Computational Processing, Representation and Analysis of Data

Code:

PRODEM065

Acronym:

PRACD

Keywords
Classification	Keyword
OFICIAL	Mechanical Engineering

Instance: 2009/2010 - 2S

Active?	Yes
Web Page:	http://www.fe.up.pt/~tavares
Responsible unit:	Industrial Design Section
Course/CS Responsible:	Doctoral Program in Mechanical Engineering

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
PRODEM	1	Syllabus since 2009/10	1	-	6,5	60	175,5

Teaching language

Portuguese

Objectives

Introduction:

Currently, the Computational Processing, Representation and Analysis of Data constitute essential tools for an adequate communication form based on a transformation of the data considered in computational representations that traduces efficiently and precisely the information contained in the same data.
The several types of Computational Processing, Representation and Analysis of Data have application in different areas of the human knowledge as Medicine, Engineering and Science; namely, in medical diagnosis, meteorological maps, automobile industry, study of physical processes, etc.
With this course is intended to approach the theoretical and computational fundaments of the Computational Processing, Representation and Analysis of Data, progressively necessary as the computational simulations and analyzes are become more powerful and realistic, involving therefore huger volumes of Data of higher dimension and complexity.


SPECIFIC OBJECTIVES:
To provide to the students knowledge on a set of computational techniques that allow the achievement of representations of the information contained in a data set in order to assurance its efficient analysis, taking into account operations of data reading, processing and transformation in adequate structures for algorithms of data processing and representation.


EXPECTED OUTCOMES:
At the end of the course of Computational Processing, Representation and Analysis of Data, the students should be capable of:
1. Understand the human visual perception system;
2. Know the main algorithms of computational data processing;
3. Know the main methods of computational data representation;
4. Explain the principles and develop computational systems of Processing, Representation and Analysis of Data.

Program

Programmatic Content:
The main subjects to consider in the course of Computational Processing, Representation and Analysis of Data are: Pipeline of Data Representation, Data Representation, Algorithms for Data Representation, Data Manipulation and Representation and Processing of Image Data.
Along the course, some application examples in several domains of the knowledge of the techniques studied of Computational Processing, Representation and Analysis of Data will be verified and analyzed, as in engineering, biomechanics and medicine.

The programmatic content of the course is organized in nine modules: Presentation and Introduction, Introduction to the Object-Oriented Programming, Pipeline of Data Representation, Data Representation, Algorithms for Data Representation, Algorithms for Data Improved Representation, Data Manipulation, Representation and Processing of Image Data, Application Examples.

Mandatory literature

Gonzalez, Rafael C; Digital image processing using Matlab. ISBN: 0-13-008519-7
Freeman, Ralph D. 340; Developmental neurobiology of vision. ISBN: 0-306-40306-4
Kitware; The VTK user.s guide. ISBN: 1-930934-18-1
Foley, James D. 070; Computer Graphics. ISBN: 0-201-12110-7
Yoo, Terry S. 340; Insight into images. ISBN: 1-56881-217-5
Ware, Colin; Information visualization. ISBN: 1-55860-819-2
Schroeder, Will; Martin, Ken; Lorensen, Bill; The Visualization toolkit. ISBN: 1930934076

Teaching methods and learning activities

The course of Computational Processing, Representation and Analysis of Data is based on theoretician-practical lessons.

The theoretician-practical lessons of the course will be dedicated to present the methods and computational algorithms and for the analysis of its application in several study cases; manly, in real cases involving pertinent problems in engineering.

Whenever possible, researchers, whose scientific works are relevant in the domain of Computational Processing, Representation and Analysis of Data, will be invited to present their works; those presentations will also be open to the related scientific community.

Software

ITK – Insight Segmentation and Registration Toolkit
VTK – The Visualization Toolkit
CMIS – Contour Matching Image Software
VolView – Interactive System for Volume Visualization

keywords

Technological sciences > Technology > Computer technology > Image processing
Physical sciences > Mathematics > Algorithms
Humanities > Information science > Information management > Information processing

Evaluation Type

Distributed evaluation without final exam

Eligibility for exams

The students must submit themselves to the evaluation in all of its components: delivery of the practical project and written report, presentation and discussion of the practical project done.

Relatively to the practical projects, the students will have to define individually the subject of its projects and to propose them to the professor. The subjects of the proposed projects will have to be accepted by the professor.

Calculation formula of final grade

The evaluation system of the course of Computational Processing, Representation and Analysis of Data is composed by the accomplishment, presentation and discussion of an individual practical project, being able to be complemented with the accomplishment of a written exam.

The practical project to be developed must have an integrator view and to answer to a concrete problem of the engineering area. The subject of each project will have to be agreed between each student and the professor. The work done will have to be described in a written report to be delivered to the professor until the end of the semester and public presented and discussed.

The final grade of the practical project will be obtained using the following rule: computational work developed - 65%, written report - 25%, public presentation - 10%.

Examinations or Special Assignments

It is not applied.

Special assessment (TE, DA, ...)

On the special examination periods, the students that are dismissed from attending classes, accordingly to the terms of items a) and b) of number 3 of Article 4 of the General Evaluation Rules, will be called to do a written exam and a practical project.

Classification improvement

The grade improvement will be done according to Article 10 of the General Evaluation Rules of FEUP.