234
Chapter 8 Fundamental Sampling Distributions and Data Descriptions
The Central Limit Theorem
Theorem 8.2: Central Limit Theorem: If X is the mean of a random sample of size n taken
from a population with mean [.L and nite variance 02, then the limit
"ptions
:jtzons 0f
Bally, the
isle, If an
Eresistor,
ination is
~, studied,
,; ametric
with mean
'value of
[a statistic
'Vee that
I , Iisquared
IIents. Note
ial case of
which is
" out that
eBdOIn. We
" Opulation
Die by the
8.5 Sampling Distribution of
#include "list.h"
#include <stdlib.h>
#include "fatal.h"
/* Place in the interface file */
struct Node
cfw_
ElementType Element;
Position
Next;
;
List
MakeEmpty( List L )
cfw_
if( L != NULL )
DeleteList( L );
L = malloc( sizeof( struct Node ) );
if( L = N
typedef int ElementType;
/* START: fig3_6.txt */
#ifndef _List_H
#define _List_H
struct Node;
typedef struct Node *PtrToNode;
typedef PtrToNode List;
typedef PtrToNode Position;
List MakeEmpty( List L );
int IsEmpty( List L );
int IsLast( Position P, List
Chapter 3
Intensity Transformations
and Spatial Filtering
3.1 Background
Objective of Enhancement
The result is more suitable than the
original image for a specific application.
Enhancement is problem oriented.
A certain amount of trial and error is
requi
Chapter 8
IMAGE COMPRESSION
8.1 Fundamentals
Image Compression
Reducing the amount of data required
to represent a digital image, while
retaining necessary information
Data are the means to convey information
Removal of redundant data
8-2
Measure of Compr
Chapter 10
Image Segmentation
10.1 Fundamentals
Let R represent the entire spatial region occupied by
an image. Image segmentation is a process that
partitions R into n sub-regions, R1, R2, , Rn, such
that
n
(a) Ri R.
i 1
(b) Ri is a connected set. i 1, 2
Chapter 2
Digital Image Fundamentals
2.3 Image Sensing and
Acquisition
Digital image acquisition using a single sensor
2-3
Digital image acquisition using sensor strips
Digital image acquisition using sensor arrays
2-5
2.4 Image Sampling and
Quantization
Chapter 4
Filtering in the Frequency
Domain
4.2 Preliminary Concepts
Fourier Theory
Fourier series
Any function that periodically repeats can be
expressed as the sum of sines and/or cosines of
different frequencies, each multiplied by a
different coeffici
Chapter 1
Introduction
1.1 What is Digital Image
Processing?
Refers to processing digital images by
means of a digital computer;
Encompasses processes
whose inputs and outputs are images;
that extract attributes from images;
that recognize individual obje
Chapter 11
Representation & Description
Overview
Representation used to make the data useful to a
computer (further process : description)
representing region in 2 ways
in terms of its external characteristics (its boundary)
focus on shape characteristic
Chapter 5
Image Restoration
5.1 A Model of the Image
Degradation/ Restoration
Process
Basic Concepts
Improve the appearance of an image
Enhancement is subjective
Heuristic procedure
Restoration is objective
Modeling the degradation and applying the
invers
Chapter 9
Morphological Image
Processing
9.1 Introduction
Morphology: a branch of biology that deals with the
form and structure of animals and plants
Morphological image processing is used to extract
image components for representation and description
of
Chapter 6
Color Image Processing
6.1 Color Fundamentals
Physical Nature of Color
The color spectrum can be divided into six
regions
violet, blue, green, yellow, orange and red
The visible light is composed of a narrow
band frequencies with wavelengths fr
Chapter 7
WAVELETS AND
MULTIRESOLUTION PROCESSING
7.1 Background
Multiresolution Processing
Small objects need higher
resolutions for analysis.
Large objects need lower
resolutions for analysis.
7-2
Low resolution
High resolution
Image pyramid
A simple st
Data Structure and Algorithm I
Trees II
Huiwu Luo
luohuiwu@gmail.com
Faculty of Science and Technology
University of Macau, Macau
20/04/2017
Huiwu Luo
Trees
20/04/2017
1 / 26
Properties of Binary Search Tree (BST) I
Figure: An example of a binary search
Introduction
Data Structure and Algorithm I
Trees
Huiwu Luo
luohuiwu@gmail.com
Faculty of Science and Technology
University of Macau, Macau
13/04/2017
Huiwu Luo
Trees
13/04/2017
1 / 32
Introduction
Why Do We Need Trees?
Note: Most of the contents are tak
Operations on Sets
union, AB = cfw_x| xA or xB
intersection, AB = cfw_x| xA and xB
disjoint sets: sets have no common elements
complement of B with respect to A, A-B = cfw_x|
xA and xB
U, universal set containing A, then U-A is the
complement of A, A=cfw
Part 1
Fundamentals
Sets
Subsets
Sets
A collection of elements or members
List elements between braces
A = cfw_ 1, 3, 5, 7
Use uppercase to denote sets, lowercase to denote
members
Notation P(x) denotes a sentence or statement P
concerning the variab
CISB111 Homework 2
Deadline: 23/09/2016
Student No._
Question
Marks
1
Name: _
2
3
Chinese Name: _
4
5
Total
1. [20] Let = cfw_, , . Tell whether or not the string on the left belongs to the regular set
corresponding to the regular expression on the right.
Exercise 1
1.Determine whether each of the following statements is true or false.
(a) x cfw_x
(b) cfw_x cfw_x
(c) cfw_x cfw_x
(d) cfw_x cfw_x
(e) cfw_x
(f) cfw_x
2.Let A = cfw_2, 3, 4, 5.
(a) Show that A is not a subset of B = cfw_x N | x is even.
(b) Sho
Faculty of science and Technology
Course study plan for academic year 2016/2017 Semester 2
Computer Science
Student No: _
Student Name: _
Phone No: _
Email: _
Please tick () the box next to the course(s) you will take in 2nd semester of academic year
2016
VE
AD E D E
M
AC
AU
UNI
ID
RS
Faculty of science and Technology
Course study plan for academic year 2017/2018 Semester 1
Computer Science
Student No: _
Student Name: _
Phone No: _
Email: _
Please tick () the box next to the course(s) you will take in 1st
CEEB351
Shear Strength of Clay Part 2
Basic Types of Triaxial Tests
Types
Drainage valve
Strength parameters
c
d
CD (S)low
Open
Open
Effective: c,
CU R
Open
Closed
c, and c,
UU (Q)uick
Closed
Closed
Total: cu or Su
Objectives of Different Tests
UU test
CEEB351
Soil Compaction
Compaction
Compaction is the process of packing soil particles together
by the application of mechanical energy, then reducing the void
ratio of soil by driving out the air.
Why compact soils?
Constructions such as dams, retaining
CEEB351
Vertical Drains
Vertical Drains in Soft Soil
Use of Vertical Drains
Vertical drains are artificially-created drainage paths which are inserted into the
soft clay subsoil.
Typical spacing:
1.5~3.5m
Drainage path:
Vertical: 15m
Horizontal: 1.5m
Th