• Title/Summary/Keyword: Quantitative parameters

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Automatic scoring system of EEG and quantitative evaluation of its visual interpretation

  • Nakamura, Masatoshi;Shibasaki, Hiroshi;Nishida, Shigeto
    • 제어로봇시스템학회:학술대회논문집
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    • 1989.10a
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    • pp.967-971
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    • 1989
  • A new system for automatic scoring of 'organization' of the EEG dominant rhythm was constructed and applied to 18 normal subjects and 15 patients. Organization parameters which best represented the 'organization' as judged by 5 neurologists' visual inspection were calculated and the automatic organization scoring was obtained by a linear regression of those organization parameters. Furthermore, values of the regression coefficients were used to study the characteristics of EEG interpretation by each neurologist, and this scoring technique can also be applied to the training of EEG interpretation.

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Quantitative representation for EEG interpretation and its automatic scoring

  • Nakamura, Masatoshi;Shibasaki, Hiroshi;Imajoh, Kaoru;Nishida, Shigeto;Neshige, Ryuji
    • 제어로봇시스템학회:학술대회논문집
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    • 1990.10b
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    • pp.1190-1195
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    • 1990
  • A new system for automatic interpretation of the awake electroencephalogram(EEG) was developed in this work. We first clarified all the necessary items for EEG interpretation in accordance with an analysis of visual inspection of the rhythms by a qualified electroencephalographer (EEGer), and then defined each item quantitatively. Concerning the automatic interpretation, we made an effort to find out specific EEG parameters which faithfully represent the procedure of visual interpretation by the qualified EEGer. Those specific EEG parameters were calculated from periodograms of the EEG time series. By using EEG data of 14 subjects, the automatic EEG interpretation system was constructed and compared with the visual interpretation done by the EEGer. The automatic EEG interpretation thus established was proved to be in agreement with the visual interpretation by the EEGer.

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Quantitative Interpretation of Cooling Rate of Clinker and It's Effects on the Cement Strength Development (클링커 냉각속도의 정량적 해석 및 냉각속도가 시멘트 강도발현에 미치는 영향고찰)

  • Kim, Chang-Bum;Choi, Sung-Churl
    • Journal of the Korean Ceramic Society
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    • v.44 no.4 s.299
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    • pp.224-229
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    • 2007
  • To evaluate the cooling rate of clinker quantitatively, several clinkers with different cooling rate were made in the laboratory. The X-ray diffraction pattern of Ferrite 002 reflection were measured and the parameters were calculated by using split type pseudo-Voigt function. The X-ray diffraction patterns of the Ferrite phase in the clinkers from cement manufacturing plant were analyzed by using the parameters and the analysis program was developed to calculate the cooling rate quantitatively. The cooling rate coefficients of the clinkers were calculated by using the profile fitting method of the program and the influence of cooling rate on strength was evaluated. The results show that there is a close relation between the cooling rate of clinker and the strength of cement.

Decision of Lubricated Friction Conditions for Materials of Automobile Transmission Gear Using Neural Network

  • Cho Yon-Sang;Park Heung-Sik
    • Journal of Mechanical Science and Technology
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    • v.20 no.5
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    • pp.583-590
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    • 2006
  • It is hard to inspect the state of lubrication of an automobile transmission visually. Thus, it is necessary to develop a new inspection method. Wear debris can be collected from the lubricants of an operating transmission of an automobile, and its morphology will be directly related to the friction condition of the interacting materials from which the wear debris originated in the lubricated transmission. In this study, wear debris in lubricating oil are extracted by membrane filter $(0.45{\mu}m)$, and the quantitative values of shape parameters of wear debris are calculated by digital image processing. These shape parameters are studied and identified by an artificial neural network algorithm. The results of the study may be applicable to the prediction and diagnosis of the operating condition of transmission gear.

RBF Network Based QFT Parameter-Scheduling Control Design for Linear Time-Varying Systems and Its Application to a Missile Control System (시변시스템을 위한 RBF 신경망 기반의 QFT 파라미터계획 제어기법과 alt일 제어시스템에의 적용)

  • 임기홍;최재원
    • 제어로봇시스템학회:학술대회논문집
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    • 2000.10a
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    • pp.199-199
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    • 2000
  • Most of linear time-varying(LTV) systems except special cases have no general solution for the dynamic equations. Thus, it is difficult to design time-varying controllers in analytic ways, and other control design approaches such as robust control have been applied to control design for uncertain LTI systems which are the approximation of LTV systems have been generally used instead. A robust control method such as quantitative feedback theory(QFT) has an advantage of guaranteeing the stability and the performance specification against plant parameter uncertainties in frozen time sense. However, if these methods are applied to the approximated linear time-invariant(LTI) plants which have large uncertainty, the designed control will be constructed in complicated forms and usually not suitable for fast dynamic performance. In this paper, as a method to enhance the fast dynamic performance, the approximated uncertainty of time-varying parameters are reduced by the proposed QFT parameter-scheduling control design based on radial basis function (RBF) networks for LTV systems with bounded time-varying parameters.

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A Digital Signal Processing System for Analysis of Skeletal Muscle EMG Signal (골격근의 근전도 신호 분석을 위하 디지탈 신호처리 시스템의 설계)

  • 전철완
    • Journal of Biomedical Engineering Research
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    • v.17 no.2
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    • pp.155-164
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    • 1996
  • In the clinical environment, measurements of some characteristics of the skeletal muscle are currently used to assess the severity of a neuromuscular disease or in some cases to assist in making a diagnosis. But a quantitative method of evaluation has not yet been introduced satisfactorily. In this paper, the skeletal EMG(biceps muscle, masseter muscle) analysis has been processed both in the time and in the frequency domain by designing the digital signal processing system based on pentium PC and transputer (IMS 7805). The experiment have been performed in five normal subjects, and various parameters have been statistically tested and compare4 As a results, the effective parameters obtained for the evaluation of skeletal EMG electrical activity are turn analysis, MiTi, MiTa, IEMG, PDF in the time domain, and are mean frequency, median frequency, skewness, kurtosis, muscle fatigue slope in the frequency domain. The designed H/W and S/W in this study can be used effectively for the establishment of EMG data base and for clinical research.

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Detection of Grinding Troubles Utilizing a Neural Network (Neural Network을 이용한 연삭가공의 트러블 검지)

  • 곽재섭;송지복;김건희;하만경;김희술;이재경
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 1994.10a
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    • pp.131-137
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    • 1994
  • Detection of grinding trouble occuring during the grinding process is classified into two types, i.e, based on the quantitative and qualitative knowledge. But, since the grinding operation is especially related with a large amount of functional parameters, it is actually defficult to cope with the grinding troubles occuring during process. Therefore, grinding trouble-shooting has difficulty in satisfying the requirement from the user. To cope with the grinding troubles occuring during the process, the application of neural network is on effective way. In this study, we identify the four parameters derived from the AE(Acoustic Emission) signals and present the grinding trouble-shooting system utilizing a back-propagation model of the neural network.

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A Study on Recognition of Operating Condition for Hydraulic Driving Members (유압구동 부재의 작동조건 식별에 관한 연구)

  • 조연상;류미라;김동호;박흥식
    • Journal of the Korean Society for Precision Engineering
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    • v.20 no.4
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    • pp.136-142
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    • 2003
  • The morphological analysis of wear debris can provide early a failure diagnosis in lubricated moving system. It can be effective to analyze operating conditions of oil-lubricated tribological system with shape characteristics of wear debris in a lubricant. But, in order to predict and recognize an operating condition of lubricated machine, it is needed to analyze and to identify shape characteristics of wear debris. Therefore, If the morphological characteristics of wear debris are recognized by computer image analysis using the neural network algorithm, it is possible to recognize operating condition of hydraulic driving members. In this study, wear debris in the lubricating oil are extracted by membrane filter (0.45 ${\mu}{\textrm}{m}$), and the quantitative values of shape parameters of wear debris are calculated by the digital image processing. This shape parameters are studied and identified by the artificial neural network algorithm. The result of study could be applied to prediction and to recognition of the operating condition of hydraulic driving members in lubricated machine systems.

Analyses of Fracture Parameters and Prediction of Crack Propagation Path on Delamination in the LSI Package (반도체 패키지의 층간박리 파괴역학인자 해석 및 균열진전경로 예측)

  • Chung, Nam-Yong;Park, Cheol-Hee
    • Journal of the Korean Society of Manufacturing Technology Engineers
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    • v.18 no.4
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    • pp.401-409
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    • 2009
  • This paper presents a method of calculating the stress intensity factor (K) and crack propagation direction (${\theta}_0$) at the crack-tip that is associated with delamination in the large scale integration(LSI) package. To establish a reasonable strength evaluation method and life prediction, it is necessary to assess fracture parameters under various fracture conditions. Therefore, we conducted quantitative stress singularity analysis considering thermal stress simulating the changes of crack length (a), (h) and (v) in delamination using the 2-dimensional elastic boundary element method (BEM), and from these results predicted crack propagation direction and path.

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Quantitative Assessment of Variation in Poroelastic Properties of Composite Materials Using Micromechanical RVE Models

  • Han, Su Yeon;Kim, Sung Jun;Shin, Eui Sup
    • International Journal of Aeronautical and Space Sciences
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    • v.17 no.2
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    • pp.175-183
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    • 2016
  • A poroelastic composite material, containing different material phases and filled with fluids, serves as a model to formulate the overall ablative behaviors of such materials. This article deals with the assessment of variation in nondeterministic poroelastic properties of two-phase composite materials using micromechanical representative volume element (RVE) models. Considering the configuration and arrangement of pores in a matrix phase, various RVEs are modeled and analyzed according to their porosity. In order to quantitatively investigate the effects of microstructure, changes in effective elastic moduli and poroelastic parameters are measured via finite element (FE) analysis. The poroelastic parameters are calculated from the effective elastic moduli and the pore-pressure-induced strains. The reliability of the numerical results is verified through image-based FE models with the actual shape of pores in carbon-phenolic ablative materials. Additionally, the variation of strain energy density is measured, which can possibly be used to evaluate microstress concentrations.