• 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.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.14 no.4
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• pp.268-275
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• 2014

In future, hospitals are expected to automatically issue remote transcriptions. Many general hospitals are planning to encrypt their medical database to secure personal information as mandated by law. The electronic medical record system, picture archiving communication system, and the clinical data warehouse, amongst others, are the preferred targets for which stronger security is planned. In the near future, medical systems can be assumed to be automated and connected to remote locations, such as rural areas, and islands. Connecting patients who are in remote locations to medical complexes that are usually based in larger cities requires not only automatic processing, but also a certain amount of security in terms of medical data that is of a sensitive and critical nature. Unauthorized access to patients' transcription data could result in the data being modified, with possible lethal results. Hence, personal and sensitive data on telemedicine and medical information systems should be encrypted to protect patients from these risks. Login passwords, personal identification information, and biological information should similarly be protected in a systematic way. This paper proposes the use of electronic acupuncture with a built-in multi-pad, which has the advantage of being able to establish a patient's physical condition, while simultaneously treating the patient with acupuncture. This system implements a sensing pad, amplifier, a small signal drive circuit, and a digital signal processing system, while the use of a built-in fuzzy technique and a control algorithm have been proposed for performing analyses.

• The Bulletin of The Korean Astronomical Society
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• v.38 no.1
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• pp.74-74
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• 2013

Multi-purpose Infra-Red Imaging System (MIRIS) is the main payload of the Science and Technology Satellite-3 (STSAT-3) to be launched in the late half of this year. For the Space Observation Camera (SOC) of MIRIS, we developed the data reduction pipeline with Python powered by Astropy, a community Python library for astronomy. The pipeline features the following functionalities: i) to retrieve the raw observation data from database and convert it to a FITS format, ii) to mask bad pixels, iii) to correct the non-linearity, iv) to differentiate the frames, v) to correct the flat-field, vi) to correct focal-plane distortion, vii) to improve the world coordinate system (WCS) information using known point-source catalog, and viii) to combine the sequentially taken frames. The pipeline is well modularized and has flexibility for later update. In this poster, we introduce the details of the pipeline's features and the future maintenance plan.

• Journal of the Korean Data and Information Science Society
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• v.22 no.4
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• pp.671-678
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• 2011

Data mining searches for interesting relationships among items in a given database. The methods of data mining are decision tree, association rules, clustering, neural network and so on. The decision tree approach is most useful in classification problems and to divide the search space into rectangular regions. Decision tree algorithms are used extensively for data mining in many domains such as retail target marketing, customer classification, etc. When create decision tree model, complicated model by standard of model creation and number of input variable is produced. Specially, there is difficulty in model creation and analysis in case of there are a lot of numbers of input variable. In this study, we study on decision tree using intervening variable. We apply to actuality data to suggest method that remove unnecessary input variable for created model and search the efficiency.