• Journal of the Korean Society for Geothermal and Hydrothermal Energy
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• v.16 no.4
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• pp.31-38
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• 2020

The investment in the technology of using a combined heat source is insufficient, which utilizes the advantages of various heat sources to maximize the potential energy and at the same time increases the performance of the heat pump. In this study, as basic data for the development of a high-efficiency hybrid heat pump system that actively connects and uses various heat sources, simulations were conducted for the heat pumps in two cases where geothermal and hydrothermal heat were applied respectively. In May, COP increased by about 27.3% compared to geothermal heat. In February, the COP percentage decrease of hydrothermal heat compared to geothermal heat is -6.9%. In May, total energy consumption can be reduced by 21.1% when hydrothermal is applied compared to geothermal heat. In February, the total energy consumption increases by 3.4%.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.43 no.1 s.307
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• pp.31-38
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• 2006

In this paper, we consider one-step-ahead control of waveform parameters (pulse amplitudes and lengths, and FM sweep rate) as well as detection thresholds for optimal range and range-rate tracking in clutter. The optimal control of the combined parameter set minimizes a tracking performance index under a set of parameter constraints. The performance index includes the probability of track loss and a function of estimation error covariances. The track loss probability and the error covariance are predicted using a hybrid conditional average algorithm The effect of the false alarms and clutter interference is taken into account in the prediction. Tracking performance of the one-step-ahead control is presented for several examples and compared with a control strategy heuristically derived from a finite horizon optimization.

• 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.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.10
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• pp.1293-1302
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• 1999

In this paper, an on-line process scheme is presented for implementation of a intelligent on-line modeling of nonlinear complex system. The proposed on-line process scheme is composed of FNN-based model algorithm and PLC-based simulator, Here, an adaptive fuzzy-neural networks and HCM(Hard C-Means) clustering method are used as an intelligent identification algorithm for on-line modeling. The adaptive fuzzy-neural networks consists of two distinct modifiable sturctures such as the premise and the consequence part. The parameters of two structures are adapted by a combined hybrid learning algorithm of gradient decent method and least square method. Also we design an interface S/W between PLC(Proguammable Logic Controller) and main PC computer, and construct a monitoring and control simulator for real process system. Accordingly the on-line identification algorithm and interface S/W are used to obtain the on-line FNN model structure and to accomplish the on-line modeling. And using some I/O data gathered partly in the field(plant), computer simulation is carried out to evaluate the performance of FNN model structure generated by the on-line identification algorithm. This simulation results show that the proposed technique can produce the optimal fuzzy model with higher accuracy and feasibility than other works achieved previously.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.372-372
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• 2000

In this paper, we propose Neuro Fuzzy Polynomial Networks(NFPN) based on Polynomial Neural Network(PNN) and Neuro-Fuzzy(NF) for model identification of complex and nonlinear systems. The proposed NFPN is generated from the mutually combined structure of both NF and PNN. The one and the other are considered as the premise part and consequence part of NFPN structure respectively. As the premise part of NFPN, NF uses both the simplified fuzzy inference as fuzzy inference method and error back-propagation algorithm as learning rule. The parameters such as parameters of membership functions, learning rates and momentum coefficients are adjusted using genetic algorithms. As the consequence part of NFPN, PNN is based on Group Method of Data Handling(GMDH) method and its structure is similar to Neural Networks. But the structure of PNN is not fixed like in conventional Neural Networks and self-organizing networks that can be generated. NFPN is available effectively for multi-input variables and high-order polynomial according to the combination of NF with PNN. Accordingly it is possible to consider the nonlinearity characteristics of process and to get better output performance with superb predictive ability. In order to evaluate the performance of proposed models, we use the nonlinear function. The results show that the proposed FPNN can produce the model with higher accuracy and more robustness than any other method presented previously.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.3 no.2
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• pp.209-218
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• 2009

In a wireless sensor network(WSN) each sensor node deals with numerous sensing data elements. For the sake of energy efficiency and network lifetime, sensing data must be handled effectively. A technique used for this is data aggregation. Sending/receiving data involves numerous steps such as MAC layer control packet handshakes and route path setup, and these steps consume energy. Because these steps are involved in all data communication, the total cost increases are related to the counts of data sent/received. Therefore, many studies have proposed sending combined data, which is known as data aggregation. Very effective methods to aggregate sensing data have been suggested, but there is no means of deciding how long the sensor node should wait for aggregation. This is a very important issue, because the wait time affects the total communication cost and data reliability. There are two types of data aggregation; the data counting method and the time waiting method. However, each has weaknesses in terms of the delay. A hybrid method can be adopted to alleviate these problems. But, it cannot provide an optimal point of aggregation. In this paper, we suggest a stochastic-based data aggregation scheme, which provides the cost(in terms of communication and delay) optimal aggregation point. We present numerical analysis and results.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.50 no.12
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• pp.584-590
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• 2001

This paper presents a windows program package for solving security constrained OPF in interconnected Power systems, which is based on the combined application of evolutionary programming(EP) and sequential quadratic programming(SQP). The objective functions are the minimization of generation fuel costs and system power losses. The control variables are the active power of the generating units, the voltage magnitude of the generator, transformer tap settings and SYC setting. The state variables are the bus voltage magnitude, the reactive power of the generating unit, line flows and the tie line flow In OPF considering security, the outages are selected by contingency ranking method. The resulting optimal operating point has to be feasible after outages such as any single line outage(respect of voltage magnitude, reactive power generation and power flow limits). The OPF package proposed is applied to IEEE 14 buses and 10 machines 39 buses model system.

• Horticultural Science & Technology
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• v.35 no.4
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• pp.418-430
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• 2017

The objective of this study was to understand the combined effect of shading treatment and harvest time on pungency, ascorbic acid content, market-quality pepper yield, and photosynthetic activity in a yellow 'Star Flame' and 'Fire Flame' F1 hybrid pepper cultivar (Capsicum annuum). Plants were cultivated in a greenhouse under white, red, and green shading nets and compared to those grown under unshaded control conditions. The ascorbic acid and pungency parameters were analyzed by high-performance liquid chromatographic methods. Ascorbic acid, a compound of high nutritive value in pepper, was highest in fruits gathered during the first summer harvest in both hybrids. The ascorbic acid content was found to be further increased in fruits from plants grown under white net shading in both 'Star Flame' and 'Fire Flame'. Total capsaicinoid contents in 'Star Flame' were influenced by the interaction of shading treatment and harvest time (p = 0.004), with the lowest amounts ($241.2-251.5mg{\cdot}kg^{-1}$ fresh weight) resulting from white and red shading treatments at the early autumn harvest. In 'Fire Flame', both shading treatment (p = 0.009) and harvest time (p < 0.001) affected total capsaicinoid contents. We observed significantly higher total capsaicinoid contents in control fruits compared to that resulting from red and green shading treatments at the second harvest, and that resulting from red shading treatment at the third harvest. Analysis of photosynthetic activity revealed a significant and negative correlation between Fv/Fm values and total capsaicinoid contents in both hybrids (p < 0.001). Based on the obtained results, the harvest of peppers during summer should be promoted to produce fruits with high pungency.

• Journal of the Optical Society of Korea
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• v.20 no.4
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• pp.488-499
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• 2016

We present a design and optical simulation of a cost-effective hybrid daylighting/LED system composed of mixing sunlight and light-emitting diode (LED) illumination powered by renewable solar energy for indoor lighting. In this approach, the sunlight collected by the concentrator is split into visible and non-visible rays by a beam splitter. The proposed sunlight collector consists of a Fresnel lens array. The non-visible rays are absorbed by the solar photovoltaic devices to provide electrical power for the LEDs. The visible rays passing through the beam splitters are coupled to a stepped thickness waveguide (STW) by tilted mirrors and confined by total internal reflection (TIR). LEDs are integrated at the end of the STW to improve the lighting quality. LEDs’ light and sunlight are mixed in the waveguide and they are coupled into an optical fiber bundle for indoor illumination. An optical sensor and lighting control system are used to control the LED light flow to ensure that the total output flux for indoor lighting is a fixed value when the sunlight is inadequate. The daylighting capacity was modeled and simulated with a commercial ray tracing software (Lighttools^TM). Results show that the system can achieve 63.8% optical efficiency at geometrical concentration ratio of 630. A required accuracy of sun tracking system achieved more than ±0.5^o . Therefore, our results provide an important breakthrough for the commercialization of large scale optical fiber daylighting systems that are faced with challenges related to high costs.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.2
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• pp.535-538
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• 2005

Wireless LANs based on the IEEE 802.11 standard are widely spread for use nowadays. Traffic which are conveyed over the WLANs change rapidly from normal data such a Email and Web pages, to multimedia data of high resolution video and voice. To meet QoS (Quality of Service) required by these multimedia traffic, the IEEE 802 committee recently has developed a new standard, IEEE 802.11e. IEEe 802.11.e contains two MAC mechanisms for providing QoS: EDCA(Enhanced Distributed Channel Access) and HCCA (HCF Controlled Channel Access). Using these standardized MAC mechanisms as a building platform, various admission control mechanisms can be combined to offer QoS gurantees for multimedia traffic. This paper surveys these research efforts.