• Proceedings of the KOSOMBE Conference
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• v.1996 no.05
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• pp.88-90
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• 1996

The right and left atrial pressures are important parameters in automatic control of a total artificial heart (TAH) within normal physiological ranges. Our TAH is composed of a moving actuator, right and left ventricles and the interventricular space enclosed by a semi-rigid housing. During operation of the TAH, the jnterventpicular space's volume is changed dynamically by the difference between the ejection volume of one ventricle and the inflow volume of the other. Therefore, the changes in pressure of the interventricular space is related to both atrial pressures. We measured the interventricular pressure (IVP) waveform using a pressure sensor and attempted to indirectly estimate the changes of atrial pressures. This method has an advantage that the sensor does not contact the blood directly. Furthermore, the IVP waveforms have its zero baseline in each pump cycle, thus the pressure measurements are free from the transducer drift problems by measuring the peak pressure from these baseline values. From the In vitro experiments, we found that the IVP waveform contained several useful parameters such as negative peak, dP/dT on the initial break, the area enclosed by the profile in each stroke, which are associated with atrial pressures and the filling conditions of the ventricles. The measured atrial pressures were linearly related to the negative peak of the interventricular pressure.

• Journal of the Korean Society of Tobacco Science
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• v.17 no.1
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• pp.5-14
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• 1995

Efficient algorithms for the automatic classification of flue-cured tovacco ripeness and grading have been developed The ripeness of the tobacco was classified into 4 levels vased on the color. The lab-built simple RGB color measuring system was utilized for detecting the light reflectance of the tobacco leaves. The measured data were used far training the artificial neural network The performance of the trained network was also tested far the untrained samples. The spectrophotometer was used to detect the light reflectance and absorption of the graded tobacco leaves in the frequency ranges of the visible light The measured data and the statistical analysis was performed to investigate the light characteristics of the graded samples. The measured data were obtained from samples of 5 different grades directly without considering the leaf positions. Those data were used far training the artificial neural network The performance of the trained network was also tested far the untrained samples. The neural network based sensor information processing showed successful results for grading of tobacco leaves.

• Korean Journal of Remote Sensing
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• v.31 no.3
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• pp.215-226
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• 2015

Normally, aero photography using UAV uses about 430 MHz bandwidth radio frequency (RF) modem and navigates and remotely controls through the connection between UAV and ground control system. When using the exhausting method, it has communication range of 1-2 km with frequent cross line and since wireless communication sends information using radio wave as a carrier, it has 10 mW of signal strength limitation which gave restraints on life my distance communication. The purpose of research is to use communication technologies such as long-term evolution (LTE) of smart camera, Bluetooth, Wi-Fi and other communication modules and cameras that can transfer data to design and develop automatic shooting system that acquires images to UAV at the necessary locations. We conclude that the android based UAV filming and communication module system can not only film images with just one smart camera but also connects UAV system and ground control system together and also able to obtain real-time 3D location information and 3D position information using UAV system, GPS, a gyroscope, an accelerometer, and magnetic measuring sensor which will allow us to use real-time position of the UAV and correction work through aerial triangulation.

• Journal of Sensor Science and Technology
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• v.23 no.6
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• pp.368-376
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• 2014

In order to measure the segmental impedance of the body, a bioelectrical impedance measurement system (BIMS) using multi-frequency applying method and two-electrode method was implemented in this study. The BIMS was composed of constant current source, automatic gain control, and multi-frequency generation units. Three experiments were performed using the BIMS and a commercial impedance analyzer (CIA). First, in order to evaluate the performance of the BIMS, four RC circuits connected with a resistor and capacitor in serial and/or parallel were composed. Bioelectrical impedance (BI) was measured by applying multi-frequencies -5, 10, 50, 100, 150, 200, 300, 400, and 500 KHz - to each circuit. BI values measured by the BIMS were in good agreement with those obtained by the CIA for four RC circuits. Second, after measuring BI at each frequency by applying multi-frequency to the left and right forearm and the popliteal region of the body, BI values measured by the BIMS were compared to those acquired by the CIA. Third, when the distance between electrodes was changed to 1, 3, 5, 7, 9, 11, 13, and 15 cm, BI by the BIMS was also compared to BI from the CIA. In addition, BI of extracellular fluid (ECF) was measured at each frequency ranging from 10 to 500 KHz. BI of intracellular fluid (ICF) was calculated by subtracting BI of ECF measured at 500 kHZ from BI measured at seven frequencies ranging from 50 to 500 KHz. BI of ICF and ECF decreased as the frequency increased. BI of ICF sharply decreased at frequencies above 300 KHz.

• Science of Emotion and Sensibility
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• v.6 no.4
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• pp.9-14
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• 2003

Sleep stages have been useful indicator to check a person's comfortableness in a sleep, But the traditional method of scoring sleep stages with polysomnography based on the integrated analysis of the electroencephalogram(EEG), electrooculogram(EOG), electrocardiogram(ECG), and electromyogram(EMG) is too restrictive to take a comfortable sleep for the participants, While the sympathetic nervous system is predominant during a wakefulness, the parasympathetic nervous system is more active during a sleep, Cardiovascular function is controlled by this autonomic nervous system, So, we have interpreted the heart rate variability(HRV) among sleep stages to find a simple method of classifying sleep stages, Six healthy male college students participated, and 12 night sleeps were recorded in this research, Sleep stages based on the "Standard scoring system for sleep stage" were automatically classified with polysomnograph by measuring EEG, EOG, ECG, and EMG(chin and leg) for the six participants during sleeping, To extract only the ECG signals from the polysomnograph and to interpret the HRV, a Sleep Data Acquisition/Analysis System was devised in this research, The power spectrum of HRV was divided into three ranges; low frequency(LF), medium frequency(MF), and high frequency(HF), It showed that, the LF/HF ratio of the Stage W(Wakefulness) was 325% higher than that of the Stage 2(p＜.05), 628% higher than that of the Stage 3(p＜.001), and 800% higher than that of the Stage 4(p＜.001), Moreover, this ratio of the Stage 4 was 427% lower than that of the Stage REM (rapid eye movement) (p＜.05) and 418% lower than that of the Stage l(p＜.05), respectively, It was observed that the LF/HF ratio decreased monotonously as the sleep stage changes from the Stage W, Stage REM, Stage 1, Stage 2, Stage 3, to Stage 4, While the difference of the MF/(LF+HF) ratio among sleep Stages was not significant, it was higher in the Stage REM and Stage 3 than that of in the other sleep stages in view of descriptive statistic analysis for the sample group.