• Proceedings of the Korean Institute of Communication Sciences Conference
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• 1986.10a
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• pp.191-193
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• 1986

This paper presents a methodology for the design and test of software by using. Decision Table. We believe that this methodology can be used in improving software Environment in the future.

• Fire Science and Engineering
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• v.10 no.1
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• pp.62-75
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• 1996

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.10
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• pp.4007-4024
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• 2020

It is tremendously important to construct decision trees to use as a tool for knowledge representation from a given decision table. However, the usual algorithms may split the decision table based on each value, which is not efficient for numerical attributes. The methodology of this paper is to split the given decision table into binary groups as like the CART algorithm, that uses binary split to work for both categorical and numerical attributes. The difference is that it uses split for each attribute established by the directed acyclic graph in a dynamic programming fashion whereas, the CART uses binary split among all considered attributes in a greedy fashion. The aim of this paper is to study the effect of binary splits in comparison with each value splits when building the decision trees. Such effect can be studied by comparing the number of nodes, local and global misclassification rate among the constructed decision trees based on three proposed algorithms.

• Journal of Biomedical Engineering Research
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• v.12 no.1
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• pp.63-70
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• 1991

Design of Arrhythmia Automatic Diagnostic System Using Decision Table We have developed an arrhythmia automatic diagnostic system using decision table which is based on the criteria of Minnesota code. This system is divided into two Parts. One is wave detection algorithm using significant point extraction method, the other is arrhythmia diag- nostic algorthm. The proposed system allows physicians to diagnose more accurately by pro- viding the objective information about a lot of computer -processed ECG data.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.11a
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• pp.81-86
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• 1997

It is proposed, for fuzzy combustion control system of refuse incinerator to find the relationship between inputs and outputs and to generate rules to control by using rough set theory. It is not easy to find out the corresponding inputs for each output and the control rules with incomplete or imprecise information consisting expert knowledge, process and manipulator values in the field, and operation manual for the given system. Most decision problems can be formulated employing decision table formalism. A decision table on fuzzy combustion control system for refuse incinerator is simplified and produces control(rules). The I/O realtions and the control rules found by rough set theory are compared with the previous result.

• Journal of the Korea Society of Computer and Information
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• v.27 no.12
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• pp.51-58
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• 2022

In this paper, we propose a decision tree-based machine learning model that leads to food exchange table renewal by classifying food groups through machine learning for existing food and food data found by web crawling. The food exchange table is the standard for food exchange intake when composing a diet such as diet and diet, as well as patients who need nutritional management. The food exchange table, which is the standard for the composition of the diet, takes a lot of manpower and time in the process of revision through the National Health and Nutrition Survey, making it difficult to quickly reflect food changes according to new foods or trends. Since the proposed technique classifies newly added foods based on the existing food group, it is possible to organize a rapid food exchange table reflecting the trend of food. As a result of classifying food into the proposed model in the study, the accuracy of the food group in the food exchange table was 97.45%, so this food classification model is expected to be highly utilized for the composition of a diet that suits your taste in hospitals and nursing homes.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.2
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• pp.107-113
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• 2014

The derivation of optimal information from decision table is based on the concept of indiscernibility relation and approximation space in rough set. Because decision table is more likely to be susceptible to the superposition or inconsistency in decision table, the reduction of attributes is a important concept in knowledge representation. While complete subsets of the attribute's domain is considered in algebraic definition, incomplete subsets of the attribute's domain is considered in information-theoretic definition. Therefore there is a marked difference between algebraic and information-theoretic definition. This paper proposes a conditional entropy using rough set as information theoretical measures in order to deduct the optimal information which may contain condition attributes and decision attribute of information system and shows its effectiveness.

• Journal of Korean Society of Transportation
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• v.28 no.4
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• pp.19-30
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• 2010

It has become important to have some proper guidelines of how to provide public transport information services in response to the rapid IT developments and the wide spread of public information services. The current study takes a contextual approach to the analysis of public transportation information use under a dynamic decision situation, complementing the conventional cross-sectional approaches. Using the CHAID of decision tree induction based on decision table formalism applied to the survey data of activity travel and information use, the study found that the information type and medium choices are strongly affected by the decision contexts in addition to the individuals' socio-demographic characteristics. The results suggest an important implication to the market segmentation of information services for public transportation.

• Management & Information Systems Review
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• v.4
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• pp.573-593
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• 2000

The purpose of this study is to investigate the level of correctness accounting information with the two alternative forms of presenting information outputs. Specifically two different methods of presenting accounting information, the table form and the graphical form were employed to test the level of correctness of the accounting information user's decision making. Using college students as a surrogate decision maker, this research have found that there is no statistically significant difference in the correctness of decision making between the two groups, one group using the table form of accounting information and another group using the graphical form of accounting information.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.11a
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• pp.1452-1455
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• 2012

본 논문은 출시된 지능형 교통 기반으로 설계된 RoboCAR 운행제어 개발과 시험을 하고자 한다. 이를 위해 시스템 설계를 통해,Test Case 추출과 실제로 적용하여 구현된 소프트웨어를 시험에 목적을 둔다. 이 절차는 Use-Case Diagram 설계, Decision Factor 추출, 이 기반으로 Cause-Effect Diagram을 생성한다. Cause-Effect Diagram을 통해 Decision Table을 생성한다. 최종적으로 Decision Table을 기반으로 Test Case를 추출한다. 추출된 Test Case를 적용하여 시스템을 테스트 하였고, 설계와 구현이 동일하게 되었음을 검증하였다.