The CODCr removal rates of the first,the second filter and the system are respectively and stably above the level of 60%,30%,80%; they are a little lower than those of the same loading before the stop-running,which are 68%,40%,90%.

Relying on the only α,β measure system,the α,β counts per three minutes in the sample of the first and second filter are worked out,so is the decay constant-00199,00201.After the revision of the values in the second layer,the filtering efficiency is about 87%.

The biomass attached to filter media and its biological performances during the startup are analyzed. The results demonstrate that the compound startup can shorten the startup time and removal rate of COD stays at over 80% in seven days from the startup, furthermore it can shorten the startup time in the first column and accelerate accumulation rates of nitro bacteria in the second filter column with 73.2% of the removal rate of NH 3N.

The second filter also transmits the Thomson continuum through its spectral window, so that the Balmer images contain Thomson contamination.

Two of these patients had no further filter manipulation, three had a second filter placed under fluoroscopic guidance, and the most recent five had filters retrieved and repositioned under fluoroscopic guidance.

A second filter, was placed in the infrarenal vena cava in both cases.

A mechanism for sharpening of the frequency selectivity or an unknown "second filter" is therefore assumed to exist in the cochlea.

Its significance for models of the second filter and cochlear nonlinearity is discussed.

Based upon the nonzero mean-value time correlation model,a sliding acceleration meanvalue model and algorithm using two Kalman filters in series is put forward.The first filter is designed to cope with all possible target maneuvers and gives out a sliding mean-value of acceleration. Using the sliding mean-value as the input,the parameter of the second filter can be controlled adaptively to match the real states of the maneuvering target. This method widen the changable range of target maneuvering acceleration...

Based upon the nonzero mean-value time correlation model,a sliding acceleration meanvalue model and algorithm using two Kalman filters in series is put forward.The first filter is designed to cope with all possible target maneuvers and gives out a sliding mean-value of acceleration. Using the sliding mean-value as the input,the parameter of the second filter can be controlled adaptively to match the real states of the maneuvering target. This method widen the changable range of target maneuvering acceleration with high-precision of state estimation comparing with the ordinary non7ero mean-value time correlation model,such as"current"model.There are also no problems of the correlated measurement noise and correlated estimates of the two filters in early research work.Results from computer simulations are included to demonstrate the performance.

The NWP fields of T.H.U.V. of NMC's T63, T106 and ECMWF's numerical model were separtely interpoleted into 108 meteorological stations. The interpoleted results were used as predicting factors to establish predicting equations of max. and min. tempreture by means of PPM, MOS and KF filter methods. With the above predicted results, the second filter consensus forecast and perfect consensus forecast were made, and the Temperatute Forecasting System for Every County by the provincial meteorological observatory...

The NWP fields of T.H.U.V. of NMC's T63, T106 and ECMWF's numerical model were separtely interpoleted into 108 meteorological stations. The interpoleted results were used as predicting factors to establish predicting equations of max. and min. tempreture by means of PPM, MOS and KF filter methods. With the above predicted results, the second filter consensus forecast and perfect consensus forecast were made, and the Temperatute Forecasting System for Every County by the provincial meteorological observatory based on the NWP product was developed. The operational practics from June to November in 1997 proved that the system showed good predicting results.

The earthquake ground motion is modeled as a twice filtered gaussian white noise random process with zero mean. The high frequency content of the white noise is reduced by the first filter;the low frequency content of the white noise is cut down by the second filter. On the basis of power spectra of earthquake records,the parameters of the power spectral density function of the twice filtered Gaussian white noise random process are determined by using the least -squares procedure of a nonlinear...

The earthquake ground motion is modeled as a twice filtered gaussian white noise random process with zero mean. The high frequency content of the white noise is reduced by the first filter;the low frequency content of the white noise is cut down by the second filter. On the basis of power spectra of earthquake records,the parameters of the power spectral density function of the twice filtered Gaussian white noise random process are determined by using the least -squares procedure of a nonlinear function.