The increasing concern over radiation exposure in the nuclear industry has fostered agrressive efforts to reduce the levels of radiation exposure. One area of the effot to reduce the radiation exposure is the development of a remote radiation monitoring system. Remote radiation monitoring can serve many benificaial functions reduce exposure to radiation by plant personnel, impruve the quality of the data that is collected and recognize the radiation environment easily. Radiation mapping system gives a good information that represents radiation level distribution. The system we have developed consists of a data acquistion parts, mobile robot and remote control parts. Data acquisition parts consist of radiation detection module and vision acquistion module which collect radiation data, visiion data and distance information. In remote control parts, the acquision data are processed and displayed. We have constructed radiation mapping image by overlaying the vision and radiation data. The radiation mapping techniques for displaying the results of the survey in an easily comprehendable form will facilitate a better understanding of the radiation environment in the facility. This system can reduce workers radiation exposure and aid to help work plan, so it has significant benifits in cost and safety.
This study aimed to investigate protective factors and risk factors in elementary students' life satisfaction. Participants were 2844 (1524 boys, 1320 girls) children who grades were 4th, 5th, 6th in KYPS (Korea Youth Panel Survey). Data mining decision tree model was performed with sex, appearance, delinquency, family income, attachment to parents, parental monitoring, attachment to teachers, academic achievement, peer delinquency, and attachments to peer. The results revealed that : (1) For 4th graders, academic achievement, attachment to parents, and appearance were significant predictors for life satisfaction. (2) For 5th graders, attachment to parents, academic achievement, parental monitoring and appearance were significant predictors for life satisfaction. (3) For 6th graders, attachment to parents, appearance, parental monitoring and delinquency were significant predictors for life satisfaction. Protective factors and risk factors were changed according to interactions between significant independent variables. These results suggest that children's diverse conditions should be considered individually in programs for children's life satisfaction.
Journal of the Korean Institute of Educational Facilities
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v.16
no.5
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pp.3-10
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2009
The purpose of this study is to provide an remodification method for elementary school complex facilities in Seoul Metropolitan city. This study analyzes the questionnaire survey for 568 entire elementary schools and the questionnaire survey for school facility complex project operated 44 elementary schools. Then the result of this study was deduced from the comparison between the 568 entire survey data and 44 survey data in terms of the cognition of school facility complex project, the required type of facility and the problems of complex facility maintenance and operation. Four major findings were revealed as the result of research. First, there is a very high agreement with the school facility complex projects. Second, it was need that the process of planning and design was remodified to enhance participation of parents of students and local residents for selecting an appropriate complex facility. Third, education environment and student safety should be protected from any other school facility complex environments. Fourth, an agreement and regulation is needed for more effective maintenance and operation of school complex facilities.
This paper reports the Survey results from a field monitoring study of office occupancy densities. The field measurement of a office in Yongin was carried out from 19 September to 30 September 2011. The survey has an aim to reveal the building energy consumption relationship between occupancy densities of a realistic office and the previous studies. The results showed that hourly occupied density of the previous studies is more higher than a field survey. we investigated the effects of difference occupancy densities on annual heating and cooling energy consumption using EnergyPlus. Heating and cooling consumption was raised because of the increased occupancy density. therefore, accurately measure the occupnacy schedule is important in order to reduce excessive building energy consumption, and is an significant element to be considered in the energy simulation.
Birds are effective ecological indicators but there is no national protocol in place to monitor population dynamics of forest birds in Korea. To support the establishment of future monitoring protocols, we compared the results of two generally used monitoring methods for forest bird surveys in two temperate mixed forests in central Korea. There was no statistical difference in the number of species and individuals detected per unit survey effort when comparing line transects and point counts. The number of species and individuals were higher in a five-minute count than in a three-minute point count, but the total accumulated number of expected observed species showed no difference between the two count durations. The number of observed species and individuals increased in both methods as plot radius or transect width increased, suggesting that multi-layer or multi-band surveys may be useful for quantitative and qualitative objectives. The decreasing number of observed species and individuals after sunrise suggested that bird monitoring should be conducted earlier in the morning, within four hours after sunrise. To detect 70% of the total number of species, 7.0 to 7.6 survey hours, equivalent to 42 three-minute counts (95% confidence interval [CI]: 26 to 61) or 33 five-minute counts (95% CI: 19 to 53) were needed for unlimited radius point counts. On the other hand, 4.8 survey hours, equivalent to 26 line transect counts (95% CI: 15 to 45) using 200-m transects with unlimited width, were required to achieve the same level of species detection. Therefore, the line transect method may be more effective than the point count method, at least in terms of local species richness assessment. For national forest bird monitoring, our data indicated that one or both survey methods can be selected as a basic protocol, based on the goals and scales of monitoring, forest types, and the conditions of the target areas.
Sea ice currently covers approximately 7% of the world's ocean area, primarily concentrated in polar and high-altitude regions, subject to seasonal and annual variations. It is very important to analyze the area and type classification of sea ice through time series monitoring because sea ice is formed in various types on a large spatial scale, and oil and gas exploration and other marine activities are rapidly increasing. Currently, research on the type and area of sea ice is being conducted based on high-resolution satellite images and field measurement data, but there is a limit to sea ice monitoring by acquiring field measurement data. High-resolution optical satellite images can visually detect and identify types of sea ice in a wide range and can compensate for gaps in sea ice monitoring using Geostationary Ocean Color Imager-II (GOCI-II), an ocean satellite with short time resolution. This study tried to find out the possibility of utilizing sea ice monitoring by training a rule-based machine learning model based on learning data produced using high-resolution optical satellite images and performing detection on GOCI-II images. Learning materials were extracted from Liaodong Bay in the Bohai Sea from 2021 to 2022, and a Random Forest (RF) model using GOCI-II was constructed to compare qualitative and quantitative with sea ice areas obtained from existing normalized difference snow index (NDSI) based and high-resolution satellite images. Unlike NDSI index-based results, which underestimated the sea ice area, this study detected relatively detailed sea ice areas and confirmed that sea ice can be classified by type, enabling sea ice monitoring. If the accuracy of the detection model is improved through the construction of continuous learning materials and influencing factors on sea ice formation in the future, it is expected that it can be used in the field of sea ice monitoring in high-altitude ocean areas.
The following research analyzes that the level of self-monitoring have an influence on user experience about website. For this research, university students participated in a survey where they evaluated user experience -usability, aesthetics, pleasure- about the new screen images of two homepages of differences in brand recognizability. The "self-monitoring(high/low, except for middle)" and the "brand recognizability(high/low, except for middle)" were set as independent variables and the "usability | deviation |", the "aesthetics | deviation |", the "pleasure | deviation |" were set as the dependent variables. Results, as with new screen images of homepage, there were significant differences in the usability and aesthetics based on the level in self-monitoring. Especially, when level of brand recognizability is low, there was more differences in the usability and aesthetics based on the level in self-monitoring. However, the influence of pleasure on self-monitoring was insignificant.
The study of the validity test on the self-monitoring scale for nurses In this study, both the literary survey as well as empirical research has been executed to test the validity of the scales that measure the construct of the self-monitoring scale. The self-monitoring scale could not be classified into five factors as Snyder suggested. Many other scholars (Briggs, Cheek and Buss, 1980) suggested 3 different classifications which was accepted by Snyder and Gangestad (1986). John, Cheek and Klohnen(1996) claimed a two-factor classification. As has been discussed, factor analysis is used to prove convergent validity within the factor and discriminant validity between the factors. However, depending on the researchers, many variations in classification of the factors were found and a lack of content and discriminant validity were found in the previous research findings. It is also important to note that Snyder's self-monitoring scale did not factor-load at over. 30 for all 25 items, regardless of how many factors could be classified. According to findings of this study, the self-monitoring scale neither classified as five, three or two factors nor factor loaded as hypothesized. It is also clear that Snyder's self-monitoring scale lacks convergent validity as the sub-factors of the scale failed to prove its uni-dimensionality. The A self-monit oring scale not only fail to overcome the problems of Snyder's self-monitori ng scale but even lost the attractiveness of the self-monitoring scale. In this study it was also found that the A self-monitoring scale was not classified in either in a two or three-factor classification as hypothesized. It is, of course, not desirable to use any scale that lacks convergent and discriminant validity even though it has been widely used and has held a great deal of influence on the field of social psychology. To overcome the shortcomings of Snyder's self-monitoring scale, Lennox and Wolfe(1984) suggested 13 items. This study was dedicated to test the validity and reliability of the scale, in which we found that the data presented in validity as the two factors were class ified and loaded as expected. Reliability was also proven by checking Cronbach's α for each factor and for the total items. In addition, a confirmatory factor analysis was executed for the 13 items using LISREL 8.12 program to confirm convergent validity in a two-factor classification. The model was fitting and sound : however, the self-monitoring scale was unfitted and not validated. Thus, it is recommended to use not the original nor the abbreviated self-monitoring scale but the 13 items in future studies. It should also be noted that items 7 and 13 should be removed to obtain better uni-dimensionality for the 13 items. These items loaded at over. 30, too high for the two factors in the test results of Factor analysis. In addition, it is necessary to double-check the cause of two-hold loading at over .30 for the two factors. It could be a problem caused by data or by the scale itself. Therefore, additional studies should follow to better clarify this matter.
Purpose: This study is to contribute to the development of monitoring technology through the increase of confidence in construction monitoring by deriving the analysis of construction monitoring cost and improvement measures of railway tunnel construction in Seoul. Method: It presents the status on design and contract of construction monitoring cost, status on application construction monitoring cost and its analysis, analysis on safety management cost and quality management cost, expansion of application of the price calculation standard for monitoring management services to improve this, and monitoring for direct order of ordering organization. Results: If the monitoring management service that was meanwhile ordered as included in the construction work is performed by the directly selected company of ordering organization through the preliminary screening for bidding qualification, then the improvement of monitoring quality and the accurate monitoring data can be secured. Conclusion: For the price calculation standard for monitoring management service, the application of actual cost addition method under the Engineering Promotion Act and the calculation standard of monitoring management cost for standard estimation for ground survey should be extended through the direct order of ordering organization, not the method to be included in the net construction cost where it is performed by a subcontractor via contractor.
Park, Sangchul;Park, Yeongbin;Jang, Soyeong;Kim, Tae-Ho
Korean Journal of Remote Sensing
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v.38
no.6_1
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pp.1463-1478
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2022
Maritime transport accounts for 99.7% of the exports and imports of the Republic of Korea; therefore, developing a vessel monitoring system for efficient operation is of significant interest. Several studies have focused on tracking and monitoring vessel movements based on automatic identification system (AIS) data; however, ships without AIS have limited monitoring and tracking ability. High-resolution optical satellite images can provide the missing layer of information in AIS-based monitoring systems because they can identify non-AIS vessels and small ships over a wide range. Therefore, it is necessary to investigate vessel monitoring and small vessel classification systems using high-resolution optical satellite images. This study examined the possibility of developing ship monitoring systems using Compact Advanced Satellite 500-1 (CAS500-1) satellite images by first training a deep learning model using satellite image data and then performing detection in other images. To determine the effectiveness of the proposed method, the learning data was acquired from ships in the Yellow Sea and its major ports, and the detection model was established using the You Only Look Once (YOLO) algorithm. The ship detection performance was evaluated for a domestic and an international port. The results obtained using the detection model in ships in the anchorage and berth areas were compared with the ship classification information obtained using AIS, and an accuracy of 85.5% and 70% was achieved using domestic and international classification models, respectively. The results indicate that high-resolution satellite images can be used in mooring ships for vessel monitoring. The developed approach can potentially be used in vessel tracking and monitoring systems at major ports around the world if the accuracy of the detection model is improved through continuous learning data construction.
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