102,079 research outputs found
Migration, Class Attainment and Social Mobility : An Analysis of Migrants’ Socio-Economic Integration in Italy
No full textThis article focuses on the socio-economic integration of ethnic minorities in Italy, combining the literature on migration with research on social stratification. We analyse the ethnic penalty on occupational attainment and career mobility, integrating the origin–education–destination theoretical framework with the migration status. Since ethnic penalty is an ‘umbrella concept’, we also quantify the extent to which it is mediated by differences in education and social origin. Furthermore, adopting a diachronic view of migrants’ class attainment, we verify whether the post-migration downgrading is followed by a recovery during the career, considering also mobility within the working class (standard and non-standard). Our analyses are based on the Multipurpose Survey on Households and Social Condition and Integration of Foreign Citizens. The results show that migrants are penalized in the Italian labour market, remaining largely ‘trapped’ in the working class. This inclusion at the bottom of the class structure reduces their heterogeneity by education and by social origin. Moreover, their penalty increases during the career, except when they move from the non-standard to the standard working class. Finally, we find that the ‘unexplained’ component of ethnic penalty, net of education and social origin, is substantial and increases from the first to the current job
3D Modelling to Support Dental Surgery
No full textIn a previous work, we developed a general purpose framework to support the three-dimensional reconstruction,
rendering and processing of biomedical images, 3D Bio-IPF. In this paper we present a structured component of 3D Bio-IPF, the
plug-in Implant, to model customised dental implants on a three-dimensional representation of the oral cavity derived from
diagnostic images. The proposed tool was tested on different cases and a result is reported. It has been proven it is very effective for
dental surgery planning, implant design and positioning. Moreover, if integrated with a position indicator system and a numerically
positionable drilling machine, it could be employed for semi-automatic surgery
Migration, social stratification, and labor market attainment: An analysis of the ethnic penalty in 12 Western European countries
No full textThis article presents a comprehensive investigation into the socioeconomic integration of migrants across 12 Western European countries, considering their likelihood of employment and socioeconomic status. Using the data from the European Social Survey, the study employs linear regression and probit models to achieve two aims: (a) to quantify the penalty for male and female migrants in terms of employment and socioeconomic status attainment; (b) to assess how the ethnic penalty for men and women changes based on their education and social background of origin. Results reveal that male and female migrants face a penalty in most countries under consideration, albeit with varying degrees of magnitude and characteristics. Migrants in Southern European countries exhibit a trade-off between employment and socioeconomic status attainment, while those in Central-Northern Europe experience a double penalty on both outcomes. Moreover, it emerges that the ethnic penalty in labor market attainment is more heterogeneous across migrants with different educational levels than with different social classes of origin: migrants’ social background of origin affects to a lesser extent their labor market outcomes, if compared with their human capital. Migrants with high education and social origin suffer the largest penalty, due to hurdles in leveraging their educational qualifications and social position. This pattern is particularly evident in Southern Europe, where the socioeconomic integration of migrant workers is characterized by a leveling-down process, pushing them into the lowest strata of the occupational hierarchy regardless of their education and social background
Caratterizzazione preliminare di farine di semi di carruba (Ceratonia siliqua L.) di differente origine geografica
No full textLa farina di semi di carruba, nota internazionalmente come Locust Bean Gum (LBG) e classificata nella lista europea degli additivi alimentari con la sigla E410, viene impiegata come addensante e stabilizzante nelle preparazioni alimentari. Obiettivo del presente lavoro è quello di valutare le varietà di carrubo più idonee per l'ottenimento di rivestimenti edibili da impiegare nella conservazione degli alimenti. L'interesse verso i film edibili per il diretto rivestimento dei prodotti alimentari è legato alla capacità di fungere da barriera con l'esterno e quindi di regolare gli scambi gassosi che potrebbero compromettere la salubrità e le proprietà sensoriali dell'alimento. Dodici varietà di carrubo, di differente provenienza geografica (Italia, Spagna, Tunisia, Turchia, Marocco), sono state analizzate effettuando le seguenti determinazioni: caratterizzazione dei semi, resa in germe e gomma, proprietà reologiche di soluzioni standard. Lo studio è stato sviluppato in modo da caratterizzare dal punto di vista reologico, diverse tipologie di soluzioni per coating in modo da ottenere il maggior numero di informazioni al fine della loro eventuale selezione ed applicazione.
Le varietà italiane Ibla e Racemosa e quella marocchina si sono dimostrate le migliori in termini di resa, la varietà proveniente dal Marocco si distingue anche per l'elevato potenziale tecnologico
Disuguaglianze territoriali e ritorni dell’istruzione. Un’analisi del dualismo Nord-Sud e delle differenze tra aree centrali e marginali in Italia = Geographical inequalities and returns to education. An analysis of the North-South divide and differences between central and marginal areas in Italy
No full textClassical research on returns to education has systematically shown that individuals with more schooling are more likely to have higher earnings, prestige, social status, etc. Few studies focused on the role of spatial arrangements and geographical inequalities in this debate, despite most developed societies experience growing territorial disparities. In this respect, Italy has been experiencing large disparities between ‘central’ and ‘marginal’ areas, which go beyond the classic rural/urban and North/South cleavages. This work aims at studying if and how returns to education differ between ‘central’ and ‘marginal’ areas in Italy. Analyses based on the Italian Labour Force Survey (2009-2020) show that tertiary educated living in Northern provinces earn much more than those living in provinces located in the South or in the Islands. Moreover, the higher the marginality of a province (i.e., the larger the proportion of population of a province living in ‘marginal’ municipalities), the lower the returns to tertiary education. However, large part of this association is explained by the North-South divide. Therefore, the cleavage between marginal and central areas is crucial and cumulates with the North-South one. The penalization of tertiary educated living in marginal areas occurs only in an already disadvantaged context (South), whereas more advantaged contexts (North) are likely to have characteristics that compensate for the penalization given by the geographical marginality
FaceVision-GAN: A 3D Model Face Reconstruction Method from a Single Image Using GANs
No full textGenerative algorithms have been very successful in recent years. This phenomenon derives from the strong computational power that even consumer computers can provide. Moreover, a huge amount of data is available today for feeding deep learning algorithms. In this context, human 3D face mesh reconstruction is becoming an important but challenging topic in computer vision and computer graphics. It could be exploited in different application areas, from security to avatarization. This paper provides a 3D face reconstruction pipeline based on Generative Adversarial Networks (GANs). It can generate high-quality depth and correspondence maps from 2D images, which are exploited for producing a 3D model of the subject’s face
SIRe-Networks: Convolutional neural networks architectural extension for information preservation via skip/residual connections and interlaced auto-encoders
No full textImproving existing neural network architectures can involve several design choices such as manipulating the loss functions, employing a diverse learning strategy, exploiting gradient evolution at training time, optimizing the network hyper-parameters, or increasing the architecture depth. The latter approach is a straightforward solution, since it directly enhances the representation capabilities of a network; however, the increased depth generally incurs in the well-known vanishing gradient problem. In this paper, borrowing from different methods addressing this issue, we introduce an interlaced multi-task learning strategy, defined SIRe, to reduce the vanishing gradient in relation to the object classification task. The presented methodology directly improves a convolutional neural network (CNN) by preserving information from the input image through interlaced auto-encoders (AEs), and further refines the base network architecture by means of skip and residual connections. To validate the presented methodology, a simple CNN and various implementations of famous networks are extended via the SIRe strategy and extensively tested on five collections, i.e., MNIST, Fashion-MNIST, CIFAR-10, CIFAR-100, and Caltech-256; where the SIRe-extended architectures achieve significantly increased performances across all models and datasets, thus confirming the presented approach effectiveness
Homography vs similarity transformation in aerial mosaicking: which is the best at different altitudes?
No full textAerial image mosaicking of an area of interest is the process of combining multiple images, of an area with overlapping regions, into a single comprehensive view. In this process, image registration, i.e., the operation of geometric transformation to align and overlay two or more images of the same scene taken from different viewpoints, starting from their common parts, plays a key role in terms of artifacts reduction. In the current state-of-the-art, image registration of aerial images is usually performed through the use of the homography transformation. This occurs because these images are frequently acquired at high altitudes (more than 100 meters) and the homography has always provided excellent performance. The recent widespread of Unmanned Aerial Vehicles (UAVs) has enabled the development of several applications where mosaics are used as reference images for high precision tasks, including Detection, Recognition, and Identification (hereinafter DRI) of people and objects. These tasks need to acquire images at very low altitudes (below 50 meters), in which the homography tends to introduce artifacts during the registration process. Therefore, a different transformation able to limit how an image can be morphed, i.e., the similarity transformation, is necessary to perform the image registration, thus improving the overall accuracy of the obtained mosaics. In this paper, for the first time in literature, a comparison between the homography and similarity transformations is performed. In particular, the comparison is carried out by using three recently released public datasets, i.e., NPU Drone-Map, senseFly, and UAV Mosaicking and Change Detection (UMCD), containing challenging aerial video sequences acquired at high and low altitudes. The experimental tests have pointed out the direct relationship among best image transformation, UAV altitude, and spatial resolution, required to accomplish the DRI tasks reported above
Overall Design and Implementation of the Virtual Glove
No full textPost-stroke patients and people suffering from hand diseases often need rehabilitation therapy. The recovery of original skills, when possible, is closely related to the frequency, quality, and duration of rehabilitative therapy. Rehabilitation gloves are tools used both to facilitate rehabilitation and to control improvements by an evaluation system. Mechanical gloves have high cost, are often cumbersome, are not re-usable and, hence, not usable with the healthy hand to collect patient-specific hand mobility information to which rehabilitation should tend. The approach we propose is the virtual glove, a system that, unlike tools based on mechanical haptic interfaces, uses a set of video cameras surrounding the patient hand to collect a set of synchronized videos used to track hand movements. The hand tracking is associated with a numerical hand model that is used to calculate physical, geometrical and mechanical parameters, and to implement some boundary constraints such as joint dimensions, shape, joint angles, and so on. Besides being accurate, the proposed system is aimed to be low cost, not bulky (touch-less), easy to use, and re-usable.Previous works described the virtual glove general concepts, the hand model, and its characterization including system calibration strategy. The present paper provides the virtual glove overall design, both in real-time and in off-line modalities. In particular, the real-time modality is described and implemented and a marker-based hand tracking algorithm, including a marker positioning, coloring, labeling, detection and classification strategy, is presented for the off-line modality. Moreover, model based hand tracking experimental measurements are reported, discussed and compared with the corresponding poses of the real hand. An error estimation strategy is also presented and used for the collected measurements. System limitations and future work for system improvement are also discussed. © 2013 Elsevier Ltd
- …
