October 15, 2018
Partially updated: December 10, 2018
"Oh that's nice" - Teddy Rendahl.
Recall back in early 2017 I released my first shot chart post. Well, after a year and a half and with some free time on my hands after returning from my trip to Africa, I figured it was time to make some much needed updates to the ol' shot chart machine and accompanying Twitter bot as I am now (slightly) less dumb, (slightly) more compotent, and have a (slightly) better understanding of the NBA, or I at least hope (at least one of) these things are true.
If you've only come to look at pretty pictures, then click here for all player charts or click here for all team charts. If you'd like to read on, this post is divided into a few sections, follow any links to jump to that portion of the write-up.
To best describe these charts, we will use a labeled example chart, and explain the significance of each label. For the example, let's use what is arguably the greatest single season shooting effort in NBA history, Stephen Curry's breath-taking, earth-shaking, record-breaking, history-making 2015/16 season.
The first thing to notice about this chart is how ridiculous of a season it was. It is easily the top PAA season in my database, worth 405.9 PAA; 86.2 points higher than the next best season, which is more than the difference between second place (Shquille O'Neal's 1999/2000 season) and the 11th best season on record. What's also astonishing is that Curry did this primarily via outside shooting while most of the other top seasons are from guys who can dominant the paint (primarily Shaq). The top-15 best seasons by this metric contain the following names: Shaquille O'Neal (6 seasons), LeBron James (2 seasons), Stephen Curry (2 seasons), DeAndre Jordan (2 seasons), and a single season each from Peja Stojakovic, Amar'e Stoudemire, and Steve Nash.
Moving on, we notice seven labels (A through G):
A: This is the title of the chart. It appears fairly straightforward, but there is one unique aspect, the dark red color. This color corresponds to the player's EFG+ percentile with the higher the percentile, the darker the color. Since Curry's season was in the 100th percentile, his color is the as dark red as possible (on the other hand, a player in the 0th percentile, would have their name in white).
B: The date the chart was plotted, so it is possible to tell when a chart is out of date.
C: Key for the size of the hexagons. Similar to the title of the chart, the color of this key corresponds to the player's EFG+ percentile with the higher the percentile, the darker the color.
D: Color bar key. The color is again based on a player's EFG+ for each zone. For example, if a player shoots 40% from a 3-point zone, that zone will be darker red than a 40% 2-point zone.
E: A listing of the date-range that the chart and the teams the player played for over that range.
F: Percentiles for four categories; volume as measured by FGA/Game (Field Goal Attempts per Game), shooting skill as measured by ShotSkill+, efficiency as measured by overall EFG+, and efficiency value added as measured by PAA/Game.
G: A player's Favorite Zone as measured by z%+, Best/Worst Skill Zones as measured by zEFG+, and Best/Least Value Zones as measured by zPAA.
Let's compare Curry's chart to other charts from that showcase a few different season types for high volume players (click on image to see full-size):
Three very different looking shot profiles, but all three were high usage players who finished in the 95th percentile or higher in terms of shot skill, efficiency, and value added.
LeBron James (2012/13) dominated with his finishing close to the basket to rack up 285 zPAA in the Restricted Area.
Peja Stojakovic (2003/04) destroyed every zone beyond the arc but was especially fond of the Corners, where he took 152% more shots than an average distribution (z%+).
Nikola Jokic (2016/17) used his soft touch to shoot 56% better than league average (zEFG+) in the typically awkward Non-Restricted Area of the paint.
Smart shot selection boosts these players efficiency value, even while they were non-outstanding players by ShotSkill+. Personally, I like to think of these players as the basketball representation of Simpson's Paradox.
Quentin Richardson (2004/05) was a below average shooter (95 ShotSkill+, 41st percentile). Even in his most skilled zone (Above the Break 3), he was only 3% above the average NBA player. However, due to his shot selection (primarily shooting 3s and dunks/layups), he still managed to generate positive efficiency value for the season (0.4 PAA/Game).
Nicolas Batum (2011/12) was a skilled shooter (64th percentile by ShotSkill+), but produced upper echelon efficiency value (92nd percentile by PAA) by heavily favoring shooting from the Corner 3 zones (298 z%+).
Shawn Marion (2007/08) was similar to Batum in that he had above average skill (68th percentile by ShotSkill+), while generating tons of value (97th percentile by PAA). However, Marion generated his value with great skill finishing around the rim (111 zEFG+, 125 zPAA in the Restricted Area).
An affinity for the Mid Range drags down the efficiency value for these players, all of whom are talented shooters.
DeMar DeRozan (2016/17) is the poster child for this group; 75th percentile in ShotSkill+, but his extreme favoring towards the two least valuable zones (Mid Range and Non-Restricted area of the paint) ruin his efficiency (28th percentile in EFG+). (NOTE: As mentioned below, my metrics will generally underrate players like DeRozan more than any other, due to most of his true value coming from free throws and volume scoring).
LaMarcus Aldridge (2013/14), you can basically copy and paste what was said about DeRozan and put it here for Aldridge. However, his efficiency has generally improved after moving to San Antonio, maybe the same will happen for DDR.
Jamal Crawford (2016/17), even at 36 years old, Crawford was still an extremely talented player (111 ShotSkill+, 92nd percentile). Unfortunately, his shot selection hadn't adapted to the more efficient modern NBA (93 EFG+, 30th percentile).
Generally, players in this class can be described as "chuckers" and would have been better off taking a lower volume of shots.
Emmanuel Mudiay (2015/16) had a terrible rookie season. He failed to generate positive efficiency value from a single zone (his Best Value Zone was worth -9 zPAA).
Josh Smith (2013/14) managed to negate all value he created with his above average finishing in the restricted area by chucking up bricks from every other zone on the court.
Andray Blatche (2010/11). It's rare for a big man to below below league average at finishing in the Restricted Area, but Blatche managed to do this, finishing with a 98 zEFG+ in his Best Skill Zone.
Effective Field Goal Percentage Plus is an index metric comparing a player's Effective Field Goal Percentage to the league average, where 100 is average. An EFG+ of 125 is 25% better than league average, while an EFG+ of 75 is 25% worse than league average.
Points (Added) Above Average is a basic measure of the number of points a player has added via his shooting. The general formula is Efficiency x Volume.
Shot Skill Plus measures the amount above or below league average a player performed at shooting given his shot profile, where 100 is average. A ShotSkill+ of 125 means that a player made 25% more shots than we would expect an average player to make given the same shots.
Zone Percentage is the percentage of shots a player takes from a given zone.
Zone Percentage Plus compares the a player's distribution of shots to league average, where 100 is average. A z%+ of 125 from a zone means that a player's distribution of shots featured 25% more shots from that zone than the league average distribution.
Zone Effective Field Goal Percentage Plus compares a player's shooting percentage in a zone to league average, wher 100 is average. A zEFG+ of 125 from a zone means that a player was 25% better than league average at shooting in that zone.
Zone Points (Added) Above Average measures how many points added or subtracted a player has added via his shooting in that zone. Most players will have positive zPAA in the efficient zones (notably the Restricted Area and Corner 3) and negative zPAA in inefficient zones (notably the Mid Range).
I have leaderboards for the statistics I created. If there's a statistic not on here that you'd like to see, or you have a specific data request, feel free to e-mail me.
You can also download any of this data as .csv from my github.
Dec.10, 2018 Update: I added a column for Points Above Replacement (and Points Above Replacement per Game), which does a better job of capturing volume for volume shooters. Replacement Level is set as the EFG% of the worst team in the season that season.
Free Throws: My metrics and charts do not account for any value gained via drawing and shooting free throws. As a few notable players have demonstrated, this is a very valuable and repeatable skill.
Accounting for Volume: We know that in general, a player's efficiency declines as usage increases (an inverse Jevons Paradox if you will). My metrics don't account for this. Therefore, a high volume, slightly below average efficiency player will score very low by the PAA metric, even though we know them to be valuable offensively (think of players like Allen Iverson or Russell Westbrook).
Role/Positional Consideration: All averages and percentiles are based on the entire set of NBA players, instead of being divided up into groups by position or role. Therefore, it is very difficult for a small Point Guard to grade out as above average at finishing in the restricted area even if they are better than most other guards. It is similarly very easy for a plodding Center to be described as an above average finisher there, even if they are worse than most other big men.
Passing, Defense, Off-Ball Play, and More: There are obviously many other ways to contribute value on a basketball court, and none of them are considered by these metrics. If you're looking for a metric that is more all-encompassing, I would suggest checking out any of the Plus-Minus, On/Off, or WOWY based metrics.
Custom Charts: I have a script that can generate "custom" charts, based on custom date-ranges, Pre-Season/Playoff shots, multiple players, etc. Unfortunately, it uses a lot of bad legacy code, takes a long time, and is not compatible with my newer suite of metrics. Hopefully I'll find to update this script during the season as it is especially fun to play around with during the playoffs.
Similarity Scores: I've always wanted to make some form of a similarity score to find the player's with the most similar shot profiles but it's never been my top priority so I haven't tackled it yet.
Gather Positional/Physical Data: Gathering data on a player's listed position and his physical profile would allow me to bin players based by bigs/wings/guards, or better, create a model to determine player roles when joined with their shot profile. This would allow for better comparisons and percentile baselines based on role.
Playoff/Pre-Season Charts: I have the data to automate the generate of pre-season and playoff charts, but I'm not sure if it's worth the computing energy. If this is something anybody is interested in, let me know and I'll set it up.
WNBA and G-League Charts: I have the API calls to get shot location data for the WNBA and G-League, but I never decided on the best method for data storage. Should I make new tables? Set up a new database? Just add in new fields that signify league? The best answer is probably new tables. Still, I haven't had the motivation to do this yet since I don't follow either league outside of the playoffs and occasional regular season game.
Improve the ShotSkill+ Model: Right now, the ShotSkill+ model is based on comparing a player's performance in each subzone to the NBA average. However, I could use a more predictive method based on shot distance/angle that would improve the model (the best method would be to get more data, such as nearest defender distance, nearest defender height/length, pre-shot player movement, pre-shot ball movement, etc.). However, I've left the model as is, using the idea that when compared to a better model, what I have right now was 10% of the work while capturing 90% of the signal.
As always, the code for all of the charting tools are available on github. Any further questions can be sent to me at connor.reed.92@gmail.com.


WOMBAT 2016 Wrap Up
06 Mar 2016 Blag rbloggersA few weeks ago I spoke at the Workshop Organized by Monash Business Analytics Team (WOMBAT), held in the Melbourne Zoo (!) on Thursday and Friday the 18th and 19th February.
It was my first time at the Melbourne Zoo, and my first time having a conference in a Zoo. It was a pretty surreal experience briskly walking to the conference room while trying to navigate a zoo, passing monkeys, macaws, and tigers. And during the lunch breaks you could sit down and chat with other conference attendees…or go and see the Orangutan show, watch the elephants get a clean, or see some Gorillas.
Two other colleagues from QUT also attended, Amy Cook (as a contributed speaker), and Dr. Zoé van Havre (as an invited Speaker). Amy is currently completing a Masters by research in statistics, and Zoé has just finished her PhD in Statistics and is about to complete a Post-Doc at CSIRO.
The conference was organised by Di Cook and Rob Hyndman, of the Monash Business School. Di Cook is well known for her work in visualisation and software. Di also supervised both Hadley Wickham and Yihui Xie. Hadley has improved the R experience drastically with packages ggplot2, dplyr, tidyr, and devtools. Yihui wrote the package knitr
, making reproducible reporting easy and fun to do in R. Rob Hyndman is the creator and maintainer of the forecast
package, and has written a free online textbook on forecasting.
Hadley Wickham was they Keynote speaker for the conference. Hadley’s talk discussed one way to go about summarizing large datasets by fitting many models using purrr
. purrr
takes a functional programming approach so you emphasises the verbs in your data anyalsis. This approach means that you can avoid writing loops so that you emphasize actions rather than book keeping. I had always been told that you should avoid writing loops in R because they are slow. However, Hadley said the following about that when asked about performance differences between apply, purrr, and for loops:
A lot of people tell you to not use for-loops because they are slow - that is complete and utter garbage. You should not use for loops because they are not very expressive. The speed is almost the same for any trivial operation. The overhead of a for-loop is not significant. The reason to avoid for loops is because they make your code harder to read and harder to write.
So why do we hear that loops are slow in R? Apparently it is an Historical Hangover from the S language, and the early days of R. Credit to Thomas Lumley for pointing this out.
The conference organisers filmed the keynote talk from Hadley, and you can watch the video here and see Hadley’s slides here. I Highly recommend watching the talk.
Zoé delivered an awesome talk that was really appropriate for the audience and did a great job of condensing 4 years of her PhD on Bayesian Mixture Models into something that everyone could understand. It was also very satisfying to see Zoé answer the question at the end “How did you choose your prior?” in excellent style, clearly demonstrating the depth of her knowledge on Bayesian stats. It was clear that Zoe could communicate “bleeding edge” statistics in a technical and non-technical sense. Awesome job. You can see her slides here and read her paper on Mixture Models here.
Amy spoke excellently about how to extract and use data from timesheets. The first question out of people’s mouths at the end of the talk was “how much money have you made from this idea?” - she then had a lot of people describe to her how her idea is commercially viable. Very cool. You can see slides here.
I delivered a talk on two packages I have developed alongside Miles McBain and Di Cook: visdat
and ggmissing
. The idea of visdat
is to allow you do visualise an entire dataframe at once, and ggmissing
extends ggplot to incorporate missingness, similar to ggobi. I had some good questions at the end, with some cool suggestions like including natural language processing to highlight specific characters/patterns, and that vis_miss
could run some missingness diagnostics and provide a warning message to the user along the lines of “you might have variables MAR, investigate further”. I shall talk more about this in a future blog post.
It looks like WOMBAT might be an annual occurence, I would highly encourage attending the next one if you have the opportunity. Thank you once more to the conference Organisers for putting together such an awesome conference. Looking forward to the next one!


On this page, we will give more information about the use of a story file to create a story.
The path-to-a-story-file must point to a story file in the same web domain as the Story Utility html page.
The reason for this restriction is that the story file is loaded
using Javascript and the tool XMLHttpRequest
. Therefore
standard browser security restrictions apply.
We said that each line in the story file that starts with a non-blank character should consist of:
url
for a slide in the story
The url
for an individual slide may be quite arbitrary
because a slide is loaded into an HTML iframe
. There
are no browser security restrictions in specifying the source for
an iframe
.
For the url
, you may use:
url
where relative is interpreted
as relative to the web directory of the story file
url
that opens with
http://
or https://
In a few cases such as for the New York Times web site,
the target page is designed so that it
will not permit itself to be displayed in an iframe
.
For such a page, the Story Utility may not be used.


If you think you’ve found a bug in The Minimal Theme, please check the existing issues, and if no one has reported the problem, open a new issue.
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I think my problem is best explained with how I want the code to look. Only problem is it doesn't work (Line 11). I have some experience with templates but I'm not a pro.
Basically I want the "Channels<3>" to be a type that I can use to specify a Cable with similar to vector<float/int> it would be Cable<Channels<2 or 3>>.
I don't really like the 2nd and 3rd because they don't have the syntax I would like. I really want the syntax " Cable<Static_Property<value>> " for some really nice flexibility when things get more complicated.
With the first solution, it breaks with any type that has a "channels" property...
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17
template<int channel_count>
struct Channels {
staticconstint channels = channel_count;
};
//adding this...
template<int channel_count>
struct Tricked {
staticconstexprint channels = channel_count;
};
int main() {
// compiles...
// but that makes no sense
Cable< Tricked<3> > c;
return 0;
}
I want to add specialization later on based on Cable<Channels<2>>, Cable<Channels<3>>, etc that do specific mixing, or connections/io and at a minimum the number of channels have to match. It would be nice to catch that at compile time.
So something like this would work...
1 2 3 4 5 6 7
Mixer< Slots<20>, Cable<Channels<3>> > m;
Cable<Channels<2>> c2;
Cable<Channels<3>> c3;
m.add_to_mix(c3); // ok
m.add_to_mix(c2); // should fail
> I really want the syntax " Cable<Static_Property<value>> "
> it breaks with any type that has a "channels" property...
> It would be nice to catch that at compile time.


---
description: Preview create-eleventy-site output
orientation: vertical
externalIframeSrc: https://hopeful-mccarthy-f891b7.netlify.app/
title: https://hopeful-mccarthy-f891b7.netlify.app/
typing:
- 9999
---
React: 1.3 kB SVG and 1.0 kB CSS
Eleventy: 0.9 kB SVG and 0.6 kB CSS


MDEOptimiser now supports the generation of atomic consistency preserving search operators(aCPSOs). aCPSOs are mutation operators that ensure multiplicity constraint satisfaction after their application.
A description of the currently supported search operators is given in the two sections below. The first section shows node manipulation patterns supported and the second includes edge manipulation cases supported.
The two tables below assume the multiplicity pattern between two nodes as shown in the figure below.
Node Manipulation
A list of the supported node manipulation multiplicities is included in the tables below. The first table shows the node creation operators. The second table contains the node deletion operators.
| Create Node | n=0 | n=1 and m > n | n > 1 and m > n | n = m |
|---|---|---|---|---|
| k >= 0 l > k l < * |
c A | Create A add n B (f#l A) Create A lb r single B |
Create A add n B Create A lb r single B Create A lb r many B |
Create A add n B (f#l A) |
| k >= 0 l = * |
Create A add n B | |||
| k = l | Create A lb r single B | Create A add n B Create A lb r single B Create A lb r many B |
N/A |
| Delete Node | m > n and m < * | m = * | n = m |
|---|---|---|---|
| k = 0 | Delete A | ||
| k > 0 l > k |
Delete A (require each B still has #k A) | ||
| k=l=1 | Delete A r lb sg B (f#m A) | Delete A r lb sg B | N/A |
| k=l > 1 | Delete A r lb sg B (f#m A) d A r lb mm B (f#m A) |
Delete A r lb sg B d A r lb mm B |
N/A |
Edge Manipulation
The list of supported multiplicities for generating edge manipulation search operators is included in the tables below. The first table contains the edge creation supported multiplicities and the generated operators. The second table contains the operators generated for edge removal.
| Edge Creation | m < * | m = * | n=m |
|---|---|---|---|
| l < * | Add edge NAC A B | Add edge NAC B | Swap edge |
| l = * | Add edge NAC A | Add edge | Swap edge |
| k = l | Change edge (P/N A) | Change edge (P/N A) | Swap edge |
| Edge Removal | n = 0 | n > 0 | n = m |
|---|---|---|---|
| k = 0 | Remove edge | Remove edge PAC A | Swap Edge |
| k > 0 | Remove edge PAC B | Remove edge PAC AB | Swap Edge |
| k = l | Change edge (P/N A) | Change edge (P/N A) | Swap Edge |


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| PREV CLASS NEXT CLASS | FRAMES NO FRAMES | |||||||||
| SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |
public interface AuthenticationToken
An AuthenticationToken is a consolidation of an account's principals and supporting credentials submitted by a user during an authentication attempt.
The token is submitted to an Authenticator
via the
authenticate(token)
method. The
Authenticator then executes the authentication/log-in process.
Common implementations of an AuthenticationToken would have username/password
pairs, X.509 Certificate, PGP key, or anything else you can think of. The token can be
anything needed by an Authenticator
to authenticate properly.
Because applications represent user data and credentials in different ways, implementations of this interface are application-specific. You are free to acquire a user's principals and credentials however you wish (e.g. web form, Swing form, fingerprint identification, etc) and then submit them to the Shiro framework in the form of an implementation of this interface.
If your application's authentication process is username/password based
(like most), instead of implementing this interface yourself, take a look at the
UsernamePasswordToken
class, as it is probably sufficient for your needs.
RememberMe services are enabled for a token if they implement a sub-interface of this one, called
RememberMeAuthenticationToken
. Implement that interfac if you need
RememberMe services (the UsernamePasswordToken already implements this interface).
If you are familiar with JAAS, an AuthenticationToken replaces the concept of a
Callback
, and defines meaningful behavior
(Callback is just a marker interface, and of little use). We
also think the name AuthenticationToken more accurately reflects its true purpose
in a login framework, whereas Callback is less obvious.
RememberMeAuthenticationToken
,
HostAuthenticationToken
,
UsernamePasswordToken
| Method Summary | |
|---|---|
Object |
getCredentials()
Returns the credentials submitted by the user during the authentication process that verifies the submitted account identity . |
Object |
getPrincipal()
Returns the account identity submitted during the authentication process. |
| Method Detail |
|---|
Object getPrincipal()
Most application authentications are username/password based and have this
object represent a username. If this is the case for your application,
take a look at the UsernamePasswordToken
, as it is probably
sufficient for your use.
Ultimately, the object returned is application specific and can represent any account identity (user id, X.509 certificate, etc).
UsernamePasswordToken
Object getCredentials()
account identity
.
Most application authentications are username/password based and have this object
represent a submitted password. If this is the case for your application,
take a look at the UsernamePasswordToken
, as it is probably
sufficient for your use.
Ultimately, the credentials Object returned is application specific and can represent any credential mechanism.
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With IoT, things have now become "smart". With this project we aim to make a "smart" device which is able to monitor electrical consumptions of various appliances(exhaust fan,fogger, water pump etc), inform the user about consumption and provide options for scheduling turn on/off time of appliance. The system will consist of a wi-fi enabled device which measure and display power consumption of an appliance. Device should be capable of turning on/off the device from web, scheduling the on/off time of the device.
System will have following components:
1. A Voltage, Current, Phase and frequency measuring Circuit.
2. Microcontroller based system which is wifi enabled and after measuring the electrical parameters, it is able to log those parameters in database and display it on web interface with proper visualization
3. User interface for controlling devices from web
4. Feature to turn on/off device based on rules/schedule set by user
5. Design PCB of circuit and a miniaturized device which can fit in spike guard/switch board for ensuring easy installation in existing system.


Gogol Library
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{% extends "global/Page.html" %} {% load otree %} {% block title %} Introduction (Round level) {% endblock %} {% block content %}
This is an experimental prediction market. There are {{ Constants.num_rounds}} in total, and in each round, you will be randomly assigned into a group of {{ Constants.players_per_group }}. At the beginning of each round, you will have an initial balance of {{ Constants.round_initial_balance }}; at the end of each round, your remaining balance will be recorded. Then your balance will be reset for next round.
This is round {{ player.subsession.round_number }}
{% next_button %} {% endblock %}


Geotechnical Testing Equipment, have been providing clients with the most appropriate and tailored test solutions and instrumentation for their very specific needs for over 10 years. The Equipment is used for both research and development, and quality control applications to test the strength, elasticity, durability and properties of building materials.
The company is both based and registered in the United Kingdom, 40 miles North of London, in Buckinghamshire. Geotechnical Testing Equipment has enjoyed expansive growth in recent years, as a result of expanding into a global arena.
Similar to FORNEY, Geotechnical supplies testing machines in the following fields:


QUESTION #1
person := models.Person{}
Which uAdmin function will return the count of all records in a table?
QUESTION #2
wall := []models.Wall{}
Which uAdmin function will return the count of all records in a table?
QUESTION #3
monitor := []models.Monitor{}
Which uAdmin function will return the count of all records in a table?
QUESTION #4
animal := []models.Animal{}
Which uAdmin function will return the count of all records in a table?
QUESTION #5
student := []models.Student{}
Which uAdmin function will return the count of all records in a table that starts with letter j?
QUESTION #6
museum := []models.Museum{}
Which uAdmin function will return the count of all records in a table that ends with letter p?
QUESTION #7
decoration := []models.Decoration{}
Which uAdmin function will return the count of all records in a table that starts with letter b and ends with letter d?
QUESTION #8
place := []models.Place{}
Which uAdmin function will return the count of all records in a table that contains the word "trip"?
QUESTION #9
basement := []models.Basement{}
Field to Query: building_id
Parameter: building_id
Which uAdmin function will return the count of basements in a specific building?
QUESTION #10
city := []models.City{}
Field to Query: country_id
Parameter: country_id
Which uAdmin function will return the count of cities in a specific country?
QUESTION #11
motorcycle := []models.Motorcycle{}
Field to Query: vehicle_id
Parameter: vehicle
Which uAdmin function will return the count of motorcycles in a specific vehicle?
QUESTION #12
basketball := []models.Basketball{}
Field to Query: sport_id
Parameter: sport
Which uAdmin function will return the count of basketballs in a specific sport?
QUESTION #13
Suppose you have this model as shown below:
| CUSTOMER | NAME | GENDER |
|---|---|---|
| John Doe | John Doe | Male |
| Jane Doe | Jane Doe | Female |
| Allen Dale | Allen Dale |
Code:
customer := models.Customer{}
gender := models.Gender{}
uadmin.Get(&gender, "id = ?", customer.GenderID)
Which uAdmin function will return the count of all customers with a gender value in a table?
QUESTION #14
Suppose you have this model as shown below:
| MOUNTAIN | NAME | CONTINENT |
|---|---|---|
| Mount Everest | Mount Everest | Asia |
| Mount Olympus | Mount Olympus | |
| Mount Elbrus | Mount Elbrus | Europe |
Code:
mountain := models.Mountain{}
continent := models.Continent{}
uadmin.Get(&continent, "id = ?", mountain.ContinentID)
Which uAdmin function will return the count of all mountains with a continent value in a table?
QUESTION #15
Suppose you have this model as shown below:
| SKYSCRAPER | NAME | COUNTRY |
|---|---|---|
| Burj Khalifa | Burj Khalifa | United Arab Emirates |
| X-Seed 4000 | X-Seed 4000 | |
| Taipei 101 | Taipei 101 | Taiwan |
Code:
skyscraper := models.Skyscraper{}
country := models.Country{}
uadmin.Get(&country, "id = ?", skyscraper.CountryID)
Which uAdmin function will return the count of all skyscrapers with a country value in a table?


'Crisis on Infinite Earths': Bruce Wayne Makes His 'Arrowverse' Debut
Kevin Conroy will portray a version of the Dark Knight from the future in upcoming mega event
by Tim BaysingerBruce Wayne has finally entered the Arrowverse. Well, a version of Bruce Wayne anyway.
The CW has been teasing out its upcoming massive, five-part crossover, “Crisis on Infinite Earths,” and on Tuesday, the network showed off the first look at Kevin Conroy’s Dark Knight. Conroy, who is well known for providing the voice for the Caped Crusader in “Batman: The Animated Series” and “Batman Beyond,” will appear as Bruce Wayne from the future during the “Batwoman” episode on Dec. 9.
As you can see in the photo below, he may no longer be wearing the batsuit, but it appears Wayne hasn’t given up his love high-tech outfits.
Also Read:
“Crisis on Infinite Earths” has an ever-growing roster of past and present DC Comics superheroes. These include the entire “Arrowverse” casts from “Supergirl,” “Arrow,” “Legends of Tomorrow,” “The Flash,” newcomer “Batwoman,” and for the first time, “Black Lightning.” Erica Durance reprising her version of Lois Lane from “Smallville,” and “Batman” fan favorite Burt Ward will appear as well in an undisclosed role.
The crossover begins Dec. 8 with “Supergirl.” That will be followed by “Batwoman” and “The Flash” on Dec. 9 and 10, respectively. “Crisis on Infinite Earths” will wrap up on Jan. 14 with “Arrow” and “DC’s Legends of Tomorrow” going back-to-back.


Lead the journey to the cloud and drive innovation! Discover what makes the cloud so compelling to enterprises; with which applications you should start your cloud journey; how your organization will change, and how skill sets will evolve; how to measure progress; how to think about security, compliance, and business buy-in; and how to exploit the ever-growing feature set that the cloud offers to gain strategic and competitive advantage.
At the Build 2016 conference, Microsoft announced the Microsoft Bot Framework, a package of tools for building intelligent bots that could be integrated with a variety of communication platforms. With Microsoft Bot Framework Succinctly, you can jump right into building your own bots with the framework, whether you want to make bots for personal use only, or customer-facing bots for your business. Author Ed Freitas provides clear guidance from setting up a bot project in Visual Studio and writing your first bare-bones bot, to publishing one capable of searching for current flight prices.
This ebook is for anyone whose responsibilities include training people to use Windows 10. That group includes full-time professional trainers, of course, but it also includes IT pros and those brave souls who staff the help desk in corporations. Most of all, it includes the incredibly large population of people who have earned a reputation for being “the person who knows Windows.”


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{% extends "layouts/_block_content.html" %} {% from "components/breadcrumbs/_macro.njk" import onsBreadcrumbs %} {% from "components/button/_macro.njk" import onsButton %} {% set breadcrumbsData = [ { "text": "Surveys", "url": "/surveys/todo", "id": "b-item-1" }, { "text": "Help", "url": "/surveys/surveys-help?survey_ref="~survey_ref~"&ru_ref="~ru_ref, "id": "b-item-2" }, { "text": "Help completing this survey", "url": "/surveys/help/"~option, "id": "b-item-3" } ] %} {% block breadcrumbs %} {{ onsBreadcrumbs({ "ariaLabel": "Breadcrumbs", "id": "breadcrumbs", "itemsList": breadcrumbsData }) }} {% endblock breadcrumbs %} {% block main %}
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iOS application which is currently under development. It is a calendar application focused on today's events. Design and user experience are key ingredients here, so I'm working on this as a collaborative project with a graphic designer. I want this to be visually appealing and easy to use, as I feel most mobile calendar apps tend to have too much information.
Again, the goal here is to learn about iOS development, and to create a nice and useful app.


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--- layout: help title: Meld - Help ---
Meld lets you compare two or three text files side-by-side. You can start a new file comparison by selecting the File ▸ New... menu item.
Once you've selected your files, Meld will show them side-by-side. Differences between the files will be highlighted to make individual changes easier to see. Editing the files will cause the comparison to update on-the-fly. For details on navigating between individual changes, and on how to use change-based editing, see Dealing with changes.
There are several different parts to a file comparison. The most important parts are the editors where your files appear. In addition to these editors, the areas around and between your files give you a visual overview and actions to help you handle changes between the files.
On the left and right-hand sides of the window, there are two small vertical bars showing various coloured blocks. These bars are designed to give you an overview of all of the differences between your two files. Each coloured block represents a section that is inserted, deleted, changed or in conflict between your files, depending on the block's colour used.
In between each pair of files is a segment that shows how the changed sections between your files correspond to each other. You can click on the arrows in a segment to replace sections in one file with sections from the other. You can also delete, copy or merge changes. For details on what you can do with individual change segments, see Changing changes.
Once you've finished editing your files, you need to save each file you've changed.
You can tell whether your files have been saved since they last changed by the save icon that appears next to the file name above each file. Also, the notebook label will show an asterisk (*) after any file that hasn't been saved.
You can save the current file by selecting the File ▸ Save menu item, or using the Ctrl+S keyboard shortcut.
Saving only saves the currently focused file, which is the file containing the cursor. If you can't tell which file is focused, you can click on the file to focus it before saving.


The simplest open protocol that is able to create a censorship-resistant global “social” network once and for all.
It doesn’t rely on any trusted central server, hence it is resilient; it is based on cryptographic keys and signatures, so it is tamperproof; it does not rely on P2P techniques, therefore it works.
Very short summary of how it works, if you don’t plan to read anything else:
Everybody runs a client. It can be a native client, a web client, etc. To publish something, you write a post, sign it with your key and send it to multiple relays (servers hosted by someone else, or yourself). To get updates from other people, you ask multiple relays if they know anything about these other people. Anyone can run a relay. A relay is very simple and dumb. It does nothing besides accepting posts from some people and forwarding to others. Relays don’t have to be trusted. Signatures are verified on the client side.
This is needed because other solutions are broken:
The problem with Twitter
- Twitter has ads;
- Twitter uses bizarre techniques to keep you addicted;
- Twitter doesn’t show an actual historical feed from people you follow;
- Twitter bans people;
- Twitter shadowbans people.
- Twitter has a lot of spam.
The problem with Mastodon and similar programs
- User identities are attached to domain names controlled by third-parties;
- Server owners can ban you, just like Twitter; Server owners can also block other servers;
- Migration between servers is an afterthought and can only be accomplished if servers cooperate. It doesn’t work in an adversarial environment (all followers are lost);
- There are no clear incentives to run servers, therefore they tend to be run by enthusiasts and people who want to have their name attached to a cool domain. Then, users are subject to the despotism of a single person, which is often worse than that of a big company like Twitter, and they can’t migrate out;
- Since servers tend to be run amateurishly, they are often abandoned after a while — which is effectively the same as banning everybody;
- It doesn’t make sense to have a ton of servers if updates from every server will have to be painfully pushed (and saved!) to a ton of other servers. This point is exacerbated by the fact that servers tend to exist in huge numbers, therefore more data has to be passed to more places more often;
- For the specific example of video sharing, ActivityPub enthusiasts realized it would be completely impossible to transmit video from server to server the way text notes are, so they decided to keep the video hosted only from the single instance where it was posted to, which is similar to the Nostr approach.
The problem with SSB (Secure Scuttlebutt)
- It doesn’t have many problems. I think it’s great. In fact, I was going to use it as a basis for this, but
- its protocol is too complicated because it wasn’t thought about being an open protocol at all. It was just written in JavaScript in probably a quick way to solve a specific problem and grew from that, therefore it has weird and unnecessary quirks like signing a JSON string which must strictly follow the rules of ECMA-262 6th Edition;
- It insists on having a chain of updates from a single user, which feels unnecessary to me and something that adds bloat and rigidity to the thing — each server/user needs to store all the chain of posts to be sure the new one is valid. Why? (Maybe they have a good reason);
- It is not as simple as Nostr, as it was primarily made for P2P syncing, with “pubs” being an afterthought;
- Still, it may be worth considering using SSB instead of this custom protocol and just adapting it to the client-relay server model, because reusing a standard is always better than trying to get people in a new one.
The problem with other solutions that require everybody to run their own server
- They require everybody to run their own server;
- Sometimes people can still be censored in these because domain names can be censored.
How does Nostr work?
- There are two components: clients and relays. Each user runs a client. Anyone can run a relay.
- Every user is identified by a public key. Every post is signed. Every client validates these signatures.
- Clients fetch data from relays of their choice and publish data to other relays of their choice. A relay doesn’t talk to another relay, only directly to users.
- For example, to “follow” someone a user just instructs their client to query the relays it knows for posts from that public key.
- On startup, a client queries data from all relays it knows for all users it follows (for example, all updates from the last day), then displays that data to the user chronologically.
- A “post” can contain any kind of structured data, but the most used ones are going to find their way into the standard so all clients and relays can handle them seamlessly.
How does it solve the problems the networks above can’t?
-
Users getting banned and servers being closed
- A relay can block a user from publishing anything there, but that has no effect on them as they can still publish to other relays. Since users are identified by a public key, they don’t lose their identities and their follower base when they get banned.
- Instead of requiring users to manually type new relay addresses (although this should also be supported), whenever someone you’re following posts a server recommendation, the client should automatically add that to the list of relays it will query.
- If someone is using a relay to publish their data but wants to migrate to another one, they can publish a server recommendation to that previous relay and go;
- If someone gets banned from many relays such that they can’t get their server recommendations broadcasted, they may still let some close friends know through other means with which relay they are publishing now. Then, these close friends can publish server recommendations to that new server, and slowly, the old follower base of the banned user will begin finding their posts again from the new relay.
- All of the above is valid too for when a relay ceases its operations.
-
Censorship-resistance
- Each user can publish their updates to any number of relays.
- A relay can charge a fee (the negotiation of that fee is outside of the protocol for now) from users to publish there, which ensures censorship-resistance (there will always be some Russian server willing to take your money in exchange for serving your posts).
-
Spam
- If spam is a concern for a relay, it can require payment for publication or some other form of authentication, such as an email address or phone, and associate these internally with a pubkey that then gets to publish to that relay — or other anti-spam techniques, like hashcash or captchas. If a relay is being used as a spam vector, it can easily be unlisted by clients, which can continue to fetch updates from other relays.
-
Data storage
- For the network to stay healthy, there is no need for hundreds of active relays. In fact, it can work just fine with just a handful, given the fact that new relays can be created and spread through the network easily in case the existing relays start misbehaving. Therefore, the amount of data storage required, in general, is relatively less than Mastodon or similar software.
- Or considering a different outcome: one in which there exist hundreds of niche relays run by amateurs, each relaying updates from a small group of users. The architecture scales just as well: data is sent from users to a single server, and from that server directly to the users who will consume that. It doesn’t have to be stored by anyone else. In this situation, it is not a big burden for any single server to process updates from others, and having amateur servers is not a problem.
-
Video and other heavy content
- It’s easy for a relay to reject large content, or to charge for accepting and hosting large content. When information and incentives are clear, it’s easy for the market forces to solve the problem.
-
Techniques to trick the user
- Each client can decide how to best show posts to users, so there is always the option of just consuming what you want in the manner you want — from using an AI to decide the order of the updates you’ll see to just reading them in chronological order.
FAQ
-
This is very simple. Why hasn’t anyone done it before?
I don’t know, but I imagine it has to do with the fact that people making social networks are either companies wanting to make money or P2P activists who want to make a thing completely without servers. They both fail to see the specific mix of both worlds that Nostr uses.
-
How do I find people to follow?
First, you must know them and get their public key somehow, either by asking or by seeing it referenced somewhere. Once you’re inside a Nostr social network you’ll be able to see them interacting with other people and then you can also start following and interacting with these others.
-
How do I find relays? What happens if I’m not connected to the same relays someone else is?
You won’t be able to communicate with that person. But there are hints on events that can be used so that your client software (or you, manually) knows how to connect to the other person’s relay and interact with them. There are other ideas on how to solve this too in the future but we can’t ever promise perfect reachability, no protocol can.
-
Can I know how many people are following me?
No, but you can get some estimates if relays cooperate in an extra-protocol way.
-
What incentive is there for people to run relays?
The question is misleading. It assumes that relays are free dumb pipes that exist such that people can move data around through them. In this case yes, the incentives would not exist. This in fact could be said of DHT nodes in all other p2p network stacks: what incentive is there for people to run DHT nodes?
-
Nostr enables you to move between server relays or use multiple relays but if these relays are just on AWS or Azure what’s the difference?
There are literally thousands of VPS providers scattered all around the globe today, there is not only AWS or Azure. AWS or Azure are exactly the providers used by single centralized service providers that need a lot of scale, and even then not just these two. For smaller relay servers any VPS will do the job very well.


Predictions 2020: Automation strike teams and services rise to fend off a paradox
by Forrester ResearchRead the top three predictions for the automation market from Forrester Research analyst Chris Gardner.
While automation remains a major focus for many organizations, the biggest challenges in deploying automation aren't with the technology itself. According to recent Forrester polling of global data and analytics decision-makers:
- 25% said their firm lacks an overall vision or strategy for automation.
- 26% told us they face challenges with culture and change management.
- 25% believe there are gaps in their organizational structure, alignment, and readiness.
The reasons behind these results are varied. In some cases, islands of automation form, where firms unknowingly use similar types of automation in different parts of the organization. In other cases, the bottoms-up deployment method prevents scale and leads to governance nightmares. And overall, federated operating models are developing too slowly to keep pace with the growth of the technology.
With all these trends continuing next year, we're expecting some pretty dramatic automation-based events to unfold, as well. Some of these trends will impact individual organizational units and toolsets, while others will change the future of work for everyone.
In 2020, expect to see the following:
- Automation and the future of work will be discussed at the UN. In 2020, 3.9% of cubicle jobs will be cannibalized, while human-touch jobs, such as nurses, will grow by 0.62%. Tasks ranging from posting account ledgers to calculating HR benefits will be replaced by RPA (robotic process automation). Work that requires intuition, empathy, and mental agility, such as cross-domain knowledge workers, teachers, and explainers, will add 300,000 jobs to the economy.
 After years of falling, MTTR (mean time to resolve) incidents will increase. The reason? All the easy tasks have been automated. To counter shrinking knowledge lifecycles and growing L2/L3 service desks, enterprises will try to address this paradox by applying SRE (site reliability engineering) and tackling observability issues with new tools powered by AI.
- Automation strike teams will rise. In between traditional IT and domain experts, unique strike teams are coming up in enterprises to address islands of automation. This practice will formalize in 2020. These teams, manned by roles such as robot architects and automation jump-starters, will standardize automation portfolios and accelerate user journey mapping. More importantly, they will form a key part of the purchasing cycle and will become a targeted persona for many automation vendors.
Whether your automation strategy and portfolio need a retune or you're just getting started on your automation plans, it's vitally important to prepare for 2020, because next year will be a transformative year for automation.
Download
Forrester's Predictions 2020 guide
to understand the major dynamics that will impact firms next year.
This post was written by Principal Analyst Chris Gardner and originally appeared
here
.


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Dissertation Project
Master’s Thesis - Offensive Language Detection Natural Language Processing Machine Learning Deep LearningPosting offensive or abusive content on social media has been a serious concern in recent years. This has created a lot of problems because of the huge popularity and usage of social media sites like Facebook and Twitter. The main motivation lies in the fact that our model will automate and accelerate the detection of the posted offensive content so as to facilitate the relevant actions and moderation of these offensive posts. We would be using the publicly available benchmark dataset OLID 2019 (Offensive Language Identication Dataset) for this research project. The scope of our work lies in predicting whether the tweet post is offensive or not. We contributed by making the training dataset balanced using the Random Under-sampling technique. We also performed a thorough comparative analysis of various Feature Extraction Mechanisms and the Model Building Algorithms. The final comparative analysis concluded that the best model came out to be Bidirectional Encoder Representation from Transformer (BERT). Our results outperform the previous work achieving the Macro F1 score of 0.82 on this OLID dataset. Finally, a real-time system could be deployed on various social media platforms to detect and analyze the offensive post content and taking the appropriate action in order to normalize the behaviour on these sites and society.
Click here to see my publication on ResearchGate


- Organized freshmen to attend class meetings, campus tour and other activities.
- Gave lectures on advanced mathematics, inorganic and analytical chemistry to address the needs of freshmen.
- Worked as the assistant for Poling’s teachers.
- Participated in organization of a monthly academic lecture.


kluge
`Prev `__
K
`Next `__
--------------
**kluge**: /klooj/
[from the German ‘klug’, clever; poss. related to Polish & Russian
‘klucz’ (a key, a hint, a main point)]
1. n. A Rube Goldberg (or Heath Robinson) device, whether in hardware or
software.
2. n. A clever programming trick intended to solve a particular nasty
case in an expedient, if not clear, manner. Often used to repair bugs.
Often involves `*ad-hockery* <../A/ad-hockery.html>`__ and verges on
being a `*crock* <../C/crock.html>`__.
3. n. Something that works for the wrong reason.
4. vt. To insert a kluge into a program. “I've kluged this routine to
get around that weird bug, but there's probably a better way.”
5. [WPI] n. A feature that is implemented in a
`*rude* <../R/rude.html>`__ manner.
Nowadays this term is often encountered in the variant spelling
‘kludge’. Reports from `*old fart* <../O/old-fart.html>`__\ s are
consistent that ‘kluge’ was the original spelling, reported around
computers as far back as the mid-1950s and, at that time, used
exclusively of *hardware* kluges. In 1947, the *New York Folklore
Quarterly* reported a classic shaggy-dog story ‘Murgatroyd the Kluge
Maker’ then current in the Armed Forces, in which a ‘kluge’ was a
complex and puzzling artifact with a trivial function. Other sources
report that ‘kluge’ was common Navy slang in the WWII era for any piece
of electronics that worked well on shore but consistently failed at sea.
However, there is reason to believe this slang use may be a decade
older. Several respondents have connected it to the brand name of a
device called a “Kluge paper feeder”, an adjunct to mechanical printing
presses. Legend has it that the Kluge feeder was designed before small,
cheap electric motors and control electronics; it relied on a fiendishly
complex assortment of cams, belts, and linkages to both power and
synchronize all its operations from one motive driveshaft. It was
accordingly temperamental, subject to frequent breakdowns, and
devilishly difficult to repair — but oh, so clever! People who tell this
story also aver that ‘Kluge’ was the name of a design engineer.
There is in fact a Brandtjen & Kluge Inc., an old family business that
manufactures printing equipment — interestingly, their name is
pronounced /kloo´gee/! Henry Brandtjen, president of the firm, told me
(ESR, 1994) that his company was co-founded by his father and an
engineer named Kluge /kloo´gee/, who built and co-designed the original
Kluge automatic feeder in 1919. Mr. Brandtjen claims, however, that this
was a *simple* device (with only four cams); he says he has no idea how
the myth of its complexity took hold. Other correspondents differ with
Mr. Brandtjen's history of the device and his allegation that it was a
simple rather than complex one, but agree that the Kluge automatic
feeder was the most likely source of the folklore.
`*TMRC* <../T/TMRC.html>`__ and the MIT hacker culture of the early '60s
seems to have developed in a milieu that remembered and still used some
WWII military slang (see also `*foobar* <../F/foobar.html>`__). It seems
likely that ‘kluge’ came to MIT via alumni of the many military
electronics projects that had been located in Cambridge (many in MIT's
venerable Building 20, in which `*TMRC* <../T/TMRC.html>`__ is also
located) during the war.
The variant ‘kludge’ was apparently popularized by the
`*Datamation* <../D/Datamation.html>`__ article mentioned under
`*kludge* `__; it was titled *How to Design a Kludge*
(February 1962, pp. 30, 31). This spelling was probably imported from
Great Britain, where `*kludge* `__ has an independent
history (though this fact was largely unknown to hackers on either side
of the Atlantic before a mid-1993 debate in the Usenet group
``alt.folklore.computers`` over the First and Second Edition versions of
this entry; everybody used to think `*kludge* `__ was just
a mutation of `*kluge* `__). It now appears that the
British, having forgotten the etymology of their own ‘kludge’ when
‘kluge’ crossed the Atlantic, repaid the U.S. by lobbing the ‘kludge’
orthography in the other direction and confusing their American cousins'
spelling!
The result of this history is a tangle. Many younger U.S. hackers
pronounce the word as /klooj/ but spell it, incorrectly for its meaning
and pronunciation, as ‘kludge’. (Phonetically, consider huge, refuge,
centrifuge, and deluge as opposed to sludge, judge, budge, and fudge.
Whatever its failings in other areas, English spelling is perfectly
consistent about this distinction.) British hackers mostly learned
/kluhj/ orally, use it in a restricted negative sense and are at least
consistent. European hackers have mostly learned the word from written
American sources and tend to pronounce it /kluhj/ but use the wider
American meaning!
Some observers consider this mess appropriate in view of the word's
meaning.
--------------
+---------------------------+----------------------------+---------------------------------+
| `Prev `__ | `Up <../K.html>`__ | `Next `__ |
+---------------------------+----------------------------+---------------------------------+
| kludge | `Home <../index.html>`__ | kluge around |
+---------------------------+----------------------------+---------------------------------+


This page is used to test creation and deletion of various site data types. The functions are called from BrowsingDataRemoverBrowserTest::HasDataForType and BrowsingDataRemoverBrowserTest::SetDataForType.


pvaClient is a software library that provides, to an EPICS client programmer, a friendly client side programming interface to the data of an EPICS based control system. It is intended for such uses as rapid development of ad hoc programs by controls engineers, or to provide scientists a way to directly develop analytical applications.
Specifically, pvaClient provides a synchronous interface for pvAccess, which is the software support for high speed controls network communications used in EPICS version 4. pvAccess provides a callback based interface, which can be hard to use. pvaClient provides an interface that does not require callbacks even for monitors.
pvaClientChannel provides many "convenience" methods to directly get and put scalar and scalarArray data types. Additional methods provide access to the full features of pvAccess.
pvaClientMultiChannel provides access to data from multiple channels. It can be used directly by a client or via pvaClientMultiDouble or pvaClientNTMultiChannel. pvaClientMultiDouble allows the client to get and put data to multiple channels. But each channel must have a value field that is a numeric scalar. pvaClientNTMultiChannel allows the client to get and put data to multiple channels. Each channel must have a value field. The data for the channels is presented via normative type NTMultiChannel.
For more information about EPICS generally, please refer to the home page of the Experimental Physics and Industrial Control System.
Documentation for pvaClientCPP is available at: pvaClient
pvaClientCPP is one of the components of EPICS-7
This document is only a guide to help locate code and documentation related to pvaClientCPP
It is intended for developers that want to use pvaClientCPP.
A guide for developers is available at developerGuide
This guide provides an overview of the components that are part of an EPICS V4 release. Some understanding of the components and how they are related is necessary in order to develop code that uses pvaClientCPP. In particular read everything related to pvaClient.
doxygen documentation is available at doxygen
Example code is available at exampleCPP
In particular look at exampleClient. It has many examples of using pvaClientCPP.


Colordinates
Colordinates uses your devices geographic position to display a color swatch and the HSLA color value
Find out more about colordinates development.
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I have developed a number of web apps to solve various problems and improve my skills.
Colordinates uses your devices geographic position to display a color swatch and the HSLA color value
Find out more about colordinates development.
The next time you find yourself wondering when you last changed your brush, check back and see how many days until you need a new brush.
Read more about Brush Swap creation.
Current mix of electricity sources in the UK National Grid using the Carbon Intensity API by National Grid.
Find out more about Elitricity development.