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31.
Combustion, Explosion, and Shock Waves - Results of a numerical study of mixing, ignition, and combustion of a cold hydrogen jet propagating along the lower wall of a channel parallel to a... 相似文献
32.
Multimedia Tools and Applications - In this work, a new fuzzy logic-based algorithm is proposed for the enhancement of low light color images. A generalization of a fuzzy set known as an... 相似文献
33.
34.
Deepika M. Malini Raajan N. R. Srinivasan A. 《Multimedia Tools and Applications》2022,81(9):12701-12724
Multimedia Tools and Applications - The three-dimensional models of brain tumors serve as diagnostic assistance for physicians, surgeons, and radiologists. The proposed system establishes an... 相似文献
35.
Zhang Nan Zhao Man Liu Guangfa Wang Jiaoyang Chen Yunzhi Zhang Zhengjian 《Journal of Materials Science》2022,57(19):8687-8700
Journal of Materials Science - A green modification method for effectively enhancing toughness of PLA was established. Herein, alkaline lignin (LG) was firstly alkylated with dodecane, and then... 相似文献
36.
Wang Chen Bao Chun-Hui Wu Wan-Yu Hsu Chia-Hsun Zhao Ming-Jie Zhang Xiao-Ying Lien Shui-Yang Zhu Wen-Zhang 《Journal of Materials Science》2022,57(26):12341-12355
Journal of Materials Science - Molybdenum oxide (MoOx) films had been grown by using plasma-enhanced atomic layer deposition (PEALD) with Mo(CO)6 precursor and O2 plasma reactant in a substrate... 相似文献
37.
38.
Karimi Bayan Chang Yu-Cheng Pekola Jukka P. 《Journal of Low Temperature Physics》2022,207(3-4):220-225
We discuss the temperature dependence of a common low temperature local thermometer, a tunnel junction between a superconductor and a normal metal (NIS junction). Towards the lowest temperatures its characteristics tend to saturate, which is usually attributed to selfheating effects. In this technical note, we reanalyze this saturation and show that the temperature independent subgap current of the junction alone explains in some cases the low temperature behavior quantitatively.
相似文献39.
Engineering new glass compositions have experienced a sturdy tendency to move forward from (educated) trial-and-error to data- and simulation-driven strategies. In this work, we developed a computer program that combines data-driven predictive models (in this case, neural networks) with a genetic algorithm to design glass compositions with desired combinations of properties. First, we induced predictive models for the glass transition temperature (Tg) using a dataset of 45,302 compositions with 39 different chemical elements, and for the refractive index (nd) using a dataset of 41,225 compositions with 38 different chemical elements. Then, we searched for relevant glass compositions using a genetic algorithm informed by a design trend of glasses having high nd (1.7 or more) and low Tg (500 °C or less). Two candidate compositions suggested by the combined algorithms were selected and produced in the laboratory. These compositions are significantly different from those in the datasets used to induce the predictive models, showing that the used method is indeed capable of exploration. Both glasses met the constraints of the work, which supports the proposed framework. Therefore, this new tool can be immediately used for accelerating the design of new glasses. These results are a stepping stone in the pathway of machine learning-guided design of novel glasses. 相似文献
40.
Journal of Chemical Ecology - Biocontrol agents such as parasitic wasps use long-range volatiles and host-associated cues from lower trophic levels to find their hosts. However, this chemical... 相似文献