Search results for "Data processing"
showing 10 items of 175 documents
A DAQ-based sampling wattmeter for IEEE Std. 1459-2010 powers measurements. Uncertainty evaluation in nonsinusoidal conditions
2015
Abstract This paper presents the evaluation of the metrological performances of a DAQ-based sampling wattmeter (DAQ-SW) for the measurement of IEEE Std. 1459-2010 power quantities in non-sinusoidal conditions. The instrument makes use of two commercial data acquisition (DAQ) boards, a non-inductive current shunt, a personal computer and a commercial software for data processing. Starting from the results of an experimental characterization of the two instrument channels with non-sinusoidal voltages and currents and a correlation analysis, the combined standard uncertainties of IEEE Std. 1459-2010 quantities are evaluated, following the approach of the ISO Guide to the Expression of Uncertai…
Development of a high-accuracy PC-based wattmeter with commercial data acquisition boards
2011
This paper presents the development of a high accuracy sampling wattmeter, which makes use of two commercial data acquisition boards (DAQs) connected to a common personal computer. Commercial software is also used for data processing and implementation of the virtual instrument. The set up of the PC-based wattmeter is described and a preliminary evaluation of its metrological performances is made by means of two series of experimental tests, which were carried out with an electric power standard and a high performance multifunction calibrator. © 2011 IEEE.
Optimizing colormaps with consideration for color vision deficiency to enable accurate interpretation of scientific data
2018
Color vision deficiency (CVD) affects more than 4% of the population and leads to a different visual perception of colors. Though this has been known for decades, colormaps with many colors across the visual spectra are often used to represent data, leading to the potential for misinterpretation or difficulty with interpretation by someone with this deficiency. Until the creation of the module presented here, there were no colormaps mathematically optimized for CVD using modern color appearance models. While there have been some attempts to make aesthetically pleasing or subjectively tolerable colormaps for those with CVD, our goal was to make optimized colormaps for the most accurate perce…
Rule Extraction From Binary Neural Networks With Convolutional Rules for Model Validation.
2020
Classification approaches that allow to extract logical rules such as decision trees are often considered to be more interpretable than neural networks. Also, logical rules are comparatively easy to verify with any possible input. This is an important part in systems that aim to ensure correct operation of a given model. However, for high-dimensional input data such as images, the individual symbols, i.e. pixels, are not easily interpretable. Therefore, rule-based approaches are not typically used for this kind of high-dimensional data. We introduce the concept of first-order convolutional rules, which are logical rules that can be extracted using a convolutional neural network (CNN), and w…
The IceProd framework: distributed data processing for the IceCube neutrino observatory
2015
IceCube is a one-gigaton instrument located at the geographic South Pole, designed to detect cosmic neutrinos, identify the particle nature of dark matter, and study high-energy neutrinos themselves. Simulation of the IceCube detector and processing of data require a significant amount of computational resources. This paper presents the first detailed description of IceProd, a lightweight distributed management system designed to meet these requirements. It is driven by a central database in order to manage mass production of simulations and analysis of data produced by the IceCube detector. IceProd runs as a separate layer on top of other middleware and can take advantage of a variety of c…
Quantum pattern recognition in photonic circuits
2021
This paper proposes a machine learning method to characterize photonic states via a simple optical circuit and data processing of photon number distributions, such as photonic patterns. The input states consist of two coherent states used as references and a two-mode unknown state to be studied. We successfully trained supervised learning algorithms that can predict the degree of entanglement in the two-mode state as well as perform the full tomography of one photonic mode, obtaining satisfactory values in the considered regression metrics.
Using the factorial experiment method to analyze the corrosion protection process
2017
The organization functions are: research-development, production, commercial, financial-accounting, personnel and quality. In this paper the factorial experimental method will be applied, which is currently one of the most widespread methods used in the research-development departments of the organizations, due to its advantages and efficiency. The experiment was carried out at SC Coifer Impex SRL-Mirsa’s metal structures factory. In this paper it is presented the factors modelling that exerts their influence on two objectives functions: the ensuring the nominal thickness of the rough-cast film and the consumption limiting. For data processing the STATISTICA 7 software was used which provid…
Autonomous on-board data processing and instrument calibration software for the SO/PHI
2018
The extension of on-board data processing capabilities is an attractive option to reduce telemetry for scientific instruments on deep space missions. The challenges that this presents, however, require a comprehensive software system, which operates on the limited resources a data processing unit in space allows. We implemented such a system for the Polarimetric and Helioseismic Imager (PHI) on-board the Solar Orbiter (SO) spacecraft. It ensures autonomous operation to handle long command-response times, easy changing of the processes after new lessons have been learned and meticulous book-keeping of all operations to ensure scientific accuracy. This contribution presents the requirements a…
Liquid chromatography‐Orbitrap Tribrid high‐resolution mass spectrometry using data dependent‐tandem mass spectrometry with triple stage fragmentatio…
2021
A new, fast, and automatic approach has been applied for the tentative identification of unknown substances released by food contact epoxy resin after performing a migration test with food simulant. This approach combines intelligent data acquisition with AcquireX linked to liquid chromatography-Orbitrap Tribrid high-resolution mass spectrometry using data dependent-tandem mass spectrometry with triple stage fragmentation coupled to Compound Discoverer™ software for automated data processing and compound identification. The identification of the observed features was performed using a set of identification criteria, including exact mass, isotope pattern, tandem mass spectrometry spectra mat…
Analytical Validation of Multiplex Biomarker Assay to Stratify Colorectal Cancer into Molecular Subtypes
2019
International audience; Previously, we classified colorectal cancers (CRCs) into five CRCAssigner (CRCA) subtypes with different prognoses and potential treatment responses, later consolidated into four consensus molecular subtypes (CMS). Here we demonstrate the analytical development and validation of a custom NanoString nCounter platform-based biomarker assay (NanoCRCA) to stratify CRCs into subtypes. To reduce costs, we switched from the standard nCounter protocol to a custom modified protocol. The assay included a reduced 38-gene panel that was selected using an in-house machine-learning pipeline. We applied NanoCRCA to 413 samples from 355 CRC patients. From the fresh frozen samples (n…