• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.3
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• pp.136-142
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• 2014

Distinct features in heart rate signals during the driver's wake and sleep states could provide an initiative for the development of a safe driving systems such as drowsiness detecting sensor in a smart wheel. We measured ECG from health subjects ($23.5{\pm}2.5$ in age) during the wake and drowsiness states. The proposed method is able to detect R waves and R-R interval calculation in the ECG even when the signal includes in abnormal signals. Heart rate variability(HRV) was investigated for the time domain and frequency domains. The STD HR(0.029), NN50(0.044) and VLF power(0.0018) of the RR interval series of the subjects were significantly different from those of the control group (p < 0.05). In conclusion, there are changes in heart rate from wake to drowsiness that are potentially to be detected. The results in our study could be useful for the development of drowsiness detection sensors for effective real-time monitoring.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.6
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• pp.519-526
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• 2013

ECG signal has the feature that is repeated in a cycle of P, Q, R, S, and T waves and is sampled at a high sampling frequency in general. By using the feature of periodic ECG signals, maximizing compression efficiency while minimizing the loss of important information for diagnosis is required. However, the periodic characteristics of such amplitude and period is not constant by measuring time and patients. Even though measured at the same time, the patient's characteristics display different periodic intervals. In this paper, an adaptive multi-level coding is provided by coding adaptively the dominant and non-dominant signal interval of the ECG signal. The proposed method can maximize the compression efficiency by using a multi-level code that applies different compression ratios considering information loss associated with the dominant signal intervals and non-dominant signal intervals. For the case of long time measurement, this method has a merit of maximizing compression ratio compared with existing compression methods that do not use the periodicity of the ECG signal and for the lossless compression coding of non-dominant signal intervals, the method has an advantage that can be stored without loss of information. The effectiveness of the ECG signal compression is proved throughout the experiment on ECG signal of MIT-BIH arrhythmia database.

• Journal of the Korean Society of Laryngology, Phoniatrics and Logopedics
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• v.5 no.1
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• pp.38-43
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• 1994

Though normal vocal cords show regular vibration, pathologic vocal cords show irregularity between peaks. Jitter means fluctuation in the time interval between peaks, and Shimmer means cycle to cycle variation in the amplitude of the peaks. We investigated the vocal vibration of Korean normal persons objectively. The fundamental frequency, Jitter, Shimmer and SNR(signal to noise ratio) of normal persons were compared with that of vocal Polyp Patients with CSpeech Program for the possibility of distinguishing the pathologic vocal vibration from normal. The results were as follows ; Comparing the fundamental frequency of vocal Polyp Patients with normal persons, great change was noted only in female cases. But the Jitter and Shimmer of vocal polyp patients were greater than normal significantly in both male and female cases. SNR was lower than normal in vocal polyp patients. In the conclusion, fundamental frequency, Jitter, Shimmer and SNR might be meaningful parameters distinguisuing pathologic vibration from normal.

• Science of Emotion and Sensibility
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• v.4 no.1
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• pp.61-67
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• 2001

This paper described the effect of subjective approach in case of the human sensibility experiments. The procedure is proceeded subjectively. Human faces are selected as the image presentation media. Pleasant and unpleasant images are selected directly by examiner, And also the image presentation system, which is executed with a computer and has the square-type black box monitor equipment, is manufactured. Images are presented with the step-variation time interval technique. questionnaire test and EEG signal detection data are analyzed. The analysis parameters are a “frequency band integral value” and a “band differential variation ratio”. he results show the high sensibility and fast response. The fact that image presenting repetition alleviates is verified.

• Journal of the Korean Operations Research and Management Science Society
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• v.30 no.4
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• pp.1-14
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• 2005

We propose a VSSI-CRL(Variable Sampling Size and Samplina Interval-Conforming Run length) synthetic control chart in order to improve the statistical characteristics of both the VSSI chart and the CRL synthetic chart. The VSSI-CRL chart utilizes VSSI sampling scheme, but it produces a signal only when the CRI is less than a given limit. An algorithm for calculating the ARL(Average Run length) and ATS(Average Time to Signal) of the VSSI-CRL chart is developed by employing Markov chain method. We present some lemmas for describing the statistical characteristics of the VSSI-CRL chart under in-control state. A procedure for designing the VSSI-CRL chart is proposed based on the lemmas. Extensive comparative studios show that the VSSI-CRL chart is superior to the CRL synthetic chart or the VSSI chart in general, and is comparable to the EWMA chart in ATS performance.

• Proceedings of the KIEE Conference
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• 2005.07a
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• pp.495-497
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• 2005

A new small signal stability analysis method for eigenvalue analysis is presented. This method is called RCF method and based on the computation of the state transition equations and state transition matrix over a specified time interval that corresponds to one or some cycle operations of the system. This method is applicable to any system with or without switching elements. As an applicable example of RCF method in power system, the one machine infinite bus system connected switching SVC at generator terminal is investigated and the results proved that variations of oscillation modes after switching operations can be calculated exactly.

• Journal of Advanced Marine Engineering and Technology
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• v.11 no.4
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• pp.33-40
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• 1987

Arc power is consumed energy per unit time between welding electrodes. The relations between consumed energy and electrode distance, current, voltage are nonlinear characteristics. Therefore commercial A.C. wattmeter cannot be used for measurement of the arc power. Most of arc energy measuring systems are developed for relay contact arc measurement. Relaly arc requires integrated instantaneous power because relay arc finishes in a short instant. But most of welding powers are continually consumed powers, therefore instantaneous power must be continually indicated in the form of averagy value. The author propose a new measurement method of power in which the current and voltage of welding electrode is multiplied and the resultant signal is passed to low pass filter in order to remove higher order frequency components. After integrating, the signal is devided by the integral interval and the results are stored in a computer memory.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.321-323
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• 2006

The IEEE 802.15.4 uses a CSMA/CA algorithm on access of media. The CSMA/CA algorithm does Random Backoff before the data is transmitted to avoid collisions. The random backoff is a kind of unavoidable delays and introduces the side effect of energy consumptions. To cope with those problems we propose a new media access algorithm, the Priority Based Ordered Media Access (PBOMA) algorithm, which uses different IFSs. The PBOMA algorithm uses Sampling Rate and Beacon Interval to get a different access probability(or IFS). The access probability is higher, the IFS is shorter. Note that The transfer of urgent data uses tone signal to transmit it immediately. The proposed algorithm is expected to reduce the energy consumptions and the delay.

• Journal of Multimedia Information System
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• v.3 no.2
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• pp.1-8
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• 2016

In this paper, we propose a method to automatically diagnose various diseases. The input data consists of electrocardiograph (ECG) recordings. We extract R-to-R interval (RRI) signals from ECG recordings, which are preprocessed to remove trends and ectopic beats, and to keep the signal stationary. After that, we perform some prospective analysis to extract time-domain parameters, frequency-domain parameters, and nonlinear parameters of the signal. Those parameters are unique for each disease and can be used as the statistical symptoms for each disease. Then, we perform feature selection to improve the performance of the diagnosis classifier. We utilize the selected features to diagnose various diseases using machine learning. We subsequently measure the performance of the machine learning classifier to make sure that it will not misdiagnose the diseases. The first two steps, which are R-to-R extraction and preprocessing, have been successfully implemented with satisfactory results.

• Proceedings of the KIEE Conference
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• 2002.11b
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• pp.94-97
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• 2002

A new small signal stability analysis method for eigenvalue analysis is presented. The method is based on the computation of the transition matrix over a specified time interval that corresponds to one cycle operation of the system The method is applicable to any system with or without nonlinear elements. An applicable example of RCF method is presented and the eigenvalues are compared with those of the conventional state space method to show the exactness of the computed eigenvalues of the new method. Also, the variations of oscillation modes which were caused by the switching operation can be analyzed exactly using RCF method.