• Journal of the Korean Society of Environmental Restoration Technology
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• v.10 no.1
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• pp.23-35
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• 2007

Nowadays, as a result of increasing income and spare time, the social demands for better living environment become more increasing. Above all, landscape improvement, the essential part of physical environment, will be a more important subject in urban planning. In these circumstances, classification of urban scenic quality is required for urban landscape development programs. The major purpose of this study is to suggest a technical method of designing urban scenic quality map for urban district area based on the scenery management system of the USDA forest service and literature studies. As a conclusion of this study, four steps are desirable for the technical method for designing a scenic quality map of urban districts areas : 1) Define a landscape unit on the map, 2) Take a photograph of these landscape unit on site, 3) Evaluate the landscape unit by semantic differential scale with landscape adjectives, and 4) Draw the scenic quality map, investigate the landscape characteristics and suggest the landscape scenic development plans.

• Journal of Digital Convergence
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• v.10 no.6
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• pp.219-224
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• 2012

In the communication mobile terminal, Vocabulary recognition system has low recognition rates, because this problems are due to phoneme feature extract from inaccurate vocabulary. Therefore they are not recognize the phoneme and similar phoneme misunderstanding error. To solve this problem, this paper propose the system model, which based on the two step process. First, input phoneme is represent by number which measure the distance of phonemes through phoneme likelihood process. next step is recognize the result through the reliability measure. By this process, we minimize the phoneme misunderstanding error caused by inaccurate vocabulary and perform error correction rate for error provrd vocabulary using phoneme likelihood and reliability. System performance comparison as a result of recognition improve represent 2.7% by method using error pattern learning and semantic pattern.

• Architectural research
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• v.12 no.2
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• pp.53-62
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• 2010

The purpose of this study is to examine design preferences for the sales spaces of duty-free shops (DFSs) by conducting image evaluations. The results will help improve quality by influencing designs for the construction, extension or remodeling of these shops. An image measurement method, the semantic differential method, was used to measure cognitive structure using photos of shops. Photos were collected of the DFS at Jeju Island, as well as photos of brand stores designed by architects. Two sets of 16 photos (32 different photos in all) were selected according to photo classification standards and design concepts, both decided by reviewing previous studies and related materials. The evaluation and survey were done by two sets of subjects: sales employees, who have experience and special knowledge of the evaluation of sales space; and students majoring in architecture. To strengthen the evaluation results, I conducted a preliminary survey and a main survey, verifying and complementing findings. 116 surveys were conducted, of which 14 were of poor quality and rejected, leaving and 102 to be analyzed. The collected surveys were statistically analyzed, using SPSS 12.0 for Windows. Reliability, image profile, factor and multi-dimensional scaling analyses were conducted. As a result, image evaluation structure and characteristics were obtained for sales spaces of DFSs, confirming the difference between them and other spaces.

• Genomics & Informatics
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• v.13 no.1
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• pp.7-14
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• 2015

During recent years, there has been exponential growth in biological information. With the emergence of large datasets in biology, life scientists are encountering bottlenecks in handling the biological data. This study presents an integrated geographic information system (GIS)-ontology application for handling microbial genome data. The application uses a linear referencing technique as one of the GIS functionalities to represent genes as linear events on the genome layer, where users can define/change the attributes of genes in an event table and interactively see the gene events on a genome layer. Our application adopted ontology to portray and store genomic data in a semantic framework, which facilitates data-sharing among biology domains, applications, and experts. The application was developed in two steps. In the first step, the genome annotated data were prepared and stored in a MySQL database. The second step involved the connection of the database to both ArcGIS and $Prot{\acute{e}}g{\acute{e}}$ as the GIS engine and ontology platform, respectively. We have designed this application specifically to manage the genome-annotated data of rumen microbial populations. Such a GIS-ontology application offers powerful capabilities for visualizing, managing, reusing, sharing, and querying genome-related data.

• Journal of Information Management
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• v.42 no.2
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• pp.193-210
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• 2011

The study was applied to context window sizes and weighting method to obtain the best performance of word sense disambiguation using support vector machine. The context window sizes were used to a 3-word, sentence, 50-bytes, and document window around the targeted word. The weighting methods were used to Binary, Term Frequency(TF), TF ${\times}$ Inverse Document Frequency(IDF), and Log TF ${\times}$ IDF. As a result, the performance of 50-bytes in the context window size was best. The Binary weighting method showed the best performance.

• Journal of Korean Institute of Industrial Engineers
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• v.41 no.4
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• pp.344-351
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• 2015

Recently, an ERP (Enterprise resource Planning) system has been becoming an essential S/W tool for companies to manage their business processes and manufacturing resources. As the information exchange becomes more complex, not only corporate companies but also small- and mid- sized enterprises (SMEs) are required to build an ERP system. However, for small- and middle- sized companies, the adoption of ERP systems becomes challenging due to high cost and long installation time of the system. This paper presents a novel concept of an adaptive ERP system incorporating the ontology structure of the business supply chain information. The proposed ERP installation methodology is illustrated with an example of a door-trim manufacturing company in the automotive supply chain.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2003.10a
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• pp.3-3
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• 2003

With biomedical literature expanding so rapidly, there is an urgent need to discover and organize knowledge extracted from texts. Although factual databases contain crucial information the overwhelming amount of new knowledge remains in textual form (e.g. MEDLINE). In addition, new terms are constantly coined as the relationships linking new genes, drugs, proteins etc. As the size of biomedical literature is expanding, more systems are applying a variety of methods to automate the process of knowledge acquisition and management. In my talk, I focus on the project, GENIA, of our group at the University of Tokyo, the objective of which is to construct an information extraction system of protein - protein interaction from abstracts of MEDLINE. The talk includes (1) Techniques we use fDr named entity recognition (1-a) SOHMM (Self-organized HMM) (1-b) Maximum Entropy Model (1-c) Lexicon-based Recognizer (2) Treatment of term variants and acronym finders (3) Event extraction using a full parser (4) Linguistic resources for text mining (GENIA corpus) (4-a) Semantic Tags (4-b) Structural Annotations (4-c) Co-reference tags (4-d) GENIA ontology I will also talk about possible extension of our work that links the findings of molecular biology with clinical findings, and claim that textual based or conceptual based biology would be a viable alternative to system biology that tends to emphasize the role of simulation models in bioinformatics.

• Asia pacific journal of information systems
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• v.20 no.4
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• pp.25-51
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• 2010

This study compares and contrasts the intellectual development of the MIS field in Korea from 2005 to 2009 to that of international trends by using a keyword co-occurrence network analysis of the two flagship journals: APJIS and MIS Quarterly. From 316 research articles in these two journals, 132 unique and most frequently co-occurred keywords were put into analysis. The results of structural equivalence show a mild correlation between APJIS and MIS Quarterly. The e-commerce, trust, and technology adoption are the high frequency keywords in both journals. In Korea e-learning, purchasing, and recommendation systems turn out to be important keywords while outsourcing, research method, quantitative method, design research, information theory, and empirical research are in average international journals. This connotes that the Korean scholarship tends to focus more on practically oriented topics, but the clustering and relational mapping of research topics in each journal show a mild level of overlap with distinctive orientations due to intrinsic disparities depending on the concerned journals' geographical scopes, namely domestic or global.

• Journal of Computing Science and Engineering
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• v.6 no.3
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• pp.193-206
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• 2012

Keys play a fundamental role in all data models. They allow database systems to uniquely identify data items, and therefore, promote efficient data processing in many applications. Due to this, support is required to discover keys. These include keys that are semantically meaningful for the application domain, or are satisfied by a given database. We study the discovery of keys from SQL tables. We investigate the structural and computational properties of Armstrong tables for sets of SQL keys. Inspections of Armstrong tables enable data engineers to consolidate their understanding of semantically meaningful keys, and to communicate this understanding to other stake-holders. The stake-holders may want to make changes to the tables or provide entirely different tables to communicate their views to the data engineers. For such a purpose, we propose data mining algorithms that discover keys from a given SQL table. We combine the key mining algorithms with Armstrong table computations to generate informative Armstrong tables, that is, key-preserving semantic samples of existing SQL tables. Finally, we define formal measures to assess the distance between sets of SQL keys. The measures can be applied to validate the usefulness of Armstrong tables, and to automate the marking and feedback of non-multiple choice questions in database courses.

• Journal of Computing Science and Engineering
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• v.1 no.1
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• pp.95-123
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• 2007

Existing systems that support semistructured views do not maintain semantics during the process of designing the views. Thus, these systems do not guarantee the validity and reversibility of the views. In this paper, we propose an approach to address the issue of valid and reversible semistructured views, We design a set of view operators for designing semistructured views. These operators are select, drop, join and swap. For each operator, we develop a complete set of rules to maintain the semantics of the views. In particular, we maintain the evolution and integrity of relationships once an operator is applied. We also examine the reversible view problem under our operators and develop rules to guarantee that the designed views are reversible. Finally, we examine the changes in the participation constraints of relationship types during the view design process, and develop rules to ensure the correctness of the participation constraints.