• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 Proceedings of the Korea Automatic Control Conference, 11th (KACC); Pohang, Korea; 24-26 Oct. 1996
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• pp.95-98
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• 1996

Universal Learning Network(U.L.N.), which can model and control the large scale complicated systems naturally, consists of nonlinearly operated nodes and multi-branches that may have arbitrary time delays including zero or minus ones. Therefore, U.L.N. can be applied to many kinds of systems which are difficult to be expressed by ordinary first order difference equations with one sampling time delay. It has been already reported that learning algorithm of parameter variables in U.L.N. by forward and backward propagation is useful for modeling, managing and controlling of the large scale complicated systems such as industrial plants, economic, social and life phenomena. But, in the previous learning algorithm of U.L.N., time delays between the nodes were fixed, in other words, criterion function of U.L.N. was improved by adjusting only parameter variables. In this paper, a new learning algorithm is proposed, where not only parameter variables but also time delays between the nodes can be adjusted. Because time delays are integral numbers, adjustment of time delays can be carried out by a kind of random search procedure which executes intensified and diversified search in a single framework.

• Journal of Communications and Networks
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• 제12권5호
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• pp.499-509
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• 2010

A plethora of transmission control protocol (TCP) congestion control algorithms have been devoted to achieving the ultimate goal of high link utilization and fair bandwidth sharing in high bandwidth-delay product (HBDP) networks. We present a new insight into the TCP congestion control problem; in particular an end-to-end delay-based approach for an HBDP network. Our main focus is to design an end-to-end mechanism that can achieve the goal without the assistance of any network feedback. Without a router's aid in notifying the network load factor of a bottleneck link, we utilize goodput and throughput values in order to estimate the load factor. The obtained load factor affects the congestion window adjustment. The new protocol, which is called TCP-goodput and throughput (GT), adopts the carefully designed inversely-proportional increase multiplicative decrease window control policy. Our protocol is stable and efficient regardless of the link capacity, the number of flows, and the round-trip delay. Simulation results show that TCP-GT achieves high utilization, good fairness, small standing queue size, and no packet loss in an HBDP environment.

• 한국지역사회생활과학회지
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• 제27권2호
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• pp.185-197
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• 2016

This study was conducted to examine the factors affecting the life satisfaction of married female immigrants and Korean husbands. Data for this study were obtained from the National Survey of Multicultural Families conducted in 2012. The study sample consisted of 5,232 couples within the first five years of marriage. Data were evaluated using a paired t-test, K-mean cluster analysis, ANOVA, and ordered logistic regression analysis. The results were as follows: 1) life satisfaction was higher for married female immigrants than for Korean husbands. 2) The general characteristics, acceptance attitude, language acceptance, and social network differed significantly depending on life satisfaction levels. 3) The multicultural acceptance attitude of husbands, ability of married female immigrants to speak Korean, and ability of Korean husbands to speak wives' native languages improved life satisfaction levels. The results of this study can be used to improve the life satisfaction of married female immigrants and Korean husbands.

• 한국멀티미디어학회논문지
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• 제16권11호
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• pp.1261-1271
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• 2013

Zoom tracking involves the automatic adjustment of the focus motor in response to the zoom motor movements for the purpose of keeping an object of interest in focus, and is typically achieved by moving the zoom and focus motors in a zoom lens module so as to follow the so-called "trace curve", which shows the in-focus motor positions versus the zoom motor positions for a specific object distance. Thus, one can simply implement zoom tracking by following the most closest trace curve after all the trace curve data are stored in memory. However, this approach is often prohibitive in practical implementation because of its large memory requirement. Many other zoom tracking methods such as GZT, AZT and etc. have been proposed to avoid large memory requirement but with a deteriorated performance. In this paper, we propose a new zoom tracking method called 'Approximate Feedback Zoom Tracking method (AFZT)' on DM36x-based IP network camera, which does not need large memory by approximating nearby trace curves, but generates better zoom tracking accuracy than GZT or AZT by utilizing focus value as feedback information. Experiments through real implementation shows the proposed zoom tracking method improves the tracking performance and works in real-time.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 제36회 하계학술대회 논문집 D
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• pp.2891-2893
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• 2005

In this paper, we introduce a new category of Self-Organizing Fuzzy Polynomial Neural Networks (SOFPNN) that is based on a genetically optimized multi-layer perceptron with fuzzy polynomial neurons (FPNs) and discuss its comprehensive design methodology involving mechanisms of genetic optimization. The conventional SOFPNN algorithm leads to a tendency to produce overly complex networks as well as a repetitive computation load by the trial and error method and/or the a repetitive parameter adjustment by designer. In order to generate a structurally and parametrically optimized network, such parameters need to be optimal. In this study, in solving the problems with the conventional SOFPNN, we introduce a new design approach of evolutionary optimized SOFPNN. Optimal parameters design available within FPN (viz. the no. of input variables, the order of the polynomial, input variables, and the no. of membership function) lead to structurally and parametrically optimized network which is more flexible as well as simpler architecture than the conventional SOFPNN. In addition, we determine the initial apexes of membership functions by genetic algorithm.

• 한국지능시스템학회논문지
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• 제11권5호
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• pp.367-372
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• 2001

본 논문은 미시공간에서 다수의 로봇들의 자율 이동에 대해 계층적 구조를 가진 퍼지-뉴럴 알고리즘을 제안한다. 이 계층적 알고리즘은 그 하부에 로봇이 목표에 도달하게 하며 주는 퍼지 알고리즘과 주행 중 만날 수 있는 장애물들에 대한 회피를 수행하는 퍼지-뉴럴 알고리즘이 존재하고 상부의 가중치 퍼지 알고리즘은 위의 두 알고리즘에 의한 로봇의 회전각도 와 이동 거리를 합성하여 주위 환경에 대하여 로봇이 지능적인 주행을 수행한 누 있도록 구성되어 있으며 시뮬레이션을 통하여 만족할 만한 결과를 얻을 수 있었다.

• 전자공학회논문지CI
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• 제48권1호
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• pp.33-43
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• 2011

본 논문에서는 IEEE 802.11e에서 전송 흐름을 고려한 능동적 자원할당 방법을 제안한다. IEEE 802.11e에서는 비디오나 음성 데이터의 QoS를 제공하기 위해 우선순위가 높은 노드에게 정해진 시간동안 연속해서 보낼 수 있도록 TXOP 파라메터 값을 정해놓고 있다. 해당 시간동안 연속해서 데이터를 전송하므로써 채널의 점유를 위한 경쟁을 줄임으로써 충돌의 횟수가 줄어들어 빠른 데이터 전송의 장점은 있지만, 해당노드의 채널 상태가 좋지 못한 경우 전체 네트워크의 전송률은 떨어지고 우선순위는 낮지만 채널 상태가 좋은 노드의 경우 기다리는 시간이 길어지는 문제가 발생하게 된다. 이러한 문제점을 해결하기 위해 채널 상태에 따라 TXOP를 조정하여 우선순위는 낮지만 채널 상태가 좋은 노드에게도 점차적으로 할당함으로써 채널을 최대한으로 활용하도록 하였고 자원의 능동적인 할당으로 전송률 향상에 기여하는 알고리듬을 제안하였다.

• 한국측량학회지
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• 제13권1호
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• pp.13-20
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• 1995

수평위치 결정에서 오차해석은 중요하다. 오차해석의 경우 표준오차타원이 정밀도의 척도로써 사용되나, 오차한계의 설정이나 측정치의 합격기준과 상대오차를 비교하는데 한계가 있어, 캐나다나 미국에서는 작업규정 에 95%신뢰타원을 오차한계로 설정하고 있다. 본 연구에서는 수평위치 결정시 신뢰타원을 오차해석에 적용하여 분석하였다. 최소제곱법과 오차해석이론에 대해 검토하였으며 , 컴퓨터 프로그램으로 E.D.M 삼변망에 대해 오차분석을 하였다. 본 연구결과 오차한계의 설정 , 측정치의 합격기준, 상대오차를 비교할 때 95%신뢰타원이 합리적이므로 작업규정에 95％신뢰타원을 도입하는 것이 필요하다. 또한 경제성있는 최적망 설계를 위해 측량망의 예비분석에도 95%신뢰타원이 효과적으로 적용될 수 있다고 사료된다.

• Child Health Nursing Research
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• 제23권2호
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• pp.238-248
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• 2017

Purpose: The main purpose of this study was to explore the adaptation experience of adolescent cancer survivors during and after cancer treatment, and their perceived social support networks. Methods: This study was a qualitative descriptive study using the in-depth interview. Eight adolescent cancer survivors who were diagnosed with cancer between 11 to 18 years old participated in the study. Results: The adaptation experiences of adolescent cancer survivors over time were identified within five categories for during their treatment such as "being catapulted from one's life," "standing at the center of discomfort," "falling behind the line," "accepting the change," "being developed", and another five categories for after the treatment including "being shackled," "encountering the forgotten reality," "overcoming and emerging from the reality," "growing into adulthood," "entering into a new orbit." Participants reported the various members of their social support network and their roles during and after the treatment as well. Conclusion: While adolescent cancer survivors adjusted to their changing situations after the cancer diagnosis, their internalized adaptation, as well as perceived social support from their diverse surrounding network, played significant roles. These findings will become a valuable asset for developing age-appropriate nursing interventions to promote psychosocial adjustment of adolescents with cancer.

• Journal of Electrical Engineering and Technology
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• 제9권2호
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• pp.550-558
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• 2014

Direct Torque controlled induction motor (DTC-IM) drives use stator resistance of the motor for stator flux estimation. So, stator resistance estimation properly is very important for a stable and effective operation of the induction motor. Stator resistance variations because of changing in temperature make DTC operation difficult mainly at low speed. A method based on artificial neural network (ANN) to estimate the stator resistance online of IM for DTC drive is modeled and verified in this paper. To train the neural network a back propagation algorithm is used. Weight adjustment of neural network is done by back propagating the error signal between measured and estimated stator current. An extensive simulation has been carried out in MATLAB/SIMULINK to prove the efficacy of the proposed stator resistance estimator. The simulation & experimental result reveals that proposed method is able to obtain precise torque and flux control at low speed.