A bed and breakfast (typically shortened to B&B) is a small lodging establishment that offers overnight accommodation and breakfast. At present, the design strategy of B&B is generally based on the personal views of B&B operators or interior designers, rather than the actual market data. Thus, the determination of design strategy is always divorced from the actual sales data of B&B. In this study, the optimal design strategy of B&B will be figured out based on the analysis of the comments data and operation data of B&B with methods of text mining and machine learning. The B&B design strategy based on text mining and machine learning would be more consistent with the consumer needs of users and business needs of B&B operators. It is a future evolution method of design to formulate design strategies for B&B based on big data and artificial intelligence.
With the radiation sources widely used in the field of industry, agriculture, medicine, and resources all over the world, the occurrences of the lost and theft incidents are not unusual. There will be great threats to human health and environment for uncontrolled sources. It can be even worse when they are used by terrorists as weapons in the city, such as RDD, which would disperse the radioactive substances into the environment and have a long-term negative impact on human society. Besides the security control and surveillance of radiation sources, the source-searching method using radiation detectors is also needed to find the lost or stolen sources. In the case of radiation monitoring in a city, a mass of people with detectors are needed to cover the large area, while radiation dosimeters are appropriate for its portability and economy.
In this paper, a simple approach to finding and locating unknown radiation sources, which might be in static or mobile condition, using distributed mobile radiation dosimeters is put forward. This approach is able to estimate the time-dependent sources location and the intensity with the dose rate measurements over time periods.
Random data is introduced to verify the approach. Virtual radiation sources and detectors with random movement are created in the cases and the dose rate measurements are computed accordingly, with which sources location and intensity are estimated, where natural background radiation and the statistical fluctuation of measurements are taken into account. The results of the estimated sources show a good consistency with the assumptions.
Path search is a hot issue in computer science and artificial intelligence science. When the user enters the starting point and ending point to be queried in the road network path search system, the system will return the best path to the user. In this paper, the road network path search system that can run and calculate the optimal navigation path to the test data is developed by designing the software architecture through the comprehensive use of database design, programming language, shortest path algorithm, UML diagram, software development model, GIS system source data, and other methods. Based on the software design principles of scalability, flexibility, and pluggability, the design and code in this paper can be practically applied to various systems such as GIS, GPS, logistics robots, unmanned aerial vehicles, and autonomous vehicles to realize their road network path planning and navigation functions.
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