• The KIPS Transactions:PartD
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• v.8D no.3
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• pp.203-210
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• 2001

These days data is being collected and accumulated in a wide variety of fields. Stored data itself is to be an information system which helps us to make decisions. An information system includes many kinds of necessary and unnecessary attribute. So many algorithms have been developed for finding useful patterns from the data and reasoning approximately new objects. We are interested in the simple and understandable rules that can represent useful patterns. In this paper we propose an algorithm which can reduce the information in the system to a minimum, based on a probabilistic rough set theory. The proposed algorithm uses a value that tolerates accuracy of classification. The tolerant value helps minimizing the necessary attribute which is needed to reason a new object by reducing conditional attributes. It has the advantage that it reduces the time of generalizing rules. We experiment a proposed algorithm with the IRIS data and Wisconsin Breast Cancer data. The experiment results show that this algorithm retrieves a small reduct, and minimizes the size of the rule under the tolerant classification rate.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.7
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• pp.907-912
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• 2007

The present level of ubiquitous computing technology have developed to the point where Home-server provides services that user require directly for user in the intelligent space. But it will need intelligent system to provides more active services for user in the near future. In this paper, we define the environment information about situation that user is in as Context, and collect the Context that stereotype as 4W1H form for construct the system that can decision service will be provide from information about a situation that user is in, without user's involvement. Additionally we collect information about user's emotional state, use these informations as nodes of Bayesian network for probabilistic reasoning. From that, we materialize Context Awareness system about it that what kind of situation user is in. And, we propose the Context-based Service reasoning model using Bayesian Network from the result of Context Awareness.

• Journal of Educational Research in Mathematics
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• v.19 no.2
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• pp.233-256
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• 2009

The notions of conditional probability and independence are fundamental to all aspects of probabilistic reasoning. Several previous studies identified some misconceptions in students' thinking in conditional probability. However, they have not analyzed enough the nature of conditional probability. The purpose of this study was to analyze conditional probability and students' knowledge on conditional probability. First, we analyzed the conditional probability from mathematical, historico-genetic, psychological, epistemological points of view, and identified the essential aspects of the conditional probability. Second, we investigated the high school students' and undergraduate students' thinking m conditional probability and independence. The results showed that the students have some misconceptions and difficulties to solve some tasks with regard to conditional probability. Based on these analysis, the characteristics of reasoning about conditional probability are investigated and some suggestions are elicited.

• Journal of the Korea Institute of Building Construction
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• v.18 no.3
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• pp.295-303
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• 2018

In the DBB delivery system, the design stage and the construction stage are separated. Because of this, design changes frequently occur, and problems such as construction cost overrun, schedule delay, and quality deterioration happen as well. Recently, in the construction industry CM at Risk(CM@R) delivery system, which can systematically solve the above-mentioned problems of DBB delivery system, meet various demands of clients, and overcome the limited cost and period. In the CM@R delivery system, the contractor negotiates for a maximum guaranteed price(GMP) with the client at the design stage, and the CM performer carries out the construction within the GMP. However, uncertainties are inherent in the GMP calculation because the calculation is based on unfinished drawings and documents. In this study, a Probabilistic Earlier GMP Calculation Method by combining a probabilistic tool of Monte Carlo simulation with a case based reasoning is proposed so that the uncertainty in GMP calculation is reflected. After the earlier GMP is calculated, a process to calculate the $2^{nd}$ GMP at the time of around 80 % of detailed deign and to negotiate with the client to fix the final GMP is proposed. The Probabilistic Earlier GMP Calculation Method is verified through the case study. In this study, researchers set the range of GMP through the proposed probabilistic GMP calculation and tried to reduce the risk through negotiation between the client and the CM performer. The proposed method and process would contribute to the successful introduction of CM@R in Korea.

• Journal of Digital Convergence
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• v.10 no.2
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• pp.287-292
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• 2012

In this paper, user personalized services through the emotion perception required to support location-based sensing data preprocessing techniques and emotion data preprocessing techniques is studied for user's emotion data building and preprocessing in V-A emotion model. For this purpose the granular context tree and string matching based emotion pattern matching techniques are used. In addition, context-aware and personalized recommendation services technique using probabilistic reasoning is studied for personalized services based on context awareness.

• Research in Mathematical Education
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• v.18 no.4
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• pp.289-305
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• 2014

The current mathematical education calls for a learning environment from the constructionism perspective that actively creates mathematical objects. This research first analyzes JavaMAL's expression 'move' that enables students to express the agent's behavior constructively before they learn vector as a formal concept. Since expression 'move' is based on a coordinate, it naturally corresponds with the expression of vectors used in school mathematics and lets students take an embodied approach to the concept of vector. Furthermore, as a design tool, expression 'move' can be used in various activities that include vector structure. This research studies the educational significance entailed in JavaMAL's expression 'move'.

• Journal of The Korean Association For Science Education
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• v.17 no.3
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• pp.273-288
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• 1997

The purpose of this study was to review the studies related to the problem of context in science education. Firstly, studies on context and context effects in science education (and also those related in cognitive psychology) were summarized according to the topics concerning science learning, such as deductive reasoning and probabilistic judgement, controlling variables, scientific inquiry skills, memory and consistency of misconceptions, selecting cognitive strategies and problem solving, achievement and momentum effect, and interest, religion and culture. Secondly, the common problems appeared from the analysis of the studies were discussed, such as (1) how to define contexts?, (2) how to classify contexts?, (3) how to characterize the effects of contexts? and (4) how to explain the context effects? Finally, the implications of the analysis of the studies on the problem of context were discussed in terms of recent development of science education, such as misconception studies, STS science education and the application of the history of science to science teaching.

• Journal of the Korea Institute of Building Construction
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• v.11 no.1
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• pp.91-99
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• 2011

Bayesian network is a form of probabilistic graphical model. It incorporates human reasoning to deal with sparse data availability and to determine the probabilities of uncertain cases. In this research, bayesian network is adopted to model the problem of construction project cost. General information, time, cost, and material, the four main factors dominating the characteristic of construction costs, are incorporated into the model. This research presents verify a model that were conducted to illustrate the functionality and application of a decision support system for predicting the costs. The Markov Chain Monte Carlo (MCMC) method is applied to estimate parameter distributions. Furthermore, it is shown that not all the parameters are normally distributed. In addition, cost estimates based on the Gibbs output is performed. It can enhance the decision the decision-making process.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.106-112
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• 1993

A new model for the construction of a sonar map in a specular environment has been developed ad implemented. In a real world where most of the object surfaces are specular ones, a sonar sensor suffers from a multipath effect which results in a wrong interpretation of an objects's location. To reduce this effect and hence to construct a reliable map of a robot's surroundings, a probabilistic approach based on Bayesian reasoning is adopted to both evaluation of object orientations and estimation of an occupancy probability of a cell by an object. The usefulness of this approach is illustrated with the results produced by our mobile robot equipped with ultrasonic sensors.

• Korean Journal of Computational Design and Engineering
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• v.5 no.4
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• pp.319-326
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• 2000

Expert systems using uncertain and ambiguous knowledge are not of the recent interests about uncertainty problem for performing inference similar to the decision making of a human expert. Human factors on rule-based systems often involve uncertain information. Expert systems had been used the methods of conflict resolution in a rule conflict situation, but this methods not properly solved the rule conflict. If a human expert appends a new rule to an original rule base, the rule base rightly causes a rule conflict. In this paper, the problem of rule conflict is regarded as one in which uncertainty of information is fundamentally involved. In the reduction of problem with uncertainty, we propose an enhanced rule ordering method, which improve the rule ordering method using Dempster-Shafer theory. We also propose a combinative index, which involve human factors of experts decision making.