Computational Science

Course Information

College	Tsuyama College	Year	2021
Course Title	Computational Science
Course Code	0055	Course Category	General / Compulsory
Class Format	Lecture	Credits	School Credit: 2
Department	Department of Integrated Science and Technology Electrical and Electronic Systems Program	Student Grade	3rd
Term	Year-round	Classes per Week	2
Textbook and/or Teaching Materials	Textbook: Cによる数値計算法入門（森北出版）
Instructor	TAKETANI Hisashi,MATSUSHIMA Yukiko,HATA Yoshikazu,FANG Guanshen

Course Objectives

Learning purposes : To learn the computional methods, and conduct such methods and simulation of data to solve various actual problems by using computer.To learn computional methods, and use such methods and simulation of data to solve actual problem.

Course Objectives :
1. To comprehend the basis of simulation of data.
2. To understand the basis of computional methods.
3. To understand the basis of C programming language.
4. To know the problems in massively parallel computing.

Rubric

	Excellent	Good	Acceptable	Not acceptable
Achievement 1	The student can explain the basis of simulation, and propose methods of simulation to solve actual problems.	The student understands the basis of simulation, and can try to solve actual problems via simulation.	The student partly understands the basis of simulation, and know the reasons and some methods to solve problems.	The student does not understand the basis of simulation, and does not know the reasons and some methods to solve problems.
Achievement 2	The student deeply comprehends and can represent the basis of computional methods.	The student fully comprehends the basis of computional methods.	The student roughly comprehends the basis of computional methods.	The student does not comprehend the basis of computional methods.
Achievement 3	The student deeply comprehends and can represent the basis of C programming language.	The student fully comprehends the basis of C programming language.	The student roughly comprehends the basis of C programming language.	The student does not comprehend the basis of C programming language.
Achievement 4	The student deeply comprehends and can represent the current problems in massively parallel computing to others.	The student fully comprehends the current problems in massively parallel computing.	The student roughly comprehends the current problems in massively parallel computing.	The student does not understand the current problems in massively parallel computing.

Teaching Method

Outline:

General or Specialized : Specialized

Required, Elective, etc. : Must complete subjects

Field of learning : Information science, Information Engineering and conern subjects, computational science.

Relationship with Educational Objectives :This class is equivalent to "(2) Acquire basic science and technical knowledge".

Relationship with JABEE programs :The main goals of learning / education in this class are "(C)Acquirement of the information technology ".

Course outline :
In this lecture, students learn the basis of simulation and computational methods, and how to apply them on computer to sovle actual problems. In detail, students learn and understand 1) the application of C programming language, 2) basic computitional methods, and 3) solution of typical problems based on such methods. In additional, students also learn current situation of massively parallel computing, which is necessary in computer simulation. At last, the heat topic in recent years, Artificial Intelligence is also concerned in class.

Style:

Course method :
Classes are conducted by way of presentation and student exercises. Class focus is on solving problems using computational methods. In every lesson, a presentation will be given by the professor in the first 45 minutes, and students will do exercises in the second 45 minutes. Every time a report will be given as portfolio to students to confirm their understanding.

Grade evaluation method :
Exams (50%) + reports (30%) + effort in exercises(20%).
Regular examinations will be conducted 4 times, each equally weighted. Students who cannot achieve 60 points on exams can take retests. In that event, score changes cannot exceed 60 points.

Notice:

Precautions on the enrollment :Students must take this class (no more than one-third of the required number of class hours missed) and earn the credit in order to complete the 3rd year course.

Course advice : Ensure that every report is submitted.

Foundational subjects : Foundation of Integrated science and engineering,Information literacy, electrical and electronic circuit, Introduction of CAD

Subjects concerned: All specialized subjects since grade three.

Attendance advice : Computer, network, and information techniques have miracle improvement during recent years. Reading of material that related with computer and network is recommended.
2 times of late for class will be counted as 1 absence.

Course Plan

			Theme	Goals
1st Semester
	1st Quarter
		1st	Guidance.Introduction of content of this lecture, learning method, and usage of computers.
		2nd	The concept of simulation by computer. Exercise: login, setting of password, the basis of C language programming.	Understand the basis of simulation, and make sure the computer is able to be used.
		3rd	Equation: Dichotomy and exercise.	Undertand the principle of Dichotomy, make and run the program of Dichotomy.
		4th	Equation: Newton's method and exercise.	Undertand the principle of Newton's method, make and run the program of Newton's method.
		5th	Simultaneous linear equations: matrix and Upper triangular simultaneous linear equations, exercise.	Undertand the principle of Simultaneous linear equations.
		6th	Simultaneous linear equations:Gaussian elimination and exercise.	Undertand the principle of Gaussian elimination, make and run the program of Gaussian elimination.
		7th	Simultaneous linear equations:Gauss-Jordan method and exercise.	Undertand the principle of Gauss-Jordan method, make and run the program of Gauss-Jordan method.
		8th	Mid-term examination.
	2nd Quarter
		9th	Explanation of mid-term examination.	Unerstand the problems of mid-term examination.
		10th	Simultaneous linear equations: shape of solutions, Linear programming.	Undertand the principle of shape of solutions, and Linear programming.
		11th	Simultaneous linear equations:LU decomposition and exercise(1).	Understand the basis of LU decomposition, make and run the program of LU decomposition.
		12th	Simultaneous linear equations:LU decomposition and exercise(2).	Understand the basis of LU decomposition, make and run the program of LU decomposition.
		13th	Polynomial method: Lagrange polynomial method and exercise.	Understand the basis of Lagrange polynomial method, make and run the program of Lagrange polynomial method.
		14th	Polynomial method: Newton polynomial formula and exercise.	Understand the basis of Newton polynomial formula, make and run the program of Newton polynomial formula.
		15th	1st semester final exam
		16th	Return and commentary of exam answers
2nd Semester
	3rd Quarter
		1st	Curve fitting: Spline function and exercise.	Understand the basis of Spline function, make and run the program of Spline function.
		2nd	Curve fitting: Minimization of squares and exercise.	Understand the basis of Minimization of squares, make and run the program of Minimization of squares.
		3rd	Numerical integration: Trapezoidal rule and exercise.	Understand the basis of Trapezoidal rule, make and run the program of Trapezoidal rule.
		4th	Numerical integration: Simpson's rule and exercise.	Understand the basis of Simpson's rule, make and run the program of Simpson's rule.
		5th	Numerical integration: Gaussian integral formula and exercise.	Understand the basis of Gaussian integral formula, make and run the program of Gaussian integral formula.
		6th	Numerical integration: double integral and exercise.	Understand the basis of double integral, make and run the program of double integral.
		7th	Differential equation: Runge–Kutta method and exercise(1).	Understand the basis of Runge–Kutta method, make and run the program of Runge–Kutta method.
		8th	2nd semester mid-term exam
	4th Quarter
		9th	Return and commentary of exam answers
		10th	Differential equation: Runge–Kutta method and exercise(2).	Understand the basis of Runge–Kutta method, make and run the program of Runge–Kutta method.
		11th	Partial differential equation: Difference approximation and exercise(1).	Understand the basis of Difference approximation, make and run the program of Difference approximation.
		12th	Partial differential equation: Difference approximation and exercise(2).	Understand the basis of Difference approximation, make and run the program of Difference approximation.
		13th	Partial differential equation: Difference approximation and exercise(3).	Understand the basis of Difference approximation, make and run the program of Difference approximation.
		14th	Review of content, exercise.
		15th	2nd semester final exam
		16th	Return and commentary of exam answers

Evaluation Method and Weight (%)

	Examination	Presentation	Mutual Evaluations between students	Behavior	Portfolio	Other	Total
Subtotal	50	0	0	20	30	0	100
Basic Proficiency	50	0	0	20	30	0	100
Specialized Proficiency	0	0	0	0	0	0	0
Cross Area Proficiency	0	0	0	0	0	0	0