Search results for "test data"
showing 10 items of 47 documents
A Methodology for the Analysis of Memory Response to Radiation through Bitmap Superposition and Slicing
2015
A methodology is proposed for the statistical analysis of memory radiation test data, with the aim of identifying trends in the single-even upset (SEU) distribution. The treated case study is a 65nm SRAM irradiated with neutrons, protons and heavy-ions.
The CogALex-IV Shared Task on the Lexical Access Problem
2014
The shared task of the 4th Workshop on Cognitive Aspects of the Lexicon (CogALexIV) was devoted to a subtask of the lexical access problem, namely multi-stimulus association. In this task, participants were supposed to determine automatically an expected response based on a number of received stimulus words. We describe here the task definition, the theoretical background, the training and test data sets, and the evaluation procedure used for ranking the participating systems. We also summarize the approaches used and present the results of the evaluation. In conclusion, the outcome of the competition are a number of systems which provide very good solutions to the problem.
The SISCone jet algorithm optimised for low particle multiplicities
2011
The SISCone jet algorithm is a seedless infrared-safe cone jet algorithm. There exists an implementation which is highly optimised for a large number of final state particles. However, in fixed-order perturbative calculations with a small number of final state particles, it turns out that the computer time needed for the jet clustering of this implementation is comparable to the computer time of the matrix elements. This article reports on an implementation of the SISCone algorithm optimised for low particle multiplicities.
Computing Sum of Products about the Mean with Pairwise Algorithms
1997
We discuss pairwise algorithms, a kind of computational algorithm which can be useful in dynamically updating statistics as new samples of data are collected. Since test data are usually collected through time as individual data sets, these algorithms would be profitably used in computer programs to treat this situation. Pair-wise algorithms are presented for calculating the sum of products of deviations about the mean for adding a sample of data (or removing one) to the whole data set.
Generative Adversarial Networks in Cardiology
2021
A B S T R A C T Generative Adversarial Networks (GANs) are state-of-the-art neural network models used to synthesize images and other data. GANs brought a considerable improvement to the quality of synthetic data, quickly becoming the standard for data generation tasks. In this work, we summarize the applications of GANs in the field of cardiology, including generation of realistic cardiac images, electrocardiography signals, and synthetic electronic health records. The utility of GAN-generated data is discussed with respect to research, clinical care, and academia. Moreover, we present illustrative examples of our GAN-generated cardiac magnetic resonance and echocardiography images, showin…
An Analytical Tire Model with Flexible Carcass for Combined Slips
2014
Published version of an article in the journal: Mathematical Problems in Engineering. Also available from the publisher at: http://dx.doi.org/10.1155/2014/397538 The tire mechanical characteristics under combined cornering and braking/driving situations have significant effects on vehicle directional controls. The objective of this paper is to present an analytical tire model with flexible carcass for combined slip situations, which can describe tire behavior well and can also be used for studying vehicle dynamics. The tire forces and moments come mainly from the shear stress and sliding friction at the tread-road interface. In order to describe complicated tire characteristics and tire-roa…
On-line adaptive neural network in very remote control system
2006
Remote control involves several issues that degrade seriously the performance of the plant to be controlled. This paper presents a strategy improving the characteristics of the remote control system, using an on-line adaptive neural net, in order to learn the variations of the remote system parameters to minimize the errors. This strategy is successfully applied to a client-server remote control system for a two link robot arm. Tests show that an error position in a remote control brushless motor can be highly reduced since its first "reference command" using a prevision of that error to modify the original reference. The neural net, used only by the client, is previously trained using loca…
Assessment of computational methods for the analysis of single-cell ATAC-seq data
2019
Abstract Background Recent innovations in single-cell Assay for Transposase Accessible Chromatin using sequencing (scATAC-seq) enable profiling of the epigenetic landscape of thousands of individual cells. scATAC-seq data analysis presents unique methodological challenges. scATAC-seq experiments sample DNA, which, due to low copy numbers (diploid in humans), lead to inherent data sparsity (1–10% of peaks detected per cell) compared to transcriptomic (scRNA-seq) data (10–45% of expressed genes detected per cell). Such challenges in data generation emphasize the need for informative features to assess cell heterogeneity at the chromatin level. Results We present a benchmarking framework that …
An iterative based approach for hysteresis parameters estimation in Magnetorheological dampers
2012
The following work entails the problem of regenerating the hysteresis loop in the Magnetorheological (MR) dampers. The collected data from tests are not sufficient neither efficient for designing optimal controls compensating for the hysteresis in the dampers. This work presents an iterative based approach for estimating the hysteresis parameters, the method however can be generalized for different kind of dampers or actuators hence the hysteresis loop can be generalized using available test data. Some assumptions can be introduced in order to facilitate the underlines of the parameters estimation, one of the assumptions in this work is to use predetermined hysteresis parameters and regener…
Deterministic Linkage as a Preceding Filter for Other Record Linkage Methods
2015
Deterministic record linkage (RL) is frequently regarded as a rival to more sophisticated strategies like probabilistic RL. We investigate the effect of combining deterministic linkage with other linkage techniques. For this task, we use a simple deterministic linkage strategy as a preceding filter: a data pair is classified as ‘match' if all values of attributes considered agree exactly, otherwise as ‘nonmatch'. This strategy is separately combined with two probabilistic RL methods based on the Fellegi–Sunter model and with two classification tree methods (CART and Bagging). An empirical comparison was conducted on two real data sets. We used four different partitions into training data a…