This course introduces techniques that the student can use to construct simple models for analyzing and understanding the performance of systems that they are interested in. (1) To introduce students to analytical modeling of system performance. Computer systems are complex, making it hard to understand their behavior and predict their performance. Students will learn some mathematical techniques for modeling system performance, and exercise their modeling skill. (2) To broaden the student’s interest in Computer Science. Computer Science is increasingly multi-disciplinary; for example, data streams bring together issues in hardware, networking and databases. This course will give students broad exposure to analytical modeling in different areas of Computer Science. College of Electrical Engineering & Computer Science Main Campus Pre-requisites are Probability, Networks, OS Tay Young Chiang 20 Wednesday 2,3,4 CSIE5023 (922EU0240) 3 (College of Electrical Engineering and Computer Science) Graduate Institute of Networking and Multimedia,
(College of Electrical Engineering and Computer Science) Graduate Institute of Computer Science & Information Engineering
*Registration eligibility: seniors and above. http://www.csie.ntu.edu.tw/main.php?lang=en

1. Introduction 2. Fundamentals of Semiconductor Lasers 3. Mirrors and Resonators for Diode Lasers 4. Gain and Recombination Mechanisms 5. Dynamic Properties of Semiconductor Lasers 6. Tunable Lasers and Laser-modulators 7. Microcavity Lasers College of Electrical Engineering & Computer Science Main Campus Ming-Hua Mao 30 Wednesday 7,8,9 OE5013 (941EU0220) 3 Non-degree Program: Program of Photonics Technologies,
(College of Electrical Engineering and Computer Science) Graduate Institute of Electrical Engineering,
Non-degree Program: Nano-Technology Engineering,
(College of Electrical Engineering and Computer Science) Graduate Institute of Electro-Optical Engineering,
(College of Electrical Engineering and Computer Science) Graduate Institute of Electronics Engineering http://gipo.ntu.edu.tw/eng/e_index.php

i) Reflective TFT-LCDs ii) Transflective TFT-LCDs iii) Wide-viewing-angle technologies iv) Fast response time v) Blue Phase Liquid Crystals (& Displays) vi) Bistable Nematic LCDs vii) Projection displays (e.g. LCoS) & Flexible Displays viii) Low operation voltage ix) (Optional) LCD Optics: 2×2 extended Jones Matrix, 4 x 4 Matrix, Poincare Sphere, etc College of Electrical Engineering & Computer Science Main Campus Prerequisite: “Introduction to Liquid crystals”(OE5011) Grading: Homework 20%, Mid-term Exam 40%, Final Exam 40% Wing-Kit Choi 24 Thursday 8,9,10 OE5034 (941EU0430) 3 (College of Electrical Engineering and Computer Science) Graduate Institute of Electro-Optical Engineering,
Non-degree Program: Program of Photonics Technologies,
(College of Electrical Engineering and Computer Science) Graduate Institute of Electrical Engineering http://gipo.ntu.edu.tw/eng/e_index.php

.1.Humanoid Robotics — Definition of walking, dynamic and static gaits — ZMP (zero moment point) — Lagrange’s

Equations — Control Algorithms of Humanoid Robotics — Sensors and Sensing Aspects of Humanoid Robotics

2.Mutisensor Fusion and Integration –Sigal Level Fusion –Pixel Level Fusion –Feature Level Fusion –Decision Level

Fusion –Kalman Filter –Extended Kalman Filter –Particle Filter –Covariance Intersection –Covariance Union —
Dempster-Shafer Evidence Theory 3.Sensing and Control for Robot Motion 4.Interactive Service Robotics
5.Advanced Topics on Robot Sensing and Control 6.Practical examples of robot sensing and control through photos and video demonstrations. The objectives of this course are to let students who have had the basic background of the robot sensing and control issues, approaches with more in depth understanding of theories and practical applications in robot sensing

and control. The idea of this course is to convey the concept that usually sensing and control should not be

separated and they are interdependent in dealing with an intelligent systems, such as an intelligent robotics system.

Firstly, student will learn more advanced robot sensing and control issues in humanoid robot including definition of

walking, dynamics static gaiting issues, control algorithms and the need for robot sensors interact with different

control aspects. The second focus will be the study of advanced issues of sensor fusion and integration.

Synergistic use of multiple sensors by machines and systems enables greater intelligence to be incorporated into

their overall operation. Motivation for using multiple sensors can be considered as response to simple question:

if a single sensor can increase the capability of a system, would the use of more sensors increase it even further ?

In this course, theories of multisensory fusion and its applications to sensory controlled robotics systems which

involves mathematical and statistical issues including combining sensor uncertainty methods for sensor fusion

includes estimation methods, such as covariance Intersection (CI), Kalman Filtering; Classification methods,

such asSupport Vector Machine (SVM) etc. will be presented and discussed. The third focus will be the advanced

robot motionplanning and control issues. The fourth focus will be the advanced topics in interactive service robotics
by using various sensing and control algorithms.Finally, a variety of practical examples of robot sensing and control

will be presented through photos and video demonstrations. After taking this course, it is expected that students

will l get the state of the art knowledge about the advanced core robotics technologies especially in robot sensing

and control. College of Electrical Engineering & Computer Science Main Campus This course is suitable for senior and graduate students. There is a take home project in addition to the weekly class meets. The final grade will be computed on the basis of the following weights: Take Home Project Report. 25% Project Presentation during the Class. 25% Midterm Exam. 25% Final Exam. 25% TOTAL 100% Ren C. Luo 20 Thursday A,B,C EE5155 (921EU4350) 3 (College of Electrical Engineering and Computer Science) Graduate Institute of Electrical Engineering http://www.ee.ntu.edu.tw/en/

This is an introductory course in system identification, the process of developing or improving a mathematical representation of a physical system using experimental data. This course focuses equally on theoretical and practical aspects of the subject. Students will learn key mathematical skills including linear time-invariant systems, random processes, and basic estimation techniques. Practical system identification skills such as input signal design, system excitation, and model validation will also be discussed. Students are required to integrate the knowledge into their works of final projects. 1. Review of linear systems 2. Random variables and random processes 3. Least-square estimation 4. Non-parametric model identification 5. Parametric model identification 6. State-space methods 7. System identification in practice 8. Advanced topics* (subspace identification, time varying or nonlinear systems) 9. Final project presentation College of Electrical Engineering & Computer Science Main Campus Undergraduate-level Control Systems, and/or Signal and Systems. Basic/working knowledge about linear algebra, linear dynamical systems, state-space models, and Fourier, Laplace, and Z-transforms. Kuen-Yu Tsai 15 Thursday 2,3,4 EE5129 (921EU8300) 3 (College of Electrical Engineering and Computer Science) Graduate Institute of Electronics Engineering,
(College of Electrical Engineering and Computer Science) Graduate Institute of Electrical Engineering,
Non-degree Program: Transprotation Electrification Technology Program http://www.ee.ntu.edu.tw/en/

This course introduces technologies involved in mechatronics. Topics to be covered include with emphasis on electrical elements, digital logic, system response, analog signal processing, microcontroller programming, data acquisition, and automatic control. Lectures are intended to provide the students operational principles and integrated issues in mechatronics systems design. College of Bio-Resources & Agriculture Main Campus Kuo, Yan-Fu 50 Intensive courses BME5125 (631EU1630) 2 (College of Bioresources and Agriculture) Department of Bio-Industrial Mechatronics Engineering,
(College of Bioresources and Agriculture) Graduate Institute of Bio-Industrial Mechatronics Engineering http://www2.bime.ntu.edu.tw/about/introduction?locale=en

This is an introductory to finite elements offered by the Department of Civil Engineering. The finite element method has been coined as the most useful numerical method for solving engineering problems governed by partial differential equations. The contents are vast and the commercial programs are sophisticated. It is thus impetus (and sometimes difficult) to cover the important aspects of the method. This course is offered to guide you through the basic of the method and help you to acquire hands-on experience on programming the method. Learn the basic theory and formulation for finite elements (FE) with hands-on experience on FE programming (MATLAB). College of Engineering Main Campus Prerequisites: undergraduate courses in engineering mathematics, statics, dynamics and mechanics of materials. Chuin-Shan Chen 80 Wednesday 2,3,4 Thursday A,B CIE7017 (521EM1210) 3 (College of Engineering) Graduate Institute of Civil Engineering,Computer-Aided Engineering Division,
(College of Engineering) Graduate Institute of Civil Engineering, Structural Engineering Division,
Non-degree Program: Nano-Technology Engineering
*Registration eligibility: graduate students. http://www.ce.ntu.edu.tw/ce_eng/

To gain deeper insight into photogrammetric methodologies, learn state-of-the-art photogrammetric developements, and conduct photogrammetry-related project.  1.Deep understanding of photogrammetric methodologies. 2.conducting project and gaining practical photogrammetric training. 3.Treatment in advancing reading and writing skill College of Engineering Main Campus Perferrably with the knowledge of Photogrammetry.
Grading policy: 1. Article reading & writing: 30% 2. Work on Project (40%), final written report excluded. Oral Presentations: 20% Paper Reports: 20% 3. Project final written report: 30% Jen-Jer Jaw 20 Thursday 2,3,4 CIE7092 (521EM6420) 3 (College of Engineering) Graduate Institute of Civil Engineering,Geotechnical Engineering Division
*Majors-only (including minor and double major students). http://www.ce.ntu.edu.tw/ce_eng/

Understand the basic behavior of various seismic resisting steel members and systems. Discuss the core concepts and the implementation of the latest seismic steel building codes. Exercise the seismic design and nonlinear response analysis of seismic steel building systems. College of Engineering Main Campus *Loading and resistance *Seismic load and structural ductility *Basic concepts on seismic design of steel building systems *Special moment resisting frame (SMRF) *Special concentrically braced frame (SCBF) *Eccentrically braced frame (EBF) *Buckling restrained braced frame (BRBF) *Steel panel shear wall (SPSW) *Steel and concrete composite beam *Elastic and inelastic static/dynamic response analysis of seismic steel building structures Keh-Chyuan Tsai 34 Monday 7,8,9 CIE7131 (521EM7180) 3 (College of Engineering) Graduate Institute of Civil Engineering, Structural Engineering Division
*Registration eligibility: graduate students. http://www.ce.ntu.edu.tw/ce_eng/

Course Description: The course is to study the fundamentals of engineering mechanics on rigid body. The topics on statics include the concept of free-body diagram, force system resultants, equilibrium of rigid body, friction, center of gravity, and moment of inertia, etc. The topics of dynamics cover kinematics of particle force and acceleration, planar kinematics of rigid body force and acceleration, and work and energy of planar kinematics of rigid body. Course Objectives: This course is to convey the fundamental concepts on engineering statics and dynamics of a rigid body. It also serves as a basis for advanced courses in mechanics. College of Engineering Main Campus Course Requirements: Homework assignments will be given on weekly basis. There are four in-class quizzes, one midterm exam, and final exam. The students are expected to attend the lectures on time and study the course materials regularly. Yuning Liuis Ge 40 Tuesday 6,7 Wednesday 6 CIE2004 (501E21100) 3 *Majors-only (including minor and double major students).

(College of Engineering) Department of Civil Engineering http://www.ce.ntu.edu.tw/ce_eng/