LIST OF TABLES

movedearAI and Robotics

Nov 17, 2013 (3 years and 8 months ago)

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xviii


CHAPTER

?

LIST OF TABLES



1.1

Top 10 causes of death

26


2.1

Reference limits for LV

5
5


2.2

Reference limits for RV measured in Apical four chamber
view

5
5


2.3

Reference limits for LA

5
7


2.4

Normal Values, Two
-
Dimensional Echocardiography


Apical four
-
chamber view (50 subjects. Age 19
-
63 Years,
Mean 31.2 ± 10.0

5
8


3
.
1

Matrices / Tables

6
9


3
.
2

Running time comparison of other variants

9
5


5.1

Texture features

14
4


7.1

Severity Grading for Mitral Regurgitation

1
6
6


7.2

Severity Grading for Mitral Stenosis

1
6
7


7.3

Attributes and Normal values

1
71


7.4

Sample data of
EDT

table

1
7
3


7.5

Structure of Database Tables (Training and Testing Phases)

1
7
5


7.6

Sample Dataset present in
EDT

18
2


7.7

EClass

18
2


7.8

Populating
EPC

table

18
3


7.9

Contents of
EPX

18
3


7.10

Output of Query 5 (
EPXi
)

18
4


7.11

Target table (
X

whose class label is to be determined)

18
5


7.12

Training Table for OLAP based Design

18
8


7.13

Sample Dataset for PL/SQL External Procedure Design

19
1


7.14

Training Table showing Mean and Variance for a Training
Dataset

19
2


7.15

Confusion Matrix

(Attributes: Categorical values)

1
9
4


7.16

Confusion Matrix

(Attributes:
Continuous

values)

19
4


9.1

Candidate Keys

2
2
8

xix



9.2

Minimal Cover

2
2
9


9.3

Third Normal Form

2
2
9


9.4

Boyce
-
Codd Normal Form

2
2
9


10.1

Running time modified K
-
Means:
Image Size (
n
): 400×250
(100000 pixels), # of iterations (
Q
): 4, Machine: M1

2
3
7


10.2

Test image:
Img3, # of iterations (
Q
) = 4,
d

= 1,
k

= 3

2
3
8


10.3

Running Time of Quick K
-
Means Algorithm

2
40


10.4

Running Time of Quick K
-
Means Algorithm for different
image sizes

2
41


10.5

Running Time of Quick K
-
Means Algorithm for different
iterations

2
41


10.6

Comparing Fast SQL K
-
Means with the results of other
authors in terms of running time

2
4
3


10.7

Comparing running time of data size and dimensions (
Q

= 4)

24
4


10.8

R
unning time of 100×100 size image with increasing
Q


24
4


10.9

Running time of 2D echo image (varying n) with
k

= 3 and #
of iterations = 4.

2
4
5


10.10

Running time of 2D echo image (varying iteration) with
k

= 3
and
n

= 100000

2
4
5


10.11

Comparison of running time between unconstrained and
constrained K
-
Means
clustering

2
4
6


10.12

Running time comparison between Constrained Clustering
(CC) and Unconstrained Clustering (UC). k = 3, # of
iterations = 4,
n

= 100000

2
4
7


10.13

UC vs CC interms of average running time and standard
Deviation (SD)

2
4
7


10.14

Comparison of running time of all proposed K
-
Means
clustering algorithms

2
4
8


10.15

Description of Datasets

2
51


10.16

Running time(s) KMEP

2
51


1
0.17

Confusion Matrix

(Categorical variables)

27
4


10.18

Confusion Matrix

(Continuous variables)

2
7
5


10.
19

Training Data Set

27
6


10.2
0

Dataset after Normalization

27
7