336 research outputs found
Sull’asse Bologna-Padova-Venezia: un’inaspettata relazione fra Pietro Lombardo e Marco Zoppo
No full textThe article sheds light on the relationship between the oculi on the pediment of the polyptych by Marco Zoppo at the Collegio di Spagna in Bologna, and those carved by Pietro Lombardo for the pendentives of the cupola of the presbytery of San Giobbe in Venice. After noting how unlikely it would be that these solutions might be linked to a single prototype that has now been lost, the author sets out the circumstances that would have made it possible for Lombardo, whose oculi are of later date than those of Zoppo, to have seen the Collegio’s polyptych. Other works by Lombardo demonstrate that, at a time when both artists were living in the Venice area, he maintained a certain amount of attention to what Zoppo released. Zoppo, for his part, without having any particular partiality for Lombardo’s production, was nevertheless regularly compared to the highest-level sculptural works of the day
A continuous-time learning rule for memristor-based recurrent neural networks
No full textAmong the recent disruptive technologies, volatile/nonvolatile memory-resistor (memristor) has attracted the researchers' attention as a fundamental computation element. It has been experimentally shown that memristive elements can emulate synaptic dynamics and are even capable of supporting spike timing dependent plasticity (STDP), an important adaptation rule for competitive Hebbian learning. The overall goal of this work is to provide a novel analogue computing platform based on memristor devices and recurrent neural networks that exploit the memristor device physics to implement the backpropagation algorithm. Back propagation for recurrent neural networks requires a side network for the propagation of error derivatives. The use of memristor-based synaptic weights permit to propagate the error signals in the network via the nonlinear dynamics without the need of a digital side network. Experimental results show that the approach significantly outperforms conventional architectures used for pattern reconstruction. Further results will be reported in an extended work
Computing with Memristor-based Nonlinear Oscillators
No full textAmong the recent disruptive technologies, volatile/nonvolatile memory-resistor (memristor) has attracted the researchers' attention as a fundamental computation element. It has been experimentally shown that memristive elements can emulate synaptic dynamics and are even capable of supporting spike timing dependent plasticity (STDP), an important adaptation rule for neuromorphic computing systems. The overall goal of this work is to provide an unconventional computing platform exploiting memristor-based nonlinear oscillators described by means of phase deviation equations. Experimental results show that the approach significantly outperforms conventional architectures used for pattern recognition tasks
Pattern Characterization in Second Order Memristor Networks
No full textSecond order memristors are two terminal devices which present a conductance depending on two orders of variables, namely the geometric parameters and the internal temperature. They have shown to be able to mimic some specific features of neuron synapses, specifically Spike-Timing-Dependent-Plasticity (STDP), and consequently to be good candidates for neuromorphic computing. In particular memristor crossbar structures appear to be suitable for implementing locally competitive algorithms and for tackling classification problems, by exploiting temporal learning techniques. On the other hand spiking networks have been intensively studied in the context of unsupervised, supervised and reinforcement learning. In this manuscript we briefly present a simplified model of second order memristors, that we have derived in a previous paper. Then we focus on two main results. As a first step we show that the model is capable of accurately reproducing a correct synaptic response to complex inputs, like cycles of spike triplets and quadruplets at different frequencies. Then we show that, exploiting such a simple model, complex spatio-temporal patterns can be almost analytically characterized, in memristor networks connecting an arbitrary number of presynaptic and postsynaptic neurons
Recycling of wasted wool fibers from sheep shearing for green building components: a review
No full textIt is nowadays recognized that the building sector causes the greatest environmental impact in terms of both waste production and carbon emissions. Within the context of ecologically sustainable development (ESD), the construction sector is looking for more eco-friendly materials, such as natural fibres. Natural fibers are worldwide recognized as ideal replacement for traditional construction materials, providing excellent thermal and acoustic insulation for building but also for adoption as reinforcement fibers in cement mortars, composite materials, solid boards/panels, raw biomasses, multi-layers, filled loosen/foaming types, particles, slurry types, coils, bricks, etc. The aim of this work is to provide a clear overview on the natural fibers currently employed in the green production of building components, with the main focus on wool fibers deriving from the livestock sector, where wool waste disposal is a crucial problem. This article is a review conducted using the Systematic Literature Review (SLR) approach, a globally recognized method that is not inherently innovative. The innovation of this article lies in the addressed topic, which is relatively new and has only recently gained significant attention, resulting in a limited number of highly relevant articles in the literature. A systematic literature review of the use of wool fibers for green building components is conducted herein to highlight the characteristics that make such material a usable resource in the construction sector and the limits of its use. Given the findings from the reviewed papers, the authors could document that most of the reviewed articles aimed at analyzing the mechanical, thermal, and acoustic properties of building components containing wool fibres. The review highlights that the strength of the wool fiber relies on its thermal properties which can be exploited for building thermal insulation. The wool fiber is also featured to provide good resistance to flexural loads; conversely, all the studies highlighted a negative effect of wool fibers on the compressive behavior of the investigated building components. The analysis of the acoustic properties showed that given the strong capacity of the wool fiber to absorb sound, wool is a great alternative to the conventional materials derived from non-renewable resources. Nevertheless, despite the eligibility of such fiber to be employed soon in the building sector, the analysis about the economic viability of the manufacturing process suggests that the high costs for the raw material, labor, electricity, and above all the high volume of water have to be drastically reduced by prompting the development of sheep wool fiber waterless processing. The achieved results could represent a first step in planning the sustainable re-use of wool waste as natural, renewable, and biodegradable fiber in the construction sector, providing the possibility of creating a new supply chain and solving the problem of its disposal
“Durability Assessment-based Design" approach for structural applications of advanced cement-based materials
No full textThe prescriptive method, recommended by international codes for the durability design of concrete structures, provides limits on the mix composition and steel cover. The early loss of performance of several concrete structures clearly shows the inefficiency of this method especially for structures ex-posed to challenging service scenarios. For this reason, this approach must be replaced by a durability performance-based design approach that allows to define of the evolution of the structural performance over time and schedule, consequently, ordinary maintenance campaigns. This is especially true for ad-vanced cement-based materials, whose advantages, while automatically fulfilling the composition re-quirements above, can only be appreciated in an extended maintenance-free service life.
To demonstrate the differences among the aforesaid approaches, a case study is herein presented dealing with a tank containing harsh water, rich in chlorides and sulphates, for which the degradation phenom-ena have been evaluated for both ordinary reinforced concrete and ultra-high durability concrete, both considered in the design.
All results found for both materials have been evaluated and compared to show the difference in safety and reliability between these two methods
Automatic Visual Inspection Machine for Pharmaceutical Infusion Bags Implementing Cellular Neural Networks
No full textAutomation procedures and machines in the pharmaceutical field are required to implement a series of methodologies, designed parting from international standards, in order to ensure the high quality of the products. Regarding infusion bags, the standards require to thoroughly assess the conformity of the product before being used in patients. The inspection procedures are usually operator-based and therefore subject to human factor errors. A novel inspection machine has been designed and developed with the use of a specifically designed cellular neural network (CNN) coupled with an off-the-shelf neural network trainable solution. The novel machine, thanks to the computational versatility of the CNN, is capable of reaching high standards of assessment drastically decreasing the risk of operator-based errors in the procedure
Assessing the effect of tsunami-induced vertical loads on RC frames
No full textThe increasing number of people, structures and economic activities being exposed to tsunami hazards
makes it important to estimate the effects of this hazard on coastal developments. Tsunami onshore
flow generates significant loading on buildings and infrastructure, which can lead to structural failure.
Literature works recently proposed a non-linear static analysis method, called Variable Depth Pushover
(VDPO), for assessing the performance of buildings under the lateral pressures induced by a tsunami
onshore flow. This methodology was developed under the assumption that the building is watertight.
However, in the case of buildings with breakaway cladding (e.g., masonry infills), the water flow passing through the building induces vertical loads on horizontal structural members, due to uplift and
buoyancy pressures, that should be considered during the analysis. Thus, to address this phenomenon,
in this paper a numerical investigation is performed considering a combination of tsunami-induced
horizontal and vertical loads on a case-study reinforced concrete (RC) moment-resisting frame with
breakaway infills, typical of Mediterranean construction. The building model is subjected to a VDPO
analysis that applies different types and sizes of vertical loading on the horizontal elements of the building, as the tsunami inundation depth increases. From the results of this analysis, the effects of tsunamiinduced vertical load components on the case-study building in terms of damage propagation and failure
mode are discussed, and the significance of considering vertical loading is proven
Analog Solutions of Discrete Markov Chains via Memristor Crossbars
No full textProblems involving discrete Markov Chains are solved mathematically using matrix methods. Recently, several research groups have demonstrated that matrix-vector multiplication can be performed analytically in a single time step with an electronic circuit that incorporates an open-loop memristor crossbar that is effectively a resistive random-access memory. Ielmini and co-workers have taken this a step further by demonstrating that linear algebraic systems can also be solved in a single time step using similar hardware with feedback. These two approaches can both be applied to Markov chains, in the first case using matrix-vector multiplication to compute successive updates to a discrete Markov process and in the second directly calculating the stationary distribution by solving a constrained eigenvector problem. We present circuit models for open-loop and feedback configurations, and perform detailed analyses that include memristor programming errors, thermal noise sources and element nonidealities in realistic circuit simulations to determine both the precision and accuracy of the analog solutions. We provide mathematical tools to formally describe the trade-offs in the circuit model between power consumption and the magnitude of errors. We compare the two approaches by analyzing Markov chains that lead to two different types of matrices, essentially random and ill-conditioned, and observe that ill-conditioned matrices suffer from significantly larger errors. We compare our analog results to those from digital computations and find a significant power efficiency advantage for the crossbar approach for similar precision results
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