• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1285-1300
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• 2022

Turbidity, the measure of the cloudiness of water, is used as an important index for water quality management. The turbidity can vary greatly in small river systems, which affects water quality in national rivers. Therefore, the generation of high-resolution spatial information on turbidity is very important. In this study, a turbidity retrieval model using the Korea Multi-Purpose Satellite-3 and -3A (KOMPSAT-3/3A) images was developed for high-resolution turbidity mapping of Han River system based on eXtreme Gradient Boosting (XGBoost) algorithm. To this end, the top of atmosphere (TOA) spectral reflectance was calculated from a total of 24 KOMPSAT-3/3A images and 150 Landsat-8 images. The Landsat-8 TOA spectral reflectance was cross-calibrated to the KOMPSAT-3/3A bands. The turbidity measured by the National Water Quality Monitoring Network was used as a reference dataset, and as input variables, the TOA spectral reflectance at the locations of in situ turbidity measurement, the spectral indices (the normalized difference vegetation index, normalized difference water index, and normalized difference turbidity index), and the Moderate Resolution Imaging Spectroradiometer (MODIS)-derived atmospheric products(the atmospheric optical thickness, water vapor, and ozone) were used. Furthermore, by analyzing the KOMPSAT-3/3A TOA spectral reflectance of different turbidities, a new spectral index, new normalized difference turbidity index (nNDTI), was proposed, and it was added as an input variable to the turbidity retrieval model. The XGBoost model showed excellent performance for the retrieval of turbidity with a root mean square error (RMSE) of 2.70 NTU and a normalized RMSE (NRMSE) of 14.70% compared to in situ turbidity, in which the nNDTI proposed in this study was used as the most important variable. The developed turbidity retrieval model was applied to the KOMPSAT-3/3A images to map high-resolution river turbidity, and it was possible to analyze the spatiotemporal variations of turbidity. Through this study, we could confirm that the KOMPSAT-3/3A images are very useful for retrieving high-resolution and accurate spatial information on the river turbidity.

• Tuberculosis and Respiratory Diseases
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• v.40 no.3
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• pp.267-273
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• 1993

Background: Panting method for airway resistance measurement has the disadvantages of departing from the normal breathing pattern and of difficult for some patients to perform. We can measure airway resistance during quiet breathing under more physiologic conditions. Airway resistance is often measured during panting but attempts have been made to facilitate resistance measurements during quiet breathing. This study was designed to compare airway resistance measurements during panting with those during quiet breathing. Method: The 24 normal persons and 29 pulmonary disease patients were included in this study. Spirometry was performed and airway resistance measurement was also done during panting and quiet breathing concomittently. Results: The results were as follows; 1) High correlations were found between airway resistance measurements during panting and quiet breathing. 2) Resistance fell during panting, 21.2% in Raw tot, and 22.1% in Raw 0.5. 3) In normal persons, airway resistance fell more during panting when comparing to those in pulmonary disease patients. 4) This was largely independent of thoracic gas volume differences, because the specific airway conductance rose significantly during panting 5) The patients in whom resistance didn't fell during panting was supposed to the patients who couldn't perform panting successively because of high resistance. Conclusions: Although airway resistance can be measured during panting or quiet breathing according to the patient's performance, we must consider resistance fell during panting, by a mean 20%. It may be concluded that quiet breathing is more likely than panting to provide a relevant measurement of airway resistance.

• Journal of the korean academy of Pediatric Dentistry
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• v.28 no.3
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• pp.441-446
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• 2001

Flumazenil is a competitive antagonist of benzodiazepines. It is usually administered intravenously. However, if the intravenous route is not available then other routes of drug administration should be considered. This study was designed to evaluate the reversal effects of flumazenil after nasal administration. Twenty-five young, healthy adult volunteers participated in this clinical trial. The dosage of 0.08mg/kg midazolam was administered intravenously to induce deep sedation. Ten minutes after midazolam administration, 0.5mg of flumazenil was dropped nasally, over a period of one minute. Blood samples were taken to measure the concentration of midazolam and flumazenil at 0, 5, 10, and 20min after nasal administration of flumazenil, using High Performance Liquid Chromatography. The degree of sedation was evaluated with sedation score and bispectral index (BIS), Statistical analysis was performed by multivariate ANOVA and correlation analysis (P<0.05). Peak serum flumazenil concentration was reached in 10min. Sedation score decreased after midazolam administration and showed a significant increase after flumazenil administration. However, BIS decreased during the first 10min after midazolam administration and then no significant changes after flumazenil administration. There were two instances representing rapid and complete reversal of midazolam after intranasal administration of flumazenil. In conclusion, intranasal flumazenil administration may be effective in some patients when intravenous route is not available in condition of benzodiazepine overdose.

• Journal of dental hygiene science
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• v.13 no.4
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• pp.493-500
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• 2013

The study aims to determine the status of oral health of mental illness patients and establish the preliminary data. The examinations and questionnaire survey were done 92 psychiatric patients to measure sociodemographic characteristics, decayed, missing and filled teeth (DMFT) index, patient hygiene performance (PHP) index, community periodontal index of treatment need (CPITN). Result of the missing teeth index in the state of oral health was higher in the hospital group (6.42) while the filled teeth index was higher in the center group (4.78). In the DMFT index, mental illness patients were higher than the national sample. The oral health status of medical aid recipients was poorer as the subjects were older and less educated (p<0.05). The PHP index was 3.41, close to the bad oral hygiene state. The hospital group (81.7%) required higher need for periodontal treatment. The periodontal health state was much poorer especially when the subject was in the age of 40's and 60's, received less education, and had no family (p<0.05). $CPITN_3$ was higher in the hospital group (13.3%) than the national sample (5.7%). The mental illness patients were socially vulnerable, therefore oral health care program should be needed and age, education level, health insurance type, presence of family and other factors needs to be considered in this approach.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.14 no.3
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• pp.73-84
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• 2019

Despite decades of work experience, workers at small- and medium-sized enterprises(SME) here have yet to make inroads into the self-employed sector that utilizes the job competency they have accumulated at work after retirement. Unlike large companies, SME do not have a proper system for improving the long-term job competency of their employees as they focus on their immediate performance. It is necessary to analyse the independent variables affecting the job competency of employees of SME to derive practical implications for the personnel of SME. In the preceding studies, there are independent variable analyses that affect job competency in specialized industries, such as health care, public officials and IT, but the analysis of workers at SME is insufficient. This study set the person-job fit and organizational justice based on the prior studies of the independent variables that affect the job competency of SME general workers as a dependent variable. The sub-variables of each variable derived knowledge, skills, experience, and desire for person-job fit, and distribution, procedural and deployment justice for organizational justice, respectively. The survey of employees of SME in Korea was conducted from February to March 2019 by Likert 5 scales, and the survey was retrieved from 323 people and analyzed in a demonstration using the SPSS and AMOS statistics package. Among the four sub-independent variables of person-job fit, knowledge, skills and experience were shown to have a significant impact on the job competency, and desire was not shown to be so. Among the three sub-independent variables of organizational justice, deployment justice has a significant impact on job competency, but distribution and procedural justices have not. Personnel managers of SME need to improve the job competency of their employees by appropriately utilizing independent variables such as knowledge, skills, experience and deployment at each stage, including recruitment, deployment, and promotion. Future job competency modeling studies are needed to overcome the limitations of this study, which fails to objectively measure job competency.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.spc
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• pp.30-36
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• 2022

A sensor is needed to continuously and automatically measure the change in HNS concentration in industrial facilities that directly discharge to the sea after water treatment. The basic function of the sensor is to be able to detect ppb levels even at room temperature. Therefore, a method for increasing the sensitivity of the existing sensor is proposed. First, a method for increasing the conductivity of a film using a conductive carbon-based additive in a nanoparticle thin film and a method for increasing ion adsorption on the surface using a catalyst metal were studied.. To improve conductivity, carbon black was selected as an additive in the film using ITO nanoparticles, and the performance change of the sensor according to the content of the additive was observed. As a result, the change in resistance and response time due to the increase in conductivity at a CB content of 5 wt% could be observed, and notably, the lower limit of detection was lowered to about 250 ppb in an experiment with organic solvents. In addition, to increase the degree of ion adsorption in the liquid, an experiment was conducted using a sample in which a surface catalyst layer was formed by sputtering Au. Notably, the response of the sensor increased by more than 20% and the average lower limit of detection was lowered to 61 ppm. This result confirmed that the chemical resistance sensor using metal oxide nanoparticles could detect HNS of several tens of ppb even at room temperature.

• Journal of Venture Innovation
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• v.4 no.2
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• pp.57-75
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• 2021

KHNP's shared growth activities are based on such public good. Reflecting the characteristics of a comprehensive energy company, a high-tech plant company, and a leading company for shared growth, it presents strategies to link performance indicators with its partners and implements various measures. Key tasks include maintaining the nuclear power plant ecosystem, improving management conditions for partner companies, strengthening future capabilities of the nuclear power plant industry, and supporting a virtuous cycle of regional development. This is made by reflecting the specificity of nuclear power generation as much as possible, and is designed to reflect the spirit of shared growth through win-win and cooperation in order to solve the challenges of the times while considering the characteristics as much as possible as possible. KHNP's shared growth activities can be said to be the practice of the spirit of the times(Zeitgeist). The spirit of the times given to us now is that companies should strive for sustainable growth as social air. KHNP has been striving to establish a creative and leading shared growth ecosystem. In particular, considering the positions of partners, it has been promoting continuous system improvement to establish a fair trade culture and deregulation. In addition, it has continuously discovered and implemented new customized support projects that are effective for partner companies and local communities. To this end, efforts have been made for shared growth through organic collaboration with partners and stakeholders. As detailed tasks, it also presents fostering new markets and new industries, maintaining supply chains, and emergency support for COVID-19 to maintain the nuclear power plant ecosystem. This reflects the social public good after the recent COVID-19 incident. In order to improve the management conditions of partner companies, productivity improvement, human resources enhancement, and customized funding are being implemented as detailed tasks. This is a plan to practice win-win growth with partner companies emphasized by corporate social responsibility (CSR) and ISO 26000 while being faithful to the main job. Until now, ESG management has focused on the environmental field to cope with the catastrophe of climate change. According to KHNP is presenting a public enterprise-type model in the environmental field. In order to strengthen the future capabilities of the nuclear power plant industry as a state-of-the-art energy company, it has set tasks to attract investment from partner companies, localization and new technologies R&D, and commercialization of innovative technologies. This is an effort to develop advanced nuclear power plant technology as a concrete practical measure of eco-friendly development. Meanwhile, the EU is preparing a social taxonomy to focus on the social sector, another important axis in ESG management, following the Green Taxonomy, a classification system in the environmental sector. KHNP includes enhancing local vitality, increasing income for the underprivileged, and overcoming the COVID-19 crisis as part of its shared growth activities, which is a representative social taxonomy field. The draft social taxonomy being promoted by the EU was announced in July, and the contents promoted by KHNP are consistent with this, leading the practice of social taxonomy

• Asian-Australasian Journal of Animal Sciences
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• v.28 no.12
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• pp.1696-1702
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• 2015

The objective of this study was to compare the effects of body weight growth adjustment methods on genetic parameters of body growth and tissue among three pig breeds. Data collected on 101,820 Landrace, 281,411 Yorkshire, and 78,068 Duroc pigs, born in Korean swine breeder farms since 2000, were analyzed. Records included body weights on test day and amplitude (A)-mode ultrasound carcass measures of backfat thickness (BF), eye muscle area (EMA), and retail cut percentage (RCP). Days to 90 kg body weight (DAYS90), through an adjustment of the age based on the body weight at the test day, were obtained. Ultrasound measures were also pre-adjusted (ABF, EMA, AEMA, ARCP) based on their test day measures. The (co)variance components were obtained with 3 multi-trait animal models using the REMLF90 software package. Model I included DAYS90 and ultrasound traits, whereas model II and III accounted DAYS90 and pre-adjusted ultrasound traits. Fixed factors were sex (sex) and contemporary groups (herd-year-month of birth) for all traits among the models. Additionally, model I and II considered a linear covariate of final weight on the ultrasound measure traits. Heritability ($h^2$) estimates for DAYS90, BF, EMA, and RCP ranged from 0.36 to 0.42, 0.34 to 0.43, 0.20 to 0.22, and 0.39 to 0.45, respectively, among the models. The $h^2$ estimates of DAYS90 from model II and III were also somewhat similar. The $h^2$ for ABF, AEMA, and ARCP were 0.35 to 0.44, 0.20 to 0.25, and 0.41 to 0.46, respectively. Our heritability estimates varied mostly among the breeds. The genetic correlations ($r_G$) were moderately negative between DAYS90 and BF (-0.29 to -0.38), and between DAYS90 and EMA (-0.16 to -0.26). BF had strong $r_G$ with RCP (-0.87 to -0.93). Moderately positive $r_G$ existed between DAYS90 and RCP (0.20 to 0.28) and between EMA and RCP (0.35 to 0.44) among the breeds. For DAYS90, model II and III, its correlations with ABF, AEMA, and ARCP were mostly low or negligible except the $r_G$ between DAYS90 and AEMA from model III (0.27 to 0.30). The $r_G$ between AEMA and ABF and between AEMA and ARCP were moderate but with negative and positive signs, respectively; also reflected influence of pre-adjustments. However, the $r_G$ between BF and RCP remained non-influential to trait pre-adjustments or covariable fits. Therefore, we conclude that ultrasound measures taken at a body weight of about 90 kg as the test final should be adjusted for body weight growth. Our adjustment formulas, particularly those for BF and EMA, should be revised further to accommodate the added variation due to different performance testing endpoints with regard to differential growth in body composition.

• Journal of Intelligence and Information Systems
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• v.18 no.2
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• pp.47-60
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• 2012

Video data comes in the form of the unstructured and the complex structure. As the importance of efficient management and retrieval for video data increases, studies on the video parsing based on the visual features contained in the video contents are researched to reconstruct video data as the meaningful structure. The early studies on video parsing are focused on splitting video data into shots, but detecting the shot boundary defined with the physical boundary does not cosider the semantic association of video data. Recently, studies on structuralizing video shots having the semantic association to the video scene defined with the semantic boundary by utilizing clustering methods are actively progressed. Previous studies on detecting the video scene try to detect video scenes by utilizing clustering algorithms based on the similarity measure between video shots mainly depended on color features. However, the correct identification of a video shot or scene and the detection of the gradual transitions such as dissolve, fade and wipe are difficult because color features of video data contain a noise and are abruptly changed due to the intervention of an unexpected object. In this paper, to solve these problems, we propose the Scene Detector by using Color histogram, corner Edge and Object color histogram (SDCEO) that clusters similar shots organizing same event based on visual features including the color histogram, the corner edge and the object color histogram to detect video scenes. The SDCEO is worthy of notice in a sense that it uses the edge feature with the color feature, and as a result, it effectively detects the gradual transitions as well as the abrupt transitions. The SDCEO consists of the Shot Bound Identifier and the Video Scene Detector. The Shot Bound Identifier is comprised of the Color Histogram Analysis step and the Corner Edge Analysis step. In the Color Histogram Analysis step, SDCEO uses the color histogram feature to organizing shot boundaries. The color histogram, recording the percentage of each quantized color among all pixels in a frame, are chosen for their good performance, as also reported in other work of content-based image and video analysis. To organize shot boundaries, SDCEO joins associated sequential frames into shot boundaries by measuring the similarity of the color histogram between frames. In the Corner Edge Analysis step, SDCEO identifies the final shot boundaries by using the corner edge feature. SDCEO detect associated shot boundaries comparing the corner edge feature between the last frame of previous shot boundary and the first frame of next shot boundary. In the Key-frame Extraction step, SDCEO compares each frame with all frames and measures the similarity by using histogram euclidean distance, and then select the frame the most similar with all frames contained in same shot boundary as the key-frame. Video Scene Detector clusters associated shots organizing same event by utilizing the hierarchical agglomerative clustering method based on the visual features including the color histogram and the object color histogram. After detecting video scenes, SDCEO organizes final video scene by repetitive clustering until the simiarity distance between shot boundaries less than the threshold h. In this paper, we construct the prototype of SDCEO and experiments are carried out with the baseline data that are manually constructed, and the experimental results that the precision of shot boundary detection is 93.3% and the precision of video scene detection is 83.3% are satisfactory.

• Journal of Climate Change Research
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• v.5 no.2
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• pp.95-107
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• 2014

The 'Green Start Movement' is a practical movement of green living to efficiently reduce the greenhouse gases originating from non-industrial fields such as household, commerce, transportation, etc. for the 'materialization of a low carbon society through green growth (Low Carbon, Green Korea)'. When the new government took office, following the Lee Myeongbak Administration that had presented 'Low Carbon, Green Growth' as a national vision, it was required to set up the direction of the practical movement of green life to respond to climate change persistently and stably as well as to evaluate the performance of the green start movement over the past 5 years. A questionnaire survey was administered to a total of 265 persons including public servants, members of environmental and non-environmental NGOs, participants of the green start movement and professionals. In the results of the questionnaire survey, many opinions have indicated that the awareness of the green start movement is increasing and the green start movement has had a positive impact on individual behavior and group behavior in terms of green living. The result shows, however, that the environmental NGOs don't cooperate sufficiently to create a 'green living' effect on a national scale. Action needs to be taken on the community level in order to generate a culture of environmental responsibility. The national administration office of the Green Start Movement Network should play the leading role between the government and environmental NGOs. The Green Start National Network should have greater autonomy and governance of the network needs to be restructured in order to work effectively. Also the Green Start Movement should identify specific local characteristics to support activities that reduce greenhouse gas emissions. Best practices can be shared to reduce greenhouse gas emissions by a substantial amount.