CSE 5194.02
Transcript Abbreviation:
Sci. Visualization
Course Description:
Designed to give the student an opportunity to pursue special studies not otherwise offered.
Course Levels:
Undergraduate (1000-5000 level)
Graduate
Designation:
Elective
General Education Course:
(N/A)
Cross-Listings:
(N/A)
Credit Hours (Minimum if “Range”selected):
1.00
Max Credit Hours:
10.00
Select if Repeatable:
On
Maximum Repeatable Credits:
10.00
Total Completions Allowed:
(N/A)
Allow Multiple Enrollments in Term:
Yes
Course Length:
14 weeks (autumn or spring)
12 weeks (summer only)
Off Campus:
Never
Campus Location:
Columbus
Instruction Modes:
In Person (75-100% campus; 0-24% online)
Prerequisites and Co-requisites:
Prereq: Permission of instructor.
Electronically Enforced:
No
Exclusions:
(N/A)
Course Goals / Objectives:
Designed to give the student an opportunity to pursue special studies not otherwise offered.
Check if concurrence sought:
No
Contact Hours:
| Topic | LEC | REC | LAB | LAB Inst |
|---|---|---|---|---|
| Course overview and mathematical foundations. | 3.0 | 0.0 | 0.0 | 0 |
| Scientific data models and scientific visualization software. | 3.0 | 0.0 | 0.0 | 0 |
| Scalar data visualization I: basic visualization techniques, isosurface (marching cubes), isosurface topology, efficient isosurface search algorithms. | 6.0 | 0.0 | 0.0 | 0 |
| Scalar data visualization II: direct volume rendering – optical model, discrete approximation, transfer function design. | 6.0 | 0.0 | 0.0 | 0 |
| Scalar data visualization III: topological methods. | 3.0 | 0.0 | 0.0 | 0 |
| Vector data visualization I: basic visualization techniques, numerical integration and particle tracing. | 3.0 | 0.0 | 0.0 | 0 |
| Vector data visualization II: stream function and stream surface, flow texture synthesis. | 3.0 | 0.0 | 0.0 | 0 |
| Vector data visualization III: vector field topology. | 3.0 | 0.0 | 0.0 | 0 |
| Unstructured and scattered data visualization techniques. | 3.0 | 0.0 | 0.0 | 0 |
| Large data visualization I: parallel algorithms (volume rendering, image compositing, particle tracing). | 3.0 | 0.0 | 0.0 | 0 |
| Large data visualization II: statistics based data reduction, scientific data compression. | 3.0 | 0.0 | 0.0 | 0 |
| Machine learning for scientific visualization | 1.5 | 0.0 | 0.0 | 0 |
| Visualization software | 1.0 | 0.0 | 0.0 | 0 |
| Visualization applications: case studies | 1.0 | 0.0 | 0.0 | 0 |
| Total | 42.5 | 0 | 0 | 0 |
Grading Plan:
Letter Grade
Course Components:
Lecture
Grade Roster Component:
Lecture
Credit by Exam (EM):
No
Grades Breakdown:
| Aspect | Percent |
|---|---|
| Four lab assignments. | 60% |
| Midterm | 15% |
| Final project | 25% |
Representative Textbooks and Other Course Materials:
| Title | Author | Year |
|---|---|---|
| The Visualization Handbook | Charles D. Hansen and Christopher R. Johnson | |
| The Visualization Toolkit, 4th edition | Bill Schroeder, Ken Martin, and Bill Lorensen |
ABET-CAC Criterion 3 Outcomes:
| Outcome | Contribution | Description |
|---|---|---|
| 1 | Substantial contribution (3-6 hours) | Analyze a complex computing problem and to apply principles of computing and other relevant disciplines to identify solutions. |
| 2 | Significant contribution (7+ hours) | Design, implement, and evaluate a computing-based solution to meet a given set of computing requirements in the context of the program’s discipline. |
| 3 | Substantial contribution (3-6 hours) | Communicate effectively in a variety of professional contexts. |
| 4 | Some contribution (1-2 hours) | Recognize professional responsibilities and make informed judgments in computing practice based on legal and ethical principles |
| 5 | Some contribution (1-2 hours) | Function effectively as a member or leader of a team engaged in activities appropriate to the program’s discipline |
| 6 | Significant contribution (7+ hours) | Apply computer science theory and software development fundamentals to produce computing-based solutions. |
ABET-ETAC Criterion 3 Outcomes:
(N/A)
ABET-EAC Criterion 3 Outcomes:
| Outcome | Contribution | Description |
|---|---|---|
| 1 | Substantial contribution (3-6 hours) | an ability to identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics |
| 2 | Substantial contribution (3-6 hours) | an ability to apply engineering design to produce solutions that meet specified needs with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors |
| 3 | Substantial contribution (3-6 hours) | an ability to communicate effectively with a range of audiences - pre-2019 EAC SLO (g) |
| 4 | Some contribution (1-2 hours) | an ability to recognize ethical and professional responsibilities in engineering situations and make informed judgments, which must consider the impact of engineering solutions in global, economic, environmental, and societal contexts |
| 5 | Some contribution (1-2 hours) | an ability to function effectively on a team whose members together provide leadership, create a collaborative and inclusive environment, establish goals, plan tasks, and meet objectives |
| 6 | Substantial contribution (3-6 hours) | an ability to develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions |
| 7 | Significant contribution (7+ hours) | an ability to acquire and apply new knowledge as needed, using appropriate learning strategies |
Embedded Literacies Info:
Attachments:
(N/A)
Additional Notes or Comments:
(N/A)
Basic Course Overview:
CSE_5194.02_basic.pdf
(10.46 KB)