This paper discusses an elevator monitoring system based on embedded system and the internet of things. Through multi-sensor information acquisition, much information can be accessed to such as vibration, acceleration, speed, running noise,direction,floor station,door switch of the elevator car and power supply voltage,current, temperature of the traction machine,at the same time the noise and the temperature of the computer room with the information if there is anyone in the elevator, etc.. WinCE operating system is ported to the master control chip S3C2410 of ARM9 architecture,and a WAN connection between the elevator parameter monitoring terminals and the remote control center is established to realize the centralized monitoring and automatic remote failure alarm for the elevator operation. This system provides technical support for elevator safety regulation and the practical running results is satisfactory.

The read-write process in perpendicular magnetic recording channels includes a number of nonlinear effects. Nonlinear transition shift (NLTS) arising from previously written transitions is one of these. The signal distortion induced by NLTS is reduced by use of write precompensation during data recording. In this paper, we numerically evaluate the effect of NLTS on the read-back signal by using the model proposed by Bertram and Nakamoto. By means of computer simulation, we examine the effectiveness of two write precompensation schemes in combating NLTS effects in a channel characterized by both transition jitter noise and additive white Gaussian electronics noise. We numerically optimize the precompensation schemes according to channel bit-error-rate, as well as more computationally tractable criteria. Our results suggest that a write-precompensation technique with as few as two adjustable parameters can be very effective against NLTS effects.

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The principle and implementation steps of the method of feature extraction of weak multi-frequency signal based on the array of modulated stochastic resonance under the background of strong noise are described in the paper. By the modulation of the known multi-frequency weak signals under the strong noise background and the carrieres with different frequency respectively; multiple signals with the same frequency of 0.01Hz were generated. Then these generated signals were as the input signals of multiple parallel non-coupled resonant units. The Runge-Kutta algorithm was used to obtain the unit outputs and to analysis the frequency spectrum. According to the SNR of the 0.01Hz to determine whether the 0.01Hz frequency components were contained in the frequency spectrum. Finally the frequency characteristic vectors of the weak signals were generated by the systemization of the detection results of the stochastic resonance units.Results show that this method has obvious effect in the extraction of the feature of the weak multi-frequencies signals, and has a very good application prospect.

In order to make a numerical simulation of the chaos in standing wave lasers, a dynamic equation that is feasible to mathematical evaluation is required. There is a summation symbol in the well known Haken laser equation, and it results in a tremendously heavy quantity of evaluation. In order to simplify the evaluation, the light field in the Haken laser equation was expanded in the standing wave form. Two macroscopic variables were brought in to eliminate the summation symbol in terms of single mode and homogeneously broadening. Therefore, a simplified Maxwell-Bloch equation was gained. Then by normalizing, a new equation was obtained. This equation is in a simple form. Its every variable has unambiguous meaning and every coefficient is only related to gain or dissipation and is easy to obtain. Moreover, the equation is used in two MATLAB numerical simulations of a CO2laser and a chaotic attractor is obtained. So the equation could be a mathematical model in numerical simulations of standing wave laser chaos.