Search results for " Network"

2021

Abstract Reliable patient-specific ventricular repolarization times (RTs) can identify regions of functional block or afterdepolarizations, indicating arrhythmogenic cardiac tissue and the risk of sudden cardiac death. Unipolar electrograms (UEs) record electric potentials, and the Wyatt method has been shown to be accurate for estimating RT from a UE. High-pass filtering is an important step in processing UEs, however, it is known to distort the T-wave phase of the UE, which may compromise the accuracy of the Wyatt method. The aim of this study was to examine the effects of high-pass filtering, and improve RT estimates derived from filtered UEs. We first generated a comprehensive set of UE…

QSPR with descriptors based on averages of vertex invariants. An artificial neural network study

2014

New type of indices, the mean molecular connectivity indices (MMCI), based on nine different concepts of mean are proposed to model, together with molecular connectivity indices (MCI), experimental parameters and random variables, eleven properties of organic solvents. Two model methodologies are used to test the different descriptors: the multilinear least-squares (MLS) methodology and the Artificial Neural Network (ANN) methodology. The top three quantitative structure–property relationships (QSPR) for each property are chosen with the MLS method. The indices of these three QSPRs were used to train the ANNs that selected the best training sets of indices to estimate the evaluation sets of…

The Potsdam Open Source Radio Interferometry Tool (PORT)

2021

The Potsdam Open Source Radio Interferometry Tool (PORT) is the very long baseline interferometry (VLBI) analysis software developed and maintained at the GFZ German Research Centre for Geosciences. Chiefly, PORT is tasked with the timely processing of VLBI sessions and post-processing activities supporting the generation of celestial and terrestrial reference frames. In addition, it serves as a framework for research and development within the GFZ's VLBI working group and is part of the tool set employed in educating young researchers. Starting out from VLBI group delays, PORT estimates station and radio sources positions, as well as Earth orientation parameters, tropospheric parameters, a…

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…

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…

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 …

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 …