An Adult with Episodic Abnormal Limb Posturing

info:eu-repo/semantics/publishedVersio

The application of interactive graphics to large time-dependent hydrodynamics problems

A written companion of a movie entitled "Interactive Graphics at Los Alamos Scientific Laboratory" was presented. While the movie presents the actual graphics terminal and the functions performed on it, the paper attempts to put in perspective the complexity of the application code and the complexity of the interaction that is possible

Kata Sifat Dalam Bahasa Inggris Dan Bahasa Tabaru Suatu Analisis Kontrastif

This study entitled “ The Adjective in English and Tabaru Language: A Contrastive Analysis‟‟ aims at identifiying and classifiying the adjectives in English and Tabaru Language, in terms of froms types and position. The English data were collected from some English book. while the Tabaru Language data was collected from six s informants. The data was analyzed using Frank , than theory than contrasted Lado‟s theory to find out the differences adjective of both Language in terms of their types and position. The result shows that English has six types of adjectives those are determiner ( article, demonstrative adjective, possessive adjective, numeral adjective, relative and interrogative adjective, and adjective of indenfinitie quantity). And descriptive adjectives whereas Tabaru Language has those types except relative adjective in term of position. Tabaru Language doesn‟t have adjectives after in definite pronoun

Laser printer\u27s image quality using paper substrates

This thesis reports the results of an investigation into the quality of an image produced by a laser printer. The laser printer used was the Kodak Ektaprint Electronic Publishing System, 300 dots per inch, resolution. It was found that certain aspects of the image quality vary with the paper substrate. Papers used in this experiment varied in basis weights and qualities of smoothness, brightness, gloss, opacity, porosity and caliper. The papers chosen were of three basis weights, two of each weight. six papers in all were tested. Quantitfication and subjective judgement were used for evaluation of image quality. Image quality was evaluated based on the following criteria: (a) Tonal reproduction/toner transfer (b) Resolution: (i) number of lines per millimeter resolved (ii) Line thickness in millimeters reprduced (c) Edge Definition as defined by edge raggedness and blur Some aspects of image quality were affected by paper variables. Basis weight alone does not affect image quality. However, factors such as smoothness, porosity and caliper had a significant, although subtle effect on tonal reproduction

Deconvolving the information from an imperfect spherical gravitational wave antenna

We have studied the effects of imperfections in spherical gravitational wave antenna on our ability to properly interpret the data it will produce. The results of a numerical simulation are reported that quantitatively describe the systematic errors resulting from imperfections in various components of the antenna. In addition, the results of measurements on a room-temperature prototype are presented that verify it is possible to accurately deconvolve the data in practice.Comment: 5 pages, 2 figures, to be published in Europhysics Letter

On the Sensitivity of a Hollow Sphere as a Multi-modal Resonant Gravitational Wave Detector

We present a numerical analysis to simulate the response of a spherical resonant gravitational wave detector and to compute its sensitivity. Under the assump- tion of optimal filtering, we work out the sensitivity curve for a sphere first taking into account only a single transducer, and then using a coherent analysis of the whole set of transducers.Comment: 24 pages, 11 figures, published versio

Cosmological solutions in generalized hybrid metric-Palatini gravity

We construct exact solutions representing a Friedmann-Lema\^itre-Robsertson-Walker (FLRW) universe in a generalized hybrid metric-Palatini theory. By writing the gravitational action in a scalar-tensor representation, the new solutions are obtained by either making an ansatz on the scale factor or on the effective potential. Among other relevant results, we show that it is possible to obtain exponentially expanding solutions for flat universes even when the cosmology is not purely vacuum. We then derive the classes of actions for the original theory which generate these solutions.Comment: 14 pages, 17 figure

On the Transferability of Knowledge among Vehicle Routing Problems by using Cellular Evolutionary Multitasking

Multitasking optimization is a recently introduced paradigm, focused on the simultaneous solving of multiple optimization problem instances (tasks). The goal of multitasking environments is to dynamically exploit existing complementarities and synergies among tasks, helping each other through the transfer of genetic material. More concretely, Evolutionary Multitasking (EM) regards to the resolution of multitasking scenarios using concepts inherited from Evolutionary Computation. EM approaches such as the well-known Multifactorial Evolutionary Algorithm (MFEA) are lately gaining a notable research momentum when facing with multiple optimization problems. This work is focused on the application of the recently proposed Multifactorial Cellular Genetic Algorithm (MFCGA) to the well-known Capacitated Vehicle Routing Problem (CVRP). In overall, 11 different multitasking setups have been built using 12 datasets. The contribution of this research is twofold. On the one hand, it is the first application of the MFCGA to the Vehicle Routing Problem family of problems. On the other hand, equally interesting is the second contribution, which is focused on the quantitative analysis of the positive genetic transferability among the problem instances. To do that, we provide an empirical demonstration of the synergies arisen between the different optimization tasks.Comment: 8 pages, 1 figure, paper accepted for presentation in the 23rd IEEE International Conference on Intelligent Transportation Systems 2020 (IEEE ITSC 2020

Stream Learning in Energy IoT Systems: A Case Study in Combined Cycle Power Plants

The prediction of electrical power produced in combined cycle power plants is a key challenge in the electrical power and energy systems field. This power production can vary depending on environmental variables, such as temperature, pressure, and humidity. Thus, the business problem is how to predict the power production as a function of these environmental conditions, in order to maximize the profit. The research community has solved this problem by applying Machine Learning techniques, and has managed to reduce the computational and time costs in comparison with the traditional thermodynamical analysis. Until now, this challenge has been tackled from a batch learning perspective, in which data is assumed to be at rest, and where models do not continuously integrate new information into already constructed models. We present an approach closer to the Big Data and Internet of Things paradigms, in which data are continuously arriving and where models learn incrementally, achieving significant enhancements in terms of data processing (time, memory and computational costs), and obtaining competitive performances. This work compares and examines the hourly electrical power prediction of several streaming regressors, and discusses about the best technique in terms of time processing and predictive performance to be applied on this streaming scenario.This work has been partially supported by the EU project iDev40. This project has received funding from the ECSEL Joint Undertaking (JU) under grant agreement No 783163. The JU receives support from the European Union’s Horizon 2020 research and innovation programme and Austria, Germany, Belgium, Italy, Spain, Romania. It has also been supported by the Basque Government (Spain) through the project VIRTUAL (KK-2018/00096), and by Ministerio de Economía y Competitividad of Spain (Grant Ref. TIN2017-85887-C2-2-P)