• Journal of Korea Multimedia Society
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• v.16 no.7
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• pp.870-878
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• 2013

In this paper, we propose a novel fingerprint classification method to enhance the accuracy and efficiency of the fingerprint identification system, one of biometrics systems. According to the previous researches, fingerprints can be categorized into the several patterns based on their pattern of ridges and valleys. After construction of fingerprint database based on their patters, fingerprint classification approach can help to accelerate the fingerprint recognition. The reason is that classification methods reduce the size of the search space to the fingerprints of the same category before matching. First, we suggest a method to extract region of interest (ROI) which have real information about fingerprint from the image. And then we propose a feature extraction method which combines gray level co-occurrence matrix (GLCM) and wavelet features. Finally, we compare the performance of our proposed method with the existing method which use only GLCM as the feature of fingerprint by using the multi-layer perceptron and support vector machine.

• The Journal of Korean Institute for Practical Engineering Education
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• v.4 no.2
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• pp.38-45
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• 2012

Building a game has been used as effective and attractive way of teaching computer science. Building a usable Multi-player Game is requires important aspects of technology, teamwork and software engineering principles. The whole class was structured in to several teams and students needed to join one or two teams. Each team presented their progress, discussed future milestones and troubleshoots, updated documents for clearer communication and utilized SVN(Subversion) throughout the semester. Unlike usual class setting, all students worked collaboratively together like one company to achieve the goal. In one semester, students started from concept design and completed a working Multiplayer Online Game called "deBugger" (Fall 2009), and "World of Balance" (Fall 2011), while learning game design, 3D graphics, Game Engine, Server-client architecture, Game Protocol, network programming, database, Software Engineering principles, and large application development as a team project.

• KIISE Transactions on Computing Practices
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• v.22 no.2
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• pp.61-68
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• 2016

Surveillance cameras have been installed in many places because security and safety has become an important issue in modern society. However, watching surveillance videos and judging accidental situations is very labor-intensive and time-consuming. So now, requests for research to automatically analyze the surveillance videos is growing. In this paper, we propose a surveillance system to track multiple persons in videos and to summarize the videos based on tracking information. The proposed surveillance summarization system applies an adaptive illumination correction, subtracts the background, detects multiple persons, tracks the persons, and saves their tracking information in a database. The tracking information includes tracking one's path, their movement status, length of staying time at the location, enterance/exit times, and so on. The movement status is classified into six statuses(Enter, Stay, Slow, Normal, Fast, and Exit). This proposed summarization system provides a person's status as a graph in time and space and helps to quickly determine the status of the tracked person.

• Journal of Internet Computing and Services
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• v.7 no.5
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• pp.135-145
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• 2006

This paper presents a novel approach to real-time recognition of 3D environment and objects for intelligent robots. First. we establish the three fundamental principles that humans use for recognizing and interacting with the environment. These principles have led to the development of an integrated approach to real-time 3D recognition and modeling, as follows: 1) It starts with a rapid but approximate characterization of the geometric configuration of workspace by identifying global plane features. 2) It quickly recognizes known objects in environment and replaces them by their models in database based on 3D registration. 3) It models the geometric details on the fly adaptively to the need of the given task based on a multi-resolution octree representation. SIFT features with their 3D position data, referred to here as stereo-sis SIFT, are used extensively, together with point clouds, for fast extraction of global plane features, for fast recognition of objects, for fast registration of scenes, as well as for overcoming incomplete and noisy nature of point clouds. The experimental results show the feasibility of real-time and behavior-oriented 3D modeling of workspace for robotic manipulative tasks.

• Journal of Korea Spatial Information System Society
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• v.7 no.3 s.15
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• pp.55-65
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• 2005

This paper presents a bulk insertion technique for efficiently inserting data items. Traditional moving object database focused on efficient query processing that happens mainly after index building. Traditional index structures rarely considered disk I/O overhead for index rebuilding by inserting data items. This paper, to solve this problem, describes a new bulk insertion technique which efficiently induces the current positions of moving objects and reduces update cost greatly. This technique uses buffering technique for bulk insertion in spatial index structures such as R-tree. To analyze split or merge node, we add a secondary index for information management on leaf node of primary index. And operations are classified to reduce unnecessary insertion and deletion. This technique decides processing order of moving objects, which minimize split and merge cost as a result of update operations. Experimental results show that this technique reduces insertion cost as compared with existing insertion techniques.

• Radiation Oncology Journal
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• v.30 no.1
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• pp.14-19
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• 2012

Purpose: We collected the data of Science Citation Index (SCI) and SCI Expended (SCIE) papers written by the members of the Korean Society of Radiation Oncology (KOSRO) to analyze the current status and the future trend. Materials and Methods: We searched the database of SCIE for the period from 1981 to 2011 at the Web of Knowledge site. Articles, reviews or proceedings written by KOSRO members as the first or corresponding authors were included. Search terms were the following combination of subject headings: therapeut radiol, radiat oncol, Korea. For National Cancer Center, combined search terms such as natl canc ctr, Korea and the names of faculties were applied. Results: The total number of SCIE papers was 547. Numbers of the published papers in 1995, 2000, 2005, and 2010, were increased continuously, which was 2, 14, 40, and 83, respectively. The average impact factor was 2.9. The papers were published at the 134 different journals. The proportion of "International Journal of Radiation Oncology Biology Physics" was 23.4% of all the papers. The number and proportions of papers by subject categories were 87 (15.9%) in biology, 73 (13.3%) in physics and 387 (70.6%) in clinics. The papers of the top five institutions, based on the number of published papers, occupied 66.3%. Conclusion: The number of SCIE papers is increasing rapidly in the field of radiation oncology in Korea. To improve the quality of papers, multi-institutional retrospective or prospective randomized studies should be done for the common cancers in Korea.

• Mass Spectrometry Letters
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• v.5 no.1
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• pp.16-23
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• 2014

Liquid chromatography based mass spectrometry (LC-MS) is a key technology for analyzing highly complex and dynamic proteome samples. With highly accurate and sensitive LC-MS analysis of complex proteome samples, efficient data processing is another critical issue to obtain more information from LC-MS data. A typical proteomic data processing starts with protein database search engine which assigns peptide sequences to MS/MS spectra and finds proteins. Although several search engines, such as SEQUEST and MASCOT, have been widely used, there is no unique standard way to interpret MS/MS spectra of peptides. Each search engine has pros and cons depending on types of mass spectrometers and physicochemical properties of peptides. In this study, we describe a novel data process pipeline which identifies more peptides and proteins by correcting precursor ion mass numbers and unifying multi search engines results. The pipeline utilizes two open-source software, iPE-MMR for mass number correction, and iProphet to combine several search results. The integrated pipeline identified 25% more proteins in mouse epididymal adipose tissue compared with the conventional method. Also the pipeline was validated using control and colitis induced colon tissue. The results of the present study shows that the integrated pipeline can efficiently identify increased number of proteins compared to the conventional method which can be a breakthrough in identification of a potential biomarker candidate.

• Journal of the Korean Society of Clothing and Textiles
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• v.28 no.910
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• pp.1341-1350
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• 2004

With the advent of the globalization trend of the industry, the enterprises in the fashion industry around the world have witnessed a surge in exports and foreign direct investment (FDI). Many fashion enterprises in each country, along with the multi-national enterprises, have engaged in global outsourcing of the production process in order to increase their global competitiveness, and have attempted to expand their commercial presence in the world market by entering into other foreign markets. Such market entry attempts have lead to the increase of FDI and trade by the fashion enterprises. This study attempts to examine the interactive relation between FDI and export/import of fashion products in different fashion industries both worldwide and in Korea. First, we will look into the relation between export/imports and FDI of each regional fashion industry, then expand the study to the relation between those two factors found in the fashion industry of Korea in general, and finally, to the relation between the two factors in the fashion industry of countries that are the major export nations of fashion goods into Korea. The data which this study is based on were collected from the International Trade Statistics Yearbook Vol. II (UN, 1991-2002, New York: UN), UNCTAD Handbook of Statistics (UN, 1996-2001, Vienna: UN), UNCTAD database, the archives of the Korea Federation of Textile Industry and the archives of the Export-Import Bank of Korea. The methods of analysis used in this study were correlation, regression, and descriptive statistics of the data. The result of this study showed that each fashion industry of different regions was subject to a diversity of effects. For one, the fashion industry in Korea showed a significant correlation between outbound investment and both export and import. On the other hand, the apparel industry in Korea showed a significant correlation between outbound investment and imports, but no such correlation between outbound investment and exports.

• Spatial Information Research
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• v.14 no.2 s.37
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• pp.245-260
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• 2006

A practical use of the location information and user requirement are increased in a mobile environment which supports the portability. And Various service which GIS is related with a Spatial DB have been processed. Generally, logical relation of a traffic network which organizes the Road DB uses a basic node-link structure. In this way, Designed structure can not be flexible at various model apply and are not efficient with a database retrieval in a maintenance management side. In this research, We supplement with the problem of a existing network model and the limitation of the building through the design of a network model which uses dynamic segmentation. And we tried to implement efficient hierarchy model at the retrieval of the network and presentation. Designed model supports a stage presentation of various level and a hierarchy entity relation and We are expected to supplement a network spatial modelling function which the GIS has.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.5
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• pp.437-443
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• 2015

This paper presents face recognition based on the fusion of visible image and thermal infrared (IR) texture estimated from the face image in the visible spectrum. The proposed face recognition scheme uses a multi- layer neural network to estimate thermal texture from visible imagery. In the training process, a set of visible and thermal IR image pairs are used to determine the parameters of the neural network to learn a complex mapping from a visible image to its thermal texture in the low-dimensional feature space. The trained neural network estimates the principal components of the thermal texture corresponding to the input visible image. Extensive experiments on face recognition were performed using two popular face recognition algorithms, Eigenfaces and Fisherfaces for NIST/Equinox database for benchmarking. The fusion of visible image and thermal IR texture demonstrated improved face recognition accuracies over conventional face recognition in terms of receiver operating characteristics (ROC) as well as first matching performances.