• Journal of Integrative Natural Science
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• v.5 no.3
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• pp.151-156
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• 2012

Because of the equivalence between control chart procedures and hypothesis testing, we propose to use likelihood ratio test (LRT) statistic $Z_i^2$ as the multivariate control statistic for simultaneous monitoring means of the multivariate normal process. Properties and comparisons of the proposed control charts are explored and conducted for matched fixed sampling interval (FSI) and variable sampling interval (VSI) with two sampling interval charts. The result of numerical comparisons shows that EWMA chart with two sampling interval procedure is more efficient than the corresponding FSI chart for small or moderate changes. When large shift of the process has occurred, we also found that Shewhart chart is more efficient than EWMA chart.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.6
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• pp.794-798
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• 2018

There is a growing need for a care system that can continuously monitor, manage and effectively relieve stress for modern people. In recent years, mobile healthcare devices capable of measuring heart rate have become popular, and many stress monitoring techniques using heart rate variability analysis have been actively proposed and commercialized. In addition, respiratory biofeedback methods are used to provide stress relieving services in environments using mobile healthcare devices. In this case, breathing information should be measured well to assess whether the user is doing well in biofeedback training. In this study, we extracted the heart beat interval signal from the PPG and used the oscillator based notch filter based on the IIR band pass filter to track the strongest frequency in the heart beat interval signal. The respiration signal was then estimated by filtering the heart beat interval signal with this frequency as the center frequency. Experimental results showed that the number of breathing could be measured accurately when the subject was guided to take a deep breath. Also, in the timeing measurement of inspiration and expiration, a time delay of about 1 second occurred. It is expected that this will provide a respiratory biofeedback service that can assess whether or not breathing exercise are performed well.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.7
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• pp.885-890
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• 2020

In the distance measurement system the time-to-digital conversion circuit used measures the distance using the time interval between the start signal and the stop signal. The time interval is generally converted to digital information using a counter circuit considering the response speed. Therefore, a clock signal with a high frequency is required to improve precision, and a clock signal with a high frequency is also required to measure fine distances. In this paper, a counter circuit was designed to increase the accuracy of distance measurement while using the same frequency. The circuit design was performed using a 0.18㎛ CMOS process technology, and the operation of the designed circuit was confirmed through HSPICE simulation. As a result of the simulation, it is possible to obtain an improvement of four times the precision compared to the case of using a general counter circuit.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.11
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• pp.643-649
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• 2005

A heart diagnosis system adopts Superconducting Quantum Interface Device(SQUD) sensors for precise MCG(MagnetoCardioGram) signal acquisitions. Such system needs to deal with hundreds of sensors, requiring fast signal sampling md precise analog-to-digital conversions(ADC). Our development of hardware board, processing 64-channel 12-bit in 1 ks/s speed, is built by using 8-channel ADC chips, 8-bit microprocessors, SPI interfaces, and specially designed parallel data transfers between microprocessors to meet the 1ks/s, i.e. 1 mili-second sampling interval. We extend the design into 256-channel hardware and analyze the speed .using the measured data from the 64-channel hardware. Since our design exploits full parallel processing, Assembly level coding, and NOP(No Operation) instruction for timing control, the design provides expandability and lowest system timing margin. Our result concludes that the data collection with 256-channel analog input signals can be done in 201.5us time-interval which is much shorter than the required 1 mili-second period.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2082-2086
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• 2003

This paper presents the analysis of satellite received signal by focus on the new prediction method for amplitude scintillation expression. A predict method based in the relationship of standard deviation values and the peak to peak values of amplitude scintillation in various of time period and various of sampling rate of signal variation. The principal techniques finding, the proper sampling rate and time interval, for the best expression method. The experiment has been performed in Bangkok of Thailand, at King Mongkut's Institute of Technology, Ladkrabang, data collected in C-Band and Ku-Band on high elevation angles. The result of analysis shows the relationship between two methods is given by ${\sigma}_x={\alpha}(P-P)+{\beta}$. The value of ${\alpha}$ depends on sampling rate by closely with three-minute maximum time interval.

• Proceedings of the KIEE Conference
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• 2001.11c
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• pp.394-397
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• 2001

There are several methods of measuring position. For example GPS, AOA, TDOA and using radio camera. In this Paper I used TDOA method in position measuring system. TDOA method uses arrival time difference. In position measuring system, three transfers which is placed in different position transfer signal to receiver in fixed time interval and receiver records arrival time of signal. Because receiver knows idle signal's arrival time, receiver can calculate the difference of the signal's arrival time between idle and real. When we obtain time difference we can know the receiver position by Newton Raphson method.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.3 no.1
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• pp.66-71
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• 2003

In the past, when there were few vehicles on the road, the T.O.D.(Time of Day) traffic signal worked very well. The T.O.D. signal operates on a preset signal cycling which cycles on the basis of the average number of average passenger cars in the memory device of an electric signal unit. Today, with increasing traffic and congested roads, the conventional traffic light creates startup-delay time and end lag time so that thirty to forty-five percent efficiency in traffic handling is lost, as well as adding to fuel costs. To solve this problem, this paper proposes a new concept of optimal green time algorithm, which reduces average vehicle waiting time while improving average vehicle speed using fuzzy rules and neural networks. Through computer simulation, this method has been proven to be much more efficient than fixed time interval signals. Fuzzy Neural Network will consistanly improve average waiting time, vehicle speed, and fuel consumption.

• 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.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.364-364
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• 2000

Timed Petri Net(TPN) is one of methods to model and to analyze Discrete Event Dynamic Systems(DEDSs) with real time values. It has two time values, earliest firing time ($\alpha$$_{i}$) and latest firing time ($\beta$$_{I}$) for the each transition. A transition of TPN is fired at arbitrary time of time interval ($\alpha$$_{I}$, $\beta$$_{i}$). Uncertainty of firing time gives difficulty to analyze and estimate a modeled system. In this paper, we proposed the Fuzzy Transition Timed Petri Net(FTTPN) with fuzzy theory to determine the optimal transition time (${\gamma}$$_{i}$). The transition firing time (${\gamma}$$_{i}$) of FTTPN is determined from fuzzy controller which is modeled with information of state transition. Each of the traffic signal controllers are modeled using the proposed method and timed petri net. And its Performance is evaluated by simulation of traffic signal controller. controller.

• Journal of the Korean Statistical Society
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• v.26 no.2
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• pp.181-198
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• 1997

The variable sampling rates scheme is proposed by taking random sample size and sampling interval during the process. The performance of the scheme is measured in terms of the average time to signal adjusted by teh sampling cost when the process is out of control. This measurement evaluates the effectiveness of the scheme in terms of the cost incurred due to nonconformation as well as sampling. The variable sampling rates scheme is shown to be effective especially for small and moderate shifts of the mean when compared to the standard scheme.