Study on spatial planning and design of learning commons in university libraries based on fuzzy matrix model

Abstract

Campus university library as a spiritual force, in the development of social economy and science and technology innovation, according to the requirements of education management research scholars and students growth changes proposed learning Shared space, the effective integration of space, resources, service as one of the new construction idea, not only makes the university library become more perfect effective, It can also enhance the cohesion and innovation of internal operation. Nowadays, with the increase of the number of university libraries around the country, the scale of internal construction is getting bigger and bigger, and the planning and design of learning shared space based on university libraries has become the focus of scientific research. In essence, learning shared space, as a seamless learning environment, begins to innovate toward intellectualization and modernization while transforming the functional role of university libraries. In this article, therefore, learn about the current university library, on the basis of Shared space planning and design content, according to the fuzzy matrix model, analysis of the application of image retrieval algorithm is verified, the final results show that in the university library to promote learning sharing space, can not only meet the diverse needs of the readers, you can also change the traditional mode of the library service.

Comparing some plant communities in a region of Türkiye via fuzzy similarity

“…The fuzzy theory is one of the most studied fields of science. This theory has been used in various fields of science by Gu et al [1], Gong et al [2], Rasham et al [3] and Kausar et al [4]. We know that the works of Moraczewski [5,6], Feoli et al [7], Pedersen et al [8], Srivastava and Shukla [9], Feoli [10], Rapinel et al [11], Akdeniz Şafak et al [12], Bingöl et al [13], Akdeniz Şafak et al [14], Akın et al [15], have examined plant communities in fuzzy environment.…”

“…In our study, the membership degrees in the tables were prepared according to the presence (1) or absence (0) of plant communities determined in the field with the Braun-Blanquet approach which has been calculated in a fuzzy sense beyond {0, 1} logic. In other words, with our work, a classical similarity of plant sociology studies has been extended by fuzzy approach.…”

“…4-B2.3) FS e (r i , r j ), Fuzzy similarity of elements (relevés) (for r i , r j ; i = 47(1)62, j = 32(1)46). FS e (r i , r j ) r 32 r 33 r 34 r 35 r 36 r 37 r 38 r 39 r 40 r 41 r 42 r 43 r 44 r 45 r 46 .16 0.16 0.16 0.16 0.16 0.16 0.16 0.16 0.25 0.25 0.25 0.25 0.25 0.25 r 59 0.16 0.16 0.16 0.16 0.16 0.16 0.16 0.16 0.16 0.25 0.25 0.25 0.25 0.25 0.25 r 60 0.16 0.16 0.16 0.16 0.16 0.16 0.16 0.16 0.16 0.25 0.25 0.25 0.25 0.25 0.25 r 61 0.16 0.16 0.16 0.16 0.16 0.16 0.16 0.16 0.16 0.25 0.25 0.25 0.25 0.25 0.25 r 62 0.16 0.16 0.16 0.16 0.16 0.16 0.16 0.16 0.16 0.25 0.25 0.25 0.25 0.25 0.25…”