• Title/Summary/Keyword: beat

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A Study on the Access Network Using CDMA-PON (CDMA-PON을 이용한 가입자 통신망에 관한 연구)

  • 안병구;조철희;박영일
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.26 no.12B
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    • pp.1629-1636
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    • 2001
  • A CDMA-PON system is proposed to be used for the optical access network which is becoming indispensable to keep up with the subscriber\`s uprising data traffic. CDMA technique is efficiently used not just to deliver multiple channels to each remote unit, but also to suppress the optical beat noise. In this study, multiple beat noises environments was analysed, modulation schemes for both forward and reverse links were suggested and a simulation and basic experiment for multiple channels was performed successfully.

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Comparison of performance for classification arrhythmia with PCA, ICA, LDA using artificial neural network (신경망 분류법을 사용한 PCA, ICA, LDA에 따른 부정맥 판별 성능 평가)

  • Kim, Jin-Kwon;Shin, Kwang-Soo;Shin, Hang-Sik;Lee, Myoung-Ho
    • Proceedings of the KIEE Conference
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    • 2007.07a
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    • pp.1924-1925
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    • 2007
  • 본 논문에서는 부정맥 판별을 위한 전처리 과정으로 PCA, LDA, ICA를 바탕으로 하여 정확도를 비교하여 보았다. 각각의 전처리는 고유의 특성을 가지고 있으며 본 논문의 목적은 부정맥 판별상 어떤 전처리가 더욱 정확성의 면에서 효과적인지를 알아보는 것이다. 본 논문의 데이터는 MIT-BIH에 기반하고 있으며, Beat의 분류는 정상(Normal), 좌각차단(Left Bundle Branch Block, LBBB), 우각차단(Right Bundle Branch Block, RBBB), 조기심실수축(Premature Ventricular Contraction, PVC), 조기심방수축(Atrial Premature Beat, APB), paced Beat, 심실보충수축(Ventricular Escape Beat)로 나누었다. 실험적 결과는 PCA-BPNN의 경우 95.53%, ICA-BPNN의 경우 93.95%, LDA-BPNN의 경우 96.42%로 LDA가 가장 ECG 부정맥 판별 응용에 있어 가장 효율적인 방법으로 나타났다.

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A Study on Analysis of Beat Spectra in a Radar System (레이다 시스템에서의 비트 스펙트럼 분석에 관한 연구)

  • Lee, Jong-Gil
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.14 no.10
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    • pp.2187-2193
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    • 2010
  • A specific radar system can be implemented more easily using the frequency modulated continuous wave comparing with the pulse Doppler radar. It also has the advantage of LPI (low probability of interception) because of the low power and wide bandwidth characteristics. These radars are usually used to cover the short range area and to obtain the high resolution measurements of the target range and velocity information. The transmitted waveform is used in the mixer to demodulate the received echo signal and the resulting beat signal can be obtained. This beat signal is analyzed using the FFT method for the purpose of clutter removal, detection of a target, extraction of velocity and range information, etc. However, for the case of short signal acquisition time, this FFT method can cause the serious leakage effect which disables the detection of weaker echo signals masked by strong side lobes of the clutter. Therefore, in this paper, the weighting window method is analyzed to suppress the strong side lobes while maintaining the proper main lobe width. Also, the results of FFT beat spectrum analysis are shown under various environments.

Changes in Oxygen-Pulse During Treadmill Walking (Treadmill 보행시 산소맥의 변화)

  • Lee, Chang-Hoon;Chung, Kyou-Chull
    • Journal of Preventive Medicine and Public Health
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    • v.17 no.1
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    • pp.281-287
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    • 1984
  • In search for a method of evaluating the cardiopulmonary function. 74 male and 33 female volunteers ages $18{\sim}25$ were subjected to this study The subjects walked on a treadmill at speed of 2,4,6 and 8km/hr with 0,5,10,15,20 and 25% grade of inclination, respectively, for a measurement of heart rate and oxygen-pulse. Heart rate was measured every 5 seconds at resting state and during walking by telemetric method using Heart Checker 108 System (Senoh Co., Japan). Oxygen concentration was measured by Douglas bag method collecting expired air for 5 minutes at rest, and for 2 minutes at the end of each walking exercise. Oxygen concentration in an expired air was analyzed with Orzat gas analyser and expressed in terms of STPD. Oxygen-pulse was defined as an amount of oxygen consumed at every heart at a cellular level. The followings were the results obtained from this study. 1. Mean values of oxygen-pulse at resting state was $3.1{\pm}0.11ml/beat$ in male and $2.5{\pm}0.87ml/beat$ in female, respectively. 2. Mean values of oxygen-pulse during treadmill walking were increased in proportion with the load of exercise, namely, the speed and grade of inclination, from minimum of 7.1ml/beat upto maximum of 18.2ml/beat in male and from minimum of 4.2ml/beat upto maximum of 12,7ml/beat in female. 3. Both linear and logarithmic regressional relationships between oxygen-pulse and speed of walking and grade of inclination were observed in both sexes. Predicted values of oxygen-pulse by logarithmic regressional formula on speed and on grade of inclination were better coincided with the measured values than those predicted by the linear regressional formula.

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Pattern of Species Distribution along Environmental Variables in Two Different Forest Beat of Raghunandan Reserve Forest of Habiganj

  • Hosen, Md. Shahadat;Ahamed, Md. Saleh
    • Journal of Forest and Environmental Science
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    • v.33 no.4
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    • pp.257-269
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    • 2017
  • The study has piloted to find the Pattern of species distribution along environmental variables and disturbance in Raghunandan Reserve Forest. Shaltila and Shahapur beat of Raghunandan Hill Reserve Forest are situated in Chunarughat sub-district of Habiganj district between $24^{\circ}5^{\prime}-24^{\circ}10^{\prime}N$ and $91^{\circ}25^{\prime}-91^{\circ}30^{\prime}E$ under the Sylhet Forest Division. The Environmental variable and vegetation data were collected from 30 sample plots from each forest beat by using arbitrary sampling without preconceived bias. 51 species were found from Shaltila and 34 species found in Shahapur forest beat. Thus the dataset continued with total 85 species in 60 samples. To determine the relationships between tree species distribution and environmental variables, Canonical Correspondence Analysis (CCA) ordination method were performed separately for two forest beat. In CCA ordination, tree species showed significant variation along environmental gradients in terms of soil organic matter and disturbances (p<0.05) in the case of Shaltila forest. Potassium has a significant relationship with axis 1 and axis 2 in this forest. But Shahapur forest showed no significant relationship between species and environmental variables. Phosphorus has a significantly negative relationship with axis 2 in this forest. Disturbance played as a critical role of this forest thus influencing the distribution of species. The study showed that the distributions of tree species are strongly influenced by disturbance and organic matter in Shaltila and Shahapur forest beat showed no significant relationship between species and environmental variables. Future research should be included more environmental variables with larger study area that identify the most important environmental forces which will drive by species distribution findings in this forest.

Comparative Learning based Deep Learning Algorithm for Abnormal Beat Detection using Imaged Electrocardiogram Signal (비정상심박 검출을 위해 영상화된 심전도 신호를 이용한 비교학습 기반 딥러닝 알고리즘)

  • Bae, Jinkyung;Kwak, Minsoo;Noh, Kyeungkap;Lee, Dongkyu;Park, Daejin;Lee, Seungmin
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.26 no.1
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    • pp.30-40
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    • 2022
  • Electrocardiogram (ECG) signal's shape and characteristic varies through each individual, so it is difficult to classify with one neural network. It is difficult to classify the given data directly, but if corresponding normal beat is given, it is relatively easy and accurate to classify the beat by comparing two beats. In this study, we classify the ECG signal by generating the reference normal beat through the template cluster, and combining with the input ECG signal. It is possible to detect abnormal beats of various individual's records with one neural network by learning and classifying with the imaged ECG beats which are combined with corresponding reference normal beat. Especially, various neural networks, such as GoogLeNet, ResNet, and DarkNet, showed excellent performance when using the comparative learning. Also, we can confirmed that GoogLeNet has 99.72% sensitivity, which is the highest performance of the three neural networks.

A Postscript of the Session Titled "Al-Mg Alloys Processes" in the 74th World Foundry Congress (제 74회 세계주조대회 "Al-Mg Alloys Processes" 세션을 마치며)

  • Seong-Ho Ha;Nam-Seok Kim;Young-Gil Jung;Seung-Yoon Yang;Kweon-Hoon Choi;Heon Kang;Bong-Hwan Kim;Young-Ok Yoon;Hyun-Kyu Lim;Shae-Kwang Kim;Franco Chiesa;David Levasseur;Jin-Kyu Lee;Sunki Kim;Dawid Kapinos;Boguslaw Augustyn;Bartłomiej Płonka;Sonia Boczkal;Jang Hum Yeon;Si Woo Lee;Jeong Hun Hong
    • Journal of Korea Foundry Society
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    • v.43 no.1
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    • pp.43-49
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    • 2023

An SPC-Based Forward-Backward Algorithm for Arrhythmic Beat Detection and Classification

  • Jiang, Bernard C.;Yang, Wen-Hung;Yang, Chi-Yu
    • Industrial Engineering and Management Systems
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    • v.12 no.4
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    • pp.380-388
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    • 2013
  • Large variation in electrocardiogram (ECG) waveforms continues to present challenges in defining R-wave locations in ECG signals. This research presents a procedure to extract the R-wave locations by forward-backward (FB) algorithm and classify the arrhythmic beat conditions by using RR intervals. The FB algorithm shows forward and backward searching rules from QRS onset and eliminates lower-amplitude signals near the baseline using a statistical process control concept. The proposed algorithm was trained the optimal parameters by using MIT-BIH arrhythmia database (MITDB), and it was verified by actual Holter ECG signals from a local hospital. The signals are classified into normal (N) and three arrhythmia beat types including premature ventricular contraction (PVC), ventricular flutter/fibrillation (VF), and second-degree heart block (BII) beat. This work produces 98.54% accuracy in the detection of R-wave location; 98.68% for N beats; 91.17% for PVC beats; and 87.2% for VF beats in the collected Holter ECG signals, and the results are better than what are reported in literature.

The Unconstrained Sleep Monitoring System for Home Healthcare using Air Mattress and Digital Signal Processing (공기 매트리스와 디지털 신호처리를 이용한 홈헬스케어용 무구속 수면 모니터링 시스템)

  • Chee, Young-Joon;Park, Kwang-Suk
    • Proceedings of the IEEK Conference
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    • 2005.11a
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    • pp.493-496
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    • 2005
  • For home healthcare, the unconstrained measurement of physiological signal is highly required to avoid the inconvenience of users. The recording and analysis of the fundamental parameters during sleep like respiration and heart beat provide valuable information on his/her healthcare. Using the air mattress sensor system, the respiration and heart beat movements can be measured without any harness or sensor on the subject's body. The differential measurement technique between two air cells is adopted to enhance the sensitivity. The balancing tube between two air cells is used to increase the robustness against postural changes during the measurement period. The meaningful frequency range could be selected by the pneumatic filter with balancing tube. ECG (Electrocardiography) and respiration sensor (plethysmography) were measured for comparison with the signal from air mattress. To extract the heart beat information from air pressure sensor, digital signal processing technique was used. The accuracy for breathing interval and heart beat monitoring was acceptable. It shows the potentials of air mattress sensor system to be the unconstrained home sleep monitoring system.

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