HBPreferencesChangeCallback Block Reference
| Declared in | HBPreferences.h |
|---|
Block Definition
HBPreferencesChangeCallback
The HBPreferences
class in Cephei
provides an interface for managing
user-defined preferences of a tweak, and the default values used when the
user has not yet changed a value.
typedef void (^HBPreferencesChangeCallback) ()
Discussion
HBPreferences
is very similar to NSUserDefaults
, however it is
specifically tailored to iOS tweak development, since tweaks may be loaded
into a sandboxed app (for instance, App Store apps), or one that runs as
the root
user (for instance, iFile, although these apps are slowly changing
their model so they now run as mobile). In both of these cases, using
NSUserDefaults
will result in reading from preferences inside the sandbox,
or inside root
’s home directory; both of which are not what is expected.
Advantages HBPreferences
has over NSUserDefaults
are:
- Directly reading the property list from the
mobile
user’s home directory, to support sandboxed apps and apps running asroot
. - Intuitive method of setting a default preference value.
- Updating of the app/tweak’s variables when preferences are changed.
- Keyed subscripting is allowed, which enables simple array syntax.
- Values in the preferences plist are called preferences, not defaults, to
avoid ambiguity -
NSUserDefaults
uses “defaults” to refer to both preferences themselves and the fallback values if a key doesn’t exist.
Ensure you read the discussion for [HBPreferences registerObject:default:forKey:] before using the automatic updating mechanism. [HBPreferences objectForKey:] does not update as another process updates the preferences on iOS 7 or older; if you need to support older iOS versions, use the registration methods instead.
Example usage
HBPreferences *preferences;
BOOL doThing;
%ctor {
preferences = [[HBPreferences alloc]<EMAIL_ADDRESS>[preferences registerDefaults:@{
@"Enabled": @YES,
@"AnotherSetting": @1.f
}];
[preferences registerBool:&doThing default:NO forKey:@"DoThing"];
NSLog(@"Am I enabled? %i", [preferences boolForKey:@"Enabled"]);
NSLog(@"Can I do thing? %i", doThing);
}
References
Declared In
HBPreferences.h


|
libpqxx 4.0
|
Prepared statements are SQL queries that you define once and then invoke as many times as you like, typically with varying parameters. It's basically a function that you can define ad hoc.
If you have an SQL statement that you're going to execute many times in quick succession, it may be more efficient to prepare it once and reuse it. This saves the database backend the effort of parsing complex SQL and figuring out an efficient execution plan. Another nice side effect is that you don't need to worry about escaping parameters.
You create a prepared statement by preparing it on the connection, passing an identifier and its SQL text. The identifier is the name by which the prepared statement will be known; it should consist of letters, digits, and underscores only and start with a letter. The name is case-sensitive.
void prepare_my_statement(pqxx::connection_base &c) { c.prepare("my_statement", "SELECT * FROM Employee WHERE name = 'Xavier'"); }
Once you've done this, you'll be able to call my_statement
from any transaction you execute on the same connection. Note that this uses a member function called "prepared"
; the definition used a member function called "prepare"
.
pqxx::result execute_my_statement(pqxx::transaction_base &t) { return t.prepared("my_statement").exec(); }
Did I mention that you can pass parameters to prepared statements? You define those along with the statement. The query text uses $1
, $2
etc. as placeholders for the parameters in the SQL text. Since your C++ compiler doesn't know how many parameters you're going to define, the syntax that lets you do this is a bit strange:
void prepare_find(pqxx::connection_base &c) { // Prepare a statement called "find" that looks for employees with a given // name (parameter 1) whose salary exceeds a given number (parameter 2). const std::string sql = "SELECT * FROM Employee WHERE name = $1 AND salary > $2"; c.prepare("find", sql)()(); }
It's the ()() that declares the two parameters. If any of the parameters will be in binary form, you will pass treat_binary in the corresponding pair of parentheses.
When invoking the prepared statement, you pass parameter values using a similar syntax.
pqxx::result execute_find( pqxx::transaction_base &t, std::string name, int min_salary) { return t.prepared("find")(name)(min_salary).exec(); }


Contains Study-Materials for B.E./B.Tech students of JNTU-Kakinada affliated Colleges
Welcome
To
JNTUK-Instant!
-- This is the Main Section --
-_-


Please confirm your email by clicking the link bellow:
{% button activate_uri "activate account" %} {% endblock %}


• Complex Digital Marketing support (cooperation with XoXo Party, Prosell International LTD)
• Creating a landing pages, building websites (HTML, CSS, Javascript)
• Campaigns management: Google Ads, Facebook, e-mail and display/programmatic
• Web analytics (Google Analytics)
• Website optimization (SEO, UX)
• Logistic support for an online store (Prosell International LTD.): shipment, warehouse and employees management.
•Supervision over scientific research in the field of molecular oncology.
•Managment of project of own doctoral thesis
•Management of grant projects and laboratory supplies
•Supervision over foreign students doing internships in Department of Genetics.
•Supervision over of marketing projects
• Staff recruitment (hostesses, promoters, supervisors)
•Drawing up contracts, cost estimates, logistics activities, supervision over marketing events
Epigenetics
Behavioral psychology
Natural medicine and cosmetics
Traveling


Krzysztof Gadecki, 40, fused razor blades into two pieces of plastic cutlery to create a shank that he used to attack Colin Mathieson, 42, at Glenochil Prison in Scotland.
Mathieson suffered a six-inch gash from his forehead to his mouth on the left side of his face, a four-inch cut across his right cheek, a one-inch wound on his right heel and a 1.5-inch "gaping" injury on his right arm.
The rapist needed 35 stitches to close his wounds in an attack that Gadecki says Mathieson brought on himself for taking his porn films and "being rude".
Gadecki was jailed for life in 2017 with minimum terms of 26 years for fatally stabbing Holly Alexander, 37, and her partner Ronnie Kidd, 40, in their Dundee flat.
Mathieson was jailed for life in 2001 after a judge ruled he was too dangerous to be allowed to live on the outside. He preyed on women alone in their homes.
Speaking through an interpreter at Falkirk Sheriff Court, Gadecki disputed a prosecution account that he had initially lent Mathieson some DVDs.
With a detachment described as “chilling” by seasoned court-watchers, he said: “I found that person in my cell. I caught him rummaging through my DVDs.
“I told him to stop and he didn’t reply.
“He was very rude and arrogant and extremely disrespectful to me and kept touching my stuff.
“He took a whole box of 15 Polish DVDs and a couple of light porn movies as well.
“I said to myself, ‘I’m not happy with it, maybe if I break his nose he’ll realise it’s a big deal to me’."
He added: “I made the weapons with razor blades and plastic cutlery. It took me about 40 minutes to make them, and I went to his cell with the intention to hurt him.
“For eight months nobody made me so angry as this guy.

“I punched him with a closed fist and headbutted him. He hit his head on the safety rail of his bed.
“He was in the foetal position. I was on top of him and I pushed my knee between his arms and legs.
“He said to me ‘Is that all you’ve got?’ so I pulled out both my weapons and I cut him.
“Then I asked him, ‘Is that enough’?”
Gadecki represented himself because he claimed there was “no point” getting a solicitor to defend him over the July 25, 2018, attack at the top security prison in Clackmannanshire.
The court heard Mathieson ran, streaming with blood, to warders.
In hospital, medics inserted 18 stitches into the wound on the left hand side of his face, nine into the right side, six into his arm, and two into his heel.
Gadecki admitted assaulting Mathieson to his severe injury and permanent disfigurement. He also admitted possessing three bladed weapons in jail - two modified plastic knives and a plastic spoon.
He told Sheriff Derek Hamilton: “I’m concerned I’m not safe to be around.”
Sheriff Hamilton sentenced Gadecki to a further 26 months imprisonment, to be served at the expiry of his 26-year life term.
He said: “Such extreme violence in custody cannot go unrecognised.”
Before he was led the cells, Gadecki turned and muttered to the interpreter.
She said: “He says he’ll probably not live to see the end of his sentence, and if he does, things will have changed so much there’ll be no planes or buses and he will just be able to teleport himself back to his country."
Gadecki had been jailed for rape, robbery and fraud in Poland, but was at liberty when he committed the murders having appealed against deportation.


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Use mouseover for title attributes.
inRepository:
unit name
file name
movie width
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each-seg tiers
endOnly tiers
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breakAtNewLines:
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Created an online mock shopping website allowing registration as a customer or an owner, and providing the ability to purchase products as a user, or view shopping analytics and create new products as an owner. Front-end done in HTML and JavaScript. Back-end done in Java, using a PostgreSQL database and Apache Tomcat webserver.
Back to project portfolio


This program outputs a list of supermarket goods filtered by expiry date, you can choose the settings using the button below.
Insert the values you want to change. Empty fields will use default settings.


Probability Notation Cheatsheet
I recently found myself using Bayesian inference techniques to solve a problem. Wanting to know more, I turned to the literature. But the notation looked foreign to me. The symbols were recognizable, but I couldn’t draw meaning from their arrangements on the screen.
Familiarize yourself with the definitions of σ-algebras and probability spaces. For the rest of the article, assume that $(\Omega,\mathcal{F},\mathbb{P})$ is a discrete probability space.
The first object on which I stubbed my math toes was the random variable and its use to construct events. A discrete random variable is a function $X: \Omega \rightarrow \mathbb{R}$. That’s it.
Often, random variables are used to construct events that are passed to $\mathbb{P}$. For example, $\mathbb{P}(X \leq 100)$. The notation $X \leq 100$ describes an event; an element in $\mathcal{F}$; a subset of $\Omega$. The means the following.
$X \leq 100 \triangleq \{ \omega \in \Omega ~|~ X(\omega) \leq 100 \}$
More generally, if we have a constraint $C$ (like only evens or between 1 and 10), then the notation $C(X)$ is interpreted as the event $\{ \omega \in \Omega ~|~ C(X(\omega)) \}$.
Similarly, use of natural languge connectives like “and” and “or” translate to set operations. Consider $\mathbb{P}(H \leq 160 ~\mathrm{and}~ W \geq 60)$. The use of “and” refers to set intersection.
Summary
Here is a list of common notational conventions for constructing events.
- For some $A \subseteq \mathbb{R}$, $X \in A \triangleq \{ \omega \in \Omega ~|~ X(\omega) \in A \}$.
- For some relation $R \subseteq \mathbb{R} \times \mathbb{R}$ and $t \in \mathbb{R}$, $X ~R~ t \triangleq \{ \omega \in \Omega ~|~ (X(\omega), t) \in R \}$. Common relations include $\leq$, $<$, $=$, etc.
- For events $A,B \in \mathcal{F}$, $\mathbb{P}(A ~\mathrm{and}~ B)$ is equivalent to $\mathbb{P}(A \cap B)$.


A File Test Property is an optional parameter that will alter the behavior of a File Test. Where possible, File Test Properties should be avoided in order to simplify the user experience. As new File Test Properties are created, care must be taken to ensure that they will behave in both the GUI mode and the Command Line mode.


For better orthogonality, the assembler defines similar symbols as the compiler, depending on the target system selected:
__APPLE2__
- Target system is apple2
__APPLE2ENH__
- Target system is apple2enh
__ATARI__
- Target system is atari
__ATMOS__
- Target system is atmos
__BBC__
- Target system is bbc
__C128__
- Target system is c128
__C16__
- Target system is c16
__C64__
- Target system is c64
__CBM__
- Target is a Commodore system__CBM510__
- Target system is cbm510
__CBM610__
- Target system is cbm610
__GEOS__
- Target system is geos
__LUNIX__
- Target system is lunix
__NES__
- Target system is nes
__PET__
- Target system is pet
__PLUS4__
- Target system is plus4
__SUPERVISION__
- Target system is supervision
__VIC20__
- Target system is vic20


Create Your DelveMItt Account..!
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Resource Type: dns
- Defined in:
- lib/puppet/type/dns.rb
- Providers:
-
dns
Overview
Manage the configuration of the DNS client for Oracle Solaris
Properties
-
domain
The local domain name
-
nameserver
The IP address(es) the resolver is to query. A maximum of 3 IP addresses may be specified. Specify multiple IP addresses as an array
-
options
Set internal resolver variables. Valid values are debug, ndots:n, timeout:n, retrans:n, attempts:n, retry:n, rotate, no-check-names, inet6. For values with 'n', specify 'n' as an integer. Specify multiple options as an array.
Supported values:- debug
- rotate
- no-check-names
- inet6
- /ndots:(\d+)?/
- /timeout:(\d+)?/
- /retrans:(\d+)?/
- /attempts:(\d+)?/
- /retry:(\d+)?/
- absent
-
search
The search list for host name lookup. A maximum of 6 search entries may be specified. Specify multiple search entries as an array.
-
sortlist
Addresses returned by gethostbyname() to be sorted. Entries must be specified in IP 'slash notation'. A maximum of 10 sortlist entries may be specified. Specify multiple entries as an array.
Parameters
-
name (namevar)
The symbolic name for the DNS client settings to use. This name is used for human reference only.
Supported values:- current


Post edited 1 x times, last by
Topicstarter
hello, i have to ask this here because it seems that EA/dice/esn doesn't care...
is there a way to hide your status and the server you are playing on ?
for example sometimes i'm just behing stalked by guys following me on any servers and there's absolutly no way to stop that...
if anyone knows a way, a plugin etc etc please let me know :)
Thx
Now, I'm no coding expert but I'm pretty sure this is impossible for anyone else but DICE to do.
i have to admit that it would be great to have such an option...should be standard those days
Post edited 3 x times, last by
BrainFooLong
Administrator
BrainFooLong
Administrator
xXJumpyXx wrote:
Now, I'm no coding expert but I'm pretty sure this is impossible for anyone else but DICE to do.
That's what it is. You need to talk with DICE.
Topicstarter
Ok thx for your answers :)


Games use p5.js, p5.play and matter.js libraries in javascript
To open the game, Download Visual Studio Code, then click on the game you want to see, click on the CODE icon then click on download zip.
Then open the download folder and unzip it anywhere you want. Then open the chrome Extension WEB SERVERS FOR CHROME and then click on the CHOOSE FOLDER ICON
Then click on the folder you have unzipped and then click on the link below the choose folder icon.
Then ENJOY !!


{% extends "base.html" %} {% block title %}Contact{% endblock %} {% block content %}
This is the page with contact information.


| June 1, 2018 | SSB workshop |
|---|---|
| 1:00 PM | Introductions; |
| Random Forest and Predictive Modeling | |
| 1:30 PM | Predicting cryptic species example |
| 1:45 PM | Tutorial 1; predicting IUCN status |
| -discuss dataset | |
| -evaluating classifier / downsampling | |
| -variable importance / making predictions | |
| 3:15 PM | ~Coffee Break~ |
| 3:30 PM | Model selection with random forest |
| 3:45 PM | Tutorial 2; predicting cryptic diversity |
| -discuss dataset | |
| -evaluating classifier | |
| -adding predictor variables | |
| 4:30 PM | Discuss main results and conclusions |
| 4:55 PM | Concluding remarks |


We are really glad to be a part of the line up at Houston Festival 2015 in Kimberley, VA. This festival features something of the biggest names in country music.


DenseColumn
that converts from sparse, categorical input.
tf.compat.v1.feature_column.embedding_column
tf.compat.v2.feature_column.embedding_column
tf.feature_column.embedding_column( categorical_column, dimension, combiner='mean', initializer=None, ckpt_to_load_from=None, tensor_name_in_ckpt=None, max_norm=None, trainable=True )
Use this when your inputs are sparse, but you want to convert them to a dense representation (e.g., to feed to a DNN).
Inputs must be a CategoricalColumn
created by any of the
categorical_column_*
function. Here is an example of using
embedding_column
with DNNClassifier
:
video_id = categorical_column_with_identity( key='video_id', num_buckets=1000000, default_value=0) columns = [embedding_column(video_id, 9),...] estimator = tf.estimator.DNNClassifier(feature_columns=columns, ...) label_column = ... def input_fn(): features = tf.io.parse_example( ..., features=make_parse_example_spec(columns + [label_column])) labels = features.pop(label_column.name) return features, labels estimator.train(input_fn=input_fn, steps=100)
Here is an example using embedding_column
with model_fn:
def model_fn(features, ...): video_id = categorical_column_with_identity( key='video_id', num_buckets=1000000, default_value=0) columns = [embedding_column(video_id, 9),...] dense_tensor = input_layer(features, columns) # Form DNN layers, calculate loss, and return EstimatorSpec. ...
categorical_column
: A CategoricalColumn
created by a
categorical_column_with_*
function. This column produces the sparse IDs
that are inputs to the embedding lookup.dimension
: An integer specifying dimension of the embedding, must be > 0.combiner
: A string specifying how to reduce if there are multiple entries in
a single row. Currently 'mean', 'sqrtn' and 'sum' are supported, with
'mean' the default. 'sqrtn' often achieves good accuracy, in particular
with bag-of-words columns. Each of this can be thought as example level
normalizations on the column. For more information, see
tf.embedding_lookup_sparse
.initializer
: A variable initializer function to be used in embedding
variable initialization. If not specified, defaults to
truncated_normal_initializer
with mean 0.0
and
standard deviation 1/sqrt(dimension)
.ckpt_to_load_from
: String representing checkpoint name/pattern from which to
restore column weights. Required if tensor_name_in_ckpt
is not None
.tensor_name_in_ckpt
: Name of the Tensor
in ckpt_to_load_from
from which
to restore the column weights. Required if ckpt_to_load_from
is not
None
.max_norm
: If not None
, embedding values are l2-normalized to this value.trainable
: Whether or not the embedding is trainable. Default is True.DenseColumn
that converts from sparse input.
ValueError
: if dimension
not > 0.ValueError
: if exactly one of ckpt_to_load_from
and tensor_name_in_ckpt
is specified.ValueError
: if initializer
is specified and is not callable.RuntimeError
: If eager execution is enabled.