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MASTER SYLLABUS |
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HPC 2800 |
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Class Hours: 3.0
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Credit Hours:
3.0
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Laboratory Hours:
0.0
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Revised: Spring
03
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NOTE: This course
is not designed for transfer credit.
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Catalog Course
Description:
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Provides training
in the use of advanced image and raster analysis tools in the high performance
computing (HPC) environment, including the development and use of applications
to divide, distribute the analysis and recombine image data in a final
result. Students will also be trained to use commercially available and
public domain tools to analyze, combine and visualize complex image data.
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Entry Level Standards:
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College level reading
and math skills; keyboarding skills of at least 20 wpm; knowledge and experience
working in the Linux operating system and the parallel computing environment.
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Prerequisites:
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None
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Textbook(s) and
Other Course Materials:
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TBA
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I. Week/Unit/Topic
Basis:
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Week
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Topic
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1-15
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TBA
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16
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Final Exam Period
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II. Course Objectives*:
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A.
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Understand basic
image and raster image properties. I, II, IV
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B.
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Understand the relationships
between image and raster properties and the electromagnetic spectrum. I,
II, IV
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C.
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Understand how to
divide the image analysis problem in order to make efficient use of parallel
processing technology and tools **
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D.
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Understand how to
modify the application of image processing and analysis tools in order
to accomplish the goals of the analysis task**
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E.
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Understand how to
extend the skills and knowledge of successful image processing and analysis
applications to different disciplines with different analysis goals. **
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*Roman numerals after
course objectives reference goals of the HPC program.
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III. Instructional
Processes*:
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Students will:
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1.
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Use spatial elements,
measurements, locations and references to develop graphic and numerical
awareness of the real world. Understand how information in the form
of images connect to the physical world. Numerical Literacy Outcome,
Transitional Strategy
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2.
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Be familiar with
the basic procedures and the overall quality of image databases.
Numerical Literacy Outcome, Problem Solving and Decision Making Outcome
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3.
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Participate in open
discussions regarding the strengths and weaknesses of image analysis procedures
and what improvements might be made in future releases. Active
Learning Strategies, Communication Outcome, Transitional Strategy
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4.
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Use the Internet
and electronic mail to communicate effectively between the instructor,
other students, and for information gathering. Technological Literacy
Outcome, Information Literacy Outcome
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5.
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Internalize the work
ethic by demonstrating regular attendance, punctuality, dependability,
cooperation with teachers and peers, and professionalism. Personal Development
Outcome
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*Strategies and outcomes
listed after instructional processes reference Pellissippi State’s goals
for strengthening general education knowledge and skills, connecting coursework
to experiences beyond the classroom, and encouraging students to take active
and responsible roles in the educational process.
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IV. Expectations
for Student Performance*:
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Upon successful completion
of this course, the student should be able to:
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1.
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Use advanced HPC
software and tools to analyze image data. A, B, C, D
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2.
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Demonstrate unsupervised
classification of multispectral image data. A, B
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3.
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Demonstrate supervised
classification of multispectral image data. A, B
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4.
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Use HPC tools to
combine and register image data. A, C, D
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5.
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Demonstrate problem
solving ability in analyzing image data. A, B, C, E
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6.
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Use 3-D software
tools to visualize combined and registered image data. A, B, C
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7.
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Create hard-copy
output of analyzed image. A, B
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8.
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Demonstrate the ability
to use HPC tools to divide the image analysis problem. A, C, D, E
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9.
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Demonstrate the ability
to balance the image processing load between processors in the HPC cluster
used. A, C, D
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*Letters after performance
expectations reference the course objectives listed above.
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V. Evaluation:
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A. Testing Procedures:
65% of grade
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Two tests will be
administered (one test plus the final) counting for approximately 65% of
the final grade.
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B. Laboratory Expectations:
35% of grade
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Students will be
assigned group and/or individual projects. The ability to work with
others, the ability to make efficient use of equipment, and the level at
which students perform will contribute to the grade.
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C. Field Work:
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N/A
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D. Other Evaluation
Methods:
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N/A
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VI. Policies:
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A. Attendance Policy:
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Pellissippi State
Technical Community College expects students to attend all scheduled instructional
activities. As a minimum, students in all courses must be present
for at least 75 percent of their scheduled class and laboratory meetings
in order to receive credit for the course.
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B. Academic Dishonesty:
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Plagiarism, cheating
and other forms of academic dishonesty are prohibited. A student
guilty of academic misconduct, either directly or indirectly through participation
or assistance, is immediately responsible to the instructor of the class.
In addition to other possible disciplinary sanctions that may be imposed
through the regular Pellissippi State procedures as a result of academic
misconduct, the instructor has the authority to assign an F for the exercise
or examination or to assign an F in the course.
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C. Other Policies:
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Any act of misuse,
vandalism, malicious or unwarranted damage or destruction, defacing, disfiguring,
or unauthorized use of property/equipment belonging to Pellissippi State
is subject to disciplinary sanction.
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