Interdisciplinary, multi-instructor graduate education in electronics packaging

A modern approach to graduate flight dynamics, stability, and control courses

This Innovative Practice Work in Progress Paper describes the experience and assessment of introducing machine learning concepts in a sophomore signals and systems course. Advanced machine learning concepts are typically covered in graduate level courses. However, as machine learning applications become more and more ubiquitous in our daily lives, it is important to expose students to machine learning concepts early at the undergraduate level. Signals and Systems I is a sophomore level course in the Electrical Engineering online bachelor degree curriculum. As the first course in signals and systems, it focuses on the basic concepts including signal transformation, linear time-invariant systems, Fourier series, Fourier transforms, Laplace and Z transforms. The course was taught using lecture videos and reading materials. MATLAB labs were also incorporated to introduce students to practical applications. Feedback from students showed their preference for more real world applications. This paper describes how a web-based simulation lab exercise was introduced to expose students to machine learning concepts. Specifically, students made the connection between machine learning and signals and systems concepts through a speech recognition application. In particular, students applied spectral analysis and identified voice features through pole/zero representation. To evaluate the effectiveness of the exercise, statistics from pre/post quizzes as well as student comments from a survey is analyzed.

The Packaging Research Center at the Georgia Institute of Technology focuses on thin-film multi-chip modules (MCMs) as the strategic solution in electronic packaging because this technology offers advantages in miniaturization, electrical and thermal performance, cost and reliability. Via formation using photosensitive polymer technology reduces process costs and hence is of great interest. However, to overcome process complexity issues and to facilitate low-cost manufacturing, process optimization and control are required. In this paper, a modeling approach for via formation in MCM dielectric layers composed of benzocyclobutene (BCB) is presented. A series of designed experiment is used to characterize the via formation workcell, and neural network process models are constructed for the various unit process (including spin coating, pre-bake, expose, develop, cure and de-scum). Film thickness, uniformity, via wall angle, via yield, and film retention are modeled. The neural network models will eventually be used for the development of a supervisory process control scheme.

A new graduate level course on the 'Simulation of Optical Fibre Systems' has been developed and presented for the first time within the Ottawa Carleton Institute of Electrical and Computer Engineering. The course was intended as a bridge between the areas of CAD and photonics. The course focuses on numerical techniques as well as the optics, for example, part of the course includes details on the use of finite difference techniques as well as the split-step Fourier method to solve the nonlinear Schrödinger equation (which is used to simulate pulse propagation in optical fibre). Simulation work for the first part of the course was using Matlab (for example, examining modes in fibre and examining pulse propagation), then Optisystem was used for the later part (for example, looking at dispersion compensation and WDM systems). The course was intended not to be a first course in optical fibre communications and so requires completion of a prerequisite course which covers appropriate material, or relevant experience. Details of the course are presented and discussed.

A graduate level course on economic metrics and innovative finance mechanisms for has been developed. Topics include non-traditional financing structures for project development and the application of economic metrics to investment decision making. The development of this course was motivated by recent surveys and through consultation with wind energy professionals. Recent surveys have indicated that highly qualified persons entering renewable energy fields are lacking knowledge of the technical, economic, and policy-connected aspects of their work. Synthesis of these discussions, which have guided the development of course content, highlighted that an understanding of market policy and project economics would greatly enhance the efficacy of energy technical professionals. The purpose of this course is to develop holistically equipped wind energy professionals who can intelligently engage with business and finance professionals in their field. Both live instruction and online versions of this course intend to provide this knowledge through application-based lectures and case studies to set graduates of this course apart from their peers. Course delivery, topics, learning outcomes, and evaluation methods are provided.

At Brigham Young University we offer a graduate level course on the fundamentals of acoustics. This course has traditionally covered vibrations in masses and springs, strings, bars, membranes and plates in the first half of the course. The second half covers the derivation of the wave equation, wave propagation, reflection/transmission phenomena, and source radiation problems. For decades, we used Kinsler and Frey’s “Fundamentals of Acoustics” book but the rising costs, lack of updates, and dissatisfaction with the rigor of the book motivated us to find a new text. For a few years, we used Kinsler and Frey for the vibrations portion of the course and also Blackstock’s “Fundamentals of Physical Acoustics” for the fluids portion. Two books meant even higher costs, although the Kinsler and Frey text was also used in another class at that time. When we switched instructors for the course, Anderson was asked to review Garrett’s “Understanding Acoustics” text and he ended up adopting it for this course. This talk will review our experiences in switching textbooks and discuss our reasons for selecting our current text and how we are using it in class in conjunction with pre-class reading quizzes, which has helped increase classroom discussions.

This paper describes a programming system used in the teaching of two Computer Science courses at The Pennsylvania State University (7). The courses are; an upper level undergraduate-beginning graduate level course in graph theory, and a graduate level course in the theory of graphs and networks. As can be ascertained from the description of these courses they are not primarily what would normally be called programming courses. However, since they are computer science courses they do stress the computational aspects of graph and network theory and analysis. Past experiences have indicated that if a computational problem of any reasonable complexity is assigned in class the majority of the students focus an inordinate amount of their energies to the programming problems, and consequently fail to grasp the significant features of the theoretical problems involved. In addition, since graph and network theory encompasses not only computer science, but engineering and physical, and to a lesser extent, the social sciences, many of these students would be unduly burdened by writing many rather complex programs. On the other hand, teaching the computational aspects of graph theory without doing some programming is equally ludicrous. Thus, a default type solution of assigning two or three problems from a narrow set of problems was rapidly becoming an undesirable solution to this dilema. It was at this point that the concept of a dynamically growing programming system, as described in this paper, began to formulate itself.

Is designing a graduate level course challenging enough?

Thermo-mechanical finite element analysis in a multichip build up substrate based package design

Analysis of algorithms is a part of computing curriculums throughout the world in both undergraduate and graduate levels. However, students in general find this topic to be difficult subject due its theoretical and mathematical nature. This paper presents BiGO, a tool to support the students to understand and learn to analyze the time complexity of algorithms in rigorous manner. BiGO has four main features: i. it enables students to encode any given primitive recursive function with a specific scripting language in order to ii. automatically compute the upper bounds of the script and to, iii. visualize the behavior of the upper bounds in comparison to the most commonly occurring time complexity classes and, iv. view how long it takes for a computer to process the algorithm based on the different input values. This paper outlines the pedagogical goals of the tool and the system implementation architecture. Furthermore, we discuss future developmental plans for the tool and an evaluation within undergraduate and graduate level courses such as Data structures and algorithms and Design and analysis of algorithms.

Performance + InstructionVolume 31, Issue 7 p. 33-40 Series Performance-based instruction part 5: Evaluating Performance-Based Instruction Dale M. Brethower, Dale M. Brethower Dale, a professor/consultant and 20-year member of NSPI, has used performance technology successfully in manufacturing, retailing, and service environments (both public and private sector). His major emphasis is human learning: he has taught “Learning-to-Learn” to thousands of adult learners. He teaches graduate level courses in performance technology.Search for more papers by this authorKarolyn A. Smalley, Karolyn A. Smalley Karolyn, as Corporate Manager of Human Resource Development for Amway, directs a department that specializes in the development of performance systems and performance-based training. Her M.A. in I/O Psychology was earned at Western Michigan University. She is a founding member and Past-President of the Western Michigan Chapter of NSPI.Search for more papers by this author Dale M. Brethower, Dale M. Brethower Dale, a professor/consultant and 20-year member of NSPI, has used performance technology successfully in manufacturing, retailing, and service environments (both public and private sector). His major emphasis is human learning: he has taught “Learning-to-Learn” to thousands of adult learners. He teaches graduate level courses in performance technology.Search for more papers by this authorKarolyn A. Smalley, Karolyn A. Smalley Karolyn, as Corporate Manager of Human Resource Development for Amway, directs a department that specializes in the development of performance systems and performance-based training. Her M.A. in I/O Psychology was earned at Western Michigan University. She is a founding member and Past-President of the Western Michigan Chapter of NSPI.Search for more papers by this author First published: August 1992 https://doi.org/10.1002/pfi.4170310710 AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat Volume31, Issue7August 1992Pages 33-40 RelatedInformation

Stochastic models are everywhere. In manufacturing, queuing models are used for modeling production processes, realistic inventory models are stochastic in nature. Stochastic models are considered in transportation and communication. Marketing models use stochastic descriptions of the demands and buyer's behaviors. In finance, market prices and exchange rates are assumed to be certain stochastic processes, and insurance claims appear at random times with random amounts. To each decision problem, a cost function is associated. Costs may be direct or indirect, like loss of time, quality deterioration, loss in production or dissatisfaction of customers. In decision making under uncertainty, the goal is to minimize the expected costs. However, in practically all realistic models, the calculation of the expected costs is impossible due to the model complexity. Simulation is the only practicable way of getting insight into such models. Thus, the problem of optimal decisions can be seen as getting simulation and optimization effectively combined. The field is quite new and yet the number of publications is enormous. This book does not even try to touch all work done in this area. Instead, many concepts are presented and treated with mathematical rigor and necessary conditions for the correctness of various approaches are stated. Optimization of Stochastic Models: The Interface Between Simulation and Optimization is suitable as a text for a graduate level course on Stochastic Models or as a secondary text for a graduate level course in Operations Research.

This paper presents a realistic generator of power quality (PQ) disturbances developed using real time—hardware in the loop (RT‐HIL) technologies; the aim is to reduce the gap between the PQ mathematical theory and its practical application by improving the technical skills of students through the use of instruments in a controlled and safe laboratory environment. The implementation of this interactive teaching tool in a graduate level course has significantly enhanced the communication process between the teacher and students and thus, resulted in a highly effective teaching methodology. © 2014 Wiley Periodicals, Inc. Comput Appl Eng Educ 23:391–402, 2015; View this article online atwileyonlinelibrary.com/journal/cae; DOI10.1002/cae.21609

This essay details the experience of designing, implementing, and evaluating an online course in audience analysis at the graduate level. It describes efforts to create a quality learning experience, and discusses how the Web modules and listserv and MOO conversations influenced rituals of learning and communication.

How do children develop an understanding of people as psychological entities - as feeling, thinking beings? How do they come to understand human behavior as driven by desires and informed by reason? These questions are at the heart of contemporary research on children's "theories of mind." Although there has been an enormous amount of research on this topic, nobody - until now - has provided a coherent account that traces the development of theory of mind from birth to five years. This book begins by analyzing the nature of commonsense psychology and exploring the developmental processes relevant to its development. It then describes the manner in which the child moves from being a newborn with perceptual sensitivities to people, to an infant who can share psychological experiences with others, to a young child who can recognize people, including both self and others, as individual psychological beings. Finally, the book shows how, throughout this developmental process, the child's social interactive experiences are used by the child to generate ever more sophisticated forms of commonsense psychology. The Development of Commonsense Psychology incorporates material from a wide range of research on early development, including infant social interaction, joint attention, self development, language development, theory of mind, and autobiographical memory. Suitable as a text for senior undergraduate/honors courses or graduate level courses in early development, the primary audience for this book is developmental psychologists. However, it is also written in a way that will make it accessible and appealing to anyone with an interest in social cognitive development in early childhood, including parents, educators, and policymakers.