• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.870-876
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• 1993

This paper presents a binary clustering network (BCN) and a heuristic algorithm to detect pitch for recognition of keywords in continuous speech. In order to classify nonlinear patterns, BCN separates patterns into binary clusters hierarchically and links same patterns at root level by using the supervised learning and the unsupervised learning. BCN has many desirable properties such as flexibility of dynamic structure, high classification accuracy, short learning time, and short recall time. Pitch Detection algorithm is a heuristic model that can solve the difficulties such as scaling invariance, time warping, time-shift invariance, and redundance. This recognition algorithm has shown recognition rates as high as 95% for speaker-dependent as well as multispeaker-dependent tests.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.97-97
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• 2000

In this paper, a signal processing algorithm for software GPS receiver is proposed. The signal processor takes snapshot of the sampled If signal from the RF section of the GPS receiver. All the processing for code and carrier tracking and correlation are implemented using the digital signal processing techniques. In order to achieve fast code acquisition, correlation of the incoming GPS signal is performed using the FFT method, After code acquisition, to reduce the Doppler shift effect and increase the accuracy, the interpolation or the tracking are performed. The performance of the proposed processing algorithm is first evaluated using matlab/simulink. A signal acquisition board for sampling and logging GPS IF signal form the Mitel GPS RF chip set is constructed. In order to analyze the performance of the designed algorithm the experiments are performed and the results are analyzed.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.71.1-71
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• 2001

In this paper, an improved method of environment map building and a region search algorithm for mobile robot are presented. For the environment map building of mobile robot, measurement data of ultrasonic sensors and certainty grid representation is usually used. In this case, inaccuracies due to the uncertainty of ultrasonic data are included in the map. In order to solve this problem, an environment map building method using a Bayesian model was proposed previously[5]. In this study, we present an improved method of probability map building that uses infrared sensors and shift division Gaussian probability distribution with the existing Bayesian update method using ultrasonic sensors. Also, a region search algorithm for ...

• Journal of the Korea Society of Computer and Information
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• v.7 no.1
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• pp.174-183
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• 2002

In this paper a control chart pattern recognition methodology based on the back propagation algorithm and Multi layer perceptron, a neural computing theory, is presented. This pattern recognition algorithm, suitable for real time statistical process control. evaluates observations routinely collected for control charting to determine whether a Pattern, such as a cycle. trend or shift, which is exists in the data. This approach is promising because of its flexible training and high speed computation with low-end workstation. The artificial neural network methodology is developed utilizing the delta learning rule, sigmoid activation function with two hidden layers. In a computer integrated manufacturing environment, the operator need not routinely monitor the control chart but, rather, can be alerted to patterns by a computer signal generated by the proposed system.

• International Journal of Control, Automation, and Systems
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• v.4 no.5
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• pp.637-644
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• 2006

Biomedical image is often complex. An applied image analysis system should deal with the images which are of quite low quality and are challenging to segment. This paper presents a framework for color cell image segmentation by learning and classification online. It is a robust two-stage scheme using kernel method and watershed transform. In first stage, a two-class SVM is employed to discriminate the pixels of object from background; where the SVM is trained on the data which has been analyzed using the mean shift procedure. A real-time training strategy is also developed for SVM. In second stage, as the post-processing, local watershed transform is used to separate clustering cells. Comparison with the SSF (Scale space filter) and classical watershed-based algorithm (those are often employed for cell image segmentation) is given. Experimental results demonstrate that the new method is more accurate and robust than compared methods.

• Korean Management Science Review
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• v.30 no.1
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• pp.1-14
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• 2013

We conduct the future studies suggested by Park and Seo [3]. They considered a seat inventory control problem in which flights depart sequentially during a similar time-interval and passengers purchase available seats depending on individual customer choice behavior. Customer choice behavior can lead to one among a horizontal shift, a diversion-up, and a booking loss when a desired fare class is unavailable. We investigate how seat availability calculation method, booking limit control mechanism, seat inventory capacity, number of booking class, type of seat demand influence on revenues in an airline industry through thorough computer simulation experiments.

• Journal of Biomedical Engineering Research
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• v.32 no.1
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• pp.7-14
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• 2011

This study suggested an optimized algorithm for detecting the loss of balance(LOB) in the seated position. And the sensitivity analysis was performed in order to identify the role of each design variable in the algorithm. The LOB algorithm consisted of data processing of measured signals, an internal model of the central nervous system and a control error anomaly(CEA) detector. This study optimized design variables of a CEA detector to obtain improved values of the success rate(SR) of detecting the LOB and the margin time(MT) provided for preventing the falling. Nine healthy adult volunteers were involved in the experiments. All the subjects were asked to balance their body in a predescribed seated posture with the rear legs of a four-legged wooden chair. The ground reaction force from the right leg was measured from the force plate while the accelerations of the chair and the head were measured from a couple of piezoelectric accelerometers. The measured data were processed to predict the LOB using a detection algorithm. Variables S2, h2 and hd are related to the detector: S2 represents a data selecting window, h2 a time shift and hd an operating period of the LOB detection algorithm. S2 was varied from 0.1 to 10 sec with an increment of 0.1 sec, and both h2 and hd were varied from 0.01 to 1.0 sec with an increment of 0.01 sec. It was found that the SR and MT were increased by up to 9.7% and 0.497 sec comparing with the previously published case when the values of S2, h2 and hd were set to 4.5, 0.3 and 0.2 sec, respectively. Also the results of sensitivity analysis showed that S2 and h2 had considerable influence on the SR while these variables were not so sensitive to the MT.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.5
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• pp.462-466
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• 2007

This paper proposes an automatic bandwidth control method for the performance improvement of Binary Amplitude Shift Keying (BASK) system for Giga-Bit Modem in millimeter band. In order to improve the performance of the BASK system with a fixed bandwidth, the proposed method is to adjust a bandwidth of low pass filter in receiver using the fuzzy system. The BASK system consists of a high speed shutter of the transmitter and a counter and a repeater of receiver. The repeater consists of four stage converters, and a converter is constructed with a low pass filter and a limiter. The inputs to the fuzzy system are the reminder and integral of remainder of counter, and output is a bandwidth. We used a Viterbi algorithm to find the optimum detection from the output of the counter. Simulation results showed that the proposed system improves the performance compared to the fixed bandwidth.

• Proceedings of the KIPE Conference
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• 2001.07a
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• pp.356-359
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• 2001

In this paper, the new control algorithm is proposed that compensates instantaneously the active and reactive components of the input currents by the synchronous d,q axis conversion of a single-phase current in controlling the single-phase AC/DC parallel converters for a high speed train. The leakage inductance of a transformer was used as a boost inductance and the ripple of a transformer's primary current was reduced considerably by the parallel operation of the two converters with a proper switching phase-shift. The stable and fast control response characteristic is certificated by a simulation.

• The Transactions of the Korean Institute of Power Electronics
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• v.27 no.1
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• pp.40-47
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• 2022

At present, the low-voltage, high-current type power supply is mainly used for effective sterilization in the ballast water treatment system. Research on PSFB converters without output capacitors has been ongoing. Such converters effectively treat ballast water without a separate disinfectant through electric pulses by applying a pulse-type power to the output electrode without an output capacitor. However, in the case of the pulse-type electrolysis treatment method, voltage overshoot can occur due to abrupt voltage fluctuations when the load changes, resulting in circuit reliability problems because of the output capacitorless system. Therefore, a new voltage control algorithm is required. In this paper, we will discuss voltage control for pulsed electrolysis topology without an output capacitor. The proposed voltage control method has been verified using Simulation and experiment. The usefulness of the proposed control method has been proven by the experimental results.