DATA ANALYSIS



FACTOR ANALYSIS:
Factor Analysis is a technique for analyzing complex, multidimensional problems. It is used to examine the underlying patterns or relationships for a large number of variables and condense the information to a smaller set of factors or components. The purpose of factor analysis is to identify a set of dimensions that are latent, combine large number of objects into distinctly different groups or factors and create an entirely ....etc

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The file system must be user friendly as far as possible. Hence the operation on the system by tfie costumers must be limited. Thus the procedure for a search can be settled as follows. 'First of all the system displays a message Search:- to the costumer. The costumer must enter the first few letters of the name of the tram or the product or the patient. Then he must close the enter hey. Then the soft key 'FT' can be keyed to start the search. The system displays the details of if any match occurs. The Tsc %ey can 6 ....etc

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hi.
i am working on simulation of laser cladding of copper powder over steel in ansys workbench. so, if you have any idea regarding how can i find
1)heat affected zone during laser cladding
2)stress generated during laser cladding
3)deformation in steel plate due to cladding of copper over steel plate.
then please me guide. ....etc

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I take a project on automatic liquid filling machine. In this project we need literature review. I searched but i cant find. Please help me. ....etc

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B = FIR1(N,Wn) designs an N'th order lowpass FIR digital filter
and returns the filter coefficients in length N+1 vector B.
The cut-off frequency Wn must be between 0 < Wn < 1.0, with 1.0
corresponding to half the sample rate. The filter B is real and
has linear phase, i.e., even symmetric coefficients obeying B(k) =
B(N+2-k), k = 1,2,...,N+1.
If Wn is a two-element vector, Wn = , FIR1 returns an
order N bandpass filter with passband W1 < W < W2.
B = FIR1(N,Wn,'high') designs a highpa ....etc

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C-STORE A COLUMN ORIENTED DBMS
presented by
JACOB K JOSE
DEPARTMENT OF COMPUTER SCIENCE & ENGINEERING
COLLEGE OF ENGINEERING TRIVANDRUM
2007-11 Batch




Contents

Abstract
1. Introduction
2. Features of C-store
3. Data models
3.1 Storage Keys
3.2 Join Indices
4. Internal architecture
5. Readable store (rs)
6. Writeable store (ws)
7. Storage Management
8. Updates and Transactions
8.1 Providing Snapshot isolation
9. Recovery
10. Tuple ....etc

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CRM & Customer Service
 FOLLOW THE SUN
Call Centers / Contact Centers
 Customer interaction center or Customer Care are all the same names for Call Centers
 20 years ago consumers complained by letters and waited for response
 Not today, the 800 number has sparked off a revolution
 Real-time dispute resolution has become mandatory
 Even Dell Computers discovered that the customers who order PCs from company’s web site made an average of 2.5 calls to their support center !!!
Kn ....etc

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ELECTRONIC NOSE



Introduction

An electronic nose system typically consists of a multisensor array, an information-processing unit such as an artificial neural network (ANN), software with digital pattern-recognition algorithms, and reference-library databases . The cross-reactive sensor array is composed of incrementally-different sensors chosen to respond to a wide range of chemical classes and discriminate diverse mixtures of possible analytes. The ou ....etc

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% FIR Low pass filters using rectangular, triangular and kaiser windows
% sampling rate – 8000
order = 50;
cf=; cf--> contains set of cut-off frequencies

% cutoff frequency – 500
b_rect1=fir1(order,cf(1),boxcar(51)); %Rectangular
b_tri1=fir1(order,cf(1),bartlett(51)); %Triangular
b_kai1=fir1(order,cf(1),kaiser(51,8)); %Kaisar

% cutoff frequency - 1000
b_rect2=fir1(order,cf(2),boxcar(51));
b_tri2=fir1(order,cf(2),bartlett(51));
b_kai2=fir1(order,cf(2) ....etc

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Abstract
This paper demonstrates some consideration results
on feature extraction and selection for handwritten
Japanese Hiragana characters using independent
component analysis (ICA). In some ICA
algorithms where whitening of input signals is introduced
as preprocessing, one can consider that
the process of feature extraction using ICA consists
of two types of transformations: one is the transformation
from an input image to its principal components
(PCs), and the other is the transformation
from PCs to independent component ....etc

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