To meet national workforce need, we integrated computational modeling training into undergraduate materials science and engineering (MSE) courses, including Thermodynamics, and Structure of Materials. We also flipped ...
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In this paper, we presented a computational modeling of frequency relay for islanding detection of distributed generation (DG) by the performance of frequency estimation methods. For this end, are presented an analysi...
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In this paper, we presented a computational modeling of frequency relay for islanding detection of distributed generation (DG) by the performance of frequency estimation methods. For this end, are presented an analysis and application of four methods of fundamental frequency estimation applied in distribution systems with DG in islanding situation such as: (a) Zero crossing, (b) adjustment of points to a sinusoidal waveform (APSW), (c) hybrid method, which combines (a) and (b), and (d) DFT algorithm. For the evaluation and validation of the performance of the frequency estimation methods were carried out by using the performance curves. The simulations and results prove the effectiveness of frequency methods for be used in the protection for islanding detection.
The fracture behavior of rubber-toughened polymers is governed by two dissipative microscopic deformation and damage mechanisms: matrix shear yielding and crazing. These mechanisms are strongly interconnected with the...
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The fracture behavior of rubber-toughened polymers is governed by two dissipative microscopic deformation and damage mechanisms: matrix shear yielding and crazing. These mechanisms are strongly interconnected with the eventual cavitation of the fine dispersed rubber particles. The present work summarizes and discusses a variety of micromechanical-computational modeling approaches undertaken over the past twenty years aiming at an improved understanding of the relation between microstructure and toughening in this class of materials. The focus is on materials such as ABS where both mechanisms are prevalent.
The use of strong lighting contrast to accentuate objects and figures in a painting-called Chiaroscuro-is popular among Renaissance painters such as Caravaggio, La Tour and Rembrandt. In this paper, we propose a new m...
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ISBN:
(纸本)9781509003556
The use of strong lighting contrast to accentuate objects and figures in a painting-called Chiaroscuro-is popular among Renaissance painters such as Caravaggio, La Tour and Rembrandt. In this paper, we propose a new metric called LuCo to quantify the extent to which Chiaroscuro is employed by an artist in a painting. This measurement could be used to assess the capability of any system to fulfill the original artistic intention and consequently ensure minimal disruptions of Quality of Experience. We first argue that Chiaroscuro is a device for artists to draw attention to specific spatial regions; thus it can be understood as a restricted notion of visual saliency computed using only luminance features. Operationally, using a set of local luminance patches we first compute a Bayesian surprise value, where the prior and posterior probabilities are computed assuming a Gaussian Markov Random Field (GMRF) model. Inverse covariance matrices of the GMRF model are estimated via sparse graph learning for robustness. We construct a histogram using the computed surprise values from different local patches in a painting. Finally, we compute a skewness parameter for the constructed histogram as our LuCo score: large skewness means luminance surprises are either very small or very large, meaning that the artist accentuated lighting contrast in the painting. Experimental results show that paintings by Chiaroscuro artists have higher LuCo scores than 19th century French Impressionists, and Rembrandt's self-portraits have increasingly higher LuCo scores as he aged except for his late period-both trends are in agreement with art historians' interpretations.
High Frequency Oscillations (HFOs) are a potential biomarker of epileptogenic regions. They have been extensively investigated in terms of automatic detection, classification and feature extraction. However, the mecha...
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High Frequency Oscillations (HFOs) are a potential biomarker of epileptogenic regions. They have been extensively investigated in terms of automatic detection, classification and feature extraction. However, the mechanisms governing the generation of HFOs as well as the observability conditions on clinical intracranial macroelectrodes remain elusive. In this paper, we propose a novel physiologically-relevant macroscopic model for accurate simulation of HFOs as invasively recorded in epileptic patients. This model accounts for both the temporal and spatial properties of the cortical patch at the origin of epileptiform activity. Indeed, neuronal populations are combined with a 3D geometrical representation to simulate an extended epileptic source. Then, by solving the forward problem, the contributions of neuronal population signals are projected onto intracerebral electrode contacts. The obtained signals are qualitatively and quantitatively compared to real HFOs, and a relationship is drawn between macroscopic model parameters such as synchronization and spatial extent on the one hand, and HFO features such as the wave and fast ripple (200-600 Hz) components, on the other hand.
Knowledge management becomes increasingly more important for individuals since it would make the best use of knowledge through helping learners to better understand, administer and transfer the knowledge. Externalize ...
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ISBN:
(纸本)9781509047963
Knowledge management becomes increasingly more important for individuals since it would make the best use of knowledge through helping learners to better understand, administer and transfer the knowledge. Externalize what the learners already know is one of the most important aspects of knowledge management. Although mind tools, ontology and knowledge graph are the most popular methodologies to interpret and organize knowledge, they still have defects to simulate individuals' mental images of the knowledge, especially lack the necessary supporting mechanisms on sophisticated semantic reasoning and related cognitive simulation required by the personal knowledge maps' producing. This paper proposed a computational model to simulate the personal knowledge building process which not only enriches semantic relations and inferring, but also is supported by the general cognitive intelligence theory about knowledge integration and the constructivism learning theory. Finally, the experiment result shows the personalized map has a good fidelity to the changing of the learners' mental images which consistently evolve along with the learning progress.
A good deal of recent research has centered on the identification of biomarkers and endophenotypic measures of psychiatric illnesses using in vivo and in vitro studies. This is understandable, as these measures as opp...
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A good deal of recent research has centered on the identification of biomarkers and endophenotypic measures of psychiatric illnesses using in vivo and in vitro studies. This is understandable, as these measures as opposed to complex clinical phenotypes may be more closely related to neurobiological and genetic vulnerabilities. However, instantiation of such biomarkers using computational models in silico studies has received less attention. This approach could become increasingly important, given the wealth of detailed information produced by recent basic neuroscience research, and increasing availability of high capacity computing platforms. The purpose of this review is to survey the current state of the art of research in this area. We discuss computational approaches to schizophrenia, bipolar disorder, Alzheimer's disease, fragile X syndrome and autism, and argue that it represents a promising and underappreciated research modality. In conclusion, we outline specific avenues for future research;also, potential uses of in silico models to conduct "virtual experiments" and to generate novel hypotheses, and as an aid in neuropsychiatric drug development are discussed. (C) 2015 Elsevier Ltd. All rights reserved.
The United States Air Force (USAF) often deploys personnel to remote locations or responds to disasters worldwide. Point-of-Use (PoU) ultraviolet (UV) water treatment could provide the DoD with the ability to provide ...
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The United States Air Force (USAF) often deploys personnel to remote locations or responds to disasters worldwide. Point-of-Use (PoU) ultraviolet (UV) water treatment could provide the DoD with the ability to provide water for small mobile entities that are incapable of providing the support network that larger water purification devices require. PoUs could be used as the water treatment system within the DoD for applications that include disaster response, austere locations, aircraft/helicopter survival kit or small unit for special operations teams. This research investigates the ability to use computer modeling software to predict and optimize the characteristics of a UV LED PoU water purification reactor for such applications. This research developed a working model using computational multiphysics software to predict reaction processes within a UV LED water purification reactor, and validated the model with laboratory data. The research also investigated the effect of altering the reactor geometry and the corresponding interactions with corresponding reactor rate effectiveness. The model demonstrated the ability to predict the reaction curves gathered from the lab data as well as illustrated trends in reactor geometry. When investigating the efficiency of various reactor geometries, minimizing the surface area: volume ratio was shown to result in the largest increases in efficiency. However the volume of the reactor, reflectance, and flow rates also played a role in reactor effectiveness.
We have carried out computational modeling of nonstationary conductive-convective heat transfer in a closed rectangular domain in a conjugate formulation with a local heat source (a gas infrared radiator). Four varian...
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We have carried out computational modeling of nonstationary conductive-convective heat transfer in a closed rectangular domain in a conjugate formulation with a local heat source (a gas infrared radiator). Four variants of possible description of the radiant energy distribution over the inner surfaces of enclosures have been considered. As a result of the computational modeling, differential (temperature fields and stream functions) and integral (Nusselt numbers) heat transfer characteristics have been obtained. It has been shown that the radiant flux distribution influences the heat transfer intensity.
When developing high-fidelity computational model of vocal fold vibration for voice production of individuals, one would run into typical issues of unknown model parameters and model validation of individual-specific ...
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When developing high-fidelity computational model of vocal fold vibration for voice production of individuals, one would run into typical issues of unknown model parameters and model validation of individual-specific characteristics of phonation. In the current study, the evoked rabbit phonation is adopted to explore some of these issues. In particular, the mechanical properties of the rabbit's vocal fold tissue are unknown for individual subjects. In the model, we couple a 3D vocal fold model that is based on the magnetic resonance (MR) scan of the rabbit larynx and a simple one-dimensional (1D) model for the glottal airflow to perform fast simulations of the vocal fold dynamics. This hybrid three-dimensional (3D)/1D model is then used along with the experimental measurement of each individual subject for determination of the vocal fold properties. The vibration frequency and deformation amplitude from the final model are matched reasonably well for individual subjects. The modeling and validation approaches adopted here could be useful for future development of subject-specific computational models of vocal fold vibration.
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