• Korean Journal of Child Studies
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• v.24 no.3
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• pp.135-149
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• 2003

This study aimed to develop an observation scale for assessing the quality of day care programs and to examine reliability and validity of the scale. Instruments included 3 self-assessment scales, the Evaluation Scale for Early Childhood Programs and an observation scale completed by 8 trained observers in 89 day care sites. Item analysis indicated that most items were acceptable in terms of item discrimination and item response distribution. Cronbach ${\alpha}^{\prime}s$ and inter-observer reliability were relatively high. Validity of the scale was evidenced by correlations between the observation scale and the criterion measure and inter-correlations among sub-areas of the observation scale. Scores on the observation scale were validated by quality ratings from self-assessment scores.

• Korean Institute of Interior Design Journal
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• v.22 no.1
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• pp.174-182
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• 2013

This study divided the observation area in an indoor space for area setup to analyse the effect of the difference of design types on the characteristics of observation with the observed time of each area as objects. Though it is thought that the difference of design patterns may be influenced by the factors and material composing the space, no existing approaches have had any quantitatively measuring method. Eye-tracking could be efficiently utilized for observation analysis from the viewpoint of dating observation behavior. The followings are the results of analysing the observation characteristics depending on design pattern. First, 5 observing areas were set up according to concentration of observation time in order for the concentration by area to be examined and the factors of design having effect on the difference of observation patterns by design type could be analysed. Second, as a whole, the observation of modern types showed high observation characteristics. When the difference of observation characteristics by pattern was examined by difference at observation frequency, the observation frequency defined to be more than 50% was seen to be almost same from Area I to III and to get higher from Area IV, and that defined to be 30% was high at Areas III and IV. In Area V, it was very high at natural. Third, that of Area II is no more than 8.2% but had the most observation time. As for observation characteristics, the horizontal observation of the central part was the highest and had more observation frequency at modern type that at natural one. These observation characteristics by area enabled to analyse the observation tendency depending on design characters at relevant area. Fourth, the design factors composing natural type were found to bring more attention when the area showed higher concentration at natural type than at modern one. And the analysis of design factors could make it to be confirmed that the quality of material and background factors in addition to design factors in the area had more effect on sight concentration.

• Atmosphere
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• v.30 no.2
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• pp.169-181
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• 2020

We conducted a study on the impact of observation station density; this was done in order to enable the accurate estimation of spatial meteorological variables. The purpose of this study is to help operate an efficient observation network by examining distributions of temperature, relative humidity, and wind speed in a test area of a three-dimensional meteorological observation project in the Yeongdong region in 2019. For our analysis, we grouped the observation stations as follows: 41 stations (for Step 4), 34 stations (for Step 3), 17 stations (for Step 2), and 10 stations (for Step 1). Grid values were interpolated using the kriging method. We compared the spatial accuracy of the estimated meteorological grid by using station density. The effect of increased observation network density varied and was dependent on meteorological variables and weather conditions. The temperature is sufficient for the current weather observation network (featuring an average distance about 9.30 km between stations), and the relative humidity is sufficient when the average distance between stations is about 5.04 km. However, it is recommended that all observation networks, with an average distance of approximately 4.59 km between stations, be utilized for monitoring wind speed. In addition, this also enables the operation of an effective observation network through the classification of outliers.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.32 no.2
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• pp.135-145
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• 2020

Wave observation is widely used to direct observation method for observing the water surface elevation using wave buoy or pressure gauge and remote-sensing wave observation method. The wave buoy and pressure gauge can produce high-quality wave data but have disadvantages of the high risk of damage and loss of the instrument, and high maintenance cost in the offshore area. On the other hand, remote observation method such as radar is easy to maintain by installing the equipment on the land, but the accuracy is somewhat lower than the direct observation method. This study investigates the data quality of MIROS Wave and Current Radar (MWR) installed at Dokdo and improve the data quality of remote wave observation data using the wave buoy (CWB) observation data operated by the Korea Meteorological Administration. We applied and developed the three types of wave data quality control; 1) the combined use (Optimal Filter) of the filter designed by MIROS (Reduce Noise Frequency, Phillips Check, Energy Level Check), 2) Spike Test Algorithm (Spike Test) developed by OOI (Ocean Observatories Initiative) and 3) a new filter (H-Ts QC) using the significant wave height-period relationship. As a result, the wave observation data of MWR using three quality control have some reliability about the significant wave height. On the other hand, there are still some errors in the significant wave period, so improvements are required. Also, since the wave observation data of MWR is different somewhat from the CWB data in high waves of over 3 m, further research such as collection and analysis of long-term remote wave observation data and filter development is necessary.

• Journal of Environmental Science International
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• v.31 no.4
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• pp.329-339
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• 2022

Better understanding the mechanism of black ice occurrence on the road in winter is necessary to reduce the socio-economic damage it causes. In this study, intensive observations of road weather elements and surface information under the influence of synoptic high-pressure patterns (22^nd December, 2020 and 29^th January, and 25^th February, 2021) were carried out using a mobile observation vehicle. We found that temperature and road surface temperature change is significantly influenced by observation time, altitude and structure of the road, surrounding terrain, and traffic volume, especially in tunnels and bridges. In addition, even if the spatial distribution of temperature and road surface temperature for the entire observation route is similar, there is a difference between air and road surface temperatures due to the influence of current weather conditions. The observed road temperature, air temperature and air pressure in Nongong Bridge were significantly different to other fixed road weather observation points.

• Korean Journal of Child Studies
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• v.25 no.6
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• pp.225-240
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• 2004

Subjects were 15 teachers and 143 children at 15 child-care centers in Seoul that varied by quality of care. The Child Care Program Observation Scale(Rhee et at., 2003) was employed to observe the quality of the centers. Information on teachers' participation in play was collected by 20 units of observation for each teacher using a rating scale developed by the author. Children's behaviors were observed with time sampling method in 12 categories of play behaviors based on Social and Cognitive Play Scales(Rubin et al., 1978). Children's play behaviors varied by quality of child-care centers and teachers' participation in play. When child-care quality was high, teachers' participated actively in children's play and children showed developmentally appropriate play behaviors.

• Atmosphere
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• v.33 no.5
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• pp.561-570
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• 2023

In order to improve the predictability of marine high-impacts weather such as typhoon and high waves, the marine observation network is an essential because it could be rapidly changed by strong air-sea interaction. In this regard, the National Institute of Meteorological Sciences, Korea Meteorological Administration (NIMS/KMA) has promoted the Argo float observation program since 2001 to participate in the International Argo program. In this study, current status and future direction of the NIMS/KMA Argo program are presented through the internal meeting and external expert forum. To date, a total of 264 Argo floats have been deployed into the offshore around the Korean Peninsula and the Northwestern Pacific Ocean. The real-time and delayed modes quality control (QC) system of Argo data was developed, and an official regional data assembling center (call-sign 'KM') was run. In 2002, the Argo homepage was established for the systematic management and dissemination of Argo data for domestic and international users. The future goal of the NIMS/KMA Argo program is to improve response to the marine high-impacts weather through a marine environment monitoring and observing system. The promotion strategy for this is divided into four areas: strengthening policy communication, developing observation strategies, promoting utilization research, and activating international cooperation.

• Journal of Korean Society for Quality Management
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• v.28 no.3
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• pp.145-154
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• 2000

Effective management of knowledge is essential to keep up with demands of this challenging information age. The first step for this kind of management would be to define indicators to evaluate the quality of knowledge. In this paper, we use five latent variables (intrinsic quality, representational quality, ease of use of quality, maintainable quality, usage of quality) as basis for a preliminary path analysis for knowledge management. Preliminary study results showed that high intrinsic quality does not necessarily guarantee high frequency of use. A modified questionnaire is made and is used for SERVQUAL. The result of SERVQUAL shows that customers are not relatively happy about both intrinsic quality and its ease of use. Additional path analyses are done for both expected and observed quality indicators. The path model based on the expectation indicated that the presentation method of knowledge would induce its easy maintenance while that based on observation did not back up the same phenomenon.

• Korean Journal of Child Studies
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• v.20 no.2
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• pp.151-169
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• 1999

The purpose of this study was to investigate and evaluate quality of early childhood programs in day care centers. The subjects were 283 day care centers in Korea. Quality of early childhood programs was evaluated by observation and interview, using questionnaire. The results showed that the quality of early childhood programs was moderate. There were significant differences in quality of early childhood programs by type of day care center ; the level of early childhood programs in national and private centers was high than in family day care. Future directions were presented for quality day care.

• Journal of Korean Society of Water and Wastewater
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• v.34 no.1
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• pp.35-43
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• 2020

Turbidity has various effects on the water quality and ecosystem of a river. High turbidity during floods increases the operation cost of a drinking water supply system. Thus, the management of turbidity is essential for providing safe water to the public. There have been various efforts to estimate turbidity in river systems for proper management and early warning of high turbidity in the water supply process. Advanced data analysis technology using machine learning has been increasingly used in water quality management processes. Artificial neural networks(ANNs) is one of the first algorithms applied, where the overfitting of a model to observed data and vanishing gradient in the backpropagation process limit the wide application of ANNs in practice. In recent years, deep learning, which overcomes the limitations of ANNs, has been applied in water quality management. LSTM(Long-Short Term Memory) is one of novel deep learning algorithms that is widely used in the analysis of time series data. In this study, LSTM is used for the prediction of high turbidity(>30 NTU) in a river from the relationship of turbidity to discharge, which enables early warning of high turbidity in a drinking water supply system. The model showed 0.98, 0.99, 0.98 and 0.99 for precision, recall, F1-score and accuracy respectively, for the prediction of high turbidity in a river with 2 hour frequency data. The sensitivity of the model to the observation intervals of data is also compared with time periods of 2 hour, 8 hour, 1 day and 2 days. The model shows higher precision with shorter observation intervals, which underscores the importance of collecting high frequency data for better management of water resources in the future.