• Bulletin of the Korean Mathematical Society
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• v.56 no.1
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• pp.1-12
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• 2019

For a finite poset $P=(X,{\preceq})$ the fractional weak discrepancy of P, denoted $wd_F(P)$, is the minimum value t for which there is a function $f:X{\rightarrow}{\mathbb{R}}$ satisfying (1) $f(x)+1{\leq}f(y)$ whenever $x{\prec}y$ and (2) ${\mid}f(x)-f(y){\mid}{\leq}t$ whenever $x{\parallel}y$. In this paper, we determine the range of the fractional weak discrepancy of (M, 2)-free posets for $M{\geq}5$, which is a problem asked in [9]. More precisely, we showed that (1) the range of the fractional weak discrepancy of (M, 2)-free interval orders is $W=\{{\frac{r}{r+1}}:r{\in}{\mathbb{N}}{\cup}\{0\}\}{\cup}\{t{\in}{\mathbb{Q}}:1{\leq}t<M-3\}$ and (2) the range of the fractional weak discrepancy of (M, 2)-free non-interval orders is $\{t{\in}{\mathbb{Q}}:1{\leq}t<M-3\}$. The result is a generalization of a well-known result for semiorders and the main result for split semiorders of [9] since the family of semiorders is the family of (4, 2)-free posets.

• Proceedings of the ESK Conference
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• 1998.04a
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• pp.188-193
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• 1998

The purpose of the study is to develop a numerical model based on experimental data to estimate the thermal comfort in the driving room of a motorcar. For the ecperiments, three air temperature level of 21, 23, 25 .deg. C are set to measure variable such as average skin temperature, R-R interval, the comfort sensation, and the performance level. By performing statistical analysis with the results obtainted, it is observed that two physiological factors-average skin temperature and R-R interval have significant relation with the thermal comfort in the driving room. Thus, those two factors are included as parameters in the proposed model to estimate the thermal comfort.

• Proceedings of the IEEK Conference
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• 2003.07c
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• pp.2879-2882
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• 2003

Obstructive Sleep Apnea(OSA) is a representative symptom of sleep disorder which is caused by airway obstruction. OSA is usually diagnosed through the laboratory based Polysomnography(PSG) which is uncomfortable and expensive. In this paper, the detection method for OSA events, using ECG, has been developed. The proposed method uses the ECG data sets provided from Physionet. The features for OSA events detection are the average and standard deviation of 1 minute R-R interval, power spectrum of R-R interval and S-pulse amplitude from data sets. These features are applied to the input of Neural Network. To evaluate the method, we used the another ECG data sets. And we achieved sensitivity of 89.66％, specificity of 95.25％. So, we can know that the features proposed in this paper are important to detect OSA.

• Journal of Biosystems Engineering
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• v.24 no.3
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• pp.259-266
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• 1999

This research was carried out to investigate the possibility of real time rice milling ratio measurement using the spectral reflection characteristics. In this study, various methods were compared such as \circled1 using the whiteness meter, \circled2 using the colorimeter, \circled3 using the Visible and the NIR reflection spectrum. The samples were milled in the domain of 84~96% by 0.5% interval classified by milling ratio. The NMG treatment method required about 20 minutes to determine the milled ratio and r2 was 0.0028 to 0.7959 that was very low. In case of whiteness meter, r2 was high but speed of measurement was 5 minutes that was very low. Measurement with the colorimeter required about 5 minutes and r2 was 0.60 to 0.85 that was low. The reflection spectrum were measured in the range of 400~2,500nm with 2nm interval and the MLR model with six-wavelength obtained from first derivative of spectra gave the best results(r2 = 0.967, SEP = 0.729%)

• 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.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.168.3-168
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• 2001

The purpose of this paper is to find the relations between the virtual reality created by the ship´s bridge simulator (simulator) at Radar Navigation Experiment and Research Facility in Kobe University of Mercantile Marine (KUMM) and the observer´s response to it. In short, we analyze the observer´s heart rate variability (R-R interval) in navigational condition seasick impression by simulator occurred, and present the R-R Interval and the stress of observer with SNS and PNS calculated by STFT. In this experiment, rolling of the ship was simulated and presented to the observer. Rolling was simulated only visually not physically or mechanically while the balancing movement and heart beat of the observer were measured and processed to produce the measures for body response to the artificially created visual environment. The results show that even a ...

• Proceedings of the Korean Information Science Society Conference
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• 2012.06b
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• pp.507-509
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• 2012

심전도 질환 데이터는 일반적으로 분류기를 사용한 실험이 많다. 심전도 신호는 QRS-Complex와 R-R interval을 추출하는 경우가 많은데 본 실험에서는 R-R interval을 추출하여 실험하였다. 심전도 데이터의 분류 실험은 일반적으로 SVM(Support Vector Machine)과 MLP(Multilayer Perceptron)으로 실험되지만 본 실험은 Decision Tree를 사용하여 정확도 향상을 추구하였다. 그리고 정확도 비교 분석을 위해 SVM과 MLP 분류기 실험을 같이 수행하였고, 동일한 데이터와 간격으로 실험한 타 논문의 결과와 비교해 보았다. Decision Tree를 다른 분류기와 타 논문의 결과와 비교해 보니 정확도 부분에서는 Decision Tree가 가장 우수하였다.

• Journal of Korea Society of Industrial Information Systems
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• v.20 no.3
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• pp.87-93
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• 2015

The accidents caused by drivers while driving are considered as the major causes along with other causes such as conditions of roads, weather and cars. In this study, we investigated the driver's workloads under three different driving conditions (Weather, Driving time zone, and Traffic density) through analyzing biological signals obtained from a car driving simulator system. The proposed method is able to detect R waves and R-R interval calculation in the ECG. Heart rate variability (HRV) was investigated for the time domain to determine the changes in driver's conditions.

• 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.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 1999.03a
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• pp.237-242
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• 1999

The nature of the interactions between the vestibular and autonomic systems is complex and has not been fully defined. Vestibuloocular reflex induced by sinusoidal rotation and activity of the autonomic nerves in the heart were measured to investigate the interactions between the vestibular system and the autonomic nervous system in healthy adults. Eye movement induced by sinusoidal rotation of the whole body or optokinetic stimulation at 0.04 Hz was analyzed in gain, phase, and symmetry. EKG was measured during vestibular stimulation and analyzed in heart rate variability including mean R-R interval, standard deviation (SD) and coefficient of variance (CV) of R-R interval, and power spectrum of low frequency region (LF) and high frequency region (HF). Gain of eye movement was 0.65${\pm}$0.03 by ratatory stimulation, 0.70${\pm}$0.02 in optokinetic stimulation, 0.08${\pm}$0.02 in visual suppression, and 0.84${\pm}$0.04 in visual enhancement. In R-R interval, resting condition (control) was 0.82${\pm}$0.03 sec, and visual suppression showed significant increase and visual enhancement did significant decrease compared with control (p<0.01).CV was 0.06${\pm}$0.02 in control and visual enhancement increased significantly (p<0.05). In LF/HF control was 1.40${\pm}$0.23, which was not different from rotatory or optokinetic stimulation. But visual suppression decreased LF/HF significantly and visual enhancement increased significantly compared with control (p<0.01). These results suggest that degree of gain corresponds with LF/HF and increased gain in visual enhancement is deeply related to the activity of sympathetic nerves.