1,766,245 research outputs found
Environmental ethics: values in and duties to the natural world (summarized with commentary by Panagiotis Perros)
No full textSummarized with commentary in Greek by Panagiotis Perros.Environmental ethics stands on a frontier, as radically theoretical as it is applied. Alone, it asks whether there can be nonhuman objects of duty. Animals, plants, endangered species, ecosystems, and even Earth are progressively unfamiliar as objects of duty, and puzzles arise both for theory and practice. Answers to such questions are as urgent as any humans face, and intimately related to the four principal issues on the world agenda: peace, population, development, and environment
EXIT Chart-Aided Convergence Analysis of Recursive Soft m-Sequence Initial Acquisition in Nakagami-m Fading Channels
No full textThis is the dataset of the accepted paper (January, 2018): Abbas Ahmed, Panagiotis Botsinis, SeungHwan Won, Lie-Liang Yang and Lajos Hanzo, "EXIT Chart-Aided Convergence Analysis of Recursive Soft m-Sequence Initial Acquisition in Nakagami-m Fading Channels" IEEE Transactions on Vehicular Technology.
</span
Intervista allo scrittore Panagiotis Chatzimoisiadis di Eleni Kassapi e Michela Corvino
Get PDFIn questa breve ma esauriente intervista della docente di Metafraseologia Eleni Kassapi allo scrittore e insegnante Panagiotis Chatzimoisiadis, tradotta dalla dottoranda Michela Corvino, vengono riportate le convinzioni dell’autore riguardo alla letteratura e alla sua scelta di cimentarsi anche con la forma del racconto breve. L’autore chiarisce, inoltre, le fonti di ispirazione per la sua scrittura e la sua opinione sulla letteratura della crisi in Grecia
Research Data: Air-to-ground NOMA Systems for the “Internet-Above-the-Clouds”
No full textThe dataset for the paper published in IEEE Access by Panagiotis Botsinis et al: Air-to-ground NOMA Systems for the “Internet-Above-the-Clouds”
</span
Panagiotis Takis Tsonis: 1953-2016
Get PDFPanagiotis Antonios Tsonis, a University of Dayton biology professor and prominent researcher who earned nearly $6 million in federal research grant funding over the course of his career, died Saturday, Sept. 3. He was 63
R-CAUSTIC: Rippling CAUSTICs underwater Image dataset
No full text<p><strong>Description</strong></p><p>Rippling caustics seem to be the main factor degrading the underwater RGB image quality and affecting the image- based 3D reconstruction process in very shallow waters. These effects are adversely affecting image matching algorithms by throwing off most of them, leading to less accurate matches and causing issues in the Simultaneous Localization and Mapping (SLAM) based navigation of the Remotely Operated Vehicles (ROV) and Autonomous Underwater Vehicles (AUV) on shallow waters. Also, they are the main cause for dissimilarities in the generated textures and orthoimages. In order to fill the gap in the literature regading underwater rippling caustics imagery with real ground truth and reference images, the first real-world underwater caustics benchmark dataset which contains 1465 underwater images is presented. Together with the RGB imagery, the corresponding generated ground truth images are delivered for facilitating the training and testing of machine learning and deep learning methods for image classification. R-CAUSTIC dataset also provides the necessary data to evaluate, at least to some extent, the performance of 3D reconstruction approaches. Data were acquired using a GoPro Hero 4 Black action camera with image dimensions of 4000 x 3000 pixels, focal length of 2.77mm and pixel size of 1.55μm and a tripod. Action cameras are widely used for underwater image acquisition. The dataset was captured in near-shore underwater sites at depths varying from 0.5 to 2m. No artificial light sources were used. Due to the wind, the turbulent surface of the water created dynamic rippling caustics on the seabed. In total 1465 RGB images were collected, separated in 7 different datasets; five of them containing stereo images, one of them tri-stereo images and one consists of multi-stereo imagery acquired in 7 different camera poses.</p><p> </p><p><strong>Publication</strong></p><p>The paper is availbale in Open Access here: https://ieeexplore.ieee.org/document/10172291</p><p><strong>If you use this dataset please cite it as R-CAUSTIC</strong> [Reference].<br>[Reference]: <strong>P. Agrafiotis, K. Karantzalos and A. Georgopoulos, "Seafloor-Invariant Caustics Removal From Underwater Imagery," in </strong><i><strong>IEEE Journal of Oceanic Engineering</strong></i><strong>, vol. 48, no. 4, pp. 1300-1321, Oct. 2023, doi: 10.1109/JOE.2023.3277168.</strong></p><p>BibTeX:</p><p>@ARTICLE{10172291,
author={Agrafiotis, Panagiotis and Karantzalos, Konstantinos and Georgopoulos, Andreas},
journal={IEEE Journal of Oceanic Engineering},
title={Seafloor-Invariant Caustics Removal From Underwater Imagery},
year={2023},
volume={48},
number={4},
pages={1300-1321},
doi={10.1109/JOE.2023.3277168}}</p><p> </p>
R-CAUSTIC: Rippling CAUSTICs underwater Image dataset
No full text<p> </p>
<h3><strong>Version 2 available! Please make sure to download the latest version of the dataset! <br></strong></h3>
<p> </p>
<p><strong>Description</strong></p>
<p>Rippling caustics seem to be the main factor degrading the underwater RGB image quality and affecting the image- based 3D reconstruction process in very shallow waters. These effects are adversely affecting image matching algorithms by throwing off most of them, leading to less accurate matches and causing issues in the Simultaneous Localization and Mapping (SLAM) based navigation of the Remotely Operated Vehicles (ROV) and Autonomous Underwater Vehicles (AUV) on shallow waters. Also, they are the main cause for dissimilarities in the generated textures and orthoimages. In order to fill the gap in the literature regading underwater rippling caustics imagery with real ground truth and reference images, the first real-world underwater caustics benchmark dataset which contains 1465 underwater images is presented. Together with the RGB imagery, the corresponding generated ground truth images are delivered for facilitating the training and testing of machine learning and deep learning methods for image classification. R-CAUSTIC dataset also provides the necessary data to evaluate, at least to some extent, the performance of 3D reconstruction approaches. Data were acquired using a GoPro Hero 4 Black action camera with image dimensions of 4000 x 3000 pixels, focal length of 2.77mm and pixel size of 1.55μm and a tripod. Action cameras are widely used for underwater image acquisition. The dataset was captured in near-shore underwater sites at depths varying from 0.5 to 2m. No artificial light sources were used. Due to the wind, the turbulent surface of the water created dynamic rippling caustics on the seabed. In total 1465 RGB images were collected, separated in 7 different datasets; five of them containing stereo images, one of them tri-stereo images and one consists of multi-stereo imagery acquired in 7 different camera poses.</p>
<p> </p>
<p><strong>Publication</strong></p>
<p>The paper is availbale in Open Access here: https://ieeexplore.ieee.org/document/10172291</p>
<p><strong>If you use this dataset please cite it as R-CAUSTIC</strong> [Reference].<br>[Reference]: <strong>P. Agrafiotis, K. Karantzalos and A. Georgopoulos, "Seafloor-Invariant Caustics Removal From Underwater Imagery," in </strong><em><strong>IEEE Journal of Oceanic Engineering</strong></em><strong>, vol. 48, no. 4, pp. 1300-1321, Oct. 2023, doi: 10.1109/JOE.2023.3277168.</strong></p>
<p>BibTeX:</p>
<p>@ARTICLE{10172291, author={Agrafiotis, Panagiotis and Karantzalos, Konstantinos and Georgopoulos, Andreas}, journal={IEEE Journal of Oceanic Engineering}, title={Seafloor-Invariant Caustics Removal From Underwater Imagery}, year={2023}, volume={48}, number={4}, pages={1300-1321}, doi={10.1109/JOE.2023.3277168}}</p>
<p> </p>
Does genetic diversity on corporate boards lead to improved environmental performance?
Get PDFElsevier
Journal of International Financial Markets, Institutions and Money
Volume 84, April 2023, 101756
Journal of International Financial Markets, Institutions and Money
Does genetic diversity on corporate boards lead to improved environmental performance?
Author links open overlay panelRenatas Kizys a, Emmanuel C. Mamatzakis b, Panagiotis Tzouvanas c
Show more
Outline
Share
Cite
https://doi.org/10.1016/j.intfin.2023.101756
Get rights and content
Under a Creative Commons license
open access
Highlights
•
We examine the effect of boards’ genetic diversity (GENETICD) on corporate ESG performance.
•
ESG performance and disclosures are higher in more genetically diverse firms.
•
The positive GENETICD effect on ESG performance is driven by the environmental pillar.
•
Corporate carbon performance significantly improves with increases in GENETICD.
We study the effects of boards’ genetic diversity on corporate environmental performance. Using a multidimensional information set for 3690 US firms during the period from 2005 to 2019, and three different measures of genetic diversity, we find that, pursuant to the diversity theory, which posits that diversity improves the quality of management decisions and business ethics, genetic diversity leads to improved environmental performance. We also find that genetic diversity improves carbon and governance performance, and ESG disclosure. Particularly, a one percentage point increase in boards’ genetic diversity will increase the carbon performance, measured by the inverse of the carbon emissions to total assets ratio, and environmental performance by 3.54% and 5.57%, respectively. Our results remain robust to different model specifications, while also controlling for endogeneity. In terms of policy implications, results suggest that the key to tackling climate challenges is to promote boards’ genetic diversity
- …
