Statistics
Here you can see statistics about the JVM (Java Virtual Machine) settings and parameters as well as the computation that
is currently being processed.
Updating every ? second(s).
Maximum Graph Size Estimation
Here we try to estimate how large a data set might be at most to still be processable by your current infrastructure.
This estimation, however, is quite vague and should not be taken for granted.
Logs
These are logging messages the system emitted while processing your data set. You can filter the messages
according to their source and log level by using the following buttons:
Computation does not seem to start
When a computation does not seem to start, it might have crashed. The log messages below might indicate such a problem.
However, as long as the charts below are still updating, a crash is unlikely. In such cases, the graph might take a lot
of time to load. You can observe the graph loading stage by having a look at the charts regarding the infrastructure.
Computation does not converge
When a computation does not converge, there might be cyclic signal and collect messages so that it might never
converge. You can observe the charts below to see whether there are any messages sent or received. We also show CPU time
and load to investigate whether the node(s) is calculating anything. Additionally,
you could observe
the graph with a state visualization.
Computation crashes
A computation can crash for various reasons. There might be a problem in the the code (e.g. a
NullPointerException
) in which case you might see an error message in the list of log messages below.
Another reason for a crash could be an infrastructure that is too weak to process the current data set. In this case, you might
see an error message as well but could also observe the memory usage in the charts below.
A further reason for a crashed computation might by that an OutOfMemory exception occurred. You may observe that by
looking at the "Max Memory" and "Total Memory" charts below.
Computation takes very long
A computation on a large data set, or even a complex computation on a small data set, might take hours,
days or even longer to compute. Please be patient. However, there might be other reasons that a computation takes very
long. First, not every computation
converges at all. Second, a high CPU usage shows that the computation is still running and you have to wait for it to
end.
Node Charts
Here you can view all node charts that are generated and updated while processing your data. The different colors of the lines
represent the minimum, average, and
maximum values over all nodes. You can hover the lines to get more information.
Worker Charts
Here you can view all worker charts that are generated and updated while processing your data. The different colors of the lines
represent the minimum, average, and
maximum values over all workers. You can hover the lines to get more information.
+
«·»
-
Signal/Collect
Infrastructure
Log Messages
Computation
- Start Time: ?
- Running for (not accurate when stepping): 0
- Status: waiting
- Number of Workers: ?
- Execution Mode: ?
- Global Termination Condition: ?
- Steps Limit: ?
- Time Limit: ?
- Signal Threshold: ?
- Collect Threshold: ?
Graph Size Estimation
Waiting for more data.


doit - Script to run various performance runs
./doit [OPTIONS] [VERSIONS]
This script uses a specified simulator (default Mentor questa) to run UVM objections performance testing. Default is to raise and lower objections millions of times and report the overall CPU time.
-1 single test -A # agents -B 0|1 bfm (driver/monitor) objections -C # count -h help -I # infos -L # levels of hierarchy in agent -M 0|1 monitor in/active -n not really -o objection tracing -p # pause # seconds between simulations -P 0|1 propagate objections up hierarchy -q quiet -R LIST run-lengths of transactions -S 0|1 shape wide|narrow -t TAG part of logfile name -U 0|1 use short|full sequence -V LIST vendor list -v verbose -W # warnings -X # context switching choice
Run a single test (pipe cleaner).
Number of agents to instantiate
Specify whether to use BFM objections.
Number of times to repeat inner loop
Display this help.
Number of info messages to display
Number of levels of hierarchy above drivers
Specify whether to use the monitor.
Not really
Turn-on objection tracing
Seconds to delay between simulations (minimum 5)
Propagate objections or not (affects 1.2 and above only)
Quiet mode to suppress unnecessary output.
Specify transaction length to use. This has a special format using one hex digit for each driver. Example: 3_2_1 means a length of 3ps for driver 2, 2ps for driver 1, and 1ps for driver 0. Unspecified drivers get a value of 1ps.
Specify the shape to use: {SHAPE_WIDE=0, SHAPE_NARROW=1}
Specify a TAG to include in log file name.
Specify whether to use a full sequence (1) or a short 1ps sequence.
Specify vendor (or simulator) to use.
Verbose mode to expand explanatory output.
Number of warning messages to display
Specify context switching choice.
Supported UVM versions are:
Copyright (C) 2014 Doulos Inc. All rights reserved.
David C Black <david.black@doulos.com>


This project aims to create badges that helps in making research reproducible. That is, the badges will explain the state of any component (for example data, code and articles) in a research so that it can be understood by others when they have a look at it later and possibly even build upon it. The badges aim to display the state of key factors about the research such that the output is very evident and presented right at the face of it.
The results are presented in an interactive manner that gives the display of the badge an even better meaning. The results are provided with a certain colored background which depends on the type of output. For example a positive result is shown with a green color, a negative result is shown with a red color and intermediate results are sometimes in yellow or orange color, again depending upon the specific type of outcome.
In this project key aspects about a research that a user is interested in knowing are represented evidently on the badges. For example a user might want to know if a research is peer-reviewed or not, in order to get an idea about the quality of the research. Similarly a user might also be interested to know about the licensing or the executibility of a code in a research. These important factors along with some more are displayed on the badges along with their results.
Nowadays, we get into contact with badges nearly everyday, e.g in software development communities (see: shields.io) and digital learning (see: openbadges.org) Badges provide a concise, recognizable yet useful piece of information, such as the build state or the number of downloads.
There is a part of the API that is the same for every task. That base part is as following:
/api/1.0/badge
The rest of the API is case dependent. The structure would be dependent on the name of the task, platform from which metadata of a research is taken, the id for calling a particular research compendium and a final addition which is optional in case you want to request a big badge, is the keyword "extended". Example APIs are provided below:
This is an example from the licensing task:
/api/1.0/badge/licence/id/extended (returns a big badge)
/api/1.0/badge/licence/id (returns a small badge)
This is an example from the executibility task:
/api/1.0/badge/executable/id/extended (returns a big badge)
/api/1.0/badge/executable/id (returns a small badge)
The extender is part of the o2r project, a DFG-funded research project. It aims to improve reproducibility in modern research. You can find more about the project here.
Here you can find the link to the current GitHub repository of the o2r extender. For feedback and suggestions, feel free to create a Github issue.This study project was realized at the Institute for Geoinformatics (ifgi) at the University of Münster under the supervision of Daniel Nüst during the winter term 2016/17. The participants of the project team are: Antonia van Eek, Clara Rendel, Lasse Einfeldt, Laura Meierkort, Marlena Götza, Salman Khalid, Shahzeib Tariq Jaswal, Nimrod Gavish, Matthias Mohr and Daniel Nüst.
The extender is an open source project and licensed under [Apache License 2.0](https://www.apache.org/licenses/LICENSE-2.0).


---
layout: archive
title: Lean Prover Zulip Chat Archive
permalink: 113489newmembers/92415CDeditorwithLeanprooflogic.html
---
The archive URL format has changed. Please find this page at:
https://leanprover-community.github.io/archive/stream/113489-new-members/topic/CD.20editor.20with.20Lean.20proof.20logic.html


DEBCONF-APT-PROGRESS(1) Debconf DEBCONF-APT-PROGRESS(1) NAME debconf-apt-progress - install packages using debconf to display a progress bar SYNOPSIS debconf-apt-progress [--] command [args ...] debconf-apt-progress --config debconf-apt-progress --start debconf-apt-progress --from waypoint --to waypoint [--] command [args ...] debconf-apt-progress --stop DESCRIPTION debconf-apt-progress installs packages using debconf to display a progress bar. The given command should be any command-line apt frontend; specifically, it must send progress information to the file descriptor selected by the "APT::Status-Fd" configuration option, and must keep the file descriptors nominated by the "APT::Keep-Fds" configuration option open when invoking debconf (directly or indirectly), as those file descriptors will be used for the debconf passthrough protocol. The arguments to the command you supply should generally include -y (for apt-get or aptitude) or similar to avoid the apt frontend prompting for input. debconf-apt-progress cannot do this itself because the appropriate argument may differ between apt frontends. The --start, --stop, --from, and --to options may be used to create a progress bar with multiple segments for different stages of installation, provided that the caller is a debconf confmodule. The caller may also interact with the progress bar itself using the debconf protocol if it so desires. debconf locks its config database when it starts up, which makes it unfortunately inconvenient to have one instance of debconf displaying the progress bar and another passing through questions from packages being installed. If you're using a multiple-segment progress bar, you'll need to eval the output of the --config option before starting the debconf frontend to work around this. See "EXAMPLES" in the EXAMPLES section below. OPTIONS --config Print environment variables necessary to start up a progress bar frontend. --start Start up a progress bar, running from 0 to 100 by default. Use --from and --to to use other endpoints. --from waypoint If used with --start, make the progress bar begin at waypoint rather than 0. Otherwise, install packages with their progress bar beginning at this "waypoint". Must be used with --to. --to waypoint If used with --start, make the progress bar end at waypoint rather than 100. Otherwise, install packages with their progress bar ending at this "waypoint". Must be used with --from. --stop Stop a running progress bar. --no-progress Avoid starting, stopping, or stepping the progress bar. Progress messages from apt, media change events, and debconf questions will still be passed through to debconf. --dlwaypoint percentage Specify what percent of the progress bar to use for downloading packages. The remainder will be used for installing packages. The default is to use 15% for downloading and the remaining 85% for installing. --logfile file Send the normal output from apt to the given file. --logstderr Send the normal output from apt to stderr. If you supply neither --logfile nor --logstderr, the normal output from apt will be discarded. -- Terminate options. Since you will normally need to give at least the -y argument to the command being run, you will usually need to use -- to prevent that being interpreted as an option to debconf-apt- progress itself. EXAMPLES Install the GNOME desktop and an X window system development environment within a progress bar: debconf-apt-progress -- aptitude -y install gnome x-window-system-dev Install the GNOME, KDE, and XFCE desktops within a single progress bar, allocating 45% of the progress bar for each of GNOME and KDE and the remaining 10% for XFCE: #! /bin/sh set -e case $1 in '') eval "$(debconf-apt-progress --config)" "$0" debconf ;; debconf) . /usr/share/debconf/confmodule debconf-apt-progress --start debconf-apt-progress --from 0 --to 45 -- apt-get -y install gnome debconf-apt-progress --from 45 --to 90 -- apt-get -y install kde debconf-apt-progress --from 90 --to 100 -- apt-get -y install xfce4 debconf-apt-progress --stop ;; esac RETURN CODE The exit code of the specified command is returned, unless the user hit the cancel button on the progress bar. If the cancel button was hit, a value of 30 is returned. To avoid ambiguity, if the command returned 30, a value of 3 will be returned. AUTHORS Colin Watson<EMAIL_ADDRESS>Joey Hess<EMAIL_ADDRESS>2012-09-10 DEBCONF-APT-PROGRESS(1)


ProbAnno (Probabilistic Annotation) is a method for annotating each protein sequence in a proteome based on similarity to proteins of known function in other organisms, and assigning a probability to each annotation.
This web service, created by Terry Farrah and Brendan King. The code for the probabilistic annotation algorithm, ProbAnno-Standalone, can be downloaded and run independently, and is also available as a python package probannopy


| Rank | Player | TEAM | GP | GS | MINS | G | A | S | SOG | FC | OFF | CK | PKA | PKG | YC | RC | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 |
Lynn Williams |
WNY | 19 | 19 | 1671 | 11 | 5 | 72 | 35 | 16 | 18 | 0 | 0 | 0 | 0 | 0 | |
| 2 |
Kealia Ohai |
HOU | 20 | 18 | 1626 | 11 | 3 | 43 | 29 | 12 | 30 | 6 | 0 | 0 | 0 | 0 | |
| 3 |
Jessica McDonald |
WNY | 19 | 19 | 1665 | 10 | 7 | 50 | 29 | 12 | 14 | 0 | 0 | 0 | 0 | 0 | |
| 4 |
Nadia Nadim |
POR | 20 | 20 | 1649 | 9 | 3 | 32 | 15 | 36 | 20 | 13 | 4 | 4 | 4 | 0 | |
| 5 |
Shea Groom |
KC | 19 | 19 | 1660 | 8 | 0 | 50 | 25 | 28 | 18 | 0 | 1 | 0 | 1 | 1 | |
| 6 |
Christen Press |
CHI | 14 | 14 | 1260 | 8 | 0 | 56 | 32 | 16 | 15 | 0 | 1 | 1 | 0 | 0 | |
| 7 |
Manon Melis |
SEA | 16 | 15 | 1051 | 7 | 1 | 29 | 21 | 7 | 5 | 0 | 0 | 0 | 0 | 0 | |
| 8 |
Sofia Huerta |
CHI | 20 | 20 | 1742 | 7 | 2 | 39 | 16 | 21 | 13 | 1 | 0 | 0 | 2 | 0 | |
| 9 |
Kim Little |
SEA | 20 | 20 | 1795 | 6 | 2 | 27 | 16 | 17 | 5 | 13 | 3 | 3 | 0 | 0 | |
| 10 |
Christine Sinclair |
POR | 11 | 10 | 826 | 6 | 2 | 17 | 12 | 6 | 7 | 0 | 0 | 0 | 0 | 0 | |
| 11 |
Allie Long |
POR | 15 | 15 | 1350 | 6 | 2 | 25 | 13 | 20 | 2 | 3 | 0 | 0 | 0 | 0 | |
| 12 |
Kristen Edmonds |
ORL | 19 | 19 | 1701 | 6 | 2 | 23 | 13 | 13 | 1 | 41 | 0 | 0 | 1 | 0 | |
| 13 |
Carli Lloyd |
HOU | 7 | 7 | 553 | 5 | 3 | 26 | 12 | 4 | 7 | 3 | 1 | 1 | 0 | 0 | |
| 14 |
Lianne Sanderson |
WNY | 17 | 11 | 1120 | 5 | 1 | 20 | 13 | 10 | 3 | 19 | 0 | 0 | 0 | 0 | |
| 15 |
Samantha Mewis |
WNY | 14 | 14 | 1260 | 5 | 2 | 37 | 14 | 19 | 1 | 4 | 2 | 1 | 1 | 0 | |
| 16 |
Dagný Brynjarsdóttir |
POR | 17 | 12 | 1072 | 5 | 0 | 11 | 8 | 27 | 3 | 1 | 0 | 0 | 1 | 0 | |
| 17 |
Lindsey Horan |
POR | 15 | 15 | 1304 | 5 | 0 | 25 | 16 | 23 | 6 | 3 | 0 | 0 | 4 | 0 | |
| 18 |
Estefanía Banini |
WAS | 13 | 9 | 887 | 5 | 1 | 16 | 10 | 4 | 0 | 0 | 0 | 0 | 0 | 0 | |
| 19 |
Sam Kerr |
NJ | 9 | 6 | 616 | 5 | 0 | 20 | 12 | 5 | 6 | 1 | 0 | 0 | 0 | 0 | |
| 20 |
Alex Morgan |
ORL | 15 | 15 | 1350 | 4 | 1 | 37 | 18 | 11 | 11 | 1 | 0 | 0 | 1 | 0 | |
| 21 |
Jasmyne Spencer |
ORL | 20 | 17 | 1564 | 4 | 0 | 29 | 19 | 14 | 8 | 0 | 0 | 0 | 3 | 0 | |
| 22 |
Katie Stengel |
WAS | 19 | 10 | 929 | 4 | 1 | 17 | 8 | 2 | 9 | 1 | 0 | 0 | 0 | 0 | |
| 23 |
Diana Matheson |
WAS | 12 | 9 | 799 | 4 | 0 | 10 | 8 | 4 | 3 | 22 | 1 | 1 | 1 | 0 | |
| 24 |
Rachel Daly |
HOU | 16 | 12 | 1186 | 4 | 3 | 29 | 14 | 23 | 25 | 1 | 0 | 0 | 2 | 0 | |
| 25 |
Joanna Lohman |
WAS | 20 | 17 | 1538 | 4 | 1 | 25 | 15 | 29 | 0 | 1 | 0 | 0 | 1 | 0 | |
| 26 |
Natasha Kai |
NJ | 20 | 17 | 1401 | 4 | 1 | 33 | 18 | 17 | 27 | 0 | 0 | 0 | 3 | 0 | |
| 27 |
Nahomi Kawasumi |
SEA | 10 | 8 | 750 | 3 | 2 | 11 | 8 | 0 | 10 | 14 | 0 | 0 | 0 | 0 | |
| 28 |
Natasha Dowie |
BOS | 7 | 7 | 605 | 3 | 0 | 19 | 10 | 12 | 11 | 0 | 0 | 0 | 1 | 0 | |
| 29 |
Christine Nairn |
WAS | 20 | 18 | 1618 | 3 | 3 | 29 | 11 | 8 | 1 | 87 | 2 | 1 | 1 | 0 | |
| 30 |
Cheyna Williams |
WAS | 17 | 8 | 780 | 3 | 0 | 16 | 9 | 10 | 9 | 0 | 0 | 0 | 1 | 0 | |
| 31 |
Janine Beckie |
HOU | 14 | 11 | 917 | 3 | 2 | 16 | 7 | 6 | 6 | 0 | 0 | 0 | 0 | 0 | |
| 32 |
Sarah Killion |
NJ | 18 | 18 | 1606 | 3 | 1 | 10 | 7 | 15 | 1 | 22 | 4 | 3 | 0 | 0 | |
| 33 |
Makenzy Doniak |
WNY | 20 | 15 | 1141 | 3 | 4 | 14 | 10 | 8 | 5 | 4 | 0 | 0 | 1 | 0 | |
| 34 |
Yael Averbuch |
KC | 20 | 20 | 1788 | 3 | 0 | 17 | 9 | 18 | 0 | 4 | 1 | 1 | 1 | 0 | |
| 35 |
Maya Hayes |
NJ | 16 | 8 | 749 | 3 | 0 | 10 | 6 | 6 | 6 | 1 | 0 | 0 | 0 | 0 | |
| 36 |
Leah Galton |
NJ | 14 | 10 | 1022 | 3 | 4 | 16 | 9 | 10 | 11 | 11 | 0 | 0 | 1 | 0 | |
| 37 |
Beverly Yanez |
SEA | 20 | 18 | 1543 | 3 | 3 | 22 | 14 | 10 | 11 | 1 | 0 | 0 | 0 | 0 | |
| 38 |
Stephanie McCaffrey |
CHI | 18 | 15 | 1276 | 2 | 0 | 19 | 10 | 12 | 14 | 3 | 0 | 0 | 0 | 0 | |
| 39 |
Abby Dahlkemper |
WNY | 20 | 20 | 1800 | 2 | 1 | 10 | 5 | 15 | 1 | 58 | 2 | 2 | 2 | 0 | |
| 40 |
Taylor Smith |
WNY | 18 | 5 | 725 | 2 | 0 | 11 | 4 | 11 | 0 | 2 | 0 | 0 | 1 | 0 | |
| 41 |
Julie King |
BOS | 18 | 17 | 1524 | 2 | 1 | 9 | 5 | 19 | 2 | 1 | 0 | 0 | 5 | 0 | |
| 42 |
Crystal Dunn |
WAS | 13 | 12 | 1140 | 2 | 5 | 30 | 11 | 14 | 12 | 1 | 0 | 0 | 0 | 0 | |
| 43 |
Tiffany McCarty |
KC | 16 | 10 | 916 | 2 | 4 | 14 | 4 | 18 | 13 | 0 | 0 | 0 | 0 | 0 | |
| 44 |
Francisca Ordega |
WAS | 13 | 7 | 630 | 2 | 1 | 9 | 6 | 15 | 8 | 0 | 0 | 0 | 1 | 0 | |
| 45 |
Abby Erceg |
WNY | 17 | 16 | 1474 | 2 | 1 | 11 | 3 | 26 | 1 | 0 | 0 | 0 | 0 | 1 | |
| 46 |
Frances Silva |
KC | 19 | 10 | 990 | 2 | 0 | 13 | 4 | 16 | 3 | 1 | 0 | 0 | 1 | 0 | |
| 47 |
Casey Short |
CHI | 20 | 20 | 1781 | 2 | 0 | 14 | 7 | 12 | 1 | 0 | 0 | 0 | 0 | 0 | |
| 48 |
Jennifer Hoy |
CHI | 15 | 9 | 673 | 2 | 0 | 5 | 3 | 7 | 11 | 0 | 0 | 0 | 1 | 0 | |
| 49 |
Denise O'Sullivan |
HOU | 18 | 14 | 1313 | 2 | 5 | 18 | 6 | 13 | 1 | 2 | 0 | 0 | 1 | 0 | |
| 50 |
Sarah Hagen |
ORL | 17 | 8 | 588 | 2 | 2 | 9 | 8 | 4 | 1 | 0 | 0 | 0 | 0 | 0 | |
| 51 |
Angela Salem |
BOS | 19 | 19 | 1700 | 1 | 0 | 12 | 6 | 8 | 0 | 2 | 0 | 0 | 1 | 0 | |
| 52 |
Jessica Fishlock |
SEA | 16 | 16 | 1390 | 1 | 4 | 23 | 10 | 16 | 1 | 0 | 0 | 0 | 4 | 0 | |
| 53 |
Taylor Comeau |
CHI | 16 | 6 | 667 | 1 | 1 | 4 | 2 | 9 | 0 | 0 | 0 | 0 | 0 | 0 | |
| 54 |
Kristie Mewis |
BOS | 14 | 13 | 1122 | 1 | 1 | 21 | 7 | 13 | 2 | 23 | 1 | 0 | 0 | 0 | |
| 55 |
Merritt Mathias |
SEA | 19 | 17 | 1431 | 1 | 0 | 18 | 9 | 21 | 19 | 2 | 0 | 0 | 2 | 0 | |
| 56 |
Elise Krieghoff |
BOS | 6 | 0 | 142 | 1 | 0 | 2 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | |
| 57 |
Megan Rapinoe |
SEA | 5 | 2 | 205 | 1 | 1 | 7 | 5 | 4 | 2 | 3 | 0 | 0 | 0 | 0 | |
| 58 |
Havana Solaun |
SEA | 6 | 3 | 274 | 1 | 0 | 5 | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | |
| 59 |
Rumi Utsugi |
SEA | 7 | 6 | 554 | 1 | 0 | 7 | 1 | 2 | 5 | 1 | 0 | 0 | 0 | 0 | |
| 60 |
Keelin Winters |
SEA | 20 | 20 | 1750 | 1 | 2 | 11 | 4 | 20 | 0 | 0 | 0 | 0 | 2 | 0 | |
| 61 |
Rachel Corsie |
SEA | 12 | 11 | 1005 | 1 | 0 | 4 | 1 | 12 | 0 | 0 | 0 | 0 | 3 | 0 | |
| 62 |
Kelly Conheeney |
NJ | 13 | 6 | 588 | 1 | 0 | 11 | 6 | 12 | 7 | 1 | 0 | 0 | 1 | 0 | |
| 63 |
Lauren Barnes |
SEA | 20 | 20 | 1776 | 1 | 2 | 5 | 3 | 11 | 0 | 44 | 0 | 0 | 1 | 0 | |
| 64 |
Kathryn Williamson |
POR | 5 | 3 | 198 | 1 | 0 | 1 | 1 | 3 | 0 | 1 | 0 | 0 | 0 | 0 | |
| 65 |
Whitney Engen |
BOS | 14 | 14 | 1260 | 1 | 1 | 1 | 1 | 3 | 0 | 1 | 0 | 0 | 2 | 0 | |
| 66 |
Mollie Pathman |
BOS | 13 | 12 | 1055 | 1 | 0 | 2 | 1 | 5 | 0 | 2 | 0 | 0 | 0 | 0 | |
| 67 |
Meg Morris |
POR | 7 | 3 | 274 | 1 | 1 | 2 | 1 | 6 | 3 | 0 | 0 | 0 | 2 | 0 | |
| 68 |
Taylor Lytle |
NJ | 18 | 18 | 1506 | 1 | 2 | 13 | 3 | 6 | 4 | 0 | 0 | 0 | 0 | 0 | |
| 69 |
Kelley O'Hara |
NJ | 12 | 11 | 1033 | 1 | 2 | 16 | 5 | 12 | 8 | 36 | 0 | 0 | 1 | 0 | |
| 70 |
Raquel Rodriguez |
NJ | 18 | 17 | 1464 | 1 | 1 | 21 | 11 | 12 | 1 | 0 | 0 | 0 | 1 | 0 | |
| 71 |
Erica Skroski |
NJ | 20 | 20 | 1798 | 1 | 0 | 2 | 1 | 10 | 1 | 0 | 0 | 0 | 0 | 0 | |
| 72 |
Kendall Lorraine Fletcher |
SEA | 20 | 20 | 1755 | 1 | 0 | 6 | 3 | 7 | 1 | 0 | 0 | 0 | 1 | 0 | |
| 73 |
Tobin Heath |
POR | 14 | 13 | 1159 | 1 | 10 | 32 | 16 | 28 | 5 | 55 | 0 | 0 | 1 | 1 | |
| 74 |
Tori Huster |
WAS | 19 | 19 | 1667 | 1 | 1 | 17 | 7 | 14 | 0 | 0 | 0 | 0 | 0 | 0 | |
| 75 |
Alyssa Kleiner |
WAS | 17 | 12 | 1111 | 1 | 1 | 4 | 2 | 11 | 1 | 0 | 0 | 0 | 1 | 0 | |
| 76 |
Ali Krieger |
WAS | 15 | 14 | 1267 | 1 | 0 | 8 | 4 | 9 | 1 | 7 | 0 | 0 | 2 | 0 | |
| 77 |
Louise Schillgard |
BOS | 18 | 16 | 1428 | 1 | 2 | 5 | 4 | 32 | 5 | 31 | 1 | 1 | 4 | 0 | |
| 78 |
Steph Catley |
ORL | 11 | 11 | 990 | 1 | 1 | 7 | 3 | 9 | 1 | 27 | 0 | 0 | 0 | 0 | |
| 79 |
Erika Tymrak |
KC | 17 | 14 | 1164 | 1 | 2 | 18 | 6 | 9 | 3 | 23 | 0 | 0 | 0 | 0 | |
| 80 |
Becky Sauerbrunn |
KC | 14 | 14 | 1260 | 1 | 0 | 3 | 2 | 6 | 0 | 1 | 0 | 0 | 1 | 0 | |
| 81 |
Heather O'Reilly |
KC | 14 | 14 | 1206 | 1 | 2 | 20 | 8 | 12 | 10 | 54 | 2 | 1 | 2 | 0 | |
| 82 |
Katie Schoepfer |
BOS | 12 | 8 | 597 | 1 | 0 | 9 | 5 | 5 | 1 | 0 | 0 | 0 | 1 | 0 | |
| 83 |
Chioma Ubogagu |
HOU | 15 | 9 | 805 | 1 | 1 | 16 | 7 | 8 | 8 | 0 | 0 | 0 | 0 | 0 | |
| 84 |
Kyah Simon |
BOS | 17 | 14 | 1292 | 1 | 1 | 20 | 7 | 15 | 5 | 1 | 0 | 0 | 1 | 0 | |
| 85 | Andressinha | HOU | 15 | 15 | 1297 | 1 | 1 | 19 | 8 | 12 | 1 | 37 | 0 | 0 | 1 | 0 | |
| 86 |
Michaela Hahn |
WNY | 13 | 8 | 659 | 1 | 1 | 7 | 2 | 6 | 0 | 0 | 0 | 0 | 2 | 0 | |
| 87 |
Jaelene Hinkle |
WNY | 15 | 15 | 1327 | 1 | 3 | 8 | 7 | 16 | 1 | 37 | 1 | 1 | 2 | 0 | |
| 88 |
Amber Brooks |
HOU | 19 | 11 | 1085 | 1 | 0 | 11 | 2 | 20 | 0 | 1 | 0 | 0 | 1 | 0 | |
| 89 | Poliana | HOU | 15 | 15 | 1324 | 1 | 0 | 12 | 7 | 11 | 2 | 2 | 0 | 0 | 1 | 0 | |
| 90 |
Cara Walls |
CHI | 12 | 8 | 702 | 1 | 0 | 9 | 6 | 10 | 8 | 1 | 0 | 0 | 0 | 0 | |
| 91 |
Christen Westphal |
BOS | 13 | 7 | 580 | 1 | 0 | 2 | 2 | 6 | 0 | 0 | 0 | 0 | 0 | 0 | |
| 92 |
Sam Witteman |
ORL | 16 | 12 | 1062 | 0 | 0 | 4 | 2 | 6 | 0 | 0 | 0 | 0 | 0 | 0 | |
| 93 |
Desiree Scott |
KC | 14 | 14 | 1260 | 0 | 0 | 5 | 2 | 16 | 1 | 0 | 0 | 0 | 2 | 0 | |
| 94 |
Brooke Elby |
BOS | 13 | 11 | 917 | 0 | 0 | 3 | 2 | 9 | 0 | 0 | 0 | 0 | 0 | 1 | |
| 95 |
Brittany Taylor |
KC | 20 | 20 | 1800 | 0 | 0 | 11 | 4 | 11 | 1 | 1 | 0 | 0 | 0 | 0 | |
| 96 |
Samantha Johnson |
CHI | 19 | 19 | 1676 | 0 | 0 | 0 | 0 | 14 | 0 | 0 | 0 | 0 | 2 | 0 | |
| 97 |
Tiffany Weimer |
KC | 4 | 0 | 17 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
| 98 |
Laura Alleway |
ORL | 11 | 9 | 783 | 0 | 0 | 8 | 4 | 6 | 0 | 0 | 0 | 0 | 2 | 0 | |
| 99 |
Christina Burkenroad |
ORL | 7 | 2 | 252 | 0 | 0 | 0 | 0 | 2 | 3 | 0 | 0 | 0 | 0 | 0 | |
| 100 |
Josee Belanger |
ORL | 14 | 14 | 1082 | 0 | 0 | 3 | 1 | 12 | 1 | 0 | 0 | 0 | 2 | 0 | |
| 101 |
Julie Ertz |
CHI | 12 | 12 | 1080 | 0 | 0 | 1 | 0 | 7 | 0 | 0 | 0 | 0 | 1 | 0 | |
| 102 |
Lisa De Vanna |
ORL | 3 | 2 | 153 | 0 | 0 | 2 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | |
| 103 |
Mary Luba |
CHI | 1 | 0 | 10 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
| 104 |
Becky Edwards |
ORL | 16 | 10 | 806 | 0 | 0 | 4 | 1 | 13 | 0 | 0 | 0 | 0 | 1 | 0 | |
| 105 |
Maddy Evans |
ORL | 16 | 12 | 1111 | 0 | 1 | 9 | 6 | 16 | 0 | 0 | 0 | 0 | 2 | 0 | |
| 106 |
Jamia Fields |
ORL | 12 | 6 | 627 | 0 | 1 | 3 | 1 | 10 | 4 | 0 | 0 | 0 | 0 | 0 | |
| 107 |
Leah Lynn Gabriela Fortune |
ORL | 3 | 0 | 44 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
| 108 |
Alyssa Mautz |
CHI | 18 | 10 | 1037 | 0 | 2 | 12 | 6 | 19 | 5 | 1 | 0 | 0 | 4 | 0 | |
| 109 | Monica | ORL | 16 | 15 | 1377 | 0 | 0 | 5 | 3 | 9 | 0 | 0 | 0 | 0 | 0 | 0 | |
| 110 |
Kaylyn Kyle |
ORL | 18 | 16 | 1441 | 0 | 0 | 5 | 1 | 18 | 6 | 0 | 0 | 0 | 1 | 0 | |
| 111 |
Sierra Lelii |
ORL | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
| 112 |
Camille Levin |
ORL | 10 | 9 | 836 | 0 | 1 | 1 | 0 | 4 | 2 | 0 | 0 | 0 | 0 | 0 | |
| 113 |
Toni Pressley |
ORL | 14 | 11 | 1028 | 0 | 0 | 8 | 1 | 12 | 1 | 4 | 0 | 0 | 3 | 0 | |
| 114 |
Kim Reynolds |
ORL | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
| 115 |
Dani Weatherholt |
ORL | 12 | 9 | 786 | 0 | 0 | 3 | 1 | 12 | 0 | 0 | 0 | 0 | 0 | 0 | |
| 116 |
Allie Wisner |
ORL | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
| 117 |
Kathleen Naughton |
CHI | 16 | 9 | 861 | 0 | 0 | 1 | 1 | 6 | 1 | 0 | 0 | 0 | 0 | 0 | |
| 118 |
McKenzie Berryhill |
POR | 5 | 2 | 182 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | |
| 119 |
Celeste Boureille |
POR | 6 | 5 | 466 | 0 | 0 | 3 | 0 | 4 | 0 | 0 | 0 | 0 | 0 | 0 | |
| 120 |
Eunice Beckmann |
BOS | 11 | 8 | 658 | 0 | 1 | 16 | 6 | 18 | 2 | 1 | 0 | 0 | 3 | 0 | |
| 121 |
Maureen Fitzgerald |
POR | 3 | 2 | 134 | 0 | 0 | 0 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | |
| 122 |
Courtney Raetzman |
CHI | 6 | 0 | 52 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | |
| 123 |
Amandine Henry |
POR | 9 | 8 | 638 | 0 | 1 | 8 | 2 | 16 | 0 | 0 | 0 | 0 | 0 | 0 | |
| 124 |
Rebekah Roller |
CHI | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
| 125 |
Kendall Johnson |
POR | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
| 126 |
Meghan Klingenberg |
POR | 14 | 14 | 1259 | 0 | 0 | 4 | 2 | 8 | 3 | 1 | 0 | 0 | 1 | 0 | |
| 127 |
Samantha Lofton |
POR | 3 | 0 | 54 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
| 128 |
Morgan Marlborough |
BOS | 1 | 0 | 23 | 0 | 0 | 2 | 1 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | |
| 129 |
Emily Menges |
POR | 20 | 20 | 1800 | 0 | 0 | 1 | 0 | 4 | 0 | 0 | 0 | 0 | 0 | 0 | |
| 130 |
Shade Pratt |
POR | 5 | 1 | 140 | 0 | 0 | 1 | 1 | 4 | 0 | 0 | 0 | 0 | 0 | 0 | |
| 131 |
Hayley Raso |
POR | 20 | 6 | 751 | 0 | 2 | 9 | 3 | 18 | 8 | 0 | 0 | 0 | 3 | 0 | |
| 132 |
Katherine Reynolds |
POR | 20 | 18 | 1671 | 0 | 0 | 1 | 1 | 10 | 0 | 0 | 0 | 0 | 1 | 0 | |
| 133 |
Meleana Shim |
POR | 14 | 9 | 812 | 0 | 1 | 4 | 2 | 10 | 1 | 5 | 0 | 0 | 1 | 0 | |
| 134 |
Mónica Rose Alvarado Rodriguez |
HOU | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
| 135 |
Jennifer Skogerboe |
POR | 3 | 2 | 210 | 0 | 0 | 0 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | |
| 136 |
Emily Sonnett |
POR | 15 | 15 | 1350 | 0 | 0 | 3 | 2 | 7 | 1 | 0 | 0 | 0 | 2 | 0 | |
| 137 |
Mallory Weber |
POR | 13 | 7 | 699 | 0 | 0 | 4 | 2 | 8 | 1 | 0 | 0 | 0 | 1 | 0 | |
| 138 |
Kylie Strom |
BOS | 7 | 3 | 343 | 0 | 0 | 0 | 0 | 7 | 0 | 0 | 0 | 0 | 0 | 0 | |
| 139 |
Morgan Brian |
HOU | 13 | 13 | 1005 | 0 | 0 | 7 | 4 | 5 | 3 | 16 | 0 | 0 | 0 | 0 | |
| 140 |
Michelle Cruz |
SEA | 4 | 0 | 46 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
| 141 |
Kiersten Dallstream |
SEA | 12 | 2 | 274 | 0 | 0 | 2 | 1 | 5 | 0 | 0 | 0 | 0 | 1 | 0 | |
| 142 |
Lindsay Elston |
SEA | 12 | 0 | 157 | 0 | 0 | 2 | 1 | 3 | 2 | 0 | 0 | 0 | 1 | 0 | |
| 143 |
Bianca Brinson |
HOU | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
| 144 |
Stephanie Verdoia |
BOS | 10 | 5 | 452 | 0 | 0 | 6 | 2 | 5 | 1 | 1 | 0 | 0 | 0 | 0 | |
| 145 |
Ellie Brush |
HOU | 15 | 15 | 1336 | 0 | 0 | 2 | 0 | 11 | 0 | 1 | 0 | 0 | 4 | 0 | |
| 146 |
Kassey Kallman |
BOS | 20 | 20 | 1800 | 0 | 0 | 0 | 0 | 9 | 0 | 0 | 0 | 0 | 0 | 0 | |
| 147 |
Allysha Chapman |
HOU | 9 | 8 | 711 | 0 | 0 | 2 | 1 | 6 | 0 | 0 | 0 | 0 | 1 | 0 | |
| 148 |
Paige Nielsen |
SEA | 2 | 0 | 26 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | |
| 149 |
Carson Pickett |
SEA | 15 | 8 | 841 | 0 | 1 | 5 | 2 | 3 | 0 | 0 | 0 | 0 | 0 | 1 | |
| 150 |
Megan Crosson |
HOU | 4 | 1 | 115 | 0 | 0 | 0 | 0 | 1 | 0 | 8 | 0 | 0 | 1 | 0 | |
| 151 |
Elli Reed |
SEA | 16 | 14 | 1284 | 0 | 0 | 1 | 0 | 8 | 1 | 0 | 0 | 0 | 2 | 0 | |
| 152 |
Rachel Wood |
BOS | 7 | 2 | 260 | 0 | 0 | 4 | 0 | 5 | 1 | 0 | 0 | 0 | 0 | 0 | |
| 153 |
Tessa Florio-Gavilsky |
HOU | 3 | 0 | 54 | 0 | 0 | 1 | 0 | 2 | 1 | 1 | 0 | 0 | 0 | 0 | |
| 154 |
Anna María Gilbertson Rojas |
HOU | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
| 155 |
Caity Heap |
HOU | 6 | 2 | 127 | 0 | 0 | 1 | 0 | 3 | 0 | 0 | 0 | 0 | 2 | 0 | |
| 156 |
Melissa Henderson |
HOU | 7 | 4 | 321 | 0 | 1 | 1 | 0 | 4 | 3 | 8 | 0 | 0 | 0 | 0 | |
| 157 |
Kim DeCesare |
NJ | 6 | 3 | 244 | 0 | 0 | 2 | 1 | 3 | 0 | 0 | 0 | 0 | 0 | 0 | |
| 158 |
Theresa Diederich |
NJ | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
| 159 |
Courtney Kathryn 'Coco' Goodson |
NJ | 1 | 0 | 8 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
| 160 |
Shawna Gordon |
NJ | 11 | 5 | 444 | 0 | 0 | 4 | 1 | 2 | 1 | 2 | 0 | 0 | 0 | 0 | |
| 161 |
Kristin Grubka |
NJ | 15 | 14 | 1267 | 0 | 1 | 3 | 1 | 16 | 2 | 1 | 0 | 0 | 2 | 0 | |
| 162 |
Danielle Colaprico |
CHI | 20 | 20 | 1784 | 0 | 2 | 6 | 5 | 19 | 0 | 31 | 0 | 0 | 0 | 0 | |
| 163 |
Rebecca Moros |
HOU | 17 | 17 | 1521 | 0 | 2 | 6 | 2 | 17 | 0 | 0 | 0 | 0 | 0 | 0 | |
| 164 |
Ghoutia Karchouni |
BOS | 3 | 1 | 100 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | |
| 165 |
Stephanie Ochs |
HOU | 12 | 3 | 381 | 0 | 2 | 5 | 3 | 4 | 2 | 4 | 0 | 0 | 0 | 0 | |
| 166 |
Amanda DaCosta |
CHI | 13 | 8 | 664 | 0 | 0 | 9 | 2 | 9 | 1 | 1 | 0 | 0 | 0 | 0 | |
| 167 |
Ashley Nick |
NJ | 3 | 1 | 103 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | |
| 168 |
Cami Privett |
HOU | 15 | 11 | 1056 | 0 | 0 | 3 | 1 | 9 | 1 | 0 | 0 | 0 | 1 | 0 | |
| 169 |
Christie Pearce |
NJ | 20 | 20 | 1800 | 0 | 0 | 2 | 0 | 5 | 1 | 0 | 0 | 0 | 1 | 0 | |
| 170 |
Dominique Richardson |
NJ | 2 | 0 | 54 | 0 | 0 | 2 | 1 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | |
| 171 |
Cari Roccaro |
HOU | 15 | 14 | 1267 | 0 | 0 | 1 | 0 | 6 | 0 | 1 | 0 | 0 | 2 | 0 | |
| 172 |
Danielle Schulmann |
NJ | 3 | 0 | 42 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | |
| 173 |
Erin Simon |
NJ | 19 | 18 | 1590 | 0 | 2 | 0 | 0 | 16 | 3 | 0 | 0 | 0 | 1 | 0 | |
| 174 |
Nikki Stanton |
NJ | 12 | 4 | 407 | 0 | 0 | 3 | 1 | 9 | 0 | 1 | 0 | 0 | 3 | 0 | |
| 175 |
Chestley Strother |
HOU | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
| 176 |
Whitney Church |
WAS | 11 | 7 | 612 | 0 | 0 | 0 | 0 | 4 | 0 | 0 | 0 | 0 | 0 | 0 | |
| 177 |
Caprice Dydasco |
WAS | 12 | 12 | 1080 | 0 | 2 | 6 | 2 | 9 | 1 | 0 | 0 | 0 | 1 | 0 | |
| 178 |
Cali Farquharson |
WAS | 16 | 8 | 559 | 0 | 0 | 6 | 4 | 7 | 2 | 0 | 0 | 0 | 0 | 0 | |
| 179 |
Caroline Van Slambrouck |
HOU | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
| 180 |
Estelle Johnson |
WAS | 11 | 11 | 990 | 0 | 0 | 4 | 2 | 4 | 0 | 0 | 0 | 0 | 0 | 0 | |
| 181 |
Alex Arlitt |
KC | 11 | 8 | 712 | 0 | 0 | 2 | 0 | 7 | 0 | 0 | 0 | 0 | 1 | 0 | |
| 182 |
Vanessa DiBernardo |
CHI | 20 | 20 | 1785 | 0 | 6 | 25 | 10 | 17 | 0 | 67 | 0 | 0 | 0 | 0 | |
| 183 |
Katie Bowen |
KC | 13 | 11 | 959 | 0 | 1 | 3 | 3 | 11 | 0 | 0 | 0 | 0 | 0 | 0 | |
| 184 |
Alli Murphy |
WAS | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
| 185 |
Jen Buczkowski |
KC | 5 | 5 | 426 | 0 | 0 | 2 | 1 | 9 | 0 | 0 | 0 | 0 | 0 | 0 | |
| 186 |
Amanda Frisbie |
KC | 3 | 3 | 270 | 0 | 0 | 2 | 0 | 1 | 0 | 2 | 0 | 0 | 0 | 0 | |
| 187 |
Megan Oyster |
WAS | 15 | 15 | 1341 | 0 | 0 | 1 | 0 | 11 | 0 | 0 | 0 | 0 | 2 | 0 | |
| 188 |
Haley Rosen |
WAS | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
| 189 |
Line Sigvardsen Jensen |
WAS | 3 | 2 | 141 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
| 190 |
Janelle Kalyn Flaws |
CHI | 1 | 0 | 45 | 0 | 0 | 0 | 0 | 1 | 2 | 0 | 0 | 0 | 0 | 0 | |
| 191 |
Shelina Zadorsky |
WAS | 11 | 10 | 911 | 0 | 0 | 1 | 0 | 11 | 0 | 0 | 0 | 0 | 2 | 0 | |
| 192 |
Lady Patricia Andrade Rodríguez |
WNY | 2 | 0 | 52 | 0 | 0 | 0 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | |
| 193 |
Halimatu Ibrahim Ayinde |
WNY | 1 | 1 | 45 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | |
| 194 |
Janice Cayman |
WNY | 3 | 1 | 96 | 0 | 0 | 2 | 1 | 1 | 0 | 1 | 0 | 0 | 1 | 0 | |
| 195 |
Caroline Kastor |
KC | 15 | 3 | 296 | 0 | 2 | 4 | 1 | 5 | 1 | 0 | 0 | 0 | 0 | 0 | |
| 196 |
Lo’eau LaBonta |
KC | 11 | 7 | 693 | 0 | 0 | 9 | 3 | 8 | 1 | 0 | 0 | 0 | 1 | 0 | |
| 197 |
Elizabeth Eddy |
WNY | 20 | 20 | 1753 | 0 | 2 | 5 | 2 | 31 | 1 | 9 | 0 | 0 | 3 | 0 | |
| 198 |
Mandy Laddish |
KC | 19 | 19 | 1679 | 0 | 0 | 17 | 10 | 24 | 4 | 0 | 0 | 0 | 0 | 0 | |
| 199 |
Arin Gilliland |
CHI | 20 | 20 | 1718 | 0 | 4 | 10 | 4 | 13 | 1 | 1 | 0 | 0 | 2 | 0 | |
| 200 |
Kristen Hamilton |
WNY | 12 | 0 | 126 | 0 | 0 | 1 | 1 | 6 | 0 | 0 | 0 | 0 | 1 | 0 | |
| 201 |
Molly Menchel |
KC | 3 | 2 | 185 | 0 | 0 | 0 | 0 | 3 | 0 | 2 | 0 | 0 | 1 | 0 | |
| 202 |
Ga-Eul Jeon |
WNY | 2 | 1 | 86 | 0 | 0 | 0 | 0 | 2 | 0 | 1 | 0 | 0 | 0 | 0 | |
| 203 |
Alanna Kennedy |
WNY | 15 | 15 | 1298 | 0 | 0 | 13 | 4 | 17 | 0 | 2 | 0 | 0 | 3 | 0 | |
| 204 |
Adriana Leon |
WNY | 10 | 3 | 345 | 0 | 0 | 4 | 1 | 8 | 2 | 0 | 0 | 0 | 1 | 0 | |
| 205 |
Laura Liedle |
WNY | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
| 206 |
Alexa Newfield |
KC | 8 | 2 | 236 | 0 | 0 | 3 | 1 | 5 | 0 | 1 | 0 | 0 | 0 | 0 | |
| 207 |
Sarah Gorden |
CHI | 4 | 0 | 110 | 0 | 0 | 0 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | |
| 208 |
Courtney Niemiec |
WNY | 6 | 4 | 395 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
| 209 |
Brianne Reed |
KC | 7 | 5 | 441 | 0 | 0 | 0 | 0 | 3 | 0 | 0 | 0 | 0 | 1 | 0 | |
| 210 |
Meredith Speck |
WNY | 6 | 5 | 369 | 0 | 1 | 2 | 1 | 4 | 2 | 2 | 0 | 0 | 1 | 0 | |
| 211 |
Brittany Ratcliffe |
BOS | 15 | 5 | 546 | 0 | 0 | 7 | 1 | 7 | 1 | 0 | 0 | 0 | 3 | 0 | |
| 212 |
McCall Zerboni |
WNY | 20 | 19 | 1681 | 0 | 1 | 13 | 5 | 37 | 0 | 2 | 0 | 0 | 4 | 0 |
| Rank | Player | TEAM | GP | GS | MINS | GA | GAA | SOG | SV | CS | YC | RC | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 |
Nicole Barnhart |
KC | 20 | 20 | 1800 | 20 | 1 | 98 | 78 | 6 | 0 | 0 | |
| 2 |
Kelsey Wys |
WAS | 12 | 12 | 1080 | 14 | 1.17 | 70 | 56 | 2 | 0 | 0 | |
| 3 |
Lydia Williams |
HOU | 15 | 15 | 1350 | 22 | 1.47 | 78 | 56 | 1 | 0 | 0 | |
| 4 |
Ashlyn Harris |
ORL | 15 | 15 | 1350 | 20 | 1.33 | 74 | 54 | 4 | 0 | 0 | |
| 5 |
Michelle Betos |
POR | 14 | 14 | 1260 | 16 | 1.14 | 60 | 44 | 4 | 1 | 0 | |
| 6 |
Elizabeth Stout |
BOS | 10 | 9 | 868 | 21 | 2.18 | 63 | 42 | 1 | 0 | 0 | |
| 7 |
Jami Kranich |
BOS | 9 | 9 | 810 | 25 | 2.78 | 64 | 39 | 2 | 1 | 0 | |
| 8 |
Caroline Stanley |
NJ | 11 | 11 | 940 | 16 | 1.53 | 53 | 37 | 3 | 1 | 0 | |
| 9 |
Haley Kopmeyer |
SEA | 11 | 11 | 944 | 13 | 1.24 | 47 | 34 | 3 | 0 | 0 | |
| 10 |
Alyssa Naeher |
CHI | 13 | 13 | 1170 | 13 | 1 | 45 | 32 | 6 | 0 | 0 | |
| 11 |
Sabrina D’Angelo |
WNY | 11 | 11 | 990 | 16 | 1.45 | 48 | 32 | 2 | 0 | 0 | |
| 12 |
Caroline Casey |
NJ | 10 | 9 | 860 | 14 | 1.47 | 40 | 26 | 2 | 0 | 0 | |
| 13 |
Hope Solo |
SEA | 8 | 8 | 720 | 5 | 0.63 | 27 | 22 | 5 | 2 | 0 | |
| 14 |
Stephanie Labbe |
WAS | 8 | 8 | 720 | 7 | 0.88 | 29 | 22 | 5 | 0 | 0 | |
| 15 |
Michele Dalton |
CHI | 7 | 7 | 630 | 7 | 1 | 23 | 16 | 2 | 0 | 0 | |
| 16 |
Britt Eckerstrom |
WNY | 3 | 3 | 270 | 2 | 0.67 | 18 | 16 | 2 | 0 | 0 | |
| 17 |
Kaitlyn Savage |
ORL | 4 | 4 | 360 | 8 | 2 | 23 | 15 | 0 | 0 | 0 | |
| 18 |
Adrianna Franch |
POR | 6 | 6 | 540 | 3 | 0.5 | 18 | 15 | 3 | 0 | 0 | |
| 19 |
Katelyn Rowland |
WNY | 6 | 6 | 540 | 8 | 1.33 | 21 | 13 | 1 | 0 | 0 | |
| 20 |
Bianca Henninger |
HOU | 5 | 5 | 450 | 7 | 1.4 | 18 | 11 | 1 | 0 | 0 | |
| 21 |
Andi Tostanoski |
SEA | 2 | 1 | 136 | 3 | 1.99 | 11 | 8 | 0 | 0 | 0 | |
| 22 |
Abby Smith |
BOS | 2 | 2 | 122 | 1 | 0.74 | 7 | 6 | 0 | 0 | 0 | |
| 23 |
Aubrey Bledsoe |
ORL | 1 | 1 | 90 | 2 | 2 | 5 | 3 | 0 | 0 | 0 | |
| 24 |
Brianna Smallidge |
CHI | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
| 25 |
Haley Carter |
HOU | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
| 26 |
Kate Scheele |
HOU | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
| 27 |
Catherine Parkhill |
KC | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
| 28 |
Megan Dorsey |
ORL | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
| 29 |
Emily Kruger |
POR | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
| 30 |
Abigail Steele |
SEA | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
| 31 |
Jillian Ann Loyden |
NJ | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
| 32 |
Erin Nayler |
NJ | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
| 33 |
DiDi Haracic |
WAS | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| Rank | Team | GP | G | A | S | SOG | FC | OFF | CK | PKG | YC | RC | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Western New York Flash | 22 | 40 | 28 | 274 | 133 | 196 | 48 | 126 | 4 | 27 | 1 | |
| 2 | Portland Thorns FC | 21 | 35 | 22 | 184 | 98 | 233 | 60 | 82 | 4 | 24 | 1 | |
| 3 | Washington Spirit | 22 | 30 | 16 | 199 | 99 | 142 | 47 | 119 | 2 | 15 | 0 | |
| 4 | Houston Dash | 20 | 29 | 23 | 219 | 103 | 177 | 90 | 91 | 1 | 17 | 0 | |
| 5 | Seattle Reign FC | 20 | 29 | 18 | 188 | 101 | 147 | 64 | 78 | 3 | 19 | 1 | |
| 6 | Chicago Red Stars | 21 | 24 | 17 | 198 | 99 | 174 | 60 | 103 | 1 | 13 | 0 | |
| 7 | Sky Blue FC | 20 | 24 | 14 | 169 | 84 | 163 | 80 | 76 | 3 | 15 | 0 | |
| 8 | Orlando Pride SC | 20 | 20 | 11 | 166 | 86 | 179 | 42 | 88 | 0 | 16 | 0 | |
| 9 | FC Kansas City | 20 | 18 | 11 | 193 | 83 | 210 | 55 | 89 | 2 | 12 | 1 | |
| 10 | Boston Breakers | 20 | 14 | 7 | 156 | 67 | 205 | 46 | 67 | 1 | 23 | 1 |


Ivan Lozowy
Charitable Fund
Home
About
Contacts
Schools
:
March 1, 2021 - Parents' Council of class 1-A, Okhtyrka Secondary School for I-III degrees № 11. Gift from the Lozowy Fund: Laptop computer.
November 6, 2020 - Lebedyn Secondary School for grades I-III №1. Gifts from the Lozowy Fund: Benches for the school park.
January 2, 2020 - School of Pozhnya. Gift from the Lozowy Fund: Chainsaw “Husqvarna 120 II”.
December 20, 2019 - Okhtyrka Comprehensive School for degrees I-III № 11. Gifts from the Lozowy Fund: Sweets for Christmas.
June 15, 2019 - School of Moscovsky Bobryk. Gifts from the Lozowy Fund: Laser printer and rackets for table tennis.
June 15, 2019 - School of Holubivka. Gift from the Lozowy Fund: Projector.
June 15, 2019 - School of Shtepivka. Gifts from the Lozowy Fund: Color inkjet printer and rackets for table tennis.
June 15, 2019 - School of Vorozhba. Gift from the Lozowy Fund: Refrigerator.
June 13, 2019 - School of Rybalske. Gift from the Lozowy Fund: Embroidered shirt for a boy from a low-income family.
June 6, 2019 - School of Kuzemyn. Gifts from the Lozowy Fund: Computer laptop, projector.
June 6, 2019 - School of Lutyshche. Gift from the Lozowy Fund: Computer laptop.
June 6, 2019 - School of Viazove. Gift from the Lozowy Fund: Color inkjet printer.
June 3, 2019 - School of Kyrykivka. Gifts from the Lozowy Fund: Color inkjet printer and laptop.
May 21, 2019 - School of Chupakhivka. Gift from the Lozowy Fund: Printer.
May 21, 2019 - School of Vasylivka. Gifts from the Lozowy Fund: Utensils: soup plates (50 pcs), dining plates (50 pcs), first aid kits.
May 21, 2019 - School of Mykhailivka. Gifts from the Lozowy Fund: Freezer.
May 21, 2019 - School of Pavlenkove. Gifts from the Lozowy Fund: Projector.
May 21, 2019 - School of Mezhyrych. Gifts from the Lozowy Fund: Computer laptop, first aid kits.
May 21, 2019 - Primary school of Chervlene. Gifts from the Lozowy Fund: Books and educational games.
May 21, 2019 - School of Prystailovo. Gift from the Lozowy Fund: Color inkjet printer.
May 17, 2019 - School of Khukhra. Gift from the Lozowy Fund: Photocamera.
May 17, 2019 - School of the village Zavodske. Gift from the Lozowy Fund: Projector.
May 9, 2019 - Lebedyn School №7: awarding winners. Gifts from the Lozowy Fund: Bluetooth headphones (16 pcs).
April 5, 2019 - School of Hrun. Gifts from the Lozowy Fund: Basketballs (5 pcs), footballs (5 pcs), volleyballs (5 pcs).
March 22, 2019 - School of Vilne. Gift from the Lozowy Fund: Color inkjet printer.
March 22, 2019 - School of Bratenytsia. Gift from the Lozowy Fund: Educational games.
March 15, 2019 - Okhtyrka Secondary School №2. Gifts from the Lozowy Fund: Basketballs (5 pcs), footballs (5 pcs), volleyballs (5 pcs).
November 12, 2018 - Okhtyrka Secondary School №1. Gift from the Lozowy Fund: Projector for computer classroom.
September 21, 2018 - Okhtyrka Gymnasium. Gifts from the Lozowy Fund: Fencding grid, soccer net (2 pairs) for the school’s soccer field.
March 1, 2021 - Parents' Council of class 1-A, Okhtyrka Secondary School for I-III degrees № 11. Gift from the Lozowy Fund:
Laptop computer
.
November 6, 2020 - Lebedyn Secondary School for grades I-III №1. Gifts from the Lozowy Fund:
Benches for the school park
.
January 2, 2020 - School of Pozhnya. Gift from the Lozowy Fund:
Chainsaw “Husqvarna 120 II”
.
December 20, 2019 - Okhtyrka Comprehensive School for degrees I-III № 11. Gifts from the Lozowy Fund:
Sweets for Christmas
.
June 15, 2019 - School of Moscovsky Bobryk. Gifts from the Lozowy Fund:
Laser printer and rackets for table tennis
.
June 15, 2019 - School of Holubivka. Gift from the Lozowy Fund:
Projector
.
June 15, 2019 - School of Shtepivka. Gifts from the Lozowy Fund:
Color inkjet printer and rackets for table tennis
.
June 15, 2019 - School of Vorozhba. Gift from the Lozowy Fund:
Refrigerator
.
June 13, 2019 - School of Rybalske. Gift from the Lozowy Fund:
Embroidered shirt for a boy from a low-income family
.
June 6, 2019 - School of Kuzemyn. Gifts from the Lozowy Fund:
Computer laptop, projector
.
June 6, 2019 - School of Lutyshche. Gift from the Lozowy Fund:
Computer laptop
.
June 6, 2019 - School of Viazove. Gift from the Lozowy Fund:
Color inkjet printer
.
June 3, 2019 - School of Kyrykivka. Gifts from the Lozowy Fund:
Color inkjet printer and laptop
.
May 21, 2019 - School of Chupakhivka. Gift from the Lozowy Fund:
Printer
.
May 21, 2019 - School of Vasylivka. Gifts from the Lozowy Fund:
Utensils: soup plates (50 pcs), dining plates (50 pcs), first aid kits
.
May 21, 2019 - School of Mykhailivka. Gifts from the Lozowy Fund:
Freezer
.
May 21, 2019 - School of Pavlenkove. Gifts from the Lozowy Fund:
Projector
.
May 21, 2019 - School of Mezhyrych. Gifts from the Lozowy Fund:
Computer laptop, first aid kits
.
May 21, 2019 - Primary school of Chervlene. Gifts from the Lozowy Fund:
Books and educational games
.
May 21, 2019 - School of Prystailovo. Gift from the Lozowy Fund:
Color inkjet printer
.
May 17, 2019 - School of Khukhra. Gift from the Lozowy Fund:
Photocamera
.
May 17, 2019 - School of the village Zavodske. Gift from the Lozowy Fund:
Projector
.
May 9, 2019 - Lebedyn School №7: awarding winners. Gifts from the Lozowy Fund:
Bluetooth headphones (16 pcs)
.
April 5, 2019 - School of Hrun. Gifts from the Lozowy Fund:
Basketballs (5 pcs), footballs (5 pcs), volleyballs (5 pcs)
.
March 22, 2019 - School of Vilne. Gift from the Lozowy Fund:
Color inkjet printer
.
March 22, 2019 - School of Bratenytsia. Gift from the Lozowy Fund:
Educational games
.
March 15, 2019 - Okhtyrka Secondary School №2. Gifts from the Lozowy Fund:
Basketballs (5 pcs), footballs (5 pcs), volleyballs (5 pcs)
.
November 12, 2018 - Okhtyrka Secondary School №1. Gift from the Lozowy Fund:
Projector for computer classroom
.
September 21, 2018 - Okhtyrka Gymnasium. Gifts from the Lozowy Fund:
Fencding grid, soccer net (2 pairs) for the school’s soccer field
.


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Ruins of 1985
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8 w 7 9 OR q e 4 6 a d 5 s
Px: (
0
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Cell: (
0
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Distance:
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Go!


(To be compiled only when the applicant has paid the fee of Sh. 125)
At the date stated on the front hereof, the following entries appeared in the register relating to the land
Edition
Opened
PART A - PROPERTY SECTION
Registration Section
1
2
3
Parcel number
3
Plot number
3
Approximate are
0.81 ares
Registry map sheet number
1
EASEMENTS, ETC
1
NATURE OF TITLE
1


  We have the best Global Rose Rebate anywhere. thesis_keywords: Global Rose, Global Rose Coupon Code, Global Rose Discount, Global Rose Rebate product_name: Global Rose hop_url: http://www.icouponblog.com/hop.php?id=3831 ---
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WITNESS LIST Appropriations Committee April 9, 2001-9:00A HB 515Committee Substitute (Wise) For: Gardner, Glen (Texas Coalition of Veterans Organizations) Paluguist, Michael (The American Legion Department of Texas) Patterson, Jerry (Texas Coalition of Veterans Organizations) On: Green, Billy (Texas Veterans Commission) Oldmixon, Douglas (Texas Land Commissioner) Registering, but not testifying: For: Bier, Samuel (VFW Post 856) Brooks, Chet (Self) Escamilla, Chris (Hidalgo County Advisory Committee on Veteran Affairs) Pyeatt, Dale (National Guard Association of Texas) HB 877Committee Substitute (Flores) Registering, but not testifying: For: DeLord, Ron (CLEAT) Oakley, Keith (Texas Municipal Police Association) On: Hymel, Ray (Employees Retirement System of Texas) HB 1839 Committee Substitute (Junell) On: Montford, John (Texas Tech University System) Smith, Arthur (University of Houston System) HB 1902 For: Biedrzycki, Carol (Texas Rate Payers Organization to Save Energy) Registering, but not testifying: For: Berasley, George (AARP) Briesemeister, Janee (Consumers Union) Chapman, Randall (Texas Legal Services Center) Rodriguez, Stella (Texas Association of Community Action Agencies) On: Lanford, Lane (Public Utility Commission) HB 2852 Committee Substitute (Junell) On: Fojtasek, Dolores (Comptroller of Public Accounts) Kennedy, Meredith (Office of the Attorney General) Polunsky, Steven (Texas Department of Transportation) HB 3026 Committee Substitute (Chisum) Against: Miksa, Mary (Texas Association of Business & Chambers of Commerce) On: Fisher, Jon (Texas Chemical Council) Morphew, Cindy (Texas Oil & Gas Association) Registering, but not testifying: On: Huston, Robert (TNRCC) HB 3088 Committee Substitute (Turner) On: Reissig, Mike (Comptroller of Public Accounts) HB 3189 Committee Substitute (Puente) Against: Fisher, Jon (Texas Chemical Council) Morphew, Cindy (Texas Oil and Gas Association) On: Huston, Robert (Texas Natural Resource Conservation Commission) Registering, but not testifying: Against: Miksa, Mary (Texas Association of Business & Chambers of Commerce) HB 3190 On: Johnson, John (Texas Department of Transportation) Nichols, Robert (Texas Department of Transportation) Registering, but not testifying: For: Mitchell, Seth (Bexas County Commissioners Court) On: Bass, James (Texas Department of Transportation) Heald, Wes (Texas Department of Transportation) HB 3281 Committee Substitute (Walker) On: Hull, James (Texas Forest Service) HJR 111 On: LeBas, James (Comptroller's Office)


This page starts an XHR request in 2 seconds (regardless of page load status), which
takes 20 seconds to finish. The page also has an image that takes 4 seconds to load.
The spinner should spin for just 4 seconds (not 22 seconds).
Results observed 2010-04-15:
Chrome <IP_ADDRESS>5 spins for 22 sec
Chrome 5.0.342.9 beta spins for 22 sec
Safari 4.0.4 (Win) spins for 22 sec
Arora 0.10.1 (Linux) spins for 4 sec
Midori 0.1.9 (Linux) spins for 22 sec
Firefox 3.6.3 spins for 4 sec
IE7, IE8, IE8 in IE7 mode spin for 4 sec
Opera 10.51 spins for 4 sec


Connecting University Health Services staff with Carnegie Mellon students through transparency in information, built in communication tools and shared decision making.
This project focused on developing familiarity with rich User Centered Research methods. As a team of five, we conducted open-ended interviews with stakeholders and used the data to map out multiple models of the CMU health care system from each perspective, and finally into consolidated models representative of the current state. We than envisioned a future state that resolved the tensions and pain points in the present.
Using our models of the present and an envisioned future state, our team came up with over fifty ideas of solutions to address problems at multiple levels. We chose elements of strongest ideas to dig deeper into through improvisational storyboarding, and finally chose a a small number of ideas to mock up as storyboards to test with stakeholders. Based on the storyboard testing, we finally came to our final concept, combining acquired knowledge from all parts of the process.


Computer Science
AWS Certified Cloud Practitioner
Scrum Fundamentals Certified (SFC)
Flutter
AWS
iOS
Kotlin
Android
Java
Bootcamp Cloud Architecture
CD/CI
Leadership
User Experience
Mobile Marketing
Github
Scrum
Biometrics


WIE HACK 2.0
All Women 36hr Online Hackathon
General Instructions
- It is a 36-hour online hackathon.
- There will be a total of 6 rounds and submission at every stage is compulsory to proceed in the competition
- Mentoring Sessions and workshops are compulsory for the participants to attend as they describe what is to be done in a particular round.
- There will be a live chat option, where the participants may ask their queries or doubts.
- In case you face difficulty during submission or while watching the Livestream, contact the technical team immediately.
- You must have a stable internet connection during the entire length of the hackathon to ensure uninterrupted streaming
- Participants are expected to maintain the code of conduct.
- At any time if the participants are found disobeying any of the rules of the competition, they will be disqualified from the hackathon.


BS Computer Science and Engineering
University of Connecticut Storrs
MAY 2017
Technical Skills
Other Skills
A100 Apprentice
A100 is an apprenticeship program that gives aspiring software developers the tools, skills, and training neccesarry for high preformance in the field.
MARCH 2016-MAY 2016
email: anders.fogelberg@uconn.edu


The hack-sprint-a-thon
The fastest hackathon I experienced, and some margarita 'Za
The fastest hackathon I experienced, and some margarita 'Za
My experience at NLHTML x CSSDay and my sketchnotes
How functional light programming made me a better coder
Tips and tools or tricks about accessibility
What are the differences and use the right tool for the right job


SimpleApiClient
class SimpleApiClient
Simple API Client class, wrapping HttpClient included in java.net package.


Though the brand level spend allocation is decided at the beginning of the year, it is constantly tweaked and adjusted across different channels throughout the year. Having this agility requires quick measurement of ROI and the ability to simulate different scenarios. FocusKPI’s ROI platform, customized for you, gives you this agility. Its robust and flexible infrastructure allows you to seamlessly connect to various data sources. Built-in algorithms help you analyze past performance and better understand the ROI of various investments. Optimization model with a user friendly interface gives you a peek into the future by simulating for various investment scenarios within minutes Our ROI platform helps you continuously monitor and maximize your return across all investments by providing a strong decision support to not just strategic but tactical decisions as well.


The S3ListPartsResult contains all the information about the listParts method. More...
Properties | |
| NSString * | bucket |
| The name of the bucket to which the multipart upload was initiated. | |
| NSString * | key |
| Tthe object key for which the multipart upload was initiated. | |
| NSString * | uploadId |
| The upload ID identifying the multipart upload whose parts are being listed. | |
| NSString * | storageClass |
| The class of storage used to store the uploaded object. | |
| S3Owner * | owner |
| The owner of the object that will be created from the parts. | |
| S3Owner * | initiator |
| The initiator of the multipart upload. | |
| int | partNumberMarker |
| The part number after which listing begins. | |
| int | nextPartNumberMarker |
| When a list is truncated, specifies the last part that should be skipped over to resume listing. | |
| int | maxParts |
| The maxParts which was supplied in the request. | |
| bool | isTruncated |
| Indicates whether the returned list of parts is truncated. | |
| NSMutableArray * | parts |
| The list of S3Part objects representing the parts. |
The S3ListPartsResult contains all the information about the listParts method.
- (NSString *) bucket [read, write, retain] |
The name of the bucket to which the multipart upload was initiated.
- (bool) isTruncated [read, write, assign] |
Indicates whether the returned list of parts is truncated.
A value true indicates the list was truncated. A list may be truncated if the number of parts exceeds the limit specified by MaxParts.
- (NSString *) key [read, write, retain] |
Tthe object key for which the multipart upload was initiated.
- (int) maxParts [read, write, assign] |
The maxParts which was supplied in the request.
- (int) nextPartNumberMarker [read, write, assign] |
When a list is truncated, specifies the last part that should be skipped over to resume listing.
Use this value for the partNumberMarker request property in a subsequent request.
- (int) partNumberMarker [read, write, assign] |
The part number after which listing begins.
- (NSString *) storageClass [read, write, retain] |
The class of storage used to store the uploaded object.
- (NSString *) uploadId [read, write, retain] |
The upload ID identifying the multipart upload whose parts are being listed.


Our School
Progress School of English was established in 2010 and offers quality general English language courses of all levels from Beginner to Advanced in a variety of programmes ranging from 2 weeks to academic year, as well as IELTS, Cambridge and TOEFL exam preparation courses.
The students are from various cultural backgrounds, mainly from within the EU, but also from countries like Brazil, Russia, Argentina, Korea, UAE and Egypt.
Our school is an ideal place to study English in Dublin. We are well situated on the South Side of Dublin, in Rathmines, one of the city's liveliest suburbs, just 10 minutes by bus from the city centre and served many different bus routes.


Routes, child-routes, their child-routes ad-infinitum.
A route is a path segment in the URL. A child-route is a new path segment under that route:
/route/child-route
The first-level must be a DIRECT child of the <x-app> element however, any declared deeper in the HTML will create child-routes.
Nested routes are declared statically using the <x-app-view> (and <x-app-view-do>) elements.
Child routes 'nested' or 'flat' format, depending on your taste.
Visit a deep nested route to see how it works.
Routes contain child-routes to semantically express their relationship using HTML.
You can also declare routes without nesting the elements, and use the url path explicitly.


Shorter legend names
- alias() function to specify a custom series name
- aliasByNode(2) to alias by a specific part of your metric
path
- aliasByNode(2, -1) you can add multiple segment paths, and
use negative index
- groupByNode(2, 'sum') is useful if you have 2 wildcards in
your metric path and want to sumSeries and group by
Series as parameter
- Some graphite functions allow you to have many series
arguments
- Use #[A-Z] to use a graphite query as parameter to a
function
-
Examples:
- asPercent(#A, #B)
- prod.srv-01.counters.count - asPercent(#A) :
percentage of count in comparison with A query
- prod.srv-01.counters.count - sumSeries(#A) : sum
count and series A
- divideSeries(#A, #B)
- If a query is added only to be used as a parameter, hide it
from the graph with the eye icon
Stacking
- You find the stacking option under Display Styles tab
- When stacking is enabled make sure null point mode is set to
'null as zero'
Templating
- You can use a template variable in place of metric names
- You can use a template variable in place of function
parameters
- You enable the templating feature in Dashboard settings /
Feature toggles
Max data points
- Every graphite request is issued with a maxDataPoints
parameter
- Graphite uses this parameter to consolidate the real number
of values down to this number
- If there are more real values, then by default they will be
consolidated using averages
- This could hide real peaks and max values in your series
- You can change how point consolidation is made using the
consolidateBy graphite function
- Point consolidation will effect series legend values
(min,max,total,current)
- If you override maxDataPoint and set a high value
performance can be severely effected


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Assign Subject Teacher
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x Second Teacher
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Save Subjects


pygraphc.misc package¶
Submodules¶
pygraphc.misc.IPLoM module¶
This is implementation of IPLoM method proposed by Makanju et al. in [Adetokunbo2009] and [Adetokunbo2012].
Original source of IPLoM from He et al. based on the reference [He2016a] and it is available on GitHub [He2016b]. We modify the original source to comply Python code style and add some methods to get cluster. The methods in this class has not documented and please refer to [He2016b] to get more complete descriptions.
References
| [Adetokunbo2009] | M. Adetokunbo, A. N. Zincir-Heywood, and E. E. Milios, Clustering event logs using iterative partitioning, Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2009, pp. 1255-1264. |
| [Adetokunbo2012] | M. Adetokunbo, A. N. Zincir-Heywood, and E. E. Milios, A lightweight algorithm for message type extraction in system application logs, IEEE Transactions on Knowledge and Data Engineering, 2012, 24(11), pp. 1921-1936. |
| [He2016a] | P. He, J. Zhu, S. He, J. Li, and R. Lyu, An evaluation study on log parsing and its use in log mining, Proceedings of the 46th Annual IEEE/IFIP International Conference on Dependable Systems and Networks, 2016. |
| [He2016b] | (1, 2) P. He, Logparser: A python package of log parsers with benchmarks for log template extraction. https://github.com/cuhk-cse/logparser. |
pygraphc.misc.LKE module¶
This is the implementation of Log Key Extraction (LKE) method [Fu2009].
The original code of LKE is provided by Pinjia He in his GitHub account [He2016c]. The methods in this class has not documented and please refer to [He2016c] to get more complete descriptions.
References
| [Fu2009] | Fu, Qiang, Jian-Guang Lou, Yi Wang, and Jiang Li., Execution Anomaly Detection in Distributed Systems through Unstructured Log Analysis, International Conference on Data Mining, vol. 9, pp. 149-158. 2009. |
| [He2016c] | (1, 2) P. He, Logparser: A python package of log parsers with benchmarks for log template extraction. https://github.com/cuhk-cse/logparser. |
-
class
LKE
(para, word_ll=[], word_len=[], groups=[], logline_num_per_group=[], word_len_per_group=[], word_occu_of_posi_lld=[], loglines_of_groups=[], flat_log_line_groups=[], new_groups=[])[source]¶


--- layout: default title: Contact ---
Don't hesitate to drop me a message either using the form below or directly mail me.


Every morning to help me get large!
And now that I'm grown, I eat five dozen eggs
So I'm roughly the size of a barge!"
When a character is training to get stronger, his routine will almost always involve drinking raw eggs at some point. It was originally believed that raw eggs have more protein than cooked eggs, and it makes the character look tough and determined since it takes a real hardass to down something so unpalatable.
It was later learned that cooking the egg fuses its protein strands together and increases the amount of protein that will be digested compared to a raw egg. Consuming raw eggs puts you at risk of salmonella poisoning (unless the eggs are pasteurized ahead of time), turning this into a Dead Horse Trope. Consequently, a common modern version is to have the character down the eggs and then immediately puke them up.
Note that some dishes are prepared by adding a raw egg to a hot dish just before serving. That is not this trope.
Made famous by Rocky, so this trope shows up frequently in Training Montages set to "Gonna Fly Now" or "Eye of the Tiger." See also Hideous Hangover Cure.
Examples
- Ed's father does this in Cowboy Bebop.
- Spoofed in Excel Saga when Pedro does it and then immediately spits them out.
- Saeba in City Hunter drinks raw eggs every morning.
- A thing the Red Hulk picked up with his tenure with The Avengers was eating raw eggs whole (as if he needed it; and even if the writers remembered the real-life rule, there'd be no problem since, as a Hulk, he's got a Healing Factor and since Red Hulk also can raise his temperature, they probably just end up cooking inside of him anyway). Noh-Varr seems to like these too (well, he is an alien).
- In one Peanuts strip, Charlie Brown adds a raw egg to Snoopy's dog food to give him a shiny coat. Snoopy doesn't like this.
Snoopy: BLAH!! So much for suppertime!
- Disney's Beauty and the Beast: In his Villain Song, Gaston mentions eating several dozen eggs for breakfast every day. Possibly with shells on.
Gaston: When I was a lad I ate four dozen eggs every morning to help me get large
and now that I'm grown I eat five dozen eggs so I'm roughly the size of a baaaaaaaaaarge! - In the Footrot Flats film, Wal begins his rugby training by smashing two handfuls of eggs together into a glass, drinks them down... and rushes off to the toilet to vomit them back up.
- In Stand by Me, this trope is subverted, where Lard Ass Hogan eats a raw egg to ready himself to vomit on cue.
- Rocky. The famous "egg-drinking scene" is the Trope Maker.
- In You Don't Mess with the Zohan, the Phantom hatches eggs and eats live full-formed chicks from them.
- As part of the Training Montage in Run Fat Boy Run, Dennis attempts to drink raw eggs. but immediately spits them back up.
- Referenced in the song "I Will Make You A Man" in The Rocky Horror Picture Show.
- Played for Laughs in Never Back Down. The protagonist and his best friend are shown drinking eggs during a training montage, and the friend immediately chucks them back up, to the dismay of the hero.
- Played for Laughs again in Grudge Match. Lightning gives Henry "Razor" Sharp a glass of raw eggs, and Henry asks him if fighters still do this.
- Parodied in They Call Me Bruce. The main character tries to do it but decides it would be better to make egg foo-young with them.
- Played reasonably straight in Hanna. After being on the run and having met up with Knepler, Hanna asks if she can have an egg when being offered breakfast, which she drinks raw, displaying both her survivalist roots and how badass she is.
- Also parodied in The Prize Fighter with Don Knotts and Tim Conway. Tim is Don's coach and tries to make Don drink raw eggs. Don demands Tim drink the eggs first to prove that it works and Tim ends up making scrambled eggs.
- Variant, for vocal powers instead of stamina ones: in Brazilian biopic Dois Filhos de Francisco, the children who will grow up to be a famous country duo (one of them, at least; the other dies young and is replaced by another brother) is forced to eat raw eggs by their father who wants them to be musicians.
- The serial killer protagonist in Hunting Humans mentions once having a neighbor who saw herself as a health nut, so she ate raw eggs every morning. He puts her out of her misery by poisoning a few of them.
- Jimmy King tries to do this in Ready to Rumble. He spits them back out.
- In the 1930s silent film I Was Born, But..., a boy brings a sparrow's egg to school and drinks it in front of his friends to show off how tough he is. This gets him in trouble and leads to him Standing in the Hall.
- In Miracle Run, Phillip tries to drink raw eggs like his hero Rocky, only to immediately vomit them back up.
- Downplayed-to-averted in the Mr. Men books. The text explains that "the more eggs Mr Strong eats, the stronger he becomes", but it doesn't specify raw. (The accompanying illustrations suggest fried or boiled, but the text doesn't actually specify that either.)
- Subverted and Played for Laughs in That '70s Show. Kelso attempts to impress Jackie by working out and during a conversation with her announces that he's going to drink a cup of raw eggs. She tries to say something and he rudely stops her, drinking the eggs anyway. When he's done, she reminds him that he's allergic to eggs.
- Lizzie McGuire's mother served her glasses of raw eggs as she trained for a rhythmic gymnastics competition, but Lizzie dumped the eggs into a frying pan instead of drinking them.
- An episode of Boy Meets World began with Shawn and Corey making some form of protein shake. Shawn suggests adding a raw egg. Corey, slightly disgusted, asks him why.
Shawn: Sylvester Stallone drinks raw eggs!
Corey: Yeah, and he's, like, five foot two.
 - In The Fresh Prince of Bel-Air, Will prepares to fight the guy who spun him on his head on the opening credits.
- Hal on Malcolm in the Middle trains for a race-walking competition by drinking a shake mixed with this, plus raw ground beef and some supplement powder.
- Trip tries this in Power Rangers Time Force in front of Circuit, who swiftly exclaims "that's just gross".
- SCTV did a parody of Rocky where boxer Hefty Neil (John Candy) cracks a half-dozen eggs into a glass - then pours them into a frying pan.
- World's Dumbest... Performers 11 has #2 downing a dozen raw eggs. He doesn't last long before puking them up. Naturally, Danny Bonaduce decides to do this himself — and doesn't vomit the eggs.
- Sylvester Stallone and David Letterman drank eggs on The Late Show while Stallone was on promoting Rocky: The Musical. Later in the show Letterman got Theo James (there to promote Divergent) to drink them too.
- Diff'rent Strokes: When Kimberly is training for the Olympics (she's a figure skater) Mr. Drummond feeds her raw eggs.
- This is Jin's signature meal in Kamen Rider Amazons, but it comes with at least some justification: he needs high amounts of protein to fight the Amazon craving for human flesh and to keep himself energised enough to stay transformed, and by necessity he eats them right before transforming so has no time to heat them. On at least one occasion he gives Haruka one for the same reasons.
- The music video for Decided to Break It by Marianas Trench includes plenty of raw eggs in the Training Montage the band has to go through.
- In A Very Potter Sequel, Dolores Umbridge is an impossibly strong, buff, 6ft+ woman. Apparently she used to be a "little booger like Hermione", with no self-confidence, but she became incredibly strong through a diet of "protein shakes, falcon eggs, and ROCKS". Presumably the falcon eggs were raw.
- Seymour on Sinfest drinks raw eggs as part of a Training Montage. The page image comes from this comic.
- Done in the Duck Dodgers episode about Queen and High telling anecdotes about Dodgers based on gags omitted form other episodes. One flashback has Marvin trying to invoke this trope, but finds out that Dodgers loves raw eggs and that the way he drinks it is too disgusting for poor Martian eyes.
- Steve Rogers apparently drinks raw eggs for breakfast in The Avengers: Earth's Mightiest Heroes!.
- Family Guy: In "New Kidney in Town", Peter Griffin makes his own energy drink. One ingredient is a raw egg, including the shell.
- Hey Arnold!:
- Harold tried drinking raw eggs while training for an arm-wrestling match, but they made him want to throw up.
- In another episode, as part of a Training Montage, Grandpa cracks some eggs in a glass... only to pour them into a skillet.
- SpongeBob SquarePants:
- In the episode "The Great Snail Race", SpongeBob puts Gary through Training from Hell to win the snail race. At one point, he mixes Gary an "energy drink" which includes raw eggs, simply "because they're cliché!"
- In another episode, "MuscleBob BuffPants", SpongeBob, wearing fake muscular arms to impress weightlifters at the beach, boasts "I start off with 20 raw eggs everyday. But that's just me."
- In Batman: The Brave and the Bold, Retired Badass Wildcat is shown using raw eggs in his "Tiger Tonic." Lampshaded when Batman points out that it's actually incredibly unsafe to consume raw eggs.
- South Park
- Subverted when Randy is trying to get in shape. In a scene lifted pretty much exactly out of Rocky, he gets up early, staggers into the kitchen, cracks a couple of eggs into a glass...and then pours them into a frying pan and starts scrambling them. While cracking open a beer.
- Also subverted in an earlier episode; Jesus must train himself for a boxing match against Satan, and he refuses Kyle's offer of raw eggs.
- In The Venture Bros., Hank gives Brock a glass of raw eggs when he starts training to get his secret agent license back. Brock suspects he spat in it.

Dean: It looks more like he's going to eat eggs and crap...eggs. - The Loud House: The episode The Loudest Yard gives a more realistic depiction of this trope.  Another instance of this trope occurs in "Sitting Bull", where Lynn has a couple of little kids she's babysitting guzzle down some raw eggs after making them do strenuous exercises. One of the kids is seen puking up the egg he swallowed later, to which Lynn remarks that it was a waste of "two perfectly good eggs", implying that the boy's sister likewise threw up her egg off-screen.
- Stōked: Part of Fin's Training Montage in "Dirty Little Secret, Nerdy Little Secrets". She throws up halfway through attempting to drink the eggs.
- Captain N: The Game Master episode "Videolympics" has a scene during a Training Montage where Kevin drinks a glass of several raw eggs, much to the disgust of his teammates. A regular contributor to The Annotated Series mocks this in a sing-along bonus video.
Don't drink eggs!
- King of the Hill episode "Bill, Bulk and the Body Buddies" has Bill hiring three meatheads as his personal trainers while preparing for his army physical and he gets so into his weight lifting regimen that he ruptures his rectum while doing leg presses. Unaware of his injury, the meatheads just think Bill is fatigued and they pour raw eggs down his throat via a funnel to give him a boost. Needless to say it doesn't help.
- Parodied in the VeggieTales episode "Sumo of the Opera":
Italian Scallion (Larry the Cucumber): [upon being given a glass full of raw eggs] Yuck! I'm supposed to drink this?
Mikey (Pa Grape): Of course not! They're raw! Ya scramble them!
[the chef proceeds to dump the eggs into the frying pan]


AWS Reinvent 2015 Findings and Sessions
For Adobe/Oz, AWS Re:invent 2015 was the occasion for several important announcements. Primary themes this year:
- Major Enterprise conversions from hosted to cloud
- Business analytics offerings
- Internet of Things Platform
- Deployment Tooling and Orchestration management
- Serverless platforms - no server is easier to manage than ‘no server’
A few of the interesting product announcements were:
- Amazon Inspector - security assessment tool
- Lambda extensions - VPC, 5 minute max from 60 sec, Scheduling
- ECS Registry - out later this year.
- QuickSight - business analytics tool
- MariaDB - next gen iteration MySQL
- IoT - AWS platform, this was an unpleasant surprise for the IoT startups attending
- Kinesis Firehose - get big volumes of data into Kinesis… value for Kinesis user base
- Snowball - accelerate enterprise conversion to cloud. one Customers’ Petabyte legacy stores would otherwise take “8 years” to transfer over wire.
Missing (at least for us) was a hope of.
- AWS hosted MongoDB
- Lambda support for ruby (we got python instead)
The serverless platform theme is especially interesting, external customers reported a 2X order of magnitude reduction in costs. The implicit bargain we see here is cost reduction in exchange for vendor lockin. AWS is a big absorber of open source solutions but is pointedly not making Lambda available as open soure, keeping the proprietary edge.
There were complaints from startups about Amazon announcements that collided with the emergent AWS ecosystem. Amazon response here is that they warn companies not to develop ahead of their roadmap. Problem is that AWS roadmap changes quickly and can be difficult to know what is coming.
We at Oz/Adobe have seen this as well, probably makes sense to check in regularly with AWS Adobe contacts on AWS Roadmap with our partner status to avoid inventing.
I did one bootcamp.. the scalable Microservices automation pipeline camp. The full AWS CI toolchain with Jenkins, DockerHub and ECS. My progress included:
- start with reference weather / stock type microservice
- CodePipeline - model/setup build test and deploy
- AWS CodeDeploy/CLoudformation - continuous deploys to a fleet (old Apollo amazon internal tool)
- Jenkins - we were given a jenkins server for tests
- build Docker containers from CLI
- Push to Dockoer Hub
- Deploy Service on ECS
- tests run on production
- integrate Consul for service discovery
AWS Reinvent
AWS official Summary of last weeks announcements: AWS Week in Review
Some Top Level Sessions/Summaries
Jeff Barrs summary of all the big announcements coming from AWS: Jeff Barr Reinvent
AWS Reinvent 2015 Youtube Channel page: AWS Reinvent YouTube Channel
Werner’s Keynote, some big-picture great insights here, I would say worth watching the whole session. Werners Keynote
Werner referred to this seminal paper written in the 1960’s on the management of complexity: Archicture Of Complexity,
Slideshare Pressos:
All 250+ of Reinvent2015Slideshare decks/summaries: AWS Revinvent Slideshare
Ops/DevOps/Infra
Docker corp’s single presso this year at re:invent: Docker, Compose, Machine, Swarm, and ECS CLI
dvo303 scaling infrastructure operations with aws
dvo201 scaling your web applications with aws elastic beanstalk
cmp310 data processing pipelines using containers spot instances
dvo315 log monitor and analyze your it with amazon cloudwatch
dvo301 aws opsworks under the hood
cmp201 all you need to know about auto scaling
stg304 deploying a disaster recovery site on aws
net308 consolidating dns data in the cloud with amazon route 53
sec314 aws for the enterprise implementing policy governance security
dev301 automating aws with the aws cli
Architecture
bdt404 largescale etl data flows waws data pipeline dataduct
net302 delivering a dbaas using advanced-aws networking
sec403 diving into aws cloudtrail events w apache spark on emr
arc303 pure play video ott a-microservices-architecture
stg312 amazon glacier deep dive - cold data storage in aws
stg206 using amazon cloudfront for your websites apps
mbl402 mobile identity management data sync-using amazon cognito
cmp403 aws lambda simplifying big data workloads
Microservices
arc303 pure play video ott a microservices architecture
Performance/Optimization
net404 making every packet count
stg406 using s3 to build and scale an unlimited storage service
stg312 amazon glacier deep dive cold data storage in aws
stg206 using amazon cloudfront for your-websites apps
arc301 scaling up to your first-10 million users
Cost Optimization
arc302 running lean architectures optimizing for cost efficiency
ism402 cost optimization at scale
mbl402 mobile identity management data sync using amazon cognito
Using Spot Instances to lower costs and get more capacity
Security
sec326 security science using big data
sec324 introducing amazon inspector
sec316 your architecture with security incident response simulations
spot303 security operations at massive scale
sec320 leveraging the power of aws to automate security compliance
sec402 enterprise cloud security via devsecops 20
Mobile
mbl402 mobile identity management data sync using amazon cognito
mbl309 analyze mobile app data and-build-predictive applications
Big Data/EMR
mbl402 mobile identity management data sync using amazon cognito
arc301 scaling up to your first 10 million users
Enterprise/Migration
spot210 zyngas journey back to the aws cloud
sec325 satisfy pci obligations while continuing to innovate
dat304 amazon rds for mysql best-practices
ism305 framework create cloud strategy accelerate results
ism215 why brooks brothers moved their production sap to aws
dat205 new launch introduction to aws database migration service
sec321 implementing policy governance security for enterprises
Internet of Things
mbl308 extending alexas builtin skills see-how capital one did it
mbl203 drones to cars connecting the devices in motion to the cloud
mbl204 state of the union iot powered by aws
mbl305 you have data from the-devices now what getting the value of the iot
Deep/Machine Learning
mbl309 analyze mobile app data and build predictive applications
cmp305 deep learning on aws made easycmp305
Management
ism207 how the principles of lean-transform innovation
Research/Edgy/Misc Topics
dat203 building graph databases on aws
dev201 aws sdk for go gophers get going with aws
spot203 fourth annual startup launches hosted by werner vogels
mbl310 alexa voice service under the hood
spot208 how to sponsor a diversity circle in a tech workplace
External press:
AWS reInvent 2015 to focus on cloud management security
container management and monitoring dominate amazon reinvent
New Amazon Elasticsearch service eases setup-with exceptions
day two of re invent one cloud ring to rule them all


| AutotunerPID Toolkit |
| Layout of the Control System | Overview of the control system simulated by the AutotunerPID Toolkit |
| Setting up the Simulation |
Summary of the most important steps to set up the initial condition for the simulation |
| PID Control Panel |
Description of the interface to control the PID behavior |
| Environment Panel |
Description of the interface to control the environment behavior |
Layout of the Control System
The AutotunerPID Toolkit simulates a single SISO control loop, which includes a PID with autotuner, the plant to be controlled, a lowpass filter and some auxiliary blocks to manage the simulation (for example change the set-point or perform the autotuning or include a measurement noise).
The main component of the Toolkit is the Simulink file autotunerPID.mdl
The following sections describe the role of each blocks in the model. You can view the general AutotunerPID Function reference in Function Reference.
| Note For more information about PID Autotuning, see Introduction to PID Autotuning. |
PID with Autotuning
The regulator is a subsystem composed by two S-functions: pid_isatd.m which implements a discrete time ISA-PID and pid_autotuner.m which takes in charge the autotuning process.
Discrete time ISA-PID (pid_isatd.m)
The discrete time ISA-PID includes the filter on the derivative action, the set-point weight (but not the weight of the derivative action which is fixed to c=0). Moreover the PID implements antiwindup on lower and higher saturation limits of the actuator and bumpless auto-manual switch. The structure of this "industrial PID" is more complex than the structure of the "scholastic PID" and it closely resemble the functioning of regulators used in practice.
Autotuner Supervisor (pid_autotuner.m)
The autotuner supervisor, instead, rules out the autotuning process mainly performing the identification of a FOPDT process model (idareas.m) or a set of characteristics (pid_autotuner.m) and the synthesis of the new parameters with the methods described (pid_tuning.m). Moreover it is possible to constrain the structure of the regulator to be a PI or a PID, or the structure can be automatically selected by the supervisor (pid_structure.m). In particular, the identification experiment includes both step response and relay response with tunable hysteresis and amplitude.
Plant
The plant is a subsystem which model the process that must be controlled
The structure of the plant has been left open by purpose. The user can thus include his own plant in the simulator since there is no constrain on it: the plant can be linear or nonlinear, continuous or discrete time and so on. However, the comparative analysis of a step responses and Bode diagrams is available only for linear plants (for obvious reasons).
| Note The comparative analysis is available only when the model is NOT running and for linear plants. Moreover the name of the blocks inside the Plant subsystem should not be changed since they are used as references in the functions performing this analysis |
PID Control Panel
The PID Control Panel is implemented through a masked S-function (autogui.m), which uses the graphical primitives of the MATLAB environment to create a GUI which has a close feeling to that of a real PID. The aim of this interface is to provide all the inputs and outputs typical of a real industrial PID.
Environment Panel
The Environment Panel is implemented through a masked S-function (envgui.m). It controls the parameter of the simulation which are not under direct control of the user, so that they cannot be included in the PID control panel. For example a measurement noise or a step on the load disturbance can be included.
Moreover, through the environment control panel, a comparative analysis of all the autotuning methods can be performed, both in time domain and in frequency domain.
Butterworth Analog Filter
The lowpass Butterworth analog filter in the control loop is used as an antialiasing filter and also to reduce the effects of the measurement noise. The order of the filter and the bandwidth can be set by the user (butterdesign.m).
Service Blocks
The remaining blocks are inserted just to have a fully functional environment.
| Note The GUIs control the value of the set-point, load disturbance and measurement noise through a reference to the name of the corresponding blocks. It is suggested that you DON'T change the name of this block. If you do this, you must also change the references in the masks of the block "PID Control Panel" and "Environment Panel" |
| Synthesis methods | Setting up the Simulation |


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tell
Syntax
An tellStatement is:
| |
tell : fileNumber , filePositionVar |
Description
The tell statement sets filePositionVar, whose type must be int, to the current offset in bytes from the beginning of the specified file. The fileNumber must specify a file that is open with seek capability (or else a program argument file that is implicitly opened). The tell statement is useful for recording the file position of a certain piece of data for later access using seek.
Example
This example shows how to use tell to record the location of a record in a file. This location is later used by seek to allow the record to be read.
var employeeRecord :
record
name : string ( 30 )
pay : int
dept : 0 .. 9
end record
var fileNo : int
var location : int
open : fileNo, "payroll", write, seek
tell : fileNo, location % Make note of this location
write : fileNo, employeeRecord % Write record at this location
seek : fileNo, location % Go back to location
read : fileNo, employeeRecord % Read the record
% that was previously written
See also
the read, write, open, close, seek, get and put statements.


| As You Like It | Comedy | |
| All's Well that Ends Well | Comedy | 1601 |
| Hamlet | Tragedy | 1604 |
| Macbeth | Tragedy | 1606 |
| Romeo and Juliet | Tragedy | 1595 |
| Henry IV, Part I | History | 1596 |
| Henry V | History | 1599 |
| Henry 2 | History | 1599 |
| Henry 3 | History | 1599 |
| The Fair Youth | 1–126 |
| The Dark Lady | 127–152 |
| The Rival Poet | 78–86 |


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Reconstructed photon matching a simulated photon:
GED based photon isolation: contribution from charged hadrons.
The distribution is for ecal barrel only.
|
Reconstructed photon matching a simulated photon:
GED based photon isolation contribution from charged hadrons.
The distribution is for ecal barrel only.
|
Reconstructed photon matching a simulated photon: GED based photon isolation: contribution from charged hadrons
The distribution is for ecal endcaps only.
|
Reconstructed photon matching a simulated photon: GED based photon isolation: contribution from charged hadrons
The distribution is for ecal endcaps only.
|


Evolving the Mona Lisa
Welcome! Click start to see genetics in action, as a
randomly generated collection of shapes evolve to resemble
a given picture.
How it Works
This page uses a genetic algorithm to model a population
of individuals, each containing a string of DNA which can
be visualised in the form of an image. By starting with a
population consisting of a randomly generated gene pool,
each individual is compared against the reference image
(the one on the left), and the individuals can then be
ranked by their likeness to it, known as their "fitness",
with the best fit being displayed on the output image (the
one on the right). By breeding the fittest individuals
from the population, the DNA which produces the most
accurate representation of the reference image is selected
over successive generations, effectively demonstrating the
power of a natural selection process to produce the best
candidate for any given environment.
Source Code
As with all good things in life, this was created for fun, free,
and science. The full source code for this site is available on
GitHub
and is released under the terms of the MIT License. If you just want
to see how the genetics algorithm works, you can see the JavaScript
implementation
here.
Bugs and comments
I would love to know what you think. Don't be afraid of
getting in touch with any
thoughts and suggestions. If you would like to be a little more
involved in the process, feel free to fork the
source code repository
and submit a pull request.
Credits
The code is my own, the idea is not. Full credit goes to
Roger Alsing
for the idea of using genetic algorithms to approximate fine
art. Further thanks to
Jacob Seidelin
for writing a JavaScript implementation that inspired me to
create this.


TeamUp
Find the right people for your project
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{% extends "email-layout.html" %} {% block body %} This is the list of packages updated in PyPI listed in your projects' requirements.txt files. {% include 'update_list.html' %} Cheers. http://www.pypi-notifier.org {% endblock %}


Chapter 4 Solutions
4.1
- The utility function, \(U(t,s)=\sqrt{ts}\), is really just Cobb-Douglass utility with \(\alpha = 0.5\) and \(\beta = 0.5\), so using the solution we derived in the notes,
\[t^* = \frac{I}{2p_t} \text{ and } s^* = \frac{I}{2p_s}\].
Substituting in for \(I= 1, p_t = 0.10,\) and \(p_s = 0.25\), we find the solution, \(t^* = 5,\) and \(s^* = 2\).
- Indirect utility is useful here.
\[V(p_t, p_s, I) = \frac{I}{2p_t^{0.5}p_s^{0.5}}\]
Increase income by \(k\) to achieve same utility level. To find, we solve for \(k\) in the following equation,
\[V(0.40, 0.25, 1+k) = V(0.10, 0.25, 1)\],
or in plain English, solve for \(k\) such that the utility achieved under the new prices and additional income is the same as the utility achieved with the old prices and income.
Solve:
\[\begin{align*} \frac{1+k}{2*0.40^{0.5}*0.25^{0.5}} &= \frac{1}{2*0.10^{0.5}*0.25^{0.5}} \\ k &= \frac{0.40^{0.5}*0.25^{0.5}}{0.10^{0.5}*0.25^{0.5}} - 1 \\ k &= $1 \end{align*}\]His mother should send $2, a $1 increase.
4.2
- \(w_F^* = \frac{\alpha}{\alpha + \beta} \frac{I}{p_F}\), and \(w_C^* = \frac{\beta}{\alpha + \beta} \frac{I}{p_C}\)
Substitute in the parameters given in the problem.
\[\begin{align*} w_F^* &= \frac{2}{3} \frac{600}{40} \\ &= 10 \end{align*}\] \[\begin{align*} w_C^* &= \frac{1}{3} \frac{600}{8} \\ &= 25 \end{align*}\]- California wine purchased stays the same, but now French wine purchased is,
Because the French wine is now cheaper she can buy more for the same income and achieve higher utility. To put a monetary value on it, check how much she would be willing to reduce her income in order to face the new (lower) prices.
\[V(20, 8, 600-k) = V(40, 8, 600)\],
she is willing to reduce income by as much as \(k\) to get the new lower price.
\[\begin{align*} \left( \frac{2}{3} \right) ^{\frac{2}{3}} \left( \frac{1}{3} \right) ^{\frac{1}{3}} \frac{600-k}{20^{\frac{2}{3}}8^{\frac{1}{3}}} &= \left( \frac{2}{3} \right) ^{\frac{2}{3}} \left( \frac{1}{3} \right) \frac{600}{40^{\frac{2}{3}}8^{\frac{1}{3}}} \end{align*}\]solving for \(k\)
\[\begin{align*} 600 - k &= \frac{600*20^{\frac{2}{3}}8^{\frac{1}{3}}}{40^{\frac{2}{3}}8^{\frac{1}{3}}} \\ k &= 600 - \frac{600}{2^{\frac{2}{3}}} \\ k &= 222.02 \end{align*}\]An alternative monetary measure would be to check how much she would be willing to accept (increase income) to keep the old prices. This is equivalent to the concepts if equivalent variation and compensating variation that are presented in chapter 5.
4.3
In this problem his consumption of \(c\) and \(b\) is constrained so that \(c+b = 5\). We can use a Lagrangian function to solve the constrained optimization problem.
\[\mathscr{L} = 20c - c^2 + 18b - b^2 + \lambda[5-c-b]\]
The first order conditions of the Lagrangian problem are:
\[\begin{align*} 20 - 2c - \lambda &= 0 \\ 18 - 6b - \lambda &= 0 \\ 5 -c -b &= 0 \end{align*}\]solving for \(b\) and \(c\) gives \(b = 1\) and \(c = 4\).
4.4
- Maximising \(U(x+y)= x^2+y^2\) won’t alter the results because MRS is unchanged under a monotonit increasing transformation.
\[\mathscr{L} = x^2 + y^2 +\lambda[50-3x-4y]\]
The first order conditions of the Lagrangian problem are:
\[\begin{align*} 2x - 3\lambda &= 0 \\ 2y - 4\lambda &= 0 \\ 50 - 3x - 4y & = 0 \end{align*}\] Combining eqns 1 and 2, \(\frac{x}{y} = \frac{3}{4}\). Substituting in to equation 3, the budget line, we get:\[\begin{align*} 50 &= 3 \left( \frac{3}{4}y \right) + 4y \\ 50 &= \frac{9y}{4} + 4y \\ 50 &= \frac{25y}{4} \\ \end{align*}\]
So, \(y = 8\) and \(x = 6\).
Since the indifference curves are not convex, the solution to the problem is actually a local minimum, not a local maximum!
4.7.
This graph is in our lecture notes.
The expenditure required to achieve utility of 2.
The expenditure required to achieve utility of 3.
\[\begin{align*} e(p_x, p_y, U) &= 2p_x^{\frac{1}{2}}p_y^{\frac{1}{2}}U \\ e(1, 4, 2) &= 2*1^{\frac{1}{2}}*4^{\frac{1}{2}}2 \text{ using example 4.4 prices}\\ &= \$8 \end{align*}\] \[\begin{align*} e(1, 4, 3) &= 2*1^{\frac{1}{2}}*4^{\frac{1}{2}}3 \text{ using example 4.4 prices}\\ &= \$12 \end{align*}\]So it is $4 extra (\(\$4 = \$12 - \$8\))
- Assuming the same expenditureof $8, how much would we have to subsidise \(x\) to achieve utility of 3? Solve the following:
Solving yields \(s = \$\frac{5}{9}\). To calculate the cost to the government, multiply by the quantity of x purchased.
\[\frac{5}{9}x^* = \frac{5}{9}\frac{8}{2(1-\frac{5}{9})} = \$5\]
If the objective is to raise utility from 2 to 3, it is cheaper for the government to give an income grant of $4 than to subsidise the purchase of \(x\), because that would cost $5.
This is the lump sum principle.
- The general expediture function for Cobb-Douglas utility is given by \(e(p_x, p_y, U) = \frac{p_x^{\frac{1}{2}}p_y^{\frac{1}{2}}U}{\alpha^{\alpha} \beta^{\beta}}\), and for \(\alpha = 0.3\), the quantity \(\alpha^{\alpha} \beta^{\beta} \approx 0.543\).
So, achieving utility of 2 requires
\[e(1, 4, 2) = \frac{1^{0.3}*4^{0.7}2}{0.543} = 9.774\]
while achieving utility of 3 requires
\[e(1, 4, 2) = \frac{1^{0.3}*4^{0.7}3}{0.543} = 14.66\]
which is $4.89 extra.
- Because there are no substitution effects in the fixed proportion case, the optimal point would be the same and also the cost to govt would be same.
4.10
- The solution to a utility max problem with \(U(x,y) = x^{\alpha}y^{1-\alpha}\) is
\[x^* = \alpha\frac{I}{p_x} \text{ and } y^* = \beta\frac{I}{p_y}\]
Then indirect utility is\[\begin{align*} V(p_x,p_y, I) &= \left[ \alpha\frac{I}{p_x} \right]^{\alpha} \left[ \beta\frac{I}{p_y} \right]^{\beta} \\ &= \alpha^{\alpha}(1-\alpha)^{\alpha}\frac{I}{p_x^{\alpha}*p_y^{\beta}} \end{align*}\]
- Since the indirect utility function is right in front of us, we can use duality to derive the expenditure function from the indirect utility function.
Since income is equal to expenditure, we replace \(I\) with \(e(p_x,p_y,\overline U)\), and replace \(V(p_x,p_y, I)\) with \(\overline U\).
\[\overline U = \alpha^{\alpha}(1-\alpha)^{\alpha}\frac{e(p_x,p_y,\overline U)}{p_x^{\alpha}*p_y^{1- \alpha}} \]
Now, solving for \(e(p_x,p_y, U)\)
\[e(p_x,p_y, U) = \frac{p_x^{\alpha}*p_y^{1- \alpha}* \overline U}{\alpha^{\alpha}(1-\alpha)^{\alpha}} \]
The compensation required to offset the effect of a price rise of \(x\) can be expressed as
\[\begin{align*} e(p_x^1,p_y, \overline U) - e(p_x^0,p_y, \overline U) = \frac{\left(p_x^1\right)^{\alpha}*p_y^{1- \alpha}* \overline U}{\alpha^{\alpha}(1-\alpha)^{\alpha}} - \frac{\left(p_x^0\right)^{\alpha}*p_y^{1- \alpha}* \overline U}{\alpha^{\alpha}(1-\alpha)^{\alpha}} \end{align*}\]This expression obviously varies with \(\alpha\) and the higher the \(\alpha\) the more compensation needed. One could attempt to differentiate this expression with respect to \(\alpha\) but that would be a yucky derivative so we’ll skip it.


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