scholarly journals An analysis of data sets used to train and validate cost prediction systems

2005 ◽  
Author(s):  
Carolyn Mair ◽  
Martin Shepperd ◽  
Magne Jørgensen
Keyword(s):  
Data Sets ◽  
Cost Prediction ◽  
Prediction Systems

scholarly journals An analysis of data sets used to train and validate cost prediction systems

2005 ◽  
Vol 30 (4) ◽  
pp. 1-6 ◽  
Author(s):  
Carolyn Mair ◽  
Martin Shepperd ◽  
Magne Jørgensen
Keyword(s):  
Data Sets ◽  
Cost Prediction ◽  
Prediction Systems

Warranty Cost Prediction Using the Mahalanobis-Taguchi System

2009 ◽  
Author(s):  
Rodney Kestle ◽  
Elizabeth Cudney
Keyword(s):  
Poor Quality ◽  
Correlated Data ◽  
Data Sets ◽  
Cost Prediction ◽  
Cost Avoidance ◽  
System A ◽  
Multiple Characteristics ◽  
Warranty Cost ◽  
The Cost

In any competitive market, businesses need to differentiate their offerings. Many industries use a warranty as an offering that not only differentiates the product or service, but also extends the customer’s expected durability of the product or service. By offering to share the risk of a customer’s purchase in the form of a warranty, a business assumes the cost of poor quality and therefore should have a vested interest to reduce this cost thus maximizing its profits. Warranty cost prediction methods are used by many leading companies, but these methods typically only focus on failure reduction as cost avoidance. Additional dimensions should be considered when predicting warranty cost. This paper presents the application of the Mahalanobis-Taguchi System to forecast warranty cost based on multivariate data. Using Mahalanobis-Taguchi System, a product or service’s warranty cost can be predicted using multiple characteristics thus providing a more complete estimate. The Mahalanobis-Taguchi System also enables businesses to estimate their warranty cost as early as conceptual design, due to the method’s ability to forecast based on small, correlated data sets. A case study utilizing warranty data is also provided to illustrate the technique.

scholarly journals Effects of temporal resolution of input precipitation on the performance of hydrological forecasting

2011 ◽  
Vol 29 ◽  
pp. 21-25 ◽  
Author(s):  
F. Wetterhall ◽  
Y. He ◽  
H. Cloke ◽  
F. Pappenberger
Keyword(s):  
Flood Forecasting ◽  
Lead Times ◽  
Data Sets ◽  
Precipitation Data ◽  
Hydrological Models ◽  
Data Set ◽  
Flood Prediction ◽  
Time Period ◽  
Spatial Coverage ◽  
Prediction Systems

Abstract. Flood prediction systems rely on good quality precipitation input data and forecasts to drive hydrological models. Most precipitation data comes from daily stations with a good spatial coverage. However, some flood events occur on sub-daily time scales and flood prediction systems could benefit from using models calibrated on the same time scale. This study compares precipitation data aggregated from hourly stations (HP) and data disaggregated from daily stations (DP) with 6-hourly forecasts from ECMWF over the time period 1 October 2006–31 December 2009. The HP and DP data sets were then used to calibrate two hydrological models, LISFLOOD-RR and HBV, and the latter was used in a flood case study. The HP scored better than the DP when evaluated against the forecast for lead times up to 4 days. However, this was not translated in the same way to the hydrological modelling, where the models gave similar scores for simulated runoff with the two datasets. The flood forecasting study showed that both datasets gave similar hit rates whereas the HP data set gave much smaller false alarm rates (FAR). This indicates that using sub-daily precipitation in the calibration and initiation of hydrological models can improve flood forecasting.

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].

Computer-aided methods for 3-D visualization of serial sections and thick biological specimens

1992 ◽  
Vol 50 (2) ◽  
pp. 1060-1061
Author(s):  
Mark Ellisman ◽  
Maryann Martone ◽  
Gabriel Soto ◽  
Eleizer Masliah ◽  
David Hessler ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Three Dimensional ◽  
Neuritic Plaque ◽  
Dimensional Structure ◽  
Data Sets ◽  
Molecular Physiology ◽  
Research Activities ◽  
Computer Aided ◽  
Dimensional Reconstruction

Structurally-oriented biologists examine cells, tissues, organelles and macromolecules in order to gain insight into cellular and molecular physiology by relating structure to function. The understanding of these structures can be greatly enhanced by the use of techniques for the visualization and quantitative analysis of three-dimensional structure. Three projects from current research activities will be presented in order to illustrate both the present capabilities of computer aided techniques as well as their limitations and future possibilities.The first project concerns the three-dimensional reconstruction of the neuritic plaques found in the brains of patients with Alzheimer's disease. We have developed a software package “Synu” for investigation of 3D data sets which has been used in conjunction with laser confocal light microscopy to study the structure of the neuritic plaque. Tissue sections of autopsy samples from patients with Alzheimer's disease were double-labeled for tau, a cytoskeletal marker for abnormal neurites, and synaptophysin, a marker of presynaptic terminals.

Direct phase determination in electron crystallography: small organic molecules

1992 ◽  
Vol 50 (2) ◽  
pp. 1166-1167
Author(s):  
Douglas L. Dorset
Keyword(s):  
Organic Molecules ◽  
Data Sets ◽  
Temperature Structure ◽  
3D Analysis ◽  
Intensity Data ◽  
Electron Crystallography ◽  
Phase Determination ◽  
Measured Intensity ◽  
3D Data

The quantitative use of electron diffraction intensity data for the determination of crystal structures represents the pioneering achievement in the electron crystallography of organic molecules, an effort largely begun by B. K. Vainshtein and his co-workers. However, despite numerous representative structure analyses yielding results consistent with X-ray determination, this entire effort was viewed with considerable mistrust by many crystallographers. This was no doubt due to the rather high crystallographic R-factors reported for some structures and, more importantly, the failure to convince many skeptics that the measured intensity data were adequate for ab initio structure determinations.We have recently demonstrated the utility of these data sets for structure analyses by direct phase determination based on the probabilistic estimate of three- and four-phase structure invariant sums. Examples include the structure of diketopiperazine using Vainshtein's 3D data, a similar 3D analysis of the room temperature structure of thiourea, and a zonal determination of the urea structure, the latter also based on data collected by the Moscow group.

Automated cell counting of astrocytes on patterned substrates containing aliphatic and charged properties

1995 ◽  
Vol 53 ◽  
pp. 974-975
Author(s):  
W. Shain ◽  
H. Ancin ◽  
H.C. Craighead ◽  
M. Isaacson ◽  
L. Kam ◽  
...  
Keyword(s):  
Cell Culture ◽  
Cell Attachment ◽  
Culture Method ◽  
Cell Counting ◽  
Data Sets ◽  
Nuclear Staining ◽  
Double Positive ◽  
A Cell ◽  
Wafer Test ◽  
Cell Densities

Neural protheses have potential to restore nervous system functions lost by trauma or disease. Nanofabrication extends this approach to implants for stimulating and recording from single or small groups of neurons in the spinal cord and brain; however, tissue compatibility is a major limitation to their practical application. We are using a cell culture method for quantitatively measuring cell attachment to surfaces designed for nanofabricated neural prostheses.Silicon wafer test surfaces composed of 50-μm bars separated by aliphatic regions were fabricated using methods similar to a procedure described by Kleinfeld et al. Test surfaces contained either a single or double positive charge/residue. Cyanine dyes (diIC18(3)) stained the background and cell membranes (Fig 1); however, identification of individual cells at higher densities was difficult (Fig 2). Nuclear staining with acriflavine allowed discrimination of individual cells and permitted automated counting of nuclei using 3-D data sets from the confocal microscope (Fig 3). For cell attachment assays, LRM5 5 astroglial cells and astrocytes in primary cell culture were plated at increasing cell densities on test substrates, incubated for 24 hr, fixed, stained, mounted on coverslips, and imaged with a 10x objective.

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.

Evaluation of Acoustic Analyses of Voice in Nonoptimized Conditions

2020 ◽  
Vol 63 (12) ◽  
pp. 3991-3999
Author(s):  
Benjamin van der Woerd ◽  
Min Wu ◽  
Vijay Parsa ◽  
Philip C. Doyle ◽  
Kevin Fung
Keyword(s):  
Repeated Measures ◽  
Voice Quality ◽  
Data Sets ◽  
Acoustic Measurements ◽  
Sample Collection ◽  
Experimental Conditions ◽  
Environment Analysis ◽  
Acoustic Measures ◽  
Recording Conditions ◽  
Cepstral Peak Prominence

Objectives This study aimed to evaluate the fidelity and accuracy of a smartphone microphone and recording environment on acoustic measurements of voice. Method A prospective cohort proof-of-concept study. Two sets of prerecorded samples (a) sustained vowels (/a/) and (b) Rainbow Passage sentence were played for recording via the internal iPhone microphone and the Blue Yeti USB microphone in two recording environments: a sound-treated booth and quiet office setting. Recordings were presented using a calibrated mannequin speaker with a fixed signal intensity (69 dBA), at a fixed distance (15 in.). Each set of recordings (iPhone—audio booth, Blue Yeti—audio booth, iPhone—office, and Blue Yeti—office), was time-windowed to ensure the same signal was evaluated for each condition. Acoustic measures of voice including fundamental frequency ( f o ), jitter, shimmer, harmonic-to-noise ratio (HNR), and cepstral peak prominence (CPP), were generated using a widely used analysis program (Praat Version 6.0.50). The data gathered were compared using a repeated measures analysis of variance. Two separate data sets were used. The set of vowel samples included both pathologic ( n = 10) and normal ( n = 10), male ( n = 5) and female ( n = 15) speakers. The set of sentence stimuli ranged in perceived voice quality from normal to severely disordered with an equal number of male ( n = 12) and female ( n = 12) speakers evaluated. Results The vowel analyses indicated that the jitter, shimmer, HNR, and CPP were significantly different based on microphone choice and shimmer, HNR, and CPP were significantly different based on the recording environment. Analysis of sentences revealed a statistically significant impact of recording environment and microphone type on HNR and CPP. While statistically significant, the differences across the experimental conditions for a subset of the acoustic measures (viz., jitter and CPP) have shown differences that fell within their respective normative ranges. Conclusions Both microphone and recording setting resulted in significant differences across several acoustic measurements. However, a subset of the acoustic measures that were statistically significant across the recording conditions showed small overall differences that are unlikely to have clinical significance in interpretation. For these acoustic measures, the present data suggest that, although a sound-treated setting is ideal for voice sample collection, a smartphone microphone can capture acceptable recordings for acoustic signal analysis.

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