• The Transactions of the Korean Institute of Electrical Engineers C
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• v.54 no.5
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• pp.232-237
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• 2005

In this paper, we fabricated $CO_2$ gas sensor based on the MEMS infrared sensor and characterized its electrical and $CO_2$-sensing properties. The fabricated $CO_2$ gas sensor by MEMS technique has many advanges over NDIR(nondispersive) $CO_2$ sensor such as monolithic fabrication, very high selectivity on $CO_2$, low power consumption and compact system. Microbolometer by surface micromachining was fabricated for gas detector and $CO_2$ filter chip by bulk micromachining was fabricated for signal referencing. By using the proposed and fabricated gas sensor, we are expected to measure $CO_2$ concentration more accurately with high reliability.

• Journal of Mechanical Science and Technology
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• v.19 no.11
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• pp.1998-2006
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• 2005

The lane departure avoidance systems have been considered promising to assist human drivers in AVCS (Advanced Vehicle Control System). In this paper, a lane departure monitoring and control system is developed and evaluated in the hardware-in-the-loop simulations. This system consists of lane sensing, lane departure monitoring and active steering control subsystems. The road image is obtained based on a vision sensor and the lane parameters are estimated using image processing and Kalman Filter technique. The active steering controller for avoiding the lane departure is designed based on the lane departure metric. The proposed lane departure avoidance system is realized in a steering HILS (hardware-in-the-loop simulation) tool and its performance is evaluated with a driver in the loop.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.244-247
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• 1995

A technique is presented for evaluating spinal deformity of a human back by extracting a spinal line based on 3-D topograpic reconstruction of the back from its moire image. A given moire image is differentiatedby DOG filter to extract moire stripes. The stripes are then assigned labels and the labels are interpolated by the Lagrange polynomial to yield the undulation of the back which gives a relative 3-D shape of the back. A valley is searched on the undulation near the middle part of the back and the valley line is finally extracted as an approximated spinal line. The mean differenceand the variance between the spinal line and the middle line are calculated and reported. Experiment is performed employing real moire images ofjunior-high school students' backs and some of the results are shown with discussion.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.2
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• pp.28-34
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• 1994

In this paper, a new time-domain parameter extraction method for speech recognition is proposed. The suggested emthod is based on the fact that the local peak-to-peak interval, i.e., the interval between maxima and minima of speech waveform is closely related to the frequency component of the speech signal. The parameterization is achieved by a sort of filter bank technique in the time domain. To test the proposed parameter extraction emthod, an isolated word recognizer based on Vector Quantization and Hidden Markov Model was constructed. As a test material, 22 words spoken by ten males were used and the recognition rate of 92.9% was obtained. This result leads to the conclusion that the new parameter extraction method can be used for speech recognition system. Since the proposed method is processed in the time domain, the real-time parameter extraction can be implemented in the class of personal computer equipped onlu with an A/D converter without any DSP board.

• The Journal of Korea Robotics Society
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• v.9 no.2
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• pp.117-123
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• 2014

Localization is one of the essential tasks necessary to achieve autonomous navigation of a mobile robot. One such localization technique, Monte Carlo Localization (MCL) is often applied to a digital surface model. However, there are differences between range data from laser rangefinders and the data predicted using a map. In this study, commonly observed from air and ground (COAG) features and candidate selection based on the shape of sensor data are incorporated to improve localization accuracy. COAG features are used to classify points consistent with both the range sensor data and the predicted data, and the sample candidates are classified according to their shape constructed from sensor data. Comparisons of local tracking and global localization accuracy show the improved accuracy of the proposed method over conventional methods.

• Journal of Information Processing Systems
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• v.16 no.5
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• pp.1183-1195
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• 2020

Visual saliency detection is an essential task because it is an important part of various vision-based applications. There are many techniques for saliency detection in color images. However, the number of methods for saliency detection in infrared images is limited. In this paper, we introduce a simple approach for saliency detection in infrared images based on the thresholding technique. The input image is thresholded into several Boolean maps, and an initial saliency map is calculated as a weighted sum of the created Boolean maps. The initial map is further refined by using thresholding, morphology operation, and a Gaussian filter to produce the final, high-quality saliency map. The experiment showed that the proposed method has high performance when applied to real-life data.

• Journal of Aerospace System Engineering
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• v.4 no.4
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• pp.18-27
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• 2010

Quadrotor is an aircraft which is possible in Vertical Take-off and Landing(VTOL). This aircraft can not only be created as an Unmanned Aerial Vehicle(UAV), but also can be easily used in various fields because of its simplicity of construction. This study is mainly conducted with two main purposes. The first goal is designing the quadrotor focusing on the lightweight and protecting the airframe. The second purpose is stabilizing the quadrotor's attitude by using the PID controller. MATLAB simulation is performed for obtaining PID gain based on equations of motion. We used the compensation filter technique for the calibration of sensor data. PID gain has been drawn out based on the MATLAB simulation. The efficiency of the attitude control is improved by calibration of sensor data.

• Proceedings of the KIPE Conference
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• 2005.07a
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• pp.23-26
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• 2005

This paper describes the design, construction and implementation of matrix converter based on space vector modulation technique. The matrix converter provides sinusoidal input and output wave forms, bidirectional power flow, controllable input power factor and a compact design, compared to the VSI with diode rectification stage at the input. The implemented prototype of matrix converter is built using the exclusive IGBT module and has an input filter, overvoltage protection circuit and commutation means for overcoming practical issues. The good results tested using an induction motor are also presented.

• Journal of Power Electronics
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• v.12 no.5
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• pp.830-841
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• 2012

Active power filters (APF) can be employed for harmonic compensation in power systems. In this paper, a fuzzy based method is proposed for identification of probable APF nodes of a radial distribution system. The modified adaptive particle swarm optimization (MAPSO) technique is used for final selection of the APFs size. A combination of Fuzzy-MAPSO method is implemented to determine the optimal allocation and size of APFs. New fuzzy membership functions are formulated where the harmonic current membership is an exponential function of the nodal injecting harmonic current. Harmonic voltage membership has been formulated as a function of the node harmonic voltage. The product operator shows better performance than the AND operator because all harmonics are considered in computing membership function. For evaluating the proposed method, it has been applied to the 5-bus and 18-bus test systems, respectively, which the results appear satisfactorily. The proposed membership functions are new at the APF placement problem so that weighting factors can be changed proportional to objective function.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2085-2087
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• 2003

A new interacting multiple model (IMM) method based on intelligent input estimation (IIE) is proposed for tracking a maneuvering target. In the proposed method, the acceleration level of each sub-filter is determined by IIE using the fuzzy system, which is optimized by the genetic algorithm (GA). The tracking performance of the proposed method is compared with those of the input estimation (IE) technique and the adaptive interacting multiple model (AIMM) method in computer simulations.