In this paper, a novel kind of anti-gravity technology by non-positive equivalent mass of aircraft is presented to try to reveal UFO flying secrets. Starting with a two-degree-of-freedom system, it is found that the system could produce an infinite acceleration under the condition of zero dynamic equivalent mass, and also provide a movement opposite to the direction of the external force under the negative equivalent mass. These two cases with non-positive equivalent mass could both be regarded as a novel kind of anti-gravity technology[4,5], which is also verified by a designed dynamic simulation experiment. For any aircraft that can be regarded as a multi-degree-of-freedom system driven by engine or other external forces, the non-positive equivalent mass could be designed out once the external input including gravity and engine exciting forces is known. Thus the anti-gravity technology for any aircraft could be realized, which could also be extended to matters related to flight, such as space ships, missiles, airplanes, etc.
Social networks contain a large amount of unstructured data. To ensure the stability of unstructured big data, this study proposes a method for visual dynamic simulation model of unstructured data in social networks. This study uses the Hadoop platform and data visualization technology to establish a univariate linear regression model according to the time correlation between data, estimates and approximates perceptual data, and collects unstructured data of social networks. Then, the unstructured data collected from the original social network are processed, and an adaptive threshold is designed to filter out the influence of noise. The unstructured data of social network after feature analysis are processed to extract its visual features. Finally, this study carries out the Hadoop cluster design, implements data persistence by HDFS, uses MapReduce to extract data clusters for distributed computing, builds a visual dynamic simulation model of unstructured data in social network, and realizes the display of unstructured data in social network. The experimental results show that this method has a good visualization effect on unstructured data in social networks and can effectively improve the stability and efficiency of unstructured data visualization in social networks.
The concept of zero energy buildings (ZEBs) has recently been actively introduced in the building sector, globally, to reduce energy consumption and carbon emissions. For the implementation of ZEBs, renewable energy systems, such as solar collectors, photovoltaic (PV) systems, and ground source heat pump (GSHP) systems, have been used. The system performance of solar collectors and PV systems are dependent on the weather conditions. A GSHP system requires a large area for boring machines and mud pump machines. Therefore, inhabitants of an existing small-scale buildings hesitate to introduce GSHP systems due to the difficulties in installation and limited construction area. This study proposes an integrate photovoltaic-thermal (PVT) and air source heat pump (ASHP) system for realizing ZEB in an existing small-scale building. In order to evaluate the applicability of the integrated PVT-ASHP system, a dynamic simulation model that combines the PVT-ASHP system model and the building load model based on actual building conditions was constructed. The heating and cooling performances of the system for one year were analyzed using the dynamic simulation model. As the simulation analysis results, the average coefficient of performance (COP) for heating season was 5.3, and the average COP for cooling season was 16.3., respectively. From April to June, the electrical produced by the PVT module was higher than the power consumption of the system and could realize ZEB.