• Proceedings of the Korean Institute Of Construction Engineering and Management
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• autumn
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• pp.305-310
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• 2001

The purpose of this study is to calculate delay damages for contractors. The study has been performed by investigation of delay cost occurrence status and the analysis of subway construction cases. The results of this study are as follows: 1. Delay cost( 1day) equivalent to $0.005\%$ of total construction cost by analysis case studies. 2. Including bank interest, dealy cost is analysed as the following; $1.1\~9.2\%$ of total construction cost in part extension period, $3.3\~11.0\%$ of total construction cost in total extension period. 3. In comparison between liquidated damages and delay cost, liquidated damages account for average 20.1 times of delay costs. 4. Acceleration cost will be calculate on the basis of delay cost calculation method. In the result of this method, acceleration cost is equal to delay cost at least or must be large than delay cost

• Journal of the Korean Society of Marine Environment & Safety
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• v.21 no.6
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• pp.672-678
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• 2015

The types of hazardous and noxious substances (HNS) being transported by sea in Korea are at about 6,000, HNS transport volume accounts for 19% of total tonnage shipped in Korea, and the increase rate of seaborne HNS trade in Korea is 2.5 times higher than the average increase rate of the world seaborne HNS trade. Reflecting this trend, HNS spill incidents have been frequently reported in Korean waters, and there are increasing social demands to develop HNS management technology for the preparedness, response, post-treatment and restoration in relation to HNS spill incidents at sea. In this study, a risk-based HNS prioritization system was developed and an HNS risk database was built with evaluation indices such as sea transport volume, physicochemical properties, toxicities, persistency, and bioaccumulation. Risk scores for human health and marine environments were calculated by multiplying scores for toxicity and exposure. The top-20 substances in the list of HNS were tabulated, and Aniline was ranked first place, but it needs to be managed not by individuals but by HNS groups with similar score levels. Limitations were identified in obtaining data of chronic toxicity and marine ecotoxicity due to lack of testing data. It is necessary to study on marine ecotoxicological test in the near future. Moreover, the priority list of HNS is expected to be utilized in the development of HNS management technology and the relevant technologies, after the expert's review process and making up for the lack of test data in the current research results.

• Journal of the Korean Society for Marine Environment & Energy
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• v.17 no.2
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• pp.153-165
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• 2014

Carbon dioxide capture and storage (CCS) technology is recognizing one of method responding the climate change with reduction of carbon dioxide in atmosphere. In Korea, due to its geological characteristics, sub-seabed geological $CO_2$ storage is regarded as more practical approach than on-land storage under the goal of its deployment. However, concerns on potential $CO_2$ leakage and relevant acidification issue in the marine environment can be an important subject in recently increasing sub-seabed geological $CO_2$ storage sites. In the present study effect data from literatures were collected in order to conduct an effect assessment of elevated $CO_2$ levels in marine environments using a species sensitivity distribution (SSD) various marine organisms such as microbe, crustacean, echinoderm, mollusc and fish. Results from literatures using domestic species were compared to those from foreign literatures to evaluate the reliability of the effect levels of each biological group and end-point. Ecological effect guidelines through estimating level of pH variation (${\delta}pH$) to adversely affect 5 and 50% of tested organisms, HC5 and HC50, were determined using SSD of marine organisms exposed to the $CO_2$-induced acidification. Estimated HC5 as ${\delta}pH$ of 0.137 can be used as only interim quality guideline possibly with adequate assessment factor. In the future, the current interim guideline as HC5 of ${\delta}pH$ in this study will look forward to compensate with supplement of ecotoxicological data reflecting various trophic levels and indigenous species.

• Journal of Science Education
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• v.45 no.2
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• pp.187-200
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• 2021

This study was conducted to identify students' meaningful scientific experiences and to ascertain the path through which the experience led to learning. The subjects of 'Understanding of the History of Science' were asked to write an essay on the subject of 'Effects of science on my life' to 81 students in the department of literature and 125 students in the science department. After that Classification criteria were established through scientific experts' seminars, and the scientific experiences that affected students and their effects were examined. The results from analyses were summarized as follows: First, As a result of study about Science Education experience that has impacted students' lives, the students were influenced by images, most of which were influenced by scientific videos. They were also influenced by science classes and science books. As a result of classifying science experience, most of the experience is composed of Informal Science Learning. Second, as a result of examining how students were influenced by their scientific experience, they found that they were affected by their daily life or influenced by science. As a result of the research, it can be confirmed that Informal Science Learning experience is an important learning form that has a great influence on students. Therefore, appropriate Informal Science Learning experience should be introduced into the class, and research and development on the Informal Science Learning experience preferred by the students should be done.

• Korean Chemical Engineering Research
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• v.57 no.5
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• pp.637-651
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• 2019

In the event of a major accident such as an explosion in a refinery or a petrochemical plant, it has caused a serious loss of life and property and has had a great impact on the insurance market. In the case of catastrophic incidents occurring in process industries such as refinery and petrochemical plants, only the proximate causes of loss have been drawn and studied from inspectors or claims adjustors responsible for claims of property insurers, incident cause investigators, and national forensic service workers. However, it has not been done well for conducting root cause analysis (RCA) and identifying the factors that contributed to the failure and establishing preventive measures before leading to chemical plant's catastrophic incidents. In this study, the criteria of warning signs on CCPS catastrophic incident waning sign self-assessment tool which was derived through the RCA method and the contribution factor analysis method using the swiss cheese model principle has been reviewed first. Secondly, in order to determine the major incident warning signs in an actual chemical plant, 614 recommendations which have been issued during last the 17 years by loss control engineers of global reinsurers were analyzed. Finally, in order to facilitate the assessment index for catastrophic incident warning signs, the criteria for the catastrophic incident warning sign index at chemical plants were grouped by type and classified into upper category and lower category. Then, a catastrophic incident warning sign index for a chemical plant was developed using the weighted values of each category derived by applying the analytic hierarchy process (pairwise comparison method) through a questionnaire answered by relevant experts of the chemical plant. It is expected that the final 'assessment index for catastrophic incident warning signs' can be utilized by the refinery and petrochemical plant's internal as well as external auditors to assess vulnerability levels related to incident warning signs, and identify the elements of incident warning signs that need to be tracked and managed to prevent the occurrence of serious incidents in the future.

• Journal of Korean Tunnelling and Underground Space Association
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• v.21 no.1
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• pp.61-77
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• 2019

If a new utility tunnel is planned for high density existing urban areas in Korea, a rational decision-making process such as the determination of optimum design capacity by using the feasibility evaluation system based on quantitative evaluation indexes and the economic evaluation is needed. Thus, the previous study presented the important weight of individual higher-level indexes (3 items) and sub-indexes (16 items) through a hierarchy analysis (AHP) for quantitative evaluation index items, considering the characteristics of each urban type. In addition, an economic evaluation method was proposed considering 10 benefit items and 8 cost items by adding 3 new items, including the effects of traffic accidents, noise reduction and socio-economic losses, to the existing items for the benefit cost analysis suitable for urban utility tunnels. This study presented a quantitative feasibility evaluation method using the important weight of 16 sub-index items such as the road management sector, public facilities sector and urban environment sector. Afterwards, the results of quantitative feasibility and economic evaluation were compared and analyzed in 123 main road sections of the Seoul. In addition, a comprehensive evaluation method was proposed by the combination of the two evaluation results. The design capacity optimization program, which will be developed by programming the logic of the quantitative feasibility and economic evaluation system presented in this study, will be utilized in the planning and design phases of urban community zones and will ultimately contribute to the vitalization of urban utility tunnels.

• Journal of the Korean Society of International Agriculture
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• v.30 no.4
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• pp.257-268
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• 2018

Recently, the international standardization of ISO in the field of Oriental Herbal Medicine has been progressing rapidly under the direction of China's promotion. China's intention to promote international standardization is to extend its influence to the world and beyond the domestic market. The Oriental medicine system in East Asia has similar roots in academic terms, but the medicines that can be supplied and received in each country are different and have developed independently. The international standardization of medicinal herbs is expected to function in a direction that weakens such differentiation and independence. From a commercial point of view, international standardization is no different from creating evaluation criteria for oriental medicinal products, and it is expected that its potential impact on domestic and overseas markets and producers will be large. In particular, the international standardization centered on China can lead to favorable evaluation criteria for China, which may further negatively affect the market competitiveness of domestic raw materials, which have been pushed back by Chinese manufacturers. If the domestic production base is weakened, not only will the farmers suffer but the supply and demand of raw materials will also be manipulated, safety management control will be reduced, and the development of oriental herbal products using domestic raw materials will be hurt. Therefore, in the promotion of international standardization, it is necessary not only to reflect the value of Korean herbal medicine but also to provide strategic responses to protect the domestic production base. However, in the case of recent initiatives, there is no precedent in analyzing influence on the production partners and the related industries. In addition, there are few related papers and reports on the subject, so the publicity process has not been done sufficiently. In response to this, this study will examine the countermeasures against the international standardization of herbal medicines through reviewing its present status and evaluating the agenda of the Korean initiative.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.235-250
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• 2021

The overarching question of this study is how a typical rice cultivation system in Gimje, Korea was keeping up with the triple-win challenge of climate-smart agriculture (CSA). To answer this question, we have employed (1) quantitative data from direct measurement of energy, water, carbon and information flows in and out of a rice cultivation system and (2) appropriate metrics to assess production, efficiency, GHG fluxes, and resilience. The study site was one of the Korean Network of Flux measurement (KoFlux) sites (i.e., GRK) located at Gimje, Korea, managed by National Academy of Agricultural Science, Rural Development Administration. Fluxes of energy, water, carbon dioxide (CO₂) and methane (CH₄) were directly measured using eddy-covariance technique during the growing seasons of 2011, 2012 and 2014. The production indicators include gross primary productivity (GPP), grain yield, light use efficiency (LUE), water use efficiency (WUE), and carbon uptake efficiency (CUE). The GHG mitigation was assessed with indicators such as fluxes of carbon dioxide (F_CO2), methane (F_CH4), and nitrous oxide (F_N2O). Resilience was assessed in terms of self-organization (S), using information-theoretic approach. Overall, the results demonstrated that the rice cultivation system at GRK was climate-smart in 2011 in a relative sense but failed to maintain in the following years. Resilience was high and changed little for three year. However, the apparent competing goals or trade-offs between productivity and GHG mitigation were found within individual years as well as between the years, causing difficulties in achieving the triple-win scenario. The pursuit of CSA requires for stakeholders to prioritize their goals (i.e., governance) and to practice opportune interventions (i.e., management) based on the feedback from real-time assessment of the CSA indicators (i.e., monitoring) - i.e., a purpose-driven visioneering.

• Journal of Science Education
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• v.45 no.3
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• pp.292-303
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• 2021

This study identifies the terms frequently used together with energy in online science news articles and topics of the news reports to find out how the term energy is used in everyday life and to draw implications for science curriculum and instruction about energy. A total of 2,171 online news articles in science category published by 11 major newspaper companies in Korea for one year from March 1, 2018 were selected by using energy as a search term. As a result of natural language processing, a total of 51,224 sentences consisting of 507,901 words were compiled for analysis. Using the R program, term frequency analysis, semantic network analysis, and structural topic modeling were performed. The results show that the terms with exceptionally high frequencies were technology, research, and development, which reflected the characteristics of news articles that report new findings. On the other hand, terms used more than once per two articles were industry-related terms (industry, product, system, production, market) and terms that were sufficiently expected as energy-related terms such as 'electricity' and 'environment.' Meanwhile, 'sun', 'heat', 'temperature', and 'power generation', which are frequently used in energy-related science classes, also appeared as terms belonging to the highest frequency. From a network analysis, two clusters were found including terms related to industry and technology and terms related to basic science and research. From the analysis of terms paired with energy, it was also found that terms related to the use of energy such as 'energy efficiency,' 'energy saving,' and 'energy consumption' were the most frequently used. Out of 16 topics found, four contexts of energy were drawn including 'high-tech industry,' 'industry,' 'basic science,' and 'environment and health.' The results suggest that the introduction of the concept of energy degradation as a starting point for energy classes can be effective. It also shows the need to introduce high-tech industries or the context of environment and health into energy learning.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.263-286
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• 2022

This study acquires NBA statistical information for a total of 32 years from 1990 to 2022 using web crawling, observes variables of interest through exploratory data analysis, and generates related derived variables. Unused variables were removed through a purification process on the input data, and correlation analysis, t-test, and ANOVA were performed on the remaining variables. For the variable of interest, the difference in the mean between the groups that advanced to the playoffs and did not advance to the playoffs was tested, and then to compensate for this, the average difference between the three groups (higher/middle/lower) based on ranking was reconfirmed. Of the input data, only this year's season data was used as a test set, and 5-fold cross-validation was performed by dividing the training set and the validation set for model training. The overfitting problem was solved by comparing the cross-validation result and the final analysis result using the test set to confirm that there was no difference in the performance matrix. Because the quality level of the raw data is high and the statistical assumptions are satisfied, most of the models showed good results despite the small data set. This study not only predicts NBA game results or classifies whether or not to advance to the playoffs using machine learning, but also examines whether the variables of interest are included in the major variables with high importance by understanding the importance of input attribute. Through the visualization of SHAP value, it was possible to overcome the limitation that could not be interpreted only with the result of feature importance, and to compensate for the lack of consistency in the importance calculation in the process of entering/removing variables. It was found that a number of variables related to three points and errors classified as subjects of interest in this study were included in the major variables affecting advancing to the playoffs in the NBA. Although this study is similar in that it includes topics such as match results, playoffs, and championship predictions, which have been dealt with in the existing sports data analysis field, and comparatively analyzed several machine learning models for analysis, there is a difference in that the interest features are set in advance and statistically verified, so that it is compared with the machine learning analysis result. Also, it was differentiated from existing studies by presenting explanatory visualization results using SHAP, one of the XAI models.