• Journal of the Korean School Mathematics Society
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• v.12 no.2
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• pp.309-325
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• 2009

The purpose of the study was to investigate the differences between Korean mathematics textbooks and CPMP textbooks in the view of conceptual network, structure of mathematical contents, instructional design, and teaching and learning environment to explore the implications for mathematics education in Korea. According to the results, Korean textbooks emphasized the mathematical structures and conceptual network, on the other hand, CPMP textbooks focused on making connections between mathematical concepts and corresponding real life situations as well as mathematical structures. And generalizing mathematical concepts at the symbolic level was very important objective in Korean textbooks, but in the CPMP textbooks, investigating mathematical ideas and solving problems in diverse contexts including real- life situations were considered very important. Teachers using Korean textbooks preferred an explanatory teaching method with the use of concrete manipulatives and student worksheet, however, teachers using CPMP textbooks emphasized collaborative group activities to communicate mathematical ideas and encouraged students to use graphing calculators when they explore mathematical concepts and solve problems.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.24 no.5
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• pp.379-387
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• 2006

The real world is spatially modelled conceptually either as discrete objects or earth surface. The generated data models are then usually represented as vector and raster respectively. Although there are limited cases where only one data model is sufficient to solve the spatial problem at hand, it is now generally accepted that GIS should be able to handle various types of data model. Recent advances in spatial technology introduced even more variety of heterogeneous data models and the need is ever growing to handle and manage efficiently these large variety of spatial data. The OGC (Open GIS Consortium), an international organization pursuing standardization in the geospatial industry. recently introduced the GMLJP2 (Geographic Mark-Up Language JP2) format which enables store and handle heterogeneous spatial data. The GMLJP2 format, which is based on the JP2 format which is an abbreviation for JPEG2000 wavelet image compression format, takes advantage of the versatility of the GML capabilities to add extra data on top of the compressed image. This study takes a close look into the GMLJP2 format to analyse and exploit its potential to handle and mange hetergeneous spatial data. Aerial image, digital map and LIDAR data were successfully transformed end archived into a single GMLJP2 file. A simple viewing program was made to view the heterogeneous spatial data from this single file.

• Journal of Internet Computing and Services
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• v.2 no.2
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• pp.71-93
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• 2001

Commonly to design a database system. a conceptual database has to be designed and then it is transformed into a logical database schema prior to building a target database system. This paper proposes a method which transforms a Temporal Entity-Relationship Model(TERM) into a Temporal Object-Oriented Model(TOOM) to build an efficient database schema. I formalize the time concept in view of object versioning and specify the constraints required during transformation procedure. The proposed transformation method contributes to getting the logical temporal data from the conceptual temporal events Without any loss of semantics, Compared to other approaches of supporting various properties, this approach is more general and efficient because it is the semantically seamless transformation method by using the orthogonality of types of objects, semantics of relationships and constraints over roles.

• Journal of Internet Computing and Services
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• v.10 no.5
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• pp.79-93
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• 2009

For developing the location based service which is individualized and specialized according to the characteristic of the users, the spatio-temporal pattern mining for extracting the meaningful and useful patterns among the various patterns of the mobile object on the spatio-temporal area is needed. Thus, in this paper, as the practical application toward the development of the location based service in which it is able to apply to the real life through the pattern mining from the huge historical data of mobile object, we are proposed STOMP(using Frequency of sequence and Weight) that is the new mining method for extracting the patterns with spatial and temporal constraint based on the problems of mining the optimal moving pattern which are defined in STOMP(F)[25]. Proposed method is the pattern mining method compositively using weighted value(weights) (a distance, the time, a cost, and etc) for our previous research(STOMP(F)[25]) that it uses only the pattern frequent occurrence. As to, it is the method determining the moving pattern in which the pattern frequent occurrence is above special threshold and the weight is most a little bit required among moving patterns of the object as the optimal path. And also, it can search the optimal path more accurate and faster than existing methods($A^*$, Dijkstra algorithm) or with only using pattern frequent occurrence due to less accesses to nodes by using the heuristic moving history.

• The KIPS Transactions:PartD
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• v.15D no.4
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• pp.485-494
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• 2008

Huge amounts of various web items such as keywords, images, and web pages are being made widely available on the Web. The popularities of such web items continuously change over time, and mining temporal patterns in popularities of web items is an important problem that is useful for several web applications. For example, the temporal patterns in popularities of search keywords help web search enterprises predict future popular keywords, enabling them to make price decisions when marketing search keywords to advertisers. However, presence of millions of web items makes it difficult to scale up previous techniques for this problem. This paper proposes an efficient method for mining temporal patterns in popularities of web items. We treat the popularities of web items as time-series, and propose gapmeasure to quantify the similarity between the popularities of two web items. To reduce the computation overhead for this measure, an efficient method using the Fast Fourier Transform (FFT) is presented. We assume that the popularities of web items are not necessarily following any probabilistic distribution or periodic. For finding clusters of web items with similar popularity trends, we propose to use a density-based clustering algorithm based on the gap measure. Our experiments using the popularity trends of search keywords obtained from the Google Trends web site illustrate the scalability and usefulness of the proposed approach in real-world applications.

• School Mathematics
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• v.19 no.3
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• pp.423-441
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• 2017

New Zealand had reformed their national curriculum with competence and are applying the revised curriculum. As the 2015 revised national curriculum is clothed with competency-based curriculum, New Zealand may have important implications for the study of the Korean revised curriculum. In this study, we examine characteristics of the education system and the national curriculum in New Zealand. In addition, we analyze the standards into the New Zealand national curriculum in terms of 'curriculum connectivity' that is one of important curriculum criteria for improving the quality of education. For this, we look an overview of the relation between the New Zealand curriculum and NCEA, which is the core of the student-centered education system in New Zealand, and analyze the correspondence between the New Zealand curriculum and the Korean curriculum. And we establish analysis framework of curriculum connectivity based on these comparison analysis contents, and analyze Korean mathematics standards with corresponding levels from among the New Zealand mathematics curriculum. According to the results of this study, the New Zealand curriculum includes the most of standards which Korean high school students who want to enter university of natural sciences of engineering need to require. In addition, the New Zealand curriculum highlights statistical research activities for developing problem-solving ability in real life. From perspective of curriculum connectivity, 'in-depth contents' adding on to repeating mathematical concepts or contents are included in the New Zealand curriculum.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.6
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• pp.307-312
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• 2016

Markerless tracking for augmented reality using Homography can augment virtual objects correctly and naturally on live view of real-world environment by using correct pose and direction of camera. The RANSAC algorithm is widely used for estimating Homography. CS-RANSAC algorithm is one of the novel algorithm which cooperates a constraint satisfaction problem(CSP) into RANSAC algorithm for increasing accuracy and decreasing processing time. However, CS-RANSAC algorithm can be degraded performance of calculating Homography that is caused by selecting feature points which estimate low accuracy Homography in the sampling step. In this paper, we propose feature point filtering method based on CS-RANSAC for efficient planar Homography estimating the proposed algorithm evaluate which feature points estimate high accuracy Homography for removing unnecessary feature point from the next sampling step using Symmetric Transfer Error to increase accuracy and decrease processing time. To evaluate our proposed method we have compared our algorithm with the bagic CS-RANSAC algorithm, and basic RANSAC algorithm in terms of processing time, error rate(Symmetric Transfer Error), and inlier rate. The experiment shows that the proposed method produces 5% decrease in processing time, 14% decrease in Symmetric Transfer Error, and higher accurate homography by comparing the basic CS-RANSAC algorithm.

• Journal of Korea Multimedia Society
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• v.9 no.5
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• pp.649-657
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• 2006

Reinforcement Learning is a computational approach to learning whereby an agent take an action which maximize the total amount of reward it receives among possible actions within current state when interacting with a uncertain environment. Q-learning, one of the most active algorithm in Reinforcement Learning, is consist of rewards which is obtained when an agent take an action. But it has the problem with mapping real world to discrete states. When state spaces are very large, Q-learning suffers from time for learning. In constant, when the state space is reduced, many state spaces map to single state space. Because an agent only learns single action within many states, an agent takes an action monotonously. In this paper, to reduce time for learning and complement simple action, we propose the Q-learning using influence map(QIM). By using influence map and adjacent state space's learning result, an agent could choose proper action within uncertain state where an agent does not learn. When this paper compares simulation results of QIM and Q-learning, we show that QIM effects as same as Q-learning even thought QIM uses 4.6% of the Q-learning's state spaces. This is because QIM learns faster than Q-learning about 2.77 times and the state spaces which is needed to learn is reduced, so the occurred problem is complemented by the influence map.

• Journal of the Korean School Mathematics Society
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• v.24 no.3
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• pp.283-308
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• 2021

This study aims to analyze statistical tasks in Korean and Singaporean textbooks with the mathematical modeling perspective and compare the learning contents and experiences of students from both countries. I analyzed mathematical modeling tasks in the textbooks based on five aspects: (1) the mathematical modeling process, (2) the data type, (3) the expression type, (4) the context, and (5) the mathematical activity. The results of this study show that Korean and Singaporean textbooks provide the highest percentage of the "working-with-mathematics" task, the highest percentage of the "matching task," and the highest percentage of the "picture" task. The real-world context and mathematical activities used in Korean and Singaporean textbooks differed in percentage. This study provides implications for the development of textbook tasks to support future mathematical modeling activities. This includes providing a balanced experience in mathematical modeling processes and presenting tasks in various forms of expression to raise students' cognitive level and expand the opportunity to experience meaningful mathematizing. In addition, it is necessary to present a contextually realistic task for students' interest in mathematical modeling activities or motivation for learning.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1515-1526
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• 2022

Image-based 3D reconstruction is to restore the shape and color of real-world objects, and image sensors mounted on mobile platforms are used for positioning and mapping purposes in indoor and outdoor environments. Due to the increase in accidents in underground space, the location accuracy problem of underground spatial information has been raised. Image-based location estimation studies have been conducted with the advantage of being able to determine the 3D location and simultaneously identify internal damage from image data acquired from the inside of pipeline-type underground facilities. In this study, we studied 3D reconstruction based on the images acquired inside the pipe-type underground facility and reference data. An unmanned mobile system equipped with a stereo camera was used to acquire data and image data within a pipe-type underground facility where reference data were placed at the entrance and exit. Using the acquired image and reference data, the pipe-type underground facility is reconstructed to a geo-referenced 3D shape. The accuracy of the 3D reconstruction result was verified by location and length. It was confirmed that the location was determined with an accuracy of 20 to 60 cm and the length was estimated with an accuracy of about 20 cm. Using the image-based 3D reconstruction method, the position and line-shape of the pipe-type underground facility will be effectively updated.