• Child Health Nursing Research
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• 제3권1호
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• pp.42-51
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• 1997

Although a family-centered approach to health care for developmentally disabled children has been advocated, existing systems of care have not adequately addressed the support needs of the family system and the essential role that parents play in the daily care of these children. The overall purpose of this research is to examine family system adaptation to the care of a developmetally disabled child using the Resiliency Model of Family Stress, Adjustement, and Adaptation Framework. Relationships among family system demands (stressors, strains, transitions, child's illness factors) and family system strengths and capabilities(resource of social support) were examined to determine their separate and combined contribution to explanining the variability in family system outcomes (family system coping ). The subject for this study was 46 families who have a child with developmental disabilities(mental retardation and / or autism) from three special educational programs in Seoul, Korea. Results from correlation and hierachial regression analysis revealed that perceived social support operated as a resiliency factor between family stress and coping. Child and family characteristics appeared to be important predictors of perceived social support and coping. In summary, there is evidence that the resource of social support as a family strength and capability was found to improve the family coping. These findings also must be viewed within the context that sample of families of children with disabilities was relatively small and eligible families from support group of special educational program.

• Structural Engineering and Mechanics
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• 제44권3호
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• pp.379-403
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• 2012

In recent years, the need for optimal design of structures under time-history loading aroused great attention in researchers. The main problem in this field is the extremely high computational demand of time-history analyses, which may convert the solution algorithm to an illogical one. In this paper, a new framework is developed to solve the size optimization problem of steel truss structures subjected to ground motions. In order to solve this problem, the covariance matrix adaptation evolution strategy algorithm is employed for the optimization procedure, while a generalized regression neural network is utilized as a meta-model for fitness approximation. Moreover, the computational cost of time-history analysis is decreased through a wavelet analysis. Capability and efficiency of the proposed framework is investigated via two design examples, comprising of a tower truss and a footbridge truss.

• 방송공학회논문지
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• 제13권5호
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• pp.586-595
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• 2008

본 논문에서는 이동 환경에서 다시점 비디오를 제공하는 적응형 다시점 비디오 서비스 프레임워크를 제안한다. 중간시점 영상의 실시간 생성과 다시점 비디오의 클라이언트 적응을 통해 이동 환경이 갖는 성능 제약을 해결한다. 그리고 적응 변환 작업을 서버에서 수행함으로써 클라이언트의 부하를 줄이고, H.264/AVC를 채택하여 비디오의 압축 효율을 개선한다. 이를 위해, 멀티미디어 프레임워크 표준인 MPEG-21 DIA (Digital Item Adaptation)를 참조하여, 사용자 요구와 클라이언트 기기의 특성에 맞도록 비디오를 적응시키는 이동 환경을 위한 새로운 다시점 비디오 DIA를 구현한다. 제안 프레임워크의 효율성과 성능을 측정한 결과, 다시점 비디오의 이동 서비스는 양방향으로 해상도가 $320{\times}240$이면, 최대 초당 13 프레임까지 가능하고, 기존 3D 점의 투영 방법과 비교하여 5배 빠른 중간시점 영상을 생성한다.

• 컴퓨터교육학회논문지
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• 제11권4호
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• pp.59-69
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• 2008

본 논문은 현재 간호학과에 재학 중인 학생들의 컴퓨터 활용 능력과 실제 임상에서의 컴퓨터 활용 실태를 조사하여 현장에서 컴퓨터 활용에 있어서 부족한 부분을 개선하기 위하여 필요로 하는 사항을 제시하였다. 정보과학의 발달로 인한 병원업무는 병원 정보 시스템을 이용한 시스템적 관리 체제가 이루어지고 있다. 그러므로 정보 분야에 대응하는 간호학과에서의 컴퓨터 활용교육은 교양 과목으로 진행되는 일방적이고 획일적인 공급자 중심의 교육이 아닌 현장 환경에 맞는 학습자 중심의 교육이 이루어져야 한다. 따라서 본 논문에서는 현재의 단순한 간호 정보 지식 교육에서 정보 시스템 지식 습득 및 실습으로 변경될 것을 제안한다.

• 한국컴퓨터정보학회논문지
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• 제23권12호
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• pp.211-218
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• 2018

In this paper, we propose that investigating the relationship between the dynamic capacity and the technological innovation performance of firms. Based on the previous research, we divide the dynamic capacity into the adaptive capacity, absorption capacity, and productive capacity. Among the 3,400 companies responding to the technical statistics of SMEs in 2011, we performed multiple regression analysis with 2,807 except service industries. As a result, the absorptive capacity and productive capacity have a positive effect on the technological innovation performance at the 99% level, whereas the adaptive capacity has a negative effect on the technological innovation performance at the 95% level. The implications of this study are as follows. First, in order to improve the performance of technological innovation, it is important to strengthen the absorption capacity and productive capacity of companies. Absorption capacity shows that it is important to secure sufficient R & D manpower and R & D cost to utilize internal knowledge as well as to bring outside knowledge into the capacity to assimilate and utilize external knowledge. Second, the ability to commercialize a product is a capability to commercialize a technology that has succeeded in development, showing that the technology development organization must have the capability of post-development commercialization as well as technology development. Finally it shows the negative effect on adaptation capacity and innovation performance. Companies actively utilize external sources of information in order to respond to and adapt to the rapidly changing business environment. However, the results of this study show that a strategic approach is needed to use external sources of information and technology development resources. Especially as the use of external information resources and technology development resources increases.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제7권2호
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• pp.96-101
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• 2007

Neural networks are known as kinds of intelligent strategies since they have learning capability. There are various their applications from intelligent control fields; however, their applications have limits from the point that the stability of the intelligent control systems is not usually guaranteed. In this paper we propose an adaptive tracking control for robot manipulators using the radial basis function network (RBFN) that is e. kind of neural networks. Adaptation laws for parameters of the RBFN are developed based on the Lyapunov stability theory to guarantee the stability of the overall control scheme. Filtered tracking errors between actual outputs and desired outputs are discussed in the sense of the uniformly ultimately boundedness(UUB). Additionally, it is also shown that parameters of the RBFN are bounded. Experimental results for a SCARA-type robot manipulator show that the proposed adaptive tracking controller is adaptable to the environment changes and is more robust than the conventional PID controller and the neuro-controller based on the multilayer perceptron.

• 제어로봇시스템학회논문지
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• 제12권3호
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• pp.201-207
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• 2006

A robust Kalman filtering method for uncertain stochastic systems is suggested by adopting a perturbation estimation process which is to reconstruct total uncertainty with respect to the nominal state transition equation. The predictor and corrector of discrete Kalman filter are reformulated with the perturbation estimator. Successively, the state and perturbation estimation error dynamics and the corresponding error covariance propagation equations are derived as well. Finally we have the recursive algorithm of Combined Kalman Filter-Perturbation Estimator (CKF). The proposed combined Kalman filter-perturbation estimator has the property of integrating innovations and the adaptation capability to system uncertainties. A numerical example is shown to demonstrate the effectiveness of the proposed scheme.

• 제어로봇시스템학회논문지
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• 제9권2호
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• pp.168-175
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• 2003

A new algorithm based on Genetic Algorithms is proposed f3r solving process optimization problems formulated in MINLP, GDP and hybrid MINLP/GDP. This work is focused especially on the design of the Genetic Algorithm suitable to handle disjunctive programming with the same level of MINLP handling capability. Hybridization with the Simulated Annealing is experimented and many heuristics are adopted. Real and binary coded Genetic Algorithm initiates the global search in the entire search space and at every stage Simulated Annealing makes the candidates to climb up the local hills. Multi-Niche Crowding method is adopted as the multimodal function optimization technique. and the adaptation of probabilistic parameters and dynamic penalty systems are also implemented. New strategies to take the logical variables and constraints into consideration are proposed, as well. Various test problems selected from many fields of process systems engineering are tried and satisfactory results are obtained.

• 대한의용생체공학회:의공학회지
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• 제15권3호
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• pp.355-364
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• 1994

The most important requirement for the controller of a prosthetic arm is that it has a high fidelity discriminator where the motion control may be performed open loop using EMG signals as a control source. Therefore, it is very effective method to reduce the influence of misclassification of classifier for the total system performance. This paper presents the new function discrimination method which combines MLP classifier and frizzy filter by stages for the requirement. The major advantage of MLP is a consistent learning capability for the easy adaptation to environments. The fuzzy filter uses all informations of MLP outputs and prior EMG activity informations which increase as the experience increases. That property is superior to one which uses maximum output of MLP in view of information amounts and quality. Simulation result shows that proposed method is superior to the probabilistic model, MLP model and the combined model of both in the respect of discrimination quaity.

• Journal of Communications and Networks
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• 제12권4호
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• pp.346-357
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• 2010

Opportunistic scheduling provides the capability of resource management in wireless networks by taking advantage of multiuser diversity and by allowing delay variation in delivering data packets. It generally aims to maximize system throughput or guarantee fairness and quality of service (QoS) requirements. In this paper, we develop an extended proportional fair (PF) scheduling policy that can statistically guarantee three kinds of QoS. The scheduling policy is derived by solving the optimization problems in an ideal system according to QoS constraints. We prove that the practical version of the scheduling policy is optimal in opportunistic scheduling systems. As each scheduling policy has some parameters, we also consider practical parameter adaptation algorithms that require low implementation complexity and show their convergences mathematically. Through simulations, we confirm that our proposed schedulers show good fairness performance in addition to guaranteeing each user's QoS requirements.