• Journal of Physiology & Pathology in Korean Medicine
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• v.19 no.1
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• pp.119-123
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• 2005

In the courses of in vitro screening for the angiotensin converting enzyme (ACE) inhibitory activity of the various extracts from medicinal plants, n-BuOH soluble extract of the seeds of Xanthium strumarium was found to exhibit distinctive angiotensin converting enzyme (ACE) inhibitory activity. Bioassay-guided fractionation and purification of the n-BuOH soluble extract of the seeds of Xanthium strumarium afforded a new $xanthiazone-11-{\beta}-glucopyranoside$. The ACE activity was significantly inhibited by the addition of a new $xanthiazone-11-{\beta}-glucopyranosidein$ a dose-dependent manner of which $IC_{50}$ value was $21.8\;{\mu}g/ml$.

• Korean Journal of Pharmacognosy
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• v.39 no.1
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• pp.60-67
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• 2008

The subcronic toxicity of BDR-29, a herbal preparation of Cassiae Semen, Prunellae Spica, Tribuli Fructus, and Uncariae Rhamulus et Uncus, was examined in male and female Sprague-Dawley rats. Rats were treated with the test substance at a dose 5 mg/kg, 50 mg/kg and 500 mg/kg intragastrically for 13 weeks. No death and abnormal clinical signs were observed throughout the administration period. There were not significantly different from control group in net body weight gain, food and water consumption, organ weight, gross pathological findings, and urine analysis among the groups rats treated with different doses of the BDR-29. Hematological findings and biochemical examination revealed no evidence of specific toxicity related to BDR-29. From these results, no observation effect level (NOEL) of BDR-29 is 500 mg/kg/day under the condition employed in this study.

• Journal of Physiology & Pathology in Korean Medicine
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• v.19 no.3
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• pp.797-801
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• 2005

While conducting an in vitro screening of various medicinal plant extracts, an aqueous extract of Rosa rugosa Radix (ARR) was found to exhibit a distinct vasorelaxant activity. ARR induced a concentration-dependent relaxation of the phenylephrine-precontracted aorta. This effect disappeared with the removal of functional endothelium. Pretreatment of the aortic tissues with NG-nitro-L-arginine methyl ester (L-NAME) or 1H-[1,2,4]-oxadiazole-[4,3-]-quinoxalin-1-one (ODQ) completely inhibited the relaxation induced by ARR. ARR-induced vascular relaxations were also markedly attenuated by addition of diltiazem or verapamil. However, the relaxant effect of ARR was not blocked by pretreatment with indomethacine, tetraethylammonium (TEA), glibenclamide, atropine, or propranolol. Taken together, the present study suggests that ARR dilates vascular smooth muscle via endothelium-dependent NO/cGMP signaling.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.13 no.4
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• pp.269-276
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• 2013

Information and communication technology (ICT) is a promising solution for mitigating road traffic congestion. ICT allows road users and vehicles to be managed based on real-time road status information. In Tanzania, traffic congestion causes losses of TZS 655 billion per year. The main objective of this study was to develop an optimal approach for integrating real-time road information (RRI) to mitigate traffic congestion. Our research survey focused on three cities that are highly affected by traffic congestion, i.e., Arusha, Mwanza, and Dar es Salaam. The results showed that ICT is not yet utilized fully to solve road traffic congestion. Thus, we established a possible approach for Tanzania based on an analysis of road traffic data provided by organizations responsible for road traffic management and road users. Furthermore, we evaluated the available road information management techniques to test their suitability for use in Tanzania. Using the floating car data technique, fuzzy logic was implemented for real-time traffic level detection and decision making. Based on this solution, we propose a RRI system architecture, which considers the effective utilization of readily available communication technology in Tanzania.

• Science of Emotion and Sensibility
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• v.21 no.3
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• pp.73-82
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• 2018

Attempts have been made to recognize social emotion, including competition-cooperation, while designing interaction in work places. This study aimed to determine the cardiac response associated with classifying competition-cooperation of social emotion. Sixty students from Sangmyung University participated in the study and were asked to play a pattern game to experience the social emotion associated with competition and cooperation. Electrocardiograms were measured during the task and were analyzed to obtain time domain indicators, such as RRI, SDNN, and pNN50, and frequency domain indicators, such as VLF, LF, HF, VLF/HF, LF/HF, lnVLF, lnLF, lnHF, and lnVLF/lnHF. The significance of classifying social emotions was assessed using an independent t-test. The rule-base for the classification was determined using significant parameters of 30 participants and verified from data obtained from another 30 participants. As a result, 91.67% participants were correctly classified. This study proposes a new method of classifying social emotions of competition and cooperation and provides objective data for designing social interaction.

• Journal of the Institute of Convergence Signal Processing
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• v.1 no.1
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• pp.15-22
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• 2000

The analysis of power spectrum based on linear AR model is applied widely to quantize the response of autonomic nerve noninvasively, In this paper, we estimate the power spectrum density for heartrate variability of the electrocadiogram and pulse wave for short term data(less than two minute), The time series of heart rate variability is obtained from the time interval(RRI, PPI) between the feature point of the electrocadiogram and pulse wave for normal person, The generated time series reconstructed into new time series through polynomial interpolation to apply to the AR mode. The power spectrum density for AR model is calculated by Burg algorithm, After applying AR model, the power spectrum density for heart rate variability of the electrocadiogram and the pulse wave is shown smooth spectrum power at the region of low frequence and high frequence, and that the power spectrum density of electrocadiogram and pulse wave has similar form for same subject.

• Korean Journal of Applied Biomechanics
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• v.33 no.4
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• pp.164-174
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• 2023

Objective: The aim of this study was to quantitatively analyze the impact characteristics of the lower extremity on strike pattern during running. Method: 19 young subjects (age: 26.53 ± 5.24 yrs., height: 174.89 ± 4.75 cm, weight: 70.97 ± 5.97 kg) participated in this study. All subjects performed treadmill running with fore-foot strike (FFS), mid-foot strike (MFS), and rear-foot strike (RFS) to analyze the impact characteristics in the lower extremity. Impact variables were analyzed including vertical ground reaction force, lower extremity joint moments, impact acceleration, and impact shock. Accelerometers for measuring impact acceleration and impact shock were attached to the heel, distal tibia, proximal tibia, and 50% point of the femur. Results: The peak vertical force and loading rate in passive portion were significantly higher in MFS and FFS compared to FFS. The peak plantarflexion moment at the ankle joint was significantly higher in the FFS compared to the MFS and RFS, while the peak extension moment at the knee joint was significantly higher in the RFS compared to the MFS and FFS. The resultant impact acceleration was significantly higher in FFS and MFS than in RFS at the foot and distal tibia, and MFS was significantly higher than FFS at the proximal tibia. In impact shock, FFS and MFS were significantly higher than RFS at the foot, distal tibia, and proximal tibia. Conclusion: Running with 3 strike patterns (FFS, MFS, and RFS) show different impact characteristics which may lead to an increased risk of running-related injuries (RRI). However, through the results of this study, it is possible to understand the characteristics of impact on strike patterns, and to explore preventive measures for injuries. To reduce the incidence of RRI, it is crucial to first identify one's strike pattern and then seek appropriate alternatives (such as reducing impact force and strengthening relevant muscles) on that strike pattern.

• Journal of electromagnetic engineering and science
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• v.3 no.1
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• pp.50-56
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• 2003

This paper proposes a coding scheme of control channel for mobile packet communication to maximize the minimum Hamming distance, which is based on shifting of basis vectors of Reed Muller code with optimized dynamic puncturing and/or(partial) sequence repetition. Since the maximum likelihood decoding can be performed using the extremely simple FHT(Fast Hadamard Transformation), it is suitable for real time optimum decoding of control channel information with very little complexity. We show applications of the proposed coding method to TFCI(Transport Format Combination Indicator) code in split and normal modes of 3GPP W-CDMA system. We also discuss how this method can reduce rate indication error over AWGN(Additive White Gaussian Noise) as well as fading channels when the proposed coding scheme is applied to 1xEV-DV system of $3^{rd}$TEX> generation partnership project 2(3GPP2) to indicate the data rate transmitted on the reverse traffic channel by a Mobile Station(MS).

• 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.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.2
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• pp.75-81
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• 2006

The purpose of this paper is to recognize the feature points of ECG and human pulse -which signal shows the electric and physical characteristics of heart respectively- using wavelet transform. Wavelet transform is proper method to analyze a signal in time-frequency domain. In the process of wavelet decomposition and reconstruction of ECG and human pulse signal, we removed the noises of signal and recognized the feature points of signal using some of decomposed component of signal. We obtained the result of recognition rate that is estimated about 95.45$\%$ in case of QRS complex, 98.08$\%$ in case of S point and P point and 92.81$\%$ in case of C point. And we computed diagnosis parameters such as RRI, U-time and E-time.