• Food Engineering Progress
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• v.13 no.1
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• pp.50-55
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• 2009

The effect of active gluten supplementation on the quality properties of rice bagel was investigated. Water hydration capacity of rice flour increased as the amount of gluten increased, whereas alkaline water retention capacity decreased. Pelshenke value and sedimentation value were incerased as the amount of gluten increased, but these values are lower than those of strong wheat flour. Peak viscosity, setback, peak height, and peak width decreased as the amount of gluten increased. When the active gluten of 23% was added to the rice flour, the specific loaf volume of bagel increased more that two times compared with the active gluten of 11%. Hardness, gumminess, and chewiness were decreased as the amount of gluten increased. Specific loaf volume of bagel showed highly positive correlation in water hydration capacity, Pelshenke value, and sedimentation value of which values were r=0.962, r =0.964, and r =0.966, respectively.

• Proceedings of the KOSOMBE Conference
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• v.1995 no.11
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• pp.193-196
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• 1995

An algorithm using topological mapping has been developed for a real-time detection of the QRS complexes of ECG signals. As a measurement of QRS complex energy, we used topological mapping from one dimensional sampled ECG signals to two dimensional vectors. These vectors are reconstructed with the sampled ECG signals and the delayed ones. In this method, the detection rates of CRS complex vary with the parameters such as R-R interval average and peak detection threshold coefficient. We use mean, median, and iterative method to determint R-R interval average and peak estimation. We experiment on various value of search back coefficient and peak detection threshold coefficient to find optimal rule.

• Journal of Sensor Science and Technology
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• v.22 no.6
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• pp.379-386
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• 2013

The influences of the load resistance $R_L$ on the magnetoelectric (ME) characteristics of $NiZnFe_2O_4+PZT$ composite were investigated in the non-resonance frequency range. The ME coefficient peak increases with increasing $R_L$, but the frequency indicating the ME coefficient peak decreases with increasing $R_L$. The maximum output power peak is approximately $9.3{\times}10^{-10}mW/Oe$ near $R_L=3.3M{\Omega}$ at f=280 Hz, and the ME coefficient seems to be saturated at $R_L>20M{\Omega}$. This frequency shift effect of $R_L$ shows that the frequency range for an ME sensor application can be modulated with the appropriate value of $R_L$. The ME output voltage has a good linear response to the ac field Hac and shows fair stability over a range of temperatures. The measured non-linearity of this sample is approximately 0.8%. This sample will allow for a low-strength magnetic ac-field sensor. The result from this sample will serve as basic data for a signal-processing circuit system.

• Journal of the Korean Society of Physical Medicine
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• v.16 no.1
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• pp.33-39
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• 2021

PURPOSE: This study compared the body composition according to the sport of short-distance and middle & long-distance athletes to identify the factors that affect the body composition. METHODS: Forty-eight athletes selected as youth national athletes in 2019 participated in the study. The study participants measured the length of the lower extremities, body composition, and anaerobic ability. An independent sample t-test was conducted to compare the body composition according to the event. In addition, the Pearson correlation was performed to identify the factors that influence the body composition. RESULTS: The leg length of the Short and Middle & long-distance athletes were similar (p = .584). On the other hand, there were differences in the body fat percentage (p = .001), lean percentage (p = .001), and BMI (p = .001). In addition, the body fat percentage was correlated with the lean body mass (r = .419) and BMI (r = .447). Furthermore, the lean body mass was correlated with the BMI (r = .849) and the peak power (r = .662) and mean power (r = .686) of the anaerobic capacity. Moreover, the BMI was correlated with the peak power (r = .490) and mean power (r = .543) of the anaerobic capacity. The peak power of the anaerobic ability was correlated with the mean power (r = .931). CONCLUSION: The body composition differed according to the sport. The body fat percentage correlated with the lean body mass and the BMI. The lean body mass correlated with the BMI, peak power of anaerobic ability, and mean power. The BMI correlated with the anaerobic capacity.

• The Bulletin of The Korean Astronomical Society
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• v.40 no.1
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• pp.64.3-64.3
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• 2015

We have developed a set of daily solar flare peak flux forecast models for strong flares using multiple linear regression and artificial neural network methods. We consider input parameters as solar activity data from January 1996 to December 2013 such as sunspot area, X-ray flare peak flux and weighted total flux of previous day, and mean flare rates of McIntosh sunspot group (Zpc) and Mount Wilson magnetic classification. For a training data set, we use the same number of 61 events for each C-, M-, and X-class from Jan. 1996 to Dec. 2004, while other previous models use all flares. For a testing data set, we use all flares from Jan. 2005 to Nov. 2013. The best three parameters related to the observed flare peak flux are weighted total flare flux of previous day (r = 0.51), X-ray flare peak flux (r = 0.48), and Mount Wilson magnetic classification (r = 0.47). A comparison between our neural network models and the previous models based on Heidke Skill Score (HSS) shows that our model for X-class flare is much better than the models and that for M-class flares is similar to them. Since all input parameters for our models are easily available, the models can be operated steadily and automatically in near-real time for space weather service.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.337-340
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• 2009

Wireless tele-home-care application gives new possibilities for ECG (electrocardiogram) monitoring system with wearable biomedical sensors. Thus, continuously development of high convenient ECG monitoring system for high-risk cardiac patients is essential. This paper describes to monitor a person's ECG using wearable approach. A wearable belt-type ECG electrode with integrated electronics has been developed and has proven long-term robustness and monitoring of all electrical components. The measured ECG signal is transmitted via an ultra low power consumption wireless sensor node. ECG signals carry a lot clinical information for a cardiologist especially the R-peak detection in ECG. R-peak detection generally uses the threshold value which is fixed thus it bring errors due to motion artifacts and signal size changes. Variable threshold method is used to detect the R-peak which is more accurate and efficient. In order to evaluate the performance analysis, R-peak detection using MIT-BIH databases and Long Term Real-Time ECG is performed in this research. This concept able to allow patient to follow up critical patients from their home and early detecting rarely occurrences of cardiac arrhythmia.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.41 no.6
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• pp.493-504
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• 2008

In the seas around the Korean Peninsula, the seasonal cycle of zooplankton related to North Pacific regime shifts was investigated to understand the reaction of the ecosystem to climate change using long-term data on zooplankton biomass (1965-2000) and the abundance of four major zooplankton groups: copepods, amphipods, chaetognaths, and euphausiids (1978-2000). In general, the zooplankton biomass showed a large peak in spring and a small peak in autumnin Korean waters, but there was a slight difference in the peak time depending on the location and the period before and after the North Pacific regime shift. The zooplankton biomass showed conspicuous seasonal peaks in R-III (1990-2000) compared to R-I (1965-1976) and R-II (1977-1988), and the seasonal peak shifted from the autumn in R-II to the spring in R-III. The peak of copepods and euphausiids in abundance was from April to June, while chaetognaths peaked from August to October. We postulate that the time lag between the peaks for copepods and chaetognaths results from the predator-prey relationship. The regime shift in 1989 did not alter the seasonal cycle of the four major zooplankton groups, although it enhanced their production. The seasonal peaks of the four major zooplankton groups did not shift, while the seasonal peaks of the zooplankton biomass did shift. This was not only becausethe zooplankton biomass included other mesozooplankton groups but also because the abundance of the four major zooplankton groups increased significantly in spring.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.1
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• pp.227-232
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• 2011

The QRS complex in ECG analysis is possible to obtain much information that is helpful for diagnosing different types of cardiovascular disease. This paper presents the preprocessor method to detect R-peak, RR interval, and HRV in wireless sensor node. The derivative of the electrocardiogram is efficiency of preprocessing method for resource hungry wireless sensor node with low computation. We have implemented R-peak and RR interval detection application based on dECG for wireless sensor node. The sensor node only transfers meaning parameter of ECG. Thus, implementation of sensor node can save power, reduce traffic, and eliminate congestion in a WSN.

• 한국초전도학회:학술대회논문집
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• v.9
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• pp.343-347
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• 1999

We fabricated a resistive SFCL having a shunt resistor parallel to it in order to bifurcate the transient current at faults. The SFCL consists of a YBCO film coated with an Au layer (10 ${\omega}$ at room temperature), which is to disperse the heat generated at hot spots in the YBCO film, and the 5 ${\omega}$ shunt resistor. The minimum quench current of the SFCL was found to be 12.2 A$_{peak}$. This SFCL successfully controlled the fault current below 23 A$_{peak}$ which is otherwise to increase up to 113 A$_{peak}$. Bifurcation of the current resulted in the temperature rise of the YBCO/Au film 3 times slower than without the shunt, protecting the SFCL at high currents.

• Journal of Preventive Medicine and Public Health
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• v.10 no.1
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• pp.94-101
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• 1977

Noise pollution, both in the environment and in the workplace, has been recognized as a major health hazard -one that can impair not only a person's hearing but also his physical and mental well-being. As industrialization progresses, the prevalence rate of occupational diseases is increasing, especially hearing loss, which has the highest prevalence rate among the occupational diseases. The major cause of noise is the construction of various large industries without any regulation of noise sources. Therefor, we must establish an enactment to control mechanical noise sources. as soon as possible. For the purpose of controlling the noise source, we must have exact data about such things as the sound level, the frequency of the peak sound and the revolutions per minute (r.p.m.) of the machine (a measure of the power of its motor). This study was undertaken in order to define the noise characteristics, the power of the machine's motor, the change of the sound level and the peak sound as the r.p.m. increases, and the permissible exposure time. The sample size of this study was 74 machines at 11 plants in 6 industries. The results are as follows; 1. The breakdown of the types of mechanical noise noted was : 63.6% continuous normal sound, 26.9% intermittent sound, 4.7% continuous repeating sound and 4.6% impulsive sound. 2. With respect to the type of industry, the overall sound level was the highest in the mechanical industry, with $103.8{\pm}2.8dB(A)$, and lowest in the textile industry, with $89.2{\pm}1.43dB(A)$. 3. With respect to the type of machine, the highest sound level was 124 dB(A) caused by Gauzing(II), in the mechanical industry, and the lowest was 76 dB(A) caused by Attachment (Jup Chack) (I) in the timber industry. 4. The shortest permissible exposure time to Gauzing(II) in the mechanical industry was less than 15 minutes. 5. Among 74 machines, 68.2% of the peak sound was situated in the high frequency range (52.7% at 2 KHz, 4.1% at 4 KHz and 1.4% at 8 KHz). 41.8% of the peak sound was in the middle frequency range (4.1% at 250Hz, 14.8% at 500Hz and 22.9% at 1KHz). 6. If one machine had two motors or more, the peak sound was shifted to the low frequency range. 7. As the r.p.m. increased, the overall and peak sound levels were increased without any change of the frequency of the peak sound. 8. Whenever the machines had the same kind and the same r.p.m., the overall and peak sounds were changed by the physicochemical characteristics of the raw materials and the management.