• Journal of Families and Better Life
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• v.34 no.5
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• pp.21-33
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• 2016

The purpose of this study is to explore the relative influence of psychological well-being and social support on the burnout of infant care teachers. Participants were 194 infant care teachers from 52 infant daycare centers in Gyeong-gi-do. Psychological burnout was assessed by the Maslach Burnout Inventory(Lee, 2011), psychological well-being was measured by the Psychological well-being scale(Cho & Cha, 2001) and social support was measured by the social support questionnaire(Bak, 1985). Date were analyzed using descriptive statistics and analysis, t-test, Pearson's correlation analysis, and multiple regression analysis. The major results of this study were as follows; First, there were differences in burnout in terms of marital status, work experiences, classroom operation type and income. Second, Infant care teachers' burnout was negatively correlated with psychological well-being and social support. Third, the most influential factor on infant care teachers' burnout was purpose in life, the second most influential factor was self-acceptance, the third most influential factor was emotional support, and the least influential factor was environmental mastery. Results of this study indicate that a psychological well-being enhancement program should be developed and emotional support from a social relationship network should be enhanced in order to prevent infant care teachers' burnout.

• Journal of Korea Society of Waste Management
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• v.35 no.8
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• pp.770-776
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• 2018

This study measured the energy recovery rate of each municipal waste incineration facility according to the revised energy recovery rate estimation method, which targeted four municipal waste incineration facilities (Unit No. 7). The results calculated by the measuring instruments were used for each factor to estimate the recovery rate, and the available potential of available energy was examined by analyzing the energy production and valid consumption. As a result of the low heating value, 2,540 kcal/kg was calculated on average when the LHVw formula was applied, which is approximately 116 kcal/kg higher than the average design standard of 2,424 kcal/kg. The energy recovery rate was calculated as 96.9% on average based on production and 67.5% based on effective consumption, and the analysis shows that approximately 29.4% energy can be used.

• Journal of Korean Society for Atmospheric Environment
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• v.26 no.6
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• pp.633-648
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• 2010

The study was performed to elucidate the characteristics of VOCs at distinct monitoring sites in urban atmosphere; one is at a roadside in downtown inland city of Jeonju, and the other is at an industrial site in Gunsan near coastal area. The ambient samples were collected for 24 hours in two-bed adsorbent tubes by using MTS-32 sequential tube sampler equipped with Flex air pump every 16 days in a roadside and a industrial complex from February to November in 2009. VOCs were determined by thermal desorption coupled with GC/MSD. Major individual VOCs in roadside samples were shown as following order in magnitude: toluene>m,p-xylene>ethyl benzene>decanal; and those in the industrial complex samples were as follows: toluene>ethanol>ethyl acetate>decanal>m,pxylene. High benzene concentration in the roadside was more frequently occurred than in the industrial complex. However ambient level of toluene in the industrial complex was higher than that in the road side. Results from roadside sample analysis showed that nonane and 1,2,4-trimethylbenzene were very frequently observed with higher concentrations than those in the industrial complex. It seems that nonane and 1,2,4-trimethylbenzene could be the source characteristics for the roadside air. From the diurnal variation, it was found that concentrations of benzene, ethylbenzene, xylene, nonane and 1,2,4-trimethylbenznene in the roadside were higher during rush hours; but those in the industrial complex were higher from 10 to 16 LST when the industrial activities were animated. On weekly base, the concentration of benzene, toluene, ethylbenzene and m,p-xylene in the roadside were higher specifically on Wednesday, but those in the industrial complex were higher on Sunday. It was found that the general trends of VOCs levels at both sites significantly influence on seasonal changes. The results of factor analysis showed that the VOCs in the roadside were mainly affected by the emission of vehicles and the evaporation of diesel fuel, meanwhile those in the industrial complex were influenced by the evaporation of solvents and vehicular emission.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.5
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• pp.1489-1504
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• 2014

This paper is aimed to suggest a site specific partial safety factor of offshore wind turbine (OWT) pile foundation design for the offshore wind turbine complex at a West-South mainland sea in Korea. International offshore wind design standards such as IEC, GL, DNV, API, ISO and EUROCODE were compared with each partial safety factor and resistance factor. Soil uncertainty analysis using a large number of soil data sampled was carried out, and their results were adapted to estimate partial safety factor of OWT pile foundation through reliability analyses. The representative partial safety factor has been estimated as 1.3. When a proposed partial factor is willing to use to other sites, it is recommended that further studies on code calibration are required to validate their accuracy using more site characterization data.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.37 no.1
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• pp.133-141
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• 2017

Traffic volume increases according to highway expansion and industrial development which causes repetitive defect and durability degradation on pavement. The research of quality assurance system used abroad has introduced Korea. Korea Expressway Corporation (KEC) has developed a Quality Performance Index (QPI) that quantitatively assesses the level of quality of the final product, and practical applications. Assessment factor on concrete pavement consisted of pavement thickness, compressive strength, IRI and spacing factor. Assessment factor on concrete pavement is determined by empirical evaluation factor from abroad. In this study, analysis of evaluation factors of concrete pavement by using pavement life prediction simulation and measured data were evaluated with consideration of feasibility of the assessment factor. Pavement life, performance and durability are affected by pavement thickness, compressive strength, IRI and spacing factor in assessment factor on concrete pavement, QPI.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.1D
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• pp.23-30
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• 2006

The variation in the traffic volume on any given roads is the reflection of its user's economic activities and life patterns. And traffic volume flows in every hour usually take different charateristics depending on the location and the function of the roads. This study produced the Monthly Adjustment Factor, Weekly Adjustment Factor and Design hourly Factor, each of which is the index indicating the traffic volume charaterirstics on the highways leading to the recreation areas in the mountainous and seaside tourist sites. Applying these results, it might be possible to calculate the optimal AADT (Annual Average Daily Traffic) and DHV (Design Hour Volume), also be a help to establish a traffic management policy. Finally, it hopes to promote new version of KHCM (Korea Highway Capacity Manual) which includes traffic volume characteristics on recreation areas.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.15 no.5
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• pp.103-114
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• 2012

The purpose of this research is classifying stream into different types depending on various factor from the perspective of stream corridor restoration and using it as basic data, which are used to consider efficient management and planning for the healthy stream according to the characteristic by types. In this study, 130 points of location of the Nakdong river basin which consist of various geographic factors have been chosen and hierarchical cluster analysis has been carried out in these points by using biological and physiochemical factors whose health can be considered to be predicted and evaluated. As a result of cluster analysis, there were three divided types. Type A whose biology and water quality are considered the best was the highest in forest area percentage so that it was classified into natural stream. Type B was classified into a rural region stream with a mixture of urban and agricultural region. Type C, with the most damaged water quality and biology health had the most urban region surface area and was named as urban region stream. Moreover, an overall restoration strategy according to characteristic by stream types was set. By the results of correlation analysis on factors, water quality showed a high correlation with biological properties and was affected by surrounding land usage. In evaluation of streams, it proves the need to consider not only other habitat's geographical and biological factors but also the water quality and land usage factors. There needs to be further research on stream ecosystem functionality factors and structural aspects by using a more objective and total evaluation result in selecting additional index and various other specific classification methods by stream types and its restoration strategies.

• Korean Journal of Construction Engineering and Management
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• v.17 no.2
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• pp.118-126
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• 2016

International construction market have quantitatively increased and have reached up to 700 Bil. US$ through active effort of construction firms and government. In spite of this increase, substantiality issue has been constantly disputed due to qualitative problems such as lack of capability and technical shortage. To overcome these problems, many methods in performing quantitative growth and qualitative substantiality of overseas construction are being researched which showed that selection of subcontractors in general contractor is regarded as a very important success factor. However, it is difficult to make a reasonable decision for selecting the subcontractors due to the lack of evaluation standards and reliability. This study proposes an improved evaluation system through adjustment of the evaluation indicators using correlations analysis and multiple regression analysis with pre-qualification and performance evaluation of 121 firms in 6 countries.

• Journal of Advanced Navigation Technology
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• v.23 no.4
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• pp.265-272
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• 2019

In this paper, we selected commuting scenarios in the most congested metropolitan area in Korea, and conducted noise analysis during personal air vehicle (PAV) operation using aviation environmental design tool (AEDT)software which was developed by Federal Aviation Administration (FAA). Noise is the second important factor after safety in order to operate PAVs through concepts such as ODM (on-demand mobility) introduced by National Aeronautics and Space Administration (NASA). Noise analysis were performed by modeling low-noise ePAVs as commercial helicopters and predicted residential suitability in order to resolve problems in which accurate NPD (noise power distance) data from PAVs were not released. The application of noise reduction technology such as electric propulsion has significantly reduced noise exposure levels and has reached the conclusion that commuting with PAVs is feasible without noise problems in the metropolitan area.

• Journal of Korean Society on Water Environment
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• v.38 no.6
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• pp.292-305
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• 2022

The Yeongsan River, one of the four largest rivers in South Korea, has been facing difficulties with water quality management with respect to algal bloom. The algal bloom menace has become bigger, especially after the construction of two weirs in the mainstream of the Yeongsan River. Therefore, the prediction and factor analysis of Chlorophyll-a (Chl-a) concentration is needed for effective water quality management. In this study, Chl-a prediction model was developed, and the performance evaluated using machine and deep learning methods, such as Deep Neural Network (DNN), Random Forest (RF), and eXtreme Gradient Boosting (XGBoost). Moreover, the correlation analysis and the feature importance results were compared to identify the major factors affecting the concentration of Chl-a. All models showed high prediction performance with an R² value of 0.9 or higher. In particular, XGBoost showed the highest prediction accuracy of 0.95 in the test data.The results of feature importance suggested that Ammonia (NH₃-N) and Phosphate (PO₄-P) were common major factors for the three models to manage Chl-a concentration. From the results, it was confirmed that three machine learning methods, DNN, RF, and XGBoost are powerful methods for predicting water quality parameters. Also, the comparison between feature importance and correlation analysis would present a more accurate assessment of the important major factors.