• 대한가정학회지
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• 제39권4호
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• pp.79-89
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• 2001

This study investigated institutionalized children's behavior problems depending on their family networks. Subjects were 250 institutionalized children in 15 child-welfare facilities in Seoul(132 preschooler, 55 first and 63 second grade children; 144 boys and 106 girls). Data were analyzed with t-test, ANOVA, and Duncan test. Measures of behavior problems included internalizing (anxiety, immaturity, withdrawal, physical symptom) and externalizing behavior problems (hyperactivity, aggression). Results showed that institutionalized children having parents were higher in internalizing problems than children not having parents, while children living with siblings in the facilities were lower in externalizing problems than children living without siblings. Furthermore, institutionalized children having parents and living without siblings were higher in both internalizing and externalizing problems than children not having parents and living with siblings.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2011년도 학술발표회
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• pp.473-473
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• 2011

Group method of data handling neural networks model (GMDH-NNM) is used to estimate daily reference evapotranspiration (ETo) using limited climatic variables such as max temperature ($T_{max}$), min temperature ($T_{min}$), mean wind speed ($W_{mean}$), mean relative humidity ($RH_{mean}$) and sunshine duration (SD). And, for the performances of GMDH-NNM, it consists of training and test performances, respectively. The training and test performances are carried out using daily time series data, respectively. From this research, we evaluate the impact of GMDH-NNM for the modeling of the nonlinear time series data. We should, thus, construct the credible data of the daily ETo data using GMDH-NNM, and can suggest the methodology for the irrigation and drainage networks system. Furthermore, this research represents that the strong nonlinear relationship such as ETo modeling can be generalized using GMDH-NNM.

• 한국정보시스템학회:학술대회논문집
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• 한국정보시스템학회 2005년도 추계학술대회 발표 논문집
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• pp.463-470
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• 2005

In a rapidly changing business environment, the improvement of managerial techniques through IT utilization brings about remarkable increases in profitability and redesign of work process for better performances. IT innovation by electronic instruments such as ICT e-business provides accelerates forming inter-organizational information network and helps them benchmark the best practices of advanced organizations. A new shift of paradigm by e-business across all enterprises has turned the traditional aspects of inter-organizational competition and relationship into a form of collaboration. Collaboration enables business activities in parallel position among companies and facilitates cooperation between partner enterprises. Lately, the concept of 'Synchronization' is emerging beyond dimension of cooperation between networks, and the most concepts related to it are converging into 'Collaboration Networks'. This research observes a virtual organization as a form of collaborative networks, and measures the degree of virtualization of Korean collaborative organizations.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2010년도 학술발표회
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• pp.1439-1442
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• 2010

Time-lag recurrent neural networks model (Time-Lag RNNM) is used to estimate daily pan evaporation (PE) using limited climatic variables such as max temperature ($T_{max}$), min temperature ($T_{min}$), mean wind speed ($W_{mean}$) and mean relative humidity ($RH_{mean}$). And, for the performances of Time-Lag RNNM, it is composed of training and test performances, respectively. The training and test performances are carried out using daily time series data, respectively. From this research, we evaluate the impact of Time-Lag RNNM for the modeling of the nonlinear time series data. We should, thus, construct the credible data of the daily PE using Time-Lag RNNM, and can suggest the methodology for the irrigation and drainage networks system. Furthermore, this research represents that the strong nonlinear relationship such as pan evaporation modeling can be generalized using Time-Lag RNNM.

• Genomics & Informatics
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• 제11권4호
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• pp.200-210
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• 2013

Studying biological networks, such as protein-protein interactions, is key to understanding complex biological activities. Various types of large-scale biological datasets have been collected and analyzed with high-throughput technologies, including DNA microarray, next-generation sequencing, and the two-hybrid screening system, for this purpose. In this review, we focus on network-based approaches that help in understanding biological systems and identifying biological functions. Accordingly, this paper covers two major topics in network biology: reconstruction of gene regulatory networks and network-based applications, including protein function prediction, disease gene prioritization, and network-based genome-wide association study.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2001년도 학술발표회 논문집(I)
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• pp.45-51
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• 2001

The daily inflow is apparently one of nonlinear and complicated phenomena. The nonlinear and complexity make it difficult to model the prediction of daily flow, but attractive to try the neural networks approach which contains inherently nonlinear schemes. The study focuses on developing the forecasting models of daily inflows to a large dam site using neural networks. In order to reduce the error caused by high or low outliers, the back propagation algorithm which is one of neural network structures is modified by combining a regression algorithm. The study indicates that continuous forecasting of a reservoir inflow in real time is possible through the use of modified neural network models. The positive effect of the modification using tole regression scheme in BP algorithm is showed in the low and high ends of inflows.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2019년도 학술발표회
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• pp.159-159
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• 2019

In this study, the simulation of sediment deposition at Sangju weir reservoir, South Korea, was carried out using artificial neural networks. The ANNs have typically been used in water resources engineering problems for their robustness and high degree of accuracy. Three basic variables namely turbid water inflow, outflow, and water stage have been used as input variables. It was found that ANNs were able to establish valid relationship between input variables and target variable of sedimentation. The R value was 0.9806, 0.9091, and 0.8758 for training, validation, and testing phase respectively. Comparative analysis was also performed to find optimum structure of ANN for sediment deposition prediction. 3-14-1 network architecture using BR algorithm outperformed all other combinations. It was concluded that ANN possess mapping capabilities for complex, non-linear phenomenon of reservoir sedimentation.

• 한국콘텐츠학회논문지
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• 제9권12호
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• pp.537-545
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• 2009

본 논문에서는 이동통신망을 위한 효율적인 멀티캐스트 인과순서 알고리즘과 채널전환 프로토콜을 제안하였다. 메시지 전달 순서를 유지하기 위한 제어정보의 크기는 이동통신망에서의 채널전환과 메시지 전송성능에 큰 영향을 주므로 제어정보의 크기를 최소화할 필요가 있다. 이를 위해 모든 유효한 통신패턴을 분석하여 인과순서를 유지하는데 필수적이지 않은 중복정보를 가능한 이른 시기에 찾아내어 제거하고, 전송되는 제어정보를 최소화하는 채널전환 프로토콜을 사용하였다. 시뮬레이션을 통해 제안한 알고리즘이 기존의 알고리즘보다 더 좋은 성능을 보임을 보였다.

• 한국콘텐츠학회논문지
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• 제8권6호
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• pp.34-42
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• 2008

무선망에서 다양한 트래픽의 종단간 서비스의 질을 보장하기 위해서는 매체접근제어가 요구된다. 무선망에서 다양한 트래픽이 채널에서 통합될 때 매체접근제어 프로토콜의 주요 단점은 한정된 대역폭을 어떻게 효율적으로 멀티 클래스 트래픽을 위해 지원할 수 있는가이다. 본 논문에서는 실시간 트래픽의 서비스의 질을 향상시키기 위해 동적 대역 슬롯 기법을 제안하였다. 제안된 기법에서는 동적파라미터를 전송하기 위해서 인 밴드 방식을 사용하였으며, 버퍼의 크기와 지연변이를 고려하여 이동국에서는 2상태 비트를 기지국으로 전송될 수 있도록 하였다. 제안된 기법은 실시간 트래픽의 서비스의 질을 보장하고 전송효율을 높일 수 있도록 하였다.

• 한국콘텐츠학회논문지
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• 제6권3호
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• pp.28-37
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• 2006

인터넷 기술은 지난 30여 년간 비약적으로 발전하여 모든 산업분야를 변혁시키고 개인과 기업의 필수도 구로서 국가의 중요한 기반시설로 자리 잡았다. 1990년대 중반부터 선진국들은 인터넷을 과학 및 교육 분야의 발전에 가장 중요한 기반시설의 하나로 인식하고 국가 연구 교육망을 구축하고 이를 새로운 망 기술과 과학 기술 개발을 위한 도구로 제공하고 있다. 이 논문에서 우리는 선진국의 연구 교육망 발전 현황을 종합적으로 살펴보고, 국내 첨단망 활동을 선진국과 비교하여 문제점 분석하고, 이를 토대로 한국 첨단망의 발전 방안을 제시하였다.