Embedded Files
12/6/18
The remaining topics were presented in class today.
12/4/18
Today, I observed seven more presentations.
11/29/18
I presented my research today on the discovery of the electron. There were a few other presentations too.
11/27/18
We ran some python script that changed images to deep dream versions of them.
11/20/18
We took the Homework Test.
11/15/18
We reviewed for the test and worked on Homework 9.
11/13/18
We started learning about Python and started working on Homework 9.
11/8/18
Today, we started Homework 8.
11/6/18
We worked on the computing of the homework.
11/1/18
We talked about simulation and Monte Carlo. Then, we worked on the computing part of the homework.
10/30/18
Today, we had a guest speaker, Dr. Erik Blaufuss who works on the IceCube Project.
10/25/18
Lab with Professor Dorland where we measured the spin of electrons.
10/23/18
Recapped all topics covered so far:
Standard Model
Fundamental Particles & Forces
Leptons
Quarks
Nuclear
EM
Higgs Boson
Relativity
Natural Units
Detectors
Accelerators
Linux
Root
C++
10/18/18
E, M, RF
E => accelerates (changes speed), increases E and V
M => changes direction
Cross Section => cross sectional area of the beam
=> Probability of interaction of a certain kind
L ~ f . N . N . 1/(4pi) . 1/(sigma2)
L => Luminosity
f => frequency
N => Number of protons
10/16/18
Today we learned about accelerators and watched videos on them.
10/11/18
Today there was a guest speaker named Chris Quigg from Fermilab.
10/9/18
We started off class by learning the basics about how detectors work and about the Large Hadron Collider.
FB = qVTBsin(theta)
FC = (mVT2)/R
FC = FB
10/4/18
Today we learned about particle interactions with matter
Computing:
Loops
10/2/18
Began learning C++
The main.cpp Program
"g++ main.cpp" tells the machine what how to compile the program
"./a.out" produces the output of "Hello World!"
Variables
Some Operations With Numbers
non-numeric values 1
9/27/18
We had a guess speaker who is a Decision Support Inter. Powerpoint: "Deepfakes" about "Photorealistic faceswaps using deep learning".
-Deepfakes is a method for generating realistic faceswap images/videos
-A deepfake is a faceswap produced by this method
Deepfakes Algorithm
-Getting datasets
-NN work by learning data, so we need datasets
-Can't feed regular pictures, too much noise
-We need to construct datasets with only faces
-Uses Histogram of Orientated Gradients
-Examines each pixel, compare to surrounding pixels
-Draw gradient vector from light to dark areas
-Histogram of oriented gradients for each sector
-Training Neural Network
-Autoencoders are a type of convolutional NN
-Able to convert a complex input to and from a compressed ("latent") form
-Composed of encoder (compresses) and decoder (decompresses)
-Original input > encoder > compressed representation > decoder > reconstructed input
-Used for denoising
-Uses strategic distortion to add effective diversity to our training set, we do not train directly on original data
-randomly warped, translate, zoomed, blurred, flipped
-Autoencoders become highly resistant to learning noise
-Conversion
-Frame-by-frame, extract faces with HOG, encode Face A, decode Face B, and swap Face B back in
Social Impact
-Social scientists and security experts speculate about a wide array of different application, some malicious
9/25/18
Briet Wigner - Peaks/Dist.
mass of proton = 940 MeV ~ 1 GeV (1/c2)
Rate of Events is proportional with 1/ ((E - M)2 + width/2)
(DELTA)E(DELTA)t >= h-bar
t = lifetime
1/lifetime ~ decay width
mass of w = 80 GeV
---------------------------------------------
Energey of proton = 7 TeV
mass of proton = 1 GeV
E2 - P2 = m2 c4
9/20/18
We had a guest speaker today named Maria Riaz, a software engineer at Google. Works for the Counter Abuse Technology's team. She gave a powerpoint presentation covering machine learning and related topics.
Powerpoint topics and information:
-Fundamental Question: "What can be (efficiently) automated?"
-Data growth is increasing exponentially.
-Machine learning is the act of teaching computers to recognize patterns. Getting closer to improving Artificial Intelligence.
-Over 600 companies are working towards improving machine learning.
-Enabling Factors for Machine Learning and related fields
-More Data
-Deep Learning
-Networking Infrastructure
-Advanced Algorithms
-Sensors
-Storage
-Faster Computing Resources
-Economic Trends
-ML Algorithms used for regression and classification
-Decision Tree
-Advanced Algorithms
-Deep Learning/Neural Networks
-Deep Neural Networks
-Classification and Labeling
-Hierarchical Learning
-Pixels
-1st layer "Edges"
-2nd layer "Object Parts"
-3rd layer "Objects"
-Applications
-Image Labeling
-Start with labeled pairs
-Predict new examples
-Computer Vision
-Voice Recognition
-Cognitive Computing
-Visual Search
-Geo-location
-Natural Language Processing
-Weather Prediction
-Classification
-Open Challenges in Data Science
-Technological Limitations
-Gap between expectation and reality
-Social Concerns
-Political and regulatory factors
-Shortage of talent
-Immaturity of the market
-Developing Insights From Data
-Questions
-"What am I measuring?"
-"Are observed patterns and relations in the data significant?"
-"Are they meaningful?"
-Empirical Analysis. Grounding in Theory
-"What are my hypotheses?"
-"What are the characteristics of my data?"
-"What algorithms / methodologies are useful for analyzing it?"
-Security and Privacy
-Concerns
-Hacking
-Account hijacking
-Health data breach
-credit card fraud
-identity theft
-Security
-Confidentiality
-Integrity
-ID & Authentication
-Privacy
-Principles and practices
-Regulations
-Counter Abuse Technologies
-Develop tools, techniques and infrastructure
9/18/18
I learned that mass and energy are measured in electron volts (eV). In terms of eV, both time and length are the same: 1/eV. C, h-bar bother = 1. I also started to work on Homework 3.
9/13/18
Started to learn more Linux commands, operators, etc.
'cd' change directory
'ls' list
'~' home directory
'mkdir' make directory
'rm' remove
'rmdir' remove directory
'touch' makes an empty file
'.' refers to current directory
'..' refers to the directory one level higher
'>' outputs to a file
'>>' output gets added to a file
'<' inputs from a file
'alias' used to make a short name for a command
'cp' copies a file
iSpy WebGL
Briefly played with the electron and photon files. I saw many colors and shapes that I am not entirely sure of their meaning.
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