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UMass Lowell Computer Science 91.504 Advanced Algorithms Computational Geometry Prof. Karen Daniels Spring, 2004 Project.

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Presentation on theme: "UMass Lowell Computer Science 91.504 Advanced Algorithms Computational Geometry Prof. Karen Daniels Spring, 2004 Project."— Presentation transcript:

1 UMass Lowell Computer Science 91.504 Advanced Algorithms Computational Geometry Prof. Karen Daniels Spring, 2004 Project

2 Project Deliverables Preliminary Topic Choice (proposal 1st draft) 3/29 2% Proposal4/5 3% Class Discussion & 1-page proposal summary 4/12 5% Status Report & Draft Introduction 4/215% Status Report & Draft Theoretical Results & Algorithm Design 4/26 5% Status Report & Draft Experimental Design & Implementation & Results5/35% Final Project Report & Presentation5/10 10% 35% of course grade Deliverable Due Date Grade %

3 Project Guidelines: Proposal ä Objective: State the goal of the project ä State topic/research question ä Scope it to be doable in 7 weeks ä Plan: List the tasks you need to accomplish ä Resources: What do you need? ä Specialized equipment, language, OS? ä Specialized software/libraries? ä Additional research papers, books? ä More background in some area? ä Assessment Checklist: Characterize your project (see next 2 slides)

4 Guidelines: Proposal (continued) ä Assessment Checklist: ä Characterize your project’s theoretical aspects: ä Algorithmic Paradigm Design ä Analysis Technique Design ä Algorithm Design ä Data Structure Design ä Algorithm and/or Data Structure Analysis ä correctness ä running time and/or space ä Observations/Conjectures Difficulty Creativity Clarity Organization Correctness Scope Impact

5 Guidelines: Proposal (continued) ä Assessment Checklist: ä Characterize your project’s implementation aspects: ä Reuse of existing Code/Libraries ä New Code ä Experimental Design ä Test Suites ä Degenerate/boundary cases ä Numerical robustness Creativity Clarity Impact Difficulty Organization Correctness Scope

6 Guidelines: Class Discussion ä 15 minutes per student ä Distribute written 1-page proposal summary ä Briefly state your project’s topic/research question ä Present (with a small number of slides) some interesting aspect of what you’ve learned so far from background/related work ä Prepare one or two questions or observations to use as discussion points ä Lead a short class discussion

7 Guidelines: Final Report ä Abstract ä Introduction ä Theoretical Results ä Algorithm ä Implementation ä Results ä Summary & Conclusion ä Future Work ä References Well- written final submissions with research content may be eligible for publishing as UMass Lowell CS technical reports and/or submission to CCCG’04 in Montreal this August.

8 Guidelines: Final Report (continued) ä Abstract: Concise overview (at most 1 page) ä Introduction: ä Motivation: Why did you choose this project? ä State Topic / research question ä Background people need in order to understand project ä Related Work: Context with respect to literature ä Conference, journal papers, web sites ä Summary of Results ä Overview of paper’s organization

9 Guidelines: Final Report (continued) ä Theoretical Results: ä Clear, concise statements of definitions, lemmas, theorems and proofs ä Notation guidelines ä Algorithm: ä High-level algorithm description (& example) ä Algorithmic paradigm ä Data structures ä Pseudocode ä Analysis: ä Correctness ä Solutions generated by algorithm are correct ä account for degenerate/boundary/special cases ä If a correct solution exists, algorithm finds it ä Control structures (loops, recursions,...) terminate correctly ä Asymptotic Running Time and Space Usage

10 Guidelines: Final Report (continued) ä Experimental Design & Implementation: ä Enough of the right kind of information to allow other researchers to duplicate your work ä Resources & environment: ä What language did you code in? ä What existing code did you use? ( software libraries, etc.) ä What equipment did you use? ( machine (& processor speed), OS, compiler) ä Assumptions ä Parameter values ä Treatment of special issues, such as numerical robustness ä How did you decide what kinds of measurements would be meaningful? ä Randomness: statistical significance ä Test cases ä Representative examples ä Controlled tests to establish correctness ä Boundary/extreme cases ä Benchmarks, if available

11 Guidelines: Final Report (continued) ä Results: ä Experimental analysis ä Randomness: statistical analysis ä Test cases ä Tables ä Figures ä Graphs and Charts ä Comparison with benchmarks ä Meaningful measurements: ä CPU time? ä Combinatorial size of output? ä Effect of decisions on issues, such as numerical robustness ä Drawing appropriate conclusions ä Subjective? ä Objective? ä Were the results what you expected?

12 Guidelines: Final Report (continued) ä Summary: ä Summarize what you did ä Conclusion: ä Summarize results & impact ä Future Work: ä What would you do if you had more time? ä References: Bibliography ä Papers, books, web sites that you used ä Consistent format ä All work not your own must be cited! ä Others’ exact words must be quoted!

13 Guidelines: Status Report ä Structured like Final Submission, except: ä no Abstract or Conclusion ä fill in only what you’ve done so far ä can be revised later ä include a revised proposal if needed ä identify any issues you have encountered and your plan for resolving them

14 Guidelines: Presentation ä 20 minute class presentation ä Explain to the class what you did ä Structure it any way you like! ä Some ideas: ä slides (electronic or transparency) ä demos ä handouts

15 Project Topics (some possibilities) ä Build on a Part I assignment, such as random point assignments in 2D or 3D ä Navigate based on line arrangement to do combinatorially-based overlap increase or reduction ä Visualization: Can geometric duality help with parallel coordinate representation of high- dimensional data?

16 Project Topics (some possibilities) ä Dynamic Wireless Channel Assignment: ä design a heuristic that, given an assignment of frequencies to regions, transforms it into another assignment that: ä satisfies a given demand level (number of frequencies) for each region ä respects a separation constraint ä “minimizes” the number of frequencies ä ‘minimizes” the number of frequency reassignments


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