Data analysis is of upmost importance in the mining of big data, where knowledge discovery and inference are the basis for intelligent systems to support the real world applications. However, the process involves knowledge acquisition, representation, inference and data, Bayesian network (BN) is the key technology plays a key role in knowledge representation, in order to pave way to cope with incomplete, fuzzy data to solve the real-life problems.This book presents Bayesian network as a technology to support data-intensive and incremental learning in knowledge discovery, inference and data fusion in uncertain environment.
This book focuses on recently developed crystal growth techniques to grow large and high quality superconducting single crystals. The techniques applied are traveling solvent floating zone (TSFZ) with infrared image furnace, Bridgeman, solution/flux and top seeded solution growth (TSSG) methods. The materials range from cuprates, cobaltates to pnictides including La2CuO4-based (LCO), YBa2Cu3O7-d (YBCO), Bi2Sr2Can−1CunO2n+4+δ (n=1,2,3) (BSCCO) to NaxCoO2. The modified Bridgman “cold finger” method is devoted to the pnictide system with the best quality (transition width DTc~0.5 K) with highest Tc~38.5 K of Ba0.68K0.32Fe2A2. The book presents various iron-based superconductors with different structures, such as 1111, 122, 111, 11 and 42622,10-3-8. Detailed single crystal growth methods (fluxes, Bridgman, floating zone), the associated procedures and their impact to crystal size and quality are presented. The book also describes the influence of doping on the structure and the electric, magnetic, and superconducting properties of these compounds in a comparative study of different growth methods. It describes particularly under-, optimal and over-doped with oxygen cuprates (LCO, YBCO and BSCCO) and hole/electron/isovalently doped parent compounds AFe2As2 (A = Ba, Sr, Ca) (122), chalcogenides AxFe2-ySe2(A = K, Rb, Cs) (122), and Fe1-dTe1-xSex (11). A review of the current growth technologies and future growth efforts handling volatile and poisonous components are also presented.
This book provides an overview of the new plant natural product skeletons discovered from 1999 to 2021. It categorizes these natural products by providing their names, source distributions, structural types, structure characteristics, and bioactivities. A total of 1373 plant products in 99 families are presented, which cover 36 different structure types within the Hypericaceae family of which the majority are alkaloid structures. In addition, it presents the biological profiling in the last 23 years by summarizing the biological activities and potential disadvantages. The new natural products skeleton presented are unprecedented structural scaffolds and could bring new opportunities for biological/pharmaceutical areas and provide new structure templates for synthetic chemists. This book helps readers gain in-depth insight into the past and recent trends of natural products; it also assists those interested in assessing the potential biological function of the natural products.
Data analysis is of upmost importance in the mining of big data, where knowledge discovery and inference are the basis for intelligent systems to support the real world applications. However, the process involves knowledge acquisition, representation, inference and data, Bayesian network (BN) is the key technology plays a key role in knowledge representation, in order to pave way to cope with incomplete, fuzzy data to solve the real-life problems.This book presents Bayesian network as a technology to support data-intensive and incremental learning in knowledge discovery, inference and data fusion in uncertain environment.
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