• Journal of the Korean Society of Environmental Restoration Technology
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• v.26 no.6
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• pp.21-32
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• 2023

The Environmental Impact Assessment (EIA) plays a pivotal role in predicting the potential environmental impacts of proposed developments and planning appropriate mitigation measures to minimize effects on species. However, as concerns over biodiversity loss rise, there's ongoing debate about the efficacy of these mitigation plans. In this study, we utilized data from EIAs and post-environmental impact surveys to understand the trends in biodiversity during construction and operation phases. By examining 30 urban development projects, we categorized species richness indices of mammals, birds, amphibians, and reptiles into pre-construction, during construction, and post-construction operational stages. The biodiversity trends were analyzed based on the rate of change in these indices. The results revealed three distinct biodiversity change patterns: (A) An initial increase in biodiversity indices post-development, followed by a gradual decline over time; (B) a sustained increase in biodiversity as a result of mitigation measures; and (C) a continuous decline in biodiversity post-development. Furthermore, all species exhibited a higher rate of biodiversity decline during the construction phase compared to the operational phase, with mammals showing the most significant rate of change. Notably, the biodiversity change rate during operation was generally lower than during construction. In particular, mammals seemed to be most influenced by mitigation measures, displaying the smallest rate of change. This study provides empirical evidence on the efficacy of mitigation measures and deliberates on ways to enhance their effectiveness in minimizing the adverse impacts of urban development on biodiversity. These findings can serve as foundational data for addressing terrestrial biodiversity reduction.

• Journal of Environmental Impact Assessment
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• v.30 no.2
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• pp.105-116
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• 2021

In the city of high population density crowded with buildings, Urban Heat Island (UHI) is intensified, and the city is vulnerable to thermal comfort. The maintenance of vacant land in downtown is treated as a factor that undermines the residential environment, spoils the urban landscape, and decreases the economic vitality of the whole region. Therefore, this study compared the effects on microclimate in the surrounding area according to the development scenarios targeting the vacant land in Songhyeon-dong, Jongno-gu, Seoul. The status quo, green oriented, building oriented and green-building mediation scenarios were established and ENVI-met was used to compare and analyze the impact of changes in wind speed, air temperature and mean radiant temperature (MRT) within 1 km of the target and the target site. The result of inside and 1 km radius the targeted area showed that the seasonal average temperature decreased and the wind speed increased when the green oriented scenario was compared with the current state one. It was expected that the temperature lowered to -0.73 ℃ or increased to 1.5 ℃ in summer, and the wind speed was affected up to 210 meters depending on the scenario. And it was revealed that green area inside the site generally affects inside area, but the layout and size of the buildings affect either internal and external area. This study is expected to help as a decision-making support tool for developing Songhyeon-dong area and to be used to reflect the part related to microclimate on the future environmental effects evaluation system.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.1-17
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• 2015

In this paper, we report what we have observed with regards to a prediction model for the military based on enlisted men's internal(cumulative records) and external data(SNS data). This work is significant in the military's efforts to supervise them. In spite of their effort, many commanders have failed to prevent accidents by their subordinates. One of the important duties of officers' work is to take care of their subordinates in prevention unexpected accidents. However, it is hard to prevent accidents so we must attempt to determine a proper method. Our motivation for presenting this paper is to mate it possible to predict accidents using enlisted men's internal and external data. The biggest issue facing the military is the occurrence of accidents by enlisted men related to maladjustment and the relaxation of military discipline. The core method of preventing accidents by soldiers is to identify problems and manage them quickly. Commanders predict accidents by interviewing their soldiers and observing their surroundings. It requires considerable time and effort and results in a significant difference depending on the capabilities of the commanders. In this paper, we seek to predict accidents with objective data which can easily be obtained. Recently, records of enlisted men as well as SNS communication between commanders and soldiers, make it possible to predict and prevent accidents. This paper concerns the application of data mining to identify their interests, predict accidents and make use of internal and external data (SNS). We propose both a topic analysis and decision tree method. The study is conducted in two steps. First, topic analysis is conducted through the SNS of enlisted men. Second, the decision tree method is used to analyze the internal data with the results of the first analysis. The dependent variable for these analysis is the presence of any accidents. In order to analyze their SNS, we require tools such as text mining and topic analysis. We used SAS Enterprise Miner 12.1, which provides a text miner module. Our approach for finding their interests is composed of three main phases; collecting, topic analysis, and converting topic analysis results into points for using independent variables. In the first phase, we collect enlisted men's SNS data by commender's ID. After gathering unstructured SNS data, the topic analysis phase extracts issues from them. For simplicity, 5 topics(vacation, friends, stress, training, and sports) are extracted from 20,000 articles. In the third phase, using these 5 topics, we quantify them as personal points. After quantifying their topic, we include these results in independent variables which are composed of 15 internal data sets. Then, we make two decision trees. The first tree is composed of their internal data only. The second tree is composed of their external data(SNS) as well as their internal data. After that, we compare the results of misclassification from SAS E-miner. The first model's misclassification is 12.1%. On the other hand, second model's misclassification is 7.8%. This method predicts accidents with an accuracy of approximately 92%. The gap of the two models is 4.3%. Finally, we test if the difference between them is meaningful or not, using the McNemar test. The result of test is considered relevant.(p-value : 0.0003) This study has two limitations. First, the results of the experiments cannot be generalized, mainly because the experiment is limited to a small number of enlisted men's data. Additionally, various independent variables used in the decision tree model are used as categorical variables instead of continuous variables. So it suffers a loss of information. In spite of extensive efforts to provide prediction models for the military, commanders' predictions are accurate only when they have sufficient data about their subordinates. Our proposed methodology can provide support to decision-making in the military. This study is expected to contribute to the prevention of accidents in the military based on scientific analysis of enlisted men and proper management of them.

• 한국사회정책
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• v.25 no.2
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• pp.367-402
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• 2018

This study analyzed the relationship between the act on the guarantee of rights of and support for persons with developmental disabilities(Act for PWDD) and the similar ordinance of the local governments based on this law and focused on the correspondence(the rate of reflection) and the autonomy(differentiation). As of October 2017, 63 local government regulations and Act for PWDD were analyzed in this study. The results of the analysis are as follows: First, the rate of reflection in the ordinance of Act for PWDD was different according to the clause. In the aspect of emphasizing welfare support, the agreement between local ordinance and rate was high. While the Act for PWDD emphasized the rights of persons with developmental disabilities, there was little information about their right in the ordinance of local governments. This is evidence that current ordinance is based on the protective point of view for people with developmental disabilities. In the future, policy measures will be needed to ensure that respect for decision-making by persons with developmental disabilities and rights guarantees are included in the bylaws. Second, there is a provision that the rate of ordinance reflection is 0%, which may be guaranteed by other laws in the area, so it does not mean the absence of related system in the region, but there is possibility of institutional blind spot. In the future, consideration should be given to the complementarity of other legal systems in the area with developmental disabilities, so that persons with developmental disabilities should not be placed in institutional blind spots. Third, the autonomy(differentiation) of local ordinance was examined from the contents aspect and the administrative aspect to help practical implementation. The differentiation between the ordinances vary. Emphasizing the responsibilities of the head of the organization, emphasizing the fact-finding survey, setting up the welfare committee, or adding local needs were included to the ordinance. Local governments considering the enactment of ordinances in the future should refer to these cases and establish enactable local ordinances that take advantage of the characteristics of local autonomy.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.237-262
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• 2022

There has been a growing interest in IPOs (Initial Public Offerings) due to the profitable returns that IPO stocks can offer to investors. However, IPOs can be speculative investments that may involve substantial risk as well because shares tend to be volatile, and the supply of IPO shares is often highly limited. Therefore, it is crucially important that IPO investors are well informed of the issuing firms and the market before deciding whether to invest or not. Unlike institutional investors, individual investors are at a disadvantage since there are few opportunities for individuals to obtain information on the IPOs. In this regard, the purpose of this study is to provide individual investors with the information they may consider when making an IPO investment decision. This study presents a model that uses machine learning and text analysis to predict whether an IPO stock price would move up or down after the first 5 trading days. Our sample includes 691 Korean IPOs from June 2009 to December 2020. The input variables for the prediction are three tone variables created from IPO prospectuses and quantitative variables that are either firm-specific, issue-specific, or market-specific. The three prospectus tone variables indicate the percentage of positive, neutral, and negative sentences in a prospectus, respectively. We considered only the sentences in the Risk Factors section of a prospectus for the tone analysis in this study. All sentences were classified into 'positive', 'neutral', and 'negative' via text analysis using TF-IDF (Term Frequency - Inverse Document Frequency). Measuring the tone of each sentence was conducted by machine learning instead of a lexicon-based approach due to the lack of sentiment dictionaries suitable for Korean text analysis in the context of finance. For this reason, the training set was created by randomly selecting 10% of the sentences from each prospectus, and the sentence classification task on the training set was performed after reading each sentence in person. Then, based on the training set, a Support Vector Machine model was utilized to predict the tone of sentences in the test set. Finally, the machine learning model calculated the percentages of positive, neutral, and negative sentences in each prospectus. To predict the price movement of an IPO stock, four different machine learning techniques were applied: Logistic Regression, Random Forest, Support Vector Machine, and Artificial Neural Network. According to the results, models that use quantitative variables using technical analysis and prospectus tone variables together show higher accuracy than models that use only quantitative variables. More specifically, the prediction accuracy was improved by 1.45% points in the Random Forest model, 4.34% points in the Artificial Neural Network model, and 5.07% points in the Support Vector Machine model. After testing the performance of these machine learning techniques, the Artificial Neural Network model using both quantitative variables and prospectus tone variables was the model with the highest prediction accuracy rate, which was 61.59%. The results indicate that the tone of a prospectus is a significant factor in predicting the price movement of an IPO stock. In addition, the McNemar test was used to verify the statistically significant difference between the models. The model using only quantitative variables and the model using both the quantitative variables and the prospectus tone variables were compared, and it was confirmed that the predictive performance improved significantly at a 1% significance level.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.67-86
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• 2020

Recommender Systems have been huge influence users and business more and more. Recently the importance of E-commerce has been reached rapid growth greatly in world-wide COVID-19 pandemic. Recommender system is the center of E-commerce lively. Top ranked E-commerce managers mentioned that recommender systems have a major influence on customer's purchase such as about 50% of Netflix, Amazon sales from their recommender systems. Most algorithms have been focused on improving accuracy of recommender system regardless of novelty, diversity, serendipity etc. Recommender systems with only high accuracy cannot satisfy business long-term profit because of generating sales polarization. In addition, customers do not experience enjoyment of shopping from only focusing accuracy recommender system because customer's preference is changed constantly. Therefore, recommender systems with various values need to be developed for user's high satisfaction. Reranking is the most useful methodology to realize diversity of recommender system. In this paper, diversity of recommender system is represented through constructing high similarity with users who have different preference using each user's purchased item's category algorithm. It is distinguished from past research approach which is changing the algorithm of recommender system without user's diversity preference level. We tried to discover user's diversity preference level and observed the results how the effect was different according to user's diversity preference level. In addition, graph-based recommender system was used to show diversity through user's network, not collaborative filtering. In this paper, Amazon Grocery and Gourmet Food data was used because the low-involvement product, such as habitual product, foods, low-priced goods etc., had high probability to show customer's diversity. First, a bipartite graph with users and items simultaneously is constructed to make graph-based recommender system. However, each users and items unipartite graph also need to be established to show diversity of recommender system. The weight of each unipartite graph has played crucial role changing Jaccard Distance of item's category. We can observe two important results from the user's unipartite network. First, the user's diversity preference level is observed from the network and second, dissimilar users can be discovered in the user's network. Through the research process, diversity of recommender system is presented highly with small accuracy loss and optimalization for higher accuracy is possible controlling diversity ratio. This paper has three important theoretical points. First, this research expands recommender system research for user's satisfaction with various values. Second, the graph-based recommender system is developed newly. Third, the evaluation indicator of diversity is made for diversity. In addition, recommender systems are useful for corporate profit practically and this paper has contribution on business closely. Above all, business long-term profit can be improved using recommender system with diversity and the recommender system can provide right service according to user's diversity level. Lastly, the corporate selling low-involvement products have great effect based on the results.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.4
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• pp.47-52
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• 2014

Species distribution models have been widely applied in order to assess biodiversity, design reserve, manage habitat and predict climate change. However, SDMs has been used restrictively to the public and policy sectors owing to model uncertainty. Recent studies on ensemble and consensus models have been increased to reduce model uncertainty. This paper was carried out single model and multi model for Corylopsis coreana and compares two models. First, model evaluation was used AUC, kappa and TSS. TSS was the most effective method because it was easy to compare several models and convert binary maps. Second, both single and ensemble model show good performance and RF, Maxent and GBM was evaluated higher, GAM and SRE was evaluated lower relatively. Third, ensemble model tended to overestimate over single model. This problem can be solved by the suitable model selection and weighting through collaboration between field experts and modeler. Finally, we should identify causes and magnitude of model uncertainty and improve data quality and model methods in order to apply special decision-making support system and conservation planning, and when we make policy decisions using SDMs, we should recognize uncertainty and risk.

• Journal of the Ergonomics Society of Korea
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• v.36 no.5
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• pp.525-533
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• 2017

Objective: The aim of this study is to investigate maritime officers' strategies to avoid the ship collision in crossing situations. Background: In a situation where there is a risk of collision between two ships, maritime officers can change the direction and speed of the own-ship to avoid the collision. They have four options to select; adjusting the speed only, the direction only, both the speed and direction at the same time and no action. Research questions were whether the strategy they are using differs according to the shipboard experience of maritime officers and the representation method of ARPA (automatic radar plotting aid) - radar graphic information. Method: Participants were 12. Six of them had more than 3 years of onboard experience, while the others were 4th grade students at Korea Maritime and Ocean University. For each participant, 32 ship encounter situations were provided with ARPA-radar information. 16 situations were presented by the north-up display and 16 situations were presented by the track-up display. Participants were asked to decide how to move the own-ship to avoid the ship collision for each case. Results: Most participants attempted to avoid the collision by adjusting the direction of the ship, representing an average of 22.4 times in 32 judgment trials (about 70%). Participants who did not have experience on board were more likely to control speed and direction at the same time than participants with onboard experience. Participants with onboard experience were more likely to control the direction of the ship only. On the other hand, although the same ARPA Information was provided to the participants, the participants in many cases made different judgments depending on the method of information representation; track-up display and north-up display. It was only 25% that the participants made the same judgment under the same collision situations. Participants with onboard experience did make the same judgment more than participants with no onboard experience. Conclusion: In marine collision situations, maritime officers tend to avoid collisions by adjusting only the direction of their ships, and this tendency is more pronounced among maritime officers with onboard experience. The effect of the method of information representation on their judgment was not significant. Application: The results of this research might help to train maritime officers for safe navigation and to design a collision avoidance support system.

• Industry Promotion Research
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• v.5 no.3
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• pp.145-155
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• 2020

Co-operatives are a deep-rooted organization that was first organized in Britain in the 19th century and spread to Europe and North America in the early 20th century and to the rest of the world from the mid-20th century. Cooperative in Italy are fraternal (friendly societies) separated from religion, and in the early days of socialism and the late 19th century Catholic Italy, but independent of activity. And the Church's social participation, as well as multiple personalities. Therefore, the purpose of this study is to study the laws and institutions of Italian cooperatives. And let's look at how the laws and systems of Italian co-operatives support society and the national economy. Specifically, firstly, based on prior research, the concept of co-operatives and the cooperative movement and social values are considered. Second, review the development process and characteristics of Italian co-operatives and the legal system. Third, I would like to analyze the case of Italian co-operatives. Fourth, suggest implications according to the results of the study. The results of the study suggested the following. First, the attitude such as attachment and sincerity of representatives and staff of village enterprises is very important. Second, all members of the organization should participate in decision making with empathy and attachment to the vision of the village enterprise. Third, it should be highly likely that village enterprises, which can draw capital from outside according to the needs of the organization, will generate higher economic results. Fourth, it is important to establish a model of mind enterprise by presenting factors and success factors in establishing a village enterprise based on cases and theories. In conclusion, Co-operatives should contribute to social contribution rather than economic profit-seeking.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.11
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• pp.155-167
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• 2016

Technology valuation is necessary for determining the feasibility of technology commercialization. However, existing methods focus only on technology evaluation, with limitation in sufficiently reflecting buyer viewpoint. In addition, it causes a gap between estimated value and market value. Therefore, this research suggests a new technology valuation method which focuses on the perspectives of buyers. Technology factors, buyer factors and market factors are first determined and their relationships are analyzed. Second, based on the relationships, profit projections are calculated using the discount cash flow method. Finally, profit projections for each year are discounted. The proposed method was applied using the ubiquitous home network system and audio service and illumination control method and results compared with the value of a technology valuation guide distributed by the Ministry of Trade, Industry and Energy. The technology valuation approach used in this research is quantitative and systematic and can be used as a decision making support tool in technology transfer, reflecting various perspectives of stakeholders.