• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.5
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• pp.100-112
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• 2021

With the advent of big data, traffic prediction has been developed based on historical data analysis methods, but this method deteriorates prediction performance when a traffic incident that has not been observed occurs. This study proposes a method that can compensate for the reduction in traffic prediction accuracy in traffic incidents situations by hybrid approach of machine learning and traffic simulation. The blind spots of the data-driven method are revealed when data patterns that have not been observed in the past are recognized. In this study, we tried to solve the problem by reinforcing historical data using traffic simulation. The proposed method performs machine learning-based traffic prediction and periodically compares the prediction result with real time traffic data to determine whether an incident occurs. When an incident is recognized, prediction is performed using the synthetic traffic data generated through simulation. The method proposed in this study was tested on an actual road section, and as a result of the experiment, it was confirmed that the error in predicting traffic state in incident situations was significantly reduced. The proposed traffic prediction method is expected to become a cornerstone for the advancement of traffic prediction.

• Journal of the Korea Fashion and Costume Design Association
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• v.23 no.3
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• pp.1-10
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• 2021

Harnesses are used in a variety of industries, such as rescue operations, medicine, and entertainment. However, conventional harnesses have problems as they are uncomfortable to wear and causes continuous pain. Therefore, in this study, the load and pressure applied to the body in the flying state when using a conventional harness were measured in real time and the distribution change was observed. Load and pressure were measured using a modified corset harness, a pressure sensor, and a human mannequin to measure the maximum and average pressure on the waist. As a result, it was confirmed that the load concentrated on the waist in the flying state was 104 N, and the pressure was applied to the left and right sides was 800 kPa or greater. The pressure distribution showed a pressure of 3-45 kPa in 73% in all measurable pressures. The results of the load and pressure distribution are presented as basic data for improving the wearability and reducing the discomfort of harnesses in the future, aid in the development of a harnesses that can minimize discomfort for various activities, and increase the concentration on experiential activities. In addition, using the CLO 3D program, which is a 3D virtual wearing system, a harness was put on a virtual model, and the compression level was checked and compared with the actual pressure distribution. As a result of comparing the measured pressure values in the flying state with the clothing pressure wearing the harness in the CLO 3D program, the total pressure value was found to be about 68% of the actual measured value. This helps develop a harness that can minimize discomfort during activities by predicting the load and pressure on the body by first applying new designs to a virtual wearing system during development. These new harness patterns can solve the problems of conventional harnesses.

• Korean Journal of Ecology and Environment
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• v.54 no.4
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• pp.363-373
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• 2021

An ecological niche is defined as the specific role of a species influenced by time, space, and other resources. By investigating overlaps between ecological niches of different species, we could estimate the degrees of interspecific competition. Such studies often use geographic information systems (GIS) to discover niche overlaps between species. In this study, we used GIS to estimate the spatial niches of two Korean frog species(Pelophylax nigromaculatus and P. chosenicus). This enabled us to predict their geographic distributions in order to identify their coexistence regions and distribution patterns. The results confirmed that altitude was an important variable for predicting their distribution, with a correlation with their climatic range. Spatial distributions of the two frog species were highly overlapped, as the distribution range for P. nigromaculatus included most of the range of P. chosenicus, showing a sympatric distribution pattern. Within the coexisting regions, however, the presence sites for the two species did not overlap, implying weak competition. To confirm the principal factors influencing their competitive relationship and reasons for their sympatric distribution pattern, we need more detailed in-depth studies on the diverse environmental variables within the regions where the two species coexist. By doing so, we would be able to identify various mechanisms for avoiding competition in sympatric frog species.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.6
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• pp.121-132
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• 2018

Weather is an important factor affecting roadway transportation in many aspects such as traffic flow, driver 's driving patterns, and crashes. This study focuses on the relationship between weather and road surface condition and develops a model to estimate the road surface condition using machine learning. A road surface sensor was attached to the probe vehicle to collect road surface condition classified into three categories as 'dry', 'moist' and 'wet'. Road geometry information (curvature, gradient), traffic information (link speed), weather information (rainfall, humidity, temperature, wind speed) are utilized as variables to estimate the road surface condition. A variety of machine learning algorithms examined for predicting the road surface condition, and a two - stage classification model based on 'Random forest' which has the highest accuracy was constructed. 14 days of data were used to train the model and 2 days of data were used to test the accuracy of the model. As a result, a road surface state prediction model with 81.74% accuracy was constructed. The result of this study shows the possibility of estimating the road surface condition using the existing weather and traffic information without installing new equipment or sensors.

• The Journal of the Korea Contents Association
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• v.21 no.1
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• pp.722-732
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• 2021

A recent rapid growth in the number of Chinese international students in Korea has generated interest in the key factors to affect their acculturation in domestic culture. In accordance with the growing interest, the present study aims to empirically test and analyze the effects of demographics (gender, age, the length of stay, the length of Korean language education and the level of Korean language skills), SNS use patterns (personal network sizes and hours of use for Korean and Chinese SNS, and motivations of Korean or Chinese SNS uses), and social support through Korean and Chinese SNS on acculturation for Chinese international students in Korea. A total of 322 Chinese international students in Korea participated in the online survey. Results showed that use of Chinese SNS for entertainment had an negative impact on the acculturation, while the use of Korean SNS had an overall positive impact. Finally, this study suggests that the practitioners regarding the issue of acculturation for international students in Korea should focus more on specific guidelines to help their appropriate SNS uses rather than on to prevent their SNS addiction problems.

• Journal of the Society of Disaster Information
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• v.19 no.1
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• pp.216-230
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• 2023

Purpose: The purpose is to prevent accidents by predicting disasters through the analysis of near-miss. Method: In this study, a near-miss literature review and data were collected at construction sites, and a questionnaire survey was conducted to use logistic regression analysis and decision tree analysis to classify the possibility of near-miss connection. Result: As a result of analyzing the effects of near-miss types on mental, physical, and safety habits and behaviors, the factor with a high influence on the body is the need for near-miss management, the type of job is electricity·information communication, and health status in order, and the mental factor is the construction scale The influence was high, and the factors with the highest influence on the habit behavior factors were analyzed in the order of experience, number of serious injuries, and occupation in order of illusion, inappropriate work instructions, and body parts. Through decision tree analysis, factors and patterns that affect the possibility of a near-miss being a surprise accident were identified. Conclusion: Construction site officials consider the observation of near-miss and mentally and physically. Specific management of the relevance of physical aspects to near-miss should be implemented, and a work environment in which serious accidents are reduced is expected through personnel allocation, work plans, work procedures and methods, and feedback so that inappropriate work instructions do not lead to near-miss.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.9
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• pp.387-398
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• 2023

The COVID-19 outbreak has significantly impacted human lifestyles and patterns. It was recommended to avoid face-to-face contact and over-crowded indoor places as much as possible as COVID-19 spreads through air, as well as through droplets or aerosols. Therefore, if a person who has contacted a COVID-19 patient or was at the place where the COVID-19 patient occurred is concerned that he/she may have been infected with COVID-19, it can be fully expected that he/she will search for COVID-19 symptoms on Google. In this study, an exploratory data analysis using deep learning models(DNN & LSTM) was conducted to see if we could predict the number of confirmed COVID-19 cases by summoning Google Trends, which played a major role in surveillance and management of influenza, again and combining it with data on the number of confirmed COVID-19 cases. In particular, search term frequency data used in this study are available publicly and do not invade privacy. When the deep neural network model was applied, Seoul (9.6 million) with the largest population in South Korea and Busan (3.4 million) with the second largest population recorded lower error rates when forecasting including search term frequency data. These analysis results demonstrate that search term frequency data plays an important role in cities with a population above a certain size. We also hope that these predictions can be used as evidentiary materials to decide policies, such as the deregulation or implementation of stronger preventive measures.

• Journal of Korean Academy of Nursing
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• v.53 no.4
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• pp.468-479
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• 2023

Purpose: This study aimed to evaluate the use of the respiratory rate oxygenation (ROX) index, ROX-heart rate (ROX-HR) index, and saturation of percutaneous oxygen/fraction of inspired oxygen ratio (SF ratio) to predict weaning from high-flow nasal cannula (HFNC) in patients with respiratory distress in a pediatric intensive care unit. Methods: A total of 107 children admitted to the pediatric intensive care unit were enrolled in the study between January 1, 2017, and December 31, 2021. Data on clinical and personal information, ROX index, ROX-HR index, and SF ratio were collected from nursing records. The data were analyzed using an independent t-test, χ² test, Mann-Whitney U test, and area under the curve (AUC). Results: Seventy-five (70.1%) patients were successfully weaned from HFNC, while 32 (29.9%) failed. Considering specificity and sensitivity, the optimal cut off points for predicting treatment success and failure of HFNC oxygen therapy were 6.88 and 10.16 (ROX index), 5.23 and 8.61 (ROX-HR index), and 198.75 and 353.15 (SF ratio), respectively. The measurement of time showed that the most significant AUC was 1 hour before HFNC interruption. Conclusion: The ROX index, ROX-HR index, and SF ratio appear to be promising tools for the early prediction of treatment success or failure in patients initiated on HFNC for acute hypoxemic respiratory failure. Nurses caring for critically ill pediatric patients should closely observe and periodically check their breathing patterns. It is important to continuously monitor three indexes to ensure that ventilation assistance therapy is started at the right time.

• The Korean Journal of Pain
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• v.36 no.1
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• pp.113-127
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• 2023

Background: Resting-state functional connectivity (rs-FC) may aid in understanding the link between painmodulating brain regions and the descending pain modulatory system (DPMS) in fibromyalgia (FM). This study investigated whether the differences in rs-FC of the primary somatosensory cortex in responders and non-responders to the conditioned pain modulation test (CPM-test) are related to pain, sleep quality, central sensitization, and the impact of FM on quality of life. Methods: This cross-sectional study included 33 females with FM. rs-FC was assessed by functional magnetic resonance imaging. Change in the numerical pain scale during the CPM-test assessed the DPMS function. Subjects were classified either as non-responders (i.e., DPMS dysfunction, n = 13) or responders (n = 20) to CPM-test. A generalized linear model (GLM) and a receiver operating characteristic (ROC) curve analysis were performed to check the accuracy of the rs-FC to differentiate each group. Results: Non-responders showed a decreased rs-FC between the left somatosensory cortex (S1) and the periaqueductal gray (PAG) (P < 0.001). The GLM analysis revealed that the S1-PAG rs-FC in the left-brain hemisphere was positively correlated with a central sensitization symptom and negatively correlated with sleep quality and pain scores. ROC curve analysis showed that left S1-PAG rs-FC offers a sensitivity and specificity of 85% or higher (area under the curve, 0.78, 95% confidence interval, 0.63-0.94) to discriminate who does/does not respond to the CPM-test. Conclusions: These results support using the rs-FC patterns in the left S1-PAG as a marker for predicting CPM-test response, which may aid in treatment individualization in FM patients.

• Journal of the Korean Society of Radiology
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• v.17 no.7
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• pp.1057-1065
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• 2023

Non-invasive liver fibrosis diagnosis is crucial for patients with chronic liver diseases. Many patients cannot undergo liver tissue biopsy, so predicting the degree of liver fibrosis early through meaningful methods can reduce complications related to chronic liver diseases, such as liver cell carcinoma and cirrhosis. This study compared and analyzed the quantitative measurement of liver fibrosis using shear wave elastography in conjunction with liver ultrasound findings and their associations with serum biomarkers (p<0.05). The results showed that the shear wave elastography measurement in the normal group was 4.55 ± 0.69 kPa, while the abnormal contrast group with echogenic patterns had a measurement of 8.27 ± 1.83 kPa. The hepatitis B carrier group exhibited higher shear wave elastography measurements, and among serum biomarkers, AST, ALT, GGT, and PT showed statistically significant positive correlations with fibrosis severity according to SWE categories (p<0.05), while ALP and TB did not demonstrate statistically significant differences (p=0.163, p=0.567). Conversely, Albumin and PLT showed significant negative correlations (p<0.05). Clinically, utilizing shear wave elastography measurements through liver ultrasound in the tracking and repeat testing of liver fibrosis in chronic hepatitis B patients without cirrhosis can assist in achieving more objective diagnoses among healthcare providers.