• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.635-637
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• 2021

Cybersecurity assessment is the process of assessing the risk level of a system through threat and vulnerability analysis to take appropriate security measures. Accurate security evaluation models are needed to prepare for the recent increase in cyberattacks and the ever-developing intelligent security threats. Therefore, we present a risk assessment model through a matrix-based security assessment model analysis that scores by assigning weights across security equipment, intervals, and vulnerabilities. The factors necessary for cybersecurity evaluation can be simplified and evaluated according to the corporate environment. It is expected that the evaluation will be more appropriate for the enterprise environment through evaluation by security equipment, which will help the cyber security evaluation research in the future.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.4
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• pp.611-620
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• 2021

The maintenance industry is mainly progressing based on condition-based maintenance after corrective maintenance and preventive maintenance. In condition-based maintenance, maintenance is performed at the optimum time based on the condition of equipment. In order to find the optimal maintenance point, it is important to accurately understand the condition of the equipment, especially the remaining useful life. Thus, using simulation data (C-MAPSS), a prediction model is proposed to predict the remaining useful life of a turbofan engine. For the modeling process, a C-MAPSS dataset was preprocessed, transformed, and predicted. Data pre-processing was performed through piecewise RUL, moving average filters, and standardization. The remaining useful life was predicted using principal component analysis and the k-NN method. In order to derive the optimal performance, the number of principal components and the number of neighbor data for the k-NN method were determined through 5-fold cross validation. The validity of the prediction results was analyzed through a scoring function while considering the usefulness of prior prediction and the incompatibility of post prediction. In addition, the usefulness of the RUL prediction model was proven through comparison with the prediction performance of other neural network-based algorithms.

• Korean Journal of Radiology
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• v.24 no.3
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• pp.190-203
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• 2023

Objective: We aimed to assess and validate the radiologic and clinical factors that were associated with recurrence and survival after curative surgery for heterogeneous targetoid primary liver malignancies in patients with chronic liver disease and to develop scoring systems for risk stratification. Materials and Methods: This multicenter retrospective study included 197 consecutive patients with chronic liver disease who had a single targetoid primary liver malignancy (142 hepatocellular carcinomas, 37 cholangiocarcinomas, 17 combined hepatocellular carcinoma-cholangiocarcinomas, and one neuroendocrine carcinoma) identified on preoperative gadoxetic acid-enhanced MRI and subsequently surgically removed between 2010 and 2017. Of these, 120 patients constituted the development cohort, and 77 patients from separate institution served as an external validation cohort. Factors associated with recurrence-free survival (RFS) and overall survival (OS) were identified using a Cox proportional hazards analysis, and risk scores were developed. The discriminatory power of the risk scores in the external validation cohort was evaluated using the Harrell C-index. The Kaplan-Meier curves were used to estimate RFS and OS for the different risk-score groups. Results: In RFS model 1, which eliminated features exclusively accessible on the hepatobiliary phase (HBP), tumor size of 2-5 cm or > 5 cm, and thin-rim arterial phase hyperenhancement (APHE) were included. In RFS model 2, tumors with a size of > 5 cm, tumor in vein (TIV), and HBP hypointense nodules without APHE were included. The OS model included a tumor size of > 5 cm, thin-rim APHE, TIV, and tumor vascular involvement other than TIV. The risk scores of the models showed good discriminatory performance in the external validation set (C-index, 0.62-0.76). The scoring system categorized the patients into three risk groups: favorable, intermediate, and poor, each with a distinct survival outcome (all log-rank p < 0.05). Conclusion: Risk scores based on rim arterial enhancement pattern, tumor size, HBP findings, and radiologic vascular invasion status may help predict postoperative RFS and OS in patients with targetoid primary liver malignancies.

• Journal of the Korean Data and Information Science Society
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• v.26 no.6
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• pp.1207-1216
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• 2015

This study aims to compare the model power in developing corporate credit rating models and to suggest a good way to build models based on the characteristic of data. Among many measurement methods, AR is used to measure the model power under various conditions. SAS/MACRO is in use for similar repetitions to reduce time to build models under several combination of conditions. A corporate credit rating model is composed of two sub-models; a credit scoring model and a default prediction model. We verify that the latter performs better than the former under various conditions. From the result of size comparisons, models of large size corporate are more powerful and more meaningful in financial viewpoint than those of small size corporate. As a corporate size gets smaller, the gap between sub-models becomes huge and the effect of outliers becomes serious.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.36 no.3
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• pp.109-117
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• 2013

This study designed a "Diagnostic Model for Management Innovation of Medium Enterprises" based on the theoretical background of success factor and management diagnosis model for management innovation of medium enterprises and suggested a measure for utilization of strategic subject and diagnostic model that enterprises can apply. Utilization of medium enterprises management innovation diagnostic model designed through this study would be of help for making a diagnosis of the capability maturity level of enterprises' current management system and improving it by establishing a challenging capability objective and building a circulation system capable of innovating enterprises. It is expected for enterprises to overcome growing pains and establish a management system capable of achieving outcome (productivity) by repeating measurement and innovation through management diagnosis. In addition, this study provides a method to produce a strategic subject, select priority of implementation and prepare an implementation road map by classifying and filtering management issues produced as a result of management diagnosis in a systematic way. If variables necessary for production of an objective weighted value of scoring and discover of elements for category of diagnostic model and elementary items as well as design of a self-diagnosis questionnaire, measurement of management outcome suggested in this study can be able to be verified and supplemented through case study in the future, it is expected to make the degree of completion as a diagnostic model elevated that may help for growth and development through innovation of medium enterprises.

• Journal of Technology Innovation
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• v.9 no.1
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• pp.21-35
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• 2001

The main purpose of this study is to measure and compare the state of the art (SOA) of DNA chips of Korea, Japan and the United States using Gordon's scoring model. From the comparison, Korea's SOAs of DNA chip were estimated to be 70% and 62% of those of the United States in terms of functional and technical parameters, whereas Japan's SOAs were 79% and 77%, respectively. The results of this study could be applied to the strategic technology planning for narrowing the technology gap, and used as one of the key criteria for resource allocation in national R&D programs and the fundamental information to formulate the biotechnology policy for the Korean government.

• The Journal of Information Systems
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• v.16 no.1
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• pp.1-21
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• 2007

신용평점을 위한 부도예측의 분류 문제를 다루는데 있어서 통계적 판별분석 및 인공신경망 및 유전자알고리즘 등을 이용한 데이터 마이닝의 방법들이 일반적으로 고려되어왔다. 이 연구에서는 수리계획법을 응용하여 classification gap을 고려한 이단계 수리계획 접근방법을 신용평가에 적용하는 방법론을 제안하여 수리계획법을 통한 신용평가모형 구축의 가능성을 제시한다. 1단계에서는 선형계획법을 이용해서 대출 신청자에게 대출을 허가할 것 인지의 여부를 결정하게 되는 대출 심사 filtering으로의 적용단계이고, 2단계에서는 정수계획법을 이용하여 오분류 비용이 최소가 되도록 하는 판별점수를 찾는 과정으로 모형을 구성한다. 개인 대출 신청자의 데이터(German Credit Data)에 대하여 피셔의 선형 판별함수, 로지스틱 회귀모형 및 기존의 수리계획 기법들과의 비교를 통해서 제안된 모델의 성능을 평가한다. 이단계 수리계획 접근법의 평가 결과를 통하여 신용평가모형에의 적용가능성을 기존 통계적인 접근방법 및 수리계획 접근법과 비교하여 제시하고 있다.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.11a
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• pp.205-208
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• 2006

최근 전산화를 위한 대형 IT 프로젝트가 증가 하고 있다. IT 프로젝트를 수행하기 위해서 DB, Server 등과 같은 S/W, H/W 제품과 구현을 수행할 SI 업체 등이 사전에 선정되어야 한다. 현재 대부분의 대형 IT 프로젝트의 경우 제품 및 업체를 선정함에 있어서 내부적인 의사 결정 기준을 보유하고 있으나, 이를 외부에 공개하지 않음을 원칙으로 하고 있다. 본 연구에서는 한 은행이 직면한 제품 및 업체 선정 문제 사례에 대해 AHP기법을 적용하여 그 결과를 은행 내부 기준에 의한 의사 결정 결과와 비교해 보았으며, 절대적 측정 방법에 의한 Scoring System을 제시함으로써 향후 유사한 의사결정 문제에 있어서 보다 정확하고 신속한 의사 결정에 기여하고자 하였다.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.41 no.4
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• pp.433-441
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• 1992

This paper describes an algorithm that can efficiently analyze the ECG signal using frame knowledge representation technique. Input to the analysis process is a set of significant points which have been extracted from an original sampled signal(lead II) by the syntactic peak recognition algorithm. The hierarchical property of ECG signal is represented by hierarchical AND/OR graph. The semantic information and constraints of the ECG signal are desctibed by frame. As the control mechanism for labeling points, the search mechanism with the mixed paradigms of data-driven and model driven hypothesis formation, scoring function, hypothesis modification network and instance inheritance are used. We used the CSE database in order to evaluate the performance of the proposed algorithm.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.05a
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• pp.972-975
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• 2003

The purpose of this study is to integrate Decision Theory Approach(DTA) and OR Theory Approach(OTA) systemically. and to develop Combination Theory Approach to build an optimal R&D project portfolio by strategies. To Integrate two approaches. Utility theory is introduced. Evaluation Results aye converted into utility values by the utility functions and the values are optimized by 0-1 programming. Scoring method and Integer programming is used to evaluation a correspondence with a goal and to allocation the limiting resources. And utility function is used to reflect the preference of decision makers on the project evaluation.