QOE Forecast Under the WSN Internet of Things

: The Internet of things, including Internet technology, including wired and wireless networks. In this paper, we investigate on the QOE because QOE is important in the network and packet loss rate is the key point in many papers. In order to study the QOE forecast under the Internet of things, building a NS2+MyEvalvid simulation platform, by the method of modifying QoS parameters to simulate different degrees of packet loss, focus on the QOE forecast under the Internet of things. Experimental results show that, QOE forecast under the Internet of things have many methods and is very important. SVM+PCA is an important method in the field of Internet of things, the Internet of things, including Internet technology, WSN networks, RFID can be part of the WSN network.


Introduction
Lot of QOE prediction, mainly includes the MOS, subjective and objective forecast and DMOS religion and resolving PSNR and SSIM. MOS subjective values can predict QOE, objective value can be predicted PSNR. MOS method, including subjective value and objective value of religion is shown below, SVM+PCA is an important method in the field of Internet of things, the Internet of things, including Internet technology, WSN networks, RFID can be part of the WSN network [1].
Promote and extend to the field of video I still intend to use these two formulas, the two formulas can be PSNR to MOS, recycle the second formula and SSIM, SSIM distortion cannot use when it is calculated before and after the distortion of the two videos, just need to MOS seek out SSIM values can be obtained. For SRC13, X input, the use of my = 24.3816 * (0.5-1 / (1 + exp (0.56962 * (27.49855 X)))) + 1.9663 * X 1.9663, there is no space between the symbols in the Matlab can run successfully. This formula can be used to find out the MOS distortion. After the distortion of MOS values into a 0-100 range is as follows: MOS* 5 distortion can be characterized to the range of 0-100. Calculation of MOS value is above the MOS value after the distortion, the following using MOS = y/(1-x) calculate the original MOS, x represents the packet loss rate, 1 -x indicates no lost that part, why is the PSNR, video distortion after the objective quality of divided by that part without distortion, MOS value is the original [3].                  In front of the Comparative analysis is not on the hook, you can process, as shown in figure 12.

Conclusion
The objective evaluation method is better than the subjective evaluation method. Method three is better than the method two and method one. The SSIM evaluation method is more accurate than other objective assessment methods of QOE. In the future work, we can use genetic and ant colony algorithms to build QOE model.
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Implementation of intelligent medical treatment of Internet of things based on JSP, medical card reader and electronic medical record. The main purpose of this study is to establish the information model of electronic medical records and develop an electronic medical record management system. The main content of the study is to establish an electronic medical record information model, develop an electronic medical record management system, and produce medical image acquisition software. The research method mainly adopts literature research method, practice, research methods, using UML and Rose software to establish the information model and the use of B/S structure and JSP development of electronic medical records management system, the software of medical image acquisition. The research results are mainly to establish a good information model and a developed electronic medical record management system and to produce a good collection of medical imaging software. The research conclusion is that the newly developed electronic medical record is superior to the traditional electronic medical record, and the new medical image acquisition software is superior to the former medical image acquisition software. Scientific research methods, study and summary. The software engineering group study summary, in the face of the information system of excessive development, group competition, the group's R & D, production of safe and reliable software so that a new project can be referred to as the "group of software engineering". The main contents include the architecture of the software engineering group must be a system structure, multilayer shielding principle, the combination principle of multiple groupware service, the principle of user identity, developers choose competition principle, competitive and adversarial safety test. Study of Lorawan technology, what is, and how to do doctoral students, how to do and how to do doctoral research, LoRaWAN technology was launched by the LoRa alliance a low power wide area network is a protocol specification. The emphasis is on its low power and wide area features. Technical agreement is the technical contract signed by the manufacturer and the design institute and the owner's units, which includes the technical requirements of the design institute and the owners and the technical response of the manufacturer. The doctor is an engineer and a researcher. A doctor needs intensive and narrow studies. Doctor's research is an international scientific research. Dr. topic analysis, artificial neural network feedforward LS-SVM study summary, BP: Back Propagation network is a group of scientists led by Rumelhart in 1986 and McCelland, is a kind of error back propagation training algorithm for the multilayer feedforward network, the neural network model is one of the most widely used. BP networks can learn and store a large number of input-output mapping relationships without the need to reveal the mathematical equations describing such mappings. Its learning rule is to use the steepest descent method to continuously adjust the weights and thresholds of the network by back-propagation, so that the error sum of the network is minimum. BP neural network model topology includes an input layer (input), hidden layer (hide, layer) and the output layer (output layer). An intelligent flying ball monitoring software robot based on the Internet of things. In 2010, the China Internet of things application alliance pointed out that robot is one of the 100 frontier technologies of the Internet of things. In 2015, the most advanced field of robotics, TOP10 technology, including Internet of things, embedded technology, simulation technology, big data technology, cloud computing robot, robot autonomous technology, and so on. The robot uses sensor technology in the key technologies of the Internet of things. In order to make life better and convenient, to study the technology and application of the Internet of things, this paper focuses on intelligent robot monitoring software based on the Internet of things. In this paper, Matlab simulation robots and programming algorithms can be used to develop intelligent flying robots using high-level programming language. E-commerce, such as the Jingdong and Taobao's free trial center, has become a hot topic. 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Swarm software engineering is an important way to achieve large data, especially data analysis, data simulation and data mining technology. Big data promote the emergence and development of the fourth paradigm of scientific research. In the field of scientific discovery, the first paradigm refers to the scientific research model based on experiment. The second paradigm is the model of scientific research based on theoretical research. The third paradigm, that is, the simulation of scientific experiments by computer.