Search results for "NETWORK"
showing 10 items of 7718 documents
Visual spike-based convolution processing with a Cellular Automata architecture
2010
this paper presents a first approach for implementations which fuse the Address-Event-Representation (AER) processing with the Cellular Automata using FPGA and AER-tools. This new strategy applies spike-based convolution filters inspired by Cellular Automata for AER vision processing. Spike-based systems are neuro-inspired circuits implementations traditionally used for sensory systems or sensor signal processing. AER is a neuromorphic communication protocol for transferring asynchronous events between VLSI spike-based chips. These neuro-inspired implementations allow developing complex, multilayer, multichip neuromorphic systems and have been used to design sensor chips, such as retinas an…
Hierarchical imaging and computational analysis of three-dimensional vascular network architecture in the entire postnatal and adult mouse brain
2021
The formation of new blood vessels and the establishment of vascular networks are crucial during brain development, in the adult healthy brain, as well as in various diseases of the central nervous system. Here, we describe a step-by-step protocol for our recently developed method that enables hierarchical imaging and computational analysis of vascular networks in postnatal and adult mouse brains. The different stages of the procedure include resin-based vascular corrosion casting, scanning electron microscopy, synchrotron radiation and desktop microcomputed tomography imaging, and computational network analysis. Combining these methods enables detailed visualization and quantification of t…
Integrated System for Monitoring the Tool State Using Temperature Measuring by Natural Thermocouple Method
2014
The intensive developments of intelligent manufacturing systems in the last decades open the large possibilities of more accurate monitoring of the metal cutting process. One of the most important factors of the process is the tool state given by the rate of the tool wear, which is the result of a lot of influences of almost all cutting parameters. The modern tool monitoring systems relieved that the accuracy of the results increases when using a combination of surveyed signals such as: vibrations, power consumption, acoustic emission, forces or tool temperature. Combining the output signals in a monitoring function using the neural network method gives the best results when using on-line m…
A convex optimization approach for vibration control of base isolated structures with limited wireless communication capacity
2010
The problem of H ∞ control design for vibration reduction of a base isolated structure with limited wireless communication capacity is studied in this paper. The network under consideration is subjected to measurement quantization, signal transmission delay, and data packet dropout, which appear typically in a network environment. Based on Lyapunov-Krasovskii functional (LKF) theory, some delay-range-dependent conditions are established for the existence of desired controllers such that the resulting closed-loop system is asymptotically stable and its performance is kept within a prescribed level. Finally, some simulation results are given to illustrate the effectiveness of our method.
Neural network-based models for a vibration suppression system equipped with MR brake
2012
This paper is devoted to the modeling and simulation of a full-scale commercially available magnetorheological (MR) brake installed in a semi-active suspension (SAS) system. The analysis of the Bouc-Wen and Dahl mathematical models of MR damper is presented. Influence of their parameters on the response is explored. Subsequently, by using the neural networks, the parameters characterizing each model are estimated. This makes it possible to perform the comparative analysis of the suggested damper models responses with the measured experimental results. The novelty of the presented methodology is the application of artificial intelligence methods to estimate model parameters of a MR brake uti…
Detection of Incipient Bearing Fault in a Slowly Rotating Machine Using Spline Wavelet Packets
2018
This chapter describes a successful application of spline-based wavelet packet transforms (WPTs) described in Chap. 4 to a complicated problem of detection of incipient defects in rolling element bearings by the analysis of recorded vibration signals. The methodology presented in this chapter is applied to the analysis of vibration data recorded from large bearings working in real unfavorable operation conditions in presence of strong noise and vibrations from multiple internal and external sources. It relies on properties of discrete spline-based wavelet packets such as orthogonality, near-rectangular spectra, transient oscillating shapes of testing waveforms and fast implementation of tra…
Security, QoS and self-management within an end-to-end Cloud Computing environment
2015
Today, Cloud Networking is one of the recent research areas within the Cloud Computing research communities. The main challenges of Cloud Networking concern Quality of Service (QoS) and security guarantee as well as its management in conformance with a corresponding Service Level Agreement (SLA). In this thesis, we propose a framework for resource allocation according to an end-to-end SLA established between a Cloud Service User (CSU) and several Cloud Service Providers (CSPs) within a Cloud Networking environment (Inter-Cloud Broker and Federation architectures). We focus on NaaS and IaaS Cloud services. Then, we propose the self-establishing of several kinds of SLAs and the self-managemen…
Discovering Homophily in Online Social Networks
2018
During the last ten years, Online Social Networks (OSNs) have increased their popularity by becoming part of the real life of users. Despite their tremendous widespread, OSNs have introduced several privacy issues as a consequence of the nature of the information involved in these services. Indeed, the huge amount of private information produced by users of current OSNs expose the users to a number of risks. The analysis of the users’ similarity in OSNs is attracting the attention of researchers because of its implications on privacy and social marketing. In particular, the homophily between users could be used to reveal important characteristics that users would like to keep hidden, hence …
Global Trigger Technological Demonstrator for ATLAS Phase-II upgrade
2020
ATLAS detector at the LHC will undergo a major Phase-II upgrade for the High Luminosity LHC. The upgrade affects all major ATLAS systems, including the Trigger and Data Acquisition systems. As part of the Level-0 Trigger System, the Global Trigger uses full-granularity calorimeter cells to perform algorithms, refines the trigger objects and applies topological requirements. The Global Trigger uses a Global Common Module as the building block of its design. To achieve a high input and output bandwidth and substantial processing power, the Global Common Module will host the most advanced FPGAs and optical modules. In order to evaluate the new generation of optical modules and FPGAs running at…
A Comparative Study of Nonlinear Machine Learning for the "In Silico" Depiction of Tyrosinase Inhibitory Activity from Molecular Structure.
2011
In the preset report, for the first time, support vector machine (SVM), artificial neural network (ANN), Baye- sian networks (BNs), k-nearest neighbor (k-NN) are applied and compared on two "in-house" datasets to describe the tyrosinase inhibitory activity from the molecular structure. The data set Data I is used for the identification of tyrosi- nase inhibitors (TIs) including 701 active and 728 inactive compounds. Data II consists of active chemicals for potency estimation of TIs. The 2D TOMOCOMD-CARDD atom-based quadratic indices are used as molecular descriptors. The de- rived models show rather encouraging results with the areas under the Receiver Operating Characteristic (AURC) curve …