• International Journal of Computer Science & Network Security
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• 제21권7호
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• pp.56-62
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• 2021

The surge in generic attacks execution against cipher text on the computer network has led to the continuous advancement of the mechanisms to protect information integrity and confidentiality. The implementation of explicit decision tree machine learning algorithm is reported to accurately classifier generic attacks better than some multi-classification algorithms as the multi-classification method suffers from detection oversight. However, there is a need to improve the accuracy and reduce the false alarm rate. Therefore, this study aims to improve generic attack classification by implementing two hybridized decision tree algorithms namely Naïve Bayes Decision tree (NBTree) and Logistic Model tree (LMT). The proposed hybridized methods were developed using the 10-fold cross-validation technique to avoid overfitting. The generic attack detector produced a 99.8% accuracy, an FPR score of 0.002 and an MCC score of 0.995. The performances of the proposed methods were better than the existing decision tree method. Similarly, the proposed method outperformed multi-classification methods for detecting generic attacks. Hence, it is recommended to implement hybridized decision tree method for detecting generic attacks on a computer network.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2010년도 춘계학술대회
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• pp.357-359
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• 2010

비터비 디코딩 방법은 컨볼루션 복호화 방법 중에서 가장 많이 사용되고 알려진 복호화 방법이다. 본 논문에서는 실질적인 비터비 복호화 성능 고찰을 위하여 여러 가지 파라미터 값을 이용한다. 파라미터 값에 대한 여러 가지 비터비 복호화 방법에 대하여 논의한다. 그리고 비터비 알고리즘 방법중, 중판정과 경판정 이라는 서로 다른 의사결정에 의한 복호화 방법의 차이를 비교한다. 여러 가지 파라미터 값과 의사결정 방법을 가지고 가우시안 채널 상에서의 다양한 비터비 복호화 방법에 대하여 논의하여 가장 적절한 파라미터 값과 의사결정 방법에 대하여 논의한다.

• 디지털산업정보학회논문지
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• 제16권1호
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• pp.55-65
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• 2020

With the development of display hardware, image interpolation techniques have been used in various fields such as image zooming and medical imaging. Traditional image interpolation methods, such as bi-linear interpolation, bi-cubic interpolation and edge direction-based interpolation, perform interpolation in the spatial domain. Recently, interpolation techniques in the discrete cosine transform or wavelet domain are also proposed. Using these various existing interpolation methods and machine learning, we propose decision tree classification-based image interpolation methods. In other words, this paper is about the method of adaptively applying various existing interpolation methods, not the interpolation method itself. To obtain the decision model, we used Weka's J48 library with the C4.5 decision tree algorithm. The proposed method first constructs attribute set and select classes that means interpolation methods for classification model. And after training, interpolation is performed using different interpolation methods according to attributes characteristics. Simulation results show that the proposed method yields reasonable performance.

• 대한안전경영과학회:학술대회논문집
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• 대한안전경영과학회 2006년도 춘계공동학술대회
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• pp.123-131
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• 2006

Multi-criteria decision making is deducing the relative importance in the criterion of decision making and each alternative which is able to making a variety of choices measures the preferred degree in the series of low-raking criterions. Moreover, this is possible by synthesizing them systematically. In general, a fundamental problem decision maker solve for multi-criteria decision making is evaluating a set of activities which are considered as the target logically, and this kind of work is evaluated and synthesized by various criterions of the value which a chain of activities usually hold in common. In this paper, we are the eigenvector methods in weights calculating. For the purpose of making optimal decision, the data of five different car models are used. For computing, we used Visual Numerica Version 1.0 software package.

• Management Science and Financial Engineering
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• 제7권2호
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• pp.31-57
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• 2001

Regarding all methods of decision making as parts of the same subject, one is astounded to find that the field speaks to the practitioners about multicriteria decision making with a multi-forked tongue, different methods give different and conflicting outcomes even for very simple decisions. In this paper, five well-known decision theories are described and used to work out a simple decision to choose the best of three cars. The outcomes turn out not to be the same for all the methods, which is troubling because one would expect unique answers in decision making. Several "meta" criteria that are essential for making a decision theory to make a choice as to which decision approach is best.h is best.

• 한국도서관정보학회지
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• 제13권
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• pp.131-166
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• 1986

This study is designed to review the methods of duplicate copies decision making in the academic library. In this thesis, I surveyed queueing & markov model, statistical model, and simulation model. The contents of the study can be summarized as follows: 1) Queueing and markov model is used for one of duplicate copies decision-making methods. This model was suggested by Leimkuler, Morse, and Chen, etc. Leimkuler proposed growth model, storage model, and availability model through using system analysis method. Queueing theory is a n.0, pplied to Leimkuler's availability model. Morse ad Chen a n.0, pplied queueing and markov model to their theory. They used queueing theory for measuring satisfaction level and Markov model for predicting user demand. 2) Another model of duplicate copies decision-making methods is statistical model. This model is suggested by Grant and Sohn, Jung Pyo. Grant suggested a model with a formula to satisfy the user demand more than 95%, Sohn, Jung Pyo suggested a model with two formulars: one for duplicate copies decision-making by using standard deviation and the other for duplicate copies predicting by using coefficient of variation. 3) Simulation model is used for one of duplicate copies decision-making methods. This model is suggested by Buckland and Arms. Buckland considered both loan period and duplicate copies simultaneously in his simulation model. Arms suggested computer-simulation model as one of duplicate copies decision-making methods. These methods can help improve the efficiency of collection development and solve some problems (space, staff, budget, etc, ) of Korean academic libraries today.

• Communications for Statistical Applications and Methods
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• 제24권6호
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• pp.543-559
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• 2017

Tree-based regression and classification ensembles form a standard part of the data-science toolkit. Many commonly used methods take an algorithmic view, proposing greedy methods for constructing decision trees; examples include the classification and regression trees algorithm, boosted decision trees, and random forests. Recent history has seen a surge of interest in Bayesian techniques for constructing decision tree ensembles, with these methods frequently outperforming their algorithmic counterparts. The goal of this article is to survey the landscape surrounding Bayesian decision tree methods, and to discuss recent modeling and computational developments. We provide connections between Bayesian tree-based methods and existing machine learning techniques, and outline several recent theoretical developments establishing frequentist consistency and rates of convergence for the posterior distribution. The methodology we present is applicable for a wide variety of statistical tasks including regression, classification, modeling of count data, and many others. We illustrate the methodology on both simulated and real datasets.

• The Journal of Asian Finance, Economics and Business
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• 제7권8호
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• pp.87-94
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• 2020

The paper aims to investigate the impact of presenting statements of cash flow using the direct method and the indirect method on loan decision by credit officers at Vietnamese banks. The data was collected from 150 credit officers of commercial banks in Vietnam based on the questionnaire about making loan decision when the cash flow statement is presented in different methods, namely, direct and indirect methods. This research uses T-tests to check whether using the direct or indirect method affects the accurate calculation of loan criteria, affects the loan decision by credit officers, and compare these two methods in the aspects of information provision. The research has pointed out that: 1) the direct method helps the calculation of indicators related to loans more accurately; 2) credit officers say that, while the direct method of presenting cash flow statement provides clearer information, the use of either the direct method or the indirect method does not affect the banks' loan decision. Since then, the author recommends that cash flow statements should be provided with information in a direct method to present the information needed for loan decision more accurately so as to improve the quality of cash flow statement.

• 한국국방경영분석학회지
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• 제28권1호
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• pp.83-96
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• 2002

The Analytic Hierarchy Process (AHP) is well suited to group decision making and offers numerous benefits as a synthesizing mechanism in group decisions. To date, the majority of AHP applications have been in group settings. One reason for this may be that groups often have an advantage over individual when there exists a significant difference between the importance of quality in the decision and the importance of time in which to obtain the decision. Another reason may be the best alternative is selected by comparing alternative solutions, testing against selected criteria, a task ideally suited for AHP. In general, aggregation methods employed in group AHP can be largely classified into two methods: geometric mean method and (weighted) arithmetic mean method. In a situation where there do not exist clear guidelines for selection between them, two methods do not always guarantee the same group decision result. We propose a simulation approach for building group consensus without efforts to make point estimates from individual diverse preference judgments, displaying possible disagreements as is natural in group members'different viewpoints.

• 복식
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• 제50권5호
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• pp.103-115
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• 2000

There are various presentation methods of apparel products on the internet shopping mall. The objective of this study was (a) to identify the effect of information supply about the criteria to evaluate a garment according to presentation methods and (b) to investigate the relation between the consumer's evaluation of presentation methods and confidence in purchase decision. For this experiment. 4 presentation methods of jean were selected from internet shopping mall. They were rotating appearance on the body, enlarged product picture, apparel items coordination method and just picture of wearing appearance. Each presentation method was evaluated by panels using questionnaire. Consumer's evaluation of presentation methods were developed 5 point likert scale. The major findings drawn from this study were as follows : 1. There were significant differences in degree of information supply about product criteria according to presentation methods. Enlarged product picture introduction was good for confirmation of sewing state, fabric and detail. Apparel items coordination method was good for judgement of styling and current fashion suitability. 2. Dimension of information evaluation was composed of providing pleasure, utility of information, reliability & attractiveness, negative emotions. All of these factors affect confidence in purchase decision and intention of revisiting the site. The most important factor for confidence in purchase decision making was reliability & attractiveness. as compared to this, intention of revisiting the site was more influenced by providing pleasure.