Search results for " CIRCuiTS"
showing 10 items of 187 documents
Dissemination protocol for Heterogeneous Cooperative Vehicular Networks
2012
International audience; The difficulties associated with network connectivity, unreliable channels, and city environment characteristics make data dissemination task in vehicular urban networks a real challenge. Recently, some interesting solutions have been proposed to perform data dissemination in this environment. Starting from the analysis of these solutions, we present a new dissemination protocol named DHVN (Dissemination protocol for Heterogeneous Cooperative Vehicular Networks) that considers: (i) roads topology, (ii) network connectivity and possible partitioning in case of low traffic density, and (iii) heterogeneous communication capabilities of the vehicles. We compare our proto…
Evaluating Infrastructure Alternatives for Regional Water Supply Systems by Model-assisted Cost-benefit Analysis – A Case Study from Apulia, Italy
2014
The main challenge associated to regional water supply systems planning lies in understanding the best infrastructure alternatives to improve service given a certain configuration of the resources system. While cost-effectiveness assessments are still widespread in this type of analyses, they do not account for the fact that, especially in mature systems, service improvements tend to follow the law of marginal diminishing returns, so that a cost – benefit assessment should be preferable. Both costs and benefits can be organized into a cost-benefit analysis (CBA) framework. In a complex system, a model reproducing its topology and characteristics better describes the impacts of the alternati…
A Network Tomography Approach for Traffic Monitoring in Smart Cities
2018
Traffic monitoring is a key enabler for several planning and management activities of a Smart City. However, traditional techniques are often not cost efficient, flexible, and scalable. This paper proposes an approach to traffic monitoring that does not rely on probe vehicles, nor requires vehicle localization through GPS. Conversely, it exploits just a limited number of cameras placed at road intersections to measure car end-to-end traveling times. We model the problem within the theoretical framework of network tomography, in order to infer the traveling times of all individual road segments in the road network. We specifically deal with the potential presence of noisy measurements, and t…
Short-Term Sensory Data Prediction in Ambient Intelligence Scenarios
2014
Predicting data is a crucial ability for resource-constrained devices like the nodes of a Wireless Sensor Network. In the context of Ambient Intelligence scenarios, in particular, short-term sensory data prediction becomes a key enabler for more difficult tasks such as prolonging network lifetime, reducing the amount of communication required and improving user-environment interaction. In this chapter we propose a software module designed for clustered wireless sensor networks, able to predict various environmental quantities, namely temperature, humidity and light. The software module is supported by an ontology that describes the topology of the AmI scenario and the effects of the actuato…
Simulated Annealing Technique for Fast Learning of SOM Networks
2011
The Self-Organizing Map (SOM) is a popular unsupervised neural network able to provide effective clustering and data visualization for multidimensional input datasets. In this paper, we present an application of the simulated annealing procedure to the SOM learning algorithm with the aim to obtain a fast learning and better performances in terms of quantization error. The proposed learning algorithm is called Fast Learning Self-Organized Map, and it does not affect the easiness of the basic learning algorithm of the standard SOM. The proposed learning algorithm also improves the quality of resulting maps by providing better clustering quality and topology preservation of input multi-dimensi…
Contribution to the analysis of signals obtained by dynamic photon emission for the purpose of studying very large scale integration circuits
2014
Scaling progresses has the benefit of making chips always more powerful. On the other hand, when there is a failure, the analysis of such advanced devices has became more sensitive. The defect localization step of this process is the critical one. Indeed, the aim is to find transistors which dimensions range in several nanometers on a device which surface is several square centimeters.Optical techniques like dynamical photon emission, also named Time Resolved Imaging (TRI), have proved to fit in such context. The later is based on the acquisition and exploitation of photons emitted by a switching CMOS structure. Due to its physical bacground, this tool has a limited invasive effect and can …
Dynamic Regret Analysis for Online Tracking of Time-varying Structural Equation Model Topologies
2020
Identifying dependencies among variables in a complex system is an important problem in network science. Structural equation models (SEM) have been used widely in many fields for topology inference, because they are tractable and incorporate exogenous influences in the model. Topology identification based on static SEM is useful in stationary environments; however, in many applications a time-varying underlying topology is sought. This paper presents an online algorithm to track sparse time-varying topologies in dynamic environments and most importantly, performs a detailed analysis on the performance guarantees. The tracking capability is characterized in terms of a bound on the dynamic re…
Random Feature Approximation for Online Nonlinear Graph Topology Identification
2021
Online topology estimation of graph-connected time series is challenging, especially since the causal dependencies in many real-world networks are nonlinear. In this paper, we propose a kernel-based algorithm for graph topology estimation. The algorithm uses a Fourier-based Random feature approximation to tackle the curse of dimensionality associated with the kernel representations. Exploiting the fact that the real-world networks often exhibit sparse topologies, we propose a group lasso based optimization framework, which is solve using an iterative composite objective mirror descent method, yielding an online algorithm with fixed computational complexity per iteration. The experiments con…
Online Non-linear Topology Identification from Graph-connected Time Series
2021
Estimating the unknown causal dependencies among graph-connected time series plays an important role in many applications, such as sensor network analysis, signal processing over cyber-physical systems, and finance engineering. Inference of such causal dependencies, often know as topology identification, is not well studied for non-linear non-stationary systems, and most of the existing methods are batch-based which are not capable of handling streaming sensor signals. In this paper, we propose an online kernel-based algorithm for topology estimation of non-linear vector autoregressive time series by solving a sparse online optimization framework using the composite objective mirror descent…
An interface protection system based on an embedded metrology system platform
2021
Abstract The aim of this work is to present an interface protection system (IPS) for Distributed Generators (DG) and Energy Storage Systems (ESS). The new prototype of IPS guarantees standard protection requirements, in terms of both voltage and frequency measurement accuracies and trip times. Moreover, it has the additional functionalities of implementing a communication link between the Distribution System Operator (DSO) and the DG and ESS Inverter. The new IPS is based on a smart meter platform with an integrated power line communication modem. Moreover, it has also an integrated metrology section. Experimental tests will show how this last feature allows a significant reduction of the m…