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51.
Fischer-Tropsch synthesis of the CO2 in biogas aims at producing light hydrocarbons and increasing its calorific value for feeding into the grid. Fe catalysts with Mn and K as promoters are supposed to yield high amounts of light hydrocarbons. Using a Fe-Mn-K/MgO catalyst, a parameter screening and long-term experiments were carried out. The catalyst shows, within the examined range, the highest selectivity to C2–C4 hydrocarbons at 450 °C, 8 bar(a), and a gas hourly space velocity of 350 h−1. Calcination of the catalyst resulted in a significant drop of activity and an almost complete loss of selectivity to hydrocarbons. Admixture of steam to the reactant gas lowers the tendency to carbon deposition but also promotes the water-gas shift reaction and results in lower yields of hydrocarbons. 相似文献
52.
One specific class of non-linear evolution equations, known as the Tzitzéica-type equations, has received great attention from a group of researchers involved in non-linear science. In this article, new exact solutions of the Tzitzéica-type equations arising in non-linear optics, including the Tzitzéica, Dodd–Bullough–Mikhailov and Tzitzéica–Dodd–Bullough equations, are obtained using the expa function method. The integration technique actually suggests a useful and reliable method to extract new exact solutions of a wide range of non-linear evolution equations. 相似文献
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54.
Gomes A. C. S. A. Costa L. C. Brito D. C. Frana R. J. Marques Mnica R. C. 《Polymer Bulletin》2020,77(4):1969-1981
Polymer Bulletin - In this study, we synthesized a new ion-imprinted polymer (IIP) based on introduction of amidoxime groups in acrylonitrile, complexation with Cd2+ ions and polymerization with... 相似文献
55.
Traditionally, in supervised machine learning, (a significant) part of the available data (usually 50%-80%) is used for training and the rest—for validation. In many problems, however, the data are highly imbalanced in regard to different classes or does not have good coverage of the feasible data space which, in turn, creates problems in validation and usage phase. In this paper, we propose a technique for synthesizing feasible and likely data to help balance the classes as well as to boost the performance in terms of confusion matrix as well as overall. The idea, in a nutshell, is to synthesize data samples in close vicinity to the actual data samples specifically for the less represented (minority) classes. This has also implications to the so-called fairness of machine learning. In this paper, we propose a specific method for synthesizing data in a way to balance the classes and boost the performance, especially of the minority classes. It is generic and can be applied to different base algorithms, for example, support vector machines, k-nearest neighbour classifiers deep neural, rule-based classifiers, decision trees, and so forth. The results demonstrated that (a) a significantly more balanced (and fair) classification results can be achieved and (b) that the overall performance as well as the performance per class measured by confusion matrix can be boosted. In addition, this approach can be very valuable for the cases when the number of actual available labelled data is small which itself is one of the problems of the contemporary machine learning. 相似文献
56.
Journal of Communications Technology and Electronics - Abstract—The two-dimensional diffraction problem of a plane polarized TM-wave on two identical solid silver nanocylinders is considered.... 相似文献
57.
Metallurgical and Materials Transactions B - The process of obtaining titanium tetrachloride (TiCl4) from the quartz-leucoxene concentrate (QLC) from the Yaregskoe oil-titanium field was studied.... 相似文献
58.
Wesley P. Chan Hiroto Mizohana Xiangyu Chen Yasuto Shiigi Yoshiyuki Yamanoue Masaki Nagatsuka Masayuki Inaba 《野外机器人技术杂志》2019,36(1):17-33
The use of field robots can greatly decrease the amount of time, effort, and associated risk compared to if human workers were to carryout certain tasks such as disaster response. However, transportability and reliability remain two main issues for most current robot systems. To address the issue of transportability, we have developed a lightweight modularizable platform named AeroArm. To address the issue of reliability, we utilize a multimodal sensing approach, combining the use of multiple sensors and sensor types, and the use of different detection algorithms, as well as active continuous closed‐loop feedback to accurately estimate the state of the robot with respect to the environment. We used Challenge 2 of the 2017 Mohammed Bin Zayed International Robotics Competition as an example outdoor manipulation task, demonstrating the capabilities of our robot system and approach in achieving reliable performance in the fields, and ranked fifth place internationally in the competition. 相似文献
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