Base Knowledge
Elementar mathematique techniques, statistic and probability notions.
Teaching Methodologies
The teaching method is initially expositive and later, during the problem-solving phase, collaborative.
The evaluation is done by performing three assessments throughout the semester grade to 10, 5 and 5 points
respectively. To approve without going to the final exam students must obtain 5, 2.5 and 2.5 respectively in each
assessment mentioned above. The grades of each assessment are not rounded. The final grade will be the sum of
the marks obtained in the three assessments. The student who does not obtain approval during the semester or not
wish to undergo this type of evaluation may perform the final examination at the times specified in the school
calendar ISEC. The final assessment is also composed of three parts with the same classification and the same
necessary distribution of minimum values achieved in order to get approval.
Learning Results
– Learn key concepts on Network Optimization, Queuing Systems and Image Processing (black and white images);
– Ability to use mathematical techniques;
– Develop capacity for perception of concepts, abstract reasoning, interpretation of results and their application to problems’ solving;
– Understanding the details of each subject in order to solve the different types of problems.
Program
I – Network Optimization
Representation of a network in the forward star form and backward star form;
Development of algorithms for solving the shortest path problem, the longest path problem, the maximum capacity
path problem, the path capacity problem in conjunction with the shortest paths or longest paths.
Application of the developed algorithms to real-world problems.
II – Queuing theory: Structure and elementary concepts; Modelling; Processes of life and death; Fundamental relations; Classification; Models with one or more servers and unlimited lengths limited; Combination of models; Application to concrete problems.
II – Image Treatment – Mathematical Morphology: Basic Operations on binary images: dilation and erosion;
Properties of dilation and erosion; Conditional dilation; Morphological gradient; Opening and closing of an image;
Properties of opening and closing; Hit-and-error; Thickening and thinning.
Internship(s)
NAO