• 한국벤처창업학회:학술대회논문집
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• 2019.04a
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• pp.51-55
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• 2019

기업신용평가(ICR : Issuer Credit Rating)는 기업의 금융상 채무에 대한 전반적인 적기 상환능력, 즉 채무불이행의 가능성을 평가한 것으로 오로지 금융상 채무에 대한 전반적인 채무상환능력을 평가한다. 최근에는 신용평가 등급이 금융시장과의 효과적인 의사소통수단으로 인식되고 기업 IR 및 홍보차원과 기업 간 물품공급과 납품을 위한 업체 선정시 신용등급이 적극적이고 다양하게 활용되고 있다. 이러한 기업신용평가는 최근 경제환경의 급속한 변화에 대응하여 기관별로 평가시스템을 자주 개선하고 있다. 본 연구에서는 정책금융기관 별로 변화된 평가시스템에 대한 평가지표나 구조, 평가시스템을 비교 분석해 그 차이점과 공통점 그리고 경제환경 변화에 따라 변화된 주요지표를 파악해 보고 미래의 신용평가시스템의 변화와 개선방안에 대해 생각하였다. 기관별 비교에서 평가시스템의 차이점은 신보는 신용평가(부실률 기반)와 미래성장성평가(성장성 기반)를 실시하여 보증심사등급(보증의사결정 등급)을 산출하고, 기술자산평가등급은 신용평가등급을 조정(최대 ${\pm}2$등급)하는 보조적 수단으로 활용하고 있으며, 기보는 기술평가(성장성 및 부실률 기반)와 리스크관리용 리스크평가(신보의 신용평가에 해당)로 평가체계를 이원화하여 운영하고, 평가모형은 신보는 객관성을 확보한 정량평가 위주, 기보는 공신력을 확보한 정성평가 위주의 주관적인 평가를 실시하고 있어 어떤 형태의 평가시스템이 더 좋은 평가방법 인지는 알 수 없지만, 기관별 부실율을 보면 다소 참고가 될 수도 있으나, 이것이 전적인 평가의 문제라 보기도 어렵다. 특히 신보는 창업기업 기준이 창업후 7년까지로 확대됨에 따른 창업 3단계 평가제도와 기업의 성장단계에 맞춘 성장단계별 평가기준 세분화는 기업환경을 잘 반영한 변화라 볼 수 있다. 그리고 향후 평가시스템은 경제환경의 변화속도를 어떻게 잘 반영 할 수 있는지에 대한 연구로 방향이 전개될 것으로 보인다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.8
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• pp.370-378
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• 2020

The Construction Operations Building Information Exchange (COBie) collects and documents a large amount of information from different paths in one place during design and construction projects. This documented information is readily available as a means of continuously transferring data to the facility management systems used by building engineers. In this process, the COBie Worksheet, an open standard form, is used to input the information by simplifying the list required by the user. As a result, COBie was developed to improve dramatically how relevant information is obtained and updated to support operations, maintenance, and asset management at the design and construction stages. On the other hand, to use COBie, a great deal of manual work is required for information linkage and quality inspection with heterogeneous data models. These issues become obstacles to COBie-based facility management system development. This study analyzed the COBie information system and defined the framework for simpler operating maintenance information from BIM (Building Information Modeling). Moreover, the rules for facility management information submission, quality inspection, role definition of framework components, and information linkage were derived. COBie DB schema and support data linkages could be generated effectively based on the proposed framework in prototype development.

• Journal of Digital Convergence
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• v.15 no.2
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• pp.121-133
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• 2017

The propose of study is to examine the characteristics of companies with high possibility to form an internal control weakness using forecasting model. This study use the actual listed/unlisted companies' data from K_financial institution. The first conclusion is that discriminant model is more valid than logit model to predict internal control weak companies. A discriminant model for predicting the vulnerability of internal control has high classification accuracy and has low the Type II error that is incorrectly classifying vulnerable companies to normal companies. The second conclusion is that the characteristic of weak internal control companies have a low credit rating, low asset soundness assessment, high delinquency rates, lower operating cash flow, high debt ratios, and minus operating profit to the net sales ratio. As not only a case of listed companies but unlisted companies which did not occur in previous studies are extended in this study, research results including the forecasting model can be used as a predictive tool of financial institutions predicting companies with high potential internal control weakness to prevent asset losses.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.6
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• pp.155-163
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• 2019

This paper proposes a new methodology to recognize cracks on asphalt road surfaces using the image data obtained with drones. The target section was Yuseong-daero, the main highway of Daejeon. Furthermore, two object detection algorithms, such as Tiny-YOLO-V2 and Faster-RCNN, were used to recognize cracks on road surfaces, classify the crack types, and compare the experimental results. As a result, mean average precision of Faster-RCNN and Tiny-YOLO-V2 was 71% and 33%, respectively. The Faster-RCNN algorithm, 2Stage Detection, showed better performance in identifying and separating road surface cracks than the Yolo algorithm, 1Stage Detection. In the future, it will be possible to prepare a plan for building an infrastructure asset-management system using drones and AI crack detection systems. An efficient and economical road-maintenance decision-support system will be established and an operating environment will be produced.

• The KIPS Transactions:PartD
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• v.16D no.5
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• pp.701-714
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• 2009

In the enterprises the data integration based on service requires integrated data management as the change in the environment of enterprises accelerates. Cooperation among enterprises is accomplished through accessing distributed database using business process. As this approach is performed based on the global query, problems such as data heterogeneity, schema heterogeneity, and verification of validity have to be solved in advance for the interoperability among the heterogeneous system. Thus, cooperation requires dynamic and reliable construction. In this paper, we propose XMDR-DSM (eXtended MetaData Registry-Data Service Mediator) system for cooperation. XMDR-DSM, which is comprised of XMDR-DS, XMDR-DQP, and XMDR-DAI, supports the mapping between global schema and local schema and provides data access and integration service. Therefore, XMDR-DSM enables the mutual support of business operations among heterogeneous database. In addition, it can secure information as reusable asset and the standardization of interchange. Also it can manage unified information since it provides business process based on workflow; therefore, it will be able to increase the life span of information and reduce the cost.

• The Journal of Society for e-Business Studies
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• v.24 no.3
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• pp.53-71
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• 2019

As software systems become more complex and larger, software systems require a way to reuse software components or modules to provide new functionality. This paper designed a development method of web system combining SOA(Service Oriented Architecture) with MPSL(Multi-Software Product Line). According to provides SOA and MPSL, this paper suggested to service providers and service users to provide and reuse variable services. From the viewpoint of service provider, the suggested method identifies and implements reusable variable services as features by syntax-based, functional-based, and behavior-based methods applying feature identification guidelines and manages them as reuse assets. From the user's point of view, it is possible to develop a web system by constructing a service by workflow model as a method of structure and reconfigure services. As a result of measuring the reuse of the web system constructed in this paper by the function point, the cost reduction effect was verified by applying it to the similar project with the increase of reuse.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.292-292
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• 2022

가뭄은 사회기반시설, 인적 자본 등과 같은 자산에 직접적인 영향을 미치지 않으나 물을 중요한 투입재로 사용하는 농업부문에 피해가 집중된다. 가뭄 재해는 준비와 대응에 따라 피해에 큰 차이가 크기 때문에 다른 재해와는 달리 강도뿐만 아니라 지속기간을 고려해야 한다. 효과적인 가뭄 위험 관리를 위해서는 가뭄의 특징과 가뭄 준비 및 대응 수단에 따른 환경 및 경제적 영향을 평가할 수 있는 모형 구축과 다양한 농업자원을 동시적으로 연계 평가하여 지속가능성을 판단할 수 있는 기술 개발이 필요하다. 이에 본 연구에서는 기후변화 등의 외부요인을 반영한 물-에너지-식량 (Water-Energy-Food, WEF) 넥서스 기반 농업 가뭄 평가 플랫폼 설계를 제안하고자 한다. 이를 위해 물-에너지-식량 넥서스 연계 해석 고도화 기술을 개발하고, 생물-물리학적 모델 및 경제학적 모델 연계형 기후-토양-물-에너지-식량 넥서스 (CS-WEF NEXUS) 플랫폼을 구축하여, 최종적으로 기후변화 및 농업부문 가뭄 준비 및 대응 수단의 영향 평가를 바탕으로 한 의사결정 지원 도구를 제시하는 것이 최종 목표이다. 본 연구에서 구축된 플랫폼은 넥서스 연계 해석을 통해 농업 가뭄 대응을 위한 식량 및 에너지 안보 정책에도 미칠 수 있는 영향을 분석할 수 있으며, 다양한 식량-물-에너지 정책들이 타 요소들에 미치는 영향을 쉽게 평가할 수 있다는 점에서 정책적 의사결정 지원 시스템으로서 활용도가 높을 것으로 예상한다.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.157-176
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• 2018

The purpose of this research is to develop a detection model for companies designated as administrative issue in KOSDAQ market using financial data. Administration issue designates the companies with high potential for delisting, which gives them time to overcome the reasons for the delisting under certain restrictions of the Korean stock market. It acts as an alarm to inform investors and market participants of which companies are likely to be delisted and warns them to make safe investments. Despite this importance, there are relatively few studies on administration issues prediction model in comparison with the lots of studies on bankruptcy prediction model. Therefore, this study develops and verifies the detection model of the companies designated as administrative issue using financial data of KOSDAQ companies. In this study, logistic regression and decision tree are proposed as the data mining models for detecting administrative issues. According to the results of the analysis, the logistic regression model predicted the companies designated as administrative issue using three variables - ROE(Earnings before tax), Cash flows/Shareholder's equity, and Asset turnover ratio, and its overall accuracy was 86% for the validation dataset. The decision tree (Classification and Regression Trees, CART) model applied the classification rules using Cash flows/Total assets and ROA(Net income), and the overall accuracy reached 87%. Implications of the financial indictors selected in our logistic regression and decision tree models are as follows. First, ROE(Earnings before tax) in the logistic detection model shows the profit and loss of the business segment that will continue without including the revenue and expenses of the discontinued business. Therefore, the weakening of the variable means that the competitiveness of the core business is weakened. If a large part of the profits is generated from one-off profit, it is very likely that the deterioration of business management is further intensified. As the ROE of a KOSDAQ company decreases significantly, it is highly likely that the company can be delisted. Second, cash flows to shareholder's equity represents that the firm's ability to generate cash flow under the condition that the financial condition of the subsidiary company is excluded. In other words, the weakening of the management capacity of the parent company, excluding the subsidiary's competence, can be a main reason for the increase of the possibility of administrative issue designation. Third, low asset turnover ratio means that current assets and non-current assets are ineffectively used by corporation, or that asset investment by corporation is excessive. If the asset turnover ratio of a KOSDAQ-listed company decreases, it is necessary to examine in detail corporate activities from various perspectives such as weakening sales or increasing or decreasing inventories of company. Cash flow / total assets, a variable selected by the decision tree detection model, is a key indicator of the company's cash condition and its ability to generate cash from operating activities. Cash flow indicates whether a firm can perform its main activities(maintaining its operating ability, repaying debts, paying dividends and making new investments) without relying on external financial resources. Therefore, if the index of the variable is negative(-), it indicates the possibility that a company has serious problems in business activities. If the cash flow from operating activities of a specific company is smaller than the net profit, it means that the net profit has not been cashed, indicating that there is a serious problem in managing the trade receivables and inventory assets of the company. Therefore, it can be understood that as the cash flows / total assets decrease, the probability of administrative issue designation and the probability of delisting are increased. In summary, the logistic regression-based detection model in this study was found to be affected by the company's financial activities including ROE(Earnings before tax). However, decision tree-based detection model predicts the designation based on the cash flows of the company.

• Journal of Climate Change Research
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• v.3 no.4
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• pp.225-234
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• 2012

This study analyzes domestic and overseas companies' Scope 3 verification, level of management, source and industry characteristics based on the responses of domestic excellent companies and rated 90 points or more global excellent companies which are included in CDP Korea 200 and CDP Global 500. The result of analysis conveys that global excellent companies' Scope 3 management source achieved the average of 2.7 which is one more than domestic excellent companies', according to the Scope 3 guideline of World Resource Institute and World Business Council of Sustainable Development. For domestic companies are tend to focus on business travel, employee commuting, etc. but didn't manage capital goods, leased assets and investments. Global companies' Scope 3 source is similar to domestic companies but shows more actively managing on investment and use of sold products. It seems that domestic companies should actively develop Scope 3 source especially for the capital related items and respond to the future regulations on inter-enterprise management through the Scope 3.

• Journal of Aerospace System Engineering
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• v.10 no.4
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• pp.67-74
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• 2016

The primary aim for using a Korean Condition Based Maintenance (CBM) system is to maintain military operational readiness using Interactive Collection Analysis Systems (ICAS) installed on naval vessels. Other aims are to preemptively provision maintenance and supply functions, to guarantee economical management of logistical assets, and to implement data driven equipment life cycle management. In order to accomplish these aims, it is necessary to establish standard system conditions. However, because manufacturers do not provide the technology necessary for maintenance management, it is required to retain component performance maps for each piece of equipment, and to accumulate data about frequently occurring fault patterns. This study confirms the validity of component performance maps using micro gas turbines and provides accumulated data on machine break downs. This would allow real time equipment performance checks and present performance trends. Then analysis would provide solutions for maintaining the best machine operating conditions with detailed maintenance manuals for operators. This study is a basis for further research to investigate additional ways to develop CBM using data obtained from naval vessels used in actual military operations.