• Biotechnology and Bioprocess Engineering:BBE
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• v.10 no.5
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• pp.385-399
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• 2005

The phenotypic response of a cell results from a well orchestrated web of complex interactions which propagate from the genetic architecture through the metabolic flux network. To rationally design cell factories which carry out specific functional objectives by controlling this hierarchical system is a challenge. Transcriptome analysis, the most mature high-throughput measurement technology, has been readily applied In strain improvement programs in an attempt to Identify genes involved in expressing a given phenotype. Unfortunately, while differentially expressed genes may provide targets for metabolic engineering, phenotypic responses are often not directly linked to transcriptional patterns, This limits the application of genome-wide transcriptional analysis for the design of cell factories. However, improved tools for integrating transcriptional data with other high-throughput measurements and known biological interactions are emerging. These tools hold significant promise for providing the framework to comprehensively dissect the regulatory mechanisms that identify the cellular control mechanisms and lead to more effective strategies to rewire the cellular control elements for metabolic engineering.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.4
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• pp.993-999
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• 2011

In WSN, at the initial stage, sensor nodes are randomly deployed over the region of interest, and self-configure the clustered networks by grouping a bunch of sensor nodes and selecting a cluster header among them. Specially, in WSN environment, in which the administrator's intervention is restricted, the self-configuration capability is essential to establish a power-conservative WSN which provides broad sensing coverage and communication coverage. In this paper, we propose a communication coverage-aware cluster head election algorithm for Herearchical WSNs which consists of communication coverage-aware of the Base station is the cluster head node is elected and a clustering.

• Proceedings of the Korean Information Science Society Conference
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• 2004.04a
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• pp.238-240
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• 2004

본 논문에서는 대규모 네트워크 보안관리를 위한 계층적인 위임 모델을 제시한다. 대규모 네트워크는 라우터, 방화벽, 침입 탐지 시스템, 웹 서버 등의 수많은 구성요소로 이루어진 네트워크들의 집합이며, 각 네트워크마다의 독립적인 지역 정책들로 관리되어 서로간의 협동이 이루어질 수 없기 때문에 이를 효과적으로 통제하고 일괄적으로 관리하기 위해 계층적인 위임 모델이 사용되어야 한다. 제시하는 모델의 중요 구성 요소로는 관리 서버. 정책 설정 고 수준 언어 고 수준 언어 컴파일러, 도메인 서버. 인터프리터, 정책 관리 데이터베이스가 있다. 관리 서버에서 정책 설정 고 수준 언어를 사용하여 세밀하고 정교한 정책을 작성할 수 있고, 이 정책을 고 수준 언어 컴파일러를 통하여 최하위 노드들에게 적절하고 간결한 형태로 만들어낸다. 각 도메인 서버는 이 결과를 하위의 도메인 서버나 인터프리터에게 전달하면서 Keynote 신뢰 관리 시스템을 이용하여 권한을 위임한다. 그리고 인터프리터는 정책을 라우터, 방화벽, 웹 서버 등의 하위 노드에 맞는 실제 룰로 변환하녀 상위 관리 서버에서 전달한 정책을 적용하게 된다. 정책을 적용한 결과를 상위로 전달하여 데이터베이스를 구축한 뒤 후에 작성된 정책이 기존의 정책과 충돌하는지 검사에 이용하고, 충돌한다면 협상 과정을 거쳐 정책에 순응할 수 있는 결과를 도굴하게 된다. 또한 네트워크에서 많은 새로운 형태들의 노드가 추가될 수 있는데, 각각의 인터프리터만 추가함으로서 다양한 하위 노드를 충족시킬 수 있는 확장성을 제공한다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.10 no.4
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• pp.43-52
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• 1990

Theoretical foundation and algorithms are presented of a new surface modeling and pre-processing system for the three-dimensional structures. The modeling method is based on the boundary representation scheme and composed of two hierarchical model structures: curve-network and surface models. The concept of modeling curve as a union of links is introduced to facilitate surface modeling via various transfinite mapping techniques or Coons Patches. Efficiency and novel aspects of the present method are discussed. Finite element mesh genceration and application procedures will be reported in a later paper.

• Korean Journal of Human Ecology
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• v.22 no.3
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• pp.437-453
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• 2013

The purpose of this study was to identify how social relationships and family relationships were associated with the life satisfaction of married female baby boomers who live in Busan and Gyeongnam province. This study included community sample of 499 female baby boomers who were married and had at least one child. Participants reported lower levels of life satisfaction. A hierarchical regression analysis was conducted to investigate the effects of the following variables on the female baby boomers' life satisfaction: subjective health, educational level, monthly household income, employment status, perceived size of social network, participation in leisure organizations, participation in voluntary associations, satisfaction with children, and marital satisfaction. Except employment status and participation in leisure organizations, other 7 variables were significantly and positively associated with the life satisfaction of married female baby boomers. In particular, marital satisfaction had the strongest effect on life satisfaction, followed by satisfaction with children. The results suggested family played a primary role in the life of married female baby boomers. Family life education program~ female baby boomers, their children and husbands need to be developed and offered in order to improve the life satisfaction of female baby boomers.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2000.10a
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• pp.412-418
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• 2000

In this paper, we will propose that HCN(n,n) gets Hamiltonian Cycles and analyze embedding among HCN(n,n) and UFN(n,n), and HFN(n,n) and In-hypercube. Further, we will prove that HCN(n,n) can be embedded into HFN(n,n) with dilation 3 and the cost for HFN(n,n) to be embedded into HCN(n,n) will be O(n), and HW(n,n) can be embedded into 2n-hypercube with dilation 3 and the cost for In-hypercube to be embedded into HFN(n,n) will be O(n).

• KIPS Transactions on Software and Data Engineering
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• v.6 no.6
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• pp.285-292
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• 2017

There are technological, operational and environmental constraints at tactical edge, which are disconnected operation, intermittent connectivity, and limited bandwidth (DIL), size, weight and power (SWaP) limitations, ad-hoc and mobile network, and so on. To overcome these limitations and constraints, we use service-oriented architecture (SOA) based technologies. In our research, we propose a hierarchical mission service model that supports service-oriented mission planning and execution in order for a commander to operate various SW required for mission in battlefield environment. We will also implement development tools that utilize the workflow technology and semantic capability-based recommendation and apply them to combat mission scenarios to demonstrate effectiveness.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1287-1292
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• 2005

This paper presents an effective pattern classification model by designing an artificial neural network based pattern classifiers for face recognition. First, a RGB image inputted from a frame grabber is converted into a HSV image which is similar to the human beings' vision system. Then, the coarse facial region is extracted using the hue(H) and saturation(S) components except intensity(V) component which is sensitive to the environmental illumination. Next, the fine facial region extraction process is performed by matching with the edge and gray based templates. To make a light-invariant and qualified facial image, histogram equalization and intensity compensation processing using illumination plane are performed. The finally extracted and enhanced facial images are used for training the pattern classification models. The proposed H-ART2 model which has the hierarchical ART2 layers and F-LVQ model which is optimized by fuzzy membership make it possible to classify facial patterns by optimizing relations of clusters and searching clustered reference patterns effectively. Experimental results show that the proposed face recognition system is as good as the SVM model which is famous for face recognition field in recognition rate and even better in classification speed. Moreover high recognition rate could be acquired by combining the proposed neural classification models.

• Journal of IKEEE
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• v.11 no.4
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• pp.322-330
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• 2007

Recent advances in wireless networks and low-cost, low-power design have led to active research in large-scale networks of small, wireless, low power sensors and actuators, In large-scale networks, lots of timing-synchronization protocols already exist (such as NTP, GPS), In ad-hoc networks, especially wireless sensor networks, it is hard to synchronize all nodes in networks because it has no infrastructure. In addition, sensor nodes have low-power CPU (it cannot perform the complex computation), low batteries, and even they have to have active and inactive section by periods. Therefore, new approach to time synchronization is needed for wireless sensor networks, In this paper, I propose Energy-Efficient Time Synchronization (EETS) protocol providing network-wide time synchronization in wireless sensor networks, The algorithm is organized two phase, In first phase, I make a hierarchical tree with sensor nodes by broadcasting "Level Discovery" packet. In second phase, I synchronize them by exchanging time stamp packets, And I also consider send time, access time and propagation time. I have shown the performance of EETS comparing Timing-sync Protocol for Sensor Networks (TPSN) and Reference Broadcast Synchronization (RBS) about energy efficiency and time synchronization accuracy using NESLsim.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.10
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• pp.140-148
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• 1994

In this paepr, the modified neocognitron, which has capability of recognizing multi-patterns in input image in one pass, is proposed. It is the hierarchical neural network composed of S and V layer which are able to extract features and of C layer with little effect from deformation, changes in size, shifts in position. S and V cells extract the features of all patterns in input image by applying DCC(don't care condition) to those cells. S and C cells also have position informations of extracted patterns. Position information is used in extracting good features without extracted features beting interfered one another. The proposed method is shorter in recognition time than the selective attention method with backward connection, because of recognizing multi-patterns in one passe. The modified neocognitron can recognizze attached multi-patterns because of using DCC and position informations.