Repeat the given string n times. Fastest implementation for repeating a string.
Install with npm:
$ npm install repeat-string --save
Repeat the given string
the specified number
of times.
Example:
Params
string
{String}: The string to repeatnumber
{Number}: The number of times to repeat the stringreturns
{String}: Repeated stringExample
var repeat = require('repeat-string');
repeat('A', 5);
//=> AAAAA
Repeat string is significantly faster than the native method (which is itself faster than repeating):
#1: 5
native x 10,484,023 ops/sec ±1.24% (89 runs sampled)
repeat-string x 16,189,255 ops/sec ±1.05% (91 runs sampled)
repeating x 9,051,715 ops/sec ±1.18% (90 runs sampled)
#2: 50
native x 7,975,566 ops/sec ±1.29% (91 runs sampled)
repeat-string x 15,317,972 ops/sec ±1.16% (87 runs sampled)
repeating x 6,279,112 ops/sec ±1.29% (89 runs sampled)
#3: 250
native x 6,212,752 ops/sec ±1.33% (91 runs sampled)
repeat-string x 14,565,168 ops/sec ±0.83% (93 runs sampled)
repeating x 5,787,124 ops/sec ±1.25% (92 runs sampled)
#4: 2000
native x 4,912,163 ops/sec ±1.27% (91 runs sampled)
repeat-string x 17,129,748 ops/sec ±1.01% (91 runs sampled)
repeating x 4,613,043 ops/sec ±1.37% (91 runs sampled)
#5: 20000
native x 4,506,624 ops/sec ±1.33% (90 runs sampled)
repeat-string x 14,877,672 ops/sec ±1.00% (93 runs sampled)
repeating x 4,305,756 ops/sec ±1.36% (89 runs sampled)
Run the benchmarks
Install dev dependencies:
npm i -d && node benchmark
repeat-element: Create an array by repeating the given value n times. | homepage
Pull requests and stars are always welcome. For bugs and feature requests, please create an issue.
Generate readme and API documentation with verb:
$ npm install verb && npm run docs
Or, if verb is installed globally:
$ verb
Install dev dependencies:
$ npm install -d && npm test
Jon Schlinkert
Copyright © 2016 Jon Schlinkert Released under the MIT license.
This file was generated by verb, v0.9.0, on February 29, 2016.


WATER: Uranus has a tiiiny bit of water in its atmosphere!
ATMOSPHERE: The atmosphere here is mostly made of hydrogen and helium, with some methane gas (not good for breathing!).
GRAVITY: Gravity is a bit weaker than on Earth, so you can jump higher!
MOON: Uranus has six dark moons made of rocky ice, and ten really small, really dark new moons!
Brrr, it's cold here! Temperatures here are an average of -224 degrees Celsius, can you imagine how cold that would be? Uranus is the farthest planet from the Sun, and the first to be discovered by telescope. It's often called the "ice giant."


Exclusive Preview: Black Cat Annual #1
by Blair MarnellWay back in the ’80s, Felicia Hardy and Peter Parker were inseparable lovers. However, they eventually drifted apart. Spider-Man reunited with his first love, Mary Jane, and also went on to marry her. Meanwhile, Black Cat carried a torch for Spidey that made things difficult for them. Even when Felicia returned to a life of crime, she still had feelings for her ex. Now, out of nowhere, Black Cat and Spider-Man are getting married! And that’s just in the first two pages.
In Superhero Hype’s exclusive preview for Black Cat Annual #1, Jed MacKay is joined by artists Joey Vazquez, Natacha Bustos, and Juan Gedeon as they reveal why Spidey is marrying Felicia. Naturally, the cover image was just a distraction, much like the wedding itself. The real story is about what comes after, because Felicia has a plan. And she needs Spider-Man’s help to pull it off.
RELATED: First Look At X-Force #1
Here’s the official description from Marvel.
“You are cordially invited to the wedding of Black Cat and Spider-Man! In lieu of gifts, please turn off all your security systems, laser grids and counterweight giant stone traps. All this AND a bonus story?!”
You can read the full preview in our gallery below. Black Cat Annual #1 will hit comic book stores on Wednesday, November 13.
What did you think about the preview? Let us know in the comment section below!
Recommended Reading: Marvel Comics: 75 Years of Cover Art
We are a participant in the Amazon Services LLC Associates Program, and this affiliate advertising program provides a means to earn fees by linking to Amazon.com and affiliated sites.


Hello dear, I am Mr. Chiwetalu Philips Onuma, an accountant officer with Intercontinental Bank,Plc (I.B.P) branch here in Dakar Senegal. dear I gathered your information from my country's international chamber commerce and industries, The business I am about to introduce is based-on sheer trust and with a sense of purpose. I am contacting you to assist in repatriating the sum of eighteen million two hundred thousand united state dollars. The money and property left behind by (James Groover D.) an American Chair Merchant here in my country who died accidentally On the 21st of April 2004. Sir, I gathered all this information through a good source after my several routine note to his forwarding address because he had served here in Dakar Senegal as a business consultant with the Senegalese National Petroleum & Gas Cooperation.S.N.P.G.C and a legal adviser to the O.P.E.C Chairman. Since then I have made several inquiries to American embassy here in Dakar Senegal to locate any of his extended relatives or family, this has also proved unsuccessful to locate any member of his family hence I contacted you. I am his account officer and I contact you to work with you before the fund get confiscate or declared unserviced by the bank management and board of my directors because the management of my bank has been deliberating on how to revert this fund to the bank privacy and Since I have been unsuccessful in locating the relatives for over 3 years now, I seek your consent to present you as the next of kin to the deceased since you are a foreigner so that the proceeds of this account valued at eighteen million two hundred thousand united state dollars can be paid to you and then you and I will share the money fifty percent to me and forty percent to you, while ten percent will be mapped out for any miscellaneous expenses that might incur in the cause of this transaction. Note, I have all the necessary legal documents to back up this claim, and this I must do to make sure that this fund is not wasted or end up in the wrong hands. All I require is your honest and sincere co-operation to enable us see this ordeal and claim through, again I guarantee you that this transaction will be executed under a legitimate arrangement that will protect you and I from any breach of the law. Reply me through my private e-mail addres<EMAIL_ADDRESS>for further explanations before proceed and as soon as I hear from you, A VERY GOOD EVIDENCE WILL BE GIVING TO YOU FOR CONFIRMATIONS.Trusting to hearing from you. Yours Sincerely, Mr.Chiwetalu P. Onuma.


Yayady
.
THE QUOTES WILL BE GENERATED AND APPEAR HERE ....................
The writer
Generate Quotes


What is Yard Beer?
Passable beers can, in the current craft-heavy market, only passably qualify as beer. Technically, passable beers belong to the bland, straw-colored style properly classified as American Adjunct Lager. Around my house we just call them yard beers.
Why yard beer? Because when I've been sweating out in the yard for a few summer hours, that's the drink I want the most. About the last thing I want is, for example, an Imperial Russian Goat Milk Stout. A cold yard beer in the summer is actually my second-favorite beer.
Adjunct lagers were about the only kind of beer known to most of America until the late 1990's. Words like "bland" and "swill" get thrown at Bud, Miller, and Coors for good reason. Most of their beers are bland swill. But "bland swill" doesn't automatically equal bad — although in many, many cases it does.
Beer, like food and wine, is best enjoyed in its proper context. For instance, if asked to rank my favorite beers, Carib makes the list. I do not rate it highly because it is good, objectively speaking. I rate it highly because: 1) It isn't an outright assault on the taste buds and 2) I drank it on vacation in Grenada, where it fit with the vibe (and the temperature) perfectly. Yard beers are great travel companions in the Caribbean, and now I connect the taste of Carib with some of my fondest memories.
Big Beer's marketing for passable beers gives away the game. Passable beers are "clean", "crisp", and "refreshing" instead of "good", "delicious", or "tasty. This is because those first three adjectives are technically true and the latter three are such outright lies that even the advertising industry avoids them.
After working in the hot sun you want something crisp, clean, and refreshing. You want something bland that can be consumed in giant gulps. It can only passably be called beer, but then again most of these reviews will only passably qualify as "good writing." You get what you pay for.
Welcome to Passable Beer Reviews, where I review various yard beers (and their close relatives) to determine what's passable enough to drink.


Call/Check
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BB increase time (min):
5
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خوش آمدید به
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Plan your work!
Plan your work as you like.
Have the most freedom of action in planning.Control your habits.
Do not forget any of your work!
Share your Plans!
Share your schedule with others.
Inform your friends of your schedule. Comment on other people's public programs.
Help your friends break their bad habits!
Share your Plan!
It is a long established fact that a reader will be distracted by the readable content of a page when looking at its layout.
The point of using Lorem Ipsum is that it has a more-or-less normal distribution of letters,
as opposed to using 'Content here, content here', making it look like readable English.


BIOSKOP KOTA
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Film:
Power Ranger
Waktu:
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Billy Connolly says he wants special bed to help get him up in morning
The comedy legend said he’d love to find an alarm clock linked to a bed similar to one created by his hero John Muir.
by Bill CravenBilly Connolly says he wants to find a bed that throws him out in the morning.
The comedy legend said he’d love to find an alarm clock similar to one created by his hero – Dunbar-born naturalist John Muir.
Muir’s work included a device that was hooked to a bed which would flip up whenever it went off.
And Billy, 77, who is battling Parkinson’s disease which causes muscle stiffness, believes his start to the day would be easier if he could find one.
The Bafta winner was first diagnosed with the progressive neurological condition six years ago.
Glasgow-born Billy – who now lives in Florida – said: “Muir handmade these alarm clocks, big pieces of furniture that woke you in the morning and flung you out of bed.
“I could have it beside my bed, with a chute you slide down a Sleepy Wheecher.”
Muir – best remembered as the founder of the American Great Parks – devised his “early rising machine” to help set him on his feet.
Speaking of his admiration for Muir, Connolly said: “He was way ahead of his time.”


Kenneth
H. Zawojskyj
Phone:<PHONE_NUMBER> |<EMAIL_ADDRESS>OBJECTIVE
Gain experience in the workplace for future employment and college. Put computer skills to good use. Learn new skills to help strengthen my portfolio and gain new insight on how companies work.
WORK EXPERIENCE
Sorrento Pizza: (06/2015 – 05/2016) Shelby Township, MI
Delivery driver
Duties:
· Delivering orders to customers
· Taking orders over the counter and on the phone
Taco Bell: (06/2017-09/2017)
“Food and Service Champion”
Duties:
· Preparing food, packaging it and handing it out to customers
· Taking orders in drive thru, washing dishes, sweeping and mopping
EDUCATION
Dwight D. Eisenhower High School (Class of 2016) Shelby Township, MI
Some
courses I have taken:
· Microsoft Office
· Spanish I, II, and III
· AP Computer science
Macomb
Community College Warren,
MI
Some courses I have taken:
·
Microsoft in Business
·
Certified Ethical Hacker
· Business Communications
SKILLS
· I am certified in Microsoft Word, Excel, and PowerPoint through Centriport
· Certified computer networking pro through TestOut (Network+)
· Certified network security pro through TestOut (Security+)
· I am very good with technology.
· Always respectful and positive.
Certified in Microsoft office through Centriport as of 2014.
Certified Network+ through TestOut as of 2017.
Certified in Secuirty+ through TestOut as of 2017.


help to sponsor a patient by donating for their medical treatment.
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Full-Stack Developer with a Bsc. in Industrial Design Technology...devoted to the design of experiences.....with code and CAD
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All examples use Angular Resizeable Element NPM Package and is not a part of the module, if you need to update the responsive menu if size changes you have to implement it by your own, for the simple reason there are multiple possible triggers for resize (window, css-resize, ...).
To change size of Demo containers just drag right border and move it arround.


AccessCheck (sysinternals)
SubInACL Details about reg key permissions
[WindowsDACLEnumProject](https://github.com/nccgroup/WindowsDACLEnumProject) | A collection of tools to enumerate and analyse Windows DACLs
ProcMon Process monitor, see what DLLs an .exe attempts to load
[Invoke-ProcessScan](https://github.com/vysec/Invoke-ProcessScan) | Give context to processes, ie descriptions
PowershellEmpire
PowerSploit PowerSploit seems not maintained, but integrated into Empire
Get-GPPPassword, which is part of PowerSploit gather group policy passwords (if available)
PowerUp
PowerView
Etc
[SessionGopher](https://github.com/fireeye/SessionGopher) | session information from PuTTY, WinSCP, FileZilla, SuperPuTTY, and RDP, nice
Detect Kernel Exploits / Get Patch Level
Powershell: - Get-HotFix | Sort-Object HotFixID | Format-Table Autosize
- WMI:
- Get-WmiObject -Class "win32_quickfixengineering" | Select-Object -Property "Description", "HotfixID", @{Name="InstalledOn"; Expression={([DateTime]($_.InstalledOn)).ToLocalTime()}}
- Get-MicrosoftUpdate(tomarbuthnot)
WMIC:
wmic.exe qfe list full
Microsoft Baseline Security Analyzer


| - (NSDictionary *) getLinkAtLocation: |
|
(CGPoint) |
location |
|
Returns a dictionary of data about the link that it at the location. Returns nil if there is no link. A link dictionary contains the following keys: "linkType" a TDLinkType that identifies the type of link
@"range" the range of the link within the label text
@"link" the link text. This could be an URL, handle or hashtag depending on the linkType value
- Parameters
-
| location | location of the link |
- Returns
- dictionary of the about the link at the location
| - (BOOL) automaticLinkDetectionEnabled |
|
readwritenonatomicassign |
Automatic detection of links, hashtags and usernames. When this is enabled links are coloured using the views tintColor property.
| - (KILinkDetectionTypes) linkDetectionTypes |
|
readwritenonatomicassign |
The link types that are detected
| - (KILinkTapHandler) linkTapHandler |
|
readwritenonatomiccopy |
Get or set a block that is called when a link is touched
| - (UIColor*) selectedLinkBackgroundColour |
|
readwritenonatomiccopy |
Colour used to hilight selected link background
The documentation for this class was generated from the following files:
- Views/UITableViewCells/KILabel.h
- Views/UITableViewCells/KILabel.m


1. Extended user guide¶
Step-by-step demonstration of basic and more specific py-fmas functionality. Click on any image to see the full demo including source code.
For further examples that illustrate how to work with the fmas package, see our Usage examples page.
1.1. Basic examples¶
The step-by-step demonstrations in this gallery show how to perfom basic simulations using the provided software.
1.2. More specific examples¶
The step-by-step demonstrations in this gallery show how the functionality of the provided software can be used to customize the implemented models and to compute spectrograms.
1.3. Photon number conservation¶
The examples provided in this gallery demonstrate the conservation of the photon number for the different models. Having available a proper conservation law is particularly important when the conservation quantity error method (CQE) is used for guiding step size adaption.
1.4. Attenuation¶
The examples provided in this gallery demonstrate how to use models that incorporate loss in terms of an absorption constant or a frequency dependent absorption profile.
1.5. Performance tests¶
The step-by-step demonstrations in this gallery illustrate performance tests for the various implemented solver types. All test cases are implemented on basis of the standard nonlinear Schrödinger equation.
1.6. Propagation errors¶
The step-by-step demonstrations in this gallery demonstrate propagation errors that can occur when the computational domain does not properly support the intendet propagation scenario. We include these to assist users to identify possible error sources, and to raise awareness to ensure that the propagation \(z\)-increment is small enough, the computational domain is large enough, and to bear in mind the periodic boundary conditions along the time-axis. All test cases are implemented on basis of the standard nonlinear Schrödinger equation.


Simple example¶
This example is meant to showcase the basic steps needed to fit the concentration evolution over time of different species. These steps are the following:
create a kinetic model that can be used by the chemical_kinetics module
loading and plotting the data
fitting and displaying the fit results
Kinetic model¶
We consider in this example the following reactions:
Forward reaction 1: A \(\rightarrow\) B with time constant \(\rm k_{1, fw}\)
Backward reaction 1: B \(\rightarrow\) A with time constant \(\rm k_{1, bw}\)
Forward reaction 2: B \(\rightarrow\) C with time constant \(\rm k_{2}\)
Which gives the following differential equations according to the law of mass action:
This system of differential equations will be computed at a given time t using the following function:
def derivatives(y, t, p):
"""Calculates the derivatives of the concentrations at t.
Used scipy.integrate.odeint to numerically solve the differential
equations in a given time range.
Lists ("y" and "dy") used by scipy.integrate.odeint are converted
to dictionaries ("c" and "dc") in order to make the differentials
easier to write and read for humans.
Parameters:
y (list): concentration values at t
t (float): time value where the derivatives are calculated
p (dict): dictionary containing the parameters used to
calculate the derivatives e.g. time constants
"""
# list ("y") to dict ("c") conversion
c = {"A" : y[0], "B" : y[1], "C" : y[2]}
# calculate the differentials
dc = dict()
dc["A"] = p["k_1bw"]*c["B"] - p["k_1fw"]*c["A"]
dc["B"] = p["k_1fw"]*c["A"] - p["k_1bw"]*c["B"] - p["k_2"]*c["B"]
dc["C"] = p["k_2"]*c["B"]
# dict ("dc") to list ("dy") conversion
dy = [dc["A"], dc["B"], dc["C"]]
return dy
Caution: when defining the derivatives() function, do not use keys
for the p parameters dictionary containing the string c0_ (if
you do an error will be raised). These keys are reserved for the initial
concentrations and will be defined and used in the
fit.fit_dataset()
function.
Loading and plotting the dataset¶
The dataset “data/concentrations vs time.csv” is loaded in an object of
class data.Dataset
. This object stores the raw data and the
fit results and makes these parameters easy to access.
Yon can consult the recomendations for the .csv files formatting in the
data.Dataset.load_c()
method documentation. The file loaded in
this example can be found here.
from chemical_kinetics import data
ds = data.Dataset(
files_c = ["data/concentrations vs time.csv"],
t_label = "Time [a.u.]",
c_label = "Concentration [a.u.]"
)
You can check if the data was loaded properly by plotting it using the
plot.plot_c()
function:
from chemical_kinetics import plot
plot.plot_c(ds)
Fitting and displaying the fit results¶
We already defined the derivatives to be used by the fit in the derivatives function above. However, we also need to provide an initial guess for the time constants.
Note: In this case, only time constants constitute parameters stored in the p parameter of the derivatives() function. However, a different derivatives() function definition can require parameters that are not time constants. These parameters can still be passed in the p dictionnary, the parameters in p are not required to be time constant, they can be any parameter needed by the model.
These parameters are given as a dictionary (p in the derivatives() function definition) where the keys are the time constant names. The corresponding values are a dictionary containing the parameters, used to initialize a lmfit.Parameter object. The parameters that can be passed via this dictionary are in particular: value, vary, min, max and expr. Details on these parameters, and more generally on the lmfit.Parameter class can be found in the lmfit documentation.
parameters = {
"k_1fw": dict(value = 0.1, min = 0),
"k_1bw": dict(value = 0.1, min = 0),
"k_2": dict(value = 0.1, min = 0)
}
Another parameter to be passed to the fit function are the initial concentrations. These are defined in a similar way as the parameters variable defined above, since they are also fit parameters. It is mandatory to give the same names for theses parameters as the corresponding names given to the columns in the .csv file that was loaded in your dataset object. If you do not declare a value for the initial concentration for one of the species tracked in your .csv file then this value will be the first concentration value from this file by default.
For demonstration, in this example we consider that: - the initial concentration of A is at least 0.5 and we default its initial value - the initial concentration of B is known and fixed to 0 - the initial concentration of C is unknown and we use a default value for this parameter by not declaring it at all. The default value is the initial concentration for C in the dataset
c0 = {
"A": dict(min = 0.5),
"B": dict(value = 0., vary = False)
}
We can now pass these parameters to the fit.fit_dataset()
function. Once the fit converged a message generated by the
lmfit.MinimizerResult class is displayed (see the lmfit
documentation for
details on this message significance).
from chemical_kinetics import fit
fit.fit_dataset(
dataset = ds,
derivatives = derivatives,
parameters = parameters,
c0 = c0
)
Fit succeeded.
The fit results can be printed and plotted using respectively the
fit.print_result()
and plot.plot_c()
functions:
fit.print_result(ds)
| name | value | stderr | stderr/value % | init. val. | vary | min | max | |
|---|---|---|---|---|---|---|---|---|
| 0 | k_1fw | 0.103 | 0.002 | 1.95 | 0.1 | True | 0 | inf |
| 1 | k_1bw | 0.0211 | 0.000645 | 3.06 | 0.1 | True | 0 | inf |
| 2 | k_2 | 0.0197 | 0.000209 | 1.06 | 0.1 | True | 0 | inf |
| 3 | c0_A | 0.989 | 0.00758 | 0.767 | 0.965 | True | 0.5 | inf |
| 4 | c0_B | 0 | 0 | nan | 0 | False | -inf | inf |
| 5 | c0_C | 0.204 | 0.0045 | 2.2 | 0.202 | True | -inf | inf |
from chemical_kinetics import plot
plot.plot_c(ds)
For information, here is the code that was used to generate the raw data used in this example:
from chemical_kinetics import fit
import pandas as pd
import numpy as np
import lmfit
# Time constantsand initial concentrations definitions
params = lmfit.Parameters()
params.add("k_1fw", value = 0.1)
params.add("k_1bw", value = 0.02)
params.add("k_2", value = 0.02)
params.add("c0_A", value = 1)
params.add("c0_B", value = 0)
params.add("c0_C", value = 0.2)
# Generate time and concentration evolution over time
t = np.linspace(0,100,50)
c = fit.evaluate(derivatives, params, t)
# Add random noise
c += c*0.2*(np.random.random(c.shape) - 0.5)
# Create a DataFrame from t and c and save it as .csv
data = np.hstack((t.reshape(-1,1), c))
df = pd.DataFrame(columns = ["t", "A", "B", "C"], data = data)
df.to_csv(r"data/concentrations vs time.csv", index = False)


The stemming algorithm
Letters in Spanish include the following accented forms,
-
á é í ó ú ü ñ
The following letters are vowels:
-
a e i o u á é í ó ú ü
R2 is defined in the usual way —
see the note on R1 and R2.
RV is defined as follows (and this is not the same as the
French stemmer
definition):
If the second letter is a consonant, RV is the region after the next
following vowel, or if the first two letters are vowels, RV is the region
after the next consonant, and otherwise (consonant-vowel case) RV is the
region after the third letter. But RV is the end of the word if these
positions cannot be found.

Step 0: Attached pronoun
-
Search for the longest among the following suffixes
-
me se sela selo selas selos la le lo las les los nos
and delete it, if comes after one of
-
(a) iéndo ándo ár ér ír
(b) ando iendo ar er ir
(c) yendo following u
in RV. In the case of (c), yendo must lie in RV, but the preceding
u can be outside it.
In the case of (a), deletion is followed by removing the acute accent
(for example, haciéndola -> haciendo).
Step 1: Standard suffix removal
-
Search for the longest among the following suffixes, and perform the
action indicated.
- anza anzas ico ica icos icas ismo ismos able ables ible ibles ista
istas oso osa osos osas amiento amientos imiento
imientos
- delete if in R2
- adora ador ación adoras adores aciones ante antes ancia ancias
- delete if in R2
- if preceded by ic, delete if in R2
- logía logías
- replace with log if in R2
- ución uciones
- replace with u if in R2
- encia encias
- replace with ente if in R2
- amente
- delete if in R1
- if preceded by iv, delete if in R2 (and if further preceded by at,
delete if in R2), otherwise,
- if preceded by os, ic or ad, delete if in R2
- mente
- delete if in R2
- if preceded by ante, able or ible, delete if in R2
- idad idades
- delete if in R2
- if preceded by abil, ic or iv, delete if in R2
- iva ivo ivas ivos
- delete if in R2
- if preceded by at, delete if in R2
Do step 2a if no ending was removed by step 1.
Step 2a: Verb suffixes beginning y
-
Search for the longest among the following suffixes in RV, and if found,
delete if preceded by u.
-
ya ye yan yen yeron yendo yo yó yas yes yais
yamos
(Note that the preceding u need not be in RV.)
Do Step 2b if step 2a was done, but failed to remove a suffix.
Step 2b: Other verb suffixes
-
Search for the longest among the following suffixes in RV, and perform the
action indicated.
- en es éis emos
- delete, and if preceded by gu delete the u (the gu need not be in
RV)
- arían arías arán arás aríais aría aréis aríamos aremos
ará aré
erían erías erán erás eríais ería eréis eríamos eremos
erá eré
irían irías irán irás iríais iría iréis iríamos iremos
irá iré
aba ada ida ía ara iera ad ed id ase iese aste iste an aban ían
aran ieran asen iesen aron ieron ado ido ando iendo ió ar er ir as
abas adas idas ías aras ieras ases ieses ís áis abais íais
arais ierais aseis ieseis asteis isteis ados idos amos ábamos
íamos imos áramos iéramos iésemos ásemos
- delete
Always do step 3.
Step 3: residual suffix
-
Search for the longest among the following suffixes in RV, and perform the
action indicated.
- os a o á í ó
- delete if in RV
- e é
- delete if in RV, and if preceded by gu with the u in RV delete the u
And finally:
-
Remove acute accents
|


Loading...
Failed to fetch alarm definition.
- The Name field is used to identify the alarm definition.
- The Description field can be used to describe the alarm definition's purpose.
- Each alarm definition is defined by an expression.
(e.g. max(pod.health_status) < 0)
- The Severity field allows the importance of the alarm definition to be specified.


workbox-precaching. RevisionedCacheManager
You can instantiate this class to add requests to a precache list and eventually install the assets by calling install() and to remove old entries call cleanup().
Constructor
RevisionedCacheManager
new RevisionedCacheManager(input)
Constructs a new RevisionedCacheManager to handle caching of revisioned assets only.
Parameter |
|
|---|---|
|
input |
Object |
Methods
addToCacheList
addToCacheList(input)
This method will add the supplied entries to the install list and can be called multiple times.
The revisionedFiles
parameter of the input should contain an array of objects or strings.
Objects in this array should have a url
and revision
parameter where the revision is a hash, unique to the files contents, which changes whenever the file is updated. (See our getting started guide to learn
how to automate this).
Strings should be URL's that contain revisioning information i.e. /styles/main.abcd.css
instead of /styles/main.css
. If you supply a URL which isn't revisioned, the install()
step will never update the precached asset.
Parameter |
|
|---|---|
|
input |
Object |
Example
revisionedManager.addToCacheList({
revisionedFiles: [
'/styles/hello.1234.css',
{
url: '/images/logo.png',
revision: 'abcd1234'
}
]
});
cleanup
cleanup() returns Promise
This method will compare the currently cached requests's and determine which requests are no longer in the cache list and can be removed from the cache.
This should be called in a service worker's activate event to avoid removing requests that are still be used by currently open pages.
- Returns
-
Promise
Promise that resolves once the cache entries have been cleaned.
getCachedUrls
getCachedUrls() returns Array of String
Returns an array of fully qualified URL's that will be cached by this cache manager.
- Inherited from
- module:workbox-precaching.BaseCacheManager#getCachedUrls
- Returns
-
An array of URLs that will be cached.
getCacheName
getCacheName() returns String
Gives access to the cache name used by this caching manager.
- Inherited from
- module:workbox-precaching.BaseCacheManager#getCacheName
- Returns
-
The cache name used by this manager.
install
install() returns Promise containing Array of Object
This method will go through each asset added to the cache list and fetch and update the cache for assets which have a new revision hash.
- Returns
-
Promise containing Array of Object
The promise resolves when all the desired assets are cached and up -to-date.


Module starting date:
These dates only apply to 10-credit modules. The 40-credit modules have different arrangements.
Submission dates for assessed work should normally be 10:00 am on a Monday morning, unless holidays intervene.
Submission dates are five weeks after a module has finished for full-time students and eight weeks for flexible. Extra weeks are added for Christmas and Easter vacations.
Feedback dates are 15 working days after submission.
| Submission | Feedback | ||
|---|---|---|---|
| Full time | |||
| Part time |
Please note that these dates are defaults for guidance only. For operational reasons, the actual dates may for submission and feedback may differ. Students are advised to check assignment briefs for actual submission and feedback dates.


Let's work on your App
We will now try to connect to your app at: {{ path }}
You will see the current diagnostics below, as well as a few options
Continue
Create flow
Connect to MySql db
Diagnostics


The power set of a set X is the set of all sets contained in X.
It is denoted P(X), so formally P(X) = Y : Y ⊆ X .


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{% extends 'contents/_base/events.html' %} {% load static %} {% block title %}Keynotes{% endblock %} {% block content %} {# Kyenote speakers ordered by their first name #} {# 'Amber Brown', 'Audrey Tang', 'Jim Huang', 'Paul Hildebrandt', 'Steve Dower' #} {# begin .conf #}
Audrey showed an early interest in computers, beginning to learn Perl programming at age 12. Two years later, she dropped out of high school, unable to adapt to student life. By the year 2000, at the age of 19, Audrey had already held positions in software companies, and worked in California's Silicon Valley as an entrepreneur.
Audrey is best known for initiating and leading the Pugs project, a joint effort from the Haskell and Perl communities to implement the Perl 6 language; she has also made contributions to internationalization and localization efforts for several Free Software programs, including SVK, Request Tracker (for which she also wrote a large portion of the code) and Slash, as well as heading Traditional Chinese translation efforts for various open source-related books.
On CPAN, Audrey initiated over 100 Perl projects between June 2001 and July 2006, including the popular Perl Archive Toolkit (PAR), a cross-platform packaging and deployment tool for Perl 5. She is also responsible for setting up smoke test and digital signature systems for CPAN. In October 2005, she was a speaker at O'Reilly Media's European Open Source Convention in Amsterdam.
Now she has retired and continuously engaged in developing a variety of tools and platforms to participate open government g0v events.
Jim Huang, the nickname is “jserv” on the website. As a little child, he had connected computer systems and a variety of programming languages. In 1997, he tried to develop the operating system, and hence touched Linux. After that, he has acted on Open Source. In 1999, he cooperated in web company; as the end of it, he decided that dropped out of university and go to service in the army.
When the time in the army, he continues enriched himself. Until he was working, he was still research and implement. Especially, he has enforced in integrating software and hardware. Besides, to assist Taiwan’s enterprises in connection with Open Systems and dynamic Groups.
In 2009, jserv built in 0xLab with friends from Groups; 0xLAb was applied project of software and hardware integration. In 2014, jserv built SSX with friends and be Chief Technology Officer; SSX is a venture capital company and concern in intelligent hardware, health, healthcare, IOT, etc. And SSX has still helped lots of star-up company in Southern Taiwan.
In addition, jserve is Consultant of MediaTek, ICL of ITRI, DELTA. Moreover, from 2012, jserv was invited by NCKU to be a lecturer.
Paul Hildebrandt has been a Senior Engineer with Walt Disney Animation Studios (WDAS) since 1996, and has worked in both Systems and Software engineering. His current title is Senior Software Engineer and Product Owner for the Playback tools among his primary duties is spending time working with the artists, understanding their needs, and designing tools to assist them. If he is lucky, he gets to write code.
Hildebrandt leads a team that is responsible for developing the digital asset manager, media player, dailies review system with a mobile interface, and other related tools. These tools are available on a variety of platforms including Linux, Mac, iOS, and Android. Among the Disney animated films that he has contributed are Zootopia, the Oscar® winning hits "Big Hero 6", "Frozen" and Oscar®-nominated box office hits, "Wreck-It Ralph," "Tangled," "Bolt," "Treasure Planet," and "Dinosaur." He is WDAS' evangelist for PyCon and other Python sponsorships.
Prior to joining Disney, Hildebrandt spent eight years with Hughes Aircraft as a Senior Engineer working on commercial in-flight entertainment for airlines and the Stealth Bomber trainers. He also served as the electrical lead for a team that raced a solar car across Australia in the 1990 World Solar Challenge. The team finished in the top third.
Hildebrandt was born and raised in Anaheim, California. He received his BSEE with a focus on Computing from California Polytechnic University Pomona. He resides outside of Los Angeles with his wife and three boys.
Steve is an engineer who tells people about Python and then gives them excuses to use it and great tools to use it with. He works on Python Tools for Visual Studio, contributes to many of Microsoft’s Python libraries, and is a core contributor and Windows expert for CPython.
He now works as a software engineer at Microsoft.


BOTL is a research project to test the hypothesis that using a technological solution to reduce the cost of getting informed about urban planning will result in better engagement in planning consultation.
This webpage is designed to make it easier to find out about what planning application have been submitted in your local area, and to facilitate better engagement.
If you want to use your device location to find local applications, please select the "Use my location" button bellow, otherwise the map will be centred on Nottingham castle.
You can load more applications by dragging the map to the desired location then long tap or right click where to load applications.
Comments can be added to the applications, these will be shown to other users. You can optionally enter your email in order to receive updates when other users comment on that application.
TL;DR - caveat usor
While care has been taken to ensure software correctness and user privacy is protected, the project has been developed as a research tool and should be treated as such.
The botl project is not an official forum for planning consultation; no comments will used in LPA consultation.
Any questions, issues, or requests to remove your comments should be directed to psysme@nottingham.ac.uk


freezeframe.js
basic,animate on hover.
start & stop on click
start & stop manually.
with overlay icon.
using child elements
destroy, remove event listeners.
cinemagraphs by cinemagraphs.com


Google Drive¶
Google Drive is a file storing platform where an user can store all his/her files in the google drive. Here files can be of any form ranging from documents to audio, video or image files. In free account each user will be given around 15 GB of free data space to be stored. We can create folders and subfolders in the Google Drive to store our data.
Each file will be stored in Google cloud with a unique URL and it’s up to the user to make the file sharable or not. Google Drive is reliable and if an user has different devices and if he/she wants to access those files then Google Drive is needed in this case as he can have access to his file as all his files are stored in the cloud. The user does not need to install any kind of software in order to view these files.

Create a project¶
To create a project, go to Dashboard in Google APIs console. In the Select a Project window, click NEW PROJECT.
Enter a project name we want to use. Click CREATE.
Enable APIs and Services¶
In the APIs & Services Dashboard for the project we created, click ENABLE APIS AND SERVICES.
This leads to the Welcome to the API Library page.
Search for “google drive api”.
Click ENABLE.
Create Credentials¶
At the Google Drive API Overview page, click CREATE CREDENTIALS.
Select the credentials you need. Click What credentials do I need?.

Select External user type. Click CREATE.
Enter application name. Enter the gmail account we use for the project.
Select scopes to See, edit, create, and delete all of your Google Drive files, and See and download all your Google Drive files. Click ADD.
Click Save.
At the APIs & Services Credentials page, click CREATE CREDENTIALS, select OAUTH client ID.
Select Other for application type. A default name “Other client 1” will be generated which we can keep.
This leads to OAuth client created screen. Click OK.
Click the download button to download the credential file.
The default name of the file is something like “client_secret_xxxxxxxxxxxxxxxxxxxxxxxxxxpg2.apps.googleusercontent.com.json”. Rename it to “credentials.json”, and place it in the directory specified in cloudmesh.yaml for key “credentials_json_path”.
Authorization Flow¶
In order to create the authorization flow, we also need to modify cloudmesh.yaml to store the paths of the files needed for authentication, including path for credentials.json and path for token.pickle, which we will create next.
parallelgdrive:
cm:
active: false
heading: GDrive
host: dgrive.google.com
label: parallelgdrive
kind: parallelgdrive
version: TBD
service: storage
default:
directory: TBD
credentials:
credentials_json_path: [put the path of credentials.json here]
token_path: [put the path of token.pickle here]
Now we are ready to create the authorization flow. The codes for creating credentials for authorization is included in the Provider.py file. Here is the link:
When we run the Provider.py for the first time, do so in the Terminal.
We will be redirected to the Sign in page. Choose the Google account to continue to the project.
Click Advanced.
Click Go to [your project name].
In the Grant permission page, click Allow.
Click Allow again to confirm.
Message will be displayed that the authentication flow has been completed.
When the authentication flow completes, it will create a token.pickle
file in our working directory on our computer.
We need to place this file in the token_path specified in the cloudmesh.yaml file.
This file can be used for future purposes so we do not need to login everytime. If we delete this file for any reason,
e.g. changing the permission scope, then the authorization process will again ask for login id and password, and again create
token.pickle
automatically.


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311 is a special telephone number supported in many communities in Canada and the United States. The number provides access to non-emergency municipal services. People can call in many cities to find information about services, make complaints, or report problems like graffiti or road damage. The number 311 is intended in part to divert routine inquiries and non-urgent community concerns from the 911 number which is reserved for emergency service. 311 has evolved with technological advances into a multi-channel service that connects citizen with government, while also providing a wealth of data that improves how cities are run.
For us, the 311 dataset provides us an opportunity to gain some insight on how lifes are in New York City from another angle. From the data, we can see what the New Yorkers’ complain about the most, from which area at what time. By analysising the data, a list of top complaints was derived given as below.
- Heating/Hot water
- Noise – Residential
- Street Light Condition
- Street Condition
- Blocked Driveway
- Water System
- Illegal Parking
In order to show the distribution in terms of time and locations, we design several visualizations that support different tasks. These visualizations are divided into two main sections, one is complaint-type-driven, the other one is event-driven. However, it is good to use them in conjunction to see more details.
Here we also provide some background information about the city New York.
New York City is often referred to collectively as the five boroughs - Brooklyn, Queens, Manhattan, The Bronx, and Staten Island.
If the boroughs were each independent cities, four of the boroughs (Brooklyn, Queens, Manhattan, and the Bronx) would be among the ten most populous cities in the United States (Staten island would be ranked 37th) ; these same boroughs are coterminous with the four most densely populated counties in the United States (New York [Manhattan], Kings [Brooklyn], Bronx, and Queens).
The bar chart below shows the ranking of population, borough size (land area), density and median household income for the five boroughs of NYC. We think it is helpful to provide such information to put the analysis results into context, as our visualisation counts on absolute numbers.
(Complaint numbers info from dataset, populations info from Wikipedia , income info from US Census Bureau )


After months of instability, I again have a fully working pipeline and a live web page for Sproingk, my demo project combining the latest public betas in:
If you're interested in any combination of these, please take a gander.
Kotlin (It's not just for Android!) is really where JVM programming is headed. And it's fun.
Springfox gives you a lovely UI for your REST API. (In the demo, try the "greeting controller".)
Boxfuse make minimal shrink-wrapped Linux images of your software, and handles blue/green AWS deployments.


{% extends "layout.html" %} {% block page_title %} Where you live {% endblock %} {% block content %} {% include "../includes/phase_banner_beta.html" %} Back Where you live What are your current living arrangements? {% include "../includes/help.html" %} {% endblock %}


Undefined Control Defines
Defined Control Defines
Defines
`DELIM
= "\n"
`END_ITEM
= "end_of_test"
`HOSTNAME
= "<IP_ADDRESS>"
`PORT
= 54000
`TIMEOUT
= 1


--- title: Deep Learning for Big Code ref: bigcode18-ss description: Graduate seminar on new methods and systems for learning from programs. semester: Spring 2018 number: 263-2926-00L lecturer: Prof. Dr. Martin Vechev ta: Dr. Veselin Raychev assistants: edoz: http://www.vvz.ethz.ch/Vorlesungsverzeichnis/lerneinheit.view?lerneinheitId=122999&semkez=2018S session-time-place: Mon 16-18, CHN D48 lecture-time-place: exercise-time-place: credits: 2 image: assets/images/orator.jpg ---
The objective of the seminar is to:
The seminar is carried out as a set of presentations (2 each lecture) chosen from a set of available papers (available below). The grade is determined as a function of the presentation, handling questions and answers, and participation:
| Date | Title | Presenter | Slides | Advisor |
|---|---|---|---|---|
| Introduction to the seminar (topics, objectives, structure): | Martin Vechev | |||
| March 12 | DeepCoder: Learning to Write Programs | Patrick Schmidt | Veselin Raychev | |
| A Bimodal Modelling of Source Code and Natural Language | Sandro Marcon | Pesho Ivanov | ||
| March 19 | Detecting object usage anomalies | Flavia Cavallaro | Benjamin Bichsel | |
| sk_p: a neural program corrector for MOOCs | Andrea Rinaldi | Pavol Bielik | ||
| March 26 | Probabilistic Model for Code with Decision Trees | Robin Vaaler | Timon Gehr | |
| April 9 | Code Completion with Neural Attention and Pointer Networks | Ondrej Skopek | Pavol Bielik | |
| Learning to Represent Programs with Graphs | Mislav Balunović | Benjamin Bichsel | ||
| April 23 | Melford: Using Neural Networks to Find Spreadsheet Errors | Hlynur Freyr | Pesho Ivanov | |
| A Convolutional Attention Network for Extreme Summarization of Source Code | Jovan Andonov | Veselin Raychev |


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User List
{{user}}
User List with logic
{{user}} : {{i}} : {{f}} : {{l}} : {{o}} : {{e}}
User List with logic
let i=index : number
let f=first : value = true only first element
let l=last : value = true only last element
let o=odd : value switch between true and false. start with false
let e=even : value switch between true and false. start with true
Dog List
No : {{dog.no}} Name : {{dog.name}} Owner : {{dog.owner}}


<s> <w> w1-1 w1-2 w1-3 <w> w2-1 <w> w3-1 w3-2 <w> </s>where wA-B is the Bth part of the A:th word.
counts2kn [OPTIONS] text_in lm_out
text_in should contain the training set (except for the held-out part for discount optimization) and the results are written to lm_out.
Mandatory options:
| -n | --norder | The desired n-gram model order. |
Other options:
| -h | --help | Print help |
| -o | --opti | The file containing the held-out part of training set. This will be used for training the discounts. Suitable size for held out set is around 100 000 words/tokens. If not set, use leave-one-out discount estimates. |
| -a | --arpa | Output arpa instead of binary. Recommended for compatibility with other tools. This is the only output compatible with SRILM toolkit. |
| -x | --narpa | Output nonstandard interpolated arpa instead of binary. Saves a little memory during model creation but the resulting models should be converted to standard back-off form. |
| -p | --prunetreshold | Pruning treshold for removing the least useful n-grams from the model. 0.0 for no pruning, 1.0 for lots of pruning. Corresponds to epsilon in [1]. |
| -f | --nfirst | Number of the most common words to be included in the language model vocabulary |
| -d | --ndrop | Drop the words seen less than x times from the language model vocabulary. |
| -s | --smallvocab | The vocabulary does not exceed 65000 words. Saves a lot of memory. |
| -A | --absolute | Use absolute discounting instead of Kneser-Ney smoothing. |
| -C | --clear_history | Clear language model history at the sentence boundaries. Recommended. |
| -3 | --3nzer | Use modified KN smoothing, that is 3 discount parameters per model order. Recommended. Increases the memory consumption somewhat, should be omitted if memory is tight. |
| -O | --cutoffs | Use count cutoffs, --cutoffs "val1 val2 ... valN". Remove n-grams seen less or equal than val times. Val is specified for each order of the model, if the cutoffs are only specified for a few first orders, the last cutoff value is used for all higher order n-grams. All unigrams are included in any case, so if several cutoff values are given, val1 has no real effect. |
| -L | --longint | Store the counts in "long int" type of variable instead of "int". This is necessary when the number of tokens in the training set exceeds the number that can be stored in a regular integer. Increases memory consumption somewhat. |
varigram_kn [OPTIONS] textin LM_out
text_in should contain the training set (except for the held-out part for discount optimization) and the results are written to lm_out. Suitable size for held out set is around 100 000 words/tokens.
Mandatory options:
| -D | --dscale | The treshold for accepting new n-grams to the model. 0.05 for generating a fairly small model, 0.001 for a large model. Corresponds to delta in [1]. |
Other options:
| -h | --help | Print help |
| -o | --opti | The file containing the held-out part of training set. This will be used for training the discounts. Suitable size for held out set is around 100 000 words/tokens. If not specified, use leave-one-out estimates for discounts. |
| -n | --norder | Maximum n-gram order that will be searched. |
| -a | --arpa | Output arpa instead of binary. Recommended for compatibility with other tools. This is the only output compatible with SRILM toolkit. |
| -x | --narpa | Output nonstandard interpolated arpa instead of binary. Saves a little memory during model creation but the resulting models should be converted to standard back-off form. |
| -E | --dscale2 | Pruning treshold for removing the least useful n-grams from the model. 1.0 for lots of pruning, 0 for no pruning. Corresponds to epsilon in [1]. |
| -f | --nfirst | Number of the most common words to be included in the language model vocabulary |
| -d | --ndrop | Drop the words seen less than x times from the language model vocabulary. |
| -s | --smallvocab | The vocabulary does not exceed 65000 words. Saves a lot of memory. |
| -A | --absolute | Use absolute discounting instead of Kneser-Ney smoothing. |
| -C | --clear_history | Clear language model history at the sentence boundaries. Recommended. |
| -3 | --3nzer | Use modified KN smoothing, that is 3 discount parameters per model order. Recommended. Increases the memory consumption somewhat, should be omitted if memory is tight. |
| -S | --smallmem | Do not load the training data into memory. Instead read it from the disk each time it is needed. Saves some memory, slows training down somewhat. |
| -O | --cutoffs | Use count cutoffs, --cutoffs "val1 val2 ... valN". Remove n-grams seen less or equal than val times. Val is specified for each order of the model, if the cutoffs are only specified for a few first orders, the last cutoff value is used for all higher order n-grams. All unigrams are included in any case, so if several cutoff values are given, val1 has no real effect. |
| -L | --longint | Store the counts in "long int" type of variable instead of "int". This is necessary when the number of tokens in the training set exceeds the number that can be stored in a regular integer. Increases memory consumption somewhat. |
perplexity [OPTIONS] text_in results_out
text_in should contain the test set and the results are printed to results_out.
Mandatory options:
| -a | --arpa | The input language model is in either standard arpa format or interpolated arpa. |
| -A | --bin | The input language model is in binary format. Either "-a" or "-A" must be specified. |
Other options:
| -h | --help | Print help |
| -C | --ccs | File containing the list of context cues that should be ignored during perplexity computation. |
| -W | --wb | File containing word break symbols. The language model is assumed to be a sub-word n-gram model and word breaks are explicitly marked. |
| -X | --mb | File containing morph break prefixes or postfixes. The language model is assumed to be a sub-word n-gram model and morphs that are not preceeded (or followed) by a word break are marked with a prefix (or postfix) string. Prefix strings start with "^" (e.g. "^#" tells that a token starting with "#" is not preceeded by a word break) and postfix strings end with "$" (e.g. "+$" tells that a token ending with "+" is not followed by a word break). The file should also include sentence start and end tags (e.g. "^<s>" and "^</s>"), otherwise they are considered as words. |
| -u | --unk | The string is used as the unknown word symbols. For compability reasons only. |
| -U | --unkwarn | Warn if unknown tokens are seen |
| -i | --interpolate | Interpolate with given arpa LM. |
| -I | --inter_coeff | Interpolation coefficient. The interpolated model will be weighted by coeff whereas the main model will be weighted by 1.0-coeff. |
| -t | --init_hist | The number of symbols assumed to be known from the sentence start. Normally 1, for sub-word n-grams the inital word break should be assumed known and this should be set to 2. Default 0 (fix this). |
| -S | --probstream | The filename, where the individual probabilities given to each word should be put. |
simpleinterpolate2arpa "lm1_in.arpa,weight1;lm2_in.arpa,weight2" arpa_out
To evaluate the just created model:
perplexity -t 1 -a model.arpa.bz2 test_set.txt -
or
perplexity -S stream_out.txt.gz -t 1 -a model.arpa.bz2 "| cat test_set.txt | preprocess.pl" out.txt
Note, that for evaluating a language model based on subword units, the
parameter -t 2 should be used since the two first tokens (sentence
start and word break) are assumed to be known.
To create a grown model do:
varigram_kn -a -o held_out.txt -D 0.1 -E 0.25 -s -C train.txt grown.arpa.gz


{{> partials/header data.modal-local}}
Detach a part of the content of the page to a modal box.
The default one from Twitter Bootstrap
Detach the current sentence to the modal box
There is two ways to proceed: using the data attributes or the JavaScript way.
Based on the default Twitter Bootstrap code of the modal component, the only change you need to do is to add on the controller element an attribute data-local="#myContent"
to target the element.
<button type="button" class="btn" data-toggle="modal" data-target="#myModal" data-local="#myContent">Demo</button>
Based on the default Twitter Bootstrap code of the modal component, the only change you need to do is to add on the controller element an attribute data-local="#myContent"
to target the element.
$('#myModal').modal({
local: '#myContent'
...
});

This is another content.

<button type="button" class="close" data-dismiss="modal" aria-hidden="true">×</button>

Modal title

One fine body…

<button type="button" class="btn btn-default" data-dismiss="modal">Close</button>
<button type="button" class="btn btn-primary">Save changes</button>

Some events are trigerred before and after the content has been detached/replaced.
| Event Type | Description |
|---|---|
| detach.bs.local | This event fires immediately when the content is going to be detached. |
| detached.bs.local | This event is fired when the detached content has been made placed in the modal. |
| replace.bs.local | This event is fired immediately when the modal is going to hide. |
| replaced.bs.local | This event is fired when the detached content has been made replaced at its origin place. |


Anushka Singh
Frontend Development Intern @Fit n Club • Currently learning React.js
• Passionate Web Developer 🚀


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Run the following SQL command:
alter session set container=plum;
The expected output is:
Session altered.


Brewster County Section Deck, Two Lines or Less
Above: Caption info for photo above, can use italics as needed
It’s 1:30 am on a Saturday. Emily Little is standing inside a blue aluminum-sided trailer on a Far West Texas ranch.  About 60 high school students are packed inside with her; some are pounding whiskey shots in the kitchen, others are dancing to TLC’s “Creep” in the living room. Graduation is a month away and the “senior sunrise” party is roaring. One of Little’s girlfriends is making out with a boy in a truck, hoping to make another boy jealous. In the scrub brush expanse between the two closest towns of Alpine, population 6,000, and Marathon, population 550, the high schoolers think they’re cleverly hidden away deep in the desert.
Under a pitch-black sky about 200 yards away in the Chihuahua desert idles the Terrahawk, a high-tech surveillance van that looks like it rolled off the set of Men in Black. A bizarre scissor-lift tower protrudes from the roof of the van, 25 feet into the air for birds-eye views. Inside is an infrared thermal imaging camera used for night vision and a high-powered laser for tracking multiple moving targets simultaneously. A local sheriff’s deputy has been sitting in the van for roughly three hours, quietly watching the kids and awaiting orders to bust the party.
Ronny Dodson, 52, the Brewster County sheriff and the man who is overseeing the surveillance of the party that night, says he fell in love with the Terrahawk when he first saw it in 2009 at a Sheriff’s conference in Corpus Christi. But the $300,000 sticker price was unaffordable — until he heard about a federal immigration-related grant called “Operation Stonegarden” meant to help local authorities “secure the border.” Dodson won one of the grants that same year and used it to buy his Terrahawk.
Dodson delights in recounting the Terrahawk’s first days, like when they suddenly turned its floodlights onto a curious, but unsuspecting college girl loitering outside a local university football game “Wahoo. God dang she takes off running,” or when deputies caught three guys smoking pot behind the Pizza Hut and to dazzle them later told the culprits that the vehicle spied on them from a half a mile away. “Of course they told everyone in town!”
The one big problem with the Terrahawk, is that its raison d’etre was to help stop dangerous border security threats — but as Dodson is the first to point out, there isn’t much of that to be done in these parts.
Image caption and credit for Terrahawk image goes here.
Dodson oversees a territory that spans more miles of border with Mexico than any other county in the country; it’s the largest county anchoring the vast region in Far West Texas known as “Big Bend” because of the 90-degree turn in the Rio Grande. Big Bend’s lonesome terrain has long attracted writers searching for extreme settings and thick characters, including most recently Cormac McCarthy who set his most of his book “No Country for Old Men,” where a local sheriff follows a Mexican hit man (played by Javier Bardem in the movie version) who crosses the border into a sepia-tinged desert wasteland and slaughters people with chilling efficiency as he tracks stolen drug money.
The reality is almost exactly the opposite. Brewster County has seen three homicides since 2000. All have been committed by locals. Border apprehensions in Big Bend remain the lowest of all southwestern Border Patrol sectors.
Big Bend’s salvation has been its isolation, which, mirrored by an even greater emptiness on the Mexican side, has been it its one consistent narrative in both fiction and reality. The bilateral solitude has made it a haven for astronomers finding the darkest skies in the lower 48; a healing grounds for stressed-out or chronically ill looking to dissolve themselves along the Rio’s natural hot springs, and one of the last fenceless frontiers for coyotes, roadrunners, and humans crisscrossing the Chihuahua countryside.
But over the past decade, the free-roaming enclave where people go to “get away from it all” has been slip-sliding into an occupied territory, a byproduct of the three decade-long build up of immigration enforcement.
Back in the trailer house, Little is focused on her Ping-Pong aim, when suddenly a flash and a glimpse of red, white and blue lights catches her eye. “Cops!” she screams, dropping her ball. Teenagers flee every which way, tripping over each other as they climb out of the trailer house windows and as they squeeze through its narrow front door.
Large busts of relatively minor crimes are spreading paranoia. Earlier last year, a bevy of local and federal HSI officers spent six months staking out a former Sul Ross University football player Graylen Daniel, 23, and his brother Quincey Boney, 26, who were suspected of dealing marijuana. After several undercover surveillance operations (including sniffing outside doors after they left buildings) and a 6am bust with machine guns, Boney ended up with a misdemeanor charge of personal possession of less than two ounces of marijuana.
Sheriff Dodson talks of similar raids that were “jokes” such as one recent bust that featured dozens of federal and local officers and a helicopter raid on one unarmed teenager at his home for viewing child pornography. Dodson says it would have taken two maybe three of his officers to arrest him.
“I think they’re just throwing money at the border for nothing,” Dodson told the Texas Observer, a monthly magazine, earlier this year. As an elected official in Far West Texas, Dodson has never and would never be a public fan of Big Brother. But he’s amped up he’s rhetoric recently and has become one of the most outspoken critics of the default immigration strategy of the United States to secure the border.
The Terrahawk greets them with floodlights. The faster kids get further away but the deputy inside the van pinpoints laser red dot on their backs, and radios in coordinates to other officers who scoop them up, one by one.
“Sheriff’s Office!” the deputies yell. “Get on the ground!” Pistols drawn, the officers go inside the trailer house and push the teens down onto the beer-soaked floor. One officer quickly scoops up a girl running in stilettos along a gravel road. Another shoots and fires a Taser at Little, but electrified prongs fall short. The place is crawling with nearly a dozen officers in trucks, patrol cars and ATVs.
“We’re high school kids!" shouts one of the students. "Calm down we don’t have assault rifles!”
“I think they’re just throwing money at the border for nothing.”
—Brewster County Sheriff Ronny Dodson
As they capture the teenagers, the deputies sit them on the ground, several with hands cuffed behind their backs, and issue them citations for consumption or possession of alcohol by a minor (twenty one were issued that night). Kelby Sines, a sophomore at the time, later said he understands that underage drinking is illegal. But he added that felt like he had been netted in a major raid, not a busted high school party. “They treated us like illegal immigrants,” he said.
It is an apt description. Even though it’s one of the least built-out border regions, locals say the hunt for illegal activity has transformed their cherished small government way of life. U.S. Border Patrol's force of agents based in the local Big Bend sector grew from less than 200 in 2000 to more than 600 in 2013. The Immigration and Customs Enforcement Agency’s new Homeland Security Investigations unit has placed and undisclosed number of uniformed and undercover “HSI” agents in Big Bend in recent years. Texas Parks and Wildlife Dept. now has 12 game wardens in the area adding to the significant bevy of Texas Department of Public Safety officers patrolling the streets and the skies for border security issues. They’ve built new buildings, orchestrated temporary traffic stops, and undergone several surveillance operations.
The Border Surge The Growth of 'Government Towns'
Above: CBP Officers' weapons and tactical gear look better suited for military tactics than busting teenagers for drinking underage.
Large busts of relatively minor crimes are spreading paranoia. Earlier last year, a bevy of local and federal HSI officers spent six months staking out a former Sul Ross University football player Graylen Daniel, 23, and his brother Quincey Boney, 26, who were suspected of dealing marijuana. After several undercover surveillance operations (including sniffing outside doors after they left buildings) and a 6am bust with machine guns, Boney ended up with a misdemeanor charge of personal possession of less than two ounces of marijuana.
Sheriff Dodson talks of similar raids that were “jokes” such as one recent bust that featured dozens of federal and local officers and a helicopter raid on one unarmed teenager at his home for viewing child pornography. Dodson says it would have taken two maybe three of his officers to arrest him.
“I think they’re just throwing money at the border for nothing,” Dodson told the Texas Observer, a monthly magazine, earlier this year. As an elected official in Far West Texas, Dodson has never and would never be a public fan of Big Brother. But he’s amped up he’s rhetoric recently and has become one of the most outspoken critics of the default immigration strategy of the United States to secure the border.
Brewster Country Sherrif Ronny Dodson, far right.
On this day, like most, Dodson is driving around his county, which is larger than the state of Connecticut, in his white dodge ram truck. Looking every bit the part of a West Texas sheriff, Dodson wears a desert-tan short-sleeved shirt, crisply pressed, topped by an off-white cowboy hat. He rarely leaves home without his brown leather holster carrying a silver-handled 45 automatic pistol. A big man (6’1”, 235 pounds), he speaks with a soothing drawl, the same one that pilots use to make turbulence sound less worrisome.
“We’ve become a government town,” Dodson says about the border build up as he steers his truck away from his office in Alpine looking for places to hide new border security surveillance cameras (bought with federal money). He says he thinks federal plans to double border patrol again and state plans possibly send another 500 state officers to the Texas border are insane.
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The buildup has been occurring for the past three decades since 1980, when the entire Southwestern border had only half as many officers as half what’s in Big Bend today. The United States now spends about $18 billion a year on immigration enforcement. This is more than all primary federal criminal law enforcement agencies combined, including the Drug Enforcement Agency, Federal Bureau of Investigations, and the Bureau of Alcohol and Tobacco, Firearms and Explosives, according to a 2013 study by the Migration Policy Institute, a nonpartisan research group in Washington.
Immigration and Customs Enforcement, or ICE, currently spends $11 billion annually on border security. This money goes not just towards reinforcing the border and targeting undocumented immigrants, but also toward trying to stem the flow of drugs entering the country.
Texas has built its own $450 million dragnet to supplement the federal government’s already robust border security efforts. With these funds, the state has bought five helicopters and a $7.4 million surveillance aircraft. It also purchased six armed patrol boats with 50 caliber machine guns, 326 patrol vehicles, temporary border checkpoints and an estimated 500 remote surveillance cameras and sensors.
Each time there is a spike in border crossers, such as the flood of Cuban refugees who made their way to Florida in jerry-rigged boats in 1980 to the recent surge in unaccompanied child migrants crossing into Texas’ Rio Grande Valley, or every time there’s been a national security lapse such as the Sept. 11 attacks, the natural reaction as been to secure the southwestern border.
“BOOM, we’ve got double the size of border patrol,” says Dodson of the border expansion in Big Bend after the attacks on Sept. 11, 2001. “BOOM, double the number of state officers! BOOM we’ve got double everything down here.”
And since immigration reform efforts began with former President George W. Bush in 2000, border security has become the premise to any possible path to legalization for the estimated 11 million undocumented living in the country. The 2013 Senate-passed $46 billion “Border Surge” bill included another doubling of Border Patrol along with specific increases in Big Bend: 29 mobile surveillance system; 1105 seismic, imaging and infrared ground sensors; and 131 thermal imaging systems and night vision goggles.
Dodson suspects more is coming and he wants to let those in Washington know the status quo of more guns and people is not the solution and in the meantime, it’s disrupting a way of life.
“The whole system is falling apart and it’s just wasting taxpayer money,” he says.
Dodson’s frustration with the federal incursion is rooted in something deeper than fiscal responsibility. As we drive around, the sun bears down across a rolling sea of volcanic rubble, cacti and brush. The desert teams with life while looking impossibly dry.
This terrain only attracts a certain frontiersman-type personality, people for whom the barrenness is less lonely than free and pure. Like that of most locals, Dodson’s is a mixed lineage. His relatives were bootleggers and lawmen, Mexicans and Americans. The border was in decades past seen less as a barrier than a place of commerce, he says. He shakes his head at the perception of this as a dangerous place — a view fostered both in Hollywood and in Washington.
“Let me tell you how you’re going to get hurt here,” he says.  You’re going to get snake bit.”
For as much as Dodson has emerged into an outspoken critic of the build-up, he is also become a tremendous beneficiary of it. Aside from his Terrahawk, he bought a new Chevrolet Silverado and Ford Explorer for his department. With immigration-control money, he paid for Vortex ground sensors, RTVs, radios, and hundreds of hours of overtime pay for his deputies with federal border security money. His sheriff’s department has collected more than $600,000 dollars per year on average from one federal grant program since 2008. Without these funds his annual budget amounts to about $700,000.
Dodson is quick to add that his budget is but a drop in the bucket compared to the federal dollars pouring into other agencies nearby, but he’s not stopped asking the federal government for border security grants.
Checkpoint Section Deck, For Checkpoint Section
Above:A border checkpoint in Mexico.
Dodson pulls into one of two major checkpoints in Brewster County that is a little over 50 miles north of the border. This one is just south of just south of Marathon (tourist motto: “Where there is nothing to do”) off of U.S. Route 385.
The checkpoint looks like a tractor-trailer-sized giant x-ray machine lined with a row of digital cameras. Before Sept. 11, people could just whiz by; almost never knowing it was there as it was so rarely open. Now, these outposts are full-service, 24/7 patrol stations with cameras. They have doubled the number of border patrol agents working there and brought in dogs that can smell the slightest trace of marijuana or other drugs.
Dodson rolls down the window and yells at the officer that he’s going to stop to take some pictures.  Everyone laughs.
Border Patrol’s white and green trucks have become as ubiquitous as cacti, as officers check papers, or search for drugs. It’s not unusual to pass by five trucks in a short drive down Alpine’s main street: at the gas station; at the Holland hotel; on the road, or parked for hours at a time behind the brush somewhere around the corner closer to the river.
That day, Border Patrol had an operation in Lajitas, a tiny border town in Brewster, and green and white truck filtered back and forth around a corner of a golf resort that hugs the Rio Grande.
On average, each Border Patrol agent in the Big Bend sector picked up just six undocumented immigrants in 2013, or just one every other month. Those numbers are down from an average of 70 in 2000. (The average along the southwestern border was 22 in 2013 and 192 in 2000). This is partly the reason that locals refer to them as the “Boredom Patrol.”
Many of the agents Dodson knows through his side business as a gun dealer he runs out of his home. He lives with his wife in a modest house on the edge of Alpine with a collection of guns, Harleys and four-wheelers. As sheriff, he makes $39,000 per year. It’s a decent salary in these parts, unless you compare it to the Border Patrol agents the Sheriff was talking to, who made around $90,000 with overtime in their mid-20s.
Dodson’s son was a Border Patrol agent. But after four years he left the job because it was too boring and he went to veterinarian school.
Photos by [NAME HERE]/IRW.
Lee Smith offers a different view of the work. He has been with the Border Patrol for eight years and he is the local union representative for West Texas. Smith’s father and grandfather both worked as Border Patrol agents. He admits that the job gets “monotonous” at time, but that the low apprehensions in Big Bend are misleading; they do not include those who evade detection and he sees plenty evidence of “getaways.” The probability of catching Mexican nationals along the southern border is around 50-60 percent over the last decade, according to a 2013 study by the Council on Foreign Relations, independent, nonpartisan membership organization, think tank, and publisher.
Smith says his agency’s reliance on Big Bend’s distinctly vast and treacherous desert as its greatest natural asset discouraging border crossers has put it at a relative disadvantage. Immigrants have proven increasingly desperate and willing to traverse riskier terrain. In 2012, law enforcement found 127 bodies in Brooks County, a sprawling county about six hours south of Big Bend in the Rio Grande Valley.
Smith and many other border patrol agents believe that Big Bend could become the next hot spot for drug traffickers and undocumented immigrants. They have good reason to worry. In the 1980s, Nogales, Arizona was widely viewed as too remote to cross. But in the early 2000s it became a favorite passage point after nearby El Paso and San Diego built barriers. More recently, after the federal government barricaded Nogales, Rio Grande Valley at Texas’ southern tip became the new go-to crossing. After years of declines, it experienced a 69 percent increase in apprehensions during the last six months, compared to the same period last year.
A guide rows a boat across the river from Boquillas, Mexico into the United States.
“This is now the weakest link in the chain,” Smith says referring to the Big Bend area. This is why he and other border patrol officials have been lobbying U.S. Representative Pete Gallego, a Democrat from Alpine, whose district encompasses most of Big Bend, to boost the amount of federal money set aside for immigration control in Big Bend “We should build it up,” Smith says. “They should look at Big Bend as the next place.”
Gallego says he is open to new border resources, especially if it will spur economic development through new Border Patrol jobs. But he disagrees with the general “dangerous border” characterization of Big Bend and questions whether new forces will actually mitigate migrant crossings, rather than just redirect them to find new ways to cross. Further, he says he sees border control fatigue setting into his constituents. “There is a limit,” he says of what additional border control the region can take. “If you talk to the people here, they feel somewhat like they live in a police state.”
But Gallego’s willingness to entertain the idea of double border patrol in the face of everything shows the ease at which border escalation has ensued over the past decade, even among skeptics.
Smith and many other border patrol agents believe that Big Bend could become the next hot spot for drug traffickers and undocumented immigrants.
Dodson, an expert read of his constituents leanings having been re-elected unopposed since 2003, knows there’s pushback, but at the same time, has participated in the border security expansion as many sheriffs have been along the border. However, as unique as Big Bend is and as contrary as Dodson’s opinions may seem, in fact, most of the sheriffs along the Texas-Mexico border have come out against the 2013 Senate and House –proposed plans to double border patrol and to have local law enforce federal immigration laws.
Like many border sheriffs who see ever-new ways of crossing the border, Dodson says if the government really wanted to crack down on illegal immigration, it would on work site enforcement in the interior.
But for now at least, border patrol agents in Big Bend are mostly netting Americans not immigrants, explains Brewster County Attorney Steve Houston.
Houston’s office sits in an old red brick courthouse building next door to Sheriff Dodson’s at the center of Alpine. Houston’s wood paneled office walls are now covered with rows of brightly colored college pennants that he has collected and hung in between stacks of beige file cabinets. The pennants are from the schools that the kids he has prosecuted in recent years attended.
There were the two honors students from Rice University; the kid from South Carolina, a pre-med student from who-knows-where, and a senior from the University of Virginia, who had already accepted a job with the State Department, he says, who got caught with a small amount of personal marijuana.
“We’re not talking about anything having to do with terrorists or illegal immigration,” he says. “We’re talking about native-born kids who have been caught in the immigration net.”
Houston adds that he used to prosecute every case that came across his desk. Now he only accepts about half of 400 he has in his docket at any given time because most of the rest are too petty to pursue.
Between 2005 and 2011, eighty percent of people busted for drugs by federal border patrol agents in Big Bend were U.S. citizens, according to a recent federal data obtained by the Center for Investigative Reporting, a journalism nonprofit based in Berkeley, California.
“You got all these young guys out there and they get bored. And they look for any reason to, to interact and stop somebody. Cause it’s no fun just driving around in a vehicle, 8 hours listening to the radio.”


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--- layout: default nav: examples ---
Below are some examples of Intercooler functionality, each with a working demo below the code sample.
This is a simple div that polls an http endpoint for updates every 1 second

Sample Polling Div. Value is 0

This is a div that is refreshed explicitly using events and the Intercooler library

Sample Manual Div. Value is 0
 <button onclick="Intercooler.refresh($('#manual-update'));">Update It!</button>
This is a div that is refreshed automatically when the button is clicked due to the fact that it depends on a URL that the button targets for update.

Sample Dependency Dectection. You have clicked 0 times
 <button ic-post-to="/dependency_div">Increment Counter</button>
You may want to target the value of an style attribute with an endpoint for a smoother UI experience. Below is an example targeting the 'width' attribute of the style on the progress bar, allowing for smooth easing as it updates.

You may want to target the value of an attribute with an endpoint for a smoother UI experience. Below we update the entire style block of the element

Here is some text!

This example binds two inputs to two different endpoints. The div below them then depends on a parent path, but sources from a different URL. When you change the value in the inputs (tab out) the div below will update.
<form role="form">
 First Name <input type="text" name="first_name" class="form-control" placeholder="Enter Your First Name" ic-post-to="/contacts/1/first_name">

 Last Name <input type="text" name="last_name" class="form-control" placeholder="Enter Your Last Name" ic-post-to="/contacts/1/last_name">
 </form>
Nothing Entered Yet...

Intercooler.js makes it easy to do incremental inline form element validations against your server. Below is an example that will only allow properly formatted emails.

 Enter An Email <input type="text" name="email" class="form-control" placeholder="Enter An Email">


SORCERESS A film review by Thomas E. Billings Copyright 1989 Thomas E. Billings
Synopsis: A traveling Dominican friar visits a village in medieval France, searching for heretics. He encounters an herbalist, a solitary woman that he suspects may be a sorceress. A story of religious zeal and personal guilt.
France (French with English subtitles), color, 1987, 97 minutes.
Director: Suzanne Schiffman Producers: Pamela Berger, Annie Leibovici, George Reinhart Principal cast: Tcheky Karyo, Christine Boisson, Jean Garnet
The plot involves an aggressive, zealous Dominican friar who visits a remote rural village in medieval France, searching for heretics. The heretics must be found and converted -- or executed by burning. The friar is driven both by his zeal and by his guilty conscience, for he has some dark secrets of his own to hide.
He encounters a "forest woman," a young herbalist who lives in the woods, gathering herbs and plant medicines. Her solitary ways and personal detachment seem very strange to the friar, and she becomes the target of his blind, hateful wrath.
This film is well made, with good acting, photography, and period "atmosphere." The only technical problem is with the costumes. The film depicts peasants working in the fields in the middle ages. However, everyone in the film is dressed in clean, neat clothing. (Just try to work in a field and stay clean!). Fortunately, this does not detract from the film very much.
The last half-hour or so of the film is very interesting and suspenseful. However, you have to sit thru the first hour to get there, and the first hour is very slow-moving as it builds toward the finale. I suspect that many viewers will find the first hour to be boring.
As an overall evaluation, I would only rate the film as "fair," because of the very slow pace of the first hour. If you are interested in the subject matter (religious zealotry in the Middle Ages), it is worth considering.
Reviewer: Thomas E. Billings, Department of Statistics University of California, Berkeley Reviewer contact<EMAIL_ADDRESS>The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


Rules
Boys
1.FIBA rules applicable.
2.10 minutes each quarter with 2 minute break between the quarters and 5 minutes at half time (unless otherwise stated).
3.Teams should report to the basket ball court half an hour before their match.
4.All the players of the team should have same colour of jersey with printed numbers.
5.Use of abusive or foul language during the play can lead to technical fouls or expulsion depending on the referee and the organizing committee.
6.No players should have anything on his/her hand or neck (wrist watch, necklace, ring, kada,bracelet etc.) jewellery of any kind is not allowed and nails have to be cut.
7.Maximum 12 players are allowed in a team.
Girls
1.FIBA rules applicable.
2.Match will be normal 4 quarters, each quarter being 10 minutes.(unless mentioned otherwise) .
3.Teams should report to the Basketball court half an hour before their match.
4.Use of abusive or foul language during the play can lead to technical fouls or expulsion depending on the refree and the organising committee.
5.Players should not have anything on their hands or neck (wrist watch, necklace, ring, bracelet etc.). Nails should be cut.


{{ include.licence | default: "" }} This site uses icons from GLYPHICONS.com released under a Creative Commons Attribution 3.0 Unported licence.


JekyllConf is a virtual conference. We'll stream directly to this website.
Yes, all the videos will be publicly available on YouTube.
CloudCannon is organising JekyllConf. We want to help grow the Jekyll community and showcase all the awesome people and projects using Jekyll.


Ethical hacking is an important tool in many national security agencies and evencompanies. This workshop is specifically designed to provide the right knowledge to the aspiring Cyber Forensics & Ethical Hacking enthusiasts. This workshop will explore the various means that an intruder has available to gain access to computer resources. It will investigate weaknesses by discussing the theoretical background behind, and whenever possible, actually performing the attacks.
Content for Ethical Hacking
Computer Security - Basics
- Introduction
- Hacker & Cracker
- Attacker & Victims
- ASCII Code - making a folder invisible
Network Security
- IP Address – Basic, Detecting
- Ping & Ping Sweep
- Tracing Target Location
- Detecting Victim's OS
- Detecting Firewall
- Countermeasures
Domain name and DNS
- ICANN
- Registrar, Registry, Registrant
- Top Level Domains
- Lifecycle of gTLD
- DNS Delegation
Email Security
- Email Threats
- Email Forging
- Spamming
- Email Headers
- Countermeasures
Port Scanning
- Type of Ports
- Virtual Port numbers
- Detecting Open Ports
- Tools to carry out Port Scanning
- Countermeasures
Intellectual Property Theft
- Trojan working & countermeasure
- Keylogger working & countermeasure
- Steganography
Password Cracking & Prevention
- Password Cracking Techniques
- Brute force Attack
- Countermeasures
Social Networking & Mobile Apps Hacking
- Whatsapp & WeChat hacking
- Facebook Hacking
- WiFi Hacking
Identity Attacks Security
- Proxy Servers
- Proxy Bouncing
Other Hacking
- Hacking Control panel of Websites
- Making own Virus
- SQL Injection Attack
- Social Engineering Attacks
- Hacking through Google
Cyber Law and Consulting
- What is Cyber Law
- Types of Crimes
- Blogs & Blogger's rights & limitation
- Central Acts & State Acts
- CERT-IND & AO (State level)
Certificate of Participation from Techkriti, IIT Kanpur to each participant.
Superior learning experience from the experts to enhance the practical skills


Efficiently unleash cross-media information without cross-media value. Quickly maximize timely deliverables for real-time schemas. Dramatically maintain clicks-and-mortar solutions without functional solutions.
Completely synergize resource sucking relationships via premier niche markets. Professionally cultivate one-to-one customer service with robust ideas. Dynamically innovate resource-leveling customer service for state of the art customer service
$ 200,000,000
344 Villa, Syndey, Australia
John Parker
009 229 2929


Global DRAM revenues increase 4% in 3Q19, says DRAMeXchange
by Jessie Shen, DIGITIMES, TaipeiSales in the global DRAM market grew 4.1% sequentially to US$15.45 billion in the third quarter of 2019, following three quarters of sequential drops, according to DRAMeXchange.
DRAM suppliers saw their combined bit sales ramp up rapidly in the third quarter, DRAMeXchange indicated.
"Demand-side inventory in 2H19 has returned to relatively healthy levels," said DRAMeXchange. "Furthermore, some vendors pulled their quarterly product shipment forward in an effort to avoid potential negative impacts from Trump's impending tariffs."
Looking into the fourth quarter, DRAM makers are expected to see their shipments climb further thanks to growing demand for servers and smartphones, DRAMeXchange noted.
DRAM market leader Samsung posted sequential increases of 30% and 5%, respectively, in bit sales and revenues during the third quarter, while SK Hynix saw its bit sales increase 20% on quarter with a 3.5% rise in revenues. Samsung grabbed a 46.1% share of the global DRAM market in the third quarter, followed by SK Hynix with a 28.6% share, according to DRAMeXchange.
"In spite of positive movements in shipment numbers, DRAM suppliers saw diminished operating profit margins due to a 20% industry-wide decline in ASP," DRAMeXchange continued. Samsung's operating profit margin fell to 33% in the third quarter from 41% in the second, while SK Hynix' slipped by a smaller 4pp on quarter to 24%.


Gordo’s Returning To ‘Lizzie McGuire’ & I Wonder If He’s Still Pissed At Her For Pashing Paolo
by By Matt GaleaThe OG Lizzie McGuire theme song goes, “If you believe we’ve got a picture-perfect plan, we got you fooled.” Well they got us fooled alright, but they also appear to have a very picture-perfect plan for the Disney+ reboot and it involves one of your fave characters.
Adam Lamberg is putting his dorky, know-it-all shoes back on to play David “Gordo” Gordon in a recurring role on the new show.
Our girl Hilary Duff confirmed the news with an Insta pic that took me right back to the final ep where Lizzie kisses Gordo on the cheek in the final scene, proving that she has feelings for him as well.
It looks like Gordo is still the unapologetic outcast, what with the Docs and all, and based on his closeness to Lizzie in the pic, we can only assume that he still has the hots for her.
The question is: Does she still have the hots for him?
Disney+ shared a vid confirming his return to the series, check it:
He joins recently announced returning cast members Hallie Todd, Robert Carradine and Jake Thomas, who played Lizzie’s fam in the original.
“We are standing in what will soon be the McGuire living room. What’s up fam. We doin this,” Hilary wrote on Insta.
Speaking to E! News, Duff recently discussed what possible storylines the reboot could include.
“I have said this before, but for me coming back when she’s 30 and she’s not in a marriage and she’s not having a baby and she’s not doing all the things that I have already done in my life, that story is really exciting for me,” the actress told the publication.
“I think to myself, where can we go? What are the struggles of a 30-year-old right now?  And for me, that’s Lizzie McGuire, she had those struggles in middle school where she didn’t have a place where she fits in and you know […] always on the struggle bus, but she’s also your best friend, and that’s exactly what I want to target and hit home again—is being there for girls in this time of their life.”

“Maybe at the end of the series we see her having a baby? You know, maybe it’s hard for her to get pregnant? Maybe there is something bad happening on her 30th birthday in the first episode? Maybe she’s going to be in her childhood bedroom in the first episode? I don’t know! There’s all this fun! We want to give fans what they want, but we also want to have a completely new show.”
Disney+ just arrived here in Oz and Lizzie McGuire is expected to drop on the platform next year.
Image: Disney


its 2am, I still have questions but not time to wait longer for answers. Maybe it'll come up when I'm asleep. Good luck with it
how does the lesser stake side win?
are odds variable based on spread ratio?
what profit benefit does the oracle derive, and how is it punished for misbehaving?


[Gecode] We just merged Sets.
Christian Schulte
schulte at imit.kth.se
Fri Apr 30 14:22:48 CEST 2004
Let's not jump here, there is no problem... At least to those compared under
Windows. Actually, the statistics will change its implementation to avoid
the problem right from the start.
Christian
--
Christian Schulte, http://www.imit.kth.se/~schulte/
-----Original Message-----
From: gecode-bounces at ps.uni-sb.de [mailto:gecode-bounces at ps.uni-sb.de] On
Behalf Of duchier at ps.uni-sb.de
Sent: Friday, April 30, 2004 2:21 PM
To: Technical discussions about Gecode
Subject: Re: [Gecode] We just merged Sets.
Gabor Szokoli <szokoli at ps.uni-sb.de> writes:
> As a sidenote, we can build dynamic libraries under Linux if
> statistics are disabled (nasty uninitialised global state there...)
what's the problem here?
--
Denys Duchier - Équipe Calligramme - LORIA, Nancy, France
AIM: duchierdenys
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Indiana University Class of 2021 Bachelor of Science in Computer Science Specialization: Security Minor: Pyschology
Penn High School Class of 2017 Academic Honors Diploma


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