• Journal of Digital Contents Society
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• v.6 no.4
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• pp.235-242
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• 2005

This Study examines influencing factors such as input, process, and output variables on1 student's satisfaction in cyber-education. That is to study on the effectiveness of input, process, and output variables for cyber-education and how does student's interaction moderate influencing factors and student satisfaction. The study was carried out through literature and empirical study. Questionnaire was used to varify the hypothesis based on which the input-process-output with system models were established. The result of hypothesis verification in this study is as follows : First, learning hour and grade showed a positive influence on the students' satisfaction in learning factors. Second reliant of professor, recognized teaming participate, and contents showed a positive influence on the students' satisfaction in system factors. Third, an interesting findings emerged throughout the analysis, showed that process variables were rather meaning factor than input variables.

• Education of Primary School Mathematics
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• v.9 no.2 s.18
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• pp.89-105
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• 2005

The purposes of this study were to develop an effective teaching material for slow learners in mathematics and to investigate its effect. To achieve the first goal, several pre-used teaching material and the 7th national curriculum for elementary school mathematics were analyzed to set up a framework fur developing new teaching material. Using these developed framework and curriculum data, 370 units of lesson were developed from the 3rd grade to the 6th grade. To investigate the effect of the material, 3 slow learners (2 from the 5th and 1 from the 6th grade) were selected through diagnostic tests. Then supplementary lessons were administered after school to relieve their disability accordingly for seven months. During the lessons(lasted about 40 minutes), teacher observed the subjects in detail and .judged the teaming sequence and the learning pace. Through this observation and the test administered after the treatment, several conclusions were drawn as follow: First, the supplementary lessons using the developed teaching material helped slow learners understand mathematics and solve problems. Especially, the test scores gained on formative evaluation became higher. This might be caused by the material that enabled to relieve the disablement and the teaching method that aimed to give a meaningful mathematical experience. Second, the supplementary lessons affected positively to the affective domain of the slow learners. They convinced themselves to their mathematical ability and became active in their mathematics class. This was observed by researcher and the class teacher in their lessons. Positive attitude toward mathematics and their ability is quite important for mathematics learning especially fur slow learners in mathematics.

• Journal of the Korean Geotechnical Society
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• v.18 no.5
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• pp.123-132
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• 2002

The purpose of this study is to predict the shear behavior of the weathered mudstone soil using dynamic neural network which mimics the biological system of human brain. SNN and RNN, which are kinds of the dynamic neural network realizing continuously a pattern recognition as time goes by, are used to predict a nonlinear behavior of soil. After analysis, parameters which have an effect on learning and predicting of neural network, the teaming rate, momentum constant and the optimum neural network model are decided to be 0.5, 0.7, 8$\times$18$\times$2 in SU model and 0.3, 0.9, 8$\times$24$\times$2 in R model. The results of appling both networks showed that both networks predicted the shear behavior of soil in normally consolidated state well, but RNN model which is effective fir input data of irregular patterns predicted more efficiently than SNN model in case of the prediction in overconsolidated state.

• Journal of Korean Elementary Science Education
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• v.24 no.1
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• pp.86-101
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• 2005

In this study, a brain-basrd model for science teaching and learning was developed based on the natural processes which human acquire knowledge about a natural object or on event, the major domains of science educational objectives of the national curriculum, and the human brain's organizational patterns and functions. In the model, each educational objective domain is related to the brain regions as follows: The affective domain is related to the limbic system, especially amygdala of human brain which is involved in emotions, the psychomotor domain is related to the occipital lobes of human brain which perform visual processing, temporal lobes which perform functions of language generating and understandng, and parietal lobes which receive and process sensory information and execute motor activities of body, and the cognitive domain is related to the frontal and prefrontal lobes which are involved in think-ing, planning, judging, and problem solving. The model is a kind of procedural model which proceed fiom affective domain to psychomotor domain, and to cognitive domain of science educational objective system, and emphasize the order of each step and authentic assessment at each step. The model has both properties of circularity and network of activities. At classrooms, the model can be used as various forms according to subjects and student characteristics. STS themes can be appropriately covered by the model.

• Journal of Korean Elementary Science Education
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• v.24 no.4
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• pp.399-416
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• 2005

The purpose of this study was to examine the relationship between science teaching practices and beliefs about the nature of science. Defining teachers' beliefs as a broad construct, the researcher tried to examine not only the teachers' understanding about the nature of science, but also the effect and reflection in science teaching practices with regards to the nature of science. Guiding research questions were how the teachers' science teaching practices reflected their beliefs about the nature of science. The methodology of this study was qualitative approach that included interviews, classroom observations, and instructional materials. At an urban area of Korea, five beginning elementary teacher was chosen. The cross-case and grounded theory study design were adopted as data analysis process. The results of data analysis were checked by teachers for internal validity. This study identified the teachers' beliefs about the nature of science suggested by many researchers and revealed that these teachers' beliefs reflected a little in science teaching practices. On the occasion it was reflected, restricted merely within the narrow limits the way to teach the concepts and contents presented in science curriculum. In addition, some of the obstacles that these teachers' beliefs did not reflect the science teaching practices with regards to the nature of science were investigated in this study.

• Journal of Korean Elementary Science Education
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• v.24 no.4
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• pp.351-359
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• 2005

The aims of this research are to analyze elementary preservice teacher's conception and causes of their misconceptions on biological reproduction and inheritance. In future, it would be also to provide useful data for the effective teaching-teaming method in the elementary school as well as opportunities to correct their misconceptions, which help elementary preservice teachers have the appropriate scientific conceptions. Thirty kinds of test questions were designed in science curriculum for elementary students and biology textbook for university students in order to develop reproduction and inheritance's concepts. The questionnaire was given to 166 junior students of university of education in a local city. All statistical analysis was performed using SPSS version 10.0 program. The major results are as follows: Among 30 test questions, 2 questions in plants, 5 questions in animals and 2 questions in gene were appeared as misconceptions over $50\%$. The major reason to hold the misconceptions was influenced by 'learning up to now' category. The selection reasons of response were significantly different between scientific conceptions and misconceptions in 10 questions by analysis of variance. The gender also showed statistically significant differences between scientific conception and misconception in 3 questions by $\chi^2$ test. The selection reasons according to gender were significantly different between male and female students in 5 questions. For the reasons in forming misconceptions, they may cause by stereotype, conscious priority, differences of experiences, interest or attention, lack of professional Knowledge, and so on. Therefore, it was concluded that this research may help elementary preservice teachers to reconsider their conception for reproduction and inheritance and to be successful in science instructions fur elementary students.

• Journal of the Korean Institute of Landscape Architecture
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• v.29 no.6
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• pp.50-61
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• 2002

As recognition and polices for plans to preserve natural resources and to develop environment-friendly space in school education is developed, not only organization of curriculums related to these is required but also facilities for the education are indispensable. Therefore, this study tries to suggest several standards on matters including kinds and scale of facilities and the introduction of species by facilities required for outdoor teaming spaces for environmental education in the elementary school system. The methods of this study include researching various records related to environmental education in elementary school, researching the present condition of outdoor learning space installed and operating in the existing schools by making an on-the-spot survey, and analyzing appearance frequencies of plants and animals displayed in the text. In addition, the actual conditions of the facility use and management were investigate through a questionnaire, We chose and diagrammed a model of the installed facilities by putting the results together. For analyses the investigated eight schools, were categorized as ‘facilities-arranged type’or ‘connection type with ecological park’. The first type distributed and arranged facilities, including meteorological observatory, rocky park, experience-learning area, ecological pond, animal-breeding farm and field-leaning area into appropriate locations according to the site conditions of the school while the second type created a natural learning place by integrating several facilities and arranging areas such as an animal-breeding farm and experience-learning area into appropriate sites. In this study, essential facilities for outdoor learning are classified into ecological park, experience-loaming area, field loaming area, and for natural learning, meteorological observatory, animal-breeding farm, and greenhouse.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.8
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• pp.1743-1750
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• 2003

DC motor requires a rotor speed sensor for accurate speed control. The speed sensors such as resolvers and encoders are used as a speed detector, but they increase cost and size of the motor and restrict the industrial drive applications. So in these days, many papers have reported in the sensorless operation of DC motor〔3­5〕. This paper presents a new sensorless strategy using neural networks〔6­8〕. Neural network has three layers which are input layer, hidden layer and output layer. The optimal neural network structure was tracked down by trial and error, and it was found that 4­16­1 neural network structure has given suitable results for the instantaneous rotor speed. Also, learning method is very important in neural network. Supervised learning methods〔8〕 are typically used to train the neural network for learning the input/output pattern presented. The back­propagation technique adjusts the neural network weights during training. The rotor speed is gained by weights and four inputs to the neural network. The experimental results were found satisfactory in both the independency on machine parameters and the insensitivity to the load condition.

• Journal of KIISE:Software and Applications
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• v.29 no.9
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• pp.654-668
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• 2002

In this paper, we present an empirical study for improving the Korean text chunking based on machine learning and feature set selection approaches. We focus on two issues: the problem of selecting feature set for Korean chunking, and the problem of alleviating the data sparseness. To select a proper feature set, we use a heuristic method of searching through the space of feature sets using the estimated performance from a machine learning algorithm as a measure of "incremental usefulness" of a particular feature set. Besides, for smoothing the data sparseness, we suggest a method of using a general part-of-speech tag set and selective lexical information under the consideration of Korean language characteristics. Experimental results showed that chunk tags and lexical information within a given context window are important features and spacing unit information is less important than others, which are independent on the machine teaming techniques. Furthermore, using the selective lexical information gives not only a smoothing effect but also the reduction of the feature space than using all of lexical information. Korean text chunking based on the memory-based learning and the decision tree learning with the selected feature space showed the performance of precision/recall of 90.99%/92.52%, and 93.39%/93.41% respectively.

• Journal of KIISE:Software and Applications
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• v.31 no.7
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• pp.849-858
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• 2004

Most of supervised teaming algorithms could be applied after that continuous variables are transformed to categorical ones at the preprocessing stage in order to avoid the difficulty of processing continuous variables. This preprocessing stage is called global discretization, uses the class distribution list called bins. But, when data are large and the range of the variable to be discretized is very large, many sorting and merging should be performed to produce a single bin because most of global discretization methods need a single bin. Also, if new data are added, they have to perform discretization from scratch to construct categories influenced by the data because the existing methods perform discretization in batch mode. This paper proposes a method that extracts sample points and performs discretization from these sample points in order to solve these problems. Because the approach in this paper does not require merging for producing a single bin, it is efficient when large data are needed to be discretized. In this study, an experiment using real and synthetic datasets was made to compare the proposed method with an existing one.