• Title/Summary/Keyword: analytic signal

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A Cell Phone-based ECG, Blood Pressure Monitoring System for Personal Healthcare Applications using Wireless Sensor Network Technology

  • Toh, Sing-Hui;Lee, Seung-Chul;Chung, Wan-Young
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2008.05a
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    • pp.505-508
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    • 2008
  • Electrocardiogram (ECG) and blood pressure (BP) are main vital signs which are the standards in most medical settings in assessing the most basic body functions. Multi parameters are desired in providing more information for health professionals in order to detect or monitor medical problems of patients more precisely. This study urges us to develop a robust wireless healthcare monitoring system which has multiple physiological signs measurements on real time that applicable to various environments which integrates wireless sensor network technology and code division multiple access (CDMA) network with extended feature of locally standalone diagnosis algorithms that implemented in tell phone. ECG signal and BP parameter of the patients are routinely be monitored, processed and analyzed in details at cell phone locally to produce useful medical information to ease patients for tracking and future reference purposes. Any suspected or unknown patterns of signals will be immediately forwarded to hospital server using cell phone for doctors' evaluation. This feature enables the patients always recognize the importance of self-health checking so that the preventive actions can be taken earlier through this analytic information provided by this monitoring system because "Prevention is better than Cure".

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VALIDATION OF ON-LINE MONITORING TECHNIQUES TO NUCLEAR PLANT DATA

  • Garvey, Jamie;Garvey, Dustin;Seibert, Rebecca;Hines, J. Wesley
    • Nuclear Engineering and Technology
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    • v.39 no.2
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    • pp.133-142
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    • 2007
  • The Electric Power Research Institute (EPRI) demonstrated a method for monitoring the performance of instrument channels in Topical Report (TR) 104965, 'On-Line Monitoring of Instrument Channel Performance.' This paper presents the results of several models originally developed by EPRI to monitor three nuclear plant sensor sets: Pressurizer Level, Reactor Protection System (RPS) Loop A, and Reactor Coolant System (RCS) Loop A Steam Generator (SG) Level. The sensor sets investigated include one redundant sensor model and two non-redundant sensor models. Each model employs an Auto-Associative Kernel Regression (AAKR) model architecture to predict correct sensor behavior. Performance of each of the developed models is evaluated using four metrics: accuracy, auto-sensitivity, cross-sensitivity, and newly developed Error Uncertainty Limit Monitoring (EULM) detectability. The uncertainty estimate for each model is also calculated through two methods: analytic formulas and Monte Carlo estimation. The uncertainty estimates are verified by calculating confidence interval coverages to assure that 95% of the measured data fall within the confidence intervals. The model performance evaluation identified the Pressurizer Level model as acceptable for on-line monitoring (OLM) implementation. The other two models, RPS Loop A and RCS Loop A SG Level, highlight two common problems that occur in model development and evaluation, namely faulty data and poor signal selection

Internal Aerodynamic Noise from Quick Opening Throttle Valve (쓰로틀 밸브의 빠른 열림 동작에 의한 내부공력소음)

  • 정철웅;김성태;김재헌;이수갑
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.14 no.4
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    • pp.310-318
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    • 2004
  • For many industrial problems originating from aerodynamic noise, noise prediction techniques, reliable and easy to apply, would be of great value to engineers and manufacturers. General algorithm is presented for the prediction of internal flow-induced noise from quick opening throttle valve in an automotive engine. This algorithm is based on the integral formula derived by using the General Green Function, Lighthill's acoustic analogy and Curle's extension of Lighthill's. Novel approach of this algorithm is that the integral formula is so arranged as to predict frequency-domain acoustic signal at any location in a duct by using unsteady flow data in space and time, which can be provided by the Computational Fluid Dynamics Techniques. This semi-analytic model is applied to the prediction of internal aerodynamic noise from a throttle valve in an automotive engine. The predicted noise levels from the throttle valve show good agreement with actual measurements. The results show that the dipole noise is dominant in this phenomena and the origin of noise sources is attributed to the anti-vortex lines formed in the down-stream from a throttle valve. This illustrative computation shows that the current method permits generalized predictions of flow noise generated by bluff bodies and turbulence in flow ducts.

Study on critical point of ZnCdSe by using Fourier analysis (Fourier 변환을 이용한 ZnCdSe 전이점 연구)

  • Yoon, J.J.;Ghong, T.H.;Kim, Y.D.
    • Journal of the Korean Vacuum Society
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    • v.16 no.6
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    • pp.458-462
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    • 2007
  • Spectroscopic ellipsometry is an excellent technique for determining dielectric function. To obtain critical point energy, standard analytic critical point expression is used conventionally for second derivatives of dielectric function which might increase high frequency noise than signal. However, reciprocal-space analysis offers several advantages for determining critical point parameters in optical and other spectra, for example the separation of baseline, information, and high frequency noise in low-, medium-, high-index Fourier coefficient, respectively. We used reciprocal Fourier analysis for removing noise and determining critical point of ZnCdSe alloy.

A Comparative Analysis of Edge Detection Methods in Magnetic Data

  • Jeon, Taehwan;Rim, Hyoungrea;Park, Yeong-Sue
    • Journal of the Korean earth science society
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    • v.36 no.5
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    • pp.437-446
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    • 2015
  • Many edge detection methods, based on horizontal and vertical derivatives, have been introduced to provide us with intuitive information about the horizontal distribution of a subsurface anomalous body. Understanding the characteristics of each edge detection method is important for selecting an optimized method. In order to compare the characteristics of the individual methods, this study applied each method to synthetic magnetic data created using homogeneous prisms with different sizes, the numbers of bodies, and spacings between them. Seven edge detection methods were comprehensively and quantitatively analyzed: the total horizontal derivative (HD), the vertical derivative (VD), the 3D analytic signal (AS), the title derivative (TD), the theta map (TM), the horizontal derivative of tilt angle (HTD), and the normalized total horizontal derivative (NHD). HD and VD showed average good performance for a single-body model, but failed to detect multiple bodies. AS traced the edge for a single-body model comparatively well, but it was unable to detect an angulated corner and multiple bodies at the same time. TD and TM performed well in delineating the edges of shallower and larger bodies, but they showed relatively poor performance for deeper and smaller bodies. In contrast, they had a significant advantage in detecting the edges of multiple bodies. HTD showed poor performance in tracing close bodies since it was sensitive to an interference effect. NHD showed great performance under an appropriate window.

Auditory Representations for Robust Speech Recognition in Noisy Environments (잡음 환경에서의 음성 인식을 위한 청각 표현)

  • Kim, Doh-Suk;Lee, Soo-Young;Kil, Rhee-M.
    • The Journal of the Acoustical Society of Korea
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    • v.15 no.5
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    • pp.90-98
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    • 1996
  • An auditory model is proposed for robust speech recognition in noisy environments. The model consists of cochlear bandpass filters and nonlinear stages, and represents frequency and intensity information efficiently even in noisy environments. Frequency information of the signal is obtained by zero-crossing intervals, and intensity information is also incorporated by peak detectors and saturating nonlinearities. Also, the robustness of the zero-crossings in estimating frequency is verified by the developed analytic relationship of the variance of the level-crossing interval perturbations as a function of the crossing level values. The proposed auditory model is computationally efficient and free from many unknown parameters compared with other auditory models. Speaker-independent speech recognition experiments demonstrate the robustness of the proposed method.

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SPREADING FACTOR SELECTION FOR RETRANSMISSIONS OF NON-REAL TIME DATA IN DS/CDMA SYSTEMS

  • Lee, Inho;Jeongmin Bae;Sungchae Na;Kim, Dongwoo
    • Proceedings of the IEEK Conference
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    • 2003.07a
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    • pp.230-233
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    • 2003
  • In this paper, it is shown that, in DS/CDMA mobile systems, halving or doubling the spreading factor (HSF or DSE) when retransmission is requested possibly improves the throughput. Given transmit power, DSF essentially decreases probability of packet error (PPE) by increasing the signal energy per information bit. It, however, doubles the time duration needed for transmitting the original packet. On the other hand, HSF increases PPE. It, however halves the time duration required to carry the original packet. Thus, the efficiency of HSF or DSF as a retransmission strategy depends on the amount of increased or reduced PPE after HSF or DSF is selected. With achieving given residual error probability (REP) in CDMA systems, the effective throughput is evaluated in this paper to find conditions with which HSF or DSF achieves better performance than using the original one. Analytic results show that HSF or DSF performs better when relatively small or big changes in their PPE's are present, respectively.

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A Study on the Forming Conditions of a Forging Piston by using the Finite Element Simulation and the Taguchi Method (유한요소해석과 다구찌방법을 이용한 단조피스톤의 성형조건 연구)

  • You, Ho-Young
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.13 no.5
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    • pp.1990-1995
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    • 2012
  • This paper presents design methodology to determine the design parameters that affect the manufacture of aluminum forging piston using the FE simulation and the Taguchi method. Maximum forging load is used as the objective function, and preform, material temperature and draft angle are selected as the design parameters. Their combinations are implemented by orthogonal array, and forging load is evaluated through the simulation. From the analytic results of design parameters to minimize the load using signal to noise ratio, their optimal combinations are proposed. The proposed design methodology will be able to help in selecting proper preform among preforms and to be used in determining the optimal combination of the parameters in metal forming process.

Development of Hybrid Method for the Prediction of Internal Flow-induced Noise and Its Application to Throttle Valve Noise in an Automotive Engine

  • Cheong, Cheol-Ung;Kim, Sung-Tae;Kim, Jae-Heon;Lee, Soo-Gab
    • The Journal of the Acoustical Society of Korea
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    • v.22 no.4E
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    • pp.183-196
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    • 2003
  • General algorithm is developed for the prediction of internal flow-induced noise. This algorithm is based on the integral formula derived by using the General Green Function, Lighthill's acoustic analogy and Curl's extension of Lighthill's. Novel approach of this algorithm is that the integral formula is so arranged as to predict frequency-domain acoustic signal at any location in a duct by using unsteady flow data in space and time, which can be provided by the Computational Fluid Dynamics Techniques. This semi-analytic model is applied to the prediction of internal aerodynamic noise from a throttle valve in an automotive engine. The predicted noise levels from the throttle valve are compared with actual measurements. This illustrative computation shows that the current method penn its generalized predictions of flow noise generated by bluff bodies and turbulence in flow ducts.

AM-FM Decomposition and Estimation of Instantaneous Frequency and Instantaneous Amplitude of Speech Signals for Natural Human-robot Interaction (자연스런 인간-로봇 상호작용을 위한 음성 신호의 AM-FM 성분 분해 및 순간 주파수와 순간 진폭의 추정에 관한 연구)

  • Lee, He-Young
    • Speech Sciences
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    • v.12 no.4
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    • pp.53-70
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    • 2005
  • A Vowel of speech signals are multicomponent signals composed of AM-FM components whose instantaneous frequency and instantaneous amplitude are time-varying. The changes of emotion states cause the variation of the instantaneous frequencies and the instantaneous amplitudes of AM-FM components. Therefore, it is important to estimate exactly the instantaneous frequencies and the instantaneous amplitudes of AM-FM components for the extraction of key information representing emotion states and changes in speech signals. In tills paper, firstly a method decomposing speech signals into AM - FM components is addressed. Secondly, the fundamental frequency of vowel sound is estimated by the simple method based on the spectrogram. The estimate of the fundamental frequency is used for decomposing speech signals into AM-FM components. Thirdly, an estimation method is suggested for separation of the instantaneous frequencies and the instantaneous amplitudes of the decomposed AM - FM components, based on Hilbert transform and the demodulation property of the extended Fourier transform. The estimates of the instantaneous frequencies and the instantaneous amplitudes can be used for modification of the spectral distribution and smooth connection of two words in the speech synthesis systems based on a corpus.

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