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41.
Multicomponent Diamond-Like Semiconductors Based on the InBV–CdS System: Bulk and Surface Properties
Semiconductors - According to developed methods, in the fields of the mutual solubility of initial binary compounds (InP, InSb, and CdS), solid solutions of the InP–CdS and InSb–CdS... 相似文献
42.
Silicon - The products of solid-phase mechanochemical interaction between pyrocatechol and silicon dioxide yielding a powdered composite were studied using a number of physicochemical methods. This... 相似文献
43.
In this communication, the structural, micro-structural, dielectric, electrical, magnetic, and leakage-current characteristics of a double perovskite (Y2CoMnO6) ceramic material have been reported. The material was synthesized via a high-temperature mixed-oxide route. The compound crystallizes in a monoclinic structure which is confirmed from preliminary X-ray structural study. The morphological study by using scanning electron micrograph reveals the almost homogeneous distribution of grains throughout the surface of the sample. The nature of frequency-dependence of dielectric constant has been described by the Maxwell-Wagner model. The occurrence of a dielectric anomaly in the temperature dependence of dielectric permittivity study demonstrates the ferroelectric-paraelectric phase transition in the material. From the Nyquist plots, we found the existence of both grain and grain boundary effects. The frequency dependence of conductivity was studied by the Jonscher’s Power law, and the conduction phenomenon obeys the large overlapping polaron tunneling model. By using the Arrhenius equation, the activation energy has been calculated which is nearly equal to the energy required for the hoping of the electron. Both impedance and conductivity analysis demonstrate that the sample exhibits negative temperature coefficient of resistance (NTCR) properties indicating the semiconducting type of material at high temperatures. The anti-ferromagnetic character of the material is observed from the nature of magnetic hysteresis loop. The leakage current analysis suggests that the conduction process in the material follows the space charge limited conduction phenomenon. Such material will be helpful for modern electronic devices and spintronic applications. 相似文献
44.
Ivashchuk O. A. Ivashchuk O. D. Fedorov V. I. Shtana A. I. 《Russian Engineering Research》2020,40(11):970-972
Russian Engineering Research - Models based on regression analysis for predicting the operational efficiency of high-pressure roller crushers are considered. A systematized and structured... 相似文献
45.
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47.
Kharitonov D. S. Makarova I. V. Osipenko M. A. Yanushevskii V. I. Wrzesińska A. Bobowska I. Kurilo I. I. 《Protection of Metals and Physical Chemistry of Surfaces》2020,56(1):113-124
Protection of Metals and Physical Chemistry of Surfaces - The stage mechanism of manganese-containing conversion coatings (MCCs) formation on the surface of AD31 alloy (AA6063) in acidic (pH 3)... 相似文献
48.
Kobrakov K. I. Kurnetsov D. N. Ruchkina A. G. Sharpar N. M. 《Theoretical Foundations of Chemical Engineering》2020,54(5):1052-1056
Theoretical Foundations of Chemical Engineering - New research results, as well as those published earlier by the authors, on the synthesis of azo compounds based on nitroanilines obtained by the... 相似文献
49.
Theoretical Foundations of Chemical Engineering - The extraction of nitric and oxalic acids by neutral compounds TBP, DBBP, and TBPO have been studied. The optimal conditions of their separation... 相似文献
50.
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