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Institution

National Technical University of Athens

EducationAthens, Attiki, Greece
About: National Technical University of Athens is a education organization based out in Athens, Attiki, Greece. It is known for research contribution in the topics: Large Hadron Collider & Nonlinear system. The organization has 13445 authors who have published 31259 publications receiving 723504 citations. The organization is also known as: Athens Polytechnic & NTUA.


Papers
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Journal ArticleDOI
TL;DR: The main aim of the paper is to present an integrated system for buildings’ energy-efficient automation based on a prototype software tool for the simulation and optimization of energy consumption in the building sector, enhancing the interactivity of building automation systems.

145 citations

Journal ArticleDOI
01 Jan 2011-Energy
TL;DR: In this article, the impact of various synthetic phenolic antioxidants on the oxidation stability of biodiesel blends with the employment of the modified Rancimat method was investigated, and the experimental results revealed that an improvement in oxidation stability could be achieved with all antioxidants tested.

145 citations

Journal ArticleDOI
TL;DR: In this article, the results of more than 10 materials are presented, concerning the reported ranges of variation of Consistency Coefficient and Flow Behavior Index, together with the corresponding ranges of variations of concentration and temperature.
Abstract: Recently published values of rheological properties of fluid fruit and vegetable puree products were retrieved from the literature and analyzed. The results of more than 10 materials are presented, concerning the reported ranges of variation of Consistency Coefficient and Flow Behavior Index, together with the corresponding ranges of variation of concentration and temperature. The related literature sources are presented for each material. Empirical models, relating both Consistency Coefficient and Flow Behavior Index to concentration and temperature, are proposed and fitted to all retrieved data for each material. The data were screened carefully, using residual analysis techniques.

145 citations

Journal ArticleDOI
TL;DR: In this paper, an extensive time-domain parametric study using idealized stratified profiles and Gaussian stochastic fields was conducted to characterize the spatial distribution of soil properties, and using Ricker wavelets to describe the seismic input motion; the results show that both topography and local soil conditions significantly affect the spatial variability of seismic motion.
Abstract: During the 1999 Athens earthquake, the town of Adames, located on the eastern side of the Kifissos river canyon, experienced unexpectedly heavy damage. Despite the particular geometry of the slope that caused significant motion amplification, topography effects alone cannot explain the uneven damage distribution within a 300-m zone parallel to the canyon’s crest, which is characterized by a rather uniform structural quality. In this article, we illustrate the important role of soil stratigraphy and material heterogeneity on the topographic aggravation of surface ground motion. For this purpose, we first conduct an extensive time-domain parametric study using idealized stratified profiles and Gaussian stochastic fields to characterize the spatial distribution of soil properties, and using Ricker wavelets to describe the seismic input motion; the results show that both topography and local soil conditions significantly affect the spatial variability of seismic motion. We next perform elastic two-dimensional wave propagation analyses based on available local geotechnical and seismological data and validate our results by comparison with aftershock recordings.

145 citations

Journal ArticleDOI
TL;DR: A modular neural predictor consisting of temporal genetically optimized structures of multilayer perceptrons (MLP) that are fed with volume data from sequential locations to improve the accuracy of short‐term forecasts is proposed.
Abstract: Current interest in short-term traffic volume forecasting focuses on incorporating temporal and spatial volume characteristics in the forecasting process. This paper addresses the problem of integrating and optimizing predictive information from multiple locations of an urban signalized arterial roadway and proposes a modular neural predictor consisting of temporal genetically optimized structures of multilayer perceptrons that are fed with volume data from sequential locations to improve the accuracy of short-term forecasts. Results show that the proposed methodology provides more accurate forecasts compared to the conventional statistical methodologies applied, as well as to the static forms of neural networks.

145 citations


Authors

Showing all 13584 results

NameH-indexPapersCitations
J. S. Lange1602083145919
Nicholas A. Peppas14182590533
Claude Amsler1381454135063
Y. B. Hsiung138125894278
M. I. Martínez134125179885
Elliott Cheu133121991305
Evangelos Gazis131114784159
Stavros Maltezos12994379654
Serkant Ali Cetin129136985175
Matteo Cavalli-Sforza129127389442
Stefano Colafranceschi129110379174
Konstantinos Nikolopoulos12893175907
Ilya Korolkov12888475312
Martine Bosman12894273848
Sotirios Vlachos12878977317
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023105
2022220
20211,618
20201,645
20191,721
20181,701