scispace - formally typeset
Search or ask a question
Institution

University of Florence

EducationFlorence, Toscana, Italy
About: University of Florence is a education organization based out in Florence, Toscana, Italy. It is known for research contribution in the topics: Population & Carbonic anhydrase. The organization has 27292 authors who have published 79599 publications receiving 2341684 citations. The organization is also known as: Università degli studi di Firenze & Universita degli studi di Firenze.


Papers
More filters
Journal ArticleDOI
TL;DR: In the last few decades, Indoor Air Quality has received increasing attention from the international scientific community, political institutions, and environmental governances for improving the comfort, health, and wellbeing of building occupants.
Abstract: In the last few decades, Indoor Air Quality (IAQ) has received increasing attention from the international scientific community, political institutions, and environmental governances for improving the comfort, health, and wellbeing of building occupants.[...].

357 citations

Journal ArticleDOI
01 Jun 1995
TL;DR: In this paper, a new patch antenna is analyzed which provides dual-frequency operation by means of two narrow slots close to the patch radiating edges, and the ratio between the two frequencies can be well controlled within a range varying from 1.6 to 2, by using simple semi-empirical formulas derived from a physical model.
Abstract: A new patch antenna is analysed which provides dual-frequency operation by means of two narrow slots close to the patch radiating edges. The two modes of operations show similar radiating properties. The ratio between the two frequencies can be well controlled within a range varying from 1.6 to 2, by using simple semi-empirical formulas derived from a physical model and tested by using a fullwave analysis. To obtain a more extended range of this frequency ratio, two tuning microstrip stubs are introduced on a back substrate. Satisfactory performances of simultaneous matching when using a single feed point is demonstrated. Several measurements are shown for both the input impedance and the radiation pattern.

357 citations

Journal ArticleDOI
TL;DR: The ARSIS concept is explained to help practitioners and researchers to better understand this concept through practical details about implementations and the general scheme for the implementation of a method belonging to this concept is presented.
Abstract: This article aims at explaining the ARSIS concept. By fusing two sets of images A and B, one with a high spatial resolution, the other with a low spatial resolution and different spectral bands, the ARSIS concept permits to synthesise the dataset B at the resolution of A that is as close as possible to reality. It is based on the assumption that the missing information is linked to the high frequencies in the sets A and B. It searches a relationship between the high frequencies in the multispectral set B and the set A and models this relationship. The general problem for the synthesis is presented first. The general properties of the fused product are given. Then, the ARSIS concept is discussed. The general scheme for the implementation of a method belonging to this concept is presented. Then, this article intends to help practitioners and researchers to better understand this concept through practical details about implementations. Two Multiscale Models are described as well as two Inter-Band Structure Models (IBSM). They are applied to an Ikonos image as an illustration case. The fused products are assessed by means of a known protocol comprising a series of qualitative and quantitative tests. The products are found of satisfactory quality. This case illustrates the differences existing between the various models, their advantages and limits. Tracks for future improvements are discussed.

357 citations

Journal ArticleDOI
TL;DR: A forensic tool able to discriminate between original and forged regions in an image captured by a digital camera is presented, based on a new feature measuring the presence of demosaicking artifacts at a local level and a new statistical model allowing to derive the tampering probability of each 2 × 2 image block without requiring to know a priori the position of the forged region.
Abstract: In this paper, a forensic tool able to discriminate between original and forged regions in an image captured by a digital camera is presented. We make the assumption that the image is acquired using a Color Filter Array, and that tampering removes the artifacts due to the demosaicking algorithm. The proposed method is based on a new feature measuring the presence of demosaicking artifacts at a local level, and on a new statistical model allowing to derive the tampering probability of each 2 × 2 image block without requiring to know a priori the position of the forged region. Experimental results on different cameras equipped with different demosaicking algorithms demonstrate both the validity of the theoretical model and the effectiveness of our scheme.

357 citations

Journal ArticleDOI
TL;DR: In this article, the (infinite-dimensional) supersymmetry algebra in 1 + 1 space-time dimension is extended in order to incorporate, in a non-trivial way, an internal symmetry.

357 citations


Authors

Showing all 27699 results

NameH-indexPapersCitations
Charles A. Dinarello1901058139668
D. M. Strom1763167194314
Gregory Y.H. Lip1693159171742
Christopher M. Dobson1501008105475
Dirk Inzé14964774468
Thomas Hebbeker1481984114004
Marco Zanetti1451439104610
Richard B. Devereux144962116403
Gunther Roland1411471100681
Markus Klute1391447104196
Tariq Aziz138164696586
Guido Tonelli138145897248
Giorgio Trinchieri13843378028
Christof Roland137130896632
Christoph Paus1371585100801
Network Information
Related Institutions (5)
Sapienza University of Rome
155.4K papers, 4.3M citations

98% related

University of Padua
114.8K papers, 3.6M citations

97% related

University of Milan
139.7K papers, 4.6M citations

97% related

University of Bologna
115.1K papers, 3.4M citations

97% related

University of Turin
77.9K papers, 2.4M citations

97% related

Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023244
2022631
20215,298
20205,251
20194,652
20184,147