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Multimedia Tools and Applications - Remote Sensing categorical signature classification has gained significant implications on spatial resolution image analysis due to differences in the...  相似文献   
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Theoretical Foundations of Chemical Engineering - On the basis of the classic concepts of the theory of solid-phase combustion, for the first time, a model with a detailed scheme of chemical...  相似文献   
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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   
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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   
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This study presents the development and characterization of PVDF-conjugated polymer nanofiber-based systems. Five different conducting polymers (CPs) were synthesized successfully and used to create the nanofiber systems. The CPs used are polyaniline (PANI), polypyrrole (PPY), polyindole (PIN), polyanthranilic acid (PANA), and polycarbazole (PCZ). Nanofiber systems were produced utilizing the Forcespinning® technique. The nanofiber systems were developed by mechanical stretching. No electrical field or post-process poling was used in the nanofiber systems. The morphology, structure, electrochemical and piezoelectric performance was characterized. All of the nanofiber PVDF/CP systems displayed higher piezoelectric performance than the fine fiber PVDF systems. The PVDF/PPY nanofiber system displays the highest piezoelectric performance of 15.56 V. The piezoelectric performance of the PVDF/CP nanofiber systems favors potential for an attractive source of energy where highly flexible membranes could be used in power actuators, sensors and portable, and wireless devices to mention some.  相似文献   
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Semiconductors - Abstract—In our work, we carry out a structural-spectroscopic study of AlGaN/GaN epitaxial layers grown by molecular-beam epitaxy with nitrogen-plasma activation on a hybrid...  相似文献   
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Journal of Communications Technology and Electronics - A statistical study of the effectiveness of the non-threshold search procedure for a noise-like phase-shift keyed signal by the delay time is...  相似文献   
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