• Journal of Cadastre & Land InformatiX
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• v.48 no.2
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• pp.79-98
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• 2018

The purpose of this study is to suggest a model analysing spatio-temporal characteristics of the civil complaints for the officially assessed land price based on big data mining. Specifically, in this study, the underlying reasons for the civil complaints were found from the spatio-temporal perspectives, rather than the institutional factors, and a model was suggested monitoring a trend of the occurrence of such complaints. The official documents of 6,481 civil complaints for the officially assessed land price in the district of Jung-gu of Incheon Metropolitan City over the period from 2006 to 2015 along with their temporal and spatial poperties were collected and used for the analysis. Frequencies of major key words were examined by using a text mining method. Correlations among mafor key words were studied through the social network analysis. By calculating term frequency(TF) and term frequency-inverse document frequency(TF-IDF), which correspond to the weighted value of key words, I identified the major key words for the occurrence of the civil complaint for the officially assessed land price. Then the spatio-temporal characteristics of the civil complaints were examined by analysing hot spot based on the statistics of Getis-Ord $Gi^*$. It was found that the characteristic of civil complaints for the officially assessed land price were changing, forming a cluster that is linked spatio-temporally. Using text mining and social network analysis method, we could find out that the occurrence reason of civil complaints for the officially assessed land price could be identified quantitatively based on natural language. TF and TF-IDF, the weighted averages of key words, can be used as main explanatory variables to analyze spatio-temporal characteristics of civil complaints for the officially assessed land price since these statistics are different over time across different regions.

• Korean Journal of Construction Engineering and Management
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• v.20 no.4
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• pp.22-33
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• 2019

The government has steadily revised and developed laws and systems for activating remodeling of apartments in response to the problems of aged apartments. However, despite such efforts, remodeling has yet to be activated. For many reasons, this study noted that there were no tools for reasonable profitability judgements and decision making in the preliminary stages of the remodeling project. Thus, the feasibility evaluation model was developed. Generally, the profitability judgements are made after the conceptual design. However, decisions to drive remodeling projects are made at the preliminary stage. So a feasibility evaluation model is required at the preliminary stage. Accordingly, In this study, a feasibility evaluation model was developed for determining preliminary stage profitability. Construction costs, business expenses, financial expenses, and generally sales revenue were calculated using the initial available information and remodeling variables derived through the existing cases. Through this process, we developed an algorithm that can give an overview of the return on investment. In addition, the preliminary stage feasibility evaluation model developed was applied to three cases to verify the applicability of the model. Although applied in three cases, the difference between the model's forecast and actual case values is less than 5%, which is considered highly applicable. If cases are expanded in the future, it will be a useful tool that can be used in actual work. The feasibility evaluation model developed in this study will support decision making by union members, and if the model is applied in different regions, it will be expected to help local governments to understand the size of possible remodeling projects.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.99-122
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• 2019

According to the recent IDC (International Data Corporation) report, as from 2025, the total volume of data is estimated to reach ten times higher than that of 2016, corresponding to 163 zettabytes. then the main body of generating information is moving more toward corporations than consumers. So-called "the wave of Big-data" is arriving, and the following aftermath affects entire industries and firms, respectively and collectively. Therefore, effective management of vast amounts of data is more important than ever in terms of the firm. However, there have been no previous studies that measure the effects of big data investment, even though there are number of previous studies that quantitatively the effects of IT investment. Therefore, we quantitatively analyze the Big-data investment effects, which assists firm's investment decision making. This study applied the Event Study Methodology, which is based on the efficient market hypothesis as the theoretical basis, to measure the effect of the big data investment of firms on the response of market investors. In addition, five sub-variables were set to analyze this effect in more depth: the contents are firm size classification, industry classification (finance and ICT), investment completion classification, and vendor existence classification. To measure the impact of Big data investment announcements, Data from 91 announcements from 2010 to 2017 were used as data, and the effect of investment was more empirically observed by observing changes in corporate value immediately after the disclosure. This study collected data on Big Data Investment related to Naver 's' News' category, the largest portal site in Korea. In addition, when selecting the target companies, we extracted the disclosures of listed companies in the KOSPI and KOSDAQ market. During the collection process, the search keywords were searched through the keywords 'Big data construction', 'Big data introduction', 'Big data investment', 'Big data order', and 'Big data development'. The results of the empirically proved analysis are as follows. First, we found that the market value of 91 publicly listed firms, who announced Big-data investment, increased by 0.92%. In particular, we can see that the market value of finance firms, non-ICT firms, small-cap firms are significantly increased. This result can be interpreted as the market investors perceive positively the big data investment of the enterprise, allowing market investors to better understand the company's big data investment. Second, statistical demonstration that the market value of financial firms and non - ICT firms increases after Big data investment announcement is proved statistically. Third, this study measured the effect of big data investment by dividing by company size and classified it into the top 30% and the bottom 30% of company size standard (market capitalization) without measuring the median value. To maximize the difference. The analysis showed that the investment effect of small sample companies was greater, and the difference between the two groups was also clear. Fourth, one of the most significant features of this study is that the Big Data Investment announcements are classified and structured according to vendor status. We have shown that the investment effect of a group with vendor involvement (with or without a vendor) is very large, indicating that market investors are very positive about the involvement of big data specialist vendors. Lastly but not least, it is also interesting that market investors are evaluating investment more positively at the time of the Big data Investment announcement, which is scheduled to be built rather than completed. Applying this to the industry, it would be effective for a company to make a disclosure when it decided to invest in big data in terms of increasing the market value. Our study has an academic implication, as prior research looked for the impact of Big-data investment has been nonexistent. This study also has a practical implication in that it can be a practical reference material for business decision makers considering big data investment.

• Journal of Bio-Environment Control
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• v.28 no.3
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• pp.243-254
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• 2019

With the recent accelerated policy-making and interests in new renewable energy, plans to develop and supply the new renewable energy have been devised across multiple regions in Korea. Solar energy, in particular, is being applied to small-scale power supply in provincial areas, as solar cells are used to convert solar energy into electric energy to produce electric power. Nonetheless, in the case of solar power plants, the need for a large stretch of land and considerable sum of financial support implies that the planning step should take into consideration the most suitable meteorological and geographical factors. In this study, the proxy variables of meteorological and geographical factors associated with solar energy were considered in analyzing the vulnerable areas regarding the photovoltaic power generation facility across the nation. GIS was used in the spatial analysis to develop a map for assessing the optimal location for photovoltaic power generation facility. The final vulnerability map developed in this study did not reveal any areas that exhibit vulnerability level 5 (very high) or 1 (very low). Jeollanam-do showed the largest value of vulnerability level 4 (high), while a large value of vulnerability level 3 (moderate) was shown by several administrative districts including Gwangju metropolitan city, Jeollabuk-do, Chungcheongbuk-do, and Gangwon-do. A value of vulnerability level 2 (low) was shown by the metropolitan cities including Daegu, Ulsan, and Incheon. When the 30 currently operating solar power plants were compared and reviewed, most were found to be in an area of vulnerability level 2 or 3, indicating that the locations were relatively suitable for solar energy. However, the limited data quantity for solar power plants, which is the limitation of this study, prevents the accuracy of the findings to be clearly established. Nevertheless, the significance of this study lies in that an attempt has been made to assess the vulnerability map for photovoltaic power generation facility targeting various regions across the nation, through the use of the GIS-based spatial analysis technique that takes into account the diverse meteorological and geographical factors. Furthermore, by presenting the data obtained for all regions across the nation, the findings of this study are likely to prove useful as the basic data in fields related to the photovoltaic power generation.

• Sleep Medicine and Psychophysiology
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• v.26 no.1
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• pp.33-43
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• 2019

Objectives: Bipolar disorder is characterized by repetitive relapses that result in psychosocial dysfunctions. The functioning of bipolar disorder patients is related to the severity of symptoms, quality of sleep, drug compliance, and social support. The purpose of this study was to investigate the association between sociodemographic and clinical factors and functional status in bipolar disorder patients. Methods: A total of 52 bipolar disorder patients participated in the study. The following scales were utilized: Korean version of personal and social performance scale (K-PSP), Korean version of Hamilton rating scale for depression (K-HDRS), Korean version of young mania rating scale (K-YMRS), Korean version of pittsburgh sleep quality index (PSQI-K), Korean version of drug attitude inventory (K-DAI), mood disorders insight scale (MDIS), and multidimensional scale of perceived social support (MSPSS). Results: The K-PSP score showed a negative relationship with K-HDRS score (r = -0.387, p = 0.005), but not with K-YMRS score (r = -0.205, p = 0.145). The K-PSP score showed a negative relationship with global PSQI-K score (r = -0.378, p = 0.005) and overall sleep quality (r = -0.353, p = 0.010). The K-PSP scores were positively associated with the KDAI score (r = 0.409, p = 0.003) and MSPSS score (r = 0.334, p = 0.015). The predictive factors for K-PSP were overall sleep quality and social support from family. Conclusion: Our study showed that depressive symptoms were related to overall function in bipolar disorder. Also, our study suggested that improving sleep quality is important in maintaining functional status. Appropriate social support and positive perception toward the drug may lead to the higher level of functioning. This study is meaningful in that the functional status of bipolar disorder patients is analyzed in a multivariate manner in relation to various variables in psychosocial aspects.

• Korean Journal of Child Education & Care
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• v.19 no.2
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• pp.177-196
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• 2019

Objective: This study aims to analyze research trends related to software education for young children, focusing on studies published in Korea from 2016 to 2019 March. Methods: A total of 26 research publications on software education for young children, searched from Korea Citation Index and Research Information Sharing Service were identified for the analysis. The trend in these publications was classified and examined respectively by publication dates, types of publications, and the fields of study. To investigate a means of research, the analysis included key topics, types of research methods, and characteristics of the study variables. Results: The results of the analysis show that the number of publications on the topic of software education for young children has increased over the three years, of which most were published as a scholarly journal article. Among the 26 research studies analyzed, 16 (61.5%) are related to the field of early childhood education or child studies. Key topics and target subjects of the most research include the curriculum development of software education for young children or the effectiveness of software education on 4- and 5-year-old children. Most of the analyzed studies are experimental research designs or in the form of literature reviews. The most frequently studied research variable is young children's cognitive characteristics. For the studies that employ educational programs, the use of a physical computing environment is prevalent, and the most frequently used robot as a programming tool is "Albert". The duration of the program implementation varies, ranging from 5 weeks to 48 weeks. In the analyzed research studies, computational thinking is conceptualized as a problem-solving skill that can be improved by software education, and assessed by individual instruments measuring sub-factors of computational thinking. Conclusion/Implications: The present study reveals that, although the number of research publications in software education for young children has increased, the overall sufficiency of the accumulated research data and a variety of research methods are still lacking. An increased interest in software education for young children and more research activities in this area are needed to develop and implement developmentally appropriate software education programs in early childhood settings.

• Journal of Wetlands Research
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• v.21 no.2
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• pp.102-113
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• 2019

Slack-tide sampling was carried out at 6 stations at high and low tide for a tidal cycle during spring tide of the early summer (June) and summer (July, August) of 2016 to determine the difference of water quality according to tide in Masan Bay, Korea. The mixing regime of all the water quality components investigated was well explained through the correlation with SAL. In the early summer and summer, TURB, DSi and NNN which mainly flow into the bay from the streams and SS, COD, AMN and $H_2S$ which mainly indicate the internal sink and source materials have a property of conservative mixing and non-conservative mixing, respectively. The conservative mixing showed a good linear relationship of the water quality between high and low tide, and the non-conservative mixing showed a variation of different pattern each other. Factor analysis performed on the concentration difference data sets between high and low tide helped in identifying the principal latent variables for them. In early summer, multiple effects (tidal action, natural influx and internal sinks and sources etc.) acted in combination for the differences to be distributed evenly in four factors (VF1~4), since there were few allochthonous inputs as a low-water season. On the contrary, in summer, the parameters showing large concentration difference at ST-1 affected by stream water were concentrated in one factor (VF1) and clearly distinguished from the parameters affected by the internal sinks and sources. In fact, there is no estuary (bay) that always maintains steady state flow conditions. The mixing regime of an estuary might be changed at any time due to the change of flushing time, and furthermore the change of end-member conditions due to the internal sinks and sources makes the occurrence of concentration difference inevitable. Therefore, when investigating the water quality of the estuary, it is necessary to take a sampling method considering the tide to obtain average water quality data.

• Clean Technology
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• v.25 no.2
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• pp.129-139
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• 2019

Bamboo is an evergreen perennial plant, and it is known as one of the most productive and fastest-growing plants in the world. It grows quickly in moderate climates with only moderate water and fertilizer. Traditionally in Asia, bamboo is used for building materials, as a food source, and as versatile raw materials. Bamboo as a biomass feedstock can be transformed to prepare activated carbon using the thermal treatment of pyrolysis. The effect of process variables such as carbonization temperature, activation temperature, activation time, the amount of steam, and the mixing ratio of phosphoric acid and bamboo were systematically investigated to optimize the preparation conditions. Steam activation was proceeded after carbonization with a vapor flow rate of $0.8{\sim}1.8mL-H_2O\;g-char^{-1}\;h^{-1}$ and activation time of 1 ~ 3 h at $700{\sim}900^{\circ}C$. Carbon yield and surface area reached 2.04 ~ 20.59 wt% and $499.17{\sim}1074.04m^2\;g^{-1}$, respectively, with a steam flow rate of $1.4mL-H_2O\;g-char^{-1}\;h^{-1}$ for 2 h. Also, the carbon yield and surface area were 24.67 wt% and $1389.59m^2\;g^{-1}$, respectively, when the bamboo and phosphoric acid were mixed in a 1:1 weight ratio ($700^{\circ}C$, 2 h, $1.4mL-H_2O\;g-char^{-1}\;h^{-1}$). The adsorption of methylene blue into the bamboo activated carbon was studied based on pseudo first order and second order kinetics models. The adsorption kinetics were found to follow the pseudo second order model, which is governed by chemisorption.

• 한국노년학
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• v.36 no.3
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• pp.673-691
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• 2016

As the provision of long-term care policy takes root and with a gradual increase in elderly population, the use of elderly care service has become a growing norm. More than ever, there exists an urgent need for a paradigm shift in the building of an institutional basis for the improvement of care service, from the prevalent practice of 'need based service' toward the concept of 'human rights based service'. A great focus is being shed on care-workers, at the 'front line' of advocating human rights, as their human rights advocacy behaviour is seen as a key variable in providing high quality care service for elders. This study aims to examine how care-workers' individual human rights awareness levels, and the influence of their respective organizations, as an environmental factor, affect their human rights advocacy behaviour. The study includes a comprehensive analysis of the interactions between the regulatory effect of environmental factors (service orientation?) on an organizational level, human rights awareness (individual level) and the service environment (organizational). The analysis sample consisted of 782 registered non-profit corporation of long-term care facilities all over the country in 2014. The findings of the thesis suggest that human rights awareness at individual levels has a significant influence on human rights advocacy behavior. The interaction of human resources management in service orientations was also found to influence human rights advocacy on a significant level. Both human rights awareness at individual level and service orientations at organizational level were thus determined as key variables for improving the human rights awareness of care worker in long-term care facilities in Korea.

• Journal of The Korean Society of Emergency Medicine
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• v.29 no.5
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• pp.465-473
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• 2018

Objective: We evaluated the clinical characteristics and prognoses of patients with septic shock who transferred to the emergency department (ED) in a tertiary referral center. Methods: This study was performed using a prospective, multi-center registry of septic shock, with the participation of 11 tertiary referral centers in the Korean Shock Society between October 2015 and February 2017. We classified the patients as a transferred group who transferred from other hospitals after meeting the inclusion criteria upon ED arrival and a non-transferred group who presented directly to the ED. Primary outcome was hospital mortality. We conducted multiple logistic regression analysis to assess variables related to in-hospital mortality. Results: A total of 2,098 patients were included, and we assigned 717 patients to the transferred group and 1,381 patients to the non-transferred group. The initial Sequential Organ Failure Assessment score was higher in the transferred group than the non-transferred group (6; interquartile range [IQR], 4-9 vs. 6; IQR, 4-8; P<0.001). Mechanical ventilator (29% vs. 21%, P<0.001) and renal replacement therapy (12% vs. 9%, P=0.034) within 24 hours after ED arrival were more frequently applied in the transferred group than the non-transferred group. Overall hospital mortality was 22% and there was no significant difference between transferred and non-transferred groups (23% vs. 22%, P=0.820). Multivariable analysis showed an odds ratio for in-hospital mortality of 1.00 (95% confidence interval, 0.78-1.28; P=0.999) for the transferred group compared with the non-transferred group. Conclusion: The transferred group showed higher severity and needed more organ support procedures than the non-transferred group. However, inter-hospital transfer did not affect in-hospital mortality.