Air source heat pump has the characteristics of high efficiency, energy saving, green and pollution-free, and has been widely used in building energy saving projects. However, the frosting phenomenon of the air source heat pump evaporator during the heating operation in cold areas in winter will reduce the heat production of the system, affect the comfort experience, and even cause the system down or irreversible damage to the heat pump system when the frosting is serious. This paper summarizes the research of domestic and foreign scholars on air source heat pump defrosting, analyzes the existing problems of defrosting technology, and finally looks forward to the future development trend of air source heat pump defrosting research.
As the overwhelming choice of Chinese families, home-based care has the advantages of convenience, economy and high efficiency. However, there are also some shortcomings, such as low professional level, poor emergency ability and limited time and space environment. In this regard, the paper aims at improving the effectiveness of home-based care service, and builds a home-based care system based on the Internet of Things technology, which provides a reference prototype for the service model and realization path of smart care. The whole system is B/S architecture, and the front end is an interactive page, which supports community management or medical staff to manage the aged care service. The back-end is the system server, which is developed by the framework of SpringBoot2 under Javaweb technology, aiming at completing the call and control of various data information. In addition, for all kinds of intelligent sensors and monitoring devices involved in home-based care services, real-time data collection and uploading will be completed by WIFI communication technology under MQTT protocol, and the data storage and management will be completed by relying on cloud platform technology. After simulation test, the functions of the system run smoothly and can meet the actual needs of smart home-based care services.
In the process of research on the characteristic detection method for large scale network attacks, due to the use of the current algorithm for large-scale network attack detection, it is unable to describe the attack characteristics of network attacks or detect in low accuracy. Therefore, an attack detection method for large scale network based on cooperative planning is proposed. The method is based on collaborative planning to design the detection characteristic of large scale network attacks, which is transformed into a space search problem. The difference between the parameters of the flow vector and the normal vector of the normal network spatial data is extracted as characteristics, combining Gauss mixture model with the expectation maximization algorithm, to design Lorenz chaotic asynchronous tracking detection algorithm for modeling and detection of network data stream. The experimental simulation shows that the detection method of large scale network attack detection method has high accuracy and high efficiency.
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