• Journal of Fisheries and Marine Sciences Education
• /
• v.21 no.1
• /
• pp.121-133
• /
• 2009

This study tested the relations of schools organizational climate and teachers' job stresses, perceived by 913 teachers from 45 elementary, junior- and senior-high schools. Pearson's correlation analysis for the relations between the sub-factors of both organizational climate and job stresses and cannonical correlation analysis for the relative contribution of individual variable of organizational climate upon job stress were applied for the test. The results of Pearson's correlation analysis showed that while 'intimacy', 'esprit', 'considerations', and 'production emphasis' climate had negative correlations with job stress sub-factors, 'disengagement' and 'aloofness' climate had positive correlation. 'Student guidance', a sub-factor of job stresses, did not have statistically significant correlation with any sub-factors of organizational climate. Findings from cannonical correlation analysis showed 2 significant cannonical functions to explain the relations between the sets of variables. 'Disengagement' from organizational climate positively contributed with 'authority forfeiture' and 'dissention and conflict' of the job stresses variables.

• Journal of the Korean Society of Safety
• /
• v.21 no.5 s.77
• /
• pp.60-71
• /
• 2006

In recent years, the most safety studies have been focused on identifying the relationship between safety climate and safe work behavior in accordance with the awareness that prime causes of accidents are organizational, managerial, and human factors rather than pure technical failures across the world. This study focused empirical research aimed at finding out the safety climate factors and examining the relationships of the safety climate and safe work behavior in construction site in Korea, too. A 10 numbers of safety climate factors were adapted from the Mohamed's study(2002) and tested using PLS-GRAPH 3.0 expecting same results as Mohamed' study. And then the relationship between safety climate and safe work behavior was examined. Only two safety climate factors-personal risk appreciation and worker's safety competence-were found and a strong positive relationship between safety climate and safe work behavior was identified in this study. Discussed in details about the results and implications and suggested further studies.

• Atmosphere
• /
• v.27 no.2
• /
• pp.163-175
• /
• 2017

The global terrestrial ecosystems have shown a large spatial variability in recent decades and represented a carbon sink pattern at mid-to-high latitude in Northern Hemisphere. However, there are many uncertainties in magnitude and spatial distribution of terrestrial carbon fluxes due to the effect of climate factors. So, it needs to accurately understand the spatio-temporal variations on carbon exchange flux with climate. This study focused on the effects of climate factors, .i.e. temperature, precipitation, and solar radiation, to terrestrial biosphere carbon flux. We used the terrestrial carbon flux that is simulated by a CarbonTracker, which performs data assimilation of global atmospheric $CO_2$ mole fraction measurements. We demonstrated significant interactions between Net Ecosystem Production (NEP) and climate factors by using the partial correlation analysis. NEP showed positive correlation with temperature at mid-to-high latitude in Northern Hemisphere but showed negative correlation pattern at $0-30^{\circ}N$. Also, NEP represented mostly negative correlation with precipitation at $60^{\circ}S-30^{\circ}N$. Solar radiation affected NEP positively at all latitudes and percentage of positive correlation at tropical regions was relatively lower than other latitudes. Spring and summer warming had potentially positive effect on NEP in Northern Hemisphere. On the other hand as increasing the temperature in autumn, NEP was largely reduced in most northern terrestrial ecosystems. The NEP variability that depends on climate factors also differently represented with the type of vegetation. Especially in crop regions, land carbon sinks had positive correlation with temperature but showed negative correlation with precipitation.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.16 no.5
• /
• pp.1414-1430
• /
• 2022

Due to the Internet of Things popularity, many agricultural data are collected by sensors automatically. The abundance of agricultural data makes precise prediction of rice yield possible. Because the climate factors have an essential effect on the rice yield, we considered the climate factors in the prediction model. Accordingly, this paper proposes a machine learning model for rice yield prediction in Taiwan, including the genetic algorithm and support vector regression model. The dataset of this study includes the meteorological data from the Central Weather Bureau and rice yield of Taiwan from 2003 to 2019. The experimental results show the performance of the proposed model is nearly 30% better than MARS, RF, ANN, and SVR models. The most important climate factors affecting the rice yield are the total sunshine hours, the number of rainfall days, and the temperature.The proposed model also offers three advantages: (a) the proposed model can be used in different geographical regions with high prediction accuracies; (b) the proposed model has a high explanatory ability because it could select the important climate factors which affect rice yield; (c) the proposed model is more suitable for predicting rice yield because it provides higher reliability and stability for predicting. The proposed model can assist the government in making sustainable agricultural policies.

• Journal of Climate Change Research
• /
• v.5 no.4
• /
• pp.349-357
• /
• 2014

Greenhouse gases (GHGs) from agricultural sector were categorized in a guideline book from Intergovernmental Panel on Climate Change (IPCC) as methane from rice paddy fields and nitrous oxide from agricultural soils. In general, GHG emissions were calculated by multiplying the activity data by emission factor. Tier 1 methodology uses IPCC default factors and Tier 2 uses country specific emission factors (CS). The CS and Scaling factors (SF) had been developed by NAAS (National Academy of Agricultural Science) projects from 2009 to 2012 to estimate how the advanced emissions. The purpose of this study was to compare GHG emissions calculated from IPCC default factors and NAAS CS and SF of agricultural sector in Korea. Methane emissions using CS and SF in rice paddy field was about 79% higher than those using IPCC default factors. In the agricultural soils, nitrous oxide emissions using CS from the 5 crops were about 40% lower than those using IPCC default. Except those 5 crops, approximately up to 52% lower emissions were calculated using CS compared to those using IPCC default factors. The total GHG emissions using CS and SF were about 33% higher than those using Tier 1 method by IPCC default factors.

• Journal of the Korean Society of Safety
• /
• v.20 no.2 s.70
• /
• pp.91-97
• /
• 2005

The purpose of this study is to provide basic data for establishment of prevention counterplan against construction accidents in preparation for variation of climate conditions. In order to execution of this study, it was analyzed relations of climate factors and cases of construction accident occurred construction sites. In occurrence of construction accidents inducing death upon variation of Climate factors, precipitation and wind velocity were not related directly to construction accidents inducing death. On the other hand, the more temperature and humidity are high, the more construction accidents inducing death occurred. Especially, when temperature and humidity are above $24^{\circ}C,\;70\%$ respectively, field managers must pay attention to safety management of construction sites.

• The Korean Journal of Ecology
• /
• v.21 no.6
• /
• pp.809-814
• /
• 1998

Changes of annual seed production related to climate change were studied for 12 years in Piagol, a riparian valley in Mt. Jiri. Sixty-four seed traps (sized 0.5 ${\times}$ 0.5 $m^{2}$) were set up on the forest floor of surveyed area. Seeds were collected from these traps at an interval of 15 days from September to November since 1984. Vegetation of the study area was mainly consisted of the naturally regenerated Carpinus tschonoskii in the tree layer. Acer mono, Quercus serrata, Carpinus laxiflora and Symplocos chinensis also appeared in the same layer. Maximum production occurred in 1984 and 1994. As a result of comparing seed production with local climate factors for 12 years, seed productivity and the year of maximum production of Carpinus forest were merely related with precipitation, air temperature and duration of sunshine among local climate factors. Duration of sunshine was, however, not contributed to periodically high productivity of seed of riparian valley carpinus forest.

• Journal of Environmental Policy
• /
• v.11 no.1
• /
• pp.27-48
• /
• 2012

The aim of this paper is to review the environmental assessment of urban climatic factors relating to urban planning in Korea and Germany, and suggest efficient ways to consider climatic factors in the environmental assessment process for urban planning in Korea. For these purposes, current assessment systems concerning urban master plan and urban management plan in Korea were reviewed to know how urban climatic factors are assessed. Furthermore, two German cases of Strategic Environmental Assessment were investigated to know how urban climatic factors are assessed and considered in the urban and regional planning of Germany. Based on the results, efficient ways to consider climatic factors in the environmental assessment for urban planning were suggested from three aspects of factors, methods and available data for climate assessment.

• Journal of The Korean Society of Grassland and Forage Science
• /
• v.41 no.1
• /
• pp.47-55
• /
• 2021

The objective of this study was to access the effect of climate and soil factors on alfalfa dry matter yield (DMY) by the contribution through constructing the yield prediction model in a general linear model considering climate and soil physical variables. The processes of constructing the yield prediction model for alfalfa was performed in sequence of data collection of alfalfa yield, meteorological and soil, preparation, statistical analysis, and model construction. The alfalfa yield prediction model used a multiple regression analysis to select the climate variables which are quantitative data and a general linear model considering the selected climate variables and soil physical variables which are qualitative data. As a result, the growth degree days(GDD) and growing days(GD), and the clay content(CC) were selected as the climate and soil physical variables that affect alfalfa DMY, respectively. The contributions of climate and soil factors affecting alfalfa DMY were 32% (GDD, 21%, GD 11%) and 63%, respectively. Therefore, this study indicates that the soil factor more contributes to alfalfa DMY than climate factor. However, for examming the correct contribution, the factors such as other climate and soil factors, and the cultivation technology factors which were not treated in this study should be considered as a factor in the model for future study.

• Journal of Construction Engineering and Project Management
• /
• v.5 no.2
• /
• pp.1-10
• /
• 2015

There is a high confidence based on scientific evidence that climate is changing over time. Now climate change is considered as one of the challenges facing the construction industry. As no project is risk free and climate change has a strong impact on the different phases of the construction project lifecycle. This research aimed at providing a platform of knowledge for the construction management practitioners about the impacts of climate change on the construction projects lifecycle, identify the most dangerous climate change factors on the construction project lifecycle, and identify the most affected phase by climate change factors through the construction projects lifecycle. The study depended on the opinions of civil engineers who have worked in the construction projects field among the reality of Gaza Strip. Questionnaire tool was adopted as the main research methodology in order to achieve the desired objectives. The questionnaire included 127 factors in order to obtain responses from 88 construction practitioners out of 98 representing 89.79% response rate about the influence of climate change on the generic lifecycle of construction projects. The results deduced that the most significant influence on the construction project lifecycle was related to the extreme weather events, rainfall change, and temperature change respectively. There was a general agreement between the respondents that the most affected phase by temperature, rainfall, and extreme weather events is the execution phase. The results also asserted with a high responses scale on the need to alternative procedures and clear strategies in order to face the climate change within construction industry.