• Journal of Korean Society for Geospatial Information Science
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• 제4권2호
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• pp.55-61
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• 1996

The objective of this paper is to show an optimal design model for branched water supply system which also can find the optimal location of pumping stations using linear programming. GIS is utilized in this model to better handle the data and the results front the optimization. The developed model considers hydraulic influences of some appurtenances such as supply tunnels and a filtration plant The model also considers tunnel construction cost which should be treated differently from pipe construction cost Different from other models presently available, the model guarantees a nonnegative pressure at every junction node in the system. The objective function includes annual operation cost (electricity rate) ill addition to initial construction cost, thus producing a more reasonable decision. The model selects the optimal diameter not in the form of continuous number but in the form of commercial discrete diameter (pipe size) using the pipe lengths as decision variables instead of pipe diameters. The model not only determines the optimal pumping head for each pumping station but also finds the optimal location and number of pumping stations. GIS is used to handle hydraulic and budgetary data automatically and to visualize the results for the of optimal design of the system. The model has been applied to an existing water supply system. 'The results show that the optimization model with the aid of GIS is helpful in the decision-nulling process for the design of more economical systems, and can be dot into practice successfully.

• School Mathematics
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• 제19권3호
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• pp.593-615
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• 2017

The purpose of this study is to develop a mobile-based math learning application and explore its application. In order to develop a learning application, the present study included literature review on math education involving mobile learning, investigation of literature related to mathematics education conducted in a digital environment, and method of use and implementation environment of existing math learning applications by type. Based on these preliminary investigation and analysis, an android version application, 'Mathematics Classroom for Middle School 3rd Graders' was developed. This application can be used for learning units such as Quadratic Functions and Graphs, Representative Value, and Variance and Standard Deviation. For the unit on Quadratic Functions and Graphs, the application was constructed so that students can draw various graphs by using the graphic mode and discuss their work with other students in the chatting room. For the unit on Representative Value, the application was constructed with the mathematical concept of representative value explained through animation along with activities of grouping data acquired after playing archery games by points or arranging them according to size so that students can study when and how to use median value, mode, and average. The application for Variance and Standard Deviation unit was also constructed in a way that allowed students to study the concept of variance and standard deviation and solve the problems on their own. The results of this study can be used as teaching & learning materials customized for individual student in math classes and will provide anyone the opportunity to engage in an interesting self-directed learning of math at anytime. Developed in the format of real life study, the application will contribute to helping students develop a positive attitude about math.

• Database Research
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• 제34권3호
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• pp.137-147
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• 2018

A key to a well-performing human activity recognition (HAR) system through machine learning technique is the availability of a substantial amount of labeled data. Collecting sufficient labeled data is an expensive and time-consuming task. To build a HAR system in a new environment (i.e., the target domain) with very limited labeled data, it is unfavorable to naively exploit the data or trained classifier model from the existing environment (i.e., the source domain) as it is due to the domain difference. While traditional machine learning approaches are unable to address such distribution mismatch, transfer learning approach leverages the utilization of knowledge from existing well-established source domains that help to build an accurate classifier in the target domain. In this work, we propose a transfer learning approach to create an accurate HAR classifier with very limited data through the multitask neural network. The classifier loss function minimization for source and target domain are treated as two different tasks. The knowledge transfer is performed by simultaneously minimizing the loss function of both tasks using a single neural network model. Furthermore, we utilize the unlabeled data in an unsupervised manner to help the model training. The experiment result shows that the proposed work consistently outperforms existing approaches.

• Journal of the Korean earth science society
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• 제34권6호
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• pp.515-523
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• 2013

The eastern coast of South Korea is expected to be damaged by volcanic ash when Mt. Baekdusan volcano erupts. Even if the amount of volcanic ash is small, it can be fatal on the agricultural sector withering many plants and causing soil acidification. Thus, in this paper, we aim to estimate agricultural losses caused by the volcanic ash and to visualize them with Google map. To estimate the volcanic ash losses, a damage assessment model is needed. As the volcanic ash hazard depends on the kind of a crops and the ash thickness, the fragility function of damage assessment model should represent the relation between ash thickness and damage rate of crops. Thus, we model the fragility function using the damage rate for each crop of RiskScape. The volcanic ash losses can be calculated with the agricultural output and the price of each crop using the fragility function. This paper also represents the estimated result of the losses in Gangwon province, which is most likely to get damaged by volcanic ashes in Korea. According to the result with gross agricultural output of Gangwon province in 2010, the amount of volcanic ash losses runs nearly 635,124 million wons in Korean currency if volcanic ash is accumulated over four millimeters. This amount represents about 50% of the gross agricultural output of Gangwon province. We consider the damage only for the crops in this paper. However, a volcanic ash fall has the potential to damage the assets for a farm, including the soil fertility and installations. Thus, to estimate the total amount of volcanic ash damage for the whole agricultural sectors, these collateral damages should also be considered.

• The Journal of Korean Institute of Communications and Information Sciences
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• 제32권9C호
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• pp.861-866
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• 2007

A clustering algorithm for Gaussian Probability Distribution Function (GPDF) data called Centroid Neural Network with a Bhattacharyya Kernel (BK-CNN) is proposed in this paper. The proposed BK-CNN is based on the unsupervised competitive Centroid Neural Network (CNN) and employs a kernel method for data projection. The kernel method adopted in the proposed BK-CNN is used to project data from the low dimensional input feature space into higher dimensional feature space so as the nonlinear problems associated with input space can be solved linearly in the feature space. In order to cluster the GPDF data, the Bhattacharyya kernel is used to measure the distance between two probability distributions for data projection. With the incorporation of the kernel method, the proposed BK-CNN is capable of dealing with nonlinear separation boundaries and can successfully allocate more code vector in the region that GPDF data are densely distributed. When applied to GPDF data in an image classification probleml, the experiment results show that the proposed BK-CNN algorithm gives 1.7%-4.3% improvements in average classification accuracy over other conventional algorithm such as k-means, Self-Organizing Map (SOM) and CNN algorithms with a Bhattacharyya distance, classed as Bk-Means, B-SOM, B-CNN algorithms.

• Journal of Educational Research in Mathematics
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• 제8권1호
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• pp.59-71
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• 1998

Recently, most classrooms in Korea are fully equipped with multimedia environments such as a powerful pentium pc, a 43″large sized TV, and so on through the third renovation of classroom environments. However, there is not much software teachers can use directly in their teaching. Even with existing software such as GSP, and Mathematica, it turns out that it doesn####t fit well in a large number of students in classrooms and with all written in English. The study is to analyze the characteristics of problem-solving process and to develop a computer program which integrates the instruction of problem solving into a regular math program in areas of quadratic functions and ellipses. Problem Solving in this study included two sessions: 1) Learning of basic facts, concepts, and principles; 2) problem solving with problem contexts. In the former, the program was constructed based on the definitions of concepts so that students can explore, conjecture, and discover such mathematical ideas as basic facts, concepts, and principles. In the latter, the Polya#s 4 phases of problem-solving process contributed to designing of the program. In understanding of a problem, the program enhanced students#### understanding with multiple, dynamic representations of the problem using visualization. The strategies used in making a plan were collecting data, using pictures, inductive, and deductive reasoning, and creative reasoning to develop abstract thinking. In carrying out the plan, students can solve the problem according to their strategies they planned in the previous phase. In looking back, the program is very useful to provide students an opportunity to reflect problem-solving process, generalize their solution and create a new in-depth problem. This program was well matched with the dynamic and oscillation Polya#s problem-solving process. Moreover, students can facilitate their motivation to solve a problem with dynamic, multiple representations of the problem and become a powerful problem solve with confidence within an interactive computer environment. As a follow-up study, it is recommended to research the effect of the program in classrooms.

• Communications of Mathematical Education
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• 제30권3호
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• pp.281-294
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• 2016

This study deals with the content that was developed by the authors and the utilization of the 'Interactive Engineering Math Laboratory (IEmath Lab).' IEmath Lab provides online review lectures as well as a wide range of examples and exercises from the curriculum of engineering mathematics courses. The lectures come with pre-coded Python-based SageMath cells through which students can run and modify the code directly from this free laboratory. IEmath Lab is accessible via mobile devices so that the students can use it anywhere, anytime for maximum learning effectiveness and achievement. IEmath Lab would be an ideal tool for the effective learning and teaching of engineering mathematics, which combines theory and practice.

• Journal of the Korean Association of Geographic Information Studies
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• 제14권3호
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• pp.126-135
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• 2011

In this study, the algorithm for priority area of forest fire surveillance was developed to enhance the effectiveness of fire detection. The high priority surveillance area for forest fire detection was defined as the area with not only low value of viewshed analysis of the lookouts and detection cameras but also high fire occurrence probability. To build the priority map, fuzzy function and map algebra were used. The analysis results of Bonghwa-gun, Gyeongbuk Province, showed that the surveillance priority of central and southern area is higher than north area. This algorithm could be used in the allocation of fire prevention resources and selection of suitable point for new fire detection system.

• Journal of Educational Research in Mathematics
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• 제14권3호
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• pp.305-325
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• 2004

This study is on the teaching-learning of parameter concept in secondary school mathematics. In our school mathematics curriculum, parameter concept is explicitly presented at high school mathematics textbook. But student have difficulty in understanding parameter concept because this concept is implicitly used in the textbook from 7-grade mathematics. Moreover, it is true that mathematics teacher give a little attention to student's understanding of parameter con- cept. In this study, we analyzed concept definition of parameter and the extension of parameter on the basis of preceding research, our mathematical curriculum, mathematical dictionaries. After that, we concluded that parameter is explicitly called in t where x= f(t), y= g(t) and parameter is implicitly treated in the learning of relation between quantities in our mathematical curriculum. We pointed to the importance of parameter concept in the successful learning of school algebra. Specially, when the level of algebra is in the learning of relation between quantities, parameter is the key concept for understanding and representing of families of equations or functions. In mathematics class, students have opportunity to reflect that what the role of each variable(parameter, dependent variable, independent variable etc.) is, and where the information which determines it comes from. It is for mathematical communications as well as learning school algebra. Therefore, mathematics teacher's didactical attention is more needed to student have a good concept image of parameter before they learn explicitly its concept definition.

• Journal of KIISE:Software and Applications
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• 제30권7_8호
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• pp.649-658
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• 2003

We propose a hierarchical architecture of ART2 Network for performance improvement and fast pattern classification model using fitness selection. This hierarchical network creates coarse clusters as first ART2 network layer by unsupervised learning, then creates fine clusters of the each first layer as second network layer by supervised learning. First, it compares input pattern with each clusters of first layer and select candidate clusters by fitness measure. We design a optimized fitness function for pruning clusters by measuring relative distance ratio between a input pattern and clusters. This makes it possible to improve speed and accuracy. Next, it compares input pattern with each clusters connected with selected clusters and finds winner cluster. Finally it classifies the pattern by a label of the winner cluster. Results of our experiments show that the proposed method is more accurate and fast than other approaches.