Search results for " Network"
showing 10 items of 6428 documents
Emulating the Effects of Radiation-Induced Soft-Errors for the Reliability Assessment of Neural Networks
2021
International audience; Convolutional Neural Networks (CNNs) are currently one of the most widely used predictive models in machine learning. Recent studies have demonstrated that hardware faults induced by radiation fields, including cosmic rays, may significantly impact the CNN inference leading to wrong predictions. Therefore, ensuring the reliability of CNNs is crucial, especially for safety-critical systems. In the literature, several works propose reliability assessments of CNNs mainly based on statistically injected faults. This work presents a software emulator capable of injecting real faults retrieved from radiation tests. Specifically, from the device characterisation of a DRAM m…
A Curvature Based Method for Blind Mesh Visual Quality Assessment Using a General Regression Neural Network
2016
International audience; No-reference quality assessment is a challenging issue due to the non-existence of any information related to the reference and the unknown distortion type. The main goal is to design a computational method to objectively predict the human perceived quality of a distorted mesh and deal with the practical situation when the reference is not available. In this work, we design a no reference method that relies on the general regression neural network (GRNN). Our network is trained using the mean curvature which is an important perceptual feature representing the visual aspect of a 3D mesh. Relatively to the human subjective scores, the trained network successfully asses…
Redes museales en clave feminista. El caso "Relecturas" = Museum Networks from a Feminist Perspective. The case of «Relecturas»
2020
El artículo se propone analizar como caso de estudio el proyecto «Relecturas. Itinerarios museales en clave de género», nacido en 2017 bajo la coordinación de la Universitat de València con el fin de conectar museos de la ciudad de València y de su área metropolitana a través de itinerarios que ofrezcan relecturas a sus colecciones en clave de género o feminista. Se abordan algunos antecedentes del proyecto, así como su contextualización en un momento aparentemente propicio para la paulatina entrada de las mujeres en los museos. Se exponen los diferentes objetivos y metodologías de trabajo del proyecto, así como los retos que debería afrontar en un futuro para conseguir una mayor consolidac…
Propagation of Bankruptcy Risk over Scale-Free Economic Networks.
2022
The propagation of bankruptcy-induced shocks across domestic and global economies is sometimes very dramatic; this phenomenon can be modelled as a dynamical process in economic networks. Economic networks are usually scale-free, and scale-free networks are known to be vulnerable with respect to targeted attacks, i.e., attacks directed towards the biggest nodes of the network. Here we address the following question: to what extent does the scale-free nature of economic networks and the vulnerability of the biggest nodes affect the propagation of economic shocks? We model the dynamics of bankruptcies as the propagation of financial contagion across the banking sector over a scale-free network…
Empirical Study on the Relationship between the Cross-Correlation among Stocks and the Stocks' Volatility Clustering
2013
In this paper we discuss univariate and multivariate statistical properties of volatility with the aim of understanding how these two aspects are interrelated. Specifically, we focus on the relationship between the cross-correlation among stock's volatilities and the volatility clustering. Volatility clustering is related to the memory property of the volatility time-series and therefore to its predictability. Our results show that there exists a relationship between the level of predictability of any volatility time-series and the amount of its inter-dependence with other assets. In all considered cases, the more the asset is linked to other assets, the more its volatility keeps memory of …
UAV-Aided Secure Short-Packet Data Collection and Transmission
2023
Benefiting from the deployment flexibility and the line-of-sight (LoS) channel conditions, unmanned aerial vehicle (UAV) has gained tremendous attention in data collection for wireless sensor networks. However, the high-quality air-ground channels also pose significant threats to the security of UAV aided wireless networks. In this paper, we propose a short-packet secure UAV-aided data collection and transmission scheme to guarantee the freshness and security of the transmission from the sensors to the remote ground base station (BS). First, during the data collection phase, the trajectory, the flight duration, and the user scheduling are jointly optimized with the objective of maximizing t…
Inverse problems and invisibility cloaking for FEM models and resistor networks
2013
In this paper we consider inverse problems for resistor networks and for models obtained via the finite element method (FEM) for the conductivity equation. These correspond to discrete versions of the inverse conductivity problem of Calderón. We characterize FEM models corresponding to a given triangulation of the domain that are equivalent to certain resistor networks, and apply the results to study nonuniqueness of the discrete inverse problem. It turns out that the degree of nonuniqueness for the discrete problem is larger than the one for the partial differential equation. We also study invisibility cloaking for FEM models, and show how an arbitrary body can be surrounded with a layer …
The Riverine Organism Drift Imager: A new technology to study organism drift in rivers and streams
2023
1. Drift or downstream dispersal is a fundamental process in the life cycle of many riverine organisms. In the face of rapidly declining freshwater biodiversity, there is a need to enhance our capacity to study the drift of riverine organisms, by overcoming the limitations of traditional labour-intensive sampling methods that result in data of low temporal and spatial resolution. 2. To address this need, we developed a new technology, the Riverine Organism Drift Imager (RODI), which combines in situ imaging with machine-learning classification. This technique expands on the traditional methodology by replacing the collection cup of a drift net with a camera system that continuously images r…
Promoting the Flexibility of Thermal Prosumers Equipped with Heat Pumps to Support Power Grid Management
2023
The increasing share of renewable energy sources in energy systems will lead to unpredictable moments of surplus/deficit in energy production. To address this issue, users with heat pumps can provide support to power grid operators through flexible unit operation achieved via Demand Response programs. For buildings connected to low-temperature heating networks with ensured third-party access, further room for flexibility can be explored by investigating the production of surplus heat that can be sold to the network. A key aspect lies in the identification of the energy pricing options that could encourage such flexible operation of a heat pump by “thermal prosumers”. To this aim…
A deep learning segmentation approach to calories and weight estimation of food images
2019
Master's thesis Information- and communication technology IKT590 - University of Agder 2019 Today’s generation is very aware of what they are eating and the amountof calories in their food. Eating too many calories can lead to increasedweight, which has become a big health issue. A study from 2016 states thatmore than 1,9 billion adults are overweight where almost one third of theseare obese. Statistics from Norway show that 1 of 4 men and 1 of 5 womenare obese.Artificial Intelligence in general and deep learning in particular can be usedto help understand the content of eaten food. In this master thesis, wepropose a network to estimate the weight of food from a single image. Thisis done in…