• Journal of the Korean Society of Environmental Restoration Technology
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• v.25 no.4
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• pp.49-65
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• 2022

Since trees in the city are green assets that create a healthy environment for the city, systematic management of trees improves urban ecosystem services. The sporadic urban tree information centered on the site is vast, and it is difficult to manage the data, so efforts to increase efficiency are needed. This paper summarizes tree data inventory based on data constructed by Seoul Green Trust activists and constructs and discloses online database maps using Tableau Software. In order to verify the utilization of the map, we divided into consumer and supplier aspects to collect various opinions and reflect feedback to implement tree database maps for each area and species of Seoul Forest. As a result, the utilization value of tree database in urban parks was presented. The technical significance of this study is to systematically record the process of constructing and implementing a dashboard directly using the Mapbox platform and Tableau Software in the field of landscaping for the first time in Korea. In addition, the implications and supplements of landscape information were derived by collecting user opinions on the results. This can be used as an exploratory basis in the process of developing online-based services such as web and apps by utilizing landscaping tree information in the future. Although the visualization database currently constructed has limitations that ordinary users cannot interact in both directions because it utilizes business intelligence tools in terms of service provision it has affirmed both the database construction and its usability in web public format. In the future it is essential to investigate the assets of the trees in the city park and to build a database as a public asset of the city. The survey participants positively recognized that information is intuitively presented based on the map and responded that it is necessary to provide information on the overall urban assets such as small parks and roadside trees by using open source maps in the future.

• Journal of the Korean Institute of Navigation
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• v.19 no.3
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• pp.35-65
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• 1995

The development of Korean shipping industry is maybe defined into three development stages-industry fixing stage, industry coordinating stage, industry development stage-. The development of shipping industry has been depended on the geovernment/authority role such as shipping policy, system, law, rules and regulations. In 1983, Korean shipping industry reorganization and coordination by shipping authority have made our shipping industry on the stable condition together with each company's efforts. Today's world economic environment such WTO/UR negotiation results get this government role limited. According to the being reduced government role, each company's competitive advantage power becomes more important. Besides, korean shipping industry is exposed into the entire and bitter world competition. In order to win and prevent the world shipping competition, it is necessary to look out the competitive advantage power of Korean shipping industry. The first purpose of this study is the situation analysis for competitive advantage power of Korean shipping industry. The second is to compare with our shipping policies with foreign ones concerned with ship, cargo, crew, tax and others. But in order to compare with foreign shipping, this study need their shipping statistics data, this study has some limit of the foreign data. This study has been carried on the basis of the following items. 1. Shipping environment, 2. Ships and ship acquirement(shipbuilding/purchasing), 3. Oceangoing cargo and ship's stowage rate, 4. Human factor in shipping-crew, 5. The incomes and costs in finacial statements. We have some conclusions as following through the this study. First, Korean shipping industry environment-competitive disadvantage situation- has changed rapidly due to the shipping market opening, free market entering of foreign shipping. Second, Korean shipping is disadvantageous due to the high tax rate and financing conditions in connection with ship acquirement. In order to improve the competitive advantage power, the shipping tax system and ship financing conditions should be reviewed to profitable for owners. Third, but both world and Korean oceangoing cargoes quantity have been increased annualy, Korean ship's cargo stowage rate is being decreased. This is serious situation but Korean shipping take well use of foreign vessel with hire. It is recommended to take use of owner's vessel and hired ones in the long range view, considering the world shipping management. But the number of crew has been decreased by 2, 000~3, 000 annualy, it is desirable that the long sea-experienced crew have been increased. Almost of owners usauly complain the crew cost is the main obstacles to competitive advantage power. Human factor is the most important firm's asset. All owners should pay attention to this though, and invest the proper budget to training, education, welfare as much as possible. In the long run this effects could be feedback to owners. Fifth, We must improve the financial statements structure, that is, the first step is to increase income, the second is to decrease cost, the third is to increase income on the same cost, the fourth is to decrease cost on the same income. It is essential to find out what the urgent investment is and what unnecessary cost is. At last, in order to competite world shipping race, each shipping firm must try for himself to retain the power. The government/authority is no longer dependable. I believe that each firm's power will be the industry's power, the industry's power will be the nations's power.

• The Journal of Bigdata
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• v.5 no.1
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• pp.155-180
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• 2020

It takes the most important role the problem of assigining vehicles and desigining optimal routes for each vehicle in order to enhance the logistics service level. While solving the problem, various cost factors such as number of vehicles, the capacity of vehicles, total travelling distance, should be considered at the same time. Although most of logistics service providers introduced the Transportation Management System (TMS), the system has the limitation which can not consider the practical constraints. In order to make the solution of TMS applicable, it is required experts revised the solution of TMS based on their own experience and intuition. In this research, different from previous research which have focused on minimizing the total cost, it has been proposed the methodology which can enhance the efficiency and fairness of asset utilization, simultaneously. First of all, it has been adopted the Cluster-First Route-Second (CFRS) approach. Based on the location of customers, we have grouped customers as clusters by using four different clustering algorithm such as K-Means, K-Medoids, DBSCAN, Model-based clustering and a procedural approach, Fisher & Jaikumar algorithm. After getting the result of clustering, it has been developed the optiamal vehicle routes within clusters. Based on the result of numerical experiments, it can be said that the propsed approach based on CFRS may guarantee the better performance in terms of total travelling time and distance. At the same time, the variance of travelling distance and number of visiting customers among vehicles, it can be concluded that the proposed approach can guarantee the better performance of assigning tasks in terms of fairness.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.79-99
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• 2015

The prediction of bankruptcy has been extensively studied in the accounting and finance field. It can have an important impact on lending decisions and the profitability of financial institutions in terms of risk management. Many researchers have focused on constructing a more robust bankruptcy prediction model. Early studies primarily used statistical techniques such as multiple discriminant analysis (MDA) and logit analysis for bankruptcy prediction. However, many studies have demonstrated that artificial intelligence (AI) approaches, such as artificial neural networks (ANN), decision trees, case-based reasoning (CBR), and support vector machine (SVM), have been outperforming statistical techniques since 1990s for business classification problems because statistical methods have some rigid assumptions in their application. In previous studies on corporate bankruptcy, many researchers have focused on developing a bankruptcy prediction model using financial ratios. However, there are few studies that suggest the specific types of bankruptcy. Previous bankruptcy prediction models have generally been interested in predicting whether or not firms will become bankrupt. Most of the studies on bankruptcy types have focused on reviewing the previous literature or performing a case study. Thus, this study develops a model using data mining techniques for predicting the specific types of bankruptcy as well as the occurrence of bankruptcy in Korean small- and medium-sized construction firms in terms of profitability, stability, and activity index. Thus, firms will be able to prevent it from occurring in advance. We propose a hybrid approach using two artificial neural networks (ANNs) for the prediction of bankruptcy types. The first is a back-propagation neural network (BPN) model using supervised learning for bankruptcy prediction and the second is a self-organizing map (SOM) model using unsupervised learning to classify bankruptcy data into several types. Based on the constructed model, we predict the bankruptcy of companies by applying the BPN model to a validation set that was not utilized in the development of the model. This allows for identifying the specific types of bankruptcy by using bankruptcy data predicted by the BPN model. We calculated the average of selected input variables through statistical test for each cluster to interpret characteristics of the derived clusters in the SOM model. Each cluster represents bankruptcy type classified through data of bankruptcy firms, and input variables indicate financial ratios in interpreting the meaning of each cluster. The experimental result shows that each of five bankruptcy types has different characteristics according to financial ratios. Type 1 (severe bankruptcy) has inferior financial statements except for EBITDA (earnings before interest, taxes, depreciation, and amortization) to sales based on the clustering results. Type 2 (lack of stability) has a low quick ratio, low stockholder's equity to total assets, and high total borrowings to total assets. Type 3 (lack of activity) has a slightly low total asset turnover and fixed asset turnover. Type 4 (lack of profitability) has low retained earnings to total assets and EBITDA to sales which represent the indices of profitability. Type 5 (recoverable bankruptcy) includes firms that have a relatively good financial condition as compared to other bankruptcy types even though they are bankrupt. Based on the findings, researchers and practitioners engaged in the credit evaluation field can obtain more useful information about the types of corporate bankruptcy. In this paper, we utilized the financial ratios of firms to classify bankruptcy types. It is important to select the input variables that correctly predict bankruptcy and meaningfully classify the type of bankruptcy. In a further study, we will include non-financial factors such as size, industry, and age of the firms. Thus, we can obtain realistic clustering results for bankruptcy types by combining qualitative factors and reflecting the domain knowledge of experts.

• Journal of Digital Convergence
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• v.15 no.6
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• pp.133-143
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• 2017

Data is the most important asset in the financial sector. On average, 71 percent of financial institutions generate competitive advantage over data analysis. In particular, in the card industry, the card transaction data is widely used in the development of merchant information, economic fluctuations, and information services by analyzing patterns of consumer behavior and preference trends of all customers. However, creation of new value through fusion of data is insufficient. This study introduces the analysis and forecasting of consumption trends of credit card companies which convergently analyzed the social data and the sales data of the company's own. BC Card developed an algorithm for linking card and social data with trend profiling, and developed a visualization system for analysis contents. In order to verify the performance, BC card analyzed the trends related to 'Six Pocket' and conducted th pilot marketing campaign. As a result, they increased marketing multiplier by 40~100%. This study has implications for creating a methodology and case for analyzing the convergence of structured and unstructured data analysis that have been done separately in the past. This will provide useful implications for future trends not only in card industry but also in other industries.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.14 no.4
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• pp.179-190
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• 2019

To alleviate financing difficulties of small and medium sized enterprises (SMEs), the government and municipal governments are providing a variety of SME policy funding programs. This study introduced the policy funding program of Gangwon-do and quantitatively analyzed the financial performance of companies supported by the Gangwon-do SME policy fund in the year 2014. Specifically, we compared the financial ratios for three years, from 2013 to 2015, between funded firms and non-funded firms. In addition, we applied a regression analysis to see if the policy funding program contributed to profitability (the operating profit growth and return on equity), stability (the interest coverage ratio and debt-to-equity ratio), and growth (the asset growth and sales growth) of the funded firms. The empirical results show that the firms that received the policy funds did not show any improvement compared to non-funded firms in terms of profitability, stability, and growth. This suggests that Gangwon-do should improve the policy funding program, that currently provides only an interest amount of 2-4% of the corporate loan principal, without any strategic selection criteria for the target funded firms, and without any follow-up management system, after support.

• Journal of Intelligence and Information Systems
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• v.28 no.3
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• pp.209-235
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• 2022

Starting from 2010, blockchain technology, along with the development of artificial intelligence, has been in the spotlight as the latest technology to lead the 4th industrial revolution. Furthermore, previous research regarding blockchain's technological applications has been ongoing ever since. However, few studies have been examined the standards for classifying the blockchain economic ecosystem from a capital market perspective. Our study is classified into a collection of interviews of software developers, entrepreneurs, market participants and experts who use blockchain technology to utilize the blockchain economic ecosystem from a capital market perspective for investing in stocks, and case study methodologies of blockchain economic ecosystem according to application fields of blockchain technology. Additionally, as a way that can be used in connection with equity investment in the capital market, the blockchain economic ecosystem classification methodology was established to form an investment universe consisting of global blue-chip stocks. It also helped construct an intelligent portfolio through quantitative and qualitative analysis that are based on quant and artificial intelligence strategies and evaluate its performances. Lastly, it presented a successful investment strategy according to the growth of blockchain economic ecosystem. This study not only classifies and analyzes blockchain standardization as a blockchain economic ecosystem from a capital market, rather than a technical, point of view, but also constructs a portfolio that targets global blue-chip stocks while also developing strategies to achieve superior performances. This study provides insights that are fused with global equity investment from the perspectives of investment theory and the economy. Therefore, it has practical implications that can contribute to the development of capital markets.

• Economic Analysis
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• v.27 no.3
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• pp.1-32
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• 2021

This study empirically analyzes whether bank capital channel and risk-taking channel for monetary policy work for domestic banks in South Korea by analyzing the impact of the expansionary monetary policy on the rate spread between deposit and loan, capital ratio, and loan amount. For the empirical analysis, the Uhlig (2005)'s sign-restricted SVAR(Structural Vector Auto-Regression) model is used. The empirical results are as follows: the bank's interest rate margin increases, the capital ratio improves, risk-weighted asset ratio increases, and the amount of loans increases in response to expansionary monetary shock. This empirical results confirm that bank capital channel and risk-taking channel work in domestic banks, similar to the previous research results. The implications of this study are as follows. Although the expansionary monetary policy has the effect of improving the bank's financial soundness and profitability in the short term as bank capital channel works, it could negatively affect the soundness of banks by encouraging banks to pursue risk in the long run as risk-taking channel works. It is necessary to note that the capital ratio according to the BIS minimum capital requirement of individual banks may cause an illusion in supervising the soundness of the bank. So, the bank's aggressive lending expansion may lead to an inherent weakness in the event of a crisis. Since the financial authority may have an illusion about the bank's financial soundness if the low interest rate persists, the authority needs to be actively interested in stress tests and concentration risk management in the pillar 2 of the BIS capital accord. In addition, since system risk may increase, it is necessary to conduct regular stress tests or preemptive monitoring of assets concentration risk.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.129-148
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• 2023

Bitcoin is a blockchain technology-based digital currency that has been recognized as a representative cryptocurrency and a financial investment asset. Due to its highly volatile nature, Bitcoin has gained a lot of attention from investors and the public. Based on this popularity, numerous studies have been conducted on price and trend prediction using machine learning and deep learning. This study employed LSTM (Long Short Term Memory) and CNN (Convolutional Neural Networks), which have shown potential for predictive performance in the finance domain, to enhance the classification accuracy in Bitcoin price trend prediction. XAI(eXplainable Artificial Intelligence) techniques were applied to the predictive model to enhance its explainability and interpretability by providing a comprehensive explanation of the model. In the empirical experiment, CNN was applied to technical indicators and Google trend data to build a Bitcoin price trend prediction model, and the CNN model using both technical indicators and Google trend data clearly outperformed the other models using neural networks, SVM, and LSTM. Then SHAP(Shapley Additive exPlanations) was applied to the predictive model to obtain explanations about the output values. Important prediction drivers in input variables were extracted through global interpretation, and the interpretation of the predictive model's decision process for each instance was suggested through local interpretation. The results show that our proposed research framework demonstrates both improved classification accuracy and explainability by using CNN, Google trend data, and SHAP.

• The Korean Journal of Archival Studies
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• no.48
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• pp.93-139
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• 2016

Aside from serving as a body that monitors and criticizes the government through reviews and comments on public issues, newspapers can also form and spread public opinion. Metadata contains certain picture records and, in the case of local newspapers, the former is an important means of obtaining locality. Furthermore, advertising in newspapers and the way of editing in newspapers can be viewed as a representation of the times. For the value of archiving in newspapers when a documentation strategy is established, the newspaper is considered as a top priority that should be collected. A newspaper archive that will handle preservation and management carries huge significance in many ways. Journalists use them to write articles while scholars can use a newspaper archive for academic purposes. Also, the NIE is a type of a practical usage of such an archive. In the digital age, the newspaper archive has an important position because it is located in the core of MAM, which integrates and manages the media asset. With this, there are prospects that an online archive will perform a new role in the production of newspapers and the management of publishing companies. Korea Integrated News Database System (KINDS), an integrated article database, began its service in 1991, whereas Naver operates an online newspaper archive called "News Library." Initially, KINDS received an enthusiastic response, but nowadays, the utilization ratio continues to decrease because of the omission of some major newspapers, such as Chosun Ilbo and JoongAng Ilbo, and the numerous user interface problems it poses. Despite these, however, the system still presents several advantages. For example, it is easy to access freely because there is a set budget for the public, and accessibility to local papers is simple. A national library consistently carries out the digitalization of time-honored newspapers. In addition, individual newspaper companies have also started the service, but it is not enough for such to be labeled an archive. In the United States (US), "Chronicling America"-led by the Library of Congress with funding from the National Endowment for the Humanities-is in the process of digitalizing historic newspapers. The universities of each state and historical association provide funds to their public library for the digitalization of local papers. In the United Kingdom, the British Library is constructing an online newspaper archive called "The British Newspaper Archive," but unlike the one in the US, this service charges a usage fee. The Joint Information Systems Committee has also invested in "The British Newspaper Archive," and its construction is still ongoing. ProQuest Archiver and Gale NewsVault are the representative platforms because of their efficiency and how they have established the standardization of newspapers. Now, it is time to change the way we understand things, and a drastic investment is required to improve the domestic and international online newspaper archive.