A Neural Network Approach to Transistor Circuit Design

Transistor amplifier design is an important and fundamental concept in electronics, typically encountered by students at the junior level in electrical engineering. This paper focuses on two configurations that employ neural networks to design bipolar junction transistor circuits. The purpose of this work is to determine which design best fits the required parameters. Engineers often need to develop transistor circuits using a particular topology, e.g., common emitter, common collector, or common base. These also include a set of parameters including voltage gain, input impedance, and output impedance. For the most part, there are several methodologies that can provide a suitable solution, however the objective of this work is to indicate which external resistors are necessary to yield useful designs by employing neural networks. Here, a neural network has been trained to supply these component values for a particular configuration based on the aforementioned parameters. This should save a significant amount of work when evaluating a particular topology. And it should also permit experimentation with several designs, without having to perform detailed calculations

Surface contamination on LDEF exposed materials

X-ray photoelectron spectroscopy (XPS) has been used to study the surface composition and chemistry of Long Duration Exposure Facility (LDEF) exposed materials including silvered Teflon (Ag/FEP), Kapton, S13GLO paint, quartz crystal monitors (QCM's), carbon fiber/organic matrix composites, and carbon fiber/Al Alloy composites. In each set of samples, silicones were the major contributors to the molecular film accumulated on the LDEF exposed surfaces. All surfaces analyzed have been contaminated with Si, O, and C; most have low levels (less than 1 atom percent) of N, S, and F. Occasionally observed contaminants included Cl, Na, K, P, and various metals. Orange/brown discoloration observed near vent slots in some Ag/FEP blankets were higher in carbon, sulfur, and nitrogen relative to other contamination types. The source of contamination has not been identified, but amine/amide functionalities were detected. It is probable that this same source of contamination account for the low levels of sulfur and nitrogen observed on most LDEF exposed surfaces. XPS, which probes 50 to 100 A in depth, detected the major sample components underneath the contaminant film in every analysis. This probably indicates that the contaminant overlayer is patchy, with significant areas covered by less that 100 A of molecular film. Energy dispersive x-ray spectroscopy (EDS) of LDEF exposed surfaces during secondary electron microscopy (SEM) of the samples confirmed contamination of the surfaces with Si and O. In general, particulates were not observed to develop from the contaminant overlayer on the exposed LDEF material surfaces. However, many SiO2 submicron particles were seen on a masked edge of an Ag/FEP blanket. In some cases such as the carbon fiber/organic matrix composites, interpretation of the contamination data was hindered by the lack of good laboratory controls. Examination of laboratory controls for the carbon fiber/Al alloy composites showed that preflight contamination was the most significant factor for all the contaminants generally detected at less than 1 atom percent, or detected only occasionally (i.e., all but Si, O, and C). Flight control surfaces, including sample backsides not exposed to space radiation or atomic oxygen flux, have accumulated some contamination on flight (compared to laboratory controls), but experimentally, the LDEF exposed surface contamination levels are generally higher for the contaminants Si and O. For most materials analyzed, Si contamination levels were higher on the leading edge surfaces than on the trailing edge surfaces. This was true even for the composite samples where considerable atomic oxygen erosion of the leading edge surfaces was observed by SEM. It is probable that the return flux associated with atmospheric backscatter resulted in enhanced deposition of silicones and other contaminants on the leading edge flight surfaces relative to the trailing edge. Although the Si concentration data suggested greater on-flight deposition of contaminants on the leading edge surfaces, the XPS analyses did not conclusively show different relative total thicknesses of flight deposited contamination for leading and trailing edge surfaces. It is possible that atomic oxygen reactions on the leading edge resulted in greater volatilization of the carbon component of the deposited silicones, effectively 'thinning' the leading edge deposited overlayer. Unlike other materials, exposed polymers such as Kapton and FEP-type Teflon had very low contamination on the leading edge surfaces. SEM evidence showed that undercutting of the contaminant overlayer and damaged polymer layers occurred during atomic oxygen erosion, which would enhance loss of material from the exposed surface

Maine’s Homeless Families: An Interview with Helen Hemminger

Since 1991 Helen Hemminger has been director of The Tedford Shelter, a homeless shelter serving adults and families in the Brunswick, Maine area. In this interview, Hemminger provides a first- hand account of Maine’s changing homeless population. The good news, she reports, is that the percentage of people with mental illnesses staying at the shelter has gone down. The bad news is that since 1994 the shelter has experienced a steady increase in the number of homeless families. As Hemminger notes, there are more Maine families today working very hard to make ends meet. Living on a precarious edge, one setback—like temporary unemployment or a health problem—can put them over the edge and, literally, on the streets. Hemminger provides her thoughts on how best to help this growing, vulnerable population

The Criminalization of Education: Combating the School-To-Prison Pipeline through Disciplinary Policy and Social Change

This thesis builds on previous literature about the implications of zero tolerance policies, policing in schools, and the school-to-prison pipeline. I evaluate the evolution of disciplinary policies within public school districts since the abandoning of zero tolerance. Specifically, I use the Schenectady and Niskayuna districts and apply theories about discipline, class, race, and achievement to evaluate and compare the ways in which the school-to-prison pipeline and disciplinary policies function. Through a series of case studies, I found that both schools, like many others, have taken significant steps towards moving away from criminalizing and punitive disciplinary measures. However, because of the inherent challenges urban districts like Schenectady face, their struggle with the school-to-prison pipeline is more advanced, and, therefore, their changes to their codes of conduct are more complex. My research attempts to fill a gap due to lack of research conducted on these relatively new disciplinary practices and alternative approaches towards handling behavioral issues. Overall, alternatives and practices like restorative justice, transformative justice, and implicit bias and trauma-sensitive training seem to be most effective. I make more detailed suggestions as to which methods seem to work best, and how they are carried out based on my evaluations of each district and the limited findings of other scholars thus far

Using Neural Networks to Design Transistor Amplifier Circuits

This paper is an extension of previous work that addressed the application of bipolar transistor amplifier design using neural networks That work addressed the design of common emitter amplifiers by first mathematically determining specific output parameters from a large selection of biasing resistors Once the outputs had been determined a neural network was trained using the aforementioned results as inputs and the biasing resistors as outputs This was initially performed with ideal emitter bypass capacitors but was then followed-up by employing several non-ideal capacitors making it much more interesting and useful This paper focuses on the common collector and the common base configurations Bipolar junction transistor amplifier parameters often include voltage gain input impedance output impedance and the voltage difference between the collector and emitter These will be addressed in this paper as before There are several methods that can provide a suitable solution for each design however the objective of this work is to indicate which external resistors are necessary to yield useful results by employing neural network