Engineering

This course exposes students to a range of state-of-the-art developments in biomedical engineering. It invites students from various disciplines to discuss the long-term societal impacts and ethical implications of these technological advances, particularly in human enhancements beyond therapy. The course starts by illustrating the many amazing designs in the human body and yet how vulnerable it is in terms of injuries, diseases and ageing. Examples on how modern biomedical engineering helps us face our human conditions are given, such as musculoskeletal prosthetics and orthotics, cardiovascular implants, neuro-engineering, stem cells and regenerative medicine, gene editing, bio-nanotechnology, intelligence and artificial intelligence, and senses and artificial senses. A historical account of human quest for “living” machine, including a brief coverage of modern movies on bionic human then follows. The course wraps up with some social, ethical and philosophical reflections on the above issues and on the meaning of being human, opening up questions concerning the perennial human quest of becoming super human.

In this course, students learn to implement imagen processing algorithms, inside a realistic audio-visual engineering working environment, design real production configurations, and determine the quality of systems and signals by means of specific measurement equipment. This course requires background knowledge in the fundamentals of engineering optics, digital signal processing, television, and digital imagen processing.

The course is designed to equip students with experience, knowledge, and skills for succeeding in globally interdependent and culturally diverse workplaces. Throughout the course, students will be challenged to question, reflect upon, and respond thoughtfully to the issues they observe and encounter in the internship setting and local host environment. Students will have the opportunity to cultivate professional and personal development skills as defined by the National Association of Colleges and Employers (NACE). Assignments focus on building a portfolio that highlights those competencies and their application to workplace skills. Students complete 45 hours of in-person and asynchronous online learning activities and 225-300 hours at the internship placement.

In this course, students gain the knowledge and the abilities needed for solving more difficult constructive solutions. Topics include the constructive invariants needed for developing constructive solutions with a higher complexity level, the common singular sections for the different constructive techniques considered out from the basic construction, and constructive solutions by using the current building regulations. The course includes a strong design approach and at the conclusion of the course, students design a building from the construction point of view. The course requires background knowledge in basic constructive systems, constructive materials, and technology. 

In this course, students learn the planning, design, construction, and operation of highways, traffic networks and their related infrastructure. The course is divided into the following activities: lectures, recitations (design case studies), laboratory and computer practice sessions. Students use CAD/BIM professional software for highway design. Topics include specialized vocabulary and regulatory knowledge relevant to highway engineering; the core concepts, principles, and terminology in highway design and construction; the basic characteristics of road transport supply and demand, and the main actors involved. Students gain the ability and skills to analyze, quantify and correct the traffic states in rural and urban roads, as part of the usual techniques of Traffic Engineering; skills to design urban and rural road segments, specifically including geometric design, pavement design, connections and road junctions design; the fundamental characteristics of air transport and aircrafts for its use in airport infrastructure design; and develop critical analysis capabilities, conceptual scalability, and depth of understanding applicable to this Civil Engineering specialization.

This course examines the technological properties and behavior models of concrete, steel rebars and steel tendons, both individually and globally, to resist mechanical and chemical actions. Students learn to understand and apply the European standard (EUROCODE 2, EN-1992) for the design and construction of reinforced and prestressed concrete structures. Additional topics include the different structural analysis methods for concrete structures according to European standard, competence in the project, design construction and maintenance of reinforced concrete structures of moderate complexity, and the behavior and design of statically determinate prestressed concrete members with pre-tensioned tendons, and of the materials and construction systems involved. This course requires students to have prerequisites and background knowledge.

This course introduces the fundamental theory and concepts of computational intelligence methods, in particular neural networks, fuzzy systems, genetic algorithms and their applications in the area of machine intelligence. Topics include: (1) Understand the concepts of fuzzy sets, knowledge representation using fuzzy rules, approximate reasoning, fuzzy inference systems, and fuzzy logic control and other machine intelligence applications of fuzzy logic. (2) Understand the basics of an evolutionary computing paradigm known as genetic algorithms and its application to engineering optimization problems. (3) Understand the fundamental theory and concepts of neural networks, neuro-modeling, several neural network paradigms and its applications. (4) Contents: Introduction to Fuzzy Logic. Introduction to Fuzzy Sets. Introduction to Fuzzy Inference Systems. Fuzzy Logic Applications. Introduction to Genetic Algorithm. Fundamental Concepts of Artificial Neural Networks and Neural Network Architectures.

This course introduces the essential software engineering body of knowledge, including software project management, software requirements and specifications, software design, and software testing and maintenance.

This course addresses the design and performance tuning of database applications, focusing on relational database applications implemented with relational database management systems. Topics covered include normalization theory (functional, multi-valued and join dependency, normal forms, decomposition and synthesis methods), entity relationship approach and SQL tuning (performance evaluation, execution plan verification, indexing, de-normalization, code level and transactions tuning). Additional selected topics include the technologies, design and performance tuning of non-relational database applications (for instance, network and hierarchical models and nested relational model for an historical perspective, as well as XML and NoSQL systems for a modern perspective). The course requires students to take prerequisites.

This course covers healthcare delivery systems, healthcare technology-human integration, human factors in healthcare, crew resource management, quality of care, economic analysis in healthcare, healthcare logistics, healthcare system test and evaluation, and analysis and design for patient safety.