Minimono: An ultracompact permanent magnet ion source for singly charged ions Rev. Sci. Instrum. 74, 956 (2003); 10.1063/1.1523630Status and new developments of the high intensity electron cyclotron resonance source light ion continuous wave, and pulsed mode (invited) Rev. Sci. Instrum. 71, 830 (2000)Recent development of electron cyclotron resonance ͑ECR͒ ion sources in China is reviewed. Emphasis is put on high charge state ECR ion sources which have been mainly developed in China by Institute of Modern Physics ͑IMP͒. Presently two ECR ion sources built by IMP for highly charged ion beams are put into operation for cyclotrons and atomic physics research. The development of high charge state ECR ion sources at IMP has progressed with a new magnetic field configuration, better condition for extraction of highly charged ions, high mirror magnetic field, large plasma volume, and special techniques to provide extra cold electrons. These techniques greatly enhance the production of highly charged ions from IMP ECR ion sources. So far more than 185 eA of Ar 11ϩ and 50 eA of Xe 26ϩ were produced by the IMP ECR ion sources. The metallic ion beam production was tested and the first beam 40 Ca 11ϩ was provided to the cyclotrons at IMP. The beam intensity of 40 Ca 11ϩ could reach 130 eA. The next part of this article will report the latest progress of 2.45 GHz ECR ion sources in China. A 2.45 GHz compact permanent magnet proton ion source was designed and constructed by IMP. A new microwave feeding system is applied on this ion source. The ion source is able to deliver 90 mA of mixed ion beam (H 1 ϩ ϩH 2 ϩ ϩH 3 ϩ ) after preliminary commissioning. The article also mentions a small 2.45 GHz ECR ion source which was built by Sichuan University and used for industry applications. The dependence of plasma density and electron temperature on radio frequency power, neutral gas pressure, and different microwave windows was measured by a Langmuir probe on this ion source.

Abstract. As one of the important research directions in the spatial data mining, spatial co-location pattern mining aimed at finding the spatial features whose the instances are frequent co-locate in neighbouring domain. With the introduction of fuzzy sets into traditional spatial co-location pattern mining, the research on fuzzy spatial co-location pattern mining has been deepened continuously, which extends traditional spatial co-location pattern mining to deal with fuzzy spatial objects and discover their laws of spatial symbiosis. In this paper, the operation principle of a classical join-based algorithm for mining spatial co-location patterns is briefly described firstly. Then, combining with the definition of classical participation rate and participation degree, a novel hesitant fuzzy spatial co-location pattern mining algorithm is proposed based on the establishment of the hesitant fuzzy participation rate and hesitant fuzzy participation formula according to the characteristics in fusion of hesitant fuzzy set theory, the score function and spatial co-location pattern mining. Finally, the proposed algorithm is written and implemented based on Python language, which uses a NumPy system to the expansion of the open source numerical calculation. The Python program of the proposed algorithm includes the method of computing hesitant fuzzy membership based on score function, the implementation of generating k-order candidate patterns, k-order frequent patterns and k-order table instances. A hesitant fuzzy spatial co-location pattern mining experiment is carried out and the experimental results show that the proposed and implemented algorithm is effective and feasible.

Petrochemical plants are an important guarantee for the development of people's lives, and the most important thing in petrochemical plants is the risk assessment method in operations. Based on the research of deep learning algorithms, this paper innovatively proposes a risk assessment method for petrochemical plants based on the combination of human motion simulation based on the micro-Doppler effect and fuzzy hierarchical analysis. The original monitoring image of the petrochemical plant is invoked to identify the target of human movement in the job site and generate the spectral diagram of human movement, and the operation safety risk of the petrochemical plant is assessed through the combination of fuzzy function and hierarchical analysis, which can effectively prevent the illegal actions of the on-site operators and provide protection for the personal safety of the on-site operators. This method plays an important role in improving the safety of petrochemical plants.