THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

The Design and Analysis of Experiments

Neuromorphic computing has come to refer to a variety of brain-inspired computers, devices, and models that contrast the pervasive von Neumann computer architecture This biologically inspired approach has created highly connected synthetic neurons and synapses that can be used to model neuroscience theories as well as solve challenging machine learning problems The promise of the technology is to create a brain-like ability to learn and adapt, but the technical challenges are significant, starting with an accurate neuroscience model of how the brain works, to finding materials and engineering breakthroughs to build devices to support these models, to creating a programming framework so the systems can learn, to creating applications with brain-like capabilities In this work, we provide a comprehensive survey of the research and motivations for neuromorphic computing over its history We begin with a 35-year review of the motivations and drivers of neuromorphic computing, then look at the major research areas of the field, which we define as neuro-inspired models, algorithms and learning approaches, hardware and devices, supporting systems, and finally applications We conclude with a broad discussion on the major research topics that need to be addressed in the coming years to see the promise of neuromorphic computing fulfilled The goals of this work are to provide an exhaustive review of the research conducted in neuromorphic computing since the inception of the term, and to motivate further work by illuminating gaps in the field where new research is needed

A Survey of Neuromorphic Computing and Neural Networks in Hardware.

Fabrication of monolithic lattice-mismatched semiconductor heterostructures with limited area regions having upper portions substantially exhausted of threading dislocations, as well as fabrication of semiconductor devices based on such lattice-mismatched heterostructures.

Lattice-Mismatched Semiconductor Structures with Reduced Dislocation Defect Densities and Related Methods for Device Fabrication

Asynchronous Circuit Design

Defect-free germanium has been demonstrated in SiO2 trenches on silicon via Aspect Ratio Trapping, whereby defects arising from lattice mismatch are trapped by laterally confining sidewalls. Results were achieved through a combination of conventional photolithography, reactive ion etching of SiO2, and selective growth of Ge as thin as 450nm. Full trapping of dislocations originating at the Ge∕Si interface has been demonstrated for trenches up to 400nm wide without the additional formation of defects at the sidewalls. This approach shows great promise for the integration of Ge and/or III-V materials, sufficiently large for key device applications, onto silicon substrates.

Defect reduction of selective Ge epitaxy in trenches on Si(001) substrates using aspect ratio trapping

This paper presents the implementation and outcomes of a hands-on laboratory course in microelectromechanical systems (MEMS), co-developed by a multidisciplinary team of faculty from mechanical engineering, electrical engineering, and materials engineering. Central to the design of the course is an emphasis on implementing modules that are able to overcome critical barriers related to (1) diverse academic background from different majors and (2) practical limitations in microfabrication facilities. These points are vital for promoting MEMS education, because they expand the student pool and reach audiences that need a cost-effective way to support instructional laboratory experiences in MEMS without the broader infrastructure that is often limited only to large research institutions. Laboratory projects emphasize skills in design, fabrication, and testing, while a classroom lecture portion of the course provides corresponding background theory. The paper provides technical description of three modular projects that have been implemented in the course. These encompass a variety of MEMS fabrication approaches, including surface micromachining, bulk micromachining, and soft lithography. These distinct methods are exercised in three corresponding devices: a silicon pressure sensor, an aluminum suspended beam, and a polymer microfluidic chip. These projects illustrate principles and reinforce student learning of important phenomena commonly involved in MEMS, such as piezoresistivity, electrostatics, stiction, residual stress, and electrokinetics. The modules are arranged with different levels of emphasis among design, fabrication, and testing, to reach higher levels of Bloom’s Taxonomy while simultaneously balancing time and resource constraints in a practical manner. Feedback from student opinions and plans for improvement are also presented.

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Implementation of a MEMS Laboratory Course with Modular, Multidisciplinary Team Projects

A circuit has been designed to control the temperature of the IC die upon which it resides. No special devices or layers are required. No external circuitry or special heat sinking is used. Equilibrium temperatures from below -40/spl deg/C to above +85/spl deg/C are attainable. Time to equilibrium is on the order of a few seconds. The 400/spl mu/m /spl times/ 500/spl mu/m circuit has been manufactured by the MOSIS service in a TSMC 0.25 micron process and installed in a 40-pin DIP package. Test results reveal temperature regulation within 0.3/spl deg/C for thermal control ranges of 4/spl deg/C to 40/spl deg/C.

On-chip temperature control circuit using common devices

Educational Modules Based on Semiconductor Manufacturing for Teaching Statistical Concepts

In this work, which is intended to be a Work in Progress Paper in the Research Category, a pilot study of a directed self-placement exam and a workshop designed to lower the DFW rate (% of students who earn a D, F, or W) is presented. Linear regression models that included the directed self-placement exam score, differential equations grade, introduction to circuit analysis grade, and prior GPA were created, and the four-factor model, best three-factor model, best two-factor model, and the individual factor models are presented. The most cost-effective model in terms of significance (less than 0.001) and R2 (0.48) values was a two-factor model that included the introduction to circuit analysis grade, and prior GPA. This suggests that the directed self-placement exam is not needed to predict student success in the author’s circuits and systems course.

A pilot study of a directed self-placement exam and a workshop designed to improve student learning outcomes in a junior level circuits and signals course

In this work, which is intended to be a Work in Progress Paper in the Research Category, the results of an extensive study which used three-factor and two-factor linear regression models based on prior grade point average, grades in a pre-requisite physics course, and class size is presented. In both models prior GPA was the most significant factor in predicting student success, followed by the grade in a prerequisite physics course. Even though class size was not a significant factor, removing it from the analysis lowered the R2 values. The study analyzed 39 sections of an introduction to circuit analysis course from fall 2013 to spring 2018 and examined whether previously published novel treatments or class size (or both) were the reason for increased pass rates. It was found that there were no significant entry behavior differences between those students who enrolled in a traditional course vs. the students enrolled in a directed self-placement course. It was found that the sections that used the directed self-placement policy tended to outperform sections that did not use this policy.

David W Parent

Papers

Implementation of a MEMS Laboratory Course with Modular, Multidisciplinary Team Projects

On-chip temperature control circuit using common devices

Educational Modules Based on Semiconductor Manufacturing for Teaching Statistical Concepts

A pilot study of a directed self-placement exam and a workshop designed to improve student learning outcomes in a junior level circuits and signals course

A study of student entry behaviors and directed self-placement in an introduction to circuit analysis course