• Journal of the Korean Institute of Landscape Architecture
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• v.37 no.3
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• pp.1-10
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• 2009

Wooded areas that are a part of school campuses are one type of urban forest. Most schools located in an urban environment make an excellent setting for a forest in terms of location and area. These kinds of wooded spaces also make the city greener and healthier. As a place where students spend a great deal of time, schools can also be a venue for environmental education. The creation of wooded areas in schools currently has focused on the end result only; by ignoring student needs and participation, these areas have not had a significant influence on student environmental education. Previous studies based on questionnaire survey are significant in that they have quantified subjective qualitative data via Likert Scale. There has been, however, a problem in quantifying the more ambiguous subjective data. Therefore, this paper has attempted to investigate those factors that have an influence on student satisfaction with the wooded areas of their school campus using Fuzzy Theory with elementary school students in Gyeongsangbuk-do. A change was observed in terms of the ranking of arithmetic mean values of 'school peculiarity' and 'emotion evolution' and center of gravity, which has adopted Fuzzy Theory, proving that Fuzzy Theory could rationally objectify qualitative data such as human thoughts. In terms of the influential factors on the satisfaction with school forests(regression coefficient), 'school uniqueness(0.159)' was the highest, followed by 'many trees(0.142),' 'importance of nature(0.136)' and 'emotion evolution(0.130).' This paper may therefore be useful as basic data for objective questionnaire surveys and the development of school forests.

• Korean Journal of Remote Sensing
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• v.11 no.3
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• pp.49-60
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• 1995

Features of geological lineaments generally play an important role at the data interpretation concerned geological processes, mineral exploration or natural hazard risk estimation. However, there are intrinsically discordances between lineaments-related features extracted from surficial geological syrvey and those from satellite imagery;nevertheless, any data set contained those information should not be considred as less meaningful within their own task. For the purpose of effective utilization task of extracted lineaments, the mathematical scheme, based on fuzzy set theory, for practical integration of various types of rasterized data sets is studied. As a real application, the geological map named Homyeong sheet(1:50,000) and the Landset TM imageries covering same area were used, and then lineaments-related data sets such as lineaments on the geological map, lineaments extracted from a false-color image composite satellite, and major drainage pattern were utilized. For data fusion process, fuzzy membership functions of pixel values in each data set were experimentally assigned by percentile, and then fuzzy algebraic sum operator was tested. As a result, integrated lineaments by this well-known operator are regarded as newly-generated reasonable ones. Conclusively, it was thought that the implementation within available GISs, or the stand-alone module for general applications of this simple scheme can be utilized as an effective scheme can be utilized as an effective scheme for further studies for spatial integration task for providing decision-supporting information, or as a kind of spatial reasoning scheme.

• Journal of Korean Tunnelling and Underground Space Association
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• v.2 no.2
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• pp.11-21
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• 2000

Tunnelling has been created as a great extent in view of less land space available because the growth of population in metropolitan has been accelerated at a faster pace than the development of the cities. In tunnelling, it is often faced that measures are obliged to be taken without confirmation for such abnormality as diverged movement of surrounding rock mass, growing crack of shotcrete and yielding of rockbolts. In this case, it is usually said that the judgments of experienced engineers for the selection of measure are importance and allowed us to get over the situations in many construction sites. But decrease of such experienced engineers need us to develop the new system to assist the selection of measures for the abnormality without any experiences of similar tunnelling sites. In this study, After a lot of tunnelling reinforcement methods were surveyed and the detail application were studied, an expert system was developed to predict the safety of tunnel and choose proper tunnel reinforcement system using fuzzy quantification theory and fuzzy inference rule based on tunnel information database. The expert system developed in this study have two main parts named pre-module and post-module. Pre-module decides tunnel information imput items based on the tunnel face mapping information which can be easily obtained in-situ site. Then, using fuzzy quantification theory II, fuzzy membership function is composed and tunnel safety level is inferred through this membership function. The comparison result between the predicted reinforcement system level and measured ones was very similar. In-situ data were obtained in three tunnel sites including subway tunnel under Han river. This system will be very helpful to make the most of in-situ data and suggest proper applicability of tunnel reinforcement system developing more resonable tunnel support method from dependance of some experienced experts for the absent of guide.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.1
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• pp.20-26
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• 2008

As they have more and more intelligence robots or computers these days, so the interaction between intelligence robot(computer) - human is getting more and more important also the emotion recognition and expression are indispensable for interaction between intelligence robot(computer) - human. In this paper, firstly we extract emotional features at speech signal and facial image. Secondly we apply both BL(Bayesian Learning) and PCA(Principal Component Analysis), lastly we classify five emotions patterns(normal, happy, anger, surprise and sad) also, we experiment with decision fusion and feature fusion to enhance emotion recognition rate. The decision fusion method experiment on emotion recognition that result values of each recognition system apply Fuzzy membership function and the feature fusion method selects superior features through SFS(Sequential Forward Selection) method and superior features are applied to Neural Networks based on MLP(Multi Layer Perceptron) for classifying five emotions patterns. and recognized result apply to 2D facial shape for express emotion.

• Journal of Korea Society of Industrial Information Systems
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• v.9 no.1
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• pp.92-102
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• 2004

Performance assessment was introduced to improve self-directed learning and method of assessment for differenced learning when the seventh educational curriculum was enforced. Written examinations often fail to properly assess students higher thinking abilities ad problem solving abilities. Performance assessment addresses this drawback and also allows normalization of class and school quality. However, performance assessment also has drawbacks that could lead to faulty assessment due to lack of fairness, reliability and validity of grading, ambiguity of grading standard etc. This study proposes a fuzzy performance assessment system to address the drawbacks of the conventional performance assessment. This paper presents in objective and reliable performance assesment method through fuzzy reasoning, design of fuzzy membership function. We define a fuzzy rule analyzing factor that influences in each sacred ground of performance assessment and accounts for the principle subject The proposed performance assessment method divides into three categories, namely, formation estimation subject estimation and design of membership function. Performance assessment result that is worked through fuzzy performance assessment system can reduce the burden of appraisal's fault and provide. We fair and reliable assessment results through grading that have correct standard mid consistency to students.

• Journal of the Korean Institute of Intelligent Systems
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• v.3 no.2
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• pp.18-35
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• 1993

The water level control system of the steam generator in a pressurized water reactor and its control problems are analysed. In this work the stable control strategy during the low power operation and transient states is studied. To solve the problem, a fuzzy logic control method is applied as a basic algorithm of the controller. The control algorithm is based on the operator's knowledges and the experiences of manual operation for water level control at the compact nuclear simulator set up in Korea Atomic Energy Research Institute. From a viewpoint of the system realization, the control variables and rules are established considering simpler tuning and the input-output relation. The control strategy includes the dynamic tuning method and employs a substitutional information using the bypass valve opening instead of incorrectly measured signal at the low flow rate as the fuzzy variable of the flow rate during the pressure control mode of the steam generator. It also involves the switching algorithm between the control valves to suppress the perturbation of water level. The simulation results show that both of the fine control action at the small level error and the quick response at the large level error can be obtained and that the performance of the controller is improved.

• Spatial Information Research
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• v.11 no.2
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• pp.101-117
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• 2003

High resolution satellite image analysis has been recognized as an effective technique for monitoring local land-cover and atmospheric changes. In this study, a new high resolution map for land-cover was generated using both high-resolution IKONOS image and conventional land-use mapping. Fuzzy classification method was applied to classify land-cover, with minimum operator used as a tool for joint membership functions. In separateness analysis, the values were not great for all bands due to discrepancies in spectral reflectance by seasonal variation. The land-cover map generated in this study revealed that conifer forests and farm land in the ground and tidal flat and beach in the ocean were highly changeable. The kappa coefficient was 0.94% and the overall accuracy of classification was 95.0%, thus suggesting a overall high classification accuracy. Accuracy of classification in each class was generally over 90%, whereas low classification accuracy was obtained for classes of mixed forest, river and reservoir. This may be a result of the changes in classification, e.g. reclassification of paddy field as water area after water storage or mixed use of several classification class due to similar spectral patterns. Seasonal factors should be considered to achieve higher accuracy in classification class. In conclusion, firstly, IKONOS image are used to generated a new improved high resolution land-cover map. Secondly, IKONOS image could serve as useful complementary data for decision making when combined with GIS spatial data to produce land-use map.