Engineering

In this research course, students chose from a range of research topics in various academic fields and receive one-on-one training from an experienced mentor who helps them refine research ideas, formulate questions, define methods of data collection, execute a plan, and present findings. Students review background information for their project, summarize its key outcomes, write a clear and concise research paper or report, and present results orally.

This course explores various ethical questions related to engineering. Examples include: What is the relationship between ethical and social responsibilities in engineering? What is considered ethical? What is considered legal? Who decides that? etc. It discusses the idea that the essence of ethics is not to set up barriers to technical progress, but, rather, to indicate in which direction progress should move. Key topics include: algorithmic fairness, the rationality of ethics, and strategies for engineers to maintain ethical integrity while working in complex systems and organizations. 

Mechanics of materials is a branch of applied mechanics that deals with the basic behavior of solid bodies subjected to various types of loading. The knowledge of the stress and strain set up within the bodies and resulting deflection is a prerequisite for the structural design of industrial products and infrastructures such as buildings, roads, bridges, and various equipment. In this course, the basic idea of structural design is provided based on the quantitative evaluation of mechanical stress and strain fields in various structures.

This course offers a study of the theory of automata and formal languages. Topics include: automata theory; finite automata; languages and formal grammars; regular languages; pushdown automata; Turing machine; compilers.

This module introduces the various standards and techniques of sketching, how to prepare engineering drawings and specifications, and how to interpret drawings. Students use advanced commercial CAD software to do 3D solid modeling. Above all, this module expands the students’ creative talent and enhances their ability to communicate their ideas in a meaningful manner. Major topics include: principles of projections; isometric; orthographic and isometric sketching; 3D solid modeling; sectioning and dimensioning; drawing standards; and limits, fits, and geometrical tolerances. This module provides the student with the fundamental knowledge to do calculations on design components like bolts, screws, fasteners, weld joints, springs, gears, material selection, fatigue, bearings, and shafts.

This course explores the historical evolution of the aerospace industry and technologies, highlighting the development of various elements of aircraft and the impact on human life.

This course covers the following topics: sets and mappings, complete induction; number representations, real numbers, complex numbers; number sequences, convergence, infinite series, power series, limits and continuity of functions; elementary rational and transcendental functions; differentiation, extreme values, mean value theorem and consequences; higher derivatives, Taylor polynomial and series; applications of differentiation; definite and indefinite integral, integration of rational and complex functions, improper integrals, Fourier series; matrices, linear systems of equations, Gauss algorithm; vectors and vector spaces; linear mappings; dimension and linear independence; matrix algebra; vector geometry; determinants, eigenvalues; linear differential equations.
 

This course provides individual research training for students in the Junior Year Engineering Program through the experience of belonging to a specific laboratory at Tohoku University. Students are assigned to a laboratory with the consent of the faculty member in charge. They participate in various group activities, including seminars, for the purposes of training in research methods and developing teamwork skills. The specific topic studied depends on the instructor in charge of the laboratory to which each student is assigned. The methods of assessment vary with the student's project and laboratory instructor. Students submit an abstract concerning the results of their individual research each semester and present the results near the end of this program.

This course includes practical application of data science theory and methodology to real world issues. Students complete a data science project with the following content: data collection and pre-processing; development of a technical solution based on data science; analysis of legal and ethical aspects; analysis of economic feasibility of the proposed solution.

This course emphasizes the use of stochastic dynamic optimization methods in theory and practice. General knowledge of probability theory and stochastic processes is assumed. Applications considered include revenue management, queueing systems and supply chain systems. The topics discussed also have wide applications to financial, economic, and engineering systems. 

Required Prerequisites: A background in college level mathematical analysis, probability theory, and stochastic processes is required. In addition, homework and term projects will include developing computer codes for algorithms presented in class. These computer codes could be applied to solve stochastic dynamic decision problems in practice.