• 한국환경성돌연변이발암원학회:학술대회논문집
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• 한국환경성돌연변이발암원학회 2003년도 추계학술대회
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• pp.181-181
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• 2003

• 제어로봇시스템학회논문지
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• 제6권6호
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• pp.441-446
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• 2000

This paper presents an approach for the prediction of optimal heating load using a diagonal recurrent neural networks(DRNN) and data base system of outdoor temperature. In the DRNN, a dynamic backpropagation(DBP) with delta-bar-delta teaming method is used to train an optimal heating load identifier. And the data base system is utilized for outdoor temperature prediction. Compared to other kinds of methods, the proposed method gives better prediction performance of heating load. Also a hardware for the controller is developed using a microprocessor. The experimental results show that prediction enhancement for heating load can be achieved with the proposed method regardless of the its inherent nonlinearity and large time constant.

• Journal of information and communication convergence engineering
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• 제9권3호
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• pp.341-346
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• 2011

Wireless sensor networks (WSNs) are formed by a great quantity of sensor nodes, which are consisted of battery-powered and some tiny devices. In WSN, both efficient energy management and Quality of Service (QoS) are important issues for some applications. Real-time services are usually employed to satisfy QoS requirements in critical environment. This paper proposes a real-time MAC (Medium Access Control) protocol with extended backoff scheme for wireless sensor networks. The basic idea of the proposed protocol employs (m,k)-firm constraint scheduling which is to adjust the contention window (CW) around the optimal value for decreasing the dynamic failure and reducing collisions DBP (Distant Based Priority). In the proposed protocol, the scheduling algorithm dynamically assigns uniform transmitting opportunities to each node. Numerical results reveal the effect of the proposed backoff mechanism.

• 한국안전학회지
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• 제9권1호
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• pp.68-75
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• 1994

The cetylpyridium ion-selective electrode were developed by dibenzo-18-crown-6 for auto control of the chemical plants. The effect of content of active material and the membrane thickness on the response characteristics of electrode such as the linear reponse range, the detection limit, and Nemstian slope of the electrod, were studied. The electrode characteristics was better with decreasing the content of active material above the optimum content, but became worse below these. DBP was best as a plasticizer, The effect of the membrane thickness on the electrode characteristics was improved with decreasing the membrane thickness, but below the optimum membrane thickness the electrode exhibited an inverse trend.

• 한국안전학회지
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• 제5권2호
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• pp.40-49
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• 1990

For the determination of polluant NOx in ambient air, nitrate ion-selective electrode(ISE) was made. To comparison of NOx in each method, the nitrate-ISE, NEBA, Orion electrode were used to determinee NOx in ambient air. In this work, the concentration of NOx in ambient air was average 0.06ppm. The results were good agreement with those obtained by each method within a relative error of 3％, Absorbing efficiency of nitrogen oxides in ambient air was good for Alkali solution. The determination of nitrogen oxides in ambient air using the Aliquat 336N-PVC membrane electrode was one of the useful method. The best characteristics of the Aliquat 336N-PVC me,mbrane electrode were obtained with the ion-exchanger concentration level of 6.5-9.1 percent by weight. The optimal membrane composition, was 9.09wt.％ of ion-exchanger, 30.95wt.％ of PVC, 60.6wt.％ of plasticizer (DBP), and 0.5mm of thickness. Under the above condition, the electrode approached the Nernstian slope most closely, and the linear response ranges produced the best results.

• 대한약학회:학술대회논문집
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• 대한약학회 2003년도 Proceedings of the Convention of the Pharmaceutical Society of Korea Vol.1
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• pp.187-187
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• 2003

The aims of present study were to compare the effects of in utero exposure to diethylstibestrol (DES), di(n-butyl)phthalate (DBP) and flutamide on the development of reproductive organs and to investigate the specific mechanisms of these abnormalities in the male reproductive system.During gestation days 10-19, pregnant Sparague-Dawley (SD) female rats were administered orally with corn oil (control), DES (25, 50, or 100 ${\mu}$/kg/day), (omitted)

• 대한약학회:학술대회논문집
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• 대한약학회 2003년도 Proceedings of the Convention of the Pharmaceutical Society of Korea Vol.1
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• pp.318-318
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• 2003

The current study was performed to observe the effects of Panax ginseng (PG) and P. quinquefolium (PQ) on hemodynamics such as blood flow rate (BF), blood flow velocity (BV), heart rate (HR), systolic blood pressure (SBP), and diastolic blood pressure (DBP) and body temperature (BT) in healthy young men. This is a randomized, single-blind study observed during 6 hrs after orally single administration of PG and PQ groups. (omitted)

• Bulletin of the Korean Chemical Society
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• 제29권1호
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• pp.165-167
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• 2008

The performances of tetracycline based cation selective polymeric membrane electrodes of many sets with different plasticizers were investigated as the selectivity of ion-selective electrodes and optodes are greatly influenced by membrane solvent and also controlled by plasticizers. The membrane 1 with Bis(2-ethylhexyl) sebacate (DOS) and additive shows good potentiometric performance toward Ca2+ (slope: 27.8 mV per decade; DL: -4.52) including selectivity. Contrastingly, membrane 4 with Dibutyl phthalate (DBP) shows near-Nernstian response, it has also shown the best measuring range and detection limit for Ca2+ (29.5 mV and -5.10) and Mg2+ (24.4 mV and -5.04) and the least selectivity has been also observed between Ca2+ and Mg2+. When the membrane 1 and 4 were used together to flow system, we could determine the concentration of Ca2+ and Mg2+, simultaneously.

• 대한전기학회논문지:전력기술부문A
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• 제48권10호
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• pp.1231-1238
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• 1999

This paper presents an approach for the optimal heating load Identification using Diagonal Recurrent Neural Networks(DRNN). In this paper, the DRNN captures the dynamic nature of a system and since it is not fully connected, training is much faster than a fully connected recurrent neural network. The architecture of DRNN is a modified model of the fully connected recurrent neural network with one hidden layer. The hidden layer is comprised of self-recurrent neurons, each feeding its output only into itself. In this study, A dynamic backpropagation (DBP) with delta-bar-delta learning method is used to train an optimal heating load identifier. Delta-bar-delta learning method is an empirical method to adapt the learning rate gradually during the training period in order to improve accuracy in a short time. The simulation results based on experimental data show that the proposed model is superior to the other methods in most cases, in regard of not only learning speed but also identification accuracy.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 B
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• pp.690-692
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• 1999

In this thesis, We implement the controller system only using the neural network to identify the plant characteristics with keeping the PID controller structure. The neural network has learned by the adaptive learning rates that has suggested by Chao-Chee Ku and the DBP algorithm. We proposed the on-line tuning algorithm about the unknown plant using the adaptive tuning technique. As a result of executing the parameters has tuned from the initial value to more suitable ones and the output of the Plant has improved and also it is appeared that the convergence is guaranteed.