• Journal of Korean Society of Transportation
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• v.22 no.2 s.73
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• pp.95-102
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• 2004

The COSMOS is an adaptive traffic control systems that can adjust signal timing parameters in response to various traffic conditions. To evaluate the performance of the COSMOS systems, the field study is only practical option because any evaluation tools are not available. To overcome this limitation, a newly integrated interfacing simulator between a microscopic simulation program and COSMOS was developed. In this paper, a detector module and a signal timing module as well as general feature of the simulator were described. A validation test was performed to verify the accuracy of the data flow within the simulator. It was shown that the accuracy level of information from the simulator was high enough for real application. Several practical comments on further studies were also included to enhance the functional specifications of the simulator.

• Journal of the Korean Society for information Management
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• v.20 no.3
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• pp.241-259
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• 2003

The Basic Semantic Register(BSR) is and official ISO register designed for interoperability among eBusiness and EDI systems. The entities registered in the current BSR are not defined in a machine-understandable way, which renders automatic extraction of structural and relationship information from the register impossible. The purpose of this study is to offer a framework for designing an ontology that can provide semantic interoperability among BSR-based systems by defining data structures and relationships with RDF and OWL, similar meaning by the 'equivalentClass' construct in OWL, the hierachical relationships among classes by the 'subClassOf' construct in RDF schema, definition of any entities in BSR by the 'label' construct in RDF schema, specification of usage guidelines by the 'comment' construct in RDF schema, assignment of classes to BSU's by the 'domain' construct in RDF schema, specification of data types of BSU's by the 'range' construct in RDF schema. Hierarchical relationships among properties in BSR can be expressed using the 'subPropertyOf' in RDF schema. Progress in semantic interoperability can be expected among BSR-based systems through applications of semantic web technology suggested in this study.

• The Transactions of the Korea Information Processing Society
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• v.4 no.12
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• pp.3211-3218
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• 1997

This paper addresses an eye location algorithm which is essential process of human face tracking system for natural video-conferencing. In current video-conferencing systems, user's facial movements are restricted by fixed camera, therefore it is inconvenient to users. We Propose an eye location algorithm for automatic face tracking. Because, locations of other facial features guessed from locations of eye and scale of face in the image can be calculated using inter-ocular distance. Most previous feature extraction methods for face recognition system are approached under assumption that approximative face region or location of each facial feature is known. The proposed algorithm in this paper uses no prior information on the given image. It is not sensitive to backgrounds and lighting conditions. The proposed algorithm uses the valley representation as major information to locate eyes. The experiments have been performed for 213 frames of 17 people and show very encouraging results.

• Journal of the Korean Society for Library and Information Science
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• v.49 no.1
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• pp.341-360
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• 2015

This paper proposes a noble service architecture based on scientific infographic as well as semi-automatic knowledge process for 'KISTI's Scent of Science' database, which has been highly credited as a science journalism service in Korea. Unlike other specialized scientific databases for domain experts and scientists, the database aims at providing comprehensible and intuitive information about various important scientific concepts which may seem not to be easily understandable to general public. In order to construct a knowledge-base from the database, we deeply analyze the traits of the database and then establish a semi-automatic approach to identify and extract various scientific intelligence from its contents. Furthermore, this paper defines a scientific infographic service platform based on the knowledge-base by offering its detailed structure, methods and characteristics, which shows a progressive future direction for science journalism service.

• Journal of KIISE:Software and Applications
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• v.32 no.5
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• pp.428-437
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• 2005

An ontology consists of a set and definition of concepts that represents the characteristics of a given domain and relationship between the elements. To reduce time-consuming and cost in building ontology, this paper proposes a semiautomatic method to build a domain ontology using the results of text analysis. To do this, we Propose a terminology processing method and use the extracted concepts and semantic relations between them to build ontology. An experiment domain is selected by the pharmacy field and the built ontology is applied to document retrieval. In order to represent usefulness for retrieving a document using the hierarchical relations in ontology, we compared a typical keyword based retrieval method with an ontology based retrieval method, which uses related information in an ontology for a related feedback. As a result, the latter shows the improvement of precision and recall by $4.97\%$ and $0.78\%$ respectively.

• Journal of KIISE:Software and Applications
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• v.32 no.3
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• pp.141-152
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• 2005

A new emotion-based image retrieval method is proposed in this paper. Query emotion descriptors called query color code and query gray code are designed based on the human evaluation on 13 emotions('like', 'beautiful', 'natural', 'dynamic', 'warm', 'gay', 'cheerful', 'unstable', 'light' 'strong', 'gaudy' 'hard', 'heavy') when 30 random patterns with different color, intensity, and dot sizes are presented. For emotion image retrieval, once a query emotion is selected, associated query color code and query gray code are selected. Next, DB color code and DB gray code that capture color and, intensify and dot size are extracted in each database image and a matching process between two color codes and between two gray codes are peformed to retrieve relevant emotion images. Also, a new relevance feedback method is proposed. The method incorporates human intention in the retrieval process by dynamically updating weights of the query and DB color codes and weights of an intra query color code. For the experiments over 450 images, the number of positive images was higher than that of negative images at the initial query and increased according to the relevance feedback.

• Journal of the Korean Society for information Management
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• v.25 no.3
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• pp.27-39
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• 2008

In bibliographic data, the use of personal names to indicate authors makes it difficult to specify a particular author since there are numerous authors whose personal names are the same. Resolving same-name author instances into different individuals is called author resolution, which consists of two steps: calculating author similarities and then clustering same-name author instances into different person groups. Author similarities are computed from similarities of author-related bibliographic features such as coauthors, titles of papers, publication information, using supervised or unsupervised methods. Supervised approaches employ machine learning techniques to automatically learn the author similarity function from author-resolved training samples. So far however, a few machine learning methods have been investigated for author resolution. This paper provides a comparative evaluation of a variety of recent high-performing machine learning techniques on author disambiguation, and compares several methods of processing author disambiguation features such as coauthors and titles of papers.

• Journal of Korean Society for Geospatial Information Science
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• v.21 no.3
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• pp.55-62
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• 2013

This paper aims to detect Speed Bump by using Omni-directional Camera and to suggest Real-time update scheme of Speed Bump through Vision Based Approach. In order to detect Speed Bump from sequence of camera images, noise should be removed as well as spot estimated as shape and pattern for speed bump should be detected first. Now that speed bump has a regular form of white and yellow area, we extracted speed bump on the road by applying erosion and dilation morphological operations and by using the HSV color model. By collecting huge panoramic images from the camera, we are able to detect the target object and to calculate the distance through GPS log data. Last but not least, we evaluated accuracy of obtained result and detection algorithm by implementing SLAMS (Simultaneous Localization and Mapping system).

• 한국지형공간정보학회:학술대회논문집
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• 2002.11a
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• pp.117-122
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• 2002

Change detection is a useful technology that can be applied to various fields, taking temporal change information with the comparison and analysis among multi-temporal satellite images. Especially, change detection that utilizes high-resolution satellite imagery can be implemented to extract useful change information for many purposes, such as the environmental inspection, the circumstantial analysis of disaster damage, the inspection of illegal building, and the military use, which cannot be achieved by lower middle-resolution satellite imagery. However, because of the special characteristics that result from high-resolution satellite imagery, it cannot use a pixel-based method that is used for low-resolution satellite imagery. Therefore, it must be used a feature-based algorithm based on the geographical and morphological feature. This paper presents the system that builds the change map by digitizing the boundary of the changed object. In this system, we can make the change map using manual or semi-automatic digitizing through the user interface implemented with a floating window that enables to detect the sign of the change, such as the construction or dismantlement, more efficiently.

• Journal of Advanced Navigation Technology
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• v.28 no.5
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• pp.738-744
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• 2024

The goal of this system is to effectively summarize and visualize important DICOM image data in the medical field. Using React and Node.js, the system collects and parses DICOM images, extracting critical medical information in the process. It then employs a large language model (LLM) to generate automatic summary reports, providing users with personalized medical information. This approach enhances accessibility to medical data and leverages web technologies to process large-scale data quickly and reliably. The system also aims to improve communication between patients and doctors, enhancing the quality of care and enabling medical staff to make faster, more accurate decisions. Additionally, it seeks to improve patients' medical experiences and overall satisfaction. Ultimately, the system aims to improve the quality of healthcare services.