Frequently, associated time series is an input time series, this is particularly true if changes in output tend to be anticipated by changes in input, in Vhich case we call it a "leading indicator" for output time series.

Through computing causality between a lot of precursors from input time series and a given anomaly from output time series, the method can be used to detect the precursor from datasets containing multivariate time series related to different security regimes of network system, and then produces the precursor rules and causality rules for actual attack detection and early warning with high confidence.

In group RF anaesthesia was induced with vecuronium 0. 1 mg/kg and propofol 1. 5 mg/kg followed by remifentanil 1. 0 given as a bolus over 30s(diluted to 20ml with saline) .

Liquid-phase flow pattern of loop device and liquid-phase local baclcmixing coefficient in the down-flow pipe have been investigated by signal response method with random wave shape input and curve fitting in the time domain.

The realization of FFT is based on 8096'S 4-byte floating point arithmetic function. In programming, the inverted input/decimation-in-time FFT algorithm and the 2-based arithmetic generally used are be chosen.

In this paper, a SVPWM signal generator is designed with VHDL. This signal generator can transform time signal into SVPWM trigger signal successfully with good anti-jamming capability.

it discriminated input time pattern to various degrees.

The manner in discrimination of input time pattern was dependent on the size of the unitary EPSP and the extent of the spontaneous firing activity, if it had.

Simultaneous identification of structural parameters and input time history from output-only measurements

The results demonstrate that the proposed method can accurately identify both the structural parameters and the input time history for the cases that the structural responses are not polluted or slightly contaminated by measurement noise.

The results are stored together with the input time and date.

In this paper, a high resolution technique for detecting the presence of frequency components of a narrow-band signal in the broad-band correlated noise is examined. It is based on the fact that the correlation interval of a broad-band noise is much smaller than that of a narrow-band signal. When the time lag of the autocorrelation function of the input is larger than the correlation interval of the broad-band noise, the effect of broad-band noise is negligible. Therefore, the measured autocorrelation function...

In this paper, a high resolution technique for detecting the presence of frequency components of a narrow-band signal in the broad-band correlated noise is examined. It is based on the fact that the correlation interval of a broad-band noise is much smaller than that of a narrow-band signal. When the time lag of the autocorrelation function of the input is larger than the correlation interval of the broad-band noise, the effect of broad-band noise is negligible. Therefore, the measured autocorrelation function of large time lag can be used to estimate the frequency components of the narrow-band signal. The basic procedures of the estimation is presented in the paper. Firstly, the autocorrelation function of large time lag is interpolated to the section of small time lag with complex exponential algorithm and the estimation of the autocorrelation function of small time lag for a narrow-band signal is obtained. The whole autocorrelation function is thus constructed from the measured section of large time lag and the estimated section of small time lag. Secondly, the autocorrelation function is extrapolated by using the maximum entropy method to obtain the weighting coefficients of the high-order prediction filter. Then the frequency, power and bandwidth of the components of the narrow-band signal can be estimated accurately. In order to yield high resolution, the high-order autocorrelation matrix is used, the number of the operations for the estimation of frequency and power is tremendous. An efficient method for significantly reducing the number of operation is suggested. In this method, frequency components of stronger power, instead of all components, are used to estimate the frequency accurately and the power approximately. Finally, a series of computer experiments is performed. As an example, the results for the parameter estimation of the line spectrum of sinusoids in broad-band noise are given. The computer simulation shows that spectral resolution of new method presented in this paper is higher than conventional spectral analysis.

Results obtained recently on the subject are presented here. A method of input identification in the frequency domain is given at the beginning, in which material nonlinearity is considered by an iteration process through equivalent linearizaticn. For strong nonlinearity, an equivalent multi-structure method is proposed with one equivalent structure cf higher natural frequencies to take care of the smaller-amplitude high-frequency vibration and another of lower natural frequencies to take care of the larger-amplitude...

Results obtained recently on the subject are presented here. A method of input identification in the frequency domain is given at the beginning, in which material nonlinearity is considered by an iteration process through equivalent linearizaticn. For strong nonlinearity, an equivalent multi-structure method is proposed with one equivalent structure cf higher natural frequencies to take care of the smaller-amplitude high-frequency vibration and another of lower natural frequencies to take care of the larger-amplitude low-frequency vibration of the structure.Problems on convergence-uniqueness and accuracy-error are illustrated through numerical examples using known solutions from numerical computations or shaking-table tests. These examples show that several sets of quite different initial nonlinear levels lead to the same result and quite close to the real. These examples show also that, even for very strong nonlinearity (ductility factor= 6-8), error is only about 10% in maximum acceleration and riot large in response spectrum, Error ccmes mainly frcm appreximation involved in equivalent linearization.

The initial results of observations on the effect of infusing glucose in various concentrations on blood glucose during operation are presented here. Thirty patients undergoing selected operations under extradural anesthesia were investigated in four randomized groups recieving different dosage of glucose infusion. We found that significant hyperglycemia and glycosuria were induced by the infusion of 500ml of 10% glucose in group Ⅰ and 500ml of 5% glucose in group Ⅱ within 30 minutes. However, group Ⅲ received...

The initial results of observations on the effect of infusing glucose in various concentrations on blood glucose during operation are presented here. Thirty patients undergoing selected operations under extradural anesthesia were investigated in four randomized groups recieving different dosage of glucose infusion. We found that significant hyperglycemia and glycosuria were induced by the infusion of 500ml of 10% glucose in group Ⅰ and 500ml of 5% glucose in group Ⅱ within 30 minutes. However, group Ⅲ received 25g glucose in concentrations from 1.67% to 2.5% within about 90 minutes, and the peak value of blood glucose was significantly lower than group Ⅱ. In group Ⅳ the blood glucose level was higher during operation than before, though they received Ringer's solution only. The results shows that surgical stress led to an increase in blood glucose during operation and it would be better that the concentration of glucose infusion ripidly infused during operation does not exceed 2.5%. If glucose of high concentration is necessary, insulin should be added.