Transcript Chapter 1

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Results
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Obviously you do not have results at the proposal
stage
You need to have some idea about what kind of
data you will be collected
What statistical procedures will be used?
Then you can answer question or test your
hypothesis
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Discussion
 Convince your reader of the potential impact of
your proposed research
 You need to communicate a sense of enthusiasm and
confidence without exaggerating the merits of your
research
 So you do not need to mention the limitation and
weaknesses of the proposed research
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Discussion
 It may be justified by time and financial
constrains as well as by the early
developmental stage of your research area
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Common Mistakes
 Failure to provide the proper context to frame the
research question
 Failure to delimit the boundary condition for your
research
 Failure to cite landmark studies
 Failure to accurately present the theoretical and
empirical contributions by other researchers
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Common Mistakes
 Failure to stay focused on the research question
 Failure to develop a coherent and persuasive
argument for the proposed research
 Too much detail on minor issues, but not enough
detail on major issues
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Common Mistakes in Proposal Writing
 Too much rambling (going all over the map)
without a clear sense of direction, the best
proposals move forward with ease and grace like a
seamless river.
 Too many citation lapses and incorrect references
 Too long or too short
 Slopping writing
 Failing to follow the standard style
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Research Problems (Internet)
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Routing algorithms ( BGP)
Communication protocols (TCP)
Algorithms for intelligently selecting a resource in
the face of uncertainty
Bandwidth sensing tools
Load balancing algorithms
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Research Problems (Internet)
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Streaming protocols
Structure of the internet
Cost optimization
DNS-related problems
Visualization
Large-scale data processing
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Computer Science Fields
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Algorithms
Artificial Intelligence
Compilers
Computational Complexity
Computer Programming
Computer Graphics
Computer Vision
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Computer Science Fields
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Cryptography
Data Mining
Data Structures
Human-Computer Interaction
Networking
Operating Systems
Programming Languages
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Computer Science Fields
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Robotics
Scientific Computing
Software Engineering
Steganography
Type Theory