• Journal of the Korean Society of Food Culture
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• v.24 no.6
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• pp.778-783
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• 2009

The purpose of this study was to determine the basic materials needed for nutrition and health programs for aged people. In order to set up these programs, the nutritional habit, nutritional knowledge and functional health status (mobility, functional assessment, and falls efficacy) of the aged were measured, and their relationships were determined. Data was collected on 57 aged individuals that participated in the 'Exercise Program for the Aged' conducted by the National Health Insurance Corporation. These 57 subjects were interviewed and tested by direct measurement prior to conducting the program. The data was analyzed using the SPSS 13.0 Package. According to the results, the nutritional habit ranged from 24-50 out of 50, and the average was 37.2, which was above the middle level. The average nutritional knowledge was of 4.02 out of 5, which was considered reasonably high. Especially, more than half of these subjects were uneducated, but they had a high interest in nutrition. The average mobility was determined to be 9.2 seconds and the falls efficacy was 64.2 out of 100. In addition, subjects answered that they had a fear of falling due to low confidence, which indicates that safety education for the prevention of falls should be provided to aged individuals in the future. The results showed that notable counter-relations between nutritional habit and functional health status existed.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.33 no.3
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• pp.284-290
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• 2023

Objectives: Work environment assessments were conducted to investigate epidemiologically several cases of lung cancer and COPD (chronic obstructive pulmonary disease) among workers in domestic quarries. Methods: We visited three quarries in South Korea where an epidemiological investigation was requested and measured total dust, respirable dust, and crystalline silica on rock drilling workers (4 people) and rock chipping workers (13 people). Measurement and analysis were conducted according to NIOSH (National Institute for Occupational Safety & Health) method 0500, NIOSH method 0600 for respirable dust, and NIOSH method 7500 for crystalline silica. Results: Among rock drilling workers the AMs (arithmetic mean) of total dust concentrations, respirable dust concentrations, and crystalline silica concentrations were 3.462 mg/m³ (range: 0.764~6.085 mg/m³), 0.613 mg/m³ (range: 0.153~1.251 mg/m³), and 0.105 mg/m³ (range: 0.012~0.228 mg/m³), respectively. Among rock chipping workers, the AMs of total dust concentrations, respirable dust concentrations, and crystalline silica concentrations were 2.446 mg/m³ (range: 0.156~8.494 mg/m³), 0.488 mg/m³ (range: 0.028~1.536 mg/m³), and 0.099 mg/m³ (range: 0.004~0.274 mg/m³), respectively. Conclusions: Although it cannot be said that the dust concentrations were high for both rock drilling workers and rock chipping workers, the concentrations of crystalline silica were found to be high. If such work is performed for a long period of time, diseases such as lung cancer and COPD may occur, so the work environment needs to be improved.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.5
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• pp.43-52
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• 2023

Traffic accidents among children have been decreasing after the installation of yellow carpets. However, the explanatory power of the causal relationship between yellow carpet installation and traffic accidents is still insufficient. The yellow carpet effect was analyzed in greater depth using virtual reality (VR) simulation experiments in various situation that could not be evaluated in existing actual vehicle research studies due to difficulties or risks in implementation. A target site where an actual yellow carpet was installed was selected and, implemented into a virtual environment. Subjects were made to, were gaze measurement equipment and ride the simulator. The visual/driving behavior before and after yellow carpet installation was compared, and a t-test analysis was performed for statistical verification. All the results were found to be statistically significant.

• Journal of Internet of Things and Convergence
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• v.9 no.6
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• pp.37-44
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• 2023

As a primary technology of Industry 4.0, human-robot collaboration (HRC) requires additional measures to ensure worker safety. Previous studies on avoiding collisions between collaborative robots and workers mainly detect collisions based on sensors and cameras attached to the robot. This method requires complex algorithms to continuously track robots, people, and objects and has the disadvantage of not being able to respond quickly to changes in the work environment. The present study was conducted to implement a web-based platform that manages collaborative robots by recognizing the emotions of workers - specifically their perception of danger - in the collaborative process. To this end, we developed a web-based application that collects and stores emotion-related brain waves via a wearable device; a deep-learning model that extracts and classifies the characteristics of neutral, positive, and negative emotions; and an Internet-of-things (IoT) interface program that controls motor operation according to classified emotions. We conducted a comparative analysis of our system's performance using a public open dataset and a dataset collected through actual measurement, achieving validation accuracies of 96.8% and 70.7%, respectively.

• Journal of Korean Physical Therapy Science
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• v.30 no.3
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• pp.49-58
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• 2023

Background: This study aims to examine the useful- ness of the portable spirometer "The Spirokit" as a clinical diagnostic device through technology introduction, precision test, and correction. Design: Technical note Methods: "The Spirokit" was developed using a propeller-type flow rate and flow rate measurement method using infrared and light detection sensors. The level of agreement between the Pulmonary Waveform Generator and the measured values was checked to determine the precision of "The Spirokit", and the correction equation was included using the Pulmonary Waveform Generator software to correct the error range. The analysis was requested using the ATS 24/26 waveform recognized by the Ministry of Food and Drug Safety and the American Thoracic Society for the values of Forced Voluntary Capacity (FVC), Forced Expiratory Volume in 1second (FEV1), and Peak Expiratory Flow (PEF), which are used as major indicators for pulmonary function tests. All tests were repeated five times to derive an average value, and FVC and FEV1 presented accuracy and PEF presented accuracy as the result values. Results: FVC and FEV1 of 'The Spirokit' developed in this study showed accuracy within ± 3% of the error level in the ATS 24 waveform. The PEF value of 'The Spirokit' showed accuracy within the error level ± 12% of the ATS 26 waveform. Conclusion: Through the results of this study, the precision of 'The Spirokit' as a clinical diagnosis device was identified, and it was confirmed that it can be used as a portable pulmonary function test that can replace a spirometer.

• Nutrition Research and Practice
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• v.17 no.5
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• pp.945-958
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• 2023

BACKGROUND/OBJECTIVES: Food literacy (FL) is a crucial skill for selecting sustainable and healthy food options, necessitating the identification of vulnerable groups in the community using valid measurement tools. Identifying weak domains in FL is essential for enhancing the overall FL. This study examined the FL levels of Seoul citizens based on their sociodemographic characteristics and assessed the relationship between FL, food intake, and weight status. SUBJECTS/METHODS: This study utilized the data from the Seoul Food Survey, a cross-sectional study employing representative samples of Seoul citizens. Data collection occurred from September to October 2021, with 4,039 citizens aged 18 yrs and above participating in face-to-face surveys. Thirty-three FL items were assessed, comprising 14 items in the nutrition and safety (NS) domain, eight items in the cultural and relational (CR) domain, and 11 items in the socio-ecological (SE) domain. In addition, data on food intake sufficiency and obesity status were collected. The descriptive statistics, t-tests, analysis of variance, and logistic regression analysis were used for analysis. RESULTS: Men, students, young adults, older citizens, and people experiencing food insecurity had the lowest scores for all the FL domains. The highest quartile group of NS scores had a higher probability of consuming adequate servings of vegetables and fruits, with significant linear trends observed (P for trend < 0.05). In all three FL domains, the odds ratio for obesity was significantly lower in the groups with high FL scores (P < 0.05). CONCLUSIONS: A close relationship was observed between low FL, obesity, and food intake, even after controlling for other covariates. Vulnerable groups with low FL were also identified. Therefore, it is essential to develop programs to improve FL and the health and well-being of these groups.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.6
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• pp.1307-1312
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• 2023

In this paper, we propose a hybrid camera system that combines cameras with different focal lengths and LiDAR (Light Detection and Ranging) sensors to address the core components of autonomous driving perception technology, which include object recognition and distance measurement. We extract objects within the scene and generate precise location and distance information for these objects using the proposed hybrid camera system. Initially, we employ the YOLO7 algorithm, widely utilized in the field of autonomous driving due to its advantages of fast computation, high accuracy, and real-time processing, for object recognition within the scene. Subsequently, we use multi-focal cameras to create depth maps to generate object positions and distance information. To enhance distance accuracy, we integrate the 3D distance information obtained from LiDAR sensors with the generated depth maps. In this paper, we introduce not only an autonomous vehicle platform capable of more accurately perceiving its surroundings during operation based on the proposed hybrid camera system, but also provide precise 3D spatial location and distance information. We anticipate that this will improve the safety and efficiency of autonomous vehicles.

• Journal of the Korean Geosynthetics Society
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• v.23 no.2
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• pp.19-27
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• 2024

Geotechnical structures such as dams, tunnels, and slopes require regular inspection and monitoring to ensure stability. Domestically, drones and accelerometers have become common tools for inspecting and monitoring various structures. However, drones have difficulty identifying internal changes in structures and the subsurface, and accelerometers generally serve for seismic design or strain measurement purposes. Therefore, this paper proposes to utilize accelerometers to monitor the internal information of the ground on a real-time or periodic basis. The proposed method utilizes a part of the analysis technique from the SASW test to monitor the stability and state changes of geotechnical structures. Cases where SASW was used to evaluate the safety of geotechnical structures, such as slopes, dams, and tunnels, were reviewed to verify the suitability of the technology. To make the proposed method more practical, the study considered using only the first-step analysis to derive the dispersion curve rather than the second-step analysis to determine the shear wave velocity profile, which requires complex analysis. The proposed technique is expected to enable the continuous monitoring and inspection of geotechnical structures by utilizing accelerometers.

• Journal of the Korean Geotechnical Society
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• v.40 no.2
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• pp.65-79
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• 2024

This study employs traditional statistical auto-regressive integrated moving average (ARIMA) and deep learning-based long short-term memory (LSTM) models to predict the deformation of earth retaining walls using inclinometer data from excavation sites. It compares the predictive capabilities of both models. The ARIMA model excels in analyzing linear patterns as time progresses, while the LSTM model is adept at handling complex nonlinear patterns and long-term dependencies in the data. This research includes preprocessing of inclinometer measurement data, performance evaluation across various data lengths and input conditions, and demonstrates that the LSTM model provides statistically significant improvements in prediction accuracy over the ARIMA model. The findings suggest that LSTM models can effectively assess the stability of retaining walls at excavation sites. Additionally, this study is expected to contribute to the development of safety monitoring systems at excavation sites and the advancement of time series prediction models.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.197-208
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• 2024

In today's era, where internet technology and culture are advancing rapidly, the importance of systematic internet ethics education has been underscored to address the insufficient levels of internet ethics among college students. This research primarily focused on assessing the level of internet ethics among college students, who represent a significant proportion of internet users. The innovative Flip Learning teaching method and the introduction of the Wheeler Model, along with the application of frequency measurement theory, allowed us to explore ways to maximize the effectiveness of the education. It was confirmed that students who received internet ethics education demonstrated improved levels of ethics. This study concluded that significant progress has been made in systematizing and effectively promoting internet ethics education. It also proposed the need for systematic ethics education and provided future directions for improving internet ethics education.