• Proceedings of the Korea Information Processing Society Conference
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• 2011.11a
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• pp.1031-1034
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• 2011

헬스케어에서의 상황정보는 사용자와 관련된 정보를 추론하여 질 높은 서비스를 제공하기 위해서 사용자가 필요로 하는 능동적이고 지능적인 서비스를 제공하여야 한다. 본 논문에서는 상황인식을 이용한 보건기상지수 모니터링 방법론을 제안한다. 체온, 기온, 조도, 습도, 자외선에 따른 건강지수를 사용자의 현재 위치에 따라 실시간으로 제공하기 위해서, GPS와 기상청의 RSS로부터 추출한 XML를 활용한다. 보건기상지수는 천식지수, 뇌졸중지수, 피부질환지수, 폐질환지수, 꽃가루농도지수, 도시고온지수의 요소에 따라 분석하여 모니터링한다. 상황정보 수집과 추론 과정을 통해 장치간의 유동성을 보장하는 환경에서 서비스를 지원하기 위한 도메인 상황정보를 구성한다. 이기종 디바이스의 유동성이 보장되는 환경에서 새로운 상황이 존재하면 추가된 상황정보의 서비스를 지원하기 위해서 Naive Bayes 분류자를 이용한다. 상황정보 수집, 상황인식 추론, 상황정보 모델링에 따른 새로운 상황 분류하는 방법론에 대해서 논리적 타당성과 유효성을 검증한다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4D
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• pp.573-580
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• 2006

The Saturation headway is a major parameter in estimating the intersection capacity and setting the signal timing. But Existing algorithms are still far from being robust in dealing with factors related to the variation of saturation headways at signalized intersections. So this study apply the fuzzy inference system using ANFIS. The ANFIS provides a method for the fuzzy modeling procedure to learn information about a data set, in order to compute the membership function parameters that best allow the associated fuzzy inference system to track the given input/output data. The climate conditions and the degree of brightness were chosen as the input variables when the rate of heavy vehicles is 10-25 %. These factors have the uncertain nature in quantification, which is the reason why these are chosen as the fuzzy variables. A neuro-fuzzy inference model to estimate saturation headways at signalized intersections was constructed in this study. Evaluating the model using the statistics of $R^2$, MAE and MSE, it was shown that the explainability of the model was very high, the values of the statistics being 0.993, 0.0289, 0.0173 respectively.

• Transactions of the Korean Society of Mechanical Engineers
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• v.16 no.10
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• pp.1833-1840
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• 1992

In the diagnostic process for automobile, Neuro-Fuzzy technique was compared with the conventional diagnostic method for the verification of performance, and proto-type system was developed. For the utilities of the system, 1/3 octave filter(band-pass filter) and A/D converter were used for data acquisition and then data were analyzed using octave band processing and pattern recognition using hamming network algorithm. In order to raise the reliability of the diagnostic results by considering many operating variables and condition of automobile to be diagnosed, fuzzy inference technique was applied in combining several information. The validation of this diagnostic system was examined through computer simulation and experiment, and it showed an acceptable performance for diagnostic process.

• The Korean Journal of Applied Statistics
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• v.27 no.4
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• pp.589-603
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• 2014

When consecutive data follows different distributions(depending on the time interval) change-point detection infers where the changes occur first and then finds further inferences for each sub-interval. In this paper, we investigate the Bayesian detection of multiple change points. Utilizing the reversible jump MCMC, we can explore parameter spaces with unknown dimensions. In particular, we consider a model where the signal is a piecewise linear function. For the Bayesian inference, we propose a new Bayesian structure and build our own MCMC algorithm. Through the simulation study and the real data analysis, we verified the performance of our method.

• Journal of Korean Home Economics Education Association
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• v.14 no.3
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• pp.1-9
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• 2002

The objectives of this study were to measure the effect of Practical Reasoning Instruction in Home Economics : specifically. its effect on developing of critical thinking as well as to evaluate the degree of the critical thinking process. with reference to its sub-factors and the level. The research subjects were consisted of the experimental group of 119 freshman class female students from the “A” High School and the comparative group of 110 freshman class female student from the “C” High School in the city of Chung-Ju. This research was conducted under the pre-post test control group design. administering the Pre-Post testing to both the experimental and the comparative groups. The experimental group was subjected to Practical Reasoning Instruction in Home Economics : whereas the comparative group was taught under the lecture-Instruction in Home Economics The research findings are as follows: 1. Those who studied Home Economics under the Practical reasoning method scored higher on the critical thinking Process than the comparative group students who were taught Home Economics in the lecture-style approach. 2. The experimental group of students. who studied Home Economics under the Practical reasoning method. scored higher than the comparative group in their ability to perceive assumption and to render Judgment among the five sub-factors of their critical thinking processes.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.6
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• pp.603-610
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• 2015

This paper presents a multimodal sensor system that can determine the location of house space by analyzing the postures and heights of the residents. It consists of two sensors: a tilt sensor and an altimeter sensor. The tilt sensor measures the static and dynamic postures of the residents, and the altimeter sensor measures their heights. The sensor system includes a Bluetooth transmitter, and the server receives the measured data and determines the location in the house. We describe the process determining the locations of the residents after analyzing their postures and behaviors from the measured data. We also demonstrate the usefulness of the proposed system by applying it to a real environment.

• Journal of Navigation and Port Research
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• v.26 no.1
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• pp.8-14
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• 2002

The collisions of vessel at sea show high among the whole marine accidents. Especially, the accidents of fishing vessels take the largest portion of the collisions. Therefore, a technique to reduce these accidents should be developed. The automatic control for avoiding collision suggested in this study consists of two steps. The first is recognizing collision risk with fuzzy Theory and the other is maneuvering the model ship on the basis of collision risk calculated from the first step. The information form the position and estimated time of collision point(DCPA and TCPA) is used to assess the collision risk. To verify this system, a fishing vessel was simulated according to MMG mathematical model. The simulations result shows quite good application in avoiding the collision of ship.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.3
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• pp.330-336
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• 2005

Existing Bayesian update method using ultrasonic sensors only for mobile robot map building has a problem of the quality of map being degraded in the wall with irregularity, which is caused by the wide beam distribution. For improving this problem, an infrared sensors aided map building method is presented in this paper. Information of obstacle at each region in ultrasonic sensor beam is acquired using the infrared sensors and the information is used to get the confidence of ultrasonic sensor information via fuzzy inference system and genetic algorithm. Combining the resulting confidence with the result of Bayesian update method, an improve map is constructed. The proposed method showed good results in the simulations and experiments.

• The Transactions of the Korea Information Processing Society
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• v.6 no.4
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• pp.977-987
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• 1999

The current traffic signal control systems are operated depending on the pre-planned control scheme or the selected control scheme according to a period of time. The problem with these types of traffic control systems is that they can not cope with variant traffic flows appropriately. Such a problem can be difficult to solve by using binary logic. Therefore, in this 0paper, we propose a traffic signal control system which can deal wit various traffic flows quickly and effectively. The proposed controller is operated under uncertainty and in a fuzzy environment. It show the congestion of road traffic by using fuzzy logic, and it determines the length of green signal by means of a fuzzy inference engine. It modeled using petri-net to verify its validation.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.6
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• pp.799-805
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• 2010

In this paper, we propose an intelligent navigation system that selects a proper route for user and applies the user's preference, user's tendency and environmental state estimated by driving information of user and road state. The system uses data of sensors, navigation and intelligent transport system to evaluate conditions of roads and it considers state of user's emotion. The system also uses soft-computing method to infer and learn the user's preference and tendency. We verify the proposed algorithm by computer simulation.