• Proceedings of the Korean Information Science Society Conference
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• 2002.04a
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• pp.157-159
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• 2002

본 논문에서는 신세 자인의 개발 전에도 망 관리 시스템의 개발 및 운용 테스트를 수행하도록 지원하는 실제 자원 시뮬레이터(RRS: Real Resource Simulator)를 소개한다. RRS는 객체의 상태를 유지하는 MOT(Managed Object Table)와 사용자가 정의한 동작 특성을 유지하는 SDT(Simulation Data Table), 랜덤(random) 값과 랜덤 주기(interval) 값을 발생할 지인 함수들, 순차적인 사건 발생 또는 값의 수정을 지원하는 스케줄링 테이블, 그리고 이들을 전체적으로 관장하는 메인 커널로 이루어져 있다. 본 논문에서는 구현된 RRS의 전체 동작과 테스트를 목적으로 만든 RRS의 운용 화면을 소개한다.

• Journal of Korea Society of Digital Industry and Information Management
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• v.13 no.4
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• pp.91-98
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• 2017

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 minimal feature point based on only R peak through optimal R wave. We propose an optimal R wave detection and PVC classification method through extracting minimal feature point in IoT environment. 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 record of MIT-BIH arrhythmia database. The achieved scores indicate the average of 99.758% in R wave detection and the rate of 93.94% in PVC classification.

• 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.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1643-1646
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• 1997

In this study, the method is proposed, which enable us to noninvasively assess baroreflex sensitivity through the closed-loop feedback modle between RR flucturarion and arterial blood pressure fluctuation. The proposed indexes of baroreflex sensitivity, BRS$_{LF}$와 BRS$_{HF}$ are calculated by the modulus (or gain) of the transfer function between fluctuatuons in blood pressure and RR interval in the LF band HF band, where the coherence is more than 0.5 to evaluate the performance of the proposed method, it is applied to various cardiovascular variability signals obtained form subjects under the submaximal ecericse on bicycle ergometner. In result it is concluded that the proposed method can noninvasively assess the baroreflex sensitivity.ty.

• Proceedings of the KIEE Conference
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• 1988.07a
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• pp.746-749
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• 1988

This paper describes an arrhythmia detection algorithm using PP and PR Interval. In order to detect P-wave accurately, an improved 5-point derivative method is used. In this paper, the RR, PP and PR interval. and the number of P-waves per RR Interval are detected for arrhythmia detection. These parameters can be utilized to diagnose in the varied types of AV block, atrial fibrillation, and PVC.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.4
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• pp.825-832
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• 2014

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 accurate detection of P-QRS-T point, higher computational cost and larger processing time. Even if some methods have the advantage in low complexity, but they generally suffer form low sensitivity. Also, it is difficult to detect PVC accurately because of the various QRS pattern by person's individual difference. Therefore it is necessary to design an efficient algorithm that classifies PVC based on QRS pattern in realtime and decreases computational cost by extracting minimal feature. In this paper, we propose PVC classification based on QRS pattern using QS interval and R wave amplitude. For this purpose, we detected R wave, RR interval, QRS pattern from noise-free ECG signal through the preprocessing method. Also, we classified PVC in realtime through QS interval and R wave amplitude. The performance of R wave detection, PVC classification is evaluated by using 9 record of MIT-BIH arrhythmia database that included over 30 PVC. The achieved scores indicate the average of 99.02% in R wave detection and the rate of 93.72% in PVC classification.

• Journal of The Korean Society of Agricultural Engineers
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• v.60 no.1
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• pp.111-120
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• 2018

The purpose of this study was to develop a ridge regression (RR) model to estimate BOD and TP load using runoff weighted value. The concept of runoff weighted value, based on distributed curve-number (CN), was introduced to reflect the impact of land covers on runoff. The estimated runoff depths by distributed CN were closer to the observed values than those by area weighted mean CN. The RR is a technique used when the data suffers from multicollinearity. The RR model was developed for five flow duration intervals with the independent variables of daily runoff discharge of seven land covers and dependent variables of daily pollutant load. The RR model was applied to Heuk river watershed, a subwatershed of the Han river watershed. The variance inflation factors of the RR model decreased to the value less than 10. The RR model showed a good performance with Nash-Sutcliffe efficiency (NSE) of 0.73 and 0.87, and Pearson correlation coefficient of 0.88 and 0.93 for BOD and TP, respectively. The results suggest that the methods used in the study can be applied to estimate pollutant load of different land cover watersheds using limited data.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.7C
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• pp.685-695
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• 2002

In this paper, we propose a RRS(real resource simulator) that supports the development and operational test of network management system before the development of real resources. The components of the RRS are the MOT(Managed Object Table) that holds the current status information of real resources, the SDT(Simulation Data Table) that holds the characteristics of real resources defined by user, the support functions that generate the random values and random interval values, the scheduling table that holds the sequence of events, and the main kernel. Users can set up behaviors of the RRS by extended-GDMO description. We present the structure of our extended-GDMO compiler and activities of RRS. We also show the interaction between user and the RRS, interaction between the RRS and the agent, and interaction among the NMS, the agent and the RRS.

• Journal of Multimedia Information System
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• v.5 no.2
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• pp.121-130
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• 2018

We developed multimedia esophageal catheters for use with birds to measure and record ECG and angular velocity while anesthesized, at rest, and in flight. These catheters enable estimates of blood pressure based on readings given by an angular velocity sensor and by RR intervals of ECG affected by EMG. In our experiments, the catheters had the following characteristics: 1. Esophageal catheters offer a topological advantage with 8-dB SNR improvement due to elimination of electromyography (EMG). 2. We observed a very strong correlation between blood pressure and the angular velocity of esophageal catheter axial rotation. 3. The impulse conduction pathway (Purkinje fibers) of the cardiac ventricle has a direction opposite to that of the mammalian pathway. 4. Sympathetic nerves predominate in flight, and RR interval variations are strongly suppressed. The electrophysiological data obtained by this study provided especially the state of the avian autonomic nervous system activity, so we can suspect individual's health condition. If the change of the RR interval was small, we can perform an isolation or screening from the group that prevent the pandemics of avian influenza. This catheter shall be useful to analysis an avian autonomic system, to perform a screening, and to make a positive policy against the massive infected avian influenza.

• Korean Journal of Clinical Pharmacy
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• v.21 no.2
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• pp.90-99
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• 2011

Health Insurance Review & Assessment Service (HIRA) claims database has a high potential to detect signals of new drug interactions. The aim of this study was to evaluate the usefulness of information component (IC) and relative risk (RR) as a tool for signal detection, and to analyze the possible drug interactions caused by clopidogrel using HIRA claims database. This study was performed in elderly patients over 65 years of age who administered clopidogrel from January 2005 to June 2006 in South Korea. Serious Adverse Events (SAEs) as drug interactions of clopidogrel were defined as any ambulatory hospitalization for ischemic diseases within comcomitant medication period of clopidogrel. Information Component (IC) and Relative Risk (RR) were calculated to compare the proportion of drug-SAE pairs in order to select drug specific SAEs. IC and RR signals of clopidogrel drug interaction were screened when IC's 95% confidence interval was greater than 0 and RR's 95% confidence interval was greater than 1 respectively. All detected signals were compared to references such as $Micromedex^{(R)}$ and 2010 Drug Interaction $Facts^{TM}$. Sensitivity, specificity, positive predicted value and negative predicted value were used to evaluate usefulness of this method. Among 13,252,930 cases of elderly patients who co-administered clopidogrel and other drugs, 47,485 cases were detected as SAE. Of these, one-hundred nine cases were detected by the IC-based data-mining approach and ninety one cases were detected by the RR-based data-mining approach. Total One-hundred sixty three unrecognized signals were detected by IC or RR. Twelve signals from IC-based data-mining (57.1%) were corresponded with drug interactions from references and eight signals from RR-based data-mining (38.1%) were corresponded with drug interactions from references. These signals include proton pump inhibitors, calcium channel blockers and HMG CoA reductase Inhibitors, which were known to affect CYP450 metabolism. Further studies using HIRA claims database are necessary to develop appropriate data-mining measure.