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Human activities are usually collective, so clustering has become an important feature of human behavior. This paper studied the evolution of the community in the process of public opinion propagation so as to put forward a public opinion evolution model for the network community number. This study proposed the community number evolution model of public opinion based on stochastic competitive learning, and the proposed model consists of an increase in the number of communities and a decrease in the number of communities. The highlight of this model is that on the one hand, it realizes the research on the evolution of public opinions on the dynamic network; on the other hand, unlike other public opinion evolution models, this model pays attention to the community number increase and decrease rules in the evolution of public opinions. Then, as an extension of the community number evolution model of public opinion, the community number prediction model had been proposed. Based on Twitter data from the 2017 London Bridge attack, the proposed models were validated by experiments. In the verification section of this paper, two methods had been introduced as a comparison. The experimental results show that the community number evolution model of public opinion is correct.

In this paper, the measurement ability of high precision data acquisition unit to measure impulse voltage waveform is evaluated. The transmission characteristics of RC hybrid attenuator with high input impedance are systematically studied. A high precision attenuator with attenuation ratio of 200 is developed. The standard digital recorder for impulse voltage measurement is established according to the standard requirements. Through the matching of the attenuator parameters, the system step response rise time is less than 5 ns. After calibration by the calibrator, system peak voltage measurement uncertainty is $0.2\%(k=2)$ , the front time measurement uncertainty is 0.9% ( $k=2$ ), and the half-peak time measurement uncertainty is 0.5% ( $k=2$ ). The research results show that the performance of the standard digital recorder established in this paper is better than the requirements of IEC 61083–1 for standard measuring instruments, which lays the foundation for establishing a standard device for impulse voltage measurement in China.

In order to achieve real-time and accurate data mining, this paper proposes a data association rules mining method based on RBF neural network optimization algorithm. On the basis of considering the constraint association rules, the data frequent itemsets are reduced to get the corresponding candidate data sets that meet the rules, and the update of the data frequent itemsets for user needs is completed. The candidate data set is input to RBF neural network for training, the network output is optimized by combining with rough set theory, the user demand data table and quadruple are constructed, the user demand attributes are described, and the user demand data is obtained by using upper bound pruning method. Through the upper bound pruning method, the user demand data is obtained and real-time mining is realized. Compared with other data mining algorithms, the simulation results show that the performance of the data mining algorithm proposed in this paper is less constrained by the proportion of redundant data and the size of data, the accuracy of data mining is higher, and it has better stability.

Predicting human mobility plays an important role in urban planning and functional zoning. In this paper, we propose a model for predicting the user's next check-in location where indicates that this user is about to arrive at the place based on Sina Weibo check-in data. In our prediction model, the activities are first extracted from the check-in data, then we further classify user's activities using K-Medoids and DBSCAN hybrid algorithm. Finally, we utilize Markov Chain model and our proposed activity detection method to predict the activity category of the user's next check-in location, then further predict the most likely places according to the predicted activity category. The advantage of this model is that we can reduce the prediction space and further improve the accuracy of predicting the next location. Through relevant experimental verification, we not only obtain relatively high activity category prediction accuracy, but also could predict the users' next arrival location conveniently and mobile trends.

Electrical capacitance volume tomography(ECVT) is a simple-structure and low-cost imaging technique. ECVT is used to reconstruct an image of the permittivity distribution in the three-dimensional(3-D) domain with the limited capacitance measurements and sensitivity map by a suitable reconstruction algorithm. We can get the predicted image of higher resolution by improving the sensitivity map and the capacitance value and image reconstruction methods. In this paper, we contrast the quality of the reconstruction image between ECVT system and adaptive electrical capacitance volume tomography(AECVT) system. The experiment sensors used for comparison are the same size but different plates: conventional and synthetic which are both excited by single voltage. Then, we investigate the effect of different voltage envelopes on the quality of reconstruction image in AECVT. The examples are presented to demonstrate that AECVT system is slightly superior to ECVT system for single voltage excitation. Further more, for AECVT system, it can improve the 3-D reconstruction performance by using voltage excitations of multiple amplitudes and changing the voltage position.

A 340GHz modulator based on double-layer metal hole arrays was presented in this paper. The controllable permittivity of nematic liquid crystals is utilized to realize a tunable THz transmittance. The transmission characteristics of the terahertz electromagnetic waves and following LC parameters have been calculated and analyzed. At 340GHz, modulator achieves an intensity modulation depth of 91.3% by changing LC permittivity. The effect of the incident angle of plane wave on the 340GHz transmittance has been simulation. The results of numerical simulation show that the transmittance still can be effective modulated at electromagnetic wave oblique incidence, when E→ is parallel to the surface of the metal layer.