Dynamic angular velocity modeling and error compensation of VG095M in the whole temperature range, based on a radial basis function (RBF) neural network, is presented in this paper. With gyro output voltage and environmental temperature as the input and angular velocity as the output, an RBF neural network model is established. The model is trained and validated by the experiment data. The fitting error of the model is 4.3818 × 10−6 deg s−1, which shows that the model has high precision. The experiment data except the data used for modeling were processed with this model. The results show that the maximum, minimum and mean square error of the angular velocity were reduced to 4.6%, 4.3% and 4.7% respectively after compensation.

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With the development of information technology, health management and big data have risen and developed in recent years. Big data need proper analysis and shape in order to extract meaningful information from it. This paper analyzes the application status and prospects of big data in the field of health management. The results show that the most widely used big data in health management are intelligent wearable devices. Big data applications in football players’ mental health monitoring systems and chronic disease health management systems also have a good prospect. The intelligent wearable device is applied to several aspects of sports work: teaching and sports training, real-time monitoring of football players’ physical exercise process, collecting football players’ heart rate, calorie consumption, exercise steps, and track, blood pressure, blood oxygen, and other physical exercise data; through monitoring the heart rate, we can get the intensity and duration of football players’ physical exercise in school; through the calculation, we can also get the football players’ time energy consumption and understand the overall situation of football players’ physical exercise in school; through step counting and track monitoring, we can master the number of steps and track of football players; by monitoring the changes of blood oxygen and blood pressure of football players, we need to build a third-party residents’ health information storage and analysis system and further realize the marketization of residents’ health big data. The experimental results of the proposed study show the effectiveness of the proposed work.

SrS:Ce thin films have been grown by gas source molecular beam epitaxy (GSMBE). The growth conditions have been systematically investigated as a function of growth temperature, sulfur to strontium flux ratio, and cerium flux. Single crystal SrS and high quality SrS:Ce were successfully grown on GaAs and glass substrates, respectively, without post-annealing process at temperature as low as 600~ It was found that the electroluminescence (EL) performance was greatly improved by addition of ZnS during the growth.