and unstable gas susceptible to explosion. Explosions resulting from hydrogen-air mixtures have already been encountered and well documented in research experiments. However, there are still large gaps in this research field as the use of numerical tools and field experiments are required to fully understand the safety measures necessary to prevent hydrogen explosions. The purpose of this present study is to develop and simulate 3D numerical modelling of an existing hydrogen gas station in Jeonju by using handheld LiDAR and Ansys AUTODYN, as well as the processing of point cloud scans and use of cloud dataset to develop FEM 3D meshed model for the numerical simulation to predict peak-over pressures. The results show that the Lidar scanning technique combined with the ANSYS AUTODYN can help to determine the safety distance and as well as construct, simulate and predict the peak over-pressures for hydrogen refueling station explosions.

• The Journal of the Korea Contents Association
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• v.22 no.2
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• pp.782-793
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• 2022

The rise in chronic disease not only has a negative effect on people's lives, but it also increases the cost of medical care owing to the increased usage of medical care as health and medical technology improves, life expectancy rises, and rapid population ageing. In such context, this study examined the difference in the disease cost of hypertension according to demographic information and the effect of the initial diagnosis age and treatment period on the cost. This study used the Korean Health Panel Survey from 2010 to 2017, and selected subjects based on health insurance beneficiaries between the ages of 30 and under 80. With the selected data, the direct and indirect costs of disease loss were calculated according to the cost of illness approach, and we constructed a disease-loss ratio cohort considering the age of diagnosis and time of treatment for hypertension. From the results of the study, the annual cost of disease loss for hypertensive patients differed by gender by 110,107 won, and it was found that the cost increased by 1.8 times as the treatment time increased. In addition, when comparing disease loss ratios between the same age groups, it was found that the disease loss ratios between those in their 60s and 70s were affected by treatment time. This study confirmed that hypertension significantly affects the cost of the disease, and not only requires early diagnosis and management, but also preventive efforts to lower the incidence of hypertensive disease must be strengthened.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.3
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• pp.343-350
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• 2022

High-resolution data are needed to understand water body mixing patterns at river junctions. In particular, in river analysis, hydrological and water quality characteristics are used as basic data for aquatic ecological health, so observation through continuous monitoring is necessary. In addition, since measurement is carried out through a one-dimensional and fixed measurement method in existing monitoring systems, a hydrological and water quality characteristics investigation of an entire river, except for in the immediate vicinity of the measurement point, is not undertaken. In order to obtain high-resolution measurement data, a measurer has to consider multiple factors, and the area or time that can be measured is limited. Although the resolution might be lowered, an appropriate interpolation method must be selected in order to acquire a wide range of data. Therefore, in this study, a high-elevation measurement method at a river junction was introduced, and the interpolation method according to the measurement results was compared. The overall hydraulic and water quality information of the river was indicated through the visualization of the prediction and interpolation method in the low-resolution measurement result. By comparing each interpolation method, Inverse Distance Weighting, Natural Neighbor, and Kriging techniques were applied in river mapping to improve the precision of river mapping through visualized data and quantitative evaluation. It is thought that this study will offer a new method for measuring rivers through spatial interpolation.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.67 no.4
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• pp.274-284
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• 2022

To use kenaf (Hibiscus cannabinus L.) as a fiber and livestock feed, a high-yielding variety needs to be identified. For this, accurate phenotyping of plant height is required for this breeding purpose due to the strong relationship between plant height and yield. Plant height can be estimated using RGB images from unmanned aerial vehicles (UAV-RGB) and photogrammetry based on Structure from Motion (SfM) algorithms. In kenaf, accurate measurement of height is limited because kenaf stems have high flexibility and its height is easily affected by wind, growing up to 3 ~ 4 m. Therefore, we aimed to identify a method suitable for the accurate estimation of plant height of kenaf and investigate the feasibility of using the UAV-RGB-derived plant height map. Height estimation derived from UAV-RGB was improved using multi-point calibration against the five different wooden structures with known heights (30, 60, 90, 120, and 150 cm). Using the proposed method, we analyzed the variation in temporal height of 23 kenaf cultivars. Our results demontrated that the actual and estimated heights were reliably comparable with the coefficient of determination (R²) of 0.80 and a slope of 0.94. This method enabled the effective identification of cultivars with significantly different heights at each growth stages.

• Journal of the Korea Society for Simulation
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• v.18 no.3
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• pp.103-112
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• 2009

In a nuclear power plant (NPP), periodic sensor calibrations are required to assure sensors are operating correctly. However, only a few faulty sensors are found to be calibrated. For the safe operation of an NPP and the reduction of unnecessary calibration, on-line calibration monitoring is needed. In this paper, principal component-based Auto-Associative support vector regression (PCSVR) was proposed for the sensor signal validation of the NPP. It utilizes the attractive merits of principal component analysis (PCA) for extracting predominant feature vectors and AASVR because it easily represents complicated processes that are difficult to model with analytical and mechanistic models. With the use of real plant startup data from the Kori Nuclear Power Plant Unit 3, SVR hyperparameters were optimized by the response surface methodology (RSM). Moreover the statistical techniques are integrated with PCSVR for the failure detection. The residuals between the estimated signals and the measured signals are tested by the Shewhart Control Chart, Exponentially Weighted Moving Average (EWMA), Cumulative Sum (CUSUM) and generalized likelihood ratio test (GLRT) to detect whether the sensors are failed or not. This study shows the GLRT can be a candidate for the detection of sensor drift.

• Journal of Life Science
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• v.33 no.8
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• pp.663-679
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• 2023

This review analyzes research trends related to new drug development using artificial intelligence from 2010 to 2022. This analysis organized the abstracts of 2,421 studies into a corpus, and words with high frequency and high connection centrality were extracted through preprocessing. The analysis revealed a similar word frequency trend between 2010 and 2019 to that between 2020 and 2022. In terms of the research method, many studies using machine learning were conducted from 2010 to 2020, and since 2021, research using deep learning has been increasing. Through these studies, we investigated the trends in research on artificial intelligence utilization by field and the strengths, problems, and challenges of related research. We found that since 2021, the application of artificial intelligence has been expanding, such as research using artificial intelligence for drug rearrangement, using computers to develop anticancer drugs, and applying artificial intelligence to clinical trials. This article briefly presents the prospects of new drug development research using artificial intelligence. If the reliability and safety of bio and medical data are ensured, and the development of the above artificial intelligence technology continues, it is judged that the direction of new drug development using artificial intelligence will proceed to personalized medicine and precision medicine, so we encourage efforts in that field.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.2
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• pp.281-290
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• 2022

In Korea, the number of national facilities for which a safety inspection is mandatory is increasing, and a safer safety inspection method is needed. This study aimed to increase the efficiency of the bridge safety inspection by enabling rapid exterior inspection while securing the safety of inspectors by using drones to perform the safety inspections of bridges, which had mainly relied on visual inspections. For the research, the Youngjong Grand Bridge in Incheon was selected as a test bed and was divided into four parts: the warren truss, suspension bridge main cable, main tower, and pier. It was possible to establish a five-step standard procedure for drone safety inspections. The step-by-step contents of the standard procedure obtained as a result of this research are: Step 1, facility information collection and analysis, Step 2, analysis of vulnerable parts and drone flight planning, Step 3, drone photography and data processing, Step 4, condition evaluation by external inspection, Step 5, building of external inspection diagram and database. Therefore, if the safety inspections of civil engineering facilities including bridges are performed according to this standard procedure, it is expected that these inspection can be carried out more systematically and efficiently.

• The Journal of Korean Institute of Next Generation Computing
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• v.13 no.6
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• pp.96-105
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• 2017

In this paper, we investigated the age classification from the speaker by analyzing the voice calls of the emergency center. We classified the adult and elderly from the call center calls using behavioral speech utterances and SVM(Support Vector Machine) which is a machine learning classifier. We selected two behavioral speech utterances through analysis of the call data from the emergency center: Silent Pause and Turn-taking latency. First, the criteria for age classification selected through analysis based on the behavioral speech utterances of the emergency call center and then it was significant(p <0.05) through statistical analysis. We analyzed 200 datasets (adult: 100, elderly: 100) by the 5 fold cross-validation using the SVM(Support Vector Machine) classifier. As a result, we achieved 70% accuracy using two behavioral speech utterances. It is higher accuracy than one behavioral speech utterance. These results can be suggested age classification as a new method which is used behavioral speech utterances and will be classified by combining acoustic information(MFCC) with new behavioral speech utterances of the real voice data in the further work. Furthermore, it will contribute to the development of the emergency situation judgment system related to the age classification.

• 한국체육학회지인문사회과학편
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• v.55 no.1
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• pp.457-467
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• 2016

Understanding professional baseball fans' expenditure is expected to provide fundamental marketing information that help increase each team's marketing profits and values and produce a better economic impact on its community. In this regard, this study employed a survey method with a total of 372 residents located in Changwon. A questionnaire included factors such as demographics, consumption patterns and perceived socio-psychic effect(PSE), all of which were derived from literature review. A binary logistic regression was modeled with a dichotomous dependent variable, expenditure(30,000 won more or less). The following were input in the model as the independent variables in order to see the relationships; gender, marriage, education, occupation, income, location, age, leisure type, distance, companion, transportation, interest, and PSE. The results of the logistic regression analysis are as follows. Overall, the model was statistically significant, χ²(21, N=372)=59.159, p=.000. Cox and Snell R² was reported as .147 and .200 respectively. So, the model accounted for between 14.7% and 20.0% of the variation in expenditure. Among the independent variables, income, location, companion, and PSE were found to be the significant factors to expenditure. For income, subjects with 2 million won less of income, compared to those with 4 million won more, were .38 times less likely to pay the money of 30,000 won more. For location, subjects in Masan, compared to those in Jinhae, were 3.49 times more likely to pay 30,000 won more. Subjects in Changwon, compared to those in Jinhae, were 3.05 times more likely to pay 30,000 won more. For companion, people visiting the stadium alone, compared to those with friends/colleague, were .36 times less likely to pay 30,000 won more. For PSE, the odds of 30,000 won more paid increased by 1.37 times with one-unit increase in PSE.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.335-335
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• 2022

남한상세 기후변화 전망보고서(2021)는 2100년대 강원도 강수량이 현재보다 19% 증가하고, 평균기온이 현재보다 6.5℃ 상승할 것으로 공표했다. 강원도는 영동지역과 영서지역으로 분리돼 기후 차이가 분명하다. 기상청 ASOS 데이터(1986~2020)를 이용해 기후 특성을 확인한 결과 영동지역 강수량은 1,463mm, 평균기온은 10.5℃, 상대습도는 66%로 분석됐고, 영서지역 강수량은 1,307mm, 평균기온은 11℃, 상대습도는 68%로 분석됐다. 영동지역 강수량이 영서지역 강수량보다 약 156mm 더 많으며, 이는 영동지역에서 큰 규모의 우심 피해가 발생할 가능성이 존재함을 의미한다. 강원도 평년 우심 피해 현황을 살펴본 결과 영동지역은 5회(피해액: 62억 원), 영서지역은 24회(피해액: 62억원)가 발생했다. 이는 미래로 갈수록 더 심해질 것으로 판단되며, 이런 기상 재난을 객관적으로 판단할 수 있는 기준이 필요하다. 이에 본 연구에서는 기후변화에 따른 강원도 기후 재난취약성을 평가했다. 이를 위해 기후변화 위험성, 기후변화 민감도, 기후변화 적응능력 지표를 활용해 기후변화 취약성 지표를 선정했다. 기후변화 위험성 지표는 홍수(CWD, Rx5day, R30mm), 가뭄(CDD, SU, TX90p), 폭염(SU, TR, TN90p), 한파(ID, TX10p, FD)로 RCP 8.5 기후변화시나리오를 ETCCDI 지수에 적용했다. 기후변화 민감도와 기후변화 적응능력 지표는 국가통계포털, 강원통계정보, WAMIS에서 자료를 수집해 선정했다. 또한 재난취약성 지표를 4단계(Very Low, Low, High, Very High)로 구분했다. 홍수 취약성 평가 결과 2090년대 원주시, 춘천시, 횡성군이 Low에서 Very High로 단계가 격상됐다. 가뭄 취약성 평가 결과 2090년대 양양군, 영월군, 정선군이 Very Low에서 Very High로 단계가 격상됐다. 폭염 취약성 평가 결과 2090년대 삼척시, 태백시, 영월군이 Very Low에서 Very High로 단계가 격상됐다. 한파 취약성 평가 결과 삼척시, 태백시, 영월군이 High에서 Very Low로 단계가 격하됐다. 고로 강원도는 기후 재난취약성 평가 결과에 따른 미래 기후변화를 대비하고, 각 지역 특성에 맞는 복원력 관점 기후 재난 관리가 필요하다고 사료된다.