• Journal of the Korean Society of Environmental Restoration Technology
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• v.26 no.5
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• pp.19-32
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• 2023

The fragmentation of habitats resulting from human activities leads to the isolation of wildlife and it also causes wildlife-vehicle collisions (i.e. Road-kill). In that sense, it is important to predict potential habitats of specific wildlife that causes wildlife-vehicle collisions by considering geographic, environmental and transportation variables. Road-kill, especially by large mammals, threatens human safety as well as financial losses. Therefore, we conducted this study on roe deer (Capreolus pygargus tianschanicus), a large mammal that causes frequently Road-kill in Jeju Island. So, to predict potential wildlife habitats by considering geographic, environmental, and transportation variables for a specific species this study was conducted to identify high-priority restoration sites with both characteristics of potential habitats and road-kill hotspot. we identified high-priority restoration sites that is likely to be potential habitats, and also identified the known location of a Road-kill records. For this purpose, first, we defined the environmental variables and collect the occurrence records of roe deer. After that, the potential habitat map was generated by using Random Forest model. Second, to analyze roadkill hotspots, a kernel density estimation was used to generate a hotspot map. Third, to define high-priority restoration sites, each map was normalized and overlaid. As a result, three northern regions roads and two southern regions roads of Jeju Island were defined as high-priority restoration sites. Regarding Random Forest modeling, in the case of environmental variables, The importace was found to be a lot in the order of distance from the Oreum, elevation, distance from forest edge(outside) and distance from waterbody. The AUC(Area under the curve) value, which means discrimination capacity, was found to be 0.973 and support the statistical accuracy of prediction result. As a result of predicting the habitat of C. pygargus, it was found to be mainly distributed in forests, agricultural lands, and grasslands, indicating that it supported the results of previous studies.

• Journal of the Korean Applied Science and Technology
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• v.39 no.6
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• pp.853-863
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• 2022

In order to revitalize start-ups in the beauty field, this study attempted to derive characteristic patterns of changes in demand and differences in emotions and meaning for 'beauty start-ups' by dividing the period by year from 2019 to 2021 based on exploratory data analysis (EDA). Most of the search terms related to the keyword "beauty start-up" showed more interest in institutions or certificates that can learn beauty skills than professional start-up education, which still does not recognize the importance of start-up education, and as an alternative, it is necessary to develop customized start-up education programs for each major. We establish hypotheses through exploratory data analysis and verify hypotheses by combining traditional corroborative data analysis (CDA). There has never been an exploratory data analysis method for beauty startups, and rather than mentioning the need for formal start-up education, analyzing changes in interest in beauty startups and the requirements of prospective start-ups with exploratory data will help develop customized start-up programs.

• Journal of the Korean Society of Radiology
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• v.17 no.6
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• pp.977-983
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• 2023

Due to the development of the domestic economy and science, the people's standard of living has increased. Accordingly, we want to improve the quality of life. In other words, we guarantee human rights and pursue dignity and value as human beings. Therefore, the medical field extends human life and helps maintain a healthy life. The social medicine that protects human rights is forensic medicine. Forensic medicine identifies deaths and analyzes the cause using forensic radiology images. Forensic radiology is the acquisition and provision of medical images by the radiographer. Therefore, the radiographer must have expertise by completing forensic science-related courses. Recently, medical and nursing schools have opened and operated various subjects such as forensic medicine and forensic nursing. However, the Department of Radiology science is the only school that offers courses related to forensic science. For the future development and exploration of the radiographer and department of radiology science, forensic education should be considered. For this purpose, we investigated the necessity and demand for forensic education in the department of radiology science undergraduate and graduate schools. The department of radiology science students' awareness of forensic science was found to be 2.977 points, but the need for forensic science education for the radiographer was high at 3.759 points. In addition, current students' demand for forensic science courses was high at 84.1%, with the majority responding that it was necessary to open and operate the course. This study was able to determine the demand for forensic science-related subjects among the department of radiology science undergraduate and graduate students, and there is a need to explore diversity and expertise in education. We hope that it will be used as basic data for the development of forensic medicine and radiology science.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1273-1281
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• 2023

Absolute radiometric calibration is a crucial process in converting the electromagnetic signals obtained from satellite sensors into physical quantities. It is performed to enhance the accuracy of satellite data, facilitate comparison and integration with other satellite datasets, and address changes in sensor characteristics over time or due to environmental conditions. In this study, field campaigns were conducted to perform vicarious calibration for the multispectral channels of the CAS500-1. Two valid field observations were obtained under clear-sky conditions, and the top-of-atmosphere (TOA) radiance was simulated using the MODerate resolution atmospheric TRANsmission 6 (MODTRAN 6) radiative transfer model. While a linear relationship was observed between the simulated TOA radiance of tarps and CAS500-1 digital numbers(DN), challenges such as a wide field of view and saturation in CAS500-1 imagery suggest the need for future refinement of the calibration coefficients. Nevertheless, this study represents the first attempt at absolute radiometric calibration for CAS500-1. Despite the challenges, it provides valuable insights for future research aiming to determine reliable coefficients for enhanced accuracy in CAS500-1's absolute radiometric calibration.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.10
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• pp.445-454
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• 2023

Recently, various fault diagnosis studies are being conducted utilizing data from collaborative robots. Existing studies performing fault diagnosis on collaborative robots use static data collected based on the assumed operation of predefined devices. Therefore, the fault diagnosis model has a limitation of increasing dependency on the learned data patterns. Additionally, there is a limitation in that a diagnosis reflecting the characteristics of collaborative robots operating with multiple joints could not be conducted due to experiments using a single motor. This paper proposes an LSTM diagnostic model that can overcome these two limitations. The proposed method selects representative normal patterns using the correlation analysis of vibration and current data in single-axis and multi-axis work environments, and generates residual patterns through differences from the normal representative patterns. An LSTM model that can perform gear wear diagnosis for each axis is created using the generated residual patterns as inputs. This fault diagnosis model can not only reduce the dependence on the model's learning data patterns through representative patterns for each operation, but also diagnose faults occurring during multi-axis operation. Finally, reflecting both internal and external data characteristics, the fault diagnosis performance was improved, showing a high diagnostic performance of 98.57%.

• Korean Journal of Remote Sensing
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• v.39 no.5_4
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• pp.1125-1134
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• 2023

Out of the total 17,000 reservoirs in Korea, 13,600 small agricultural reservoirs do not have hydrological measurement facilities, making it difficult to predict water storage volume and appropriate operation. This paper examined univariate and multivariate long short-term memory (LSTM) modeling to predict the storage rate of agricultural reservoirs using remote sensing and artificial intelligence. The univariate LSTM model used only water storage rate as an explanatory variable, and the multivariate LSTM model added n-day accumulative precipitation and date of year (DOY) as explanatory variables. They were trained using eight years data (2013 to 2020) for Idong Reservoir, and the predictions of the daily water storage in 2021 were validated for accuracy assessment. The univariate showed the root-mean square error (RMSE) of 1.04%, 2.52%, and 4.18% for the one, three, and five-day predictions. The multivariate model showed the RMSE 0.98%, 1.95%, and 2.76% for the one, three, and five-day predictions. In addition to the time-series storage rate, DOY and daily and 5-day cumulative precipitation variables were more significant than others for the daily model, which means that the temporal range of the impacts of precipitation on the everyday water storage rate was approximately five days.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.1
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• pp.57-68
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• 2023

With the technological development in the era of the 4th Industrial Revolution, technologies using HMD are being applied in various fields. HMD is especially useful in virtual reality fields such as AR/VR, and is very effective in receiving vivid impressions from users located in remote locations. According to these characteristics, the frequency of using HMD is increasing in the field related to collaboration. However, when HMD is applied to collaboration, communication between experts located in remote locations and workers located in the field is not smooth, causing various problems in terms of usability. In this paper, remote experts and workers in the field use HMD to solve various problems arising from collaboration, design/propose new types of HMD structures and functions that enable more efficient collaboration, and verify their usability using SUS evaluation techniques. As a result of the SUS evaluation, the new type of HMD structure and function proposed in this paper was 86.75points, which is believed to have greatly resolved the restrictions on collaboration and inconvenience in use of the existing HMD structure. In the future, when the HMD structure and design proposed in this paper are actually applied, it is expected that the application technology using HMD will expand rapidly.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.6
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• pp.775-784
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• 2023

In terms of flood management, it is necessary to analyze quantitative rainfall and runoff from a spatial and temporal perspective and to analyze runoff for heavy rainfall events that are concentrated within a short period of time. The simulation and analysis results of rainfall-runoff models vary depending on the type and input data. In particular, rainfall data is an important factor, so calculating areal mean rainfall is very important. In this study, the areal mean rainfall of the Samcheok Osipcheon(Riv.) watersheds located in the mountainous terrain was calculated using the Arithmetic Mean Method, Thiessen's Weighting Method, and the Isohyetal Method, and the rainfall-runoff results were compared by applying the distributional model S-RAT and the lumped model HEC-HMS. The results of the temporal transferability study showed that the combination of the distributional model and the Isohyetal Method had the best statistical performance with MAE of 64.62 m³/s, RMSE of 82.47 m³/s, and R² and NSE of 0.9383 and 0.8547, respectively. It is considered that this study was properly analyzed because the peak flood volume occurrence time of the observed and simulated flows is within 1 hour. Therefore, the results of this study can be used for frequency analysis in the future, which can be used to improve the accuracy of simulating peak flood volume and peak flood occurrence time in mountainous watersheds with steep slopes.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.409-417
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• 2023

This study was attempted to confirm the effects of covert narcissism, self-directed learning ability, academic achievement on self-leadership in nursing students. This study targeted 247 nursing students in B and Y cities. Data analysis was analyzed by descriptive statistics, t-test, ANOVA, Pearson's correlation coefficient, and multiple regression analysis using the SPSS 22.0 program. The average self-leadership of the subjects was 3.14±0.62 points, and the difference in self-leadership according to general characteristics was significant in major satisfaction (F=11.111, p<.001). There was positive correlation between self-leadership and self-directed learning ability (r=.630, p<.001), academic achievement (r=.532, p<.001), and negative correlation between covert narcissism (r=-.206, p=.001). The factors influencing the subject's self-leadership were identified as covert narcissism (β=-.147, p=.031), self-directed learning ability (β=.468, p<.001) and academic achievement (β=.282, p<.001) and the explanatory power was 46.9%. Based on the results of the study, the necessary of developing an effective education program considering the self-leadership and related factors of nursing students was suggested.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.1143-1149
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• 2023

The purpose of this study was to the effects of case-based learning (CBL) on problem solving ability and academic self-efficacy in nursing students and was a quasi-experimental study with a one-group pretest-posttest design. The subjects of this study were 121 grade 4 students, and the data collection period was from Aprill 24 to June 12, 2023. The research procedure was scenario development, preliminary investigation, application of case-based learning classes, and follow-up investigation, and the CBL was conducted for 2 weeks, 50 minutes per week. The general characteristics of the subjects were obtained by frequency, percentage, mean, and standard deviation and the effects of CBL on problem solving ability and academic self-efficacy was tested using a paired t-test. The results of this study showed that nursing students' problem solving ability (t=-5.70, p<.001) and academic self-efficacy (t=-3.25, p<.002) improved after applying CBL compared to before applying it. We suggest the use of case-based learning as a strategy to improve problem-solving skills and academic self-efficacy in nursing education. In the future, follow-up research is needed to verify the effectiveness by developing and applying step-by-step clinical cases at an appropriate level according to the learning content of nursing major subjects by grade.