University of Bologna

This course is part of the Laurea Magistrale program. The course is intended for advanced level students only. Enrollment is by permission of the instructor. This course offers a study of electric drives. The course discusses topics including fundamentals of electromechanical conversion systems and fundamentals of electrical machines; DC machines; brushless machines with trapezoidal back emf; brushless machines with sinusoidal back emf; and principle of static conversion. The course discusses: the fundamentals of static and electromechanical conversion systems; the configuration of basic power electronic conversion systems, of main electrical machines, either direct current (DC) or alternate current (AC), and of electric drives used in automotive sector; the topology, control principles, input, and output characteristics of main DC and AC electric drives; modeling power electronic converters, control system, electrical machines, and full drive systems with reference to application for torque and speed control; and how to represent an electric drive in terms of energetic conversion system, for the integration in a multiphasic model of a vehicle.

The course discusses topics including: the theoretical framework of the Ecological Approach to the Social Inclusion, and Inclusive Education and the Quality of Life Model (QOL); the main operational directions of the Ecological Approach underlying the processes of social inclusion, education, and well-being; the main theoretical and cultural references related to the construct of resilience in relation to fragility and vulnerability aimed at the development of a Life Project in the community; how to promote processes and practices of social inclusion and inclusive education in the community and at global level according to the approach of Universal Design (UD) and Universal Design for Learning (UDL); how to promote cultural and practical tools to develop a Life Project to enhance the Quality of Life in the community; and how to use of the universal design tried learning methods and of the acquired analysis tools for the development of students’ professional growth and for the educational design.

This course is part of the Laurea Magistrale program and is intended for advanced level students. Enrolment is by consent of the instructor. The course introduces fundamentals in economic evaluation theory and modeling methodology in healthcare. Students learn how to structure a medical decision model and how to estimate the incremental cost-effectiveness (ICER) and cost-effectiveness acceptability curves (CEACs), how to interpret results, and how to draw policy implications. Students are trained in critically reviewing HTA-studies, in order to judge their validity and applicability. The course discusses topics including CEA/CBA analysis; uncertainty and decision-making in healthcare; fundamental concepts of economic evaluation theory; theoretical foundation of modeling; types of models; development of decision trees and Markov models; an sensitivity analysis and the interpretation of the results. The course consists of ten classes. Classes are lectures which last three hours, with breaks where necessary. At least three classes are Excel workshops carried out in the computer lab. The course requires a reasonable level of understanding of basic mathematical concepts and basic probability theory. Students should also be comfortable with the basics of spreadsheet software such as MS Excel.

This course is part of the LM degree program and is intended for advanced level students. Enrollment is by consent of the instructor. The course is subdivided into two parts. Part one discusses topics including an introduction to the study of the history and culture of the ancient Mesopotamian civilizations (Sumerians, Akkadians, Babylonians, Assyrians); and introduction to the cuneiform writing; elements of the Sumerian language; a guide to the electronic resources for the study of Sumerian; and reading, translation, and grammatical analysis of elementary Sumerian texts in cuneiform writing. Part two of the course discusses topics including Sumerian royal inscriptions: typology, structure, and contents; and reading, translation and historical-philological comment of Sumerian royal inscriptions in cuneiform writing.

This course is part of the LM degree program and is intended for advanced level students. Enrollment is by consent of the instructor. This course discusses the morphology and function of specific organs and apparatuses of biotechnological interest in the context of clinical applications, correlates concepts of integrative physiology of the human organism with pathophysiology, and selects and interprets scientific data relevant to physiology and pathophysiology. Topics include cellular physiology; synaptic transmission; skeletal, smooth, and cardiac muscle; functional organization of the nervous system; cardiovascular function; respiratory function; and renal function.

The course is an introduction to the COMMEDIA: INFERNO, PURGATORIO, AND PARADISO with particular attention to key cantos. Students read texts and apply methodological tools for the analysis of literary texts. Required reading includes COMMEDIA by Dante Alighieri. Students are also required to read essays in Italian from a list provided by the course instructor.

This course is part of the Laurea Magistrale program and is intended for advanced levels students only. Enrollment is by consent of the instructor. The course considers the Indian Ocean as an interregional arena created by the intersection between maritime trade and cultural connections. It focuses on the circulation of people, goods and ideas across the oceanic space as a way to understand the connections and disconnections that created a unified system of cultural and economic exchange. The course adopts a longue durée perspective, in order to unravel the rise and development of an Indian Ocean regional identity. It considers the Indian Ocean as the first global economy produced by the decoding of the monsoon wind system and then explores the rise of Islam and the consequent development of the Swahili civilization along the East African coast. It analyses the indigenous responses to the European commercial intrusions that started in the 16th century and explores the impact of the development of formal colonial rule in the 19th century. Elements like port cities, littoral societies, trade diasporas, religion networks, long-distance trade routes, and different forms of slavery will be used as analytical tools to unravel the elements of unity and disunity in the Indian Ocean space. Particular attention is given to East African societies and their role in the Indian Ocean world. During the course, the students analyze travel accounts, novels, historical sources, and scholarly works and critically engage with the historiographical debates that characterize the Indian Ocean Studies field. At the end of the course, students reach an understanding of the Indian Ocean cultures, economies, and societies that transcends national histories and be able to engage with a non-Eurocentric approach to processes of globalization.

This is a special studies course involving an internship with a corporate, public, governmental, or private organization, arranged with the Study Center Liaison Officer. Specific internships vary each term and are described on a special study project form for each student. A substantial paper or series of reports is required. Units vary depending on the contact hours and method of assessment. The internship may be taken during one or more terms but the units cannot exceed a total of 12.0 for the year.

This course is part of the LM degree program and so is intended for advanced level students. Enrollment is by consent of the instructor. This course discusses fundamentals of the most important multivariate techniques that help to make intelligent use of large data base by recognizing patterns for predicting or estimating an output based on one or more inputs. At the end of the course the student is able; to represent and organize knowledge about big data collections; to turn data into actionable knowledge; and to choose the best suited methodology for the problem at hand to critically interpret the results. The course discusses topics including an introduction to supervised statistical learning; resampling methods: Cross-Validation, and Bootstrap; classification: Naive Bayes, k-Nearest Neighbors, Logistic Regression, and Linear Discriminant Analysis; Dimension Reduction and Regularization; Tree-based methods: Regression and Classification trees, Bagging, Random Forests, and Boosting; and an overview of the main machine learning methods: Support Vector Machines, and Neural Networks.