• 한국정보시스템학회지:정보시스템연구
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• 제19권3호
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• pp.59-73
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• 2010

Along with advance of information technology, value of information is growing much more than ever. And nearly all organizations pay great attentions to information security to protect their own important informations against every kind of hazardous accidents. Therefore, organizations want to select best information security system among many possible alternatives. For this purpose, several fuzzy AHP decision making approaches can be utilized. In this study, we consider a number of qualitative and quantitative factors to evaluate security systems and then apply three fuzzy AHP approaches for simple case to compare the results from three approaches. We find that final decision depends on both fuzzy AHP methods and degree of fuzziness.

• 산업경영시스템학회지
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• 제28권1호
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• pp.72-83
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• 2005

Recall aims to remove the products hazardous to consumers or users from the commerce. However, a recall with a poor decision making procedure could results in disaster to corporations. Therefore, recall managers should establish a proper recall plan in advance to minimize the damage to business. The purpose of the study is to propose a computerized recall management system(RMSys) to handle recall process systematically and timely manners. RMSys, a recall decision-making procedures software, consists of two different modules such as recall decision-making module and recall procedure module. RMSys on the basis of the world wide web is designed to be compatible to ERP(Enterprise Resources Panning). RMSys could play a role as a management support system to help the corporations recall the hazardous products with minimum efforts.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권1호
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• pp.385-405
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• 2019

High Efficiency Video Coding (HEVC) enables significantly improved compression performance relative to existing standards. However, the advance also requires high computational complexity. To accelerate the intra prediction mode decision, a minimum risk Bayesian classification framework is introduced. The classifier selects a small number of candidate modes to be evaluated by a rate-distortion optimization process using the sum of absolute Hadamard transformed difference (SATD). Moreover, the proposed method provides a loss factor that is a good trade-off model between computational complexity and coding efficiency. Experimental results show that the proposed method achieves a 31.54% average reduction in the encoding run time with a negligible coding loss of 0.93% BD-rate relative to HEVC test model 16.6 for the Intra_Main common test condition.

• 한국컴퓨터정보학회논문지
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• 제27권5호
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• pp.21-28
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• 2022

심혈관질환은 심장질환과 혈관질환 등 순환기계통에 생기는 모든 질병을 통칭한다. 심혈관질환은 2019년 사망의 1/3을 차지하는 전 세계 사망의 주요 원인이며, 사망자는 계속 증가하고 있다. 이와 같은 질병을 인공지능을 활용해 환자의 데이터로 미리 예측이 가능하다면 질병을 조기에 발견해 치료할 수 있을 것이다. 본 연구에서는 심혈관질환 중 하나인 심장질환을 예측하는 모델들을 생성하였으며 Accuracy, Precision, Recall의 측정값을 지표로 하여 모델들의 성능을 비교한다. 또한 Decision Tree의 성능을 향상시키는 방법에 대해 기술한다. 본 연구에서는 macOS Big Sur환경에서 Jupyter Notebook으로 Python을 사용해 scikit-learn, Keras, TensorFlow 라이브러리를 이용하여 실험을 진행하였다. 연구에 사용된 모델은 Decision Tree, KNN(K-Nearest Neighbor), SVM(Support Vector Machine), DNN(Deep Neural Network)으로 총 4가지 모델을 생성하였다. 모델들의 성능 비교 결과 Decision Tree 성능이 가장 높은 것으로 나타났다. 본 연구에서는 노드의 특성배치를 변경하고 트리의 최대 깊이를 3으로 지정한 Decision Tree를 사용하였을 때 가장 성능이 높은 것으로 나타났으므로 노드의 특성 배치 변경과 트리의 최대 깊이를 설정한 Decision Tree를 사용하는 것을 권장한다.

• 한국항만경제학회지
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• 제21권1호
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• pp.1-21
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• 2005

It has been more recent trends in container trade to make bogger ship from shipowners that many more parties concerned are getting involved. Well, it is natural to swift these situations if we have looked into container trade market in present time, which a lot of trade volumes has increased in world economy. Thus, supply side of shipping service needs to employ more capacity in the shipping market, then newbuilding may be compulsory options, that is deployment of larger ships. To cope with market situations as able shipowner, some alternatives can be also adopted, such as newbuilding, chartering and securing the space by strategic alliance. But whatever he does, shipowner has to keep in mind to prepare for the future. This is much more important factor considered to make investment decision in case of newbuilding and then he can make more efficient decision as well. However, there has been a little problems arisen due to larger ship employed on the trade route, which is linked with seaport, shipping companies and freight rates as well. Although shipowner decides to build new larger vessel as one of corporate strategic decision, there are many questions to be considered in advance. Therefore, in order to take more efficient decision, shipowner has to take into an account various situations surrounded, and then it can lead truly thoughtful decision making process.

• 한국정보과학회논문지:데이타베이스
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• 제34권1호
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• pp.70-83
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• 2007

대부분의 스카이라인 질의에 대한 연구는 정적인 데이타에 관하여 이루어지고 있다. 하지만, 모바일 응용환경의 발전에 따라 이동객체에 대한 연속적인 스카이라인 질의에 대한 필요성이 증대되고 있다. 연속적인 스카이라인 질의를 처리하기 위하여 4단계 스카이라인 영역 결정 기법이 최근 제안되었지만, 이 기법은 스카이라인 영역 계산 비용이 크므로 대량의 데이타 객체에 대해서는 사용되기 힘든 문제점이 있다. 이 논문은 이러한 문제를 해결하기 위하여 먼저 4단계 영역 결정 기법에 대해서 이론적으로 분석하고, 이를 바탕으로 4 단계 영역 결정 기법을 위한 점진적인 스카이라인 영역 결정 기법을 제안한다. 제안하는 기법은 거리 기반 가지치기와 영역 결정 선분의 범위 축소 기법을 이용하여 기존 기법의 스카이라인 영역결정 비용을 효율적으로 감소시킨다. 본 논문은 다양한 성능 시험을 통하여 제안된 기법의 효율성을 증명한다.

• 상하수도학회지
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• 제37권5호
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• pp.271-279
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• 2023

Fouling is an inevitable problem in membrane water treatment plant. It can be measured by trans-membrane pressure (TMP) in the constant flux operation, and chemical cleaning is carried out when TMP reaches a critical value. An early fouilng alarm is defined as warning the critical TMP value appearance in advance. The alarming method was developed using one of machine learning algorithms, decision tree, and applied to a ceramic microfiltration (MF) pilot plant. First, the decision tree model that classifies the normal/abnormal state of the filtration cycle of the ceramic MF pilot plant was developed and it was then used to make the early fouling alarm method. The accuracy of the classification model was up to 96.2% and the time for the early warning was when abnormal cycles occurred three times in a row. The early fouling alram can expect reaching a limit TMP in advance (e.g., 15-174 hours). By adopting TMP increasing rate and backwash efficiency as machine learning variables, the model accuracy and the reliability of the early fouling alarm method were increased, respectively.

• 한국통신학회논문지
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• 제31권3C
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• pp.271-278
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• 2006

비트율-왜곡 최적화 기법은 H.264/AVC(Advance Video Coding)의 부호화 효율을 높이기 위한 방법이긴 하나 모드 결정 과정 중 부호화기의 복잡도를 높아지는 단점이 있다. 많은 고속화 모드결정 연구들이 모드결정의 복잡도를 줄이기 위하여 제안되어져 왔었다. 본 논문에서는 H.264/AVC의 모드결정의 전체적인 복잡도를 줄이기 위하여 다중 참조 영상 선택 고속화 알고리즘과 선택적인 인트라 모드 선택 알고리즘의 두 가지 고속화 알고리즘을 제안한다. 참조영상 선택 고속화 알고리즘은 인터 모드 결정에 효과적이며, 선택적인 인트라 모드 선해 알고리즘은 과도한 인트라 모드 결정의 계산량을 효율적으로 감소시켰다. 제안된 알고리즘을 실험한 결과로 평균 44.63%의 부호화 시간 감소비를 보이면서 영상의 열화와 같은 부호화 효율 감소는 거의 눈에 띄지 않았다.

• Journal of the Korean Statistical Society
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• 제20권1호
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• pp.67-76
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• 1991

The empirical Bayes version involves ″independent″ repetitions(a sequence) of the component decision problem. With the varying sample size possible, these are not identical components. However, we impose the usual assumption that the parameters sequence $\theta$=($\theta$$_1$, $\theta$$_2$, …) consists of independent G-distributed parameters where G is unknown. We assume that G $\in$ g, a known family of distributions. The sample size $N_i$ and the decisin rule $d_i$ for component i of the sequence are determined in an evolutionary way. The sample size $N_1$ and the decision rule $d_1$$\in$ $D_{N1}$ used in the first component are fixed and chosen in advance. The sample size $N_2$and the decision rule $d_2$ are functions of *see full text($\underline{X}^1$equation omitted), the observations in the first component. In general, $N_i$ is an integer-valued function of *see full text(equation omitted) and, given $N_i$, $d_i$ is a $D_{Ni}$/-valued function of *see full text(equation omitted). The action chosen in the i-th component is *(equation omitted) which hides the display of dependence on *(equation omitted). We construct an empirical Bayes decision rule for estimating normal mean and show that it is asymptotically optimal.

• 환경영향평가
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• 제20권5호
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• pp.663-673
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• 2011

In the face of accelerating biodiversity loss and its significance in our coexistence with nature, biodiversity is becoming more crucial in sustainable development perspective. To estimate biodiversity in the future which provides valuable information for decision making system especially in the national level, a quantitative approach must be studied forehand as a baseline of the present status. In this study, we developed a large-scale map of Plant Species Richness (PSR, typical indicator of biodiversity) for Young-dong and Pyung-chang provinces. Due to the accessibility of appropriate data and advance of modelling techniques, reduction of variables without deteriorating the predictive power is considered by applying Genetic algorithm. In addition, a number of Correctly Classified Instances (CCI) with 10-fold cross validation which indicates the predictive power, was carried out for evaluation. This study, as a fundamental baseline, will be beneficial in future land work as well as ecosystem restoration business or other relevant decision making agenda.