• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
• /
• 2009.05a
• /
• pp.380-383
• /
• 2009

The grounding system of the subsurface should ensure the safe and reliable operation of power systems, and guarantee a human being's safety in the situation of grounding fault in the power system. The safety of power apparatus in the subsurface can be reached by decreasing grounding resistance and grounding potential rise of subsurface. This paper presents a method based on the design of an artificial neural network(ANN) model for modeling and predicting the relationship between the grounding resistance and temperature-humidity in the subsurface.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.14 no.6
• /
• pp.1138-1143
• /
• 2011

One of the critical items in radar testing is the ability to evaluate the performance of radar systems under real operational environments. But it takes lots of time and cost to operate real targets and analyze the test results due to a large amount of data based on these complicated environments. In this paper, the Radar Simulative T&E Lab. is introduced, and the test and analysis results of the developing radar for predicting the radar system performance are described in the Radar Simulative T&E Lab. This laboratory could be used to test the far-field characteristics of antenna radiation pattern and to perform an effective radar system test and evaluation using a simulative target generator under a low cost repeating test situation.

• International Journal of Computer Science & Network Security
• /
• v.22 no.2
• /
• pp.145-152
• /
• 2022

One of the impacts of Covid-19 on education systems has been the shift to online education. This shift has changed the way education is consumed and perceived by students. However, the exact nature of student perception about online education is not known. The aim of this study was to understand the perceptions of Saudi higher education students (e.g., post-school students) about online education during the Covid-19 pandemic. Various aspects of online education including benefits, features and cybersecurity were explored. The data collected were analysed using statistical techniques, especially artificial neural networks, to address the research aims. The key findings were that benefits of online education was perceived by students with positive experience or when ensured of safe use of online platforms without the fear cyber security breaches for which recruitment of a cyber security officer was an important predictor. The issue of whether perception of online education as a necessity only for Covid situation or a lasting option beyond the pandemic is a topic for future research.

• Journal of the Ergonomics Society of Korea
• /
• v.6 no.1
• /
• pp.9-24
• /
• 1987

The design and philosophy are presented for an intelligent aid for a hyman operator who must diagnose a novel fault in a physical system. A novel fault is defined as one that the operator has not experienced in either real system operation or training. When the operator must diagnose a novel fault, deep reasoning about the behavior of the system components is required. To aid the human operator in this situation, four aiding approaches which provide useful information are proposed. The aiding information is generated by a qualitative, component-level model of the physical system. Both the aid and the human are able to reason causally about the system in a cooperative search for a diagnosis. The aiding features were designed to help the hyman's use of his/her mental model in predicting the normal system behavior, integrating the observations into the actual system behavior, or finding discrepancies between the two. The aid can also have direct access to the operator's hypotheses and run a hypothetical system model. The different aiding approaches will be evaluated by a series of experiments.

• The Journal of the Convergence on Culture Technology
• /
• v.1 no.1
• /
• pp.15-26
• /
• 2015

The purpose of this study was to analyze the sexual related predicting factors for Female University students in Korea. The cross-sectional descriptive study design was used. We selected 320 students from 6 Universities located in Seoul, Chungchung-do and Gangwon-do by convenience random sampling and received IRB from Y Univ. 299 students were included in the final analysis using logistic regression. Among 299 students, 60.2% of students reported to have sexual experience. The result of analyzing the related factors to sexual experience revealed that the students who were having friends who had sexual experience, smokers and those who were high grade, had significantly more sexual experience. According to the results of this study, there should be an intensive and female tailed sexual related program development for the University students, especially for smokers and including smoking cessation program. And the school health services of University combined general staff working should be strengthened to protect the University students from the critical situation caused by unwanted sexual experience.

• Parasites, Hosts and Diseases
• /
• v.58 no.3
• /
• pp.229-236
• /
• 2020

Cutaneous leishmaniosis (CL) is the most common form of leishmaniasis.CL caused by L. major and L. tropica is endemic in 17 provinces of Iran. This study was carried out to elucidate situation of CL in Ardabil province and to predict distribution of Phlebotomus papatasi and Phlebotomus sergenti (Diptera: Psychodidae) as vectors of CL in the region. In this cross-sectional study, data on CL patients were collected from local health centers of Ardabil province, Iran during 2006-2018 to establish a geodatabase using ArcGIS10.3. A total of 20 CL cases were selected randomly and skin samples were collected and analyzed by PCR method. MaxEnt 3.3.3 model was used to determine ecologically suitable niches for the main vectors. A total, 309 CL human cases were reported and the highest incidence rate of disease was occurred in Bilasavar (37/100,000) and Germi (35/100,000). A total of 2,794 sand flies were collected during May to October 2018. The environmentally suitable habitats for P. papatasi and P. sergenti were predicted to be present in northern and central areas of Ardabil province. The most variable that contributed ratio in the modeling were Isothermality and slope factors. Ardabil province is possibly an endemic are for CL. The presence of P. papatasi and P. sergenti justifies local transmission while the vectors of CL are existing in the northern and central areas of the province.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.40 no.4
• /
• pp.237-245
• /
• 2017

Our research is aimed at predicting recent trend and leading technology for the future and providing optimal Nano technology trend information by analyzing Nano technology trend. Under recent global market situation, Users' needs and the technology to meet these needs are changing in real time. At this point, Nano technology also needs measures to reduce cost and enhance efficiency in order not to fall behind the times. Therefore, research like trend analysis which uses search data to satisfy both aspects is required. This research consists of four steps. We collect data and select keywords in step 1, detect trends based on frequency and create visualization in step 2, and perform analysis using data mining in step 3. This research can be used to look for changes of trend from three perspectives. This research conducted analysis on changes of trend in terms of major classification, Nano technology of 30's, and key words which consist of relevant Nano technology. Second, it is possible to provide real-time information. Trend analysis using search data can provide information depending on the continuously changing market situation due to the real-time information which search data includes. Third, through comparative analysis it is possible to establish a useful corporate policy and strategy by apprehending the trend of the United States which has relatively advanced Nano technology. Therefore, trend analysis using search data like this research can suggest proper direction of policy which respond to market change in a real time, can be used as reference material, and can help reduce cost.

• Journal of Internet of Things and Convergence
• /
• v.8 no.3
• /
• pp.69-74
• /
• 2022

Big data related analysis techniques, the prescriptive analytics methodology improves the performance of passive learning models by ensuring that active learning secures high-quality learning data. Prescriptive analytics is a performance maximizing process by enhancing the machine learning models and optimizing systems through active learning to secure high-quality learning data. It is the best subscription value analysis that constructs the expensive category data efficiently. To expand the value of data by collecting research field, research propensity, and research activity information, customized researcher through prescriptive analysis such as predicting the situation at the time of execution after data pre-processing, deriving viable alternatives, and examining the validity of alternatives according to changes in the situation Provides research information service.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.21 no.5
• /
• pp.233-252
• /
• 2022

Recently, various studies have been conducted to improve automated vehicle (AV) safety for AVs commercialization. In particular, the scenario method is directly related to essential safety assessments. However, the existing scenario do not have objectivity and explanability due to lack of data and experts' interventions. Therefore, this paper presents the AVs safety assessment extended scenario using real traffic accident data and vision transformer (ViT), which is explainable artificial intelligence (XAI). The optimal ViT showed 94% accuracy, and the scenario was presented with Attention Map. This work provides a new framework for an AVs safety assessment method to alleviate the lack of existing scenarios.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2021.10a
• /
• pp.332-334
• /
• 2021

As fatal accidents due to industrial accidents and deaths due to civil accidents were pointed out as social problems, the Act on Punishment of Serious Accidents Occurred in the Workplace was enacted to ensure the safety of citizens and to prevent serious accidents in advance. Effort is required. In this paper, we propose a distance prediction model in relation to the case where an operator is hit by heavy equipment such as a forklift. For the data, actual forklift trucks and workers roaming environments were directly captured by CCTV, and it was conducted based on the Euclidean distance. It is thought that it will be possible to learn YOLO-v4 by directly building a data-set at the industrial site, and then implement a model that predicts the distance and determines whether it is a dangerous situation, which can be used as basic data for a comprehensive risk situation judgment model.