A provably-robust sampling method for generating colormaps of large data

2013 ◽  
Author(s):  
David Thompson ◽  
Janine Bennett ◽  
C. Seshadhri ◽  
Ali Pinar
Keyword(s):  
Sampling Method ◽  
Large Data

An example of spectrum imaging used for comparison of EELS quantitative analysis techniques on Al-Li

1991 ◽  
Vol 49 ◽  
pp. 726-727
Author(s):  
John A. Hunt
Keyword(s):  
Quantitative Analysis ◽  
Large Data ◽  
Difference Spectrum ◽  
Large Data Sets ◽  
Foil Thickness ◽  
Data Sets ◽  
Analysis Techniques ◽  
Spectrum Imaging ◽  
Normal Spectrum ◽  
Electron Energy Loss

Spectrum-imaging is a useful technique for comparing different processing methods on very large data sets which are identical for each method. This paper is concerned with comparing methods of electron energy-loss spectroscopy (EELS) quantitative analysis on the Al-Li system. The spectrum-image analyzed here was obtained from an Al-10at%Li foil aged to produce δ' precipitates that can span the foil thickness. Two 1024 channel EELS spectra offset in energy by 1 eV were recorded and stored at each pixel in the 80x80 spectrum-image (25 Mbytes). An energy range of 39-89eV (20 channels/eV) are represented. During processing the spectra are either subtracted to create an artifact corrected difference spectrum, or the energy offset is numerically removed and the spectra are added to create a normal spectrum. The spectrum-images are processed into 2D floating-point images using methods and software described in [1].

Cluster analysis for large data sets: applications to individual aerosol particles from the mid-pacific

1992 ◽  
Vol 50 (2) ◽  
pp. 1488-1489
Author(s):  
Thomas W. Shattuck ◽  
James R. Anderson ◽  
Neil W. Tindale ◽  
Peter R. Buseck
Keyword(s):  
Cluster Analysis ◽  
Chemical Reactivity ◽  
Large Data ◽  
Large Data Sets ◽  
Particle Analysis ◽  
Data Sets ◽  
Halogen Chemistry ◽  
Complete Study ◽  
Components Analysis ◽  
Automated Scanning

Individual particle analysis involves the study of tens of thousands of particles using automated scanning electron microscopy and elemental analysis by energy-dispersive, x-ray emission spectroscopy (EDS). EDS produces large data sets that must be analyzed using multi-variate statistical techniques. A complete study uses cluster analysis, discriminant analysis, and factor or principal components analysis (PCA). The three techniques are used in the study of particles sampled during the FeLine cruise to the mid-Pacific ocean in the summer of 1990. The mid-Pacific aerosol provides information on long range particle transport, iron deposition, sea salt ageing, and halogen chemistry.Aerosol particle data sets suffer from a number of difficulties for pattern recognition using cluster analysis. There is a great disparity in the number of observations per cluster and the range of the variables in each cluster. The variables are not normally distributed, they are subject to considerable experimental error, and many values are zero, because of finite detection limits. Many of the clusters show considerable overlap, because of natural variability, agglomeration, and chemical reactivity.

Automated 3-D cell population analysis in thick tissue sections using laser-scanning confocal-microscopy data

1993 ◽  
Vol 51 ◽  
pp. 562-563
Author(s):  
Hakan Ancin
Keyword(s):  
Laser Scanning ◽  
Population Analysis ◽  
Three Dimensional ◽  
Large Data ◽  
Laser Scanning Confocal Microscopy ◽  
Tissue Slices ◽  
Scanning Confocal Microscopy ◽  
Tissue Sections ◽  
Spatially Adaptive ◽  
Microscopy Data

This paper presents methods for performing detailed quantitative automated three dimensional (3-D) analysis of cell populations in thick tissue sections while preserving the relative 3-D locations of cells. Specifically, the method disambiguates overlapping clusters of cells, and accurately measures the volume, 3-D location, and shape parameters for each cell. Finally, the entire population of cells is analyzed to detect patterns and groupings with respect to various combinations of cell properties. All of the above is accomplished with zero subjective bias.In this method, a laser-scanning confocal light microscope (LSCM) is used to collect optical sections through the entire thickness (100 - 500μm) of fluorescently-labelled tissue slices. The acquired stack of optical slices is first subjected to axial deblurring using the expectation maximization (EM) algorithm. The resulting isotropic 3-D image is segmented using a spatially-adaptive Poisson based image segmentation algorithm with region-dependent smoothing parameters. Extracting the voxels that were labelled as "foreground" into an active voxel data structure results in a large data reduction.

An Empirical Analysis of the Obtrusiveness of and Participants' Compliance with the Electronically Activated Recorder (EAR)

2007 ◽  
Vol 23 (4) ◽  
pp. 248-257 ◽  
Author(s):  
Matthias R. Mehl ◽  
Shannon E. Holleran
Keyword(s):  
Empirical Analysis ◽  
Sampling Method ◽  
Daily Life ◽  
Assessment Method ◽  
Data Confidentiality ◽  
Short Term ◽  
Naturally Occurring ◽  
Two Samples ◽  
Audio Recorder ◽  
Term Monitoring

Abstract. In this article, the authors provide an empirical analysis of the obtrusiveness of and participants' compliance with a relatively new psychological ambulatory assessment method, called the electronically activated recorder or EAR. The EAR is a modified portable audio-recorder that periodically records snippets of ambient sounds from participants' daily environments. In tracking moment-to-moment ambient sounds, the EAR yields an acoustic log of a person's day as it unfolds. As a naturalistic observation sampling method, it provides an observer's account of daily life and is optimized for the assessment of audible aspects of participants' naturally-occurring social behaviors and interactions. Measures of self-reported and behaviorally-assessed EAR obtrusiveness and compliance were analyzed in two samples. After an initial 2-h period of relative obtrusiveness, participants habituated to wearing the EAR and perceived it as fairly unobtrusive both in a short-term (2 days, N = 96) and a longer-term (10-11 days, N = 11) monitoring. Compliance with the method was high both during the short-term and longer-term monitoring. Somewhat reduced compliance was identified over the weekend; this effect appears to be specific to student populations. Important privacy and data confidentiality considerations around the EAR method are discussed.

Emotional Variability Predicts Tiredness in Daily Life

2016 ◽  
Vol 37 (3) ◽  
pp. 181-193 ◽  
Author(s):  
Aire Mill ◽  
Anu Realo ◽  
Jüri Allik
Keyword(s):  
Sampling Method ◽  
Daily Life ◽  
Emotional Experience ◽  
Experience Sampling ◽  
Experience Sampling Method ◽  
Building Blocks ◽  
Intraindividual Variability ◽  
Unique Role ◽  
Over Time

Abstract. Intraindividual variability, along with the more frequently studied between-person variability, has been argued to be one of the basic building blocks of emotional experience. The aim of the current study is to examine whether intraindividual variability in affect predicts tiredness in daily life. Intraindividual variability in affect was studied with the experience sampling method in a group of 110 participants (aged between 19 and 84 years) during 14 consecutive days on seven randomly determined occasions per day. The results suggest that affect variability is a stable construct over time and situations. Our findings also demonstrate that intraindividual variability in affect has a unique role in predicting increased levels of tiredness at the momentary level as well at the level of individuals.

Monitoring Daily Life Using Mobile Phones: The Experience Sampling Method

2006 ◽  
Author(s):  
Alessandra Preziosa ◽  
Marta Bassi ◽  
Daniela Villani ◽  
Andrea Gaggioli ◽  
Giuseppe Riva
Keyword(s):  
Mobile Phones ◽  
Sampling Method ◽  
Daily Life ◽  
Experience Sampling ◽  
Experience Sampling Method

Towards the Use of a Tree Branching Logic in the Environment of a Hospital Information System

1980 ◽  
Vol 19 (04) ◽  
pp. 187-194
Author(s):  
J.-Ph. Berney ◽  
R. Baud ◽  
J.-R. Scherrer
Keyword(s):  
Syntactic Structure ◽  
Large Data ◽  
Selection System ◽  
Frame Selection ◽  
Knowing That ◽  
Medical Language ◽  
Selection Systems ◽  
Definition Of ◽  
Man Machine Dialogue ◽  
Oriented System

It is well known that Frame Selection Systems (FFS) have proved both popular and effective in physician-machine and patient-machine dialogue. A formal algorithm for definition of a Frame Selection System for handling man-machine dialogue is presented here. Besides, it is shown how the natural medical language can be handled using the approach of a tree branching logic. This logic appears to be based upon ordered series of selections which enclose a syntactic structure. The external specifications are discussed with regard to convenience and efficiency. Knowing that all communication between the user and the application programmes is handled only by FSS software, FSS contributes to achieving modularity and, therefore, also maintainability in a transaction-oriented system with a large data base and concurrent accesses.

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