Online Degree Programs

Undergraduate Course> Athabasca University

Mathematics (MATH) 100
Developmental Mathematics (Revision 1)

Mathematics Diagnostic Assessment. This online test contains 70 questions that will help you assess your mathematical skills. Based on your score we will recommend which Athabasca University mathematics course you are likely ready to take successfully.

Delivery mode: Individualized study.

Credits: 0 - Science

Prerequisite: None. Students are expected to be able to perform basic arithmetic operations with ease—addition, subtraction, multiplication and division—and have some familiarity with fractions and algebraic operations

Overview

This course is intended as a review of basic mathematics. It is recommended for students who need to develop a mathematical background before taking university level mathematics courses. The course is not given for university credit.

Material covered includes basics of addition, subtraction, multiplication and division; fractions and decimals; ratios, proportions and percentages; basic algebra; solution of simple linear equations; graphing of equations; factoring; progressions and logarithms; basic ideas of sets; inequalities; basics of geometry and trigonometry; basics of probability.
Outline

Unit 1: Mathematical Operations: Numbers, Fractions and Decimals
Unit 2: Ratio, Proportion and Percentage
Unit 3: Basic Algebra
Unit 4: Linear Equations and Graphing
Unit 5: Algebraic Factoring and Fractions
Unit 6: Progressions and Logarithms
Unit 7: Sets and Inequalities
Unit 8: Geometry
Unit 9: Trigonometry
Unit 10: Probability, Data Analysis and Statistics

Department of Mathematics Degree Programs at Ateneo De Manila University

BS/M Applied Mathematics Major in Mathematical Finance (BS/M AMF)

Mathematical Finance is a flourishing area of modern science, which has rapidly developed into a substantial body of knowledge. The theory of finance has become increasingly mathematical to the point that problems in finance are now driving research in mathematics. Students of the five-year program will graduate with a BS Applied Mathematics Major in Mathematical Finance at the end of the fourth year and a Master of Applied Mathematics Major in Mathematical Finance at the end of the fifth year. The content and curriculum for the program have been worked out jointly with leading practitioners in the field to ensure relevance of the program. The program aims to produce graduates with rigorous foundation in mathematical modeling and economics of financial markets combined with keen knowledge of business practices that will enable them to enter competitively the pool of potential employees of investment banks and other financial institutions. Graduates can also pursue a higher research degree in mathematical finance.

Transportation Engineering course for School of Engineering and Technology
CE73.16 : Logistics Systems 3(3-0) [Elective course]

Rationale:

This course will provide students with an understanding of the theoretical and practical aspects of several contemporary and advanced topics on actual logistics planning based on the fundamental knowledge mathematical programming and transport systems.

Catalog Description:

Decision making system, transportation planning, non-linear programming, inventory model.

Pre-requisite(s):

None

Course Outline:

I. Introduction
1. Modeling logistics
2. Demand and supply model
3. Mathematical programming
4. Inventory model

II. Mathematical Programming for City Logistics
1. Linear programming
2. Non-linear programming
3. Application of linear and non-linear programming
III. Modeling of Logistics
1. Aggregated demand forecast for city logistics
2. Disaggregated demand forecast for city logistics
3. Inventory model
4. Delivery scheduling

IV. Future Perspectives
1. City logistics with ITS

Remote Sensing And Geographic Information System course for School of Engineering and Technology

AT76.07 : Advanced Mapping Technology 3(2-3) [Elective course]

Rationale:

This course introduces RS/GIS and Computer Mapping Technology (CMT) students to advanced mapping technology about automated map recognition, map design, 3D map display and others.

Catalog Description:

Advanced methodology of mapping technology. Automated map recognition. Map scanning. Geometric correction. Map feature extraction. Raster-vector conversion. Recognition of contour/cadastral maps. DEM Generation. 3D map display.

Pre-requisite(s):

AT76.02 (Mapping Technology) or Consent of Instructor.

Course Outline:

I Introduction
1. Overview and History
2. Concepts of Automated Cartography

II Fundamentals of Mathematical Morphology
1. Fundamental Operators of MM
2. Morphological Filtering
3. Binary Image Feature Extraction
4. Topological Properties

III Map Scanning and Processing
1. Map Scanning
2. Data Compression
3. Morphological Filtering
4. Geometric Feature Extraction
5. Topological Feature Extraction

IV Contour Map Recognition
1. Contour Line Feature Extraction
2. Contour Line Linking
3. Raster-Vector Conversion
4. Contour Line Labeling
V Cadastral Map Recognition
1. Map Line Feature Extraction
2. Polygon Generation
3. Leading Line Recognition
4. Number String Recognition
5. Multi-relations based Checking

VI DEM Generation
1. Basic Concepts
2. Algorithms of Computational Geometry
3. Generation of Triangulated Irregular Network (TIN)
4. Generation of Grid-DEM

Laboratory Sessions:

1. Introduction of Auto-2D System and Testing MM Operators
2. Pre-processing for Scanning Maps
3. Example of Contour Map Recognition
4. Example of Cadastral Map Recognition
5. Mini-project

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