3,988 research outputs found
Lyapunovâs stability theory-based model reference adaptive control for permanent magnet linear motor drives
Author name used in this publication: Norbert C. CheungRefereed conference paper2004-2005 > Academic research: refereed > Refereed conference paperVersion of RecordPublishe
An automatic disturbance rejection controller for matrix converter
Author name used in this publication: Norbert CheungRefereed conference paper2004-2005 > Academic research: refereed > Refereed conference paperVersion of RecordPublishe
SYNTHESIS OF FAUJASITE ZEOLITES WITH CROWN-ETHER TEMPLATES
[[abstract]]The function of crown ethers in the synthesis of faujasite zeolites has been studied. Hexagonal faujasite (EMT) was prepared from 18-crown-6 ether and not from 15-crown-5 ether as the organic template under hydrothermal conditions, whereas cubic faujasite (FAU) was obtained from a reaction gel using either 18-crown-6 ether or 15-crown-5 ether. During the early stages of synthesis, 18-crown-6 ether and 15-crown-5 ether were partially occluded in the aluminosilicate hydrogel and EMT or FAU nuclei, but 18-crown-6 ether was only adsorbed on the surface of the hydrogel for FAU crystals. Thermal analysis, Raman spectroscopy and composition analysis measurements indicate that sodium cations play a more important role than 18-crown-6 ether in directing the formation of FAU nuclei and balancing the charge on the framework of FAU when 18-crown-6 ether is used at the organic template. The stacking arrangement and Al content of the synthesized faujasite zeolites were found to depend on the SiO2:Al2O3 and Na2O:crown ether molar ratios of the reaction mixtures. The structure-directing role of the crown ether in the formation of faujasite zeolites was also studied by theoretical calculations.[[fileno]]2010323010044[[department]]ććž
Longitudinal diffusion tensor MR imaging study of radiation induced white matter damage in a rat model
published_or_final_versio
EEG data analysis with stacked differentiable neural computers
© 2018, Springer-Verlag London Ltd., part of Springer Nature. Differentiable neural computer (DNC) has demonstrated remarkable capabilities in solving complex problems. In this paper, we propose to stack an enhanced version of differentiable neural computer together to extend its learning capabilities. Firstly, we give an intuitive interpretation of DNC to explain the architectural essence and demonstrate the stacking feasibility by contrasting it with the conventional recurrent neural network. Secondly, the architecture of stacked DNCs is proposed and modified for electroencephalogram (EEG) data analysis. We substitute the original Long Short-Term Memory network controller by a recurrent convolutional network controller and adjust the memory accessing structures for processing EEG topographic data. Thirdly, the practicability of our proposed model is verified by an open-sourced EEG dataset with the highest average accuracy achieved; then after fine-tuning the parameters, we show the minimal mean error obtained on a proprietary EEG dataset. Finally, by analyzing the behavioral characteristics of the trained stacked DNCs model, we highlight the suitableness and potential of utilizing stacked DNCs in EEG signal processing
Magnetism and high magnetic-field-induced stability of alloy carbides in Fe-based materials.
Understanding the nature of the magnetic-field-induced precipitation behaviors represents a major step forward towards unravelling the real nature of interesting phenomena in Fe-based alloys and especially towards solving the key materials problem for the development of fusion energy. Experimental results indicate that the applied high magnetic field effectively promotes the precipitation of M23C6 carbides. We build an integrated method, which breaks through the limitations of zero temperature and zero external field, to concentrate on the dependence of the stability induced by the magnetic effect, excluding the thermal effect. We investigate the intimate relationship between the external field and the origins of various magnetics structural characteristics, which are derived from the interactions among the various Wyckoff sites of iron atoms, antiparallel spin of chromium and Fe-C bond distances. The high-magnetic-field-induced exchange coupling increases with the strength of the external field, which then causes an increase in the parallel magnetic moment. The stability of the alloy carbide M23C6 is more dependent on external field effects than thermal effects, whereas that of M2C, M3C and M7C3 is mainly determined by thermal effects
Study on knowledge base verification based on Petri nets
The comparison of rule pairs is usually involved in traditional approaches to verify knowledge base. The efficiency of these approaches is low when used in the verification of large-scale knowledge base because of the comparison. An alternative method of detecting logical errors in knowledge base is presented in this paper. This is achieved by analyzing the reachability and the transition sequence of Petri nets which is the established model of rule base
Metal-insulator transition in vanadium dioxide nanobeams: probing sub-domain properties of strongly correlated materials
Many strongly correlated electronic materials, including high-temperature
superconductors, colossal magnetoresistance and metal-insulator-transition
(MIT) materials, are inhomogeneous on a microscopic scale as a result of domain
structure or compositional variations. An important potential advantage of
nanoscale samples is that they exhibit the homogeneous properties, which can
differ greatly from those of the bulk. We demonstrate this principle using
vanadium dioxide, which has domain structure associated with its dramatic MIT
at 68 degrees C. Our studies of single-domain vanadium dioxide nanobeams reveal
new aspects of this famous MIT, including supercooling of the metallic phase by
50 degrees C; an activation energy in the insulating phase consistent with the
optical gap; and a connection between the transition and the equilibrium
carrier density in the insulating phase. Our devices also provide a
nanomechanical method of determining the transition temperature, enable
measurements on individual metal-insulator interphase walls, and allow general
investigations of a phase transition in quasi-one-dimensional geometry.Comment: 9 pages, 3 figures, original submitted in June 200
Seeing two faces together: preference formation in humans and rhesus macaques
Humans, great apes and old world monkeys show selective attention to faces depending on conspecificity, familiarity, and social status supporting the view that primates share similar face processing mechanisms. Although many studies have been done on face scanning strategy in monkeys and humans, the mechanisms influencing viewing preference have received little attention. To determine how face categories influence viewing preference in humans and rhesus macaques (Macaca mulatta), we performed two eye-tracking experiments using a visual preference task whereby pairs of faces from different species were presented simultaneously. The results indicated that viewing time was significantly influenced by the pairing of the face categories. Humans showed a strong bias towards an own-race face in an AsianâCaucasian condition. Rhesus macaques directed more attention towards non-human primate faces when they were paired with human faces, regardless of the species. When rhesus faces were paired with faces from Barbary macaques
(Macaca sylvanus) or chimpanzees (Pan troglodytes), the novel speciesâ faces attracted more attention. These results
indicate that monkeysâ viewing preferences, as assessed by a visual preference task, are modulated by several factors,
species and dominance being the most influential
- âŠ