• 한국산업정보학회:학술대회논문집
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• 한국산업정보학회 2008년도 추계 공동 국제학술대회
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• pp.479-491
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• 2008

A "task network" is a type of social network that consists of experts who exchange professional help and advice regarding executing tasks. In this study, we investigate the task network used within the IS department of a national bank in Korea. We identify how this network moderates the influence of computer-mediated communication (CMC) technology on an individual s task performance. Size, density, and centrality were measured as the characteristics of a personal task networks. Size equates to the total number of colleagues who work with a specific member for a certain project. Density is the ratio of the number of actual relationships to the total number of available relationships. Centrality defines whether an individual s position is in the exact center of whole network, and is measured by betweenness centrality, meaning the position one member holds between others in a network. Our findings conclude that the conditions - the larger the size of the task network, the smaller its density and the higher its level of centrality - lead to more benefits of using CMC media. Further, this positive effect of CMC is more noticeable when it provides synchronicity.

• 대한기계학회논문집A
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• 제24권9호
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• pp.2361-2370
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• 2000

The introduction of inexpensive cylinder pressure sensors provides new opportunities for precise engine control. This paper presents a control strategy of spark advance based upon cylinder pressure of spark ignition engines. A location of peak pressure(LPP) is the major parameter for controlling the spark timing, and also the UP is estimated, using a multi-layer feedforward neural network, which needs only five pressure sensor output voltage samples at -40˚, -20˚, 0˚, 20˚, 40˚ after top dead center. The neural network plays an important role in mitigating the A/D conversion load of an electronic engine controller by increasing the sampling interval from 10 crank angle(CA) to 20˚ CA. A proposed control algorithm does not need a sensor calibration and pegging(bias calculation) procedure because the neural network estimates the UP from the raw sensor output voltage. The estimated LPP can be regarded as a good index for combustion phasing, and can also be used as an MBT control parameter. The feasibility of this methodology is closely examined through steady and transient engine operations to control individual cylinder spark advance. The experimental results have revealed a favorable agreement of individual cylinder optimal combustion phasing.

• 한국IT서비스학회지
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• 제12권4호
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• pp.145-164
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• 2013

With the rapidly expanding social network service, the distribution of information shows that social networks have evolved into platforms of communication and new information sharing among users. Previous studies are focused on the motivational factors of information sharing through social networking service. However, in this study, we focus on the factors that affect intention to share information in terms of both user's psychological motivation and functional characteristics of social network service. This study shows that factors such as enjoyfulness, image, identity and communication positively affect the attitude and intention of information sharing.

• BMB Reports
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• 제45권4호
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• pp.213-220
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• 2012

Viruses have evolved to manipulate the host cell machinery for virus propagation, in part by interfering with the host cellular signaling network. Molecular studies of individual pathways have uncovered many viral host-protein targets; however, it is difficult to predict how viral perturbations will affect the signaling network as a whole. Systems biology approaches rely on multivariate, context-dependent measurements and computational analysis to elucidate how viral infection alters host cell signaling at a network level. Here we describe recent advances in systems analyses of signaling networks in both viral and non-viral biological contexts. These approaches have the potential to uncover virus- mediated changes to host signaling networks, suggest new therapeutic strategies, and assess how cell-to-cell variability affects host responses to infection. We argue that systems approaches will both improve understanding of how individual virus-host protein interactions fit into the progression of viral pathogenesis and help to identify novel therapeutic targets.

• 한국통계학회:학술대회논문집
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• 한국통계학회 2003년도 춘계 학술발표회 논문집
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• pp.237-242
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• 2003

Various kinds of estimation methods have been developed for imputation of categorical missing data. They include modal category method, logistic regression, and association rule. In this study, we propose two imputation methods (neural network fusion and voting fusion) that combine the results of individual imputation methods. A Monte-Carlo simulation is used to compare the performance of these methods. Five factors used to simulate the missing data are (1) true model for the data, (2) data size, (3) noise size (4) percentage of missing data, and (5) missing pattern. Overall, neural network fusion performed the best while voting fusion is better than the individual imputation methods, although it was inferior to the neural network fusion. Result of an additional real data analysis confirms the simulation result.

• 한국지능시스템학회논문지
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• 제13권4호
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• pp.474-479
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• 2003

In this paper, we proposed the novel method for the recognition of English calling cards by using the projection method and the enhanced RBF (Radial Basis Function) network. The recognition of calling cards consists of the extraction phase of character areas and the recognition phase of extracted characters. In the extraction phase, first of all, noises are removed from the images of calling cards, and the feature areas including character strings are separated from the calling card images by using the horizontal smearing method and the 8-directional contour tracking method. And using the image projection method, the feature areas are split into the areas of individual characters. We also proposed the enhanced RBF network that organizes the middle layer effectively by using the enhanced ART1 neural network adjusting the vigilance threshold dynamically according to the homogeneity between patterns. In the recognition phase, the proposed neural network is applied to recognize individual characters. Our experiment result showed that the proposed recognition algorithm has higher success rate of recognition and faster learning time than the existing neural network based recognition.

• Journal of Multimedia Information System
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• 제6권3호
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• pp.131-138
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• 2019

With the rapid evolution of communication technology, it became possible to overcome the spatial and temporal limitations faced by humans to some extent. Furthermore, the quality of personal life was revolutionized with the emergence of the personal communication device commonly known as the smart phone. In terms of defense networks, however, due to restrictions from the military and security perspectives, the use of smart phones has been prohibited and controlled in the army; thus, they are not being used for any defense strategy purposes as yet. Despite the current consideration of smart phones for military communication, due to the difficulties of network configuration and the high cost of the necessary communication devices, the main tools of communication between soldiers are limited to the use of flag, voice or hand signals, which are all very primitive. Although these primitive tools can be very effective in certain cases, they cannot overcome temporal and spatial limitations. Likewise, depending on the level of the communication skills of each individual, communication efficiency can vary significantly. As the term of military service continues to be shortened, however, types of communication of varying efficiency depending on the levels of skills of each individual newly added to the military is not desirable at all. To address this problem, it is essential to prepare an intuitive network configuration that facilitates use by soldiers in a short period of time by easily configuring the strategy network at a low cost while maintaining its security. Therefore, in this article, the author proposes a Zigbee-based local strategic network by using Opnet and performs a simulation accordingly.

• 보건교육건강증진학회지
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• 제29권1호
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• pp.39-57
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• 2012

Objectives: This study was to measure community capacity using individual-level and organizational-level capacity indicators and illuminated the relationship of community capacity and self-rated health status in two regions in Seoul, Korea. Methods: The data from individual surveys were obtained by quota sampling the residents of two autonomous gu in Seoul (N=1,000). The data from organizational surveys were obtained by snowball sampling lists of organizations in the possession of gu offices with a sampling frame (N=153). The survey tools were 6 indicators regarding residents' social capital and a sense of community and 5 indicators regarding community-based organizations and their networks. The analysis methods consisted of the effect of the components of capacity on health status and social network analysis. Results: As for capacity on individual levels, while D-gu was mainly developed inn individual capacity in terms of social interaction, Y-gu was stronger in a sense of community and cohesion among residents. As for capacity on organizational levels, Y-gu was more developed than was D-gu in associational networks. Conclusion: It is necessary to develop health promotion program per community and to strengthen partnerships with and among grassroots organizations based in local communities through the measurement of community capacity.

• 인터넷정보학회논문지
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• 제9권5호
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• pp.165-173
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• 2008

하이브리드 애드 혹 네트워크는 통합 네트워크로서 홈 네트워크, 텔레매틱스, 센서 네트워크 등에서 다양한 종류의 서비스를 제공할 수 있다. 특히 애드 혹 네트워크의 각 노드는 이웃 노드들에 데이터를 전송해야 하므로, 전체 에너지의 사용량을 줄이면서, 균형적으로 에너지를 사용하게 해야 한다. 균형적으로 에너지를 사용하지 않으면 부하가 걸린 노드에서 빠른 시간 내에 노드 전송 실패가 나타날 수 있으며, 이는 네트워크 분할 및 네트워크의 기능제공 시간이 단축되는 것을 의미한다. 그러므로 본 논문에서는 에너지의 효율성을 고려한 라우팅 알고리즘에 관한 연구를 수행하였다. 제안한 알고리즘에서는 예측모델을 이용해 각 노드의 에너지의 잔량을 예측하므로, 라우팅 경로의 설정시 에너지 정보를 얻기 위한 많은 부하를 감소시킬 수 있으며, 전체 노드에 걸쳐 에너지의 사용을 균형적으로 사용하게 할 수 있다. 이에 따라 에너지의 손실의 감소 및 네트워크의 가용시간을 연장할 수 있다

• 농업과학연구
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• 제47권3호
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• pp.509-517
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• 2020

Geographic information system (GIS) sewer network data are a fundamental input material for urban inundation modeling, which is important to reduce the increasing damages from urban inundation due to climate change. However, the essential attributes of the data built by a local government are often missing because the purpose of building the data is the maintenance of the sewer system. Inconsistent simplification and supplementation of the sewer network data made by individual researchers may increase the uncertainty of flood simulations and influence the inundation analysis results. Therefore, it is necessary to develop a basic algorithm to convert the GIS-based sewage network data into input data that can be used for inundation simulations in consistent way. In this study, the format of GIS-based sewer network data for a watershed near the Sadang Station in Seoul and the Oncheon River Basin in Busan was investigated, and a missing data supplementing algorithm was developed. The missing data such as diameter, location, elevation of pipes and manholes were assumed following a consistent rule, which was developed referring to government documents, previous studies, and average data. The developed algorithm will contribute to minimizing the uncertainty of sewer network data in an urban inundation analysis by excluding the subjective judgment of individual researchers.