Presentation Skill 2 Oral Skill 2 Prepared by

Presentation Skill 2 Oral Skill 2 Prepared by Raymond Wong

Presentation Skill 2

Presentation n Do a salesman Try to promote your “paper” to researchers Try to persuade these researchers How can we do it?

Bad salesman n Describe the problem routinely n E. g. , We have the following problem. Given a list of numbers, namely n 1, n 2, n 3, …, nk, we want to find an ordering ni 1, ni 2, … nik such that ni 1 ni 2 … nik

Bad salesman n Describe the proposed solution routinely n E. g. , We have the algorithm. (1) We select the greatest number from the list M and put it in L[k]. (2) We select the greatest number from the remaining list M and put it in L[k-1]. (3) We do it similarly until the list M becomes an empty set. (4) The sorted list can be found in L.

Good Salesman n Identify the readers International researchers

Good Salesman n Make it interesting e. g. , State more applications which interest the researchers e. g. , Use a (small) running example to illustrate the problem and the algorithm e. g. , Give some theoretical results n Identify all “good” points of your paper e. g. , Properties of the algorithm e. g. , Some advantages of the algorithm (compared with previous algorithm)

Good Salesman n State why your paper is important e. g. , List your contributions n State how “smart” you are implicitly e. g. , Describe why your proposed algorithm is better than some bestknown algorithm with simple high-level intuitions

Beyond Salesman n Well-defined Terminologies n n n Remember that you need to define notations before you use some notations If necessary, give some illustrations/intuitions Proofs of some Theorems/Lemmas

Exercise 1 n n n The problem to be studied is also sorting. However, there is ONE previous work which is NOT yours. This work proposes both the sorting problem and an algorithm. The algorithm proposed there is to find the greatest number iteratively. Now, you have an excellent idea that your new algorithm is better than this previous algorithm. E. g. , Heap-sort Write a paper (or report) in order that other researchers in the world know that you propose a new algorithm better than this previous algorithm.

La. Te. X n Installation n Input n n n La. Te. X or Mik. Te. X: http: //miktex. org/ An Editor for La. Te. X: http: //www. winedt. com/ TEX files BIB files Output n PS file n You can use Ghostview to view this file n n PDF file n n Try to install Ghost. Script And then, install Ghostview http: //pages. cs. wisc. edu/~ghost/gsview/ Try to install Acrobat Reader http: //www. adobe. com/tw/products/acrobat/readstep 2. html

La. Te. X n Figure n n n “. eps” file If you have a GIF file called “abc. gif”, type “convert abc. gif abc. eps” in a UNIX machine. Guideline n If you want to draw some professional figures, try to use n Corel. Draw n n Save as “. eps” file directly Visio/Powerpoint n n Need to print to a Postscript printer as a “. ps” file Convert “. ps” file to “. eps” file

Exercise 2 n n n Read “Readme” for La. Te. X. Try to compile La. Te. X files in La. Te. X. zip. Try to compile La. Te. X files in La. Te. X-input. zip

Submission n Paper Submission n We submit a paper Some reviewers (usually, 2 -5 reviewers) will review the paper After that, we obtain a review report

Submission n Conference n n n Each year, the same organizer holds the conference in a particular month Some authors submit papers to this conference before the deadline set by the organizer The authors of the accepted papers present their papers orally in the conference

Submission n Journal n n Some authors submit papers to this journal at any time they want The authors of the accepted papers do not need to present their papers orally

Submission n Conference n n Faster Less comprehensive Shorter paper Journal n n n Slower More comprehensive Longer paper We need both conference papers and journal papers.

Submission n n If a paper is accepted as a conference paper, then an “extended” version of this paper can be submitted to journal. But, there are 30% new materials in the “extended” version.

Submission Process n Conference Abstract deadline ~1 week Full paper deadline ~3 -4 months Accept/ Reject Camera-ready deadline Decision ~1 month ~3 months Conference starts

Submission Process n Journal Accept/ Major Revision/ Minor Revision/ Reject Full paper Decision deadline Publish Revision Deadline Accept/ Major Revision/ Minor Revision/ Reject Decision Accept/ Reject Decision … ~2 -6 months ~1 -2 month ~2 -6 months ~1 -12 months

Oral Skill 2

Exercise 3 n Please listen to the tape and follow the intonation of the speaker n audio 3. mp 3 n n audio 4. mp 3 n n Louis always recycles his newspapers. audio 5. mp 3 n n Louis always recycles his newspapers. Note: n n Try to practise the above exercise at least 10 times a day Accent should be improved gradually

Exercise 4 n Please listen to the tape and follow the intonation of the speaker n audio 6. mp 3 n Today, I would like to focus on just one of many health problems young college students much like yourselves face on a day-to-day basis: weight loss and weight gain.

Heap - overview n Heap n n n store a list of numbers return the smallest number quickly Two Operations n n insert delete-min

Heap - overview n Structure property All internal nodes n complete (except the last internal node) should have two children. binary tree The last internal node can have a left child or two children.

Heap - overview n Structure property All internal nodes n complete (except the last internal node) should have two children. binary tree The last internal node can have a left child or two children.

Heap - overview n Structure property All internal nodes n complete (except the last internal node) should have two children. binary tree The last internal node can have a left child or two children.

Heap - overview n Structure property n complete binary tree

Heap - overview n Order property n n the key in the parent of X is smaller than (or equal to) the key in X smallest element at the root 6 14 6 12 12 14

Heap - insert example n Insert 10 12 1 14 6 5 8 into an initially empty binary heap

Heap - insert example n Insert 10 12 1 14 6 5 8 into an initially empty binary heap 10

Heap - insert example n Insert 10 12 1 14 6 5 8 into an initially empty binary heap 10

Heap - insert example n Insert 10 12 1 14 6 5 8 into an initially empty binary heap 10 12

Heap - insert example n Insert 10 12 1 14 6 5 8 into an initially empty binary heap 10 12

Heap - insert example n Insert 10 12 1 14 6 5 8 into an initially empty binary heap 12 10

Heap - insert example n Insert 10 12 1 14 6 5 8 into an initially empty binary heap 1 12 10

Heap - insert example n Insert 10 12 1 14 6 5 8 into an initially empty binary heap 1 12 10

Heap - insert example n Insert 10 12 1 14 6 5 8 into an initially empty binary heap 1 12 14 10

Heap - insert example n Insert 10 12 1 14 6 5 8 into an initially empty binary heap 1 12 14 10

Heap - insert example n Insert 10 12 1 14 6 5 8 into an initially empty binary heap 1 10 14 12

Heap - insert example n Insert 10 12 1 14 6 5 8 into an initially empty binary heap 1 10 14 12

Heap - insert example n Insert 10 12 1 14 6 5 8 into an initially empty binary heap 1 6 14 10 12

Heap - insert example n Insert 10 12 1 14 6 5 8 into an initially empty binary heap 1 6 14 10 12

Heap - insert example n Insert 10 12 1 14 6 5 8 into an initially empty binary heap 1 6 14 12 10

Heap - insert example n Insert 10 12 1 14 6 5 8 into an initially empty binary heap 1 6 14 12 10

Heap - insert example n Insert 10 12 1 14 6 5 8 into an initially empty binary heap 1 6 14 5 12 10

Heap - insert example n Insert 10 12 1 14 6 5 8 into an initially empty binary heap 1 6 14 5 12 10

Heap - insert example n Insert 10 12 1 14 6 5 8 into an initially empty binary heap 1 6 14 5 12 10 8

Heap - insert example n Insert 10 12 1 14 6 5 8 into an initially empty binary heap 1 Finish! 6 14 5 12 10 8

Heap - delete n Deletemin n Remove the smallest number quickly

Heap - deletemin example 1 6 14 5 12 10 8

Heap - deletemin example n 1 6 14 5 12 10 8

Heap - deletemin example n 1 5 6 14 12 10 8

Heap - deletemin example n 1 5 6 14 8 12 10

Heap - deletemin example n 1 5 6 14 8 12 10

Heap - deletemin example n 1 5 6 14 8 12 10

Heap - deletemin example n 1 5 6 8 14 12 10

Heap - deletemin example n 1 5 6 10 14 8 12

Heap - deletemin example n 1 5 6 10 14 8 12

Heap - deletemin example n 1 5 6 10 14 8 12

Heap - deletemin example n 1 5 6 8 10 14 12

Heap - deletemin example n 1 5 6 8 10 14 12

Heap - deletemin example n 1 5 6 8 10 14 12

Heap - deletemin example n 1 5 6 8 10 14 12

Heap - deletemin example n 1 5 6 8 10 12 14

Heap - deletemin example n 1 5 6 8 10 14 12

Heap - deletemin example n 1 5 6 8 10 14 12

Heap - deletemin example n 1 5 6 8 10 14 12

Heap - deletemin example n 1 5 6 8 10 12 14

Heap - deletemin example n 1 5 6 8 10 12 14

Heap - deletemin example n 1 5 6 8 10 12 14

Heap - deletemin example n 1 5 6 8 10 12 14

Heap - deletemin example n 1 5 6 8 10 12 14

Heap - deletemin example n 1 5 6 8 10 12 14

Heap n n Heap Two Operations n n n insert delete-min Internal Structure n n Don’t need to implement a tree structure Can make use of an ARRAY structure for the implementation of heap