
ECE 695A Lecture 29R: Review Questions
08 Apr 2013  Online Presentations  Contributor(s): Muhammad Alam
Review Questions:Mention a few differences between thick and thin oxide breakdown.Is breakdown in thick oxides contact dominated? Can I use AHI theory here?How does the Paschen’s cascade initiate?What does it mean to have a fractal dimension of 1.7 for 2D breakdown? Why does the number suggest...

ECE 695A Lecture 30: Breakdown in Dielectrics with Defects
08 Apr 2013  Online Presentations  Contributor(s): Muhammad Alam
Outline:IntroductionTheory of preexisting defects: Thin oxidesTheory of preexisting defects: thick oxidesConclusions

ECE 695A Lecture 30R: Review Questions
08 Apr 2013  Online Presentations  Contributor(s): Muhammad Alam
Outline:What is the difference between extrinsic vs. intrinsic breakdown?Does gas dielectric have extrinsic breakdown? Why or why not?What does ESD damage and the plasma damage to thin oxides?Can you explain the physical meaning of infant mortality ? How does it relate to yield of semiconductor...

ECE 595E Lecture 30: Applications of CAMFR
08 Apr 2013  Online Presentations  Contributor(s): Peter Bermel

Dataadaptive Filtering and the State of the Art in Image Processing
15 Apr 2013  Online Presentations  Contributor(s): Peyman Milanfar
In this talk, I will present a practical and unified framework for understanding some common underpinnings of these methods. This leads to new insights and a broad understanding of how these diverse methods interrelate. I will also discuss the statistical performance of the resulting algorithms,...

Random Forest Model Objects for Pulmonary Toxicity Risk Assessment
17 Apr 2013  Downloads  Contributor(s): Jeremy M Gernand
This download contains MATLAB treebagger or Random Forest (RF) model objects created via metaanalysis of nanoparticle rodent pulmonary toxicity experiments. The ReadMe.txt file contains object descriptions including output definitions, input parameter descriptions, and applicable limits.

ECE 595E Lecture 32: Simulations of Coupled Mode Theory Simulation (CMT)
12 Apr 2013  Online Presentations  Contributor(s): Peter Bermel
Outline:Recap from FridayNumerical ODE solversInitial value problemsBoundary value problemsnanoHUB Tool – CMTcomb3:RationaleGoverning ODEsUser interfaceOutput analysis

ECE 595E Lecture 33: Introduction to FiniteDifference TimeDomain Simulations
12 Apr 2013  Online Presentations  Contributor(s): Peter Bermel
Outline:Recap from MondayIntroduction to FDTDSpecial features of MEEP:Perfectly matched layersSubpixel averagingSymmetryScheme (programmable) interfaceExamples:Periodic lighttrapping structuresRandomly textured structures

ECE 595E Lecture 34: Applications of FiniteDifference TimeDomain Simulations
18 Apr 2013  Online Presentations  Contributor(s): Peter Bermel
Outline:Recap from WednesdayPeriodic and randomly textured lighttrapping structuresOverviewExperimental motivationComputational setupSimulated field evolutionAbsorption spectraFront coatingsCorrelated random structures

ECE 595E Lecture 35: MEEP Tutorial I
18 Apr 2013  Online Presentations  Contributor(s): Peter Bermel
Outline:MEEP InterfacesMEEP ClassesTutorial examples:WaveguideBent waveguide

ECE 595E Lecture 36: MEEP Tutorial II
30 Apr 2013  Online Presentations  Contributor(s): Peter Bermel
Outline:Recap from MondayExamplesMultimode ring resonatorsIsolating individual resonancesKerr nonlinearitiesQuantifying thirdharmonic generation

ECE 695A Lecture 31: Collecting and Plotting Data
15 Apr 2013  Online Presentations  Contributor(s): Muhammad Alam
Outline:Origin of data, Field Acceleration vs. Statistical InferenceNonparametric informationPreparing data for projection: Hazen formula Preparing data for projection: Kaplan formulaConclusion

ECE 695A Lecture 31A: Appendix  Bootstrap Method Introduction
15 Apr 2013  Online Presentations  Contributor(s): Muhammad Alam

ECE 695A Lecture 31R: Review Questions
15 Apr 2013  Online Presentations  Contributor(s): Muhammad Alam
Review Questions:What is the difference between parametric estimation vs. nonparametric estimation?What principle did Tacho Brahe’s approach assume?What is the difference between population and sample? When we collect data for TDDB or NBTI, what type of data are we collecting?What problem does...

ECE 695A Lecture 32: Physical vs. Empirical Distribution
17 Apr 2013  Online Presentations  Contributor(s): Muhammad Alam
Outline:Physical Vs. empirical distributionProperties of classical distribution functionMomentbased fitting of dataConclusions

ECE 695A Lecture 32R: Review Questions
17 Apr 2013  Online Presentations  Contributor(s): Muhammad Alam
Review Questions:Why do people use Normal, lognormal, Weibull distributions when they do not know the exact physical distribution?What is the problem of using empirical distributions? What are the advantages?If you must choose an empirical distribution, what should be your criteria? (Nos. of...

Integrated Imaging Seminar Series
30 Apr 2013  Series  Contributor(s): Charles Addison Bouman
Integrated imaging seminar series is jointly sponsored by the Birck Nanotechnology Center and ECE. Integrated Imaging is defined as a crossdisciplinary field combining sensor science, information processing, and computer systems for the creation of novel imaging and sensing systems. In this...

Buckypaper
17 Apr 2013  Presentation Materials  Contributor(s): shaheen goel
the presentation gives a basic idea about the buckypaper and give breif details about the synthesis properties and applications of buckypaper

ECE 695A Lecture 33: Model Selection/Goodness of Fit
18 Apr 2013  Online Presentations  Contributor(s): Muhammad Alam
Outline:The problem of matching data with theoretical distributionParameter extractions: Moments, linear regression, maximum likelihoodGoodness of fit: Residual, Pearson, Cox, AkikaConclusion

ECE 695A Lecture 33R: Review Questions
18 Apr 2013  Online Presentations  Contributor(s): Muhammad Alam
Review Questions:With higher number of model parameters, you can always get a good fit – why should you minimize the number of parametersLeast square method is a subset of maximum likelihood approach to data fitting. Is this statement correct?What aspect of the distribution function does...