QoS Review: Smart Sensing in Wake of COVID-19, Current Trends and Specifications With Future Research Directions

With the continuous growth of the number of mobile devices and the continuous development of the mobile internet, people’s demand for mobile communication services is also increasing. However, the wireless spectrum resources of cellular mobile communication networks are limited and are becoming increasingly scarce and tense. In order to improve the utilization of wireless spectrum resources, people have proposed the concept of device-to-device communication. In order to improve the robustness of the system and transmission delay tolerance service, which allows users to interrupt the probability method has certain tolerance, the maximum transmission power is greater than that of the traditional robust algorithm. By monitoring the emotions of hotel employees, it can be seen that the performance accuracy of the robust algorithm in this paper is high. Low job burnout will have a negative impact on hurt job satisfaction, while emotional fatigue and depersonalization will not directly affect job satisfaction. Among the two outcome variables of job burnout and job satisfaction, surface behavior positively affects emotional exhaustion and depersonalization but has no significant effect on job satisfaction. Deep behavior negatively affects depersonalization and low sense of accomplishment and positively affects work satisfaction.

Section: Related Workmentioning

confidence: 99%

Emotion Monitoring of Hotel Staff Based on Mobile Network and Resource Allocation Algorithm

Lei

2022

“…is algorithm can effectively solve the problem that simple genetic algorithm cannot search largescale combinations efficiently. e literature proposes that the application of genetic algorithm in intelligent test paper generation can simulate the process of biological evolution, initialize the test questions in the test question bank through coding population and iterative operation, and finally get the optimal result [13,14].…”

Section: Related Workmentioning

confidence: 99%

Effectiveness of Network Classroom Teaching Based on Genetic Algorithm

Zou

Wang

Zhu

2022

In online classroom teaching, the function of teaching system can play an important role in the effectiveness of classroom teaching. How to use genetic algorithm to optimize online classroom teaching system has become a research hotspot. Based on genetic algorithm, this paper proposes an adaptive genetic algorithm model based on the traditional algorithm. After setting the appropriate mutation probability, the model can improve the convergence speed. Moreover, based on adaptive genetic algorithm, combined with the direct value method and BT neural network theory, this paper constructs the online classroom teaching quality evaluation model and the teaching system test paper data model, and optimizes adaptive mutation genetic algorithm and BP neural network to evaluate the teaching effectiveness. Simulation experiments are carried out based on the algorithm model, and the visual parameter values are obtained. After experimental comparison, the initial value of the mutation rate is set between 0.002 and 0.004. For the network classroom teaching system, this paper introduces the system demand analysis, function module design, and database design in detail. Finally, through the questionnaire survey, this paper understands the network situation of students in class and the use of online classroom teaching platform in detail, analyzes the problems and influencing factors of online teaching, and finally puts forward the strategies to improve the effectiveness of online classroom teaching.

“…e literature introduces the overall framework of computing-intensive mobile application development based on the mobile cloud computing model. According to the analysis of system requirements, the key technologies involved in the mobile cloud computing model are integrated with OpenNebula, and the specific implementation methods and methods of the online translation system are given to process and verify its feasibility [13].…”

Section: Related Workmentioning

confidence: 99%

Software Simulation in English Translation Platform Based on Gaussian Hybrid Model

Peng

Wei

Liu

et al. 2022

In this article, we will first try to create a general development platform for embedded systems. The goal of this step is to establish an experimental platform that can support various peripheral modules and can be reused. The connection between the modules can be reconfigured to meet the different needs of embedded research and learning. On this basis, the system uses the audio frequency spectrum program as an input function to represent the dispersion pattern of signal energy, which can be tested with characteristic nodes simulated by convolutional neural network software. In addition, the auxiliary neural network software simulation core can continuously learn the detailed characteristics of the audio frequency spectrum, making it easy to recognize environmental sounds. In addition, the sound signal and the neural cycle are related in time. The neural network can study the relationship between different frames in the time domain to compensate for the defects caused by the complex neural network in modeling time series. Finally, this article focuses on the process of building an English translation platform based on the mobile cloud data model. The client is targeted at the Android platform, while the server is based on the laaS system. According to the model of mobile cloud data processing, the calculation of mobile phones in computer-intensive programs is studied. Through the hardware design and distribution of the system, we are able to use mobile cloud technology as a desktop-intensive program to solve the problem of effectiveness in the solution. The article promotes the development of an English translation platform by applying the research results of environmental sound recognition based on embedded system software simulation to the design of the English translation platform.