An Improved NID Steganography Method for Low Bitrate Speech on VoIP

In the procedure of encoding process on low bitrate speech, fixed codebook division is an efficient and promising embedding method for steganography. An improved neighbor index division (NID) steganography method based on the high bitrate frame of G.723.1 codec (6.3kbit/s) is proposed, which employs the parity and low distortion of neighbor indices for G.723.1 fixed codebooks. Differing from previously NID method which performs quantized index modulation (QIM) beforehand, the proposed method divides codeword indices into separate sub-codebooks according to the secret message bits dynamically in the original G.723.1 codec quantization period. Compared with existing NID method, our proposed method doesn’t need to divide the codebook before the encoding starts. The embedding and codebook dividing happen simultaneously, which utilizes the characteristics of specific secret message bits. The experiment results show that the proposed method has a much lower quality degradation for the decoding speech and still fulfills the low latency requirement for communication.

Investigation on the Application Value of Infrared Forehead Temperature Gun in Body Temperature Screening of New Crown Epidemic

The outbreak of the novel coronavirus pneumonia has had a great impact on the life safety of our people and social production activities. Therefore, it is very important and meaningful to analyze the application value of infrared forehead thermometers in body temperature screening under the new crown pneumonia epidemic and propose improved measures for body temperature detection. This paper summarizes the questionnaire on the application value of infrared forehead thermometer in body temperature screening and the results of staff interviews, and analyzes the principle of infrared forehead thermometer temperature measurement to explain the factors that affect the accuracy of temperature measurement results. Finally, it is concluded that the reflected radiation of the environment and the temperature measurement distance affect the accuracy of the temperature measurement results of the infrared forehead gun.

A Clustering Analysis Method for Massive Music Data

Clustering analysis plays a very important role in the field of data mining, image segmentation and pattern recognition. The method of cluster analysis is introduced to analyze NetEYun music data. In addition, different types of music data are clustered to find the commonness among the same kind of music. A music data-oriented clustering analysis method is proposed: Firstly, the audio beat period is calculated by reading the audio file data, and the emotional features of the audio are extracted; Secondly, the audio beat period is calculated by Fourier transform. Finally, a clustering algorithm is designed to obtain the clustering results of music data.

Design and Implementation of Mobile Intelligent Hidden Danger Inspection System

With the increasing development of Internet technology, computer Internet, intelligent terminal, cloud computing and other new technologies continue to emerge. All kinds of app based on mobile intelligent terminal are widely used because of its convenience and intelligence. However, for the safety of the coal industry, how to use these technologies based on mobile intelligent terminal to establish a set of efficient long-term mechanism of safety inspection and risk control is a necessary method to upgrade the safety management mode. Therefore, in order to meet the requirements of hidden danger investigation and management, this paper designs an intelligent hidden danger investigation and management system. Based on Ionic, the system constructs a cross platform mixed mode mobile app development framework. The paper shows that the system can realize the basic hidden danger investigation requirements.

Product Promotion Prediction Model Based on Evaluation Information

This paper mainly studies the impact of evaluation information on e-commerce platform on the future of products. Through natural language processing and rating, an evaluation model based on user rating and evaluation is defined to measure product quality. Among them, evaluations are differentiated: review sentiment coefficient (R) and review length (L).The evaluation model is:D=0.3*S+0.7*( 0.3*L+0.7*R). In order to predict the future reputation of products, based on the above evaluation model, time series is used to rank the products studied. Each customer purchases the product through Markov chain model, so as to predict the probability of future word-of-mouth spread of the product. Use TOPSIS method to select monthly sales, stars and comment sentiment coefficient as indicators. The comprehensive measurement method based on text and score is determined to predict whether the product is successfully promoted.

Impact of Photovoltaics

Photovoltaics (PV) can convert sunlight into electricity by making use of the photovoltaic effect. Solar panels consist of photovoltaic cells made of semiconductor materials (such as silicon) to utilise the photovoltaic effect and convert sunlight into direct current (DC) electricity. Nowadays, PV has become the cheapest electrical power source with low price bids and low panel prices. The competitiveness makes it a potential path to mitigate the global warming. In this paper, we investigate the relationship of PC array output with irradiance and temperature, the performance of PV array over 24 hours period, and the simulation of PV micro grid by MATLAB simulation.

Trends of Robot Application——Ethical Response

With the rapid development of science and technology and the arrival of the information age, computer technology has also gained rapid development, and has a very wide application prospect in the current social environment. But at the same time, robots may also induce a variety of ethical problems, the existence of these ethical problems also affect the sustainable development of robots. This paper mainly aims at the change of robot application trend and related ethical issues, hoping to provide some reference for robot application and development.

Multi-channel DMA Based Design of Voltage Monitoring Using Synchronous Frequency Trace-Sampling Technique

In order to eliminate the influence of frequency change on real-time voltage acquisition, a low-cost solution of voltage monitoring was proposed using the multi-channel DMA synchronous frequency trace-sampling technique. In-chip resources of the designed voltage monitor were fully utilized in hardware design to reduce external devices. The MQX RTOS was used to perform the functional tasks flexibly and efficiently; especially the Ethernet communication applications and USB device connection were realized using its TCP/IP protocol stack and USB driver. In addition, to ensure the safety of electrical records, data statistics and alarm information management were also implemented through the management of the storage in FLASH. The test results show that the voltage monitor designed in this paper has the advantages of accurate measurement, strong resistance to frequency interference and low cost, and can be widely applied in the field of voltage monitoring in distribution networks.

Hybrid Gait Planning of A Hexapod Robot

The adapotation of gaits pattern is a basic and important for the hexapod robot to move stably and efficiently, which depends on the servos of the robot’s legs, and also the body structure of the robot.This paper compares the tripod gait and the crab-inspired gait for a specific hexapod to move forward and move backward; turn left and turn right and integrates the two gaits to apply them under different conditions. The hexapod has three servos on each legs, thus the freedom level of each leg is three-degree. From the comparative experiment, this two gait patterns are suitable for different turning demands.

Multi-factor Comprehensive Prediction of Delay Time through Congested Road Sections

The navigation software uses the positioning system to determine the traffic conditions of the road sections in advance, so as to predict the travel time of the road sections. However, in the case of traffic congestion, the accuracy of its prediction time is low. After empirical analysis, this paper establishes a multi-factor synthesis by studying 7 factors: traffic flow, number of stops, traffic light duration, road network density, average speed, road area, and number of intersections the prediction function achieves the purpose of accurately predicting the transit time of congested road sections. The gray correlation coefficients of the seven factors obtained from the gray correlation analysis are: 0.9827, 0.9679, 0.6747, 0.8030, 0.9445, 0.8759, 0.4328. The correlation coefficients of traffic volume, number of stops, average speed, and road congestion delay time were all about 95%, which were the main influencing factors of the study. The prediction needs to be based on functions. This paper fits the main influencing factors to the delay time of congested roads. It is found that the delay time varies parabolically with the traffic flow and the number of stops, and linearly with the average speed. Because the three impact factors have different weights on the delay time of congested roads, demand takes the weight of each factor. Therefore, the gray correlation coefficients occupied by the main influencing factors are normalized to obtain the weights of three of 0.340, 0.334, and 0.326. The weighted fitting function is subjected to nonlinear summation processing to obtain a multi-factor comprehensive prediction function. By comparing the original data with the fitting data and calculating the accuracy of the fitting function, it is found that the accuracy of each fitting function is close to 0, the residual error, the relative error is small, and the accuracy is high.