• Journal of Internet Computing and Services
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• v.2 no.4
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• pp.25-32
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• 2001

The CAD tools for ASIC design, which are already developed or will be developed in the future, have their own functions and different working environments in many cases. Therefore, it would be more effective in achieving the final design goal, if we have a system called CAD framework in which these CAD tools are systematically integrated. In this paper, we introduce same novel techniques for integrating systematically such the CAD tools, which are usually developed under UNIX shell environments, into the CAD framework with the standard graphics interface such as X-windows. Some meta languages and script file formats are developed for flexible specification of the system MENU hierarchy and the data dependencies among executable programs. We integrated two existing CAD tools into our CAD framework using the techniques and find out the integrated protype system is working well under the new system environments.

• Spatial Information Research
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• v.19 no.1
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• pp.83-91
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• 2011

The route finding analysis is an essential geo-related decision support tool in a LBS(Location based Services) and previous researches related to route guidance have been mainly focused on route guidances for vehicles. However, due to the recent spread of personal computing devices such as PDA, PMP and smart phone, route guidance for pedestrians have been increasingly in demand. The pedestrian route guidance is different from vehicle route guidance because pedestrians are affected more surrounding environment than vehicles. Therefore, pedestrian path finding needs considerations of factors affecting walking. This paper aimed to extract factors affecting walking and charting the factors for application factors affecting walking to pedestrian path finding. In this paper, we found various factors about environment of road for pedestrian and extract the factors affecting walking. Factors affecting walking consist of 4 categories traffic, sidewalk, network, safety facility. We calculated weights about each factor using analytic hierarchy process (AHP). Based on weights we calculated scores about each factor's attribute. The weight is maximum score of factor. These scores of factor are used to optimal pedestrian path finding as path finding cost with distance, accessibility.

• Journal of the Korean Society for Library and Information Science
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• v.49 no.2
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• pp.291-311
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• 2015

This paper demonstrates the comparative analysis of the similarity and difference between Medical Subject Headings (MeSH) and social tags. Both types of metadata have the same purpose - that is, succinctly abstracting content of a given document - but are created from heterogeneous viewpoints. The former MeSH terms show the aspects of publication related professionals, whereas the latter social tags are from the perspectives of general readers. When both types of metadata are assigned to the same publications, do they consist of different nomenclatures reflecting the heterogeneous viewpoints or are they similar, since both metadata types describe the same publications? Social tags are also compared with family terms of MeSH terms in the given MeSH hierarchy, so as to understand the specificity of social tags, related to MeSH terms. Lastly, given the fact that readers assign social tags in casual ways without any restricted vocabulary, we tested how many social tags contain consumer health terms, which are familiar to laypeople. Through these comparisons, we ultimately aim to examine how much the highly controlled publication index reflects general readers' cognitive understandings and stress the necessity of general readers' involvement in the publication indexing process.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.3
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• pp.346-350
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• 2010

Since sensor nodes have restriction of using resources in Zigbee network, number of study on improving efficiency is currently ongoing[1]. Clustering mechanism based on hierarchy structure provides a prevention of duplicated information and a facility of a network expansion[2]. however overheads can occurs when the cluster header is elected and the election of a incorrect cluster header causes to use resources inefficiently. In this paper, we propose that the cluster header election mechanism using distances between nodes and density of nodes in accordance with the operation of the central processing system in which the sync nodes are having information of location and energy with respect to general nodes based on hierachy clustering mechanism.

• Journal of Computing Science and Engineering
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• v.1 no.2
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• pp.125-160
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• 2007

Data Warehousing and OLAP (On-Line Analytical Processing) have turned into the key technology for comprehensive data analysis. Originally developed for the needs of decision support in business, data warehouses have proven to be an adequate solution for a variety of non-business applications and domains, such as government, research, and medicine. Analytical power of the OLAP technology comes from its underlying multidimensional data model, which allows users to see data from different perspectives. However, this model displays a number of deficiencies when applied to non-conventional scenarios and analysis tasks. This paper presents an attempt to systematically summarize various extensions of the original multidimensional data model that have been proposed by researchers and practitioners in the recent years. Presented concepts are arranged into a formal classification consisting of fact types, factual and fact-dimensional relationships, and dimension types, supplied with explanatory examples from real-world usage scenarios. Both the static elements of the model, such as types of fact and dimension hierarchy schemes, and dynamic features, such as support for advanced operators and derived elements. We also propose a semantically rich graphical notation called X-DFM that extends the popular Dimensional Fact Model by refining and modifying the set of constructs as to make it coherent with the formal model. An evaluation of our framework against a set of common modeling requirements summarizes the contribution.

• The Transactions of the Korea Information Processing Society
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• v.4 no.10
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• pp.2493-2500
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• 1997

We propose a new key management scheme for multiuser group which is classified as hierarchical structure (sometimes it is called a multilevel security hierarchy) in the symmetric key cryptosystem. The proposed scheme is based on the trapdoor one-way permutations which are generated by the pseudo-random permutation algorithm, and it is avaliable for multilevel hierarchical structure composed of a totally ordered set and a partially ordered set, since it has advantage for time and storage from an implemental point of view. Moreover, we obtain a performance analysis by comparing with the other scheme, and show that the proposed scheme is very efficient for computing time of key generation and memory size of key storage.

• 한국IT서비스학회:학술대회논문집
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• 2003.11a
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• pp.616-623
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• 2003

Since the computing environment changes very rapidly, the estimation of software effort is very difficult because it is not easy to collect a sufficient number of relevant cases from the historical data. If we pinpoint the cases, the number of cases becomes too small. However if we adopt too many cases, the relevance declines. So in this paper we attempt to balance the number of cases and relevance. Since many researches on software effort estimation showed that the neural network models perform at least as well as the other approaches, so we selected the neural network model as the basic estimator. We propose a search method that finds the right level of relevant cases for the neural network model. For the selected case set, eliminating the qualitative input factors with the same values can reduce the scale of the neural network model. Since there exists a multitude of combinations of case sets, we need to search for the optimal reduced neural network model and corresponding case set. To find the quasi-optimal model from the hierarchy of reduced neural network models, we adopted the beam search technique and devised the Case-Set Selection Algorithm. This algorithm can be adopted in the case-adaptive software effort estimation systems.

• Journal of Internet Computing and Services
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• v.20 no.3
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• pp.111-117
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• 2019

We categorize the model of simple payment into Magnetic Secure Transmission, Near Filed Communication, and App Card based on the Focus Group Interview. We also define the key drivers for the diffusion of simple payment services based on the literature review with the experts. Through Analytic Hierarchy Process our finding suggests that the degree of acceptance at the stores is the most critical factor which decides the diffusion of simple payment service model. Security is also the important driver but due to the fact that service providers should follow the information security rule and supervisory guidance, it actually did not make a big difference in terms of assessing competence of each model.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.133-141
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• 2001

Since the computing environment changes very rapidly, the estimation of software effort is very difficult because it is not easy to collect a sufficient number of relevant cases from the historical data. If we pinpoint the cases, the number of cases becomes too small. However is we adopt too many cases, the relevance declines. So in this paper we attempt to balance the number of cases and relevance. Since many researches on software effort estimation showed that the neural network models perform at least as well as the other approaches, so we selected the neural network model as the basic estimator. We propose a search method that finds the right level of relevant cases for the neural network model. For the selected case set. eliminating the qualitative input factors with the same values can reduce the scale of the neural network model. Since there exists a multitude of combinations of case sets, we need to search for the optimal reduced neural network model and corresponding case, set. To find the quasi-optimal model from the hierarchy of reduced neural network models, we adopted the beam search technique and devised the Case-Set Selection Algorithm. This algorithm can be adopted in the case-adaptive software effort estimation systems.

• KIISE Transactions on Computing Practices
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• v.22 no.11
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• pp.619-624
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• 2016

Social-aware video displays not only the relationships between characters but also diverse information on topics such as economics, politics and culture as a story unfolds. Particularly, the speaking habits and behavioral patterns of people in different situations are very important for the analysis of social relationships. However, when dealing with this dynamic multi-modal data, it is difficult for a computer to analyze the drama data effectively. To solve this problem, previous studies employed the deep concept hierarchy (DCH) model to automatically construct and analyze social networks in a TV drama. Nevertheless, since location knowledge was not included, they can only analyze the social network as a whole in stories. In this research, we include location knowledge and analyze the social relations in different locations. We adopt data from approximately 4400 minutes of a TV drama Friends as our dataset. We process face recognition on the characters by using a convolutional- recursive neural networks model and utilize a bag of features model to classify scenes. Then, in different scenes, we establish the social network between the characters by using a deep concept hierarchy model and analyze the change in the social network while the stories unfold.