• Journal of Information Processing Systems
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• v.5 no.2
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• pp.69-76
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• 2009

Self healing systems are considered as cognation-enabled sub form of fault tolerance system. But our experiments that we report in this paper show that self healing systems can be used for performance optimization, configuration management, access control management and bunch of other functions. The exponential complexity that results from interaction between autonomic systems and users (software and human users) has hindered the deployment and user of intelligent systems for a while now. We show that if that exceptional complexity is converted into self-growing knowledge (policies in our case), can make up for initial development cost of building an intelligent system. In this paper, we report the application of AHSEN (Autonomic Healing-based Self management Engine) to in OKKAM Project infrastructure backbone cluster that mimics the web service based architecture of u-Zone gateway infrastructure. The 'blind' load division on per-request bases is not optimal for distributed and performance hungry infrastructure such as OKKAM. The approach adopted assesses the active threads on the virtual machine and does resource estimates for active processes. The availability of a certain server is represented through worker modules at load server. Our simulation results on the OKKAM infrastructure show that the self healing significantly improves the performance and clearly demarcates the logical ambiguities in contemporary designs of self healing infrastructures proposed for large scale computing infrastructures.

• Journal of the Korean Society for Library and Information Science
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• v.42 no.1
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• pp.33-44
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• 2008

With the rapid dissemination of Internet and the fast development of IT technology. utilization and circulation of video files through Internet has been widely popularized. To keep playing a central role in information circulation in this ever-changing environment, libraries should pay attention to the circulation of video content, as it emerges to be an important type information resource. In this context, this paper examines the issues surrounding the development of the video content circulation system, while suggesting foundational knowledge required for the development of the system. First, the author reviews the current state of video content utilization and circulation on the internet and examines the related technical developments. Then, the author explains each component of the video content circulation system, while discussing the issues to be considered in the practical implementation of the system. The paper will provide practical guidelines for the librarians in their investigation and/or implementation of the video content circulation service and system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.10
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• pp.1698-1711
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• 2011

Knowledge is often represented as a set of rules or a semantic network in intelligent systems. Recently, ontology has been widely used to represent semantic knowledge, because it organizes thesaurus and hierarchal information between concepts in a particular domain. However, it is not easy to collect semantic relationships among concepts. Much time and expense are incurred in ontology construction. Collective intelligence can be a good alternative approach to solve these problems. In this paper, we propose a collective intelligence approach of Games With A Purpose (GWAP) to collect various semantic resources, such as words and word-senses. We detail how to construct the semantic information model or ontology from the collected semantic resources, constructing a system named FunWords. FunWords is a Korean lexical-based semantic resource collection tool. Experiments demonstrated the resources were grouped as common nouns, abstract nouns, adjective and neologism. Finally, we analyzed their characteristics, acquiring the semantic relationships noted above. Common nouns, with structural semantic relationships, such as hypernym and hyponym, are highlighted. Abstract nouns, with descriptive and characteristic semantic relationships, such as synonym and antonym are underlined. Adjectives, with such semantic relationships, as description and status, illustration - for example, color and sound - are expressed more. Last, neologism, with the semantic relationships, such as description and characteristics, are emphasized. Weighting the semantic relationships with these characteristics can help reduce time and cost, because it need not consider unnecessary or slightly related factors. This can improve the expressive power, such as readability, concentrating on the weighted characteristics. Our proposal to collect semantic resources from the collective intelligence approach of GWAP (our FunWords) and to weight their semantic relationship can help construct the semantic information model or ontology would be a more effective and expressive alternative.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.3
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• pp.565-573
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• 2012

To investigate the business corruption, the obtainments of the business data such as personnel, manufacture, accounting and distribution etc., is absolutely necessary. Futhermore, the investigator should have the systematic extraction solution from the business data of the enterprise database, because most company manage each business data through the distributed database system, In the general business environment, the database exists in the system with upper layer application and big size file server. Besides, original resource data which input by user are distributed and stored in one or more table following the normalized rule. The earlier researches of the database structure analysis mainly handled the table relation for database's optimization and visualization. But, in the point of the digital forensic, the data, itself analysis is more important than the table relation. This paper suggests the extraction technique from the table relation which already defined in the database. Moreover, by the systematic analysis process based on the domain knowledge, analyzes the original business data structure stored in the database and proposes the solution to extract table which is related incident.

• Korean Journal of Computational Design and Engineering
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• v.18 no.3
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• pp.177-188
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• 2013

The construction industry consists of various and massive architectural information as an architectural process includes a variety of design stages with cooperation of many disciplines. Particularly, architectural information is generated and managed through the life cycle of a building, from conceptual design stage to the construction and maintenance. A Building Information Model (BIM) serves as a shared knowledge resource for information about a facility forming a reliable basis for decisions during its life-cycle from inception onward. BIM technology accomplished quantitative development being utilized in various disciplines. However, it is necessary to develop environment and requirement for qualitative improvement of BIM based project. Particularly, requirement is very important for architectural design evaluations. The purpose of this study is to develop and apply of quality control check-list for improving the quality of architectural design in BIM environments. To achieve this purpose, the authors have investigated case study for open BIM data quality control (software, guideline and application case) and classified quality control targets according to physical/logical quality control and data quality. In addition, the authors have defined open BIM based quality control process and developed quality control check-list. Finally, the authors have developed automatic quality check system using requirements for efficient quality control based on open BIM.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.426-432
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• 2013

The construction industry consists of various and massive architectural information as an architectural process includes a variety of design stages with cooperation of many disciplines. Particularly, architectural information is generated and managed through the life cycle of a building, from conceptual design stage to the construction and maintenance. A Building Information Model (BIM) serves as a shared knowledge resource for information about a facility forming a reliable basis for decisions during its life-cycle from inception onward. BIM technology accomplished quantitative development being utilized in various disciplines. However, it is necessary to develop environment and requirement for qualitative improvement of BIM based project. Particularly, requirement is very important for architectural design evaluations. The purpose of this study is to develop and apply of quality control requirement for improving the quality of architectural design in open BIM environments. To achieve this purpose, the authors have investigated case study for open BIM data quality control (software, guideline and application case) and classified quality control targets according to physical/logical quality and data quality. In addition, the authors have defined open BIM based quality control process and developed quality control requirements. Finally, the authors have developed rule based quality check system using requirements for efficient quality control based on open BIM.

• Journal of Internet Computing and Services
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• v.14 no.2
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• pp.25-34
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• 2013

In this paper, we propose an activity-performer bipartite matrix generation algorithm for analyzing workflow-supported human-resource affiliations in a workflow model. The workflow-supported human-resource means that all performers of the organization managed by a workflow management system have to be affiliated with a certain set of activities in enacting the corresponding workflow model. We define an activity-performer affiliation network model that is a special type of social networks representing affiliation relationships between a group of performers and a group of activities in workflow models. The algorithm proposed in this paper generates a bipartite matrix from the activity-performer affiliation network model(APANM). Eventually, the generated activity-performer bipartite matrix can be used to analyze social network properties such as, centrality, density, and correlation, and to enable the organization to obtain the workflow-supported human-resource affiliations knowledge.

• Journal of Korea Spatial Information System Society
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• v.10 no.4
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• pp.67-75
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• 2008

This study is for the effective training strategy of human resources for the u-City construction to support the u-City human resource development plan of the Ministry of Land, Transport and Maritime Affairs (MLTM). One of the biggest problems concerning u-City is the shortage of advanced human resources for the u-City constructions. The characteristic of u-City makes u-City related human resources had knowledge of various fields including IT, GIS, construction engineering, urban planning and so on. But, there are only a few programs to train u-City related human resources. Therefore, this research established the objective of the training strategy for u-City human resource development as "the training strategy of human resources for the successful u-City constructions". To achieve this objective, four different core strategies are established like followings: (1) demander-oriented education, (2) regional balanced education, (3) integration education of u-City related subjects, (4) u-City related education infrastructure development. These 4 different core strategies can be achieved from 5 sub projects like followings: (1) demand estimation of u-City human resources, (2) u-City education from selected regional core universities, (3) u-City education from u-City human resource education centers, (4) online education and (5) construction of education infrastructures. These 5 interrelated sub projects can be preconditions of the successful human resource strategy development.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.1061-1065
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• 2004

The knowledge-based society of the 21st century requires effective education and learning methods in each professional field because the development of human resource determines its competence more than any other factors. It is highly desirable to develop an intelligent tutoring system, which meets ever increasing demands of education and learning. Such a system should be adaptive to each individual learner's demands as well as the continuously changing state of the learning process, thus enabling the effective education. The development of a learning environment based on learner modeling is necessary in order to be adaptive to individual learning variants. An intelligent learning environment is being developed targeting the heritage education, which is able to provide a customized and refined learning guide by storing the content of interactions between the system and the learner, analyzing the correlations in learning situations, and inferring the learning preference from the learner's learning history. This paper proposes a heritage learning system of Bulguksa temple, integrating the ontology-based learner modeling and the learning preference which considers perception styles, input and processing methods, and understanding process of information.

• Journal of Korea Society of Digital Industry and Information Management
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• v.15 no.1
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• pp.1-7
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• 2019

The objective of this study is to examine the trends in big data. Research abstracts were extracted from 4,019 articles, published between 1995 and 2018, on Web of Science and were analyzed using topic modeling and time series analysis. The 20 single-term topics that appeared most frequently were as follows: model, technology, algorithm, problem, performance, network, framework, analytics, management, process, value, user, knowledge, dataset, resource, service, cloud, storage, business, and health. The 20 multi-term topics were as follows: sense technology architecture (T10), decision system (T18), classification algorithm (T03), data analytics (T17), system performance (T09), data science (T06), distribution method (T20), service dataset (T19), network communication (T05), customer & business (T16), cloud computing (T02), health care (T14), smart city (T11), patient & disease (T04), privacy & security (T08), research design (T01), social media (T12), student & education (T13), energy consumption (T07), supply chain management (T15). The time series data indicated that the 40 single-term topics and multi-term topics were hot topics. This study provides suggestions for future research.