• Journal of the Korean Society for Marine Environment & Energy
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• v.15 no.2
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• pp.118-125
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• 2012

World population has increased rapidly following the industrial revolution, reaching 7 billion in 2012. Several forecasts estimate that this number will rise to about 8 billion in 2025. Improvements of living standards in developing nations have also raised resource and energy demands worldwide. In consequences, human beings have faced many global and urgent problems, such as global warming, water and food shortages, resource and energy crises, and so on. Many ocean utilization technologies for avoiding or reducing such big problems have been developed, for examples $CO_2$ ocean sequestration, seawater desalination, artificial upwelling, deepwater mining, and ocean energies. It is important, however, to assess such technologies from the viewpoints of sustainability and public acceptancy, since the aims of those technologies are to develop sustainable social systems rather than conventional ones based on fossil resources. Inclusive Marine Pressure Assessment and Classification Technology Research Committee (generally called IMPACT Research Committee) of Japan Society of Naval Architects and Ocean Engineers, has proposed Inclusive Impact Index "Triple I" as an indicator, which can predict both environmental sustainability and economical feasibility, in order to assess the ocean utilization technologies from the viewpoints of sustainability and public acceptancy. This index was considered by combining Ecological Footprint and Environmental Risk Assessment. The Ecological Footprint and the Environmental Risk Assessment are introduced in the first part of this paper. Then the concept and the structure of the Triple I are explained in the second part of this paper. Finally, the economy-ecology conversion factor in Triple I accounting is considered.

• Journal of the Korean Society of Clothing and Textiles
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• v.39 no.3
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• pp.337-352
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• 2015

This study selected a case study method conforming to qualitative research in order to analyzed how each type of fashion enterprises uses SNS in-side of fashion marketing based on content the researcher monitored and selected from the Facebook website for each enterprise. The standard to select fashion brands in this study is a graded list made based on ranking 5 analysis sites on social media (Socialbakers, socialDigm, Pulse K, BigFoot9, L2). The researcher sorted and then analyzed 2 brands that have many fan joiners and followers among fashion brands that were ranked top of the graded list, work in Facebook animatedly, and had representativeness in each type (SPA, Sports Brands). The study was conducted from January 2013 to March 2013, and the index of Facebook consisted of 3 kinds of elements (comment, like, and share). Each numerical value was counted to decide the monthly ranking. Content analysis was divided into public relations about brand, public relations about products, and customer participation and activities; consequently, the researcher investigated which content was post conforming to the ranking. The study analyzed the analysis results of each brand derived through the method of study compared to other brands. The results are as follows. In case of SPA brands, the category accounting for high rank in index analysis are public relation events to attract customer attention and products and offering information. The results of the monthly trend about whole post category were also similarly analyzed so the promotion goal that the brand wants to seek in priority coincides with the customer compliance rate. Next, in the case of sports brand, public relations for products offering information, event for arousing customer concern, and participation activities accounted for a high rank in the index analysis and posted the most in the analysis of the monthly trend for whole post category. The researcher came to understand that the direction of content for brands shown through Facebook coincides with customer sympathy.

• Journal of Environmental Policy
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• v.10 no.1
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• pp.71-91
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• 2011

The purpose of this paper is to estimate the environmental performance of 29 Chinese provinces by adopting the advanced measurements, integrated pollution intensity index, IPI, which can be computed using Data Envelopment Analysis(DEA) techniques. This index has the advantage of accounting for multiple resources used, good outputs produced and pollutants emitted simultaneously. The result obtained using the methodology shows the obvious evidence that provinces located around eastern area of China take relatively low levels and these phenomenons have been clearly observed throughout the sample period 1998~2007. The estimated index can be interpreted that the environmental burden in China has been steadily decreased as economic growth. This paper also tries to figure out the relationship among IPI, income levels, economic structures, the level of environmental regulations and FDI inflow. The estimated relationship between IPI and income per capita predicts improving environmental performance with increasing income levels. This explains the improvement in IPI which is simultaneously observed with income increases. According to the 'pollution haven hypothesis', many researches have been concerned the possibility that a large amount of foreign capital has been invested in China to avoid the strict environmental standards in advanced countries. However, the estimated coefficients in all model specifications take negative sign with IPI and highly statistical significant. This is a indication that there are positive impacts of foreign investments on IPI by adopting clean and high technologies from advanced countries.

• Journal of Environmental Impact Assessment
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• v.28 no.6
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• pp.525-535
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• 2019

In this study, 49 major WCS(Wildlife Crossing Structure), including Baekdu-daegan, were evaluated for the effectiveness of WCS on using the daily average frequency index and diversity Index comparing the number of species that appear with the surrounding habitats. According to the analysis, the average use frequency of the entire WCS was 1.4 times, and the average number of WCS exceeded the average was 17 and 34.7 percent of the total. There were 18 WCS with the same number of habitats and species that appeared in the same area, or 36.7 percent of the total. The daily average use frequency and variety were all analyzed at 10 efficient WCS, accounting for 20.4 percent of the total. According to the results of an site survey on the compliance rate of 4 efficient WCS, the compliance rate of the Deoksanjae overpass was the best in location selection, specifications, vegetation cover and soil, fence. The results of this research will be used as basic data for the study of WCS effectiveness, including the improvement of functions of new and installed WCS.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.5
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• pp.427-434
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• 2023

Oysters are an important organism, accounting for an average of 76% of shellfish aquaculture production. In this study, optimal habitat was searched for by calculating the Habitat Suitability Index (HSI) using water temperature, salinity, hydrodynamics, DO, SS and Chl.a in Jaran Bay. As a result, the inside of Jaran Bay was found to be a more suitable habitat than the outside with a wide entrance and rapid hydrodynamics. Oyster production and HSI showed a significant correlation (0.710, p<0.05). Hydrodynamics helps the growth of aquaculture organisms, such as food supply through seawater exchange in the bay, which showed a high correlation (0.709, p<0.05) with oyster production. It was found to have a greater effect on habitat suitability than Chl.a. The results of this study are expected to be helpful for the efficient conservation, use and management of coastal fisheries.

• Journal of Intelligence and Information Systems
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• v.22 no.2
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• pp.33-56
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• 2016

Many researchers have focused on developing bankruptcy prediction models using modeling techniques, such as statistical methods including multiple discriminant analysis (MDA) and logit analysis or artificial intelligence techniques containing artificial neural networks (ANN), decision trees, and support vector machines (SVM), to secure enhanced performance. Most of the bankruptcy prediction models in academic studies have used financial ratios as main input variables. The bankruptcy of firms is associated with firm's financial states and the external economic situation. However, the inclusion of qualitative information, such as the economic atmosphere, has not been actively discussed despite the fact that exploiting only financial ratios has some drawbacks. Accounting information, such as financial ratios, is based on past data, and it is usually determined one year before bankruptcy. Thus, a time lag exists between the point of closing financial statements and the point of credit evaluation. In addition, financial ratios do not contain environmental factors, such as external economic situations. Therefore, using only financial ratios may be insufficient in constructing a bankruptcy prediction model, because they essentially reflect past corporate internal accounting information while neglecting recent information. Thus, qualitative information must be added to the conventional bankruptcy prediction model to supplement accounting information. Due to the lack of an analytic mechanism for obtaining and processing qualitative information from various information sources, previous studies have only used qualitative information. However, recently, big data analytics, such as text mining techniques, have been drawing much attention in academia and industry, with an increasing amount of unstructured text data available on the web. A few previous studies have sought to adopt big data analytics in business prediction modeling. Nevertheless, the use of qualitative information on the web for business prediction modeling is still deemed to be in the primary stage, restricted to limited applications, such as stock prediction and movie revenue prediction applications. Thus, it is necessary to apply big data analytics techniques, such as text mining, to various business prediction problems, including credit risk evaluation. Analytic methods are required for processing qualitative information represented in unstructured text form due to the complexity of managing and processing unstructured text data. This study proposes a bankruptcy prediction model for Korean small- and medium-sized construction firms using both quantitative information, such as financial ratios, and qualitative information acquired from economic news articles. The performance of the proposed method depends on how well information types are transformed from qualitative into quantitative information that is suitable for incorporating into the bankruptcy prediction model. We employ big data analytics techniques, especially text mining, as a mechanism for processing qualitative information. The sentiment index is provided at the industry level by extracting from a large amount of text data to quantify the external economic atmosphere represented in the media. The proposed method involves keyword-based sentiment analysis using a domain-specific sentiment lexicon to extract sentiment from economic news articles. The generated sentiment lexicon is designed to represent sentiment for the construction business by considering the relationship between the occurring term and the actual situation with respect to the economic condition of the industry rather than the inherent semantics of the term. The experimental results proved that incorporating qualitative information based on big data analytics into the traditional bankruptcy prediction model based on accounting information is effective for enhancing the predictive performance. The sentiment variable extracted from economic news articles had an impact on corporate bankruptcy. In particular, a negative sentiment variable improved the accuracy of corporate bankruptcy prediction because the corporate bankruptcy of construction firms is sensitive to poor economic conditions. The bankruptcy prediction model using qualitative information based on big data analytics contributes to the field, in that it reflects not only relatively recent information but also environmental factors, such as external economic conditions.

• Economic and Environmental Geology
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• v.49 no.3
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• pp.181-191
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• 2016

We estimate the eruption history and magmatic eruptive volumes of each rock units to evaluate the volcanic eruption scale and volcanic hazard of the Ulleung Island. Especially, Maljandeung Tuff represents about 19~5.6 ka B.P. from $^{14}C$ dating, and Albong Trachyandesite, about 0.005 Ma from K-Ar dating in recent age dating data. These ages reveal evidences of volcanic activities within the last 10,000 years, indicating that the Ulleung Island can classify as an active volcano with possibility of volcanic eruption near future. Accumulated DRE-corrected eruptive volume is calculated at $40.80km^3$, within only the island. The calculated volumes of each units are $3.71km^3$ in Sataegam Tuff, and $0.10km^3$ in Maljandeung Tuff but $12.39km^3$ in accounting the distal and medial part extended into southwestern Japan. Volcanic explosivity indices range 1 to 6, estimating from the volumes of each pyroclastic deposits. The colossal explosivity indices are 5 in Sataegam Tuff, and 6 in Maljandeung Tuff in accounting the distal and medial part. Therefore, it is necessary for appropriate researches regarding possibility of volcanic eruption of the island, and establishment system of the evaluation and preparation for volcanic hazard based on the researches is required.

• International Commerce and Information Review
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• v.14 no.3
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• pp.323-350
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• 2012

This study analyzes the efficiency of 25 shipping companies in Korea over the period 2005-2009, using Data Envelopment Analysis (DEA). Among 31 companies that listed in order of decreasing sales volume for the period 2006-2010, the sample companies has been selected on the ground of data availability. This study computes the companies' efficiency, estimates their year-on-year Malmquist productivity index, and analyzes the cause leads to the changes in the productivity, In particular, this study attempts, by dividing the companies into two group, listed or not, to compare the changes in the productivity and analyze the reasons. The results from static analysis based on CCR and BCC model indicate that listed companies are higher efficient than unquoted companies. The results from tests on the productivity changes based on the Malmquist productivity index show that 19 unquoted companies increase their average productivity by 16.2 percent year after year during the period but 6 listed companies increase by 0.5% during the same period.

• Safety and Health at Work
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• v.4 no.1
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• pp.37-45
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• 2013

Objectives: As quality of work-life (QWL) among nurses affects both patient care and institutional standards, assessment regarding QWL for the profession is important. Work-related Quality of Life Scale (WRQOLS) is a reliable QWL assessment tool for the nursing profession. To develop a Chinese version of the WRQOLS-2 and to examine its psychometric properties as an instrument to assess QWL for the nursing profession in China. Methods: Forward and back translating procedures were used to develop the Chinese version of WRQOLS-2. Six nursing experts participated in content validity evaluation and 352 registered nurses (RNs) participated in the tests. After a two-week interval, 70 of the RNs were retested. Structural validity was examined by principal components analysis and the Cronbach's alphas calculated. The respective independent sample t-test and intra-class correlation coefficient were used to analyze known-group validity and test-retest reliability. Results: One item was rephrased for adaptation to Chinese organizational cultures. The content validity index of the scale was 0.98. Principal components analysis resulted in a seven-factor model, accounting for 62% of total variance, with Cronbach's alphas for subscales ranging from 0.71 to 0.88. Known-group validity was established in the assessment results of the participants in permanent employment vs. contract employment (t = 2.895, p < 0.01). Good test-retest reliability was observed (r = 0.88, p < 0.01). Conclusion: The translated Chinese version of the WRQOLS-2 has sufficient validity and reliability so that it can be used to evaluate the QWL among nurses in mainland China.

• Journal of Forest and Environmental Science
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• v.36 no.2
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• pp.113-121
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• 2020

This study was carried out in degraded and non-degraded community forests (CF) in the Terai region of Kanchanpur district, Nepal. A total of 63 concentric sample plots each of 500 ㎡ was laid in the inventory for estimating above and below-ground biomass of forests by using systematic random sampling with a sampling intensity of 0.5%. Mallotus philippinensis and Shorea robusta were the most dominant species in degraded and non-degraded CF accounting Importance Value Index (I.V.I) of 97.16 and 178.49, respectively. Above-ground tree biomass carbon in degraded and non-degraded community forests was 74.64±16.34 t ha^-1 and 163.12±20.23 t ha^-1, respectively. Soil carbon sequestration in degraded and non-degraded community forests was 42.55±3.10 t ha^-1 and 54.21±3.59 t ha^-1, respectively. Hence, the estimated total carbon stock was 152.68±22.95 t ha^-1 and 301.08±27.07 t ha^-1 in degraded and non-degraded community forests, respectively. It was found that the carbon sequestration in the non-degraded community forest was 1.97 times higher than in the degraded community forest. CO₂ equivalent in degraded and non-degraded community forests was 553 t ha^-1 and 1105 t ha^-1, respectively. Statistical analysis showed a significant difference between degraded and non-degraded community forests in terms of its total biomass and carbon sequestration potential (p<0.05). Studies indicate that the community forest has huge potential and can reward economic benefits from carbon trading to benefit from the REDD⁺/CDM mechanism by promoting the sustainable conservation of community forests.