86,566 research outputs found
A riconversion proposal: Palazzo Lembo in Baselice, Benevento, Italy
No full textGli abstract sono su carta stampata, le memorie su CD allegato al volume degli atti. E' illustrata la proposta di riqualificazione di Palazzo Lembo in Baselice (BN) ad esposizione paleontologica
EU consumers' perception of fresh-cut fruit and vegetables attributes: a choice experiment model
No full textAbstract: This thesis aims to study consumers’ perception in relation to fresh-cut fruit and
vegetables consumption. In the first part of the work, the main features of the European freshcut
fruit and vegetables market are discussed, paying more focus on the Italian demand of fruit
and vegetables. The middle part is mainly represented by a systematic review of the literature
investigating factors affecting the food choice decisions of adults in relation to fruit and
vegetable consumption, with more emphasis to fresh-cut produces. Finally, there is the
experimental part, in which European consumers’ preferences of fresh-cut fruit and vegetables
are investigated through an econometric analysis.
The fresh-cut sector is constantly evolving and innovating in order to enhance quality and
safety of products, which attributes are generally valued by consumers. Quality and safety are
multifaceted attributes because they arise from a wide set of methods/technologies, therefore
the knowledge about consumers’ preferences for food technologies is still matter of debate.
The main objective of this thesis it to test whether new fresh-cut fruit and vegetables
attributes influence consumers’ choices and preferences. At the same time, we are able to verify
the influence of socio-demographic characteristics on consumers’ preferences.
A Latent Class Multinomial Logit Model has been fitted for almost 1.500 consumers of
four different European countries: Greece, Italy, Spain and United Kingdom, in order to divide
the consumers in different latent classes based on their choice and their characteristics.
Fresh-cut F&V consumers for the four European countries, have a similar behavior in
terms of preferences. We can divide the consumers in two different latent classes: the first made
by consumers that do not appreciate any fresh-cut F&V attributes, and the second that include
consumers that appreciate the several fresh-cut F&V attributes. Even if the cross-country
comparison of consumers’ preferences has not produced substantial differences across the
different countries, socio-demographic characteristics influence the perception of consumers
about the consumption of fresh-cut fruit and vegetables
MUHD: A multi-channel ultrasound prototype for remote heartbeat detection
No full textThis paper presents a novel system based on ultrasonic waves that is capable of detecting heartbeat in a contactless fashion. The aim of this work is to design, build and test a prototype that could be effective, simple in its realisation and use and with a low cost of production. The idea is the exploit the displacement of the skin related to cardiac activity, that is possible by using phase difference between a transmitted wave and the waves resulting from the interaction with the subject skin. Nevertheless, this type of procedure is not new in the scientific literature, but in this manuscript the authors contribution mainly consists in the implementation of a multi-channel architecture in order to overcome the well known “null-point” issue. Furthermore, an a-priori regularisation function is used for making the system more robust against noise and artifact. The performance of the prototype has been tested on volunteers and the results are quite close to standard electrocardiography used as reference
WKSR-NLM: An Ultrasound Despeckling Filter Based on Patch Ratio and Statistical Similarity
No full textUltrasound images are affected by the well known speckle phenomenon, that degrades their perceived quality. In recent years, several denoising approaches have been proposed. Among all, those belonging to the non-local (NL) family have shown interesting performance. The main difference among the proposed NL filters is the metric adopted for measuring the similarity between patches. Within this manuscript, a statistical metric based on the ratio between two patches is presented. Compared to other statistical measurements, the proposed one is able to take into account the texture of the patch, to consider a weighting kernel and to limit the computational burden. A comparative analysis with other despeckling filters is presented. The method provided good balance between noise reduction and details preserving both in case of simulated (by means of Field II software) and real (breast tumor) datasets
Neural Networks for Inverse Problems: The Microwave Imaging Case
No full textIn the framework of inverse scattering problems, this paper investigates the use of different artificial-neural network architectures for imaging purposes by processing the data collected at receivers locations in a multiview-multistatic fashion. Generally, this type of problems is strongly nonlinear and ill-posed, thus the development of fast and reliable approaches is paramount for practical implementations. In the last years, machine learning approaches have proved to be very promising to recover quantitatively the electromagnetic features of objects located in an investigation domain, but at the expense of large data sets required for the training procedure. More in detail, this communication tries to explore the role of the network topology by exploiting three different scenarios with an increasingly higher degree of non-linearity
Extended Kalman Filter for Multichannel InSAR Height Reconstruction
No full textOne of the main challenges in Interferometric Synthetic Aperture Radar (SAR) is the accurate height reconstruction of the observed scene. Recently, approaches based on Extended Kalman Filter (EKF) have been proposed. Most of them are based on the hypothesis of height profile continuity. Such condition greatly reduces their applicability, being only valid for particular scenarios. Within this paper, we present a novel Kalman-based height reconstruction approach, specifically designed to work with multichannel data related to any type of scenario, both smooth or sharp. The novelty of the technique consists in its ability in detecting and correctly handling sharp height discontinuities while regularizing smooth areas. The approach is able to maintain the high computational efficiency typical of EKF and to work in an almost unsupervised way. The methodology has been tested and validated on both simulated and real X-band (TerraSAR-X and COSMO-SkyMed) high-resolution data sets. Reported results are encouraging and interesting, showing the correctness and the validity of the proposed approach
A tomographic multiview-multistatic ultrasound system for biomedical imaging applications
No full textMedical imaging is a paramount concern in modern society. Thus, there is an increasing interest and attention to new imaging modalities which can support standard exams and/or replace them in diseases diagnosis. In this framework, ultrasound tomography could have an important role for some biomedical applications, such as for breast cancer imaging, since it would allow to overcome some limitations related to standard ultrasound exams which are operator-dependent and usually are not based on a coherent processing, reducing the reconstruction performance considerably. To this aim, in this article a preliminary air-based ultrasound tomographic imaging system is described and tested. The prototype was designed, built and tested at the University of Naples Parthenope with the aim of providing some interesting data sets for testing and comparison of imaging algorithms in a laboratory-controlled environment, which represents a mandatory step before moving to the realistic case of a water-matched device
Artificial neural networks for quantitative microwave breast imaging
No full textThis paper is focused on the use of artificial neural networks (ANNs) for biomedical microwave imaging of breast tissues in the framework of advanced breast cancer imaging techniques. The proposed scheme processes the scattered field collected at receivers locations of a multiview-multistatic system and aims at providing an estimate of the morphological and dielectric features of the breast tissues, which represents a strongly nonlinear scenario with several challenging aspects. In order to train the network, a simulated data set has been created by implementing the forward problem and an automatic randomly-shaped breast profile generator based on the statistical distribution of complex permittivity of breast biological tissues was developed. Some numerical tests were carried out to evaluate the performance of the proposed method and, in conclusion, we found that the use of ANNs for quantitative biomedical imaging purposes seems to be very promising
An Experimental Ultrasound Database for Tomographic Imaging
No full textIn the framework of non-destructive testing and imaging, ultrasound tomography can have an important role in several applications, especially in the biomedical field. The motivation beyond the use of this imaging technique lies in the possibility of obtaining quantitative imaging which is also operator-independent, conversely to conventional approaches. Thus, the need for public data sets for testing inverse scattering approaches is always persisting. To this aim, this paper introduces an experimental multiple-input-multiple-output ultrasound tomographic database whose acquisitions were performed by an air-matched in-house system designed and built by the Authors. The proposed database provides several cases with single and multiple objects of different shapes, sizes, and materials, to be imaged in laboratory-controlled conditions. Therefore, these scenarios can represent interesting options for the preliminary testing of tomographic ultrasound imaging approaches
An End-to-End Deep Learning Approach for Quantitative Microwave Breast Imaging in Real-Time Applications
No full text(1) Background: In this paper, an artificial neural network approach for effective and real-time quantitative microwave breast imaging is proposed. It proposes some numerical analyses for the optimization of the network architecture and the improvement of recovery performance and processing time in the microwave breast imaging framework, which represents a fundamental preliminary step for future diagnostic applications. (2) Methods: The methodological analysis of the proposed approach is based on two main aspects: firstly, the definition and generation of a proper database adopted for the training of the neural networks and, secondly, the design and analysis of different neural network architectures. (3) Results: The methodology was tested in noisy numerical scenarios with different values of SNR showing good robustness against noise. The results seem very promising in comparison with conventional nonlinear inverse scattering approaches from a qualitative as well as a quantitative point of view. (4) Conclusion: The use of quantitative microwave imaging and neural networks can represent a valid alternative to (or completion of) modern conventional medical imaging techniques since it is cheaper, safer, fast, and quantitative, thus suitable to assist medical decisions
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