Introduction to Computer Science

 

Fall 2011, Room 4263, 9:10~12:00 Thursday
Instructor: Kun-chan Lan
(this course is offered in English) 

Objectives

    * Know what is "Computer science"?
    * Familiarize yourself with the basic
          o Terminologies
          o Principles
          o Theories
    * Also, a strong hands-on focus
          o Homework
          o Project

Scope

    * Data storage
    * Computer architecture
    * Operating system
    * Networking
    * Algorithm
    * Programming language
    * Artificial intelligence

Text Book

    * J. Glenn Brookshear, Computer Science -- An Overview, 11th edition, Addison-Wesley
          o ISBN-10: 0132569035 | ISBN-13: 978-0132569033


2011-09-29
Please download and check the team list and the roll call list. If it has any problem, please contact TA.
 
2011-09-29
For 甲班 students, Please come to TA's office to borrow the GPS receiver before 10/1.
 
2011-10-23
The course of this week (10/27) class will be canceled.
 
2011-11-10
Please check your area for term project in team list. If you have any question, please contact TA.  
 
2011-11-14
Please send your presentation slides to TA before 11-17 for midterm project presentation. 
o A 3-5 minute presentation for your navigation algorithm (10%) 
o And one-page, 11-pt-font, double-spaced report that describes/explain/justify your algorithm.
 
2011-11-21
Please in the following teams submit your midterm report to TA (Jensen): 20, 23, 30, 31, 44
 
 
2011-12-10
Please in the following teams return your GPS devices to TA Henry,
27, 35, 14, 26, 39, 24, 27, 19, 28, 29, 38, 43
 
2011-12-21
Please submit your Irobot code (homework II) to TA (Jensen).
 
2011-12-28
  
2011-12-29 Time, starting location, destination will be post on the course webpage at 9:00 AM. You have one hour to estimate the travel time based on the given info and then submit your results to TA over email before 10:00 AM (no late submission). No class today.
The question is: 
Estimate the travel time from our department (大學路) to Costco (和緯路三段) by
taking the following route 大學路 -> 勝利路-> 東豐路 -> 公園北路 -> 西門路 -> 和緯路
Please consider speeds with car density (e.g., if car density is low, the speed is maximal road speed) and depart time is 11:00 AM.  

Please submit your algorithm with results to TA (Jensen),
One page report by MS word. 
  
2012-01-02
Final exam is closed book, closed note exam. You can bring one-page A4 size note to the exam. But any electronic device is prohibited (e.g., calculator, iphone, ipad, etc.)
  
2012-01-16 Student (F24007028, Mr. 梁), please contacts TA ASAP.   
2012-01-17 Student (F24007028, Mr. 梁), since your grade have some problem, please contact TA before Friday. Otherwise, accept the consequences by yourself.  
2012-01-20 Here is final grade [download]  
2012-01-20 TA puts exam paper outside of Prof. office (East Block, Yun-Ping building 309). You can take if you want.   

 

Instructor

Prof. Kun-chan Lan
  Office: Room 309 (East Block, Yun-Ping building, Kuang-Fu Campus)
  Office hours: 11-12pm on Monday and Tuesday or by appointment via e-mail
  Email: This email address is being protected from spambots. You need JavaScript enabled to view it.
  TEL: +886 6 2757575 ext 62550
 

TA

 

Grading

    * Creative project (25%)
    * Home Work Exercise (30%)
    * Exam (45%)
    * Extra credit
          o Class participation and in-class quiz
          o Up to 10%

Syllabus

  • week 1 (9/15) Administration issues 
  • week 2 (9/22) tutorial on GPS and robots (Henry and Jensen)
  • Fundamental
  • week 3 (9/29) Data storage System
  • week 4 (10/6) Hardware
  • week 5 (10/13) Operating System(I)
  • week 6 (10/20) Operating System(II)
  • week 7 (10/27) Networking (I)
  • week 8 (11/3) Networking (II)
  • week 9 (11/10)  Midterm exam
  • week 10 (11/17) Homework I due, midterm project presentation
  • week 11 (11/24) Algorithms (I)
  • Advanced topic
  • week 12 (12/1) Algorithms (II)
  • week 13 (12/8) Programming language
  • week 14 (12/15) Demo for homework II
  • week 15 (12/22) Artificial Intelligence
  • week 16 (12/29) Final project demo
  • week 17  (1/5) Final Exam

Lecture Slides

week 1 (9/15) Administration issues [video]
week 2 (9/22) Tutorial for iRobot Create Tutorial for GPS [video1] [video2]
week 3 (9/29) History, Data Storage [video1] [video2]
week 4 (10/06) Hardware [video1] [video2] [video3]
week 5 (10/13) Operating System [video1] [video2] [video3]
week 6 (10/20) Networking and the Internet [video1] [video2] [video3]
week 8 (11/3)  [video1] [video2] [video3]
week 11 (11/24) Algorithm Project comment [video1] [video2] [video3]
week 12 (12/1) Scenario of homework II [video1] [video2] [video3]
week 13 (12/8) Artificial Intelligence Programming Languages

Homework

Homewrok1:

In this exercise, we want to answer this question:
    Is it easier to meet your friends on-line or to meet them in real world?
Methodology 
    * Every time when you are on-line
          o Go to this website http://140.116.154.67/hw1
          o Enter your student ID and click on the ?Start? button on the
            page
          o Before you go offline,click on the "End" button on the page
    * TA will announce an address let you download data.
    * Compare your online times with your teammates?
    * Draw the ?overlay? time when you and your teammate are both
      on-line with Microsoft Excel
    * Record your location with GPS
    * A GPS logger will be loaned to you, and you should carry it all
      the time
    * If you are indoor, find out your GPS location via Google Map and
      record it manually
    * Download your GPS log everyday
 
   
    * Remember to recharge the battery!!
    * Draw the ?overlay? time when you and your teammate are ?close? to
      each other with Microsoft Excel
          o ?close? is defined as your GPS location is less
            than 10m from your teammates?
    * Compare your mobility data with your teammates 
Important Date
    * Trace collection period (we only have around 100 GPS loggers)
          o 甲班(and 外系/轉系): 10/1-10/31
          o 乙班: 11/1-11/30
    * Results due
          o 甲班(and 外系/轉系): 11/12 midnight
          o 乙班: 12/10 midnight
          o Submit your results (submission instruction will be
            announced later)
          o NO late submission
Evaluation
    * The more detailed raw data you collected, the higher grade
          o GPS logger collect location every second
                + So you should have a maximum of 86400 data entries
                  every day
                + GPS can only work outdoor. Estimate your GPS location
                  using Google Earth if you are indoor
    * Your analysis of results should be sensible
    * An example is at

Homework II – Auto-parking

    * Learn simple programming via iRobot
    * Use the programmable robot (iRobot) to simulate auto-parking
    * TA will give you a tutorial on how to use and program iRobot (and
      how to use GPS for your homework) on 9/22
What to do?
    * You will be given two locations A, and B (somewhere around our
      department)
    * You need to write a program to move iRobot from A to B
How would I evaluate the performance of your program?
    * How much time it will take for your program to move iRobot from A
      to B (the shorter, the better!)?
    * Could your program park the iRobot exactly at location B? (in this
      homework, we use location B to simulate the 停車格)
Loaning Equipment
    * We only have 17 iRobot ($15K each) but we have more than 100 students
    * The equipment needs to be SHARED
    * The loaning time of any equipment from TA (including iRobot,
      sensor, GPS, etc) is up to 3 days
    * First come, first serve!
    * Make a reservation when all the iRobot have been checked out
iRobot Related Document

Term project

    * Design a car navigation system
    * Car navigation
          o Provide a route from A to B for the driver
          o A good navigation system
                + should provide a route that has the shortest travel
                  time from A to B
                + relies on accurate road information
Road information
    * Traffic light cycle (how long you need to wait for the red light)
    * Road length
    * Number of lanes
    * Traffic density, i.e. how many cars moving on the same road (e.g.

      rush-hours vs. off-peak time)

How to design your navigation system?

     1. collect the road info from the real-world
    2. Design an algorithm that use those road traffic parameters we previously discuss
        (I only listed 4 parameters, you are strongly welcome to add more if you wish) to
        predict the driving time from A to B

Collect Road information

    * We will assign different teams to collect traffic info for different areas (抽籤)
          o 中西區
          o 東區
          o 北區

Example of Traces

路 口 紅 燈 綠 燈
長榮路/大學路 30 seconds 45 seconds
長榮路/裕農路 20 seconds 30 seconds


路 名 路 段 Number of lanes Road length
長榮路三段 小東路-大學路 2 720m


路 名 路 段 Time Car density
長榮路三段 小東路-大學路 7am-8am 1239
長榮路三段 小東路-大學路 8am-9am 1102
長榮路三段 大學路-小東路 7am-8am 1011
長榮路三段 大學路-小東路 8am-9am 1259
   
    * Car density: In a given duration, the number of cars entering that
      particular road
    * Duration for collection of car density
          o 7-9am
          o 11-1pm
          o 5-7pm
Example of the algorithm
    * Should look like an equation or a function
    * For example
          o Travel time =  red light duration + car speed/road distance
            * number of lanes
          o I did not use ?car density? in the example above?but you
            should try to make use of EVERY possible parameter in your
            algorithm
    * Demo your algorithm
          o You will need to present your algorithm in mid-semester (3-5
            minutes) and explain how you design your algorithm
Demo your project demo
    * In the end of semester, you will demo your project as the following
    * I will ask you, for example, how long it takes to drive at a speed
      of 30km/hrfrom 光復校區 to 赤崁樓 at 1pm
    * You should use the collected road information traces and your
      algorithm to predict the travel time
Score for the final project demo
    * Your score = 25 x ( 1 ? D / real travel time)
          o D = | your predicted travel time ? real travel time |
Project Evaluation
    * Mid-term
          o A 3-5 minute presentation for your navigation algorithm (10%)
          o And one-page, 11-pt-font, double-spaced report that
            describes/explain/justify your algorithm
    * Final
          o Project demo (15%)
data collection: 7.5%
results: 7.5%

QUIZ

    * In class
    * Problems related to the topics of the week

Exams

    * In Q&A form
    * Questions mostly are from the textbook exercise
    * 2 Exams
          o Midterm (20%)
          o Final (25%)