• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.4
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• pp.281-292
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• 2016

The proposed scheme is based on the modified perturb and observe (P&O) algorithm combined with the sliding mode technique. A modified P&O algorithm based sliding mode controller is developed to study the effects of partial shade, temperature, and insolation on the performance of maximum power point tracking (MPPT) used in photovoltaic (PV) systems. Under partially shaded conditions and temperature, the energy conversion efficiency of a PV array is very low, leading to significant power losses. Consequently, increasing efficiency by means of MPPT is particularly important. Conventional techniques are easy to implement but produce oscillations at MPP. The proposed method is applied to a model to simulate the performance of the PV system for solar energy usage, which is compared to the conventional methods under non-uniform insolation improving the PV system utilization efficiency and allowing optimization of the system performance. The modified perturb and observe sliding mode controller successfully overcomes the issues presented by non-uniform conditions and tracks the global MPP. Compared to MPPT techniques, the proposed technique is more efficient; it produces less oscillation at MPP in the steady state, and provides more precise tracking.

• Transactions of the Korean Society of Automotive Engineers
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• v.14 no.4
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• pp.49-58
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• 2006

In the respect of the environmental protection viewpoint, $CO_2$ may be one of the most attractive alternative refrigerants for an automotive air-conditioning system. For the development of control algorithm of a $CO_2$ automotive air-conditioning system, characteristics of a $CO_2$ refrigerant should be considered. The high-side pressure of a $CO_2$ system should be controlled in order to improve the system efficiency. In this study, dynamic physical models of a $CO_2$ system were developed and dynamic behaviors of the system were predicted by using these models. Control algorithms of a $CO_2$ system were also developed and the effectiveness of these algorithm was verified by using dynamic models.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.39 no.8
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• pp.7-13
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• 2002

In this paper, we propose an traffic control algorithm for efficient link utilization of ATM-ABR service based on fuzzy logic. The proposed algorithm, controls transmission rates of source according to switch buffer size and input cell tate by using the fuzzy rate . For this method we developed a model and algorithm of fuzzy traffic control method and fuzzy traffic controller which based on ER of VS/VD. For the fuzzy traffic controller, we also designed a membership function, fuzzy control rules, and a max-min inferencing method.

• Proceedings of the Korea Database Society Conference
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• 1999.06a
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• pp.253-260
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• 1999

The recycling cell formation problem means that disposal products me classified into recycling part families using group technology in their end of life phase. Disposal products have the uncertainties of product status by usage influences during product use phase and recycling cells are formed design, process and usage attributes. In order to treat the uncertainties, fuzzy set theory and fuzzy logic-based neural network model are applied to recycling cell formation problem far disposal products. In this paper, a heuristic approach fuzzy ART neural network is suggested. The modified fuzzy ART neural network is shown that it has a great efficiency and give an extension for systematically generating alternative solutions in the recycling cell formation problem. We present the results of this approach applied to disposal refrigerators and the comparison of performances between other algorithms. This paper introduced a procedure which integrates economic and environmental factors into the disassembly of disposal products for recycling in recycling cells. A qualitative method of disassembly analysis is developed and its ai is to improve the efficiency of the disassembly and to generated an optimal disassembly which maximize profits and minimize environmental impact. Three criteria established to reduce the search space and facilitate recycling opportunities.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.7 no.4
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• pp.256-261
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• 2007

Electroencephalographic(EEG) is used to record activities of human brain in the area of psychology for many years. As technology developed, neural basis of functional areas of emotion processing is revealed gradually. So we measure fundamental areas of human brain that controls emotion of human by using EEG. Hands gestures such as shaking and head gesture such as nodding are often used as human body languages for communication with each other, and their recognition is important that it is a useful communication medium between human and computers. Research methods about gesture recognition are used of computer vision. Many researchers study Emotion Recognition method which uses one of EEG signals and Gestures in the existing research. In this paper, we use together EEG signals and Gestures for Emotion Recognition of human. And we select the driver emotion as a specific target. The experimental result shows that using of both EEG signals and gestures gets high recognition rates better than using EEG signals or gestures. Both EEG signals and gestures use Interactive Feature Selection(IFS) for the feature selection whose method is based on the reinforcement learning.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.13 no.1
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• pp.50-58
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• 2013

Estimating a driver's head pose is an important task in driver-assistance systems because it can provide information about where a driver is looking, thereby giving useful cues about the status of the driver (i.e., paying proper attention, fatigued, etc.). This study proposes a system for estimating the head pose using monocular images, which includes a novel use of backprojection. The system can use a single image to estimate a driver's head pose at a particular time stamp, or an image sequence to support the analysis of a driver's status. Using our proposed system, we compared two previous pose estimation approaches. We introduced an approach for providing ground-truth reference data using a mannequin model. Our experimental results demonstrate that the proposed system provides relatively accurate estimations of the yaw, tilt, and roll angle. The results also show that one of the pose estimation approaches (perspective-n-point, PnP) provided a consistently better estimate compared to the other (pose from orthography and scaling with iterations, POSIT) using our proposed system.

• ETRI Journal
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• v.36 no.1
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• pp.89-98
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• 2014

The integration of digital circuits has a tight relation with the scaling down of silicon technology. The continuous scaling down of the feature size of CMOS devices enters the nanoscale, which results in such destructive effects as short channel effects. Consequently, efforts to replace silicon technology with efficient substitutes have been made. The carbon nanotube field-effect transistor (CNTFET) is one of the most promising replacements for this purpose because of its essential characteristics. Various digital CNTFET-based circuits, such as standard logic cells, have been designed and the results demonstrate improvements in the delay and energy consumption of these circuits. In this paper, a new CNTFET-based 5-input XOR gate based on a novel design method is proposed and simulated using the HSPICE tool based on the compact SPICE model for the CNTFET at the 32-nm technology node. The proposed method leads to improvements in performance and device count compared to the conventional CMOS-style design.

• Journal of Elementary Mathematics Education in Korea
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• v.15 no.2
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• pp.463-485
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• 2011

This study was to investigate the effects of mathematical history-based mathematics teaching on mathematical communication and attitudes of elementary students, through selecting mathematical history content to apply to elementary mathematics and devising an instruction model to use effectively. For this purpose, while the experimental group received instruction using mathematical history and the comparative group lecture-based instruction using the common textbook, both quantitative and qualitative methods were employed to analyze gathered data. To conclusion, first, instructions using mathematical history were helpful for increasing the student's participation in communication, and secondly helped the students justify their opinions to others with mathematical logic.

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.5
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• pp.35-43
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• 2014

The automobile industry requires technological innovations to reduce fuel consumption with the public interest in environmental conservation in recent years. Thus, the hybrid system is applied not only to passenger cars but also commercial vehicles. The purpose of this paper is to develop engine ECU_ILS to develop commercial hybrid vehicles. In order to develop the engine and vehicle, the dynamometer and exhaust gas analyzer is needed. However, a lot of time and cost are required. In contrast, the model-based development environment that can be applied to a variety of test conditions can reduce development time. Therefore, a HILS system environment that can consider the behavior of actual vehicles for evaluation of the control logic, fuel consumption and exhaust gas is required. This engine ECU_ILS system was developed in this study, can analyze parameter such as the fuel injection rate, fuel injection time, fuel consumption and exhaust gas like the actual vehicle test using map data. Also, this system is expected to be able to analyze the characteristic of vehicle behavior and the development of peripheral device in relation to engine and vehicles. This HILS system can be used to develop control strategies of commercial hybrid vehicle systems in the future.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1113-1114
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• 2011

This paper is proposed design of high performance controller of SynRM drive using FNN and NNC. Also, This paper is proposed of designing fuzzy neural network controller(FNNC) which adopts the fuzzy logic to the artificial neural network(ANN). FNNC combines the capability of fuzzy reasoning in handling uncertain information and the capability of neural network in learning from processes. This controller is controlled speed using FNNC and model reference adaptive fuzzy control(MFC), and estimation of speed using ANN. The performance of proposed controller was demonstrated through response results. The results confirm that the proposed controller is high performance and robust under the variation of load torque and parameters.