• Journal of Environmental Policy
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• v.14 no.3
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• pp.75-94
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• 2015

The purpose of this study is to analyze the major issues discussed among Parties and provide a framework for predicting the agreements on those issues, prior to the final negotiation on a new legally-binding agreement on climate change adaptation in the United Nations Framework Convention on Climate Change (UNFCCC). The analyses of documents, adaptation actions, and work of the Ad Hoc Working Group on the Durban Platform for Enhanced Action (ADP) under the UNFCCC informed that the adaptation issue has primarily been focused on the support of developed country Parties for the adaptation of developing country Parties following the principle of the Convention, Common but Differentiated Responsibilities and Respective Capabilities (CBDR-RC). Three-year work of the ADP acknowledged the major issues on adaptation in the new climate agreement, which would be categorized as long-term and global aspects, commitments/contributions/actions, monitoring and evaluation, institutional arrangements, and loss and damage. A final agreement on each issue could be predicted by setting a zone of possible agreement in-between the two extremes of developing and developed country Parties and considering three major elements affecting the Parties' positions, national priority, adaptation action, and social expectation, which are proposed in this study. The three major elements should be considered in a balanced manner by Parties to draw a durable agreement that will enhance global adaptation actions from a long-term perspective. That is, the agreement needs to reflect adaptation actions occurring outside the Convention as well as social expectations for adaptation. It is expected that the new agreement on climate change adaptation, from a long-term and global perspective, would be an opportunity to reduce vulnerability and build resilience to climate change by incorporating global expectations.

• Journal of Korea Multimedia Society
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• v.23 no.10
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• pp.1286-1295
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• 2020

It has been increasingly difficult to predict the amounts of Acer mono sap to be collected due to droughts and cold waves caused by recent climate changes with few studies conducted on the prediction of its collection volume. This study thus set out to propose a Big Data prediction system based on meteorological information for the collection of Acer mono sap. The proposed system would analyze collected data and provide managers with a statistical chart of prediction values regarding climate factors to affect the amounts of Acer mono sap to be collected, thus enabling efficient work. It was designed based on Hadoop for data collection, treatment and analysis. The study also analyzed and proposed an optimal prediction model for climate conditions to influence the volume of Acer mono sap to be collected by applying a multiple regression analysis model based on Hadoop and Mahout.

• Journal of Forest and Environmental Science
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• v.34 no.2
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• pp.192-195
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• 2018

To establish a management strategy of sediment-related disasters for adaptation to climate change, it is necessary to 1) understand the specific details and problems about the present status, 2) systematize related technologies by using exact numerical values obtained from physically-based analysis, and 3) ensure the basic guidelines are applied to field elastically. To achieve these successfully, detailed guidelines are required by scientifically considering the utilization and impact of related technology on the field. Here, detailed guidelines should include 1) the development of a basic plan, 2) enhancement of relevant technical instructions, 3) establishment of survey and inspection methods, 4) procedure of erosion control works in urban living sphere, and 5) proactive countermeasures against sediment-related disaster caused by earthquakes.

• Ocean Systems Engineering
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• v.7 no.4
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• pp.319-328
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• 2017

Higher prediction efficacy is a very challenging task in any field of engineering. Due to global warming, there is a considerable increase in the global sea level. Through this work, an attempt has been made to find the sea level variability due to climate change impact at Haldia Port, India. Different statistical downscaling techniques are available and through this paper authors are intending to compare and illustrate the performances of three regression models. The models: Wavelet Neural Network (WNN), Minimax Probability Machine Regression (MPMR), Feed-Forward Neural Network (FFNN) are used for projecting the sea level variability due to climate change at Haldia Port, India. Model performance indices like PI, RMSE, NSE, MAPE, RSR etc were evaluated to get a clear picture on the model accuracy. All the indices are pointing towards the outperformance of WNN in projecting the sea level variability. The findings suggest a strong recommendation for ensembled models especially wavelet decomposed neural network to improve projecting efficiency in any time series modeling.

• Advances in Energy Research
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• v.4 no.1
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• pp.1-28
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• 2016

A grid-connected photovoltaic (PV) system comprised of multicrystalline silicon (mc-Si) modules was installed in a cold climate region in the U.S. This roof-mounted stationary PV system is a real-world application of PV for building energy generation in International Energy Conservation Code (IECC) Climate Zone 5 (and possibly similar climate zones such as 6, 7 and 8), and it served the purposes of research, demonstration, and education. The importance of this work is highlighted by the fact that there has been less emphasis on solar PV system in this region of the U.S. because of climate and latitude challenges. The system is equipped with an extensive data acquisition system capable of collecting performance and meteorological data while visually displaying real-time and historical data through an interactive online interface. Experimental data was collected and analyzed for the system over a one-year period with the focus of the study being on measurements of power production, energy generation, and efficiency. The annual average daily solar insolation incident upon the array was found to be $4.37kWh/m^2$. During the first year of operation, the PV system provided 5,801 kWh (1,264 kWh/kWp) of usable AC electrical energy, and it was found to operate at an annual average conversion efficiency and PR of 10.6 percent and 0.79, respectively. The annual average DC to AC conversion efficiency of the inverter was found to be 94 percent.

• Journal of Information Technology Applications and Management
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• v.17 no.4
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• pp.19-38
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• 2010

This paper investigates the effect of stress on knowledge creation. The goal stress of resource inadequacy and job stress had negative influences on knowledge creation. However, the cohesion and mastery climate of team had positive influence on knowledge creation. Therefore this paper verifies the moderate role of the cohesion and mastery climate of team on the relationship between stress and knowledge creation. The model developed was tested using data collected from knowledge based industry with 375 members in 69 teams in 12 different firms. A Hierarchical Linear Model (HLM) was used to test the hypotheses generated from the model. Results show that job stress had a negative influence on knowledge creation as we expected but the goal stress didn't. The mastery climate of team affected knowledge creation positively and moderated the relationship between the goal stress and knowledge creation. Furthermore, the team cohesion had a positive influence on knowledge creation. The study provided some implications that practitioners should consider the stress when they design jobs for team members and suggest them the way to manage their job stress when they work.

• Journal of Korean Public Health Nursing
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• v.36 no.3
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• pp.347-360
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• 2022

Purpose: The purpose of this study was to identify the risk perception, safety climate and preventive behaviors of COVID-19 infections, and to verify the factors influencing the adoption of preventive behaviors by health care workers. Methods: A mixed-method approach was used based on a survey carried out in a general hospital. Quantitative data (N=181) were collected through a questionnaire and analyzed using multiple regression. Qualitative data (N=8) were collected through individual interviews and analyzed through Colaizzi's phenomological research method. Results: The factors influencing adoption of preventive behaviors by health care workers were safety climate (β=.41, p<.001), education (β=-.20, p=.025), work unit (β=-.16, p=.032), and risk perception (β=.15, p=.020). The explanatory power was 28.3%, and they have shown that these health care workers felt 'the threat of a pandemic like a battlefield', experienced 'struggle with quarantine rules' and realized 'the reality of infection control and the reorganization for change'. Conclusion: The findings of this study indicate that to increase the adoption of infection control preventive behaviors by health care workers when faced with new infectious diseases in the future, it is necessary to establish organizational support and a safe climate. This study confirms the need for preemptive support and education.

• Journal of Korean Society of societal Security
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• v.4 no.2
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• pp.57-64
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• 2011

Although it is uncertain that the cause of changed pattern of the natural disaster related to water (i.e. flood and drought) is due to excessive carbon dioxide yielded from economic activity or the increased number of sunspots, it is apparent that there have been unusual climate change that directly affects the water resource management. Due to such a frequent unusual weather activities, there have been increased natural disaster and the most direct and major reason is considered as climate change. As we see, the climate change necessarily causes social costs. Especially, the effects on the water resource due to flood and drought take the considerable part of such costs. Therefore, this study is basic work to develop a new economic analysis technique to be used in pursuing appropriate adaptation project in field of the amount of cost damage through analysis of the effects of the climate change on the water resource. The models appeared in many reports for cost assessment of climate change were various (e.g., PAGE, DICE, AIM, IMAGE, MERGE, and etc.) and this report summarizes general characteristics of each model. To assess the effects of climate change of the water management, we defined the field of the water management on climate change. The results help post-study in field of the climate change's social-economic effect assessment, can be employed for the prioritizing process of the national fund's investment.

• Korean Journal of Soil Science and Fertilizer
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• v.46 no.5
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• pp.303-307
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• 2013

Research reports on soil during the years from 1906 to 2012 have been analyzed to understand the role and pattern of soil research in agriculture. The number of research reports in relation with the key word of soils were 2,211 cases and classified in accordance with the criteria of research area, research subject, and research place of report papers. During the 40 years from 1906 to 1946, research work on soil chemistry was reached 62%, highest in the research area. In the case of research subject, research reports on soil fertility and soil nutrients was highest as 42.2%, and the next subject on soil salt and desalinization was about 19.5%. Research places were in the order of paddy as 34.1%, upland as 23.7%, and reclaimed soil as 22.5%. From 1953 to 2012 during 60 years, in the research area report papers were mainly concentrated on chemistry area as 32% and the next was physics as 26%, and environment as 12%. In the case of research subject during the same period, nutrient management report was reached 21.1%, and soil improvement on chemical and physical properties for optimum crop growth was 11.9%. Soil survey and data base establishment report was 8.6%. Research place were in the order of upland as 34.9%, paddy as 25.7%, and vinyl house as 12.5%, which showed reversed pattern compared to that of before 40 years.

• The Journal of the Korea Contents Association
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• v.11 no.9
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• pp.496-505
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• 2011

The purpose of this study was to research the relationships among ethical climate, trust, organizational identification and turnover intention of employees in travel agency. Ethical climates the prevailing perceptions of typical organizational practices and procedures that have ethical content. Ethical climate involves the perceptions of rightness or wrongness present in the organization's work environment, and establishes the norms for acceptable and unacceptable behavior within the company. To accomplish this study, it was determined that the analysis derived from a hypothesis and literature reviews and data collected from 231 employees in travel agency. The results of empirical analysis showed as follows. First, Perceived ethical climate has a significant effect on trust, organizational identification and turnover intention. Second, Organizational identification has a significant effect on turnover intention while trust has no relationship with it. In addition, the mediating role of organizational identification is examined in the relationship between ethical climate and turnover intention. Based on these findings, the implications and limitations of the study were presented including some directions for future studies.