62 research outputs found
Parameters affecting the fundamental period of infilled RC frame structures
No full textDespite the fact that the fundamental period appears to be one of the most critical parameters for the seismic design of structures according to the modal superposition method, the so far available in the literature proposals for its estimation are often conflicting with each other making their use uncertain. Furthermore, the majority of these proposals do not take into account the presence of infills walls into the structure despite the fact that infill walls increase the stiffness and mass of structure leading to significant changes in the fundamental period numerical value. Toward this end, this paper presents a detailed and indepth analytical investigation on the parameters that affect the fundamental period of reinforce concrete structure. The calculated values of the fundamental period are compared against those obtained from the seismic code and equations proposed by various researchers in the literature. From the analysis of the results it has been found that the number of storeys, the span length, the stiffness of the infill wall panels, the location of the soft storeys and the soil type are crucial parameters that influence the fundamental period of RC buildings
Fundamental period of infilled reinforced concrete frame structures
No full textThe fundamental period of vibration appears to be one of the most critical parameters for the seismic design and assessment of structures. In the present paper, the results of a large-scale analytical investigation on the parameters that affect the fundamental period of reinforced concrete structures are presented. The influence of the number of storeys, the number of spans, the span length, the infill wall panel stiffness and the percentage of openings within the infill panel on the fundamental period of infilled RC frames was investigated. Based on these results, a regression analysis is applied in order to propose a new empirical equation for the estimation of the fundamental period. The derived equation is shown to have better predictive power compared with equations available in the literature
Prediction of the fundamental period of infilled rc frame structures using artificial neural networks
No full textThe fundamental period is one of the most critical parameters for the seismic design of structures. There are several literature approaches for its estimation which often conflict with each other, making their use questionable. Furthermore, the majority of these approaches do not take into account the presence of infill walls into the structure despite the fact that infill walls increase the stiffness and mass of structure leading to significant changes in the fundamental period. In the present paper, artificial neural networks (ANNs) are used to predict the fundamental period of infilled reinforced concrete (RC) structures. For the training and the validation of the ANN, a large data set is used based on a detailed investigation of the parameters that affect the fundamental period of RC structures. The comparison of the predicted values with analytical ones indicates the potential of using ANNs for the prediction of the fundamental period of infilled RC frame structures taking into account the crucial parameters that influence its value
On the Fundamental Period of Infilled RC Buildings
No full textThis paper investigates the fundamental period of vibration of RC buildings by means of finite element macro-modelling and modal eigenvalue analysis. As a base study, a number of 14-storey RC buildings have been considered \"according to code designed\" and \"according to code non-designed\". Several parameters have been studied including the number of spans; the span length in the direction of motion; the stiffness of the infills; the percentage openings of the infills and; the location of the soft storeys. The computed values of the fundamental period are compared against those obtained from seismic code and equations proposed by various researchers in the literature. From the analysis of the results it has been found that the span length, the stiffness of the infill wall panels and the location of the soft storeys are crucial parameters influencing the fundamental period of RC buildings
Review of M. C. Marcuzzo's Essays in Keynesian Persuasion, (2019, Newcastle upon Tyne: Cambridge Scholars) [Review]
No full textMarcuzzo’s Essays in Keynesian Persuasion is a collection of 15 papers published between 2002 and 2018 with a focus on the work and thought of John Maynard Keynes from a variety of perspectives. It can be seen as a companion volume to Fighting Market Failure (Marcuzzo, 2012), which is a collection of 15 papers published between 1994 and 2008 on the pantheon of economists that constitute the Cambridge
school of economics
Scalar soliton quantization with generic moduli
No full textThis article is distributed under the terms of the Creative Commons
Attribution License (CC-BY 4.0), which permits any use, distribution and reproduction in
any medium, provided the original author(s) and source are credArticle funded by SCOAP3. CP is
a Royal Society Research Fellow and partly supported by the U.S. Department of Energy
under grants DOE-SC0010008, DOE-ARRA-SC0003883 and DOE-DE-SC0007897. ABR
is supported by the Mitchell Family Foundation. We would like to thank the Mitchell
Institute at Texas A&M and the NHETC at Rutgers University respectively for hospitality
during the course of this work. We would also like to acknowledge the Aspen Center
for Physics and NSF grant 1066293 for a stimulating research environment which led to
questions addressed in this paper
Performance Investigation of Existing RC Buildings with Height Irregularity using the IDA Procedure
No full textDataset for "Large Scale Crowdsourcing and Characterization of Twitter Abusive Behavior"
No full textDataset for the publication "Large Scale Crowdsourcing and Characterization of Twitter Abusive Behavior". Antigoni-Maria Founta, Constantinos Djouvas, Despoina Chatzakou, Ilias Leontiadis, Jeremy Blackburn, Gianluca Stringhini, Athena Vakali, Michael Sirivianos and Nicolas Kourtellis. International AAAI Conference on Web and Social Media (ICWSM), 2018.
The dataset provided here includes an updated version of the original dataset, with ~100k tweets annotated using the CrowdFlower platform:
hatespeech_labels.csv: contains ~100k rows, where every row consists of a unique Tweet ID and its associated majority annotation
UPDATE: It has come to our understanding that a number of the tweets are not available anymore for download on Twitter. Therefore, upon request, we can provide one more file with the full ~100k tweet text and their associated majority labels. The tweets are shuffled so that there is no connection between tweet IDs and texts (in order to be aligned with the T&C of Twitter).
To obtain the file contact a.m.founta at gmail dot com AND antonis26papa at gmail dot com.
Please cite the paper in any published work that uses any of these resources.
@inproceedings{founta2018large,
title={Large Scale Crowdsourcing and Characterization of Twitter Abusive Behavior},
author={Founta, Antigoni-Maria and Djouvas, Constantinos and Chatzakou, Despoina and Leontiadis, Ilias and Blackburn, Jeremy and Stringhini, Gianluca and Vakali, Athena and Sirivianos, Michael and Kourtellis, Nicolas},
booktitle={11th International Conference on Web and Social Media, ICWSM 2018},
year={2018},
organization={AAAI Press}
}
For any further questions contact a.m.founta at gmail dot com.
Publication DOI: https://doi.org/10.5281/zenodo.1443348
Github: https://github.com/ENCASEH2020/hatespeech-twitter
The updated version of this Dataset is here: https://zenodo.org/record/2657374#.XMrDIY4zaUk</p
Restricted Dataset for "Large Scale Crowdsourcing and Characterization of Twitter Abusive Behavior"
No full textRestricted Dataset for the "Large Scale Crowdsourcing and Characterization of Twitter Abusive Behavior" paper, published in ICWSM 2018. The full text of the paper can be found here. The Public version of the dataset can be found here
hatespeech_text_label_vote_RESTRICTED_100K.csv: contains ~100K raws with tweet text, the associated majority label, and the number of votes for the majority label. The tweets are shuffled so that there is no connection between tweet IDs and texts (in order to be in line with the T&C of Twitter).
retweets.csv: contains ~2K rows, where every row consists of the row number in the hatespeech_text_label_vote_RESTRICTED_100K.csv file which is the first occurrence of a Tweet text followed by comma-separated row numbers of all other occurrences of the same Tweet text in the same file. There are ~8K other occurrences due to retweets.
Please cite the paper in any published work that uses any of these resources.
@inproceedings{founta2018large,
title={Large Scale Crowdsourcing and Characterization of Twitter Abusive Behavior},
author={Founta, Antigoni-Maria and Djouvas, Constantinos and Chatzakou, Despoina and Leontiadis, Ilias and Blackburn, Jeremy and Stringhini, Gianluca and Vakali, Athena and Sirivianos, Michael and Kourtellis, Nicolas},
booktitle={11th International Conference on Web and Social Media, ICWSM 2018},
year={2018},
organization={AAAI Press}
}
For any further questions contact a.m.founta at gmail dot com AND markos.charalambous at eecei dot cut dot ac dot c
Characterisation of a functionally graded duplex stainless steel: fabricated by Gas Tungsten Arc Welding
No full textFunctionally graded materials (FGM) are a class of materials in which the chemical composition or microstructure varies as a function of position, offering unique material properties. In this study, a functionally graded structure was manufactured using Gas Tungsten Arc Welding and a double wire feed device. The wire feed rate was changed step by step of the austenitic AISI 316L and ferritic AISI 430L stainless steel wire, creating a chemically graded duplex stainless steel structure. The structure, approximately 30 mm in height, was investigated using Optical Microscopy, X-Ray Diffraction, X-Ray Fluorescence and Energy Dispersive X-Ray Spectroscopy. The transverse section is composed of large elongated grains. The chemical analysis revealed a relatively smooth change in Nickel and Molybdenum composition over the section, due to remelting of previously deposited layers. The graded material showed a gradual transition in phase fractions from mainly austenite and some ferrite to mainly ferrite and some austenite, to fully ferric structure. There were no brittle phases detected in the structure
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