The design and implementation of Underwater Wireless optical Communication (UWOC) provide important scientific problems. UWOC has the ability to transmit data at a high pace across long distances. This essay makes an ...
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In recent years, significant changes have occurred in the world situation, with major power games rapidly escalating and unprecedented intense geopolitical conflicts. The new distributed, miniaturized unmanned aerial ...
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The project REVHEAL (Structural Rehabilitation of Vaults in Heritage Asset Learning: collapse identification and design of compatible strengthening systems supported by adaptive 3D models) focuses on the identificatio...
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The project REVHEAL (Structural Rehabilitation of Vaults in Heritage Asset Learning: collapse identification and design of compatible strengthening systems supported by adaptive 3D models) focuses on the identification of the main collapse mechanisms of masonry cross vaults under differential settlements and the design of sustainable strengthening systems, both items supported by the development of novel 3D adaptive models. These objectives are pursued by means of two experimental campaigns, on small-scale and full-scale specimens, respectively. The experiments on both scale specimens are supported by 3D digital models based on point clouds and multi-scale approximated surface objects, for an accurate detection of the cracks' pattern. The full-scale tests aim at assessing the response of a 3.5 m span masonry cross-vault under shear sliding of two abutments. The test program includes two reverse cyclic quasi-static tests: the first carried out on a bare vault and the second on the same vault strengthened by an TRM overlay applied at the extrados of the specimen. This paper describes the results of preliminary FE simulations carried out on the bare vault employing a nonlinear continuum approach. In particular, a parametric study was performed to investigate different layouts of interaction between the cross-vault and the perimetral arches highlighting its importance on the overall seismic response. Indeed, this aspect may affect: (a) both the lateral stiffness and the peak strength;(b) the evolution of the cracking pattern;(c) the slope of the post-peak softening branch.
The goal of this study is to provide an analytical framework, reinforced by numerical insights, to facilitate the design of optical slab waveguides for use in optical networks of communication. This paper presents the...
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We present a nano-to-macroscale design methodology for hybrid metalens refractive opticalsystems, and evaluate our approach by fabricating and characterizing an F/1.4, 22.5mm diameter aperture visible band air-spaced...
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Data driven approaches have proven very efficient in many vision tasks and are now used for optical parameters optimization in application-specific camera design. A neural network is trained to estimate images or imag...
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ISBN:
(纸本)9781510654198;9781510654181
Data driven approaches have proven very efficient in many vision tasks and are now used for optical parameters optimization in application-specific camera design. A neural network is trained to estimate images or image quality indicators from the optical characteristics. The complexity and entanglement of such optical parameters raise new challenges we investigate in the case of wide-angle systems. We highlight them by establishing a data-driven prediction model of the RMS spot size from the distortion using mathematical or AI-based methods.
Genetic algorithms enable optical system design with off-the-shelf optics. We propose a genetic algorithm that uses five-mutation operators for a scan lens design from scratch. This work demonstrates designs of multip...
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In recent years, the growth of cognitively complex systems has motivated researchers to study how to improve these systems' support of human work. At the same time, there is a momentum for introducing Artificial I...
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ISBN:
(纸本)9783031353888;9783031353895
In recent years, the growth of cognitively complex systems has motivated researchers to study how to improve these systems' support of human work. At the same time, there is a momentum for introducing Artificial Intelligence (AI) in safety critical domains. The Air Traffic Control (ATC) system is a prime example of a cognitively complex safety critical system where AI applications are expected to support air traffic controllers in performing their tasks. Nevertheless, the design of AI systems that support effectively humans poses significant challenges. Central to these challenges is the choice of the model of how air traffic controllers perform their tasks. AI algorithms are notoriously sensitive to the choice of the models of how the human operators perform their tasks. The design of AI systems should be informed by knowledge of how people think and act in the context of their work environment. In this line of reasoning, the present study has set out to propose a framework of cognitive functions of air traffic controllers that can be used to support effectively adaptive Human - AI teaming. Our aim was to emphasize the "staying in control" element of the ATC. The proposed framework is expected to have meaningful implications in the design and effective operationalization of Human - AI teaming projects at the ATC Operations rooms.
Nowadays, the high competitiveness in the global market pushes companies to pursue innovation with the aim of reaching profitable results. Even if the adoption of Model-Based System engineering (MBSE) as an innovative...
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The current demand for efficient multiplication of large integer polynomials in contemporary cryptographic systems is crucial. This work explores the Karatsuba-like multiplication, recognized as one of the most effici...
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