Search results for "lcsh:Electrical engineering. Electronics. Nuclear engineering"
showing 10 items of 157 documents
Analyses of the OSU-MASLWR Experimental Test Facility
2012
Today, considering the sustainability of the nuclear technology in the energy mix policy of developing and developed countries, the international community starts the development of new advanced reactor designs. In this framework, Oregon State University (OSU) has constructed, a system level test facility to examine natural circulation phenomena of importance to multi-application small light water reactor (MASLWR) design, a small modular pressurized water reactor (PWR), relying on natural circulation during both steady-state and transient operation. The target of this paper is to give a review of the main characteristics of the experimental facility, to analyse the main phenomena characteri…
Competencias tecnológicas en estudiantes de Educación Superior
2014
En las últimas décadas las Tecnologías de la Información y Comunicación se han incorporado en todos los ámbitos de forma extensiva, y también ha influido en el ámbito educativo, aunque todavía queda mucho recorrido para la totalidad de su implantación. Los/as estudiantes son la pieza clave para comprobar el proceso de integración de las TIC en el sistema educativo, por ello, este artículo se centra en realizar una revisión sistemática de la literatura sobre las competencias en TIC de los estudiantes universitarios, y para ello se establecen dos ámbitos: competencias tecnológicas y competencias pedagógicas y la relación que existen entre ellas, y a su vez, con el uso de las mismas, y la inf…
Extending the Tsetlin Machine With Integer-Weighted Clauses for Increased Interpretability
2020
Despite significant effort, building models that are both interpretable and accurate is an unresolved challenge for many pattern recognition problems. In general, rule-based and linear models lack accuracy, while deep learning interpretability is based on rough approximations of the underlying inference. Using a linear combination of conjunctive clauses in propositional logic, Tsetlin Machines (TMs) have shown competitive performance on diverse benchmarks. However, to do so, many clauses are needed, which impacts interpretability. Here, we address the accuracy-interpretability challenge in machine learning by equipping the TM clauses with integer weights. The resulting Integer Weighted TM (…
Using the Tsetlin Machine to Learn Human-Interpretable Rules for High-Accuracy Text Categorization With Medical Applications
2019
Medical applications challenge today's text categorization techniques by demanding both high accuracy and ease-of-interpretation. Although deep learning has provided a leap ahead in accuracy, this leap comes at the sacrifice of interpretability. To address this accuracy-interpretability challenge, we here introduce, for the first time, a text categorization approach that leverages the recently introduced Tsetlin Machine. In all brevity, we represent the terms of a text as propositional variables. From these, we capture categories using simple propositional formulae, such as: if "rash" and "reaction" and "penicillin" then Allergy. The Tsetlin Machine learns these formulae from a labelled tex…
A Two-Stage Reconstruction of Microstructures with Arbitrarily Shaped Inclusions
2020
The main goal of our research is to develop an effective method with a wide range of applications for the statistical reconstruction of heterogeneous microstructures with compact inclusions of any shape, such as highly irregular grains. The devised approach uses multi-scale extended entropic descriptors (ED) that quantify the degree of spatial non-uniformity of configurations of finite-sized objects. This technique is an innovative development of previously elaborated entropy methods for statistical reconstruction. Here, we discuss the two-dimensional case, but this method can be generalized into three dimensions. At the first stage, the developed procedure creates a set of black synthetic …
Modeling Networks of Probabilistic Memristors in SPICE
2021
Efficient simulation of stochastic memristors and their networks requires novel modeling approaches. Utilizing a master equation to find occupation probabilities of network states is a recent major departure from typical memristor modeling [Chaos, solitons fractals 142, 110385 (2021)]. In the present article we show how to implement such master equations in SPICE – a general purpose circuit simulation program. In the case studies we simulate the dynamics of acdriven probabilistic binary and multi-state memristors, and dc-driven networks of probabilistic binary and multi-state memristors. Our SPICE results are in perfect agreement with known analytical solutions. Examples of LTspice code are…
Acoustic Scene Classification with Squeeze-Excitation Residual Networks
2020
Acoustic scene classification (ASC) is a problem related to the field of machine listening whose objective is to classify/tag an audio clip in a predefined label describing a scene location (e. g. park, airport, etc.). Many state-of-the-art solutions to ASC incorporate data augmentation techniques and model ensembles. However, considerable improvements can also be achieved only by modifying the architecture of convolutional neural networks (CNNs). In this work we propose two novel squeeze-excitation blocks to improve the accuracy of a CNN-based ASC framework based on residual learning. The main idea of squeeze-excitation blocks is to learn spatial and channel-wise feature maps independently…
Ohmic Contacts on p-Type Al-Implanted 4H-SiC Layers after Different Post-Implantation Annealings
2019
This paper reports on the electrical activation and Ohmic contact properties on p-type Al-implanted silicon carbide (4H-SiC). In particular, the contacts were formed on 4H-SiC-implanted layers, subjected to three different post-implantation annealing processes, at 1675 °
Optical sectioning microscopy through single-shot Lightfield protocol
2020
Optical sectioning microscopy is usually performed by means of a scanning, multi-shot procedure in combination with non-uniform illumination. In this paper, we change the paradigm and report a method that is based in the light field concept, and that provides optical sectioning for 3D microscopy images after a single-shot capture. To do this we fi rst capture multiple orthographic perspectives of the sample by means of Fourier-domain integral microscopy (FiMic). The second stage of our protocol is the application of a novel refocusing algorithm that is able to produce optical sectioning in real time, and with no resolution worsening, in the case of sparse f luorescent samples.We provide the…
Impact of gadolinium on the structure and magnetic properties of nanocrystalline powders of iron oxides produced by the extraction-pyrolytic method
2020
The work has been done in frame of the TransFerr project. It has received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement No. 778070. This research was also supported by Latvian Research Council project lzp-2018/1-0214. A.I.P. appreciates support from the Estonian Research Council grant (PUT PRG619).