• Safety and Health at Work
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• v.11 no.2
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• pp.178-186
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• 2020

Background: Cognitive impairment is a public health burden. Our objective was to investigate associations between work hours and cognitive function. Methods: Multi-Ethnic Study of Atherosclerosis (MESA) participants (n = 2,497; 50.7% men; age range 44-84 years) reported hours per week worked in all jobs in Exams 1 (2000-2002), 2 (2002-2004), 3 (2004-2005), and 5 (2010-2011). Cognitive function was assessed (Exam 5) using the Cognitive Abilities Screening Instrument (version 2), a measure of global cognitive functioning; the Digit Symbol Coding, a measure of processing speed; and the Digit Span test, a measure of attention and working memory. We used a prospective approach and linear regression to assess associations for every 10 hours of work. Results: Among all participants, associations of hours worked with cognitive function of any type were not statistically significant. In occupation-stratified analyses (interaction p = 0.051), longer work hours were associated with poorer global cognitive function among Sales/Office and blue-collar workers, after adjustment for age, sex, physical activity, body mass index, race/ethnicity, educational level, annual income, history of heart attack, diabetes, apolipoprotein E-epsilon 4 allele (ApoE4) status, birth-place, number of years in the United States, language spoken at MESA Exam 1, and work hours at Exam 5 (β = -0.55, 95% CI = -0.99, -0.09) and (β = -0.80, -1.51, -0.09), respectively. In occupation-stratified analyses (interaction p = 0.040), we also observed an inverse association with processing speed among blue-collar workers (adjusted β = -0.80, -1.52, -0.07). Sex, race/ethnicity, and ApoE4 did not significantly modify associations between work hours and cognitive function. Conclusion: Weak inverse associations were observed between work hours and cognitive function among Sales/Office and blue-collar workers.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.31 no.3 s.52
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• pp.219-236
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• 2005

Glycolic acid, an alpha-hydroxy acid derived from fruit and milk sugars, has been commonly used as a cosmetic ingredient since it was known to have photo-protective, anti-inflammatory effects, and anti-oxidant effect in UV-irradiated skin. However, little has been know about the functional role of glycolic acid on UV-induced skin cell proliferation. It was previously found that glycolic acid inhibited UV-induced skin tumor development in hairless mouse. As a possible mechanism of glycolic acid on the UV-induced skin tumor development, the ability of glycolic acid to inhibit the UVB-induced cell growth and possible mechanisms were investigated. Glycolic acid treatment attenuated the UV-induced cell proliferation and apoptotic cell death in the skin. In vitro study, glycolic acid inhibited the UVB-induced cell growth and apoptotic death through inhibiting caspase-3 activity. These results suggest that glycolic acid may exert the Inhibitory effect on the UVB-induced skin tumor development by regulating cell growth and apoptotic cell death.

• Journal of Biomedical Engineering Research
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• v.19 no.5
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• pp.477-486
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• 1998

In this paper, we implemented the urine analysis system capable of measuring a qualitative and semi-quantitative and assay using strip. The analysis algorithm of urine analysis was adopted a fuzzy logic-based classifiers that was robust to external error factors such as temperature and electric power noises. The spectroscopic properties of 9 pads In a strip were studied to developing the urine analysis system was designed for robustnesss and stability. The urine analysis system was consisted of hardware and software. The hardware of the urine analysis system was based on one-chip microprocessor, and Its peripherals which composed of optic modulo, tray control, preamplifier, communication with PC, thermal printer and operating status indicator. The software of the urine analysis system was composed of system program and classification program. The system program did duty fort system control, data acquisition and data analysis. The classification program was composed of fuzzy inference engine and membership function generator. The membership function generator made triangular membership functions by statical method for quality control. Resulted data was transferred through serial cable to PC. The transferred data was arranged and saved be data acquisition program coded by C+ + language. The precision of urine analysis system and the stability of fuzzy classifier were evaluated by testing the standard urine samples. Experimental results showed a good stability states and a exact classification.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.2
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• pp.195-211
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• 2023

For the commercialization For the commercialization of autonomous vehicles (AV), the operational design domain (ODD) of automated driving systems (ADS) is to be clearly defined. A common language and consistent format must be prepared so that AV-related stakeholders can understand ODD at the same level. Therefore, overseas countries are presenting a standardized ODD framework and developing scenarios that can evaluate ADS-specific functions based on ODD. However, ODD includes conditions reflecting the characteristics of each country, such as road environment, weather environment, and traffic environment. Thus, it is necessary to clearly understand the meaning of the items defined overseas and to harmonize them to reflect the specific domestic conditions. Therefore, in this study, domestic optimization of the ODD classification system was performed by analyzing the domestic driving environment based on international standards. The driving environment of currently operating self-driving car test districts (Sangam, Seoul, and Gwangju) was investigated using the developed domestic ODD items. Then, based on the results obtained, the ranges of the ODDs in each test district were determined and compared.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.6B
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• pp.697-707
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• 2008

The grid-based KIneMatic wave STOrm Runoff Model (KIMSTORM) by Kim (1998) predicts the temporal variation and spatial distribution of overland flow, subsurface flow and stream flow in a watershed. The model programmed with C++ language on Unix operating system adopts single flowpath algorithm for water balance simulation of flow at each grid element. In this study, we attempted to improve the model by converting the code into FORTRAN 90 on MS Windows operating system and named as ModKIMSTORM. The improved functions are the addition of GAML (Green-Ampt & Mein-Larson) infiltration model, control of paddy runoff rate by flow depth and Manning's roughness coefficient, addition of baseflow layer, treatment of both spatial and point rainfall data, development of the pre- and post-processor, and development of automatic model evaluation function using five evaluation criteria (Pearson's coefficient of determination, Nash and Sutcliffe model efficiency, the deviation of runoff volume, relative error of the peak runoff rate, and absolute error of the time to peak runoff). The modified model adopts Shell Sort algorithm to enhance the computational performance. Input data formats are accepted as raster and MS Excel, and model outputs viz. soil moisture, discharge, flow depth and velocity are generated as BSQ, ASCII grid, binary grid and raster formats.

• Journal of the Korean Society of Radiology
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• v.8 no.5
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• pp.231-240
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• 2014

The purpose of this study were to analyze that the Seoul neuropsychological screening battery (SNSB) for the evaluating cognitive assessment of the Parkinson's disease patients with mild cognitive impairment (PD-MCI) and the changes of the cerebral ventricle volume in the brain magnetic resonance imaging (MRI), and we has been bring forward the guideline to determine the diagnostic criteria for the PD-MCI. To achieve this, we was diagnosed with Parkinson's disease patients (PD-MCI group: 34 patients; Parkinson's disease with normal cognition, PD-NC group: 34 patients) to perform the SNSB test for the attention, language, memory, visuospatial, and frontal/executive functions and the brain MRI. Additionally, to compared the change of the cerebral ventricle volume, we performed the brain MRI for the 32 normal control (NC) group. The volumetric analysis for a specific cerebral ventricle performed by using Freesurfer Ver. 5.1 (Massachusetts general Hospital, Boston MA, USA). As a results, compared to the PD-NC group, the PD-MCI group were statistically significant reduction in the ability to perform the memory and the visuospatial function (p<0.05). The volumetric changes for a specific cerebral ventricle were statistically significant variation in the left and right lateral ventricle, left and right inferior lateral ventricle, and 3rd ventricle. Although, in order to compared the objectification, the normalized percentage applied to the volumetric changes showed to extend the PD-MCI group than the PD-NC group. Specially, the left and right ventricle extension for the PD-MCI patients conspicuously had showed a quantitative linear relationship between the memory and the visuospatial function for the SNSB (r>0.5, p<0.05). Therefore, we were able to judge the diagnostic criteria of the PD-MCI through that can observe the volumetric variation of the specific cerebral ventricle by using Freesurfer in brain MRI, and to analyze the correlation between the SNSB.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.58 no.3
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• pp.301-307
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• 2013

This study was evaluated high end research grade Near Infrared Reflectance Spectrophotometer (NIRS) to field grade multiple Near Infrared Reflectance Spectrophotometer (NIRS) for rapid analysis at fresh rice leaf at sight with 238 samples of fresh rice leaf during year 2012, collected Jeollabuk-do for evaluate accuracy and precision between instruments. Firstly collected and build database high end research grade NIRS using with 400 nm ~ 2500 nm during from year 2003 to year 2009, seven years collected fresh rice leaf database then trim and fit to field grade NIRS with 1200 nm ~ 2400 nm then build and create calibration, transfer calibration with special transfer algorithm. The result between instruments was 0.005% differences, rapidly analysis for chemical constituents, Total nitrogen in fresh rice leaf within 5 minutes at sight and the result equivalent with laboratory data. Nevertheless last during more than 8 years collected samples for build calibration was organic samples that make differentiate by local or yearly bases etc. This strongly suggest population evaluation technique needed and constantly update calibration and maintenance calibration to proper handling database accumulation and spread out by knowledgable control laboratory analysis and reflect calibration update such as powerful control center needed for long lasting usage of fresh rice leaf analysis with NIRS at sight. Especially the agriculture products such as rice will continuously changes that made easily find out the changes and update routinely, if not near future NIRS was worthless due to those changes. Many research related NIRS was shortly study not long term study that made not well using NIRS, so the system needed check simple and instantly using with local language supported signal methods global distance (GD) and neighbour distance (ND) algorithm. Finally the multiple popular field grades instruments should be the same results not only between research grade instruments but also between multiple field grade instruments that needed easily transfer calibration and maintenance between instruments via internet networking techniques.

• Journal of Oral Medicine and Pain
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• v.31 no.1
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• pp.59-67
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• 2006

There exist patients complaining speech problem due to dysesthesia or anesthesia following dental surgical procedure accompanied by local anesthesia in clinical setting. However, it is not clear whether sensory problems in orofacial region may have an influence on motor speech abilities. The purpose of this study was to investigate whether transitory sensory impairment of mandibular nerve by local anesthesia may influence on the motor speech abilities and thus to evaluate possibility of distorted motor speech abilities due to dysesthesia of mandibular nerve. The subjects in this study consisted of 7 men and 3 women, whose right inferior alveolar nerve, lingual nerve and long buccal nerve was anesthetized by 1.8 mL lidocaine containing 1:100,000 epinephrine. All the subjects were instructed to self estimate degree of anesthesia on the affected region and speech discomfort with VAS before anesthesia, 30 seconds, 30, 60, 90, 120 and 150 minutes after anesthesia. In order to evaluate speech problems objectively, the words and sentences suggested to be read for testing speech speed, diadochokinetic rate, intonation, tremor and articulation were recorded according to the time and evaluated using a Computerized Speech $Lab^{(R)}$. Articulation was evaluated by a speech language clinician. The results of this study indicated that subjective discomfort of speech and depth of anesthesia was increased with time until 60 minutes after anesthesia and then decreased. Degree of subjective speech discomfort was correlated with depth of anesthesia self estimated by each subject. On the while, there was no significant difference in objective assessment item including speech speed, diadochokinetic rate, intonation and tremor. There was no change in articulation related with anesthesia. Based on the results of this study, it is not thought that sensory impairment of unilateral mandibular nerve deteriorates motor speech abilities in spite of individual's complaint of speech discomfort.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.63-88
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• 2019

The goal of this paper is to investigate changes in North Korea's domestic and foreign policies through automated text analysis over North Korea represented in South Korean mass media. Based on that data, we then analyze the status of text mining research, using a text mining technique to find the topics, methods, and trends of text mining research. We also investigate the characteristics and method of analysis of the text mining techniques, confirmed by analysis of the data. In this study, R program was used to apply the text mining technique. R program is free software for statistical computing and graphics. Also, Text mining methods allow to highlight the most frequently used keywords in a paragraph of texts. One can create a word cloud, also referred as text cloud or tag cloud. This study proposes a procedure to find meaningful tendencies based on a combination of word cloud, and co-occurrence networks. This study aims to more objectively explore the images of North Korea represented in South Korean newspapers by quantitatively reviewing the patterns of language use related to North Korea from 2016. 11. 1 to 2019. 5. 23 newspaper big data. In this study, we divided into three periods considering recent inter - Korean relations. Before January 1, 2018, it was set as a Before Phase of Peace Building. From January 1, 2018 to February 24, 2019, we have set up a Peace Building Phase. The New Year's message of Kim Jong-un and the Olympics of Pyeong Chang formed an atmosphere of peace on the Korean peninsula. After the Hanoi Pease summit, the third period was the silence of the relationship between North Korea and the United States. Therefore, it was called Depression Phase of Peace Building. This study analyzes news articles related to North Korea of the Korea Press Foundation database(www.bigkinds.or.kr) through text mining, to investigate characteristics of the Kim Jong-un regime's South Korea policy and unification discourse. The main results of this study show that trends in the North Korean national policy agenda can be discovered based on clustering and visualization algorithms. In particular, it examines the changes in the international circumstances, domestic conflicts, the living conditions of North Korea, the South's Aid project for the North, the conflicts of the two Koreas, North Korean nuclear issue, and the North Korean refugee problem through the co-occurrence word analysis. It also offers an analysis of South Korean mentality toward North Korea in terms of the semantic prosody. In the Before Phase of Peace Building, the results of the analysis showed the order of 'Missiles', 'North Korea Nuclear', 'Diplomacy', 'Unification', and ' South-North Korean'. The results of Peace Building Phase are extracted the order of 'Panmunjom', 'Unification', 'North Korea Nuclear', 'Diplomacy', and 'Military'. The results of Depression Phase of Peace Building derived the order of 'North Korea Nuclear', 'North and South Korea', 'Missile', 'State Department', and 'International'. There are 16 words adopted in all three periods. The order is as follows: 'missile', 'North Korea Nuclear', 'Diplomacy', 'Unification', 'North and South Korea', 'Military', 'Kaesong Industrial Complex', 'Defense', 'Sanctions', 'Denuclearization', 'Peace', 'Exchange and Cooperation', and 'South Korea'. We expect that the results of this study will contribute to analyze the trends of news content of North Korea associated with North Korea's provocations. And future research on North Korean trends will be conducted based on the results of this study. We will continue to study the model development for North Korea risk measurement that can anticipate and respond to North Korea's behavior in advance. We expect that the text mining analysis method and the scientific data analysis technique will be applied to North Korea and unification research field. Through these academic studies, I hope to see a lot of studies that make important contributions to the nation.

• Journal of Science Education
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• v.45 no.3
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• pp.292-303
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• 2021

This study identifies the terms frequently used together with energy in online science news articles and topics of the news reports to find out how the term energy is used in everyday life and to draw implications for science curriculum and instruction about energy. A total of 2,171 online news articles in science category published by 11 major newspaper companies in Korea for one year from March 1, 2018 were selected by using energy as a search term. As a result of natural language processing, a total of 51,224 sentences consisting of 507,901 words were compiled for analysis. Using the R program, term frequency analysis, semantic network analysis, and structural topic modeling were performed. The results show that the terms with exceptionally high frequencies were technology, research, and development, which reflected the characteristics of news articles that report new findings. On the other hand, terms used more than once per two articles were industry-related terms (industry, product, system, production, market) and terms that were sufficiently expected as energy-related terms such as 'electricity' and 'environment.' Meanwhile, 'sun', 'heat', 'temperature', and 'power generation', which are frequently used in energy-related science classes, also appeared as terms belonging to the highest frequency. From a network analysis, two clusters were found including terms related to industry and technology and terms related to basic science and research. From the analysis of terms paired with energy, it was also found that terms related to the use of energy such as 'energy efficiency,' 'energy saving,' and 'energy consumption' were the most frequently used. Out of 16 topics found, four contexts of energy were drawn including 'high-tech industry,' 'industry,' 'basic science,' and 'environment and health.' The results suggest that the introduction of the concept of energy degradation as a starting point for energy classes can be effective. It also shows the need to introduce high-tech industries or the context of environment and health into energy learning.