Lorem ipsum dolor amet keytar portland swag blue bottle keffiyeh succulents lyft synth schlitz. Slow-carb small batch post-ironic DIY deep v. Freegan meggings roof party lo-fi chillwave portland trust fund. Knausgaard small batch brooklyn fixie, +1 cronut helvetica man bun leggings unicorn readymade vegan af four loko authentic. Yr meh man braid affogato fanny pack tote bag air plant mlkshk poutine blue bottle ennui tousled roof party hammock. Portland bitters vape ugh butcher schlitz jianbing salvia aesthetic twee mumblecore kale chips gochujang master cleanse. Deep v helvetica portland readymade unicorn microdosing kinfolk, four loko art party actually mlkshk. IPhone photo booth ugh, hammock tofu keffiyeh quinoa man bun. Poutine pabst literally helvetica umami, tattooed lomo gluten-free snackwave shaman hammock VHS portland mumblecore photo booth. Cardigan irony cronut, echo park PBR&B put a bird on it church-key salvia la croix messenger bag chicharrones biodiesel roof party 8-bit. Plaid gastropub quinoa, sriracha organic gluten-free air plant hella affogato succulents art party. Wolf bitters pork belly yr.
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Hello {{user.name}}.
Somebody, hopefully you, has requested a password reset.
| Date and time | IP address | User-agent |
|---|---|---|
| {{access_date}} | {{ip_address}} | {{user_agent}} |
If this was you, please follow this link to reset your password.
If this was not you, someone may be abusing the password recovery service. You can ban this IP address from accessing your account by opening your dashboard and entering the IP address listed above into the "Banned IP addresses" table. Yours, the beacon service.


Doctor of incapacitated woman who gave birth cedes license
PHOENIX (AP) - A doctor who treated an incapacitated woman who was raped and later gave birth at a Phoenix long-term care facility can no longer practice medicine.
Arizona Medical Board records show Dr. Phillip Gear agreed last week to a consent order to surrender his license and not contest the matter in court.
Gear was the victim’s physician on and off at Hacienda HealthCare from 1992, when she was 3 years old, until September 2018.
TOP STORIES
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The woman shocked facility staff when she gave birth less than four months later.
According to the board, Gear failed to perform required monthly exams on her.
He was also found to be physically unable to carry out some tasks and didn’t adequately supervise four students.
The order was first reported by The Arizona Republic.
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---
layout: default
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---
{% include header_business_science.html %}
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gretty {
// ...
overlay ':overlay1'
overlay ':overlay2'
// ...
}
overlay
function of gretty configuration adds the specified project as an overlay source to the current project.
When performing appRun[Debug] and appStart[Debug], runtime classpath of overlay sources is added to the runtime classpath of the current project. Classpath of the current project has priority.
When assembling WAR file, the compiled resources and classes of the overlay sources are added (overlayed) to the current project. The files of the current project have priority over overlay source files. This allows to effectively customize web-app.
|
Tip
|
You can specify more than one overlay source. |
|
Tip
|
You can specify recursive overlay sources - that is, the projects, added by overlay function, can contain gretty configuration with overlay referencing other projects and so on.
|
|
Important
|
"overlay" property "understands" only gradle projects of the same project tree as an input. You can not specify maven artifacts as overlay sources. |
Gretty sources contain example programs, demonstrating use of overlays:


As the COVID-19 pandemic has progressed, the volume of new information has increased exponentially with frequent changes to the data formats, as well as new caveats for understanding the data. Processing this information is becomming a task too difficult to maintain and this has largely been done in my own time.
I have had to prioritise work on a local version of this analysis (https://wsx-c19-weekly-supplement.netlify.app) which is updated every day as new data is released. The West Sussex version does contain some comparisons with other areas (including maps) but it is focused primarily on the districts and boroughs in the county only.
For the time being, I will not be updating this version, which showed West Sussex and other Local Authorities in the South East of England. There may be an opportunity in the future for me to catch up with the changes and present a view comparing areas. Many Local Authorities are now publishing their own weekly updates of the local pictures and these provide valuable interpretations of the data so I would recommend searching for your local authority webpages and sign up to alerts.


Platform independent mutex mechanism. More...
#include <stdint.h>
Go to the source code of this file.
Enumerations | |
| enum | xtmemory_types_t { XTMEMORY_DEFAULT, XTMEMORY_SLOW, XTMEMORY_FAST, XTMEMORY_INVALID = -1 } |
Functions | |
| void | xtmemory_set_new_memory_type (xtmemory_types_t type) |
| Set which memory store to use for C++ new operator. More... | |
| xtmemory_types_t | xtmemory_get_new_memory_type (void) |
| Get which memory store is used for C++ new operator. More... | |
| xtmemory_types_t | xtmemory_classify (void *ptr) |
| Get which memory type the pointer has. More... | |
| void * | xtmemory_malloc_default (uint32_t size) |
| Allocate memory from default location. More... | |
| void | xtmemory_free_default (void *ptr) |
| Free memory allocated by xtmemory_malloc_default. More... | |
| uint32_t | xtmemory_heap_watermark_default (void) |
| Get the default memory usage watermark indicated by historically lowest amount of available memory. More... | |
| uint32_t | xtmemory_heap_available_default (void) |
| Get amount of default heap memory available. More... | |
| void * | xtmemory_malloc_slow (uint32_t size) |
| Allocate memory from slow location. More... | |
| void | xtmemory_free_slow (void *ptr) |
| Free memory allocated by xtmemory_malloc_slow. More... | |
| uint32_t | xtmemory_heap_watermark_slow (void) |
| Get the slow memory usage watermark indicated by historically lowest amount of available memory. More... | |
| uint32_t | xtmemory_heap_available_slow (void) |
| Get amount of slow heap memory available. More... | |
| void * | xtmemory_malloc_fast (uint32_t size) |
| Allocate memory from fast location. More... | |
| void | xtmemory_free_fast (void *ptr) |
| Free memory allocated by xtmemory_malloc_fast. More... | |
| uint32_t | xtmemory_heap_watermark_fast (void) |
| Get the fast memory usage watermark indicated by historically lowest amount of available memory. More... | |
| uint32_t | xtmemory_heap_available_fast (void) |
| Get amount of fast heap memory available. More... | |
Platform independent mutex mechanism.
This is a generic interface to a mutex mechanism, providing methods to create, lock and unlock the mutex.
| enum xtmemory_types_t |
| xtmemory_types_t xtmemory_classify | ( | void * | ptr | ) |
Get which memory type the pointer has.
| void xtmemory_free_default | ( | void * | ptr | ) |
Free memory allocated by xtmemory_malloc_default.
| ptr | Pointer to memory |
| void xtmemory_free_fast | ( | void * | ptr | ) |
Free memory allocated by xtmemory_malloc_fast.
| ptr | Pointer to memory |
| void xtmemory_free_slow | ( | void * | ptr | ) |
Free memory allocated by xtmemory_malloc_slow.
| ptr | Pointer to memory |
| xtmemory_types_t xtmemory_get_new_memory_type | ( | void | ) |
Get which memory store is used for C++ new operator.
| uint32_t xtmemory_heap_available_default | ( | void | ) |
Get amount of default heap memory available.
| uint32_t xtmemory_heap_available_fast | ( | void | ) |
Get amount of fast heap memory available.
| uint32_t xtmemory_heap_available_slow | ( | void | ) |
Get amount of slow heap memory available.
| uint32_t xtmemory_heap_watermark_default | ( | void | ) |
Get the default memory usage watermark indicated by historically lowest amount of available memory.
| uint32_t xtmemory_heap_watermark_fast | ( | void | ) |
Get the fast memory usage watermark indicated by historically lowest amount of available memory.
| uint32_t xtmemory_heap_watermark_slow | ( | void | ) |
Get the slow memory usage watermark indicated by historically lowest amount of available memory.
| void* xtmemory_malloc_default | ( | uint32_t | size | ) |
Allocate memory from default location.
Use operating system mechanism to allocate default memory. Normally internal SRAM.
Size of memory segment is defined in linker script - XEP memory management.
| void* xtmemory_malloc_fast | ( | uint32_t | size | ) |
Allocate memory from fast location.
Use operating system mechanism to allocate special fast memory. This can be Tightly Coupled Memory.
Size of memory segment is defined in linker script - XEP memory management.
| void* xtmemory_malloc_slow | ( | uint32_t | size | ) |
Allocate memory from slow location.
Use operating system mechanism to allocate slow memory. Normally external SRAM/SDRAM.
Size of memory segment is defined in linker script - XEP memory management.
| void xtmemory_set_new_memory_type | ( | xtmemory_types_t | type | ) |
Set which memory store to use for C++ new operator.


Armbar Open Guard
Hold ops tricep (or rest left arm over their right arm around elbow) try not to give away that your going for an armbar
Right hand goes down to ops left knee, get a grip to assist with moving your body 90degrees to that side
Left leg swings out to assist with body move, then drops over ops head/neck and presses down, left knee wants to be lower than right
Hip up, make sure ops elbow is visible, keep their thumb up.
Note: Foot in hip and leg goes up behind ops arm/shoulder to stop them pulling it back as you setup the armbar, hip up to get ops elbow deeper


Java is an object-oriented and feature-heavy programming language that’s in high demand.
It’s been built under the premise of “Write once, run anywhere,” meaning that it can be written on any device and work cross-platform.


We bundled our picnic things into gunny sacks and set out upon the road to Poxhaven. It is a long straight track, some say a ley line, pitted with many puddles, the road to Poxhaven. “Oh where are you going?” asked passing peasants, and we replied, “We are heading for Poxhaven.” And soon enough through mist and rain we saw a signpost and on the signpost, scratched it seemed by the claws of a werewolf, were the words “To Poxhaven”.
In centuries past, when town and city and countryside were ravaged by the pox, teeming thousands fled to safety along this road, to find a haven from the pox in the seaside resort of Poxhaven. Now it is for picnics we go to Poxhaven. Even in mist and rain you will find no better picnicking spot than among the many many picnic spots of Poxhaven.
There are werewolves too, werewolves that roam the streets and alleys and mews of Poxhaven. In centuries past they fed upon the pox-riddled escapees from town and city and countryside who made it as far as Poxhaven. Now the werewolves howl in hunger when dusk descends upon Poxhaven. It is a custom, and one we follow, when our picnic is done, to leave for the starving werewolves a few leftover picnic sausages, injected with the pox, upon a seaside picnic spot in Poxhaven.
As we trudge home, along the old straight track, in the dusk, we hear the grateful howling of the sausage-gobbling werewolves of Poxhaven.


Reference clock support maintains the fiction that the clock is actually an ordinary peer in the NTP tradition, but operating at a synthetic stratum of zero. The entire suite of algorithms used to filter the received data, select the best clocks or peers and combine them to produce a local clock correction are operative as with ordinary NTP peers. In this way, defective clocks can be detected and removed from the peer population. As no packets are exchanged with a reference clock, however, we replace the transmit, receive and packet procedures with separate code to simulate them.
Radio and modem reference clocks by convention have addresses in the
form 127.127.t.u,
, where t is the
clock type and u in the range 0-3 is used to distinguish multiple
instances of clocks of the same type. Most clocks require a serial port
or special bus peripheral. The particular device is normally specified
by adding a soft link /dev/devicedd
to the
particular hardware device involved, where d
corresponds to the unit number.
The best way to understand how the clock drivers work is to study the
ntp_refclock.c
module and one of the drivers already
implemented, such as refclock_wwvb.c
. Routines
refclock_transmit()
and refclock_receive()
maintain the peer variables in a state analogous to an actual peer and
pass received data on through the clock filters. Routines
refclock_peer()
and refclock_unpeer()
are
called to initialize and terminate reference clock associations, should
this ever be necessary. A set of utility routines is included to open
serial devices, process sample data, edit input lines to extract
embedded timestamps and to perform various debugging functions.
The main interface used by these routines is the
refclockproc
structure, which contains for most drivers the
decimal equivalents of the year, day, month, hour, second and
millisecond/microsecond decoded from the ASCII timecode. Additional
information includes the receive timestamp, exception report, statistics
tallies, etc. In addition, there may be a driver-specific unit structure
used for local control of the device. The support routines are passed a
pointer to the peer
structure, which is used for all peer-
specific processing and contains a pointer to the
refclockproc
structure, which in turn contains a pointer to
the unit structure, if used. A table typeunit[type][unit]
contains the peer structure pointer for each configured clock type and
unit.
Many drivers support the tty_clk
and/or
ppsclock
line disciplines or streams modules described in
the included in the Line Disciplines and Streams
Modules page. The tty_clk
module reduces latency errors
due to the operating system and serial port code in slower systems. The
ppsclock
module is an interface for the PPS signal provided
by some radios. It can be connected via a level converter/pulse
generator described in the Gadget Box PPS Level
Converter and CHU Modem page.
By convention, reference clock drivers are named in the form
refclock_xxxx.c
, where xxxx is a unique
string. Each driver is assigned a unique type number, long-form driver
name, short-form driver name, and device name. The existing assignments
are in the Reference Clock Drivers page
and its dependencies. Drivers are conditionally compiled using a unique
flag string in the CLOCKDEFS
line described in the Configuration Options page.
The standard clock driver interface includes a set of common support
routines some of which do such things as start and stop the device, open
the serial port, and establish special functions such as PPS signal
support. Other routines read and write data to the device and process
time values. Most drivers need only a little customizing code to, for
instance, transform idiosyncratic timecode formats to standard form,
poll the device as necessary, and handle exception conditions. A
standard interface is available for remote debugging and monitoring
programs, such as ntpq
and ntpdc
, as well as
the filegen
facility, which can be used to record device
status on a continuous basis.
The interface code and this documentation have been developed over some time and required not a little hard work converting old drivers, etc. Should you find success writing a driver for a new radio or modem service, please consider contributing it to the common good. Send the driver file itself and patches for the other files to Dave Mills (mills@udel.edu).
A new reference clock implementation needs to supply, in addition to the driver itself, several changes to existing files.
./include/ntp.h
REFCLK_xxxx
identification code should be recorded in the list opposite its assigned
type number.
./libntp/clocktypes.c
./libntp/clktype
array is used by certain display
functions. A unique short-form name of the driver should be entered
together with its assigned identification code.
./ntpd/ntp_control.c
clocktypes
array is used for certain control
message displays functions. It should be initialized with the reference
clock class assigned to the driver, as per the NTP specification
RFC-1305. See the ./include/ntp_control.h
header file for
the assigned classes.
./ntpd/refclock_conf.c
refclock_conf
array is a set of pointers to transfer vectors in the individual
drivers. The external name of the transfer vector should be initialized
in correspondence with the type number.
./acconfig.h
/* Define if we have a FOO clock */ #undef FOO
where FOO is the define used to cause the driver to be included in the distribution.
./configure.in
AC_MSG_CHECKING(FOO clock_description) AC_ARG_ENABLE(FOO, [ --enable-FOO clock_description], [ntp_ok=$enableval], [ntp_ok=$ntp_eac]) if test "$ntp_ok" = "yes"; then ntp_refclock=yes AC_DEFINE(FOO) fi AC_MSG_RESULT($ntp_ok)
(Note that $ntp_eac
is the value from --
{dis,en}able-all-clocks
for non-PARSE clocks and
$ntp_eacp
is the value from --{dis,en}able-parse-
clocks
for PARSE clocks. See the documentation on the autoconf
and automake tools from the GNU distributions.)
./ntpd/Makefile.am
This is the makefile prototype used by the autoconfigure scheme.
Add the driver file name to the entries already in the
ntpd_SOURCES
list.
Patches to automake-1.0
are required for the
autoconfigure scripts to work properly. The file automake-
1.0.patches
can be used for this purpose.
./ntpd/Makefile.am
automake autoconf autoheader configure
or simply run make
, which will do this command sequence
automatically.
refclock_newpeer
- initialize and start a reference
clock
refclock_unpeer
- shut down a clock
refclock_transmit
- simulate the transmit procedure
refclock_sample
- process a pile of samples from the
clock
fudgetime1
can be added to the final offset to compensate
for various systematic errors. The routine returns one if success and
zero if failure due to invalid timecode data or very noisy offsets.
Note that no provision is included for the year, as provided by some (but not all) radio clocks. Ordinarily, the year is implicit in the Unix file system and hardware/software clock support, so this is ordinarily not a problem. Nevertheless, the absence of the year should be considered more a bug than a feature and may be supported in future.
refclock_receive
- simulate the receive and packet
procedures
refclock_gtlin
- groom next input line and extract
timestamp
tty_clk
line
discipline/streams module, it returns that as the timestamp; otherwise,
it returns the buffer timestamp. The routine return code is the number
of characters in the line.
refclock_open
- open serial port for reference clock
refclock_ioctl
- set serial port control functions
termios
), SYSV
(termio
) and BSD (sgtty
) interfaces with
varying degrees of success. The routine sets up the tty_clk,
chu_clk
and ppsclock
streams module/line discipline,
if compiled in the daemon and requested in the call. The routine returns
one if success and zero if failure.
refclock_control
- set and/or return clock values
fudgetimes, fudgevalues,
reference ID and stratum.
refclock_buginfo
- return debugging info
ntpdc
and the clkbug
command.


Front camera
Back camera
-1
Delay:
sec
Looping
-- No category manually selected--
Automatic Proposition
Delete Pictures


Data Analyst with proven skills in data wrangling, mining, and visualization. Graduate of the Data Analytics and Visualization Bootcamp through the University of Central Florida. Strong skills in critical-thinking and research implementation. Excellent communication and effectively collaborates with others to ensure goals are achieved. Resourceful problem-solver with superior conflict resolution skills.
Role: Extract tree data using beautiful soup, transform using Python and load into MySQL. Build flask app.
I enjoy participating in physical activities such as biking, hiking, and rock climbing. When it comes to cooling down in Florida heat, I prefer springs over beaches. I have been a fitness class trainer at the University of Central Florida.
Other than being active I enjoy trying new foods, searching for local gems, and expanding my knowledge in tech. Subjects I am interested in are relating to Data Analyst, Data Scientist, Data Engineer, and Visualization Analyst.


|
|
Boost.RegexUnderstanding Captures |
|
Captures are the iterator ranges that are "captured" by marked sub-expressions as a regular expression gets matched. Each marked sub-expression can result in more than one capture, if it is matched more than once. This document explains how captures and marked sub-expressions in Boost.Regex are represented and accessed.
Every time a Perl regular expression contains a parenthesis group (), it spits out an extra field, known as a marked sub-expression, for example the expression:
(\w+)\W+(\w+)
Has two marked sub-expressions (known as $1 and $2 respectively), in addition the complete match is known as $&, everything before the first match as $`, and everything after the match as $'. So if the above expression is searched for within "@abc def--", then we obtain:
$`
"@" $& "abc def" $1 "abc" $2 "def" $' "--"
In Boost.regex all these are accessible via the match_results class that gets filled in when calling one of the matching algorithms (regex_search, regex_match, or regex_iterator). So given:
boost::match_results<IteratorType> m;
The Perl and Boost.Regex equivalents are as follows:
Perl Boost.Regex $` m.prefix() $& m[0] $n m[n] $' m.suffix()
In Boost.Regex each sub-expression match is represented by a sub_match object, this is basically just a pair of iterators denoting the start and end possition of the sub-expression match, but there are some additional operators provided so that objects of type sub_match behave a lot like a std::basic_string: for example they are implicitly convertible to a basic_string, they can be compared to a string, added to a string, or streamed out to an output stream.
When a regular expression match is found there is no need for all of the marked sub-expressions to have participated in the match, for example the expression:
(abc)|(def)
can match either $1 or $2, but never both at the same time. In Boost.Regex you can determine which sub-expressions matched by accessing the sub_match::matched data member.
When a marked sub-expression is repeated, then the sub-expression gets "captured" multiple times, however normally only the final capture is available, for example if
(?:(\w+)\W+)+
is matched against
one fine day
Then $1 will contain the string "day", and all the previous captures will have been forgotten.
However, Boost.Regex has an experimental feature that allows all the capture information to be retained - this is accessed either via the match_results::captures member function or the sub_match::captures member function. These functions return a container that contains a sequence of all the captures obtained during the regular expression matching. The following example program shows how this information may be used:
#include <boost/regex.hpp> #include <iostream> void print_captures(const std::string& regx, const std::string& text) { boost::regex e(regx); boost::smatch what; std::cout << "Expression: \"" << regx << "\"\n"; std::cout << "Text: \"" << text << "\"\n"; if(boost::regex_match(text, what, e, boost::match_extra)) { unsigned i, j; std::cout << "** Match found **\n Sub-Expressions:\n"; for(i = 0; i < what.size(); ++i) std::cout << " $" << i << " = \"" << what[i] << "\"\n"; std::cout << " Captures:\n"; for(i = 0; i < what.size(); ++i) { std::cout << " $" << i << " = {"; for(j = 0; j < what.captures(i).size(); ++j) { if(j) std::cout << ", "; else std::cout << " "; std::cout << "\"" << what.captures(i)[j] << "\""; } std::cout << " }\n"; } } else { std::cout << "** No Match found **\n"; } } int main(int , char* []) { print_captures("(([[:lower:]]+)|([[:upper:]]+))+", "aBBcccDDDDDeeeeeeee"); print_captures("(.*)bar|(.*)bah", "abcbar"); print_captures("(.*)bar|(.*)bah", "abcbah"); print_captures("^(?:(\\w+)|(?>\\W+))*$", "now is the time for all good men to come to the aid of the party"); return 0; }
Which produces the following output:
Expression: "(([[:lower:]]+)|([[:upper:]]+))+" Text: "aBBcccDDDDDeeeeeeee" ** Match found ** Sub-Expressions: $0 = "aBBcccDDDDDeeeeeeee" $1 = "eeeeeeee" $2 = "eeeeeeee" $3 = "DDDDD" Captures: $0 = { "aBBcccDDDDDeeeeeeee" } $1 = { "a", "BB", "ccc", "DDDDD", "eeeeeeee" } $2 = { "a", "ccc", "eeeeeeee" } $3 = { "BB", "DDDDD" } Expression: "(.*)bar|(.*)bah" Text: "abcbar" ** Match found ** Sub-Expressions: $0 = "abcbar" $1 = "abc" $2 = "" Captures: $0 = { "abcbar" } $1 = { "abc" } $2 = { } Expression: "(.*)bar|(.*)bah" Text: "abcbah" ** Match found ** Sub-Expressions: $0 = "abcbah" $1 = "" $2 = "abc" Captures: $0 = { "abcbah" } $1 = { } $2 = { "abc" } Expression: "^(?:(\w+)|(?>\W+))*$" Text: "now is the time for all good men to come to the aid of the party" ** Match found ** Sub-Expressions: $0 = "now is the time for all good men to come to the aid of the party" $1 = "party" Captures: $0 = { "now is the time for all good men to come to the aid of the party" } $1 = { "now", "is", "the", "time", "for", "all", "good", "men", "to", "come", "to", "the", "aid", "of", "the", "party" }
Unfortunately enabling this feature has an impact on performance (even if you don't use it), and a much bigger impact if you do use it, therefore to use this feature you need to:
Revised 12 Dec 2003
© Copyright John Maddock 2003
Use, modification and distribution are subject to the Boost Software License, Version 1.0. (See accompanying file LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)


Top Speed(km/hr): 40 Accelaration(m/s): 1.71 Gradeability(%): 17.72 Turning Radius (/m): 2.49 BATTERY: Li-ion 48V 35A-hr Motor: 400W BLDC Suspension: Front = Disc; Rear = Disc + BrakeShot Wheel Base(in): 41 Track Width(in): 34 Ground Clearance(in): 8
• EC 24: 24V 35A-hr Battery(Li-ion) • EC 36: 36V 35A-hr Battery(Li-ion) • EC 48L: 48V 35A-hr Battery (Lead Acid) • EC 48F: 48V 35A-hr Battery(Li-ion)
Team Leader/Marketing & Sales
Brakes
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Frame
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"The best teamwork comes from men who are working independently toward one goal in unison." .


--- title: Scraping Wikipedia Tables from Lists for Visualisation author: Gokhan Ciflikli date: '2018-01-30' slug: scraping-wikipedia categories: - R - Visualization tags: - R - rvest - ggridges - quanteda description: "Extracting table contents from Wikipedia and generating plots going back two millennia" ---
Recently I was asked to submit a short take-home challenge and I thought what better excuse for writing a quick blog post! It was on short notice so initially I stayed within the confines of my comfort zone and went for something safe and bland. However, I alleviated that rather fast; I guess you want to stand out a bit in a competitive setting. Note that it was a visualisation task, so the data scraping was just a necessary evil. On that note.
I resorted to using Wikipedia as I was asked to visualise change in a certain x
going back about 500 hundred years. Not many academic datasets go that far, so Wiki will have to do for our purposes.  First, we need a subject. I went with my PhD topic, war duration. So let’s get the list of lists first using rvest
:
#Get wikipedia time periods for List of Wars
url <- "https://en.wikipedia.org/wiki/Timeline_of_wars"
periods <- url %>%
read_html() %>%
html_nodes("ul") %>%
html_text(trim = TRUE) %>%
strsplit(split = "\n") %>%
unlist()
periods <- periods[18:26]
periods[1] <- tolower(gsub(" ", "_", periods[1]))
periods
## [1] "before_1000" "1000–1499" "1500–1799" "1800–99"
## [5] "1900–44" "1945–89" "1990–2002" "2003–10"
## [9] "2011–present"
I explained the basics of rvest
in my Game of Thrones post, so I won’t go over it again. The periods vector looks good, but not really: the timeframes themselves are lists; e.g. 1800-99 actually consists of ten tables. If we run a loop, we will only get the first table of each timeframe. I would know, that’s what I got in my first attempt. Jesus, so many missing years, Wikipedia.
We need to construct an indicator to guide the loop at each timeframe. I didn’t do this programmatically, and I would be happy to know how, but I just entered the number of tables per timeframe manually in a sequence:
tables <- c(3, 1:6, 1:3, 1:10, 1:3, 1:5, rep(1, 3))
sequences <- c(periods[1],
rep(periods[2], 6),
rep(periods[3], 3),
rep(periods[4], 10),
rep(periods[5], 3),
rep(periods[6], 5),
periods[7:9])
tables
## [1] 3 1 2 3 4 5 6 1 2 3 1 2 3 4 5 6 7 8 9 10 1 2 3
## [24] 1 2 3 4 5 1 1 1
sequences
## [1] "before_1000" "1000–1499" "1000–1499" "1000–1499"
## [5] "1000–1499" "1000–1499" "1000–1499" "1500–1799"
## [9] "1500–1799" "1500–1799" "1800–99" "1800–99"
## [13] "1800–99" "1800–99" "1800–99" "1800–99"
## [17] "1800–99" "1800–99" "1800–99" "1800–99"
## [21] "1900–44" "1900–44" "1900–44" "1945–89"
## [25] "1945–89" "1945–89" "1945–89" "1945–89"
## [29] "1990–2002" "2003–10" "2011–present"
Now, we can pass the base url in a loop using the above:
#Create a loop for extracting all wars since 1AD
baseurl <- "https://en.wikipedia.org/wiki/List_of_wars_"
all.wars <- NULL
for (i in 1:length(sequences)) {
url <- paste0(baseurl, sequences[i])
webpage <- read_html(url)
wars <- webpage %>%
html_nodes(xpath = paste0('//*[@id="mw-content-text"]/div/table[', tables[i], ']')) %>%
html_table(fill = TRUE)
all.wars[i] <- list(wars)
}
#All wars as a dataset
df <- ldply(all.wars, data.frame)
df <- df %>% arrange(Start)
Welcome to the world of uncurated data, so let’s clean it up. First, there are some internal Wikipedia inconsistencies, so we will move columns around. Then, we will extract the first set of digits to get rid of the likes of ‘c1660, 1922(armistice), 1860s’ etc. Finally, we will drop the NA
s and recode ongoing wars to 2018:
#Clean up Wikipedia inconsistencies
df$Name.of.Conflict <- ifelse(is.na(df$Name.of.Conflict),
df$Name.of.conflict, df$Name.of.Conflict)
df$Finish <- ifelse(is.na(df$Finish), df$Finished, df$Finish)
#Extract first set of digits as dates
df$Start <- stri_extract_first(df$Start, regex = "\\d+")
df$Finish <- stri_extract_first(df$Finish, regex = "\\d+")
#Drop NAs and correct starting dates
df <- df[, 1:5]
df <- df %>% arrange(Start)
#Correct finish dates
df$Start <- as.numeric(df$Start)
df$Finish <- as.numeric(df$Finish)
df <- df[!is.na(df$Start), ]
#Change ongoing to 2018 finish
df$Finish <- ifelse(is.na(df$Finish), 2018, df$Finish)
glimpse(df)
## Observations: 2,117
## Variables: 5
## $ Start <dbl> 1008, 101, 1010, 1014, 1015, 1018, 1018, 1019...
## $ Finish <dbl> 1008, 102, 1011, 1014, 1016, 1018, 1019, 1019...
## $ Name.of.Conflict <chr> "Hungarian–Ahtum War", "First Dacian War", "S...
## $ Belligerents <chr> "Kingdom of Hungary", "", "Liao Dynasty", "Mu...
## $ Belligerents.1 <chr> "Voivodship of Ahtum", "", "Goryeo", "Leinste...
Better. Still, we don’t have that many interesting variables in there. Most of my research focuses on the distinction between interstate and civil wars, especially how they differ in their average duration over time. We can programatically identify civil wars using an arbitrary criteria with text analysis. Below, I use quanteda
to accomplish the task:
#Programmatically identify civil wars using text analysis
#Define arbitrary civil war words
intrastate <- c("Revolt", "Rebellion", "Civil", "Insurgency", "Interregnum", "Uprising")
df.corpus <- corpus(df[, 3])
df.tokens <- tokens(df.corpus, what = "word")
#Identify rows that include civil war words in title
civil.wars <- tokens_select(df.tokens, pattern = intrastate, selection = "keep")
indicator <- as.data.frame(unlist(civil.wars))
#Extract row numbers as digits and only keep the first four
indicator$row <- substr(gsub("[^0-9]", "", rownames(indicator)), 1, 4)
#Drop duplicates
indicator <- distinct(indicator)
rownames(df) <- 1:nrow(df)
df$Civil.War <- ifelse(rownames(df) %in% indicator$row, 1, 0)
df$Civil.War <- as.factor(df$Civil)
df$`War Type` <- ifelse(df$Civil.War == 0, "Interstate", "Civil War")
Now that we are here, might as well include duration:
#Create a duration variable (years)
df$Duration <- (df$Finish - df$Start) + 1
#Create century indicator based on start year
df$Century <- as.integer(df$Start / 100) + 1
df$Century <- paste0(df$Century, ifelse(df$Century == 2, "nd Century",
ifelse(df$Century == 3, "rd Century",
ifelse(df$Century == 1 | df$Century == 21,
"st Century", "th Century"))))
df$Century <- as.factor(df$Century)
#Reorder levels from 1st to 21st
df$Century <- factor(df$Century, levels(df$Century)[c(11, 14:21, 1:10, 12:13)])
#Need this for later
df$Quarter <- ceiling(df$Start / 25)
Okay, so far we have collected information on conflict name, belligerents, start and end years, duration, century, and quarter. We can still create more from our existing data. Wikipedia, where applicable, (for the lack of a better word) codes belligerents as victorious and defeated. Meaning, if we extract the names of Side A and Side B over time, we might be able to capture the patterns of who ‘won’ and ‘lost’ in the last two thousand years. 1 I only include the code for the winners below and do the same for the defeated parties under the hood:
#Commonalities of belligerents by century
#Pool text for winners
victors <- df$Belligerents
victors <- gsub("\n", " ", victors)
#Group by century and identify most frequent words
dfm.vic <- dfm(corpus(victors, docvars = data.frame(Century = df$Century)),
remove = stopwords("SMART"), remove_numbers = TRUE,
remove_punct = TRUE, groups = "Century")
vic.top.words <- topfeatures(dfm.vic, n = 5, groups = docnames(dfm.vic))
#Transform list to dataframe
vic <- as.data.frame(unlist(vic.top.words))
vic$Century <- sub('\\..*', '', rownames(vic))
vic$Word <- sub('.*\\.', '', rownames(vic))
vic$Side <- "Victorious"
colnames(vic)[1] <- "Count"
Now we combine them together and create our second dataset:
#Combine and clean up
sides <- rbind(vic, def)
rownames(sides) <- 1:nrow(sides)
sides$Count <- log2(sides$Count) + .1
sides$Count <- ifelse(sides$Side == "Victorious", -sides$Count, sides$Count)
sides$Century <- as.factor(sides$Century)
sides$Century <- factor(sides$Century, levels(sides$Century)[c(11, 14:21, 1:10, 12:13)])
sides <- sides %>% group_by(Century, Word) %>% mutate(Duplicate = n() - 1)
sides$Word <- ifelse(sides$Duplicate == 0, sides$Word, paste0(sides$Word, "(", tolower(substr(sides$Side, 1, 3)), ")"))
I convert the count value for the victorious side to negative after taking its log for plotting purposes.
Okay, fun part. Also, note that we need all that code to get the data and clean it up while the visualisations are maybe one little chunk of code. Anyway, the first visualisation I had in mind is the one I used for my Weinstein effect post. In my head-cannon, I call it the ‘tidytext difference chart’, but I’m sure there’s a proper name for it. One thing I couldn’t figure out was achieving perfect sorting; not sure what causes that (e.g. Byzantine in the 9th Century, Khaganate in the 10th century etc.). Twitter solved it!
#Requires devtools::install_github("dgrtwo/drlib")
ggplot(sides, aes(reorder_within(x = Word, by = Count, within = Century), Count, fill = Side)) +
scale_x_reordered() +
facet_wrap(~Century, scales = "free_y") +
geom_col() +
coord_flip() +
scale_y_continuous(labels = c("12X", "", "8X", "", "4X", "", "",
"", "4X", "", "8X", "", "12X"),
breaks = seq(-6, 6)) +
geom_hline(yintercept = 0, alpha = .4) +
theme(legend.position = c(.5, .05)) +
labs(title = "Who Participates in Organised Violence: Change in Actor Characteristics 1 AD-2018 AD",
subtitle = "Five Most Common Descriptors based on Wikipedia Conflict Names | Stratified by Belligerent Type | Clustered by Century",
caption = "@gokhan_ciflikli | Source: Wikipedia",
x = "Most Frequent Words",
y = "Logarithmic Scale") +
guides(fill = guide_legend(reverse = TRUE))
It’s not low-resolution friendly so click here. Even though Wikipedia is not an academic source and the findings should be taken with a grain of salt, the visualisation captures what we would expect to see in terms of the evolution of armed conflict over the last two millennia in terms of actors and outcome. Romans and Chinese dynasties dominate the first five centuries, followed by the Germanic tribes and Muslim empires in the following 500 years. From the 11th century onwards, we begin to see major European powers and parties associated with the Crusades. In the next five centuries (16th-20th), we witness the fall of the Ottoman Empire and serial defeats of the ‘rebel’ factions. Finally, the 21st century (only 17 years of data) is marked by the US ‘winning’ and Islamic movements being defeated. We also see that the data can be cleaned further, e.g. the ‘unknown’ faction in the 8th century.
Although we differentiated between interstate and civil wars using an arbitrary selection of terms, it could still be interesting to plot their average durations over centuries. A good old box-plot will do nicely. I subset the data so that it only displays conflicts that lasted less than 25 years:
#Average duration
ggplot(df[df$Duration < 25, ], aes(Century, Duration)) +
geom_boxplot(aes(fill = `War Type`)) +
labs(title = "Average Armed Conflict Duration, 1 AD-2018 AD",
subtitle = "Based on Wikipedia Start/End Dates | Subset of Duration < 25 years | n = 1965",
caption = "@gokhan_ciflikli | Source: Wikipedia",
x = "Timeframe",
y = "Duration (years)") +
theme(legend.position = c(.125, .9),
axis.text.x = element_text(angle = 45, vjust = .6))
Larger resolution here. With the exception of the 2nd century, which could very well be data-quality related, we kind of observe similar patterns for both types of war but sometimes with different intervals. The outliers become more prominent in the last five centuries or so as well. However, note that we transformed ongoing conflicts to an end date of 2018, so we could be picking up those towards the tail.
Finally, as a part of my self-issued non-viridis challenge (i.e. have a visualisation post without using viridis), I want to revisit ggridges
again. We already show the important descriptives with the box-plot, so for this one I want to show, grouped by onset century, how long those conflicts lasted. I cluster the conflicts of the same type by quarter so that we have enough density in each century (otherwise some of the earlier centuries would be empty). Here it goes:
#Variation
ggplot(df, aes(y = fct_rev(Century))) +
geom_density_ridges(aes(x = Duration, fill = paste(Quarter, `War Type`)),
alpha = .9, color = "white", from = 0, to = 100) +
labs(x = "Years Lasted",
y = "Conflict Onset",
title = "Variation in Conflict Duration by Century and War Type, 1 AD-2018 AD",
subtitle = "War Duration based on Wikipedia Start Year | <100 Years Long Conflicts Subset | n = 2093",
caption = "@gokhan_ciflikli | Source: Wikipedia") +
scale_y_discrete(expand = c(.01, 0)) +
scale_x_continuous(expand = c(.01, 0)) +
scale_fill_cyclical(values = c("#ed7875", "#48bdc0"),
labels = c("Civil War", "Interstate"),
name = "War Type", guide = "legend") +
theme_ridges(grid = FALSE, font_family = "Roboto Condensed") +
theme(legend.position = c(.9, .9))
Enlarge!, a confused Picard might say in an alternate universe. On a more serious note, we find that conflicts we classify as civil wars based on their Wikipedia title have been regularly lasting more than 10+, 25+, 50+ years etc. since the 6th century. Then again, we don’t know the exact criteria for establishing the start and end dates, or even who decides what counts as conflict termination in a Wikipedia entry. With that said, feel free to experiment; code on GitHub as usual.
I quoted the terms as it is Wikipedia after all.↩


--- layout: page title: About header-img: "img/about-bg.png" ---
Former technical designer in fashion. Current software engineering student at the Flatiron School.


Ember.js
A framework for creating ambitious web applications.
Choose by trend?
Perspective.
A trend that matters (maybe?).
Client side applications are hard.
What do we want?
NOW!
When do we want it?
Race condition!
SPA challenges
- Long running apps: memory leaks.
- Serialize state into and out of the URL.
- Query parameters.
- Don't push type ahead searches onto the history stack
- Don't break the Back button.
- Optimize for all the browsers.
- Loading and error states
Conventions
- Common patterns should become framework conventions.
- Doing the wrong thing should be hard.
- You are not entirely unique; others have solved the same problems.
- "You can't not use a framework" -- Ryan Florence
MVC... but how?
- Routes turn the url into data.
- Models are persisted state.
- Views handle DOM events.
- Controllers are long lived local only state.
Mapping URLs.
-
var App = Ember.Application.create();
App.Router.map(function() {
this.resource('posts', {path: '/'}, function() {
this.route('create', {path: '/new-post'});
});
this.resource('post', {path: '/read/:id'});
});
Changing URLs.
-
var App = Ember.Application.create();
App.Router.map(function() {
this.resource('posts', {path: '/blog'}, function() {
this.route('create', {path: '/new'});
});
this.resource('post', {path: '/blog/:id'});
});
-
{{#link-to 'posts'}}Read my blog{{/link-to}}
{{#each posts}}
{{#link-to 'post' this}}Read more about {{title}}{{/link-to}}
{{/each}}
Ember Inspector: Routes
Ember Inspector: Promises
Ember Inspector: Performance
Ember CLI is the future.
- Under heavy development.
- I'm already using it; I think you can too.
- Go from idea to writing business logic in minutes.
npm install emberjs
ember serve
// write code
ember build --environment=production
Batteries included.
- Creates file structure.
- LiveReload, just install the browser plugin.
- Write ECMAScript 6 modules, it transpiles to ES5.
- Ready for testing using QUnit.
- Mock non-existent server endpoints.
What's this ES6 of which you speak?
import Geo from '../mixins/geo';
var privateGeo = Geo;
export default Ember.Controller.extend(Geo, Ember.Evented, {
location: function() {
this.trigger('moved');
}.observes('geolocation.latitude')
});
Closing.
- Googlebot now indexes single page apps quite well.
- Screen readers can navigate an Ember app.
- An Ember app is about the size of a small/medium image.
- Ember Components are based on the Web Component spec.
- HTMLBars
Jerel Unruh / @jerelunruh /<EMAIL_ADDRESS>window.close()


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| CUSTOMER | ENVIRONMENT | PRODUCT | COMPONENT | STATUS | LAST MODIFY DATE | |
|---|---|---|---|---|---|---|
| ALC | SIT | bingo | bingo-2.16 | INSTALLATION IN PROGRESS | 03/05/2016 | View Details |
| SPN | PROD | mobile-games | mobile-games-<IP_ADDRESS>.2 | TEST COMPLETED | 08/05/2016 | View Details |
| NT | NT1 | mobile-games | mobile-games-<IP_ADDRESS>.3 | CUSTOMIZATION IN PROGRESS | 10/05/2016 | View Details |
| STAR | DEV | bingo | bingo-2.16 | INSTALLATION BLOCKED | 11/05/2016 | View Details |


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java.util.function
package.See: Description
| Interface | Description |
|---|---|
| BooleanBinaryOperator |
Represents an operation upon two
boolean -valued operands and producing a
boolean -valued result. |
| BooleanConsumer | |
| BooleanPredicate |
Represents a predicate (boolean-valued function) of one
boolean -valued
argument. |
| BooleanUnaryOperator |
Represents an operation on a single
boolean -valued operand that produces an
boolean -valued result. |
| ByteBinaryOperator |
Represents an operation upon two
byte -valued operands and producing a
byte -valued result. |
| ByteConsumer | |
| BytePredicate |
Represents a predicate (boolean-valued function) of one
byte -valued
argument. |
| ByteUnaryOperator |
Represents an operation on a single
byte -valued operand that produces a
byte -valued result. |
| CharBinaryOperator |
Represents an operation upon two
char -valued operands and producing a
char -valued result. |
| CharConsumer | |
| CharPredicate |
Represents a predicate (boolean-valued function) of one
char -valued
argument. |
| CharUnaryOperator |
Represents an operation on a single
char -valued operand that produces a
char -valued result. |
| FloatBinaryOperator |
Represents an operation upon two
float -valued operands and producing a
float -valued result. |
| FloatConsumer | |
| FloatPredicate |
Represents a predicate (boolean-valued function) of one
float -valued
argument. |
| FloatUnaryOperator |
Represents an operation on a single
float -valued operand that produces a
float -valued result. |
| PartialBiFunction<T,U,R> |
A partial function that computes a value from two inputs.
|
| PartialFunction<T,R> |
A function that does not fully map the input domain to the output domain.
|
| PartialTriFunction<T,U,V,R> |
A partial function that computes a value from three inputs.
|
| ShortBinaryOperator |
Represents an operation upon two
short -valued operands and producing a
short -valued result. |
| ShortConsumer | |
| ShortPredicate |
Represents a predicate (boolean-valued function) of one
short -valued
argument. |
| ShortUnaryOperator |
Represents an operation on a single
short -valued operand that produces a
short -valued result. |
| TriConsumer<T,U,V> | |
| TriFunction<T,U,V,R> |
A functional interface that accepts three arguments and returns a value.
|
| TriPredicate<T,U,V> |
Like a
TriFunction , but returns a primitive boolean value. |
| Class | Description |
|---|---|
| Functions |
Numerous utility methods for using
Function s. |
| Operators | |
| PartialFunctions |
Numerous utility methods for using
PartialFunction s. |
| Predicates |
Numerous utility methods related to using
Predicate s. |
| Suppliers |
Utility methods for constructing and using
Supplier s. |
java.util.function
package. This
includes new functional interfaces, like PartialFunction
(and its kin) and numerous primitive specializations of standard interfaces (like
BooleanBinaryOperator
,
FloatPredicate
and
ShortConsumer
to name just a few).


The Bus Decoder component converts a 2 to 4-bit binary value on In to a true on one of four to sixteen output lines. The number of outputs is determined by the bit size and is configurable.
In this figure, a value of 4 (0b100) is decoded to a high on output O4, lighting the corresponding LED in an LED Bar. The Bus Decoder will also draw a line from the input to the corresponding activated output. If the input is out of range or undefined, the outputs are also undefined (?) and the line does not appear.


DANG MAI
... a Programmer Analyst at
The MENTOR Network.
... likes
dancing
and
making things
.
...
contributes
to open source projects.
... can be found on Linked
.


Egypt's Main Cities
Cairo
Cairo, Egypt’s sprawling capital, is set on the Nile River. At its heart is Tahrir Square and the vast Egyptian Museum, a trove of antiquities including royal mummies and gilded King Tutankhamun artifacts. Nearby, Giza is the site of the iconic pyramids and Great Sphinx, dating to the 26th century BC. In Gezira Island’s leafy Zamalek district, 187m Cairo Tower affords panoramic city views.
Alexandria
Alexandria is a Mediterranean port city in Egypt. During the Hellenistic period, it was home to a lighthouse ranking among the Seven Wonders of the Ancient World as well as a storied library. Today the library is reincarnated in the disc-shaped, ultramodern Bibliotheca Alexandrina. The city also has Greco-Roman landmarks, old-world cafes and sandy beaches. Its 15th-century seafront Qaitbay Citadel is now a museum.
Aswan
Aswan, a city on the Nile River, has been southern Egypt’s strategic and commercial gateway since antiquity. It contains significant archaeological sites like the Philae temple complex, on Agilkia Island near the landmark Aswan Dam. Philae’s ruins include the columned Temple of Isis, dating to the 4th century B.C. Downriver, Elephantine Island holds the Temple of Khnum, from the Third Dynasty.
Luxor
Luxor is a city on the east bank of the Nile River in southern Egypt. It's on the site of ancient Thebes, the pharaohs’ capital at the height of their power, during the 16th–11th centuries B.C. Today's city surrounds 2 huge, surviving ancient monuments: graceful Luxor Temple and Karnak Temple, a mile north. The royal tombs of the Valley of the Kings and the Valley of the Queens are on the river’s west bank.
Sharm El-Sheikh
Sharm el-Sheikh is an Egyptian resort town between the desert of the Sinai Peninsula and the Red Sea. It's known for its sheltered sandy beaches, clear waters and coral reefs. Naama Bay, with a palm tree-lined promenade, is filled with bars and restaurants. Ras Muhammad National Park is a major diving destination, with marine life around the Shark and Yolanda reefs and the Thistlegorm wreck.
Hurghada
Hurghada is a beach resort town stretching some 40km along Egypt’s Red Sea coast. It’s renowned for scuba diving, and has numerous dive shops and schools in its modern Sekalla district. There are many restaurants, bars and nightclubs, while the old town, El Dahar, is home to traditional Egyptian coffee shops and souks. Hurghada’s long stretch of sandy beach is lined with resort hotels.


Ability
Brock was a skilled Pokémon expert, because he was a gim leader and his knowledge of them caused Yuksi to contact him, which makes his martial art very tasty. He can cook amazing food for people and Pokemon, for which everyone loves him, he also has good fishing skills, sewing skills and cleaning skills.


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Triton's Resource of Latte Lovers
In CSE 110, we worked as a 10-person team to create coffee app that caters to people on the UCSD campus. The app shows coffee cart locations, menus, pricing, hours, and a dynamic map with icons for each location and Google Maps powered walking directions
YouTube version link to youtube.com
Embedded version