256 research outputs found
Exploiting Textons Distributions on Spatial Hierarchy for Scene Classification
This paper proposes a method to recognize scene categories using bags of visual words obtained by hierarchically partitioning into subregion the input images. Specifically, for each subregion the Textons distribution and the extension of the corresponding subregion are taken into account. The bags of visual words computed on the subregions are weighted and used to represent the whole scene. The classification of scenes is carried out by discriminative methods (i.e., SVM, KNN). A similarity measure based on Bhattacharyya coefficient is proposed to establish similarities between images, represented as hierarchy of bags of visual words. Experimental tests, using fifteen different scene categories, show that the proposed approach achieves good performances with respect to the state-of-the-art methods
Did the Hilda collisional family form during the late heavy bombardment?
We model the long-term evolution of the Hilda collisional family located in
the 3/2 mean-motion resonance with Jupiter. Its eccentricity distribution
evolves mostly due to the Yarkovsky/YORP effect and assuming that: (i) impact
disruption was isotropic, and (ii) albedo distribution of small asteroids is
the same as for large ones, we can estimate the age of the Hilda family to be
. We also calculate collisional activity in the J3/2
region. Our results indicate that current collisional rates are very low for a
200\,km parent body such that the number of expected events over Gyrs is much
smaller than one.
The large age and the low probability of the collisional disruption lead us
to the conclusion that the Hilda family might have been created during the Late
Heavy Bombardment when the collisions were much more frequent. The Hilda family
may thus serve as a test of orbital behavior of planets during the LHB. We
tested the influence of the giant-planet migration on the distribution of the
family members. The scenarios that are consistent with the observed Hilda
family are those with fast migration time scales to
, because longer time scales produce a family that is depleted
and too much spread in eccentricity. Moreover, there is an indication that
Jupiter and Saturn were no longer in a compact configuration (with period ratio
) at the time when the Hilda family was created
LAGEOS-type Satellites in Critical Supplementary Orbit Configuration and the Lense-Thirring Effect Detection
In this paper we analyze quantitatively the concept of LAGEOS--type
satellites in critical supplementary orbit configuration (CSOC) which has
proven capable of yielding various observables for many tests of General
Relativity in the terrestrial gravitational field, with particular emphasis on
the measurement of the Lense--Thirring effect.Comment: LaTex2e, 20 pages, 7 Tables, 6 Figures. Changes in Introduction,
Conclusions, reference added, accepted for publication in Classical and
Quantum Gravit
Rescaling Egocentric Vision: Collection, Pipeline and Challenges for EPIC-KITCHENS-100
This paper introduces the pipeline to extend the largest dataset in egocentric vision, EPIC-KITCHENS. The effort culminates in EPIC-KITCHENS-100, a collection of 100 hours, 20M frames, 90K actions in 700 variable-length videos, capturing long-term unscripted activities in 45 environments, using head-mounted cameras. Compared to its previous version (Damen in Scaling egocentric vision: ECCV, 2018), EPIC-KITCHENS-100 has been annotated using a novel pipeline that allows denser (54% more actions per minute) and more complete annotations of fine-grained actions (+128% more action segments). This collection enables new challenges such as action detection and evaluating the “test of time”—i.e. whether models trained on data collected in 2018 can generalise to new footage collected two years later. The dataset is aligned with 6 challenges: action recognition (full and weak supervision), action detection, action anticipation, cross-modal retrieval (from captions), as well as unsupervised domain adaptation for action recognition. For each challenge, we define the task, provide baselines and evaluation metrics.Published versionResearch at Bristol is supported by Engineering and Physical Sciences Research Council (EPSRC) Doctoral Training Program (DTP), EPSRC Fellowship UMPIRE (EP/T004991/1). Research at Catania is sponsored by Piano della Ricerca 2016-2018 linea di Intervento 2 of DMI, by MISE - PON I&C 2014-2020, ENIGMA project (CUP: B61B19000520008) and by MIUR AIM - Attrazione e Mobilita Internazionale Linea 1 - AIM1893589 - CUP E64118002540007
Colovesical fistulae in the sigmoid diverticulitis
Nella maggior parte dei casi le fistole colovescicali rappresentano una complicanza della malattia diverticolare e sono la tipologia più comune di fistola colodigestiva; meno comuni sono le fistole colovaginali, colocutanee, coloenteriche e colouterine. Nel presente lavoro abbiamo effettuato una review della letteratura riguardante le fistole colovescicali in chirurgia colorettale per diverticolite del sigma. Decriviamo anche due casi che hanno richiesto un trattamento chirurgico, in uno in elezione e nell’altro in urgenza. In entrambi i casi abbiamo eseguito una resezione colica con anastomosi primaria e minimaresezione vesvicale con posizionamento di catetere di Foley in media per 10 giorni
Objective estimation of body condition score by modeling cow body shape from digital images.
Body condition score (BCS) is considered an important tool for management of dairy cattle. The feasibility of estimating the BCS from digital images has been demonstrated in recent work. Regression machines have been successfully employed for automatic BCS estimation, taking into account information of the overall shape or information extracted on anatomical points of the shape. Despite the progress in this research area, such studies have not addressed the problem of modeling the shape of cows to build a robust descriptor for automatic BCS estimation. Moreover, a benchmark data set of images meant as a point of reference for quantitative evaluation and comparison of different automatic estimation methods for BCS is lacking. The main objective of this study was to develop a technique that was able to describe the body shape of cows in a reconstructive way. Images, used to build a benchmark data set for developing an automatic system for BCS, were taken using a camera placed above an exit gate from the milking robot. The camera was positioned at 3 m from the ground and in such a position to capture images of the rear, dorsal pelvic, and loin area of cows. The BCS of each cow was estimated on site by 2 technicians and associated to the cow images. The benchmark data set contained 286 images with associated BCS, anatomical points, and shapes. It was used for quantitative evaluation. A set of example cow body shapes was created. Linear and polynomial kernel principal component analysis was used to reconstruct shapes of cows using a linear combination of basic shapes constructed from the example database. In this manner, a cow's body shape was described by considering her variability from the average shape. The method produced a compact description of the shape to be used for automatic estimation of BCS. Model validation showed that the polynomial model proposed in this study performs better (error=0.31) than other state-of-the-art methods in estimating BCS even at the extreme values of BCS scale
Remote Working and Home Learning: How the Italian Academic Population Dealt with Changes Due to the COVID-19 Pandemic Lockdown
The COVID-19 pandemic introduced changes in people's lives that affected their mental health. Our study aimed to explore the level of psychological distress in the academic population during the lockdown period and investigate its association with the new working or studying conditions. The study sample included 9364 students and 2159 employees from five Italian universities from the study IO CONTO 2020. We applied linear regression models to investigate the association between home learning or remote working conditions and psychological distress, separately for students and employees. Psychological distress was assessed using the Hospital Anxiety and Depression Scale (HADS). In both students and employees, higher levels of distress were significantly associated with study/work-family conflicts, concerns about their future careers, and inadequacy of equipment; in employees, higher levels of distress were significantly associated with a lack of clarity on work objectives. Our results are in line with previous research on the impact of spaces and equipment in remote working/studying from home. Moreover, the study contributes to deepening the association between well-being and telework-family conflict, which in the literature is still equivocal. Practical implications require academic governance to promote sustainable environments both in remote and hybrid work conditions, by referring to a specific management by objectives approach
Remote-working and home-learning: how the Italian academic population dealt with changes due to the COVID-19 pandemic lockdown
The COVID-19 pandemic introduced changes in people’s lives that affected their mental
health. Our study aimed to explore the level of psychological distress in the academic population dur-
ing the lockdown period and investigate its association with the new working or studying conditions.
The study sample included 9364 students and 2159 employees from five Italian universities from the
study IO CONTO 2020. We applied linear regression models to investigate the association between
home learning or remote working conditions and psychological distress, separately for students and
employees. Psychological distress was assessed using the Hospital Anxiety and Depression Scale
(HADS). In both students and employees, higher levels of distress were significantly associated with
study/work–family conflicts, concerns about their future careers, and inadequacy of equipment;
in employees, higher levels of distress were significantly associated with a lack of clarity on work
objectives. Our results are in line with previous research on the impact of spaces and equipment in
remote working/studying from home. Moreover, the study contributes to deepening the association
between well-being and telework–family conflict, which in the literature is still equivocal. Practical
implications require academic governance to promote sustainable environments both in remote and
hybrid work conditions, by referring to a specific management by objectives approach
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