• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.10a
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• pp.207-210
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• 1996

Learning methodologies such as neural networks or genetic algorithms usually require long training times. Case based reasoning, however, attains peak performance swiftly and is often appropriate for learning even with small data sets. Previous work has shown that an extended case reasoning methodology can yield superior performance in the task of predicting financial data series. This paper examines the impact of reasoning procedures on stock price prediction. The following characteristics are evaluated: size of input vector, multiplicity of neighboring states, and a scaling factor for growth. The concepts are illustrated in the context of predicting the price of an individual price.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2004.11a
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• pp.189-192
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• 2004

The present much information of internet has to exist for innumerable user so that couldn't satisfy there's a variety of demand. so they have a demerit that search unnecessary information. However Web service is different with other mass media because It is possible that enable Mass Customization for Personalization strategy. In The paper suggest reasoning system that detect user connection location by using indirect abstraction techniques a kind of Case-based reasoning techniques.

• Korean Journal of Child Studies
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• v.35 no.3
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• pp.49-69
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• 2014

The purposes of this study were (1) to investigate children's moral judgment, justification reasoning in terms of aggressive behavior, and (2) it examined the relationship to false belief understanding. Children aged between 3 to 5 years(N = 120) participated in this study. Each child was interviewed individually and responded questions designed to measure his/her moral judgment and justification reasoning and false belief understanding. The 12 pictorial tasks consisted of selfish and altruistic intentions and three different types of acts (physical, verbal, relational) as responses to aggressive behavior. The results indicated that the kind of moral judgment used was different according to the intention and the types of acts. There were significant differences in children's justification reasoning according to the age and the types of acts. There was a positive relationship between false belief understanding and moral judgment, justification reasoning. This paper also provided a detailed discussion of the results and recommendations in the context of more general cognitive developmental changes.

• Journal of Korean Home Economics Education Association
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• v.12 no.3
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• pp.115-127
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• 2000

The purpose of this study is to develop lesson plans. teaching guide, and teaching materials applying practical reasoning teaching model in the area of ’human development and family relationship’in middle school home economics. The practical reasoning teaching model consists of five factors: Desired results, Awareness of context, Alternative approaches, Consequences of action, and Action. This study based on practical reasoning has following process: Curriculum development. Developing lesson pan, teaching material, an teaching guide, Experimental teaching and evaluation. Feedback, Production of CD-Rom. Teaching guide includes lesson plan, workbook multimedia materials and teaching resources. Especially teaching guide in CD-Rom can be used effectively in the actual teaching. In the classroom, this teaching model accomplished active and interesting participation of teachers and students. It is proposed that practical reasoning teaching model should be applied to other areas of home economics. In addition various teaching materials based on practical reasoning need to developed.

• International journal of advanced smart convergence
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• v.7 no.4
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• pp.185-196
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• 2018

Based on World Health Organization (WHO) children and adults have a problem with their oral health, such as Dental cavities and periodontal disease. It is not easy to obtain the high convince level of result of the dental and periodontal diseases. Because each of them have different degrees of uncertainty and there have several discounting factors (error rates) in different of survey. To solve this problem we propose the Dezert-Smarandache Theory (DSmT) for efficient combination of uncertain, imprecise and highly conflicting sources of information. Moreover, we apply the SEFP as a context reasoning. Finally, we make the simulation by using 12 surveys and compare Propotional Conflict Redistribution 5 (PCR5) and Dempster-Shafer Theory (DST) to show the belief or probability for the low, a heavy, high and ultra-high risk situation.

• Journal of Information Technology Services
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• v.9 no.1
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• pp.113-125
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• 2010

Recently, a smart space with Ubiquitous Environment is expanding rapidly due to the development of Ubiquitous Sensor Network. Therefore, more appropriate and intelligent services of the context awareness system is being required. The previous context awareness system can provide a service to the user through the inference only on the current situation. But, it does not handle certain situation properly when the system provides abnormal result. Also it does not have any proper method of generating reliable semantic data from sensed raw data. In this paper, we are trying to solve the problems as the following approaches. First, the system recognizes abnormal result and corrects it by learning feedback from the user. Second, we suggest a method of converting sensed data into more reliable semantic data. Third, we build the system based on an Ontological context model that is capable of interoperability and reusability. Therefore, the context awareness system of our study can enhance the previous system that can generate more reliable context data, can provide more effective inference method, and can provide more intelligent system structure.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1171-1174
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• 1993

A promising approach to get the benefits of neural networks and fuzzy logic is to combine them into an integrated system to merge the computational power of neural networks and the representation and reasoning properties of fuzzy logic. In this context, this paper presents a fuzzy neural network which is able to code fuzzy knowledge in the form of it-then rules in its structure. The network also provides an efficient structure not only to code knowledge, but also to support fuzzy reasoning and information processing. A learning scheme is also derived for a class of membership functions.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.4
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• pp.512-517
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• 2008

It is show that increasing of aged and handicapped people requires development of Ubiquitous computing technique to offer the specialized service for handicapped-people. For this, we need a development of Context Awareness and Service Reasoning Technique that the technique is supplied interaction between user and U-environment instead of the old unilateral relation. The old research of context awareness needed probabilistic presentation model like a Bayesian Network based on expert Systems for recognize given circumstance by a domain of uncertain real world. In this article, we define a domain of disorder activity assistant service application and context model based on ontology in diversified environment and minimized intervention of user and developer. By use this context model, we apply the structure learning of Bayesian Network and decide the service and activity to development of application service for handicapped people. Finally, we define the proper Conditional Probability Table of the structured Bayesian Network and if random situation is given to user, then present state variable of Activity and Service by given Causal relation of Bayesian Network based on Conditional Probability Table and it can be result of context awareness.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.3
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• pp.71-78
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• 2013

In this paper, we propose a method to infer the user's behavior and situation through collected data from multi-sensor equipped with a smart clothing and it was implemented as a smartphone App. User context reasoning and behavior determine is very difficult using single sensor depending on the measured value of the sensor varies from environmental noise. So, the reasoning and the digital filter algorithms to determine user behavior reducing noise and are required. In this paper, we used EWMA, Kalman Filter and SVM processing behavior for 3-axis value as a representative value of one.

• Journal of the Korea Society of Computer and Information
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• v.24 no.3
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• pp.159-166
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• 2019

The collection and manipulation of Internet of Things (IoT) data is increasing at a fast pace and its importance is recognized in every sector of our society. For efficient utilization of IoT data, the vast and varied IoT data needs to be reliable and meaningful. In this paper, we propose an IoT framework to realize this need. The IoT framework is based on a four layer IoT architecture onto which context aware computing technology is applied. If the collected IoT data is unreliable it cannot be used for its intended purpose and the whole service using the data must be abandoned. In this paper, we include techniques to remove uncertainty in the early stage of IoT data capture and collection resulting in reliable data. Since the data coming out of the various IoT devices have different formats, it is important to convert them into a standard format before further processing, We propose the RDF format to be the standard format for all IoT data. In addition, it is not feasible to process all captured Iot data from the sensor devices. In order to decide which data to process and understand, we propose to use contexts and reasoning based on these contexts. For reasoning, we propose to use standard AI and statistical techniques. We also propose an experiment environment that can be used to develop an IoT application to realize the IoT framework.