• Journal of Software Engineering Society
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• v.23 no.4
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• pp.151-163
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• 2010

In the defense software domain where large-scale software products in various application areas need to be built, reusing software is regarded as one of the important practices to build software products efficiently and economically. There have been many efforts to apply various methods to support software reuse in the defense software domain. However, developers in the defense software domain still experience many difficulties and face obstacles in reusing software assets. In this paper, we analyze practical problems of software reuse in the defense software domain, and define core requirements to solve those problems. To meet these requirements, we are currently developing the Component Grid system, a reuse-support system that provides a developer-centric software reuse environment. We have designed an architecture of Component Grid, and defined essential elements of the architecture. We have also developed the core approaches for developing the Component Grid system: a semantic-tagging-based requirement tracing method, a reuse-knowledge representation model, a social-network-based asset search method, a web-based asset management environment, and a wiki-based collaborative and participative knowledge construction and refinement method. We expect that the Component Grid system will contribute to increase the reusability of software assets in the defense software domain by providing the environment that supports transparent and efficient sharing and reuse of software assets.

• Journal of Digital Convergence
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• v.19 no.2
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• pp.231-238
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• 2021

SNS data can catch the user's thoughts and actions. And the trend of the search portal is a representative service that can observe the interests of users and their changes. In this paper, the relationship was analyzed by comparing statistics on narcotics incidents and the degree of exposure to narcotics related words in tweets of SNS and in the trends of search portal. It was confirmed that the trend of SNS and search portal trends was the same in the statistics of the prosecution office with a certain time difference.In addition, cluster analysis was performed to understand the meaning of tweets in which narcotics related words were mentioned. In the 50,000 tweets collected in January 2020, it was possible to find meaning related to the sale of actual drugs. Therefore, through SNS monitoring alone it is possible to monitor narcotics-related incidents and to find specific sales or purchase-related information, and this can be used in the investigation process. In the future, it is expected that crime monitoring and prediction systems can be proposed as related crime analysis may be possible not only with text but also images.

• Journal of Digital Convergence
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• v.20 no.2
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• pp.203-215
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• 2022

The study is to investigate research trends and knowledge structures in the Smart Farm field. To achieve the research purpose, keywords and the relationship among keywords were analyzed targeting 104 Korean academic journals related to the Smart Farm in KCI(Korea Citation Index), and topics were analyzed using the LDA Topic Modeling technique. As a result of the analysis, the main keywords in the Korean Smart Farm-related research field were 'environment', 'system', 'use', 'technology', 'cultivation', etc. The results of Degree, Betweenness, and Eigenvector Centrality were presented. There were 7 topics, such as 'Introduction analysis of Smart Farm', 'Eco-friendly Smart Farm and economic efficiency of Smart Farm', 'Smart Farm platform design', 'Smart Farm production optimization', 'Smart Farm ecosystem', 'Smart Farm system implementation', and 'Government policy for Smart Farm' in the results of Topic Modeling. This study will be expected to serve as basic data for policy development necessary to advance Korean Smart Farm research in the future by examining research trends related to Korean Smart Farm.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.397-412
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• 2023

In order for social robots to take root in human life, it is important to consider the technical implementation of social robots and human psychology toward social robots. This study aimed to derive potential social robot clusters based on the emotions consumers feel about social robot appearance design, and to identify and compare important design characteristics and emotional differences of each cluster. In our study, we established a social robot emotion framework to measure and evaluate the emotions consumers feel about social robots, and evaluated the emotions of social robot designs based on the semantic differential method, an kansei engineering approach. We classified 30 social robots into 4 clusters by conducting a multidimensional scaling method and K-means cluster analysis based on the emotion evaluation results, confirmed the characteristics of design elements for each cluster, and conducted a comparative analysis on consumer emotions. We proposed a strategic direction for successful social robot design and development from a human-centered perspective based on the design characteristics and emotional differences derived for each cluster.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.6
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• pp.609-619
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• 2023

This study aimed to investigate the formation of the social perception of domestic maritime sports using text mining analysis of keywords and topics from domestic media coverage over the past 10 years related to representative maritime sports, including yachting, rowing, and canoeing. The results are as follows: First, term frequency (TF) and word cloud analyses identified the top keywords: "maritime," "competition," "experience," "tourism," "world," "yachting," "canoeing," "leisure," and "participation." Second, semantic network analysis revealed that yachting was correlated with terms like "maritime," "industry," "competition," "leisure," "tourism," "boat," "facilities," and "business"; rowing with terms like "competition" and "Chungju"; and canoeing with terms like "maritime," "competition," "experience," "leisure," and "tourism." Third, topic modeling analysis indicated that yachting, rowing, and canoeing are perceived as elite sports and maritime leisure sports. However, the perception of these sports has been demonstrated to have little impact on society, public opinion, and social transformation. In summary, when considering these results comprehensively, it can be concluded that yachting and canoeing have gradually shifted from being perceived as elite sports to essential elements of the maritime leisure industry. Contrariwise, rowing remains primarily associated with elite sports, and its popularization as a maritime leisure sport appears limited at this time.

• Journal of Intelligence and Information Systems
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• v.8 no.1
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• pp.141-157
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• 2002

extensible Markup Language (XML) is a new markup language for data exchange on the Internet. In this paper, we propose a language extensible Rule Markup Language (XRML) which is an extension of XML. The implicit rules embedded in the Web pages should be identifiable, interchangeable with structured rule format, and finally accessible by various applications. It is possible to realize by using XRML. In this light, Web based Knowledge Management Systems (KMS) can be integrated with rule-based expert systems. To meet this end, we propose the six design criteria: Expressional Completeness, Relevance Linkability, Polymorphous Consistency, Applicative Universality, Knowledge Integrability and Interoperability. Furthermore, we propose three components such as RIML (Rule Identification Markup Language), RSML (Rule Structure Markup Language) and RTML (Rule Triggering Markup Language), and the Document Type Definition DTD). We have designed the XRML version 0.5 as illustrated above, and developed its prototype named Form/XRML which is an automated form processing for disbursement of the research fund in the Korea Advanced Institute of Science and Technology (KAISI). Since XRML allows both human and software agent to use the rules, there is huge application potential. We expect that XRML can contribute to the progress of Semantic Web platforms making knowledge management and e-commerce more intelligent. Since there are many emerging research groups and vendors who investigate this issue, it will not take long to see XRML commercial products. Matured XRML applications may change the way of designing information and knowledge systems in the near future.

• Journal of the Korean Society for information Management
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• v.21 no.4 s.54
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• pp.109-131
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• 2004

As there are diverse delivery media and forms of information resources, their management schemes are diverse as well. In library community, cataloguing. rules for describing information resources such as AACR and KCR have been developed. The efforts to automate management of information resources based on these rules resulted in the development of MARC. However, MARC records are restricted in describing the information resources and MARC has various and distinct characteristics of the structural rigidity, which does not support the representation of extended semantic structures that exist among bibliographic entities. Therefore, since the data model for MARC is single-layer data model, it is not appropriate for describing information resources represented by multi-layer data model which can be used to set up the relationships among various objects in digital libraries. In this paper, we propose an a metadata model for digital libraries based on the IFLA FRBR basic model which supports multi-layer data model and a representation scheme based on XML Schema to manage the metadata about old books, old documents, resource related to music, conferences and seminars.

• Journal of the Korean Society for information Management
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• v.32 no.4
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• pp.137-165
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• 2015

This study aimed to investigate the period-specific changes (Library 1.0, Library 2.0, Library 3.0 Period) of job factors and performance features in academic libraries. For this, the study categorized an academic library's job into five dimensions: 1) library administration 2) collection development and management 3) information organization 4) information services and 5) information system development and management, After the categorized library's job was defined in detail, the Delphi survey was conducted twice on librarians and professors of library and information science. The result showed that there were many changes in job factors and performance features in academic libraries towards the period of library 2.0 characterized by user participation, sharing and openness and into library 3.0 characterized by social network and semantic web. Library 3.0 is likely to bring about a significant change in user services with ever changing technological advances stemming from library 2.0, such as mobile services, RFID and NFC etc. The finding of the study suggest that library systems need to be continually upgraded in the period of library 3.0.

• Journal of the Korea Society of Computer and Information
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• v.8 no.2
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• pp.51-56
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• 2003

The structuring of Web information supports a strong user side viewpoint that a user wants his/her own needs on snooping a specific Web site. Not only the depth first algorithm or the breadth-first algorithm, but also the Web information is abstracted to a hierarchical structure. A prototype system is suggested in order to visualize and to represent a semantic significance. As a motivating example, the Web test site is suggested and analyzed with respect to several keywords. As a future research, the Web site model should be extended to the whole WWW and an accurate assessment function needs to be devised by which several suggested models should be evaluated.

• Journal of Intelligence and Information Systems
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• v.18 no.2
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• pp.47-60
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• 2012

Video data comes in the form of the unstructured and the complex structure. As the importance of efficient management and retrieval for video data increases, studies on the video parsing based on the visual features contained in the video contents are researched to reconstruct video data as the meaningful structure. The early studies on video parsing are focused on splitting video data into shots, but detecting the shot boundary defined with the physical boundary does not cosider the semantic association of video data. Recently, studies on structuralizing video shots having the semantic association to the video scene defined with the semantic boundary by utilizing clustering methods are actively progressed. Previous studies on detecting the video scene try to detect video scenes by utilizing clustering algorithms based on the similarity measure between video shots mainly depended on color features. However, the correct identification of a video shot or scene and the detection of the gradual transitions such as dissolve, fade and wipe are difficult because color features of video data contain a noise and are abruptly changed due to the intervention of an unexpected object. In this paper, to solve these problems, we propose the Scene Detector by using Color histogram, corner Edge and Object color histogram (SDCEO) that clusters similar shots organizing same event based on visual features including the color histogram, the corner edge and the object color histogram to detect video scenes. The SDCEO is worthy of notice in a sense that it uses the edge feature with the color feature, and as a result, it effectively detects the gradual transitions as well as the abrupt transitions. The SDCEO consists of the Shot Bound Identifier and the Video Scene Detector. The Shot Bound Identifier is comprised of the Color Histogram Analysis step and the Corner Edge Analysis step. In the Color Histogram Analysis step, SDCEO uses the color histogram feature to organizing shot boundaries. The color histogram, recording the percentage of each quantized color among all pixels in a frame, are chosen for their good performance, as also reported in other work of content-based image and video analysis. To organize shot boundaries, SDCEO joins associated sequential frames into shot boundaries by measuring the similarity of the color histogram between frames. In the Corner Edge Analysis step, SDCEO identifies the final shot boundaries by using the corner edge feature. SDCEO detect associated shot boundaries comparing the corner edge feature between the last frame of previous shot boundary and the first frame of next shot boundary. In the Key-frame Extraction step, SDCEO compares each frame with all frames and measures the similarity by using histogram euclidean distance, and then select the frame the most similar with all frames contained in same shot boundary as the key-frame. Video Scene Detector clusters associated shots organizing same event by utilizing the hierarchical agglomerative clustering method based on the visual features including the color histogram and the object color histogram. After detecting video scenes, SDCEO organizes final video scene by repetitive clustering until the simiarity distance between shot boundaries less than the threshold h. In this paper, we construct the prototype of SDCEO and experiments are carried out with the baseline data that are manually constructed, and the experimental results that the precision of shot boundary detection is 93.3% and the precision of video scene detection is 83.3% are satisfactory.