• Korean Journal of Mathematics
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• v.25 no.1
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• pp.1-18
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• 2017

In this paper, we introduce the concepts of ([r, s], [t, u])-interval-valued intuitionistic fuzzy generalized preclosed sets and ([r, s], [t, u])-interval-valued intuitionistic fuzzy generalized preopen sets in the interval-valued intuitionistic smooth topological space and ([r, s], [t, u])-interval-valued intuitionistic fuzzy generalized pre-continuous mappings and then investigate some of their properties.

• Journal of Yeungnam Medical Science
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• v.2 no.1
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• pp.77-80
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• 1985

The R-R interval analyzer was developed to measure the autonomic nervous system function using microcomputer. The system based on 8 bit microcomputer including bandpass filter, R-wave detector and clock generator in order to obtain the mean value, standard deviation, total time, CV value, maximum value and minimum value in the specific view point of R-R interval variation. The pattern of R-R interval change after resting, voluntary standing and deep breathing can be analysed in normal subjects and diabetics with autonomic nervous dysfunction. The amplitude of the R-R interval variation showed sensitive pattern for normal subjects at resting, standing and deep breathing. On the contrary, the periodicities of amplitude for abnormal subjects with autonomic nervous dysfunction showed dull pattern. It was suggested that R-R interval analyzer is a good detection method for dysfunction of autonomic nervous system.

• Korean Journal of Mathematics
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• v.25 no.2
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• pp.261-278
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• 2017

In this paper, we introduce the concepts of ([r, s], [t, u])-interval-valued intuitionistic fuzzy alpha generalized closed and open sets in the interval-valued intuitionistic smooth topological space and ([r, s], [t, u])-interval-valued intuitionistic fuzzy alpha generalized continuous mappings and then investigate some of their properties.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.13 no.3
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• pp.231-244
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• 2013

We introduce the concept of interval-valued fuzzy congruences on a semigroup S and we obtain some important results: First, for any interval-valued fuzzy congruence $R_e$ on a group G, the interval-valued congruence class Re is an interval-valued fuzzy normal subgroup of G. Second, for any interval-valued fuzzy congruence R on a groupoid S, we show that a binary operation * an S=R is well-defined and also we obtain some results related to additional conditions for S. Also we improve that for any two interval-valued fuzzy congruences R and Q on a semigroup S such that $R{\subset}Q$, there exists a unique semigroup homomorphism g : S/R${\rightarrow}$S/G.

• The Korean Journal of Physiology
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• v.8 no.2
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• pp.33-44
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• 1974

The electrocardiogram of frogs were obtained in winter (January), spring (April), summer (July) and autumn (September and November). Electrocardiograms were recorded applying electrodes to the atria, ventricle and apex of the heart by unipolar or bipolar leads. V wave was recorded prior to P wave, for the presence of the sinus venosus which controls the automaticity of the frog heart, in four seasons. Regardless of the leads or the position of the electrodes P wave was diphasic and wide. According to the rise of temperature the rate of heart beat was increased, and V-P and P-R interval were shortened. Two regression line between R-R interval and both V-P interval and P-R interval were drawn. These were calculated as V-P interval=1 0.276R-R $interva1+0.067{\pm}0.15$ (sec.) and P-R interval=0.179R-R $interva1+0.155{\pm}0.1$ (sec). From these calculation the larger gradient of V-P interval than P-R interval was suggestive that the heart rate is more dependent on the changes of V-P interval than that of P-R interval. Changes of the heart rate were also measured in four seasons and artificial temperatures. Two regression lines between the heart rate (H.H.) and both seasonal temperature (T) and artificial temperature, were drawn. These two lines were calculated as H.R.=20+3.71 (T-10) and H.R.=32+1.425 T respectively. From two gradients of the above equations it is considered that the changes of the heart rate in artificial temperature were milder than that in seasonal temperature. The number of RBC and WBC of frogs were measured in four seasons and a tendency of the changes was observed according to the seasonal variation.

• Journal of Biomedical Engineering Research
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• v.22 no.2
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• pp.197-204
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• 2001

• Journal of Internet Computing and Services
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• v.12 no.6
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• pp.63-71
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• 2011

Cardiac disorder data are generally tested using the classifier and QRS-Complex and R-R interval which is used in this experiment are often extracted by ECG(Electrocardiogram) signals. The experimentation of ECG data with classifier is generally performed with SVM(Support Vector Machine) and MLP(Multilayer Perceptron) classifier, but this study experimented with Best-First Decision Tree(B-F Tree) derived from the Dicision Tree among Random Forest classifier algorithms to improve accuracy. To compare and analyze accuracy, experimentation of SVM, MLP, RBF(Radial Basic Function) Network and Decision Tree classifiers are performed and also compared the result of announced papers carried out under same interval and data. Comparing the accuracy of Random Forest classifier with above four ones, Random Forest is the best in accuracy. As though R-R interval was extracted using Band-pass filter in pre-processing of this experiment, in future, more filter study is needed to extract accurate interval.

• Journal of Ginseng Research
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• v.37 no.3
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• pp.283-292
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• 2013

Ginsenosides are divided into two groups based on the types of the panaxadiol group (e.g., ginsenoside-Rb1 and -Rc) and the panaxatriol group (e.g., ginsenoside-Rg1 and -Re). Among them, ginsenoside-Re (G-Re) is one of the compounds with the highest content in Panax ginseng and is responsible for pharmacological effects. However, it is not yet well reported if G-Re increases the hemodynamics functions on ischemia (30 min)/reperfusion (120 min) (I/R) induction. Therefore, in the present study, we investigated whether treatment of G-Re facilitated the recovery of hemodynamic parameters (heart rate, perfusion pressure, aortic flow, coronary flow, and cardiac output) and left ventricular developed pressure (${\pm}dp/dt_{max}$). This research is designed to study the effects of G-Re by studying electrocardiographic changes such as QRS interval, QT interval and R-R interval, and inflammatory marker such as tissue necrosis factor-${\alpha}$ (TNF-${\alpha}$) in heart tissue in I/R-induced heart. From the results, I/R induction gave a significant increase in QRS interval, QT interval and R-R interval, but showed decrease in all hemodynamic parameters. I/R induction resulted in increased TNF-${\alpha}$ level. Treatment of G-Re at 30 and $100{\mu}M$ doses before I/R induction significantly prevented the decrease in hemodynamic parameters, ameliorated the electrocardiographic abnormality, and inhibited TNF-${\alpha}$ level. In this study, G-Re at $100{\mu}M$ dose exerted more beneficial effects on cardiac function and preservation of myocardium in I/R injury than $30{\mu}M$. Collectively, these results indicate that G-Re has distinct cardioprotectective effects in I/R induced rat heart.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.2
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• pp.233-242
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• 2018

Previous works for detecting arrhythmia have mostly used nonlinear method such as artificial neural network, fuzzy theory, support vector machine to increase classification accuracy. Most methods require higher computational cost and larger processing time. Therefore it is necessary to design efficient algorithm that classifies PVC(premature ventricular contraction) and decreases computational cost by accurately detecting feature point based on only R peak through optimal R wave. For this purpose, we detected R wave through optimal threshold value and extracted RR interval and R peak pattern from noise-free ECG signal through the preprocessing method. Also, we classified PVC in realtime through RR interval and R peak pattern. The performance of R wave detection and PVC classification is evaluated by using 9 record of MIT-BIH arrhythmia database that included over 30. The achieved scores indicate the average of 99.02% in R wave detection and the rate of 94.85% in PVC classification.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.2 no.2
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• pp.15-21
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• 2009

This paper proposes a novel algorithm to assess the abnormal heart beats such as PVC (Premature Ventricular Contraction) and its subsequent RUNs. Our Arrhythmic detection scheme is based on only the R-R Interval features extracted from ECG waveforms and MIT-BIH arrhythmia database is evaluated to validate the efficiency of our algorithm in terms of sensitivity, specificity, FPR(%) and FNR(%).