Design Patterns
Elements of reusable Object-Oriented
Software.
Preface to book . 10
Foreword. 12
Guide to readers. 13
Introduction . 14
What is a Design Pattern?. 15
Design Patterns in Smalltalk MVC . 17
Describing Design Patterns . 18
The Catalog of Desi
Games Programming with Java and Java 3D
Andrew Davison
Dept. of Computer Engineering
Prince of Songkla University
HatYai, Songkhla 90112
E-mail: [email protected]
Draft: 14th January 2003, #2
Abstract
This article looks at the advantages and disadv
Tone and Tightens
Beginners Guide To Weight Loss
Contents
Introduction
Section 1 - How To Lose Weight
How To Lose Weight (2)
Section 2 - Metabolism
10 Ways To Naturally Boost Your Metabolism (9)
Section 3 - Diet
How To Eat Healthier (15)
8 Rules of Health
Stacks and Queues
Chris Kiekintveld
CS 2401 (Fall 2010)
Elementary Data Structures and Algorithms
Two New ADTs
Define two new abstract data types
Both are restricted lists
Can be implemented using arrays or linked lists
Stacks
Last In First Out (LIFO
csci 210: Data Structures
Stacks and Queues
1
Summary
Topics
Stacks and Queues as abstract data types ( ADT )
Implementations
arrays
linked lists
Analysis and comparison
Applications: searching with stacks and queues
In-class problem: missionary and ca
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IKM Assessment Description
JAVA 7 PROGRAMMING (JAVA SE 7)
This test is designed for software developers to assess their understanding of the Java Platform, Standard
Edition language through Java SE 7. The Secure Evaluation Mode and Remote versions of this
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMSII: EXPRESS BRIEFS, VOL. 63, NO. 3, MARCH 2016
259
Ultralow-Power Bioimpedance IC With
Intermediate Frequency Shifting Chopper
Hyoungho Ko, Takhyung Lee, Ji-Hoon Kim, Jong-ae Park, and Jong Pal Kim
AbstractA bioele
A Fully Integrated Electroencephalogram (EEG) Analog Front-End
IC with Capacitive Input Impedance Boosting Loop
Seunghyun Lim, Changho Seok, Hyunho Kim, Haryong Song, and Hyoungho Ko
Department of Electronics, Chungnam National University, Daejeon 305-764
CHAPTER 4 (5 LECTURES)
NUMERICAL SOLUTION OF SYSTEM OF LINEAR EQUATIONS
1. Introduction
System of simultaneous linear equations are associated with many problems in engineering and
science, as well as with applications to the social sciences and quantitat
CHAPTER 6 (5 LECTURES)
ITERATIVE TECHNIQUES IN MATRIX ALGEBRA
1. Introduction
In this chapter we will study iterative techniques to solve linear systems. An initial approximation
(or approximations) will be found, and new approximations are then determine
CHAPTER 5 (4 LECTURES)
DIRECT METHODS FOR SOLVING LINEAR SYSTEMS
1. Introduction
System of simultaneous linear equations are associated with many problems in engineering and
science, as well as with applications to the social sciences and quantitative stu
CHAPTER 7 (4 LECTURES)
INITIAL-VALUE PROBLEMS FOR ORDINARY DIFFERENTIAL EQUATIONS
1. Introduction
Differential equations are used to model problems in science and engineering that involve the change
of some variable with respect to another. Most of these
OOPs With C+
UNIT-I
Programming paradigms:
Programming paradigms means the way of writing a program depending upon the requirements.
These requirements mainly focus the task of development team to develop programs for the smallscale projects to the large-
Introduction to Mobile Computing
The rapidly expanding technology of cellular communication, wireless
LANs, and satellite services will make information accessible anywhere and at
any time. Regardless of size, most mobile computers will be equipped with a
Using Weka 3 for classification and prediction
Preparing a test file
1. Copy the attribute definitions from the training ARFF file into a new test ARFF file.
2. Include a proper name for the relation in the test file, say @relation weather-test
3. Include
Difference among various Computational Intelligence
I have some experience in machine learning yet I'd never really heard of the term "Computational
Intelligence", but reading through the Wikipedia article I can say that there is indeed a difference.
Mach
Output Primitives
Output Primitives
Points
Lines
DDA Algorithm
Bresenhams Algorithm
RasterizationProcess of determining which pixels give the best
approximation to a desired line on the screen.
Scan ConversionDigitizing a picture definition given in
Output Primitives
Output Primitives
Points
Lines
DDA Algorithm
Bresenhams Algorithm
RasterizationProcess of determining which pixels give the best
approximation to a desired line on the screen.
Scan ConversionDigitizing a picture definition given in
Chapter 7: Visualization
Visualization
A picture is worth more than a thousand
words. a Chinese proverb
A picture is worth more than a thousand
numbers.
What Is Visualization?
seeing is believing
we observe and draw conclusions
seeing is also understand
Graphics
Chapter 6: Basic
Rendering
CGVR
Scene Definitions
Camera
View Frustrum
View Plane
Objects/Models
Rendering
CGVR
Rendering is the process of generating an image from a 2D or 3D
model (or models in what collectively could be called a scene file)
A
Graphics
3D Viewing &
Representations
Transformation
CGVR
P(x, y, z)
3D Object Coordinate
Model
Model Transformation
Transformation
3D Viewing
Coordinate
3D World Coordinate
Viewing
Viewing Transformation
Transformation
3D Viewing Coordinate
Projection
Pr
Graphics
2D and 3D Geometric
Transformations
Geometric Transformation
Definition
Changing the coordinates of the object
Translation, Rotation, Scaling
Motivation Why do we need geometric
transformations in CG?
As a viewing aid
As a modeling tool
As an ima
Cloud Computing
Dr. Sharad Saxena
INTRODUCTION
Cloud Computing
Cloud Computing is a framework for
enabling convenient, on-demand network
access to a shared pool of computing
resources
(e.g.
servers,
storage,
applications etc.) that can be rapidly
provisi
Clipping
Clipping
2
Clipping
Weve been assuming that all primitives (lines,
triangles, polygons) lie entirely within the viewport
In general, this assumption will not hold
3
Clipping
Analytically calculating the portions of primitives
within the viewport
Public utility cloud services
Vs
Traditional data center environments and
private enterprise clouds
3 Key Differences
Provide
true
on-demand
services,
by
multiplexing demand from numerous enterprises
into a common pool of dynamically allocated
resources.