AWS::SSM::PatchBaseline
The AWS::SSM::PatchBaseline
resource defines the basic information for an
AWS Systems Manager patch baseline. A patch baseline defines which patches are approved for
installation on your instances.
For more information, see CreatePatchBaseline in the AWS Systems Manager API Reference.
Syntax
To declare this entity in your AWS CloudFormation template, use the following syntax:
JSON
{ "Type" : "AWS::SSM::PatchBaseline", "Properties" : { "ApprovalRules" :
RuleGroup
, "ApprovedPatches" :[ String, ... ]
, "ApprovedPatchesComplianceLevel" :String
, "ApprovedPatchesEnableNonSecurity" :Boolean
, "Description" :String
, "GlobalFilters" :PatchFilterGroup
, "Name" :String
, "OperatingSystem" :String
, "PatchGroups" :[ String, ... ]
, "RejectedPatches" :[ String, ... ]
, "RejectedPatchesAction" :String
, "Sources" :[ PatchSource, ... ]
, "Tags" :[ Tag, ... ]
} }
YAML
Type: AWS::SSM::PatchBaseline Properties: ApprovalRules:
RuleGroup
ApprovedPatches:- String
ApprovedPatchesComplianceLevel:String
ApprovedPatchesEnableNonSecurity:Boolean
Description:String
GlobalFilters:PatchFilterGroup
Name:String
OperatingSystem:String
PatchGroups:- String
RejectedPatches:- String
RejectedPatchesAction:String
Sources:- PatchSource
Tags:- Tag
Properties
ApprovalRules
-
A set of rules used to include patches in the baseline.
Required: No
Type: RuleGroup
Update requires: No interruption
ApprovedPatches
-
A list of explicitly approved patches for the baseline.
For information about accepted formats for lists of approved patches and rejected patches, see About package name formats for approved and rejected patch lists in the AWS Systems Manager User Guide.
Required: No
Type: List of String
Maximum:
50
Update requires: No interruption
ApprovedPatchesComplianceLevel
-
Defines the compliance level for approved patches. When an approved patch is reported as missing, this value describes the severity of the compliance violation. The default value is
UNSPECIFIED
.Required: No
Type: String
Allowed values:
CRITICAL | HIGH | INFORMATIONAL | LOW | MEDIUM | UNSPECIFIED
Update requires: No interruption
ApprovedPatchesEnableNonSecurity
-
Indicates whether the list of approved patches includes non-security updates that should be applied to the managed nodes. The default value is
false
. Applies to Linux managed nodes only.Required: No
Type: Boolean
Update requires: No interruption
Description
-
A description of the patch baseline.
Required: No
Type: String
Minimum:
1
Maximum:
1024
Update requires: No interruption
GlobalFilters
-
A set of global filters used to include patches in the baseline.
Required: No
Type: PatchFilterGroup
Update requires: No interruption
Name
-
The name of the patch baseline.
Required: Yes
Type: String
Minimum:
3
Maximum:
128
Pattern:
^[a-zA-Z0-9_\-.]{3,128}$
Update requires: No interruption
OperatingSystem
-
Defines the operating system the patch baseline applies to. The default value is
WINDOWS
.Required: No
Type: String
Allowed values:
AMAZON_LINUX | AMAZON_LINUX_2 | AMAZON_LINUX_2022 | CENTOS | DEBIAN | MACOS | ORACLE_LINUX | RASPBIAN | REDHAT_ENTERPRISE_LINUX | ROCKY_LINUX | SUSE | UBUNTU | WINDOWS
Update requires: Replacement
PatchGroups
-
The name of the patch group to be registered with the patch baseline.
Required: No
Type: List of String
Minimum:
1
Maximum:
256
Pattern:
^([\p{L}\p{Z}\p{N}_.:/=+\-@]*)$
Update requires: No interruption
RejectedPatches
-
A list of explicitly rejected patches for the baseline.
For information about accepted formats for lists of approved patches and rejected patches, see About package name formats for approved and rejected patch lists in the AWS Systems Manager User Guide.
Required: No
Type: List of String
Maximum:
50
Update requires: No interruption
RejectedPatchesAction
-
The action for Patch Manager to take on patches included in the
RejectedPackages
list.-
ALLOW_AS_DEPENDENCY
: A package in theRejected
patches list is installed only if it is a dependency of another package. It is considered compliant with the patch baseline, and its status is reported asInstalledOther
. This is the default action if no option is specified. -
BLOCK
: Packages in theRejectedPatches
list, and packages that include them as dependencies, aren't installed under any circumstances. If a package was installed before it was added to the Rejected patches list, it is considered non-compliant with the patch baseline, and its status is reported asInstalledRejected
.
Required: No
Type: String
Allowed values:
ALLOW_AS_DEPENDENCY | BLOCK
Update requires: No interruption
-
Sources
-
Information about the patches to use to update the managed nodes, including target operating systems and source repositories. Applies to Linux managed nodes only.
Required: No
Type: List of PatchSource
Maximum:
20
Update requires: No interruption
Tags
-
Optional metadata that you assign to a resource. Tags enable you to categorize a resource in different ways, such as by purpose, owner, or environment. For example, you might want to tag a patch baseline to identify the severity level of patches it specifies and the operating system family it applies to.
Required: No
Type: List of Tag
Maximum:
1000
Update requires: No interruption
Return values
Ref
When you pass the logical ID of this resource to the intrinsic Ref
function, Ref
returns the patch baseline ID, such as
pb-abcde1234567890yz
.
The ID of the default patch baseline provided by AWS is an ARN, for example
arn:aws:ssm:us-west-2:123456789012:patchbaseline/abcde1234567890yz
.
For more information about using the Ref
function, see Ref.
Examples
Create a patch baseline
The following example creates a Systems Manager patch baseline that approves patches for Windows Server 2019 instances seven days after they are released by Microsoft. The patch baseline also approves patches for Active Directory seven days after they are released by Microsoft.
{ "Resources": { "myPatchBaseline": { "Type": "AWS::SSM::PatchBaseline", "Properties": { "Name": "myPatchBaseline", "Description": "Baseline containing all updates approved for Windows instances", "OperatingSystem": "WINDOWS", "PatchGroups": [ "myPatchGroup" ], "ApprovalRules": { "PatchRules": [ { "PatchFilterGroup": { "PatchFilters": [ { "Values": [ "Critical", "Important", "Moderate" ], "Key": "MSRC_SEVERITY" }, { "Values": [ "SecurityUpdates", "CriticalUpdates" ], "Key": "CLASSIFICATION" }, { "Values": [ "WindowsServer2019" ], "Key": "PRODUCT" } ] }, "ApproveAfterDays": 7, "ComplianceLevel": "CRITICAL" }, { "PatchFilterGroup": { "PatchFilters": [ { "Values": [ "Critical", "Important", "Moderate" ], "Key": "MSRC_SEVERITY" }, { "Values": [ "*" ], "Key": "CLASSIFICATION" }, { "Values": [ "APPLICATION" ], "Key": "PATCH_SET" }, { "Values": [ "Active Directory Rights Management Services Client 2.0" ], "Key": "PRODUCT" }, { "Values": [ "Active Directory" ], "Key": "PRODUCT_FAMILY" } ] }, "ApproveAfterDays": 7, "ComplianceLevel": "CRITICAL" } ] } } } } }
YAML
--- Resources: myPatchBaseline: Type: AWS::SSM::PatchBaseline Properties: Name: myPatchBaseline Description: Baseline containing all updates approved for Windows instances OperatingSystem: WINDOWS PatchGroups: - myPatchGroup ApprovalRules: PatchRules: - PatchFilterGroup: PatchFilters: - Values: - Critical - Important - Moderate Key: MSRC_SEVERITY - Values: - SecurityUpdates - CriticalUpdates Key: CLASSIFICATION - Values: - WindowsServer2019 Key: PRODUCT ApproveAfterDays: 7 ComplianceLevel: CRITICAL - PatchFilterGroup: PatchFilters: - Values: - Critical - Important - Moderate Key: MSRC_SEVERITY - Values: - "*" Key: CLASSIFICATION - Values: - APPLICATION Key: PATCH_SET - Values: - Active Directory Rights Management Services Client 2.0 Key: PRODUCT - Values: - Active Directory Key: PRODUCT_FAMILY ApproveAfterDays: 7 ComplianceLevel: CRITICAL
See also
-
CreatePatchBaseline in the AWS Systems Manager API Reference.


Broken bar/isolated "loner". Attach, bring to top, align if necessary and finish:
Two horizontal bars:
Two vertical bars:
Two columns:
Pseudo-Dots
Dots


| | |
- append_item(room_name, item_name)
- Adds item to a room
Parameters:
room_name: Name of the room where the player is in
item_name: Name of the item that the player droped off
Returns:
dict: Return the items of the gaven room after the player drop an item
- assembling_descriptions(names, descriptions)
- Adds the room descriptions for all rooms inside a dictionary.
Parameters:
names(list): A list that contains all the rooms
descriptions(list): A list that contains all the
descriptions of the rooms
- assembling_rooms(names, neighbors, doors, items)
- Constructs room objects for all rooms in maze and stores all the rooms
inside a dictionary.
Parameters:
names(list): A list that contains all the rooms
neighbors(list): A list that contains all the neighbors of a room
doors(list): A list that contains all the doors of a room
items(list): A list that contains all the items of a room
- current_room(room_name)
- The current room the player is in.
Parameters:
room_name(string): Name of a room
Return:
dict: Return the current room that the player is in
- delete_item(room_name, item_name)
- Deletes item from room
Parameters:
room_name(string): Name of the room where the player is in
item_name(string): Name of the item that the player picked up
Returns:
dict: Return the items of the gaven room after
the player pick up an item
- is_item_in_room(room_name, item_name)
- Retruns if item is in room
Parameters:
room_name(string): Name of a room
item_name(string): Name of an item
Returns:
bool: Return true if the item is in the room. Return false otherwise.
- items_in_room(room_name)
- Returns dictionary of items in room
Parameters:
room_name(string): Name of a room
Returns:
dict: Return dictionary of items of the gaven room
- map_yaml_representation()
- Creates a yaml friendly representation of the room with descriptions
Returns:
map_representation(dict): Return dictionary that contains
all the rooms with the description
- move(cardinal, name)
- Returns the current room of the player after the player moves
a certain direction.
Parameters:
cardifnal(list): A list that contains all the cardinals of a room
name(list): A list that contains all the rooms
Returns:
current_room_name: Return the current room after the player
moves a certain direction
- not_empty_room(room_name)
- Checks if room is empty
Parameters:
room_name: Name of a room
Returns:
bool: Return true if the room has items in it. Return false otherwise.
- open_door(room_name, cardinal, key)
- Used to open rooms
Parameters:
room_name: Name of a room
cardinal(list): A list that contains the cardinals of a room
key(list): A list that contains all the keys
Returns:
dict: Return the room with the closed door opened
if there is a matching key
string:Print a message to the user when there is no closed door
string:Print a message to the user when there is no matching key
- room_description(room_name)
- Returns description of current room
Parameters:
room_name(string): Name of a room
Returns:
dict: Return the description of the gaven room
- to_string_current_items(name)
- Returns a string that lists the items in the selected room
Parameters:
name(list): A list that contains all the items
Returns:
item_list: Return a string that lists the imtems of the gaven room
|


How to Implement Minibatching in Tensorflow
Posted on ven. 22 décembre 2017 in Minibatch by Ji Won Park
In this notebook, I show how to implement "minibatches", a method which stores gradients over several chunks of data ("mini" batch) and apply them altogether. To keep this exercise concise, I use the MNIST image set and a very simple neural network as an example. I will compare how the results differ when the network is trained with and without minibatches, for several popular optimizers.
import tensorflow as tf # I use version 1.4
from tensorflow.examples.tutorials.mnist import input_data
mnist = input_data.read_data_sets("MNIST_data/", one_hot=True, seed=123)
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
Build a toy network¶
For simplicity, we will build a simple (single-layer) fully connected feed-forward neural network. x
is the input data placeholder for an arbitrary batch size (784 = 28x28 is MNIST image size). W
and b
are weights and biases for the output layer, and y
is the output to be compared against the label. For MNIST (10 digit classification), let's use the softmax cross entropy as our loss function.
x = tf.placeholder(tf.float32, [None, 784])
W = tf.Variable(tf.zeros([784, 10]))
b = tf.Variable(tf.zeros([10]))
y = tf.matmul(x, W) + b
y_ = tf.placeholder(tf.float32, [None, 10])
correct_prediction = tf.equal(tf.argmax(y,1), tf.argmax(y_,1))
accuracy = tf.reduce_mean(tf.cast(correct_prediction, tf.float32))
loss = tf.reduce_mean(tf.nn.softmax_cross_entropy_with_logits(labels=y_, logits=y))
Data preparation¶
We will use this simple function to load and store data prior to entering the training loop. This allows us to remove randomness in data-fetching, so that we can compare training with and without minibatches on the same dataset. Note that shuffle=False
so that data is not randomly shuffled and we seed read_data_sets
for reproducibility (in the first cell).
NOTE: the shuffle argument is available as of Tensorflow v1.3.
def get_images(batch_size, n_iterations):
return [mnist.train.next_batch(batch_size = batch_size, shuffle=False) for _ in range(n_iterations)]
Standard (no minibatch) training¶
Define a function train-standard
that uses the optimizer's minimize
function with the minimization target as an argument. There is no minibatch involved here. Note we seed the initialization of all variables.
def train_standard(opt_type, learning_rate, image_set):
# Arrays for logging accuracy and loss
acc_log = np.zeros(len(image_set))
loss_log = np.zeros(len(image_set))
# Create optimizer
opt = opt_type(learning_rate)
#
# no-minibatch (standard, simple) operation
#
minimize = opt.minimize(loss)
# Create session to execute ops
sess = tf.InteractiveSession()
# Necessary initializations
tf.set_random_seed(1234)
tf.global_variables_initializer().run()
# Train loop
for i, batch in enumerate(image_set):
sess.run(minimize, feed_dict={x: batch[0], y_: batch[1]})
acc_log[i] = sess.run(accuracy,
feed_dict={x: mnist.test.images, y_: mnist.test.labels})
loss_log[i] = sess.run(loss,
feed_dict={x: mnist.test.images, y_: mnist.test.labels})
return acc_log, loss_log
Minibatch training¶
Define train_minibatch
function and implement asynchronous weight updates. The idea is to accummulate gradients across a batch-worth of minibatches, then apply the accummulated gradients to update the parameters. One should not forget to nullify (i.e. set to zero) the gradients when starting on a new batch. Note we set the same random number generator seed as train_standard
. Much of this implementation was taken from this Stack Overflow post.
def train_minibatch(opt_type, learning_rate, image_set, minibatch_size):
# Arrays for logging accuracy and loss
acc_log = np.zeros(len(image_set))
loss_log = np.zeros(len(image_set))
# Create optimizer
opt = opt_type(learning_rate)
#
# minibatch operations
#
# 0) Retrieve trainable variables
tvs = tf.trainable_variables()
# 1) Create placeholders for the accumulating gradients we'll be storing
accum_vars = [tf.Variable(tv.initialized_value(),
trainable=False) for tv in tvs]
# 2) Operation to initialize accum_vars to zero
zero_ops = [tv.assign(tf.zeros_like(tv)) for tv in accum_vars]
# 3) Operation to compute the gradients for one minibatch
gvs = opt.compute_gradients(loss)
# 4) Operation to accumulate the gradients in accum_vars
accum_ops = [accum_vars[i].assign_add(gv[0]) for i, gv in enumerate(gvs)]
# 5) Operation to perform the update (apply gradients)
apply_ops = opt.apply_gradients([(accum_vars[i], tv) for i, tv
in enumerate(tf.trainable_variables())])
# Create session to execute ops
sess = tf.InteractiveSession()
# Necessary initializations
tf.set_random_seed(1234)
tf.global_variables_initializer().run()
# Train loop
for i, batch in enumerate(image_set):
# Make sure gradients are set to 0 before entering minibatch loop
sess.run(zero_ops)
# Loop over minibatches and execute accumulate-gradient operation
for j in range(len(image_set) / minibatch_size):
sess.run(accum_ops,
feed_dict={x: batch[0][j*minibatch_size:(j+1)*minibatch_size],
y_: batch[1][j*minibatch_size:(j+1)*minibatch_size]})
# Done looping over minibatches. Now apply gradients.
sess.run(apply_ops)
acc_log[i] = sess.run(accuracy,
feed_dict={x: mnist.test.images, y_: mnist.test.labels})
loss_log[i] = sess.run(loss,
feed_dict={x: mnist.test.images, y_: mnist.test.labels})
#print("in iteration {}".format(i), sess.run(accum_vars))
return acc_log, loss_log
main function¶
We are almost there! Let's now define our main function that does the comparison between train_standard
and train_minibatch
methods. Here we define a set of optimizers, try the comparison for each optimizer independently. We use the network's loss and accuracy as a comparison metric.
def compare(batch_size, minibatch_size, n_iterations):
# Define optimizers (type, learning rate, and name) to be compared
options = { tf.train.GradientDescentOptimizer : (0.03, "SGD"),
tf.train.AdagradOptimizer : (0.001, "Adagrad"),
tf.train.AdamOptimizer : (0.001, "Adam"),
tf.train.RMSPropOptimizer : (0.0001,"RMSProp")
}
# Load a fixed set of images to run the training on
image_set = get_images(batch_size=batch_size, n_iterations=n_iterations)
# Loop over optimizers to compare
for opt_type, (lr,name) in options.iteritems():
# Canvas making
f, (ax0,ax1) = plt.subplots(1,2,figsize=(16,4),sharey=False,facecolor='w')
f.suptitle('{} Batch {}'.format(name,batch_size), fontsize=20, fontname="Georgia")
# accuracy plot
ax0.set_ylabel("accuracy",fontsize=20,fontname="Georgia")
ax0.set_xlabel("iterations",fontsize=20,fontname="Georgia")
# loss plot
ax1.set_ylabel("loss",fontsize=20,fontname="Georgia")
ax1.set_xlabel("iterations",fontsize=20,fontname="Georgia")
# "standard" training first
acc_log, loss_log = train_standard (opt_type=opt_type,
learning_rate=lr,
image_set=image_set)
ax0.plot(acc_log, 'r.-', label="No minibatch")
ax1.plot(loss_log, 'r.-', label="No minibatch")
# "minibatch" training second
acc_log, loss_log = train_minibatch (opt_type=opt_type,
learning_rate=lr,
image_set=image_set,
minibatch_size=minibatch_size)
ax0.plot(acc_log, 'b', label="Minibatch {}".format(minibatch_size))
ax1.plot(loss_log,'b', label="Minibatch {}".format(minibatch_size))
# Show
ax0.grid()
ax1.grid()
ax0.legend(loc=4,fontsize=16)
ax1.legend(loc=3,fontsize=16)
plt.show()
Test 0¶
It is important to demonstrate that this implementation for ONE minibatch is equivalent to the no-minibatch (i.e. standard) implementation. To perform this test, we set minibatch_size
and batch_size
the same value.
compare( batch_size = 10,
minibatch_size = 10,
n_iterations = 20)
This looks great = what we expected.
Test 1¶
Next, let's see what happens if we enable the minibatch option by setting minibatch_size
and batch_size
5 and 10, respectively. This means there will be 2 minibatches in the minibatch implementation.
compare( batch_size = 10,
minibatch_size = 5,
n_iterations = 20)
The results are more interesting than the previous test. For AdamOptimizer, it shows two methods are effectively identical. This is what we would expect naturally unless there is a dynamic state of an optimizer, which changed during minibatch loop. It turns out this is the case for the three other optimizers we tested here. So we do expect red and blue not to completely overlap. However, for all those methods, the state shift is designed to help the gradient applications. This is why using minibatches ends up with a better result, i.e. loss curve of minibatch method (blue) almost always resides below no-minibatch method (red).
In this notebook we exercised how to implement minibatches in TensorFlow. You can git clone
this notebook from Ji Won's repository.


- I am 22 years old
- Graduated from ZU with a BA in CS
- I am a bad singer with a horrible voice LOL!
- Am in love wiith astronounts images!
- love Arabic language and aim to participate in it's technical revival
MOHAMMAD ALMOKDAD
HERE ARE A SPRIKLES ABOUT ME!


Our market risk appetite is the total amount of risk exposure we would be willing to support for new business in a particular country.
For foreign exchange earning projects with robust financing structures and strong risk mitigants, we may be able to exceed the market risk appetite specified. We make these decisions on a case by case basis.
A to Z list of country cover policies and indicators
Disclaimer: This information is for guidance only. It may change at any time, and no commitment on our part can be assumed or inferred. The information given in no way commits us to providing cover for a particular contract. The country cover indications are not indicative of the nature of the risks of doing business in any individual country. They should not be taken to mean that doing business in the country in question is risk free, and you should carry out your own due diligence.


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ICO
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PROFILE
{% include tabs_container_contribute.html %}
{% include tabs_container_bounty.html %}
{% include tabs_container_airdrop.html %}
{% include tabs_container_referral.html %}
{% include tabs_container_profile.html %}
{% include iconpack.html %}


{% extends "base.html" %} {% block title %} Here's the latest content generated by Ewe Ebooks' mashups: {% endblock %} {% block main_content %}
{{ output.body }}


We really like to help new players, so if you're interested in either of these card games please send me an e-mail letting us know!
Looking for something we have? Head over to our collections page and send me an e-mail when you find what you are looking for.
Learn MoreWe're always looking to help improve new and existing players. We think it's a great way to grow the community. You can use our form to submit any questions you might have, and you have the option to stay completely anonymous.
Learn MoreBuilds our players have used in competitive and casual atmospheres will be posted here. If you'd like to write for us, please submit an e-mail to<EMAIL_ADDRESS>.
Learn MoreIf you like us and the kind of ideas we are about, please help spread the word. Potential affiliates can e-mail me at<EMAIL_ADDRESS>.
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... have some tangle I(2)oT fun ...
The Trits is a fully transparent, zero-sum and no house-edge casino game designed for the IOTA cryptocurrency. It can be played either by humans and machines. It aims to demonstrate the possibilities of the Tangle, while still being fun and thrill.
The game itself was conceived as a humble honor to the memory of John Forbes Nash Jr and is a cross-breed between a coin pusher and a fidget spinner.
At the beginning, there is a pile of coins in the middle of the spinner. The ultimate aim of the game is to disturb the spinner balance by placing a coin on the spinner arms. However, each coin placement is determined by a throw of a “three-sided dice”.
The spinner loses balance and flips when the number of coins on one side outnumbers the number of coins on any other arm by three. A loss of the spinner balance finishes the game immediately and determines the winning arm. If you had at least one of your coins placed on one winning arm, you are among the winners.
But of course, there is a gotcha. One of the arms belongs to the "evil" Bank and when this arm happens to be the winning arm, the Bank takes it all. The good news is – the Bank uses it solely for funding new games in the future. In other words, the Bank just looks after the progressive jackpot, so you can always have a chance to win back what you might have lost.
Some terms explained first:
Bank – the treasurer of coins lost in previous games, used mostly for adding a bonus to each game. The Bank never participates in the games as a player itself, but it can seed new games.
Initiator (Seeder) – is the player who started the game by placing the first coin
Coin – a single token used in the game
Nominal – the nominal value of one coin in IOTAs. The nominal is set at the very beginning of each game
Total – the total value of all the coins on the table.
Spinner arms – the spinner has three arms (as spinners do) marked by letters F (first), S (second), G (gotcha) and the center marked by I (initial). The G arm belongs to the Bank.
The winning arm – the spinner arm on which the last coin in the game has been placed
Winners – the players who have placed at least one coin on the winning arm
The Winner – the player who has placed the last coin on the winning arm
Game address – each game has a unique IOTA address.
Anybody can start (seed) the game by placing a single coin in the middle (i.e. sending the first IOTA transaction to the empty game address). This sets the nominal and starts the game. The coin will be placed on the I spot in the middle.
The moment a new game is seeded, the bank is obliged to add four or five coins on the I spot. This happens always, unless the Bank balance is too low. The Bank balance is publicly announced.
You play the game by throwing your coins into it (i.e. sending the IOTA transaction with the same nominal value to the game address). The game runs until the difference between the sides with the lowest and highest number of coins reaches exactly 3 (three) coins.
The game is finished at the very moment the last coin which causes the 3-coin difference is placed on the spinner. The side on which the last coin has been placed determines the winning arm.
Note: A game can come to an end also by expiring – games not finished within 24 hours will expire and all the transactions are fully reimbursed.
1) If the winning arm is G, the entire total goes to the Bank
2) If the winning side is F or S, 3 coins (a triple !) are send back to the game seeder.
3) The total* of what is left on the table after 1) and 2) is distributed according to the following rules:
*4) When the total is not divisible, the modulo goes to the Bank
The Trits game is fully transparent - meaning that each game can be completely backtracked by inspecting the IOTA Tangle. The random “three sided dice throw” results are in fact derived deterministically from the Tangle actual state, thus using the Tangle as a kind of pseudo-random number generator with a history.
The Bank maintains the incentives – it keeps the game going. It’s not there to make a profit.
There are always 23 (John Nash's favourite prime number) tables named after biggest cities on which the Trits game can be played, and their status is displayed on the public dashboard. The 24th called Atlanta is a sandbox. The Bank’s role is to keep them all active, if possible, by seeding new games and adding the bonus to thenewly seeded games.
Your odds of winning in The Trits game are equal to the theoretical maximum. The house edge is practically 0%, while the wins at the individual games are reasonably high. Even if you loose, the money is not lost forever, as it can always be won back in future games.
If you have to gamble, this is your safest home.


| Registers : |
| Register | Value | 7 | 6 | 5 | 4 | 3 | 2 | 1 | 0 |
| Accumulator | 00 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| Register B | 00 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| Register C | 00 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| Register D | 00 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| Register E | 00 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| Register H | 00 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| Register L | 00 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| Memory(M) | 00 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
|
| Register | Value | S | Z | * | AC | * | P | * | CY |
| Flag Register | 00 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
|
| Type | Value |
| Stack Pointer(SP) | 0000 |
| Memory Pointer(HL) | 0000 |
| Program Status Word(PSW) | 0000 |
| Program Counter(PC) | 0000 |
| Clock Cycle Counter | 0 |
| Instruction Counter | 0 |
|
| SOD | SID | INTR | TRAP | R7.5 | R6.5 | R5.5 |
| 0 | 0 | 0 | 0 | 0 | 0 | 0 |
|
For SIM instruction
| SOD | SDE | * | R7.5 | MSE | M7.5 | M6.5 | M5.5 |
| 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
|
For RIM instruction
| SID | 17.5 | 16.5 | 15.5 | IE | M7.5 | M6.5 | M5.5 |
| 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
|
| No. Conversion Tool: |


-
real logAdd(real log_a, real log_b)
- logAdd(log_a,log_b) = log(a+b) = log(exp(log_a)+exp(log_b)) but done in a smart way so that if log_a or log_b are large but not their difference the computation works correctly
-
real logSub(real log_a, real log_b)
- logSub(log_a,log_b) = log(a-b)
Documentation
Some simple functions for log operations.
- Author:
- Samy Bengio<EMAIL_ADDRESS>Alphabetic index HTML hierarchy of classes or Java
This page was generated with the help of DOC++.


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| PREV NEXT | FRAMES NO FRAMES |
| Packages that use fsb.explore | |
|---|---|
| ags.graph | |
| fsb.ast | |
| fsb.explore | |
| fsb.parser | |
| fsb.semantics | |
| fsb.semantics.eagerpso | |
| fsb.semantics.empeagerpso | |
| fsb.semantics.naivepso | |
| fsb.semantics.pso | |
| fsb.semantics.sc |
| Classes in fsb.explore used by ags.graph | |
|---|---|
| State
|
|
| Transition
A transition in the transition system, from a source state to a destination state, labeled by the statement executed. |
|
| Vertex
|
| Classes in fsb.explore used by fsb.ast | |
|---|---|
| SBState
|
|
| State
|
|
| Validator
A construct to indicate if a state is an error state or not. |
| Classes in fsb.explore used by fsb.explore | |
|---|---|
| Action
|
|
| Resource
|
|
| SBState
|
|
| SBState.LocalResMap
|
|
| State
|
|
| Transition
A transition in the transition system, from a source state to a destination state, labeled by the statement executed. |
|
| TransitionSystem
|
|
| Validator
A construct to indicate if a state is an error state or not. |
|
| Vertex
|
| Classes in fsb.explore used by fsb.parser | |
|---|---|
| Validator
A construct to indicate if a state is an error state or not. |
| Classes in fsb.explore used by fsb.semantics | |
|---|---|
| Action
|
|
| SBState
|
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| State
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| StateFactory
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| Classes in fsb.explore used by fsb.semantics.eagerpso | |
|---|---|
| Action
|
|
| SBState
|
|
| State
|
|
| StateFactory
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|
| Validator
A construct to indicate if a state is an error state or not. |
| Classes in fsb.explore used by fsb.semantics.empeagerpso | |
|---|---|
| Action
|
|
| SBState
|
|
| State
|
|
| StateFactory
|
|
| Validator
A construct to indicate if a state is an error state or not. |
| Classes in fsb.explore used by fsb.semantics.naivepso | |
|---|---|
| Action
|
|
| SBState
|
|
| State
|
|
| StateFactory
|
|
| Validator
A construct to indicate if a state is an error state or not. |
| Classes in fsb.explore used by fsb.semantics.pso | |
|---|---|
| Action
|
|
| SBState
|
|
| State
|
|
| StateFactory
|
|
| Validator
A construct to indicate if a state is an error state or not. |
| Classes in fsb.explore used by fsb.semantics.sc | |
|---|---|
| Action
|
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| SBState
|
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| State
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| StateFactory
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| Validator
A construct to indicate if a state is an error state or not. |
|
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| PREV NEXT | FRAMES NO FRAMES |


{% extends "layout.html" %} {% from "govuk/components/button/macro.njk" import govukButton %} {% block content %}
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ContainerAccessorTrait
trait ContainerAccessorTrait
Trait ContainerAccessorTrait
Methods
Get manager given its its entity name
Get entity repository given its entity name
Get factory given its its entity name
Get director given its its entity name
Get container service
Get container parameter
Get the entity instance with id $id
Get all entity instances
Save an entity. To ensure the method is simple, the entity will be persisted always
Remove an entity from ORM map.
Details
at line 46
ObjectManager
getObjectManager(
string $entityName)
Get manager given its its entity name
at line 60
EntityRepository
getRepository(
string $entityName)
Get entity repository given its entity name
at line 74
AbstractFactory
getFactory(
string $entityName)
Get factory given its its entity name
at line 88
ObjectDirector
getDirector(
string $entityName)
Get director given its its entity name
at line 102
mixed
get(
string $serviceName)
Get container service
at line 116
mixed
getParameter(
string $parameterName)
Get container parameter
at line 131
mixed
find(
string $entityName,
mixed $id)
Get the entity instance with id $id
at line 145
array
findAll(
string $entityName)
Get all entity instances
at line 160
$this
flush(
mixed $entity)
Save an entity. To ensure the method is simple, the entity will be persisted always
at line 182
$this
clear(
mixed $entity)
Remove an entity from ORM map.


|
MQDS
0.0.1
Molecular Quantum Dynamics and Spectroscopy
|
Module to handle a harmonic-oscillator model for the bath in quantum dynamics simulations. More...
Functions/Subroutines | |
| subroutine | initialize_bath |
| Allocates the necessary arrays to describe the bath and system-bath interactions. Also, the spectral density is uniformly sampled according to frequency-dependent reorganization energy. More... | |
| subroutine | sample_thermal_wigner (x_init, p_init, beta) |
| Sample the initial thermal distribution for harmonic bath from the Wigner transform of the Boltzmann operator. This is under the assumption that the full initil density operator can be written as \( \hat{\rho}_s\hat{\rho}_b^{eq} \). More... | |
| subroutine | finalize_bath |
| real(dp) function, dimension(nbath *nosc) | bilinear_harmonic_force_pldm (x, x_map, p_map, xt_map, pt_map) |
| Calculate bilinear coupling force for PLDM. More... | |
| real(dp) function, dimension(nbath *nosc) | bilinear_harmonic_force_twa (x, x_map, p_map) |
| Calculate the bilinear coupling force for TWA and SQC calculations. More... | |
| real(dp) function, dimension(0 :nbstep) | redfield_bath_correlation_function (sd, w, beta_local) |
| Calculate the harmonic bath correlation function for a bilinearly coupled system-bath model in the Redfield Approximation for 1 ps. More... | |
| subroutine | bath_coupled_to_vibrational_mode (q_init, pq_init, beta) |
| Subroutine to prepare the spectral density that is coupled to an "intramolecular" vibrational mode. More... | |
Variables | |
| real(dp), dimension(:), allocatable | x_bath |
| real(dp), dimension(:), allocatable | p_bath |
| real(dp), dimension(:), allocatable | omega |
| real(dp), dimension(:,:), allocatable | c |
| real(dp), dimension(:,:), allocatable | site_sd |
| real(dp), dimension(:), allocatable | site_reorg |
| real(dp), dimension(:), allocatable | site_bath_freq |
Module to handle a harmonic-oscillator model for the bath in quantum dynamics simulations.
| subroutine harmonic_bath::bath_coupled_to_vibrational_mode | ( | real(dp), dimension(:), intent(inout) | q_init, |
| real(dp), dimension(:), intent(inout) | pq_init, | ||
| real(dp), intent(in) | beta | ||
| ) |
Subroutine to prepare the spectral density that is coupled to an "intramolecular" vibrational mode.
| real(dp) function, dimension(nbath*nosc) harmonic_bath::bilinear_harmonic_force_pldm | ( | real(dp), dimension(nbath*nosc), intent(in) | x, |
| real(dp), dimension(nstate), intent(in) | x_map, | ||
| real(dp), dimension(nstate), intent(in) | p_map, | ||
| real(dp), dimension(nstate), intent(in) | xt_map, | ||
| real(dp), dimension(nstate), intent(in) | pt_map | ||
| ) |
Calculate bilinear coupling force for PLDM.
| real(dp) function, dimension(nbath*nosc) harmonic_bath::bilinear_harmonic_force_twa | ( | real(dp), dimension(nbath*nosc), intent(in) | x, |
| real(dp), dimension(nstate), intent(in) | x_map, | ||
| real(dp), dimension(nstate), intent(in) | p_map | ||
| ) |
Calculate the bilinear coupling force for TWA and SQC calculations.
| subroutine harmonic_bath::finalize_bath | ( | ) |
| subroutine harmonic_bath::initialize_bath | ( | ) |
Allocates the necessary arrays to describe the bath and system-bath interactions. Also, the spectral density is uniformly sampled according to frequency-dependent reorganization energy.
Note: This is restricted to a single range and discretization of frequencies (defined by a single dw)
Sample bath according to the method described by Wang et al JCP 110, 4828 (1999)
Writes a log of sampled modes into a file called "sampledbath.log"
| real(dp) function, dimension(0 : nbstep) harmonic_bath::redfield_bath_correlation_function | ( | real(dp), dimension(:), intent(in) | sd, |
| real(dp), dimension(:), intent(in) | w, | ||
| real(dp), intent(in) | beta_local | ||
| ) |
Calculate the harmonic bath correlation function for a bilinearly coupled system-bath model in the Redfield Approximation for 1 ps.
| subroutine harmonic_bath::sample_thermal_wigner | ( | real(dp), dimension(nbath*nosc), intent(out) | x_init, |
| real(dp), dimension(nbath*nosc), intent(out) | p_init, | ||
| real(dp), intent(in) | beta | ||
| ) |
Sample the initial thermal distribution for harmonic bath from the Wigner transform of the Boltzmann operator. This is under the assumption that the full initil density operator can be written as \( \hat{\rho}_s\hat{\rho}_b^{eq} \).
| real(dp), dimension(:,:), allocatable harmonic_bath::c |
| real(dp), dimension(:), allocatable harmonic_bath::omega |
| real(dp), dimension(:), allocatable harmonic_bath::p_bath |
| real(dp), dimension(:), allocatable harmonic_bath::site_bath_freq |
| real(dp), dimension(:), allocatable harmonic_bath::site_reorg |
| real(dp), dimension(:,:), allocatable harmonic_bath::site_sd |
| real(dp), dimension(:), allocatable harmonic_bath::x_bath |


---
layout: post
title: time of debian for my little nslu2 time of
date: '2008-09-01T00:17:00+02:00'
tags:
- photo
- nslu2
- slug
- debian
- debianslug
- lenny
- armel
- arm
- linux
- gnu
- photomadebyme
tumblr_url: http://blog.alezzandro.com/post/48194885/time-of-debian-for-my-little-nslu2-time-of
---
Time of Debian for my little nslu2..
Time of Armel!
EABI is the new “Embedded” ABI by ARM ltd. EABI is actually a family of ABI’s and one of the “subABIs” is GNU EABI, for Linux. The effective changes for users are:
Floating point performance, with or without an FPU is very much faster, and mixing soft and hardfloat code is possible
A more efficient syscall convention


Our 3D printers took a while to get working, but now that they are working printing out 3D models is super easy. In the near future, students will be able to request their own prints for a small price.
Models can be found on Thingiverse or designed in a CAD suite such as Fusion 360 or Tinkercad. Thingiverse is a site containing thousands of downloadable 3D models that can be printed in the shop.


Blogs
Cultural Blogs
DBC feelings
My Thinking Style
Biggest Problem in the Tech Industry
Feedback
Stereotype Threat
Stop Stereotype Threat
Conflict
Technical Blogs
Git Me
Positioning
Arrays and Hashes
Map
Ruby Class
Variable Scope
Ruby Hash VS JavaScript Object
What is Rails?
Contact Me at<EMAIL_ADDRESS>Back


Commons LangThe standard Java libraries fail to provide enough methods for manipulation of its core classes. Apache Commons Lang provides these extra methods. Lang provides a host of helper utilities for the java.lang API, notably String manipulation methods, basic numerical methods, object reflection, concurrency, creation and serialization and System properties. Additionally it contains basic enhancements to java.util.Date and a series of utilities dedicated to help with building methods, such as hashCode, toString and equals. Note that Lang 3.0 (and subsequent versions) use a different package (org.apache.commons.lang3) than the previous versions (org.apache.commons.lang), allowing it to be used at the same time as an earlier version. DocumentationThe package descriptions in the Javadoc give an overview of the available features and various project reports are provided. The Javadoc API documents are available online:
The git repository can be browsed, or you can browse/contribute via GitHub. Release InformationThe latest stable release of Lang is 3.8.1. You may:
Alternatively you can pull it from the central Maven repositories: <dependency> <groupId>org.apache.commons</groupId> <artifactId>commons-lang3</artifactId> <version>3.8.1</version> </dependency> For information on previous releases see the Release History, and to download previous releases see the Commons Lang Archive. Getting InvolvedThe commons developer mailing list is the main channel of communication for contributors. Please remember that the lists are shared between all commons components, so prefix your email by [lang]. You can also visit the #apache-commons IRC channel on irc.freenode.net or peruse JIRA. Specific links of interest for JIRA are:
Alternatively you can go through the Needs Work tags in the TagList report. If you'd like to offer up pull requests via GitHub rather than applying patches to JIRA, we have a GitHub mirror. SupportThe commons mailing lists act as the main support forum. The user list is suitable for most library usage queries. The dev list is intended for the development discussion. Please remember that the lists are shared between all commons components, so prefix your email by [lang]. Bug reports and enhancements are also welcomed via the JIRA issue tracker. Please read the instructions carefully. |


{% extends "install/download.html" %} {% block branchingContent %}
Create a folder called projects in your Documents folder.
{% endblock %} {% block branchingContentTwo %}Open that folder by double clicking on it. You should then see another folder named nhsuk-prototype-kit followed by the version number.
{% endblock %} {% block branchingContentThree %} {% endblock %} {% block branchingContentFour %} {% endblock %} {% block pagination %} {{ pagination({ "previousUrl": "/docs/install/windows/text-editor", "previousPage": "Step 3: HTML text editor", "nextUrl": "/docs/install/windows/open", "nextPage": "Step 5: Go to your prototype" }) }} {% endblock %}


--- title: Buckinghamshire Healthcare NHS Trust layout: gb ---
| Resource | Fetch | Format | Columns | Data | Valid | Entries | Oldest | Latest | Total (GBP) | |
|---|---|---|---|---|---|---|---|---|---|---|
| Spend over £25000 in buckinghamshire healthcare nhs trust | ||||||||||
| 2011 February return | ✘ | ✘ | ✘ | ✘ | ✘ | 0 | ||||
| Spend over £25,000 in Buckinghamshire Healthcare NHS Trust | ||||||||||
| 2010 July Return | ✘ | ✘ | ✘ | ✘ | ✘ | 0 | ||||
| 2010 November Return | ✘ | ✘ | ✘ | ✘ | ✘ | 0 | ||||
| 2010 April Return | ✔ | ✘ | ✘ | ✘ | ✘ | 0 | ||||
| 2010 June Return | ✘ | ✘ | ✘ | ✘ | ✘ | 0 | ||||
| 2010 October Return | ✘ | ✘ | ✘ | ✘ | ✘ | 0 | ||||
| 2010 August Return | ✘ | ✘ | ✘ | ✘ | ✘ | 0 | ||||
| 2010 September Return | ✘ | ✘ | ✘ | ✘ | ✘ | 0 | ||||
| 2010 May Return | ✘ | ✘ | ✘ | ✘ | ✘ | 0 | ||||
| Spend over £25,000 in Buckinghamshire Healthcare NHS Trust | ||||||||||
| 2010 December Return | ✘ | ✘ | ✘ | ✘ | ✘ | 0 | ||||
| Spend over £25,000 in Buckinghamshire Healthcare NHS trust | ||||||||||
| 2011 November Return | ✘ | ✘ | ✘ | ✘ | ✘ | 0 | ||||
| 2011 September Return | ✘ | ✘ | ✘ | ✘ | ✘ | 0 | ||||
| 2011 July Return | ✘ | ✘ | ✘ | ✘ | ✘ | 0 | ||||
| 2011 January return | ✘ | ✘ | ✘ | ✘ | ✘ | 0 | ||||
| 2011 August Return | ✘ | ✘ | ✘ | ✘ | ✘ | 0 | ||||
| 2011 April return | ✘ | ✘ | ✘ | ✘ | ✘ | 0 | ||||
| 2011 December Return | ✘ | ✘ | ✘ | ✘ | ✘ | 0 | ||||
| 2011 October Return | ✘ | ✘ | ✘ | ✘ | ✘ | 0 | ||||
| 2011 June Return | ✘ | ✘ | ✘ | ✘ | ✘ | 0 | ||||
| 2011 May return | ✘ | ✘ | ✘ | ✘ | ✘ | 0 |
| Resource/Stage | Error | |
| 2010 April Return | ||
| extract | HTML file detected |


Please check the XStream - Quick start tutorial. The only difference is in the line with the initialization:
XStream xStream = new XStream(new JsonHierarchicalStreamDriver());
The output is as follows:
{"contact": { "name": "Cristian Sulea", "addresses": [ { "street": "My Street", "city": "Bucharest" }, { "street": "Another Street", "city": "Bucharest" } ] }}
The output is as follows:
Sometimes the root node in the generated JSON is superfluous, since its name is caused by the Java type of the written object that has no meaning in JSON
and increases only the nesting level of the structure.
Therefore it is possible to drop this root by initializing the internally used JsonWriter
in a different mode.
Again, the only difference is in the initialization:
XStream xStream = new XStream(new JsonHierarchicalStreamDriver() { public HierarchicalStreamWriter createWriter(Writer writer) { return new JsonWriter(writer, JsonWriter.DROP_ROOT_MODE); } });
The output is as follows:
{ "name": "Cristian Sulea", "addresses": [ { "street": "My Street", "city": "Bucharest" }, { "street": "Another Street", "city": "Bucharest" } ] }
Contact contact = (Contact) xStream.fromXML(json);


Contact Me
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© 2136 Elizabeth Fust


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Reference/Function
Contents |
Functions
A function takes its argument on the right.
Syntax
The canonical form of the right argument is a semicolon-delimited list of parameters given in brackets:
- f[a1;a2;...;an]
Note that the expression in brackets gives n parameters to the function, but is not itself a q list, i.e. it is not the same as:
- (a1;a2;...;an)
Where a function takes only a single parameter, the brackets are not needed, so the following are the same:
- f[a1]
- f a1
Where a function takes no parameter, it can be called with empty brackets, or given an argument which is ignored:
- f[]
- f a1 / a1 is ignored
Action on Lists
Functions can be atomic, aggregate or uniform (or none of these):
- an atomic function returns an atom for each atom in its argument
- an aggregate function returns an atom from a list
- a uniform function returns a list from a list
For example:
q)signum 0 2 -3 5 / atomic 0 1 -1 1 q)sum 2 3 5 7 / aggregate 17 q)sums 2 3 5 7 / uniform 2 5 10 17 q)distinct 2 3 5 7 2 5 / none of the above 2 3 5 7
Definition
A function is created by assignment, in one of two ways:
- as an explicit definition, given as a list of statements in matching braces
- using q functional forms: adverbs and function projection
Explicit Definition
An explicit definition has a list of statements, separated by semi-colons, and enclosed in matching braces, { }. The arguments to the definition can optionally be named, as a list in square brackets, [ ]. If the arguments are not so named, then names x, y and z refer to the first three arguments. The format is:
- f:{[p1;...;pm]e1;...;en}
where the optional [p1;...;pm] are named arguments, and e1;...;en is a sequence of expressions to be evaluated.
A function can be defined and used without giving it a name, for example:
q){10+3*x} 1 2 3 13 13 16 19 49
The result of the function is the result of the last statement evaluated. If the last statement is empty, the result is the generic null (which is not displayed):
q)f:{2*x;} / last statement is empty q)f 10 / no result shown q)(::)~f 10 / matches generic null 1b
Return and Signal
Return and signal end execution early:
- return ends successfully
- signal aborts execution (after an error)
To terminate and return a value, use assignment : with no name to the left.
q)f:{a:3*x;:a;a+10} / the final a+10 is never executed q)f 1 3
To abort function execution, use signal ' with an error message to its right:
q)f:{a:3*x;'"end here";a+10} / the final a+10 is never executed q)f 1 'end here 10
Local and Global
Names assigned with : are local to the definition, and names assigned with :: are global:
q)a:b:0 / set (global) a and b to 0 q)f:{a:10+3*x;b::100+a;} / f defines local a, global b q)f 1 2 3 / run f q)a / global a is unchanged 0 q)b / global b is updated 113 116 119
A local variable exists only from the time it is first assigned. A name referenced that is not a local variable, is searched for globally:
q)a:100 / assign global a q)f:{a+x} / f references a q)f 1 2 3 101 102 103
Conditional Evaluation
Functions $ and ? allow conditional evaluation, see:
Control Words
Functions if, do and while control the order of execution, see:
Functional Forms
A function can also be defined from one of two functional forms: adverbs and function projection.
For adverbs, see adverbs.
Function projection occurs when a function or verb is given only a subset of its arguments - this results in a new function whose arguments are those not yet given. For example, this is useful when a function is to be called repeatedly with some of its arguments unchanged:
q)f:{x + 2 * y - z} / f takes 3 arguments q)f[100;10;2 3 5] 116 114 110 q)g:f[100] / g is projection of f on first argument q)g[10;2 3 5] / g takes 2 arguments 116 114 110 q)g:f[100;;2 3 5] / project on first and third arguments q)g 10 / g now takes 1 argument 116 114 110


--- layout: page title: "About" description: "This is what I do." header-img: "img/saturn-bg2.jpg" ---
My name is Abhishek Srivastava. I am a technologist. I live and work in Seattle WA. I love working on Scala technologies and specialize in Data processing, Analytics, and APIs. You can get in touch with me on twitter. My handle is @abhishes


Class AssetType
Asset types enum - used to identify type of assets.
This is not really necessary in C#, but exists to match the definition in the CPP side of it.
Inheritance
System.Object
AssetType
Namespace: BonEngineSharp.Defs
Assembly: BonEngineSharp.dll
Syntax
public sealed class AssetType : Enum
Fields
_Count
How many asset types we got.
Declaration
public const AssetType _Count
Field Value
| Type | Description |
|---|---|
| AssetType |
Config
Configuration file asset.
Declaration
public const AssetType Config
Field Value
| Type | Description |
|---|---|
| AssetType |
Effect
Effect asset, used to draw sprites with special effects.
Declaration
public const AssetType Effect
Field Value
| Type | Description |
|---|---|
| AssetType |
Font
Font asset, used to draw text.
Declaration
public const AssetType Font
Field Value
| Type | Description |
|---|---|
| AssetType |
Image
An image asset we can use for rendering.
Declaration
public const AssetType Image
Field Value
| Type | Description |
|---|---|
| AssetType |
Music
A long soundtrack asset, used for music.
Declaration
public const AssetType Music
Field Value
| Type | Description |
|---|---|
| AssetType |
Sound
Sound effect asset we can play as short sounds.
Declaration
public const AssetType Sound
Field Value
| Type | Description |
|---|---|
| AssetType |
value__
Declaration
public int value__
Field Value
| Type | Description |
|---|---|
| System.Int32 |


This isn't so much a bug as it is a tweak. In the plugins menu, when you mouse over a link, the highlight is too white and doesn't let you read the text. Not major, but it is there. This is on the BF4 side by the way.
BrainFooLong
Administrator
GameFreakBoy wrote:
This isn't so much a bug as it is a tweak. In the plugins menu, when you mouse over a link, the highlight is too white and doesn't let you read the text. Not major, but it is there. This is on the BF4 side by the way.


Reports calls to any super method from inner or anonymous class if a method with the identical signature exists in the surrounding class.
In this case it's easy to miss the super method and suggest that the call is referenced to method in the surrounding class.
To clarify the intent it is recommended to add an explicit super
qualifier to the method call.
Example:
class Parent {
void ambiguous(){}
}
class Example {
void ambiguous(){}
class Inner extends Parent {
void example(){
ambiguous(); //warning
}
}
}
The quick-fix adds an explicit super
qualifier to the method call:
super.ambiguous();


Thermostat
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Reset button
Current Temperature in
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Saving Mode
Turn off Saving Mode
Get Current Temperature
PowerSavingMode ON
Energy Usage


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Brewing
Thoughts on Brewing
Saison
Dave's Porter
Hefeweizen Mastery
A ProMash Recipe Report
Distilled Water vs 50ppm Calcium Chloride
Distilled Water Base Malt Conversion Test


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YSC1212 Introduction to CS
YSC3232 Object-Oriented Programming
YSC3226 Designing Interactive Systems
Olivier Danvy
Aquinas Hobor
Simon Perrault


Package com.jme.shadow
Class ShadowUtil
- java.lang.Object
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- com.jme.shadow.ShadowUtil
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public class ShadowUtil extends java.lang.Object
Includes various useful shadow mapping functions. See for more info.
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Nested Class Summary
Nested Classes Modifier and Type Class Description static class
ShadowUtil.OccludersExtractor
OccludersExtractor is a helper class to collect splitOccluders from scene recursively.
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Constructor Summary
Constructors Constructor Description ShadowUtil()
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Method Summary
All Methods Static Methods Concrete Methods Modifier and Type Method Description static BoundingBox
computeBoundForPoints(Vector3f[] pts, Matrix4f mat)
Compute bounds from an array of pointsstatic BoundingBox
computeBoundForPoints(Vector3f[] pts, Transform transform)
Compute bounds from an array of pointsstatic BoundingBox
computeUnionBound(GeometryList list, Matrix4f mat)
Compute bounds of a geomListstatic BoundingBox
computeUnionBound(GeometryList list, Transform transform)
Compute bounds of a geomListstatic BoundingBox
computeUnionBound(java.util.List<BoundingVolume> bv)
Computes the bounds of multiple bounding volumesstatic void
getGeometriesInCamFrustum(GeometryList inputGeometryList, Camera camera, GeometryList outputGeometryList)
Populates the outputGeometryList with the geometry of the inputGeometryList that are in the frustum of the given camerastatic void
getGeometriesInCamFrustum(Spatial rootScene, Camera camera, RenderQueue.ShadowMode mode, GeometryList outputGeometryList)
Populates the outputGeometryList with the rootScene children geometries that are in the frustum of the given camerastatic void
getGeometriesInLightRadius(GeometryList inputGeometryList, Camera[] cameras, GeometryList outputGeometryList)
Populates the outputGeometryList with the geometry of the inputGeometryList that are in the radius of a light.static void
getLitGeometriesInViewPort(Spatial rootScene, Camera vpCamera, Camera[] cameras, RenderQueue.ShadowMode mode, GeometryList outputGeometryList)
Populates the outputGeometryList with the geometries of the children of OccludersExtractor.rootScene node that are both in the frustum of the given vpCamera and some camera inside cameras array.static void
updateFrustumPoints(Camera viewCam, float nearOverride, float farOverride, float scale, Vector3f[] points)
Updates the points array to contain the frustum corners of the given camera.static void
updateFrustumPoints2(Camera viewCam, Vector3f[] points)
Updates a points arrays with the frustum corners of the provided camera.static void
updateShadowCamera(Camera shadowCam, Vector3f[] points)
Updates the shadow camera to properly contain the given points (which contain the eye camera frustum corners)static void
updateShadowCamera(ViewPort viewPort, GeometryList receivers, Camera shadowCam, Vector3f[] points, GeometryList splitOccluders, float shadowMapSize)
Updates the shadow camera to properly contain the given points (which contain the eye camera frustum corners) and the shadow occluder objects collected through the traverse of the scene hierarchy
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Method Detail
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updateFrustumPoints2
public static void updateFrustumPoints2(Camera viewCam, Vector3f[] points)
Updates a points arrays with the frustum corners of the provided camera.- Parameters:
viewCam
-points
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updateFrustumPoints
public static void updateFrustumPoints(Camera viewCam, float nearOverride, float farOverride, float scale, Vector3f[] points)
Updates the points array to contain the frustum corners of the given camera. The nearOverride and farOverride variables can be used to override the camera's near/far values with own values. TODO: Reduce creation of new vectors- Parameters:
viewCam
-nearOverride
-farOverride
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computeUnionBound
public static BoundingBox computeUnionBound(GeometryList list, Transform transform)
Compute bounds of a geomList- Parameters:
list
-transform
-- Returns:
- a new instance
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computeUnionBound
public static BoundingBox computeUnionBound(GeometryList list, Matrix4f mat)
Compute bounds of a geomList- Parameters:
list
-mat
-- Returns:
- a new instance
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computeUnionBound
public static BoundingBox computeUnionBound(java.util.List<BoundingVolume> bv)
Computes the bounds of multiple bounding volumes- Parameters:
bv
-- Returns:
- a new instance
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computeBoundForPoints
public static BoundingBox computeBoundForPoints(Vector3f[] pts, Transform transform)
Compute bounds from an array of points- Parameters:
pts
-transform
-- Returns:
- a new instance
-
computeBoundForPoints
public static BoundingBox computeBoundForPoints(Vector3f[] pts, Matrix4f mat)
Compute bounds from an array of points- Parameters:
pts
-mat
-- Returns:
- a new BoundingBox
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updateShadowCamera
public static void updateShadowCamera(Camera shadowCam, Vector3f[] points)
Updates the shadow camera to properly contain the given points (which contain the eye camera frustum corners)- Parameters:
shadowCam
-points
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updateShadowCamera
public static void updateShadowCamera(ViewPort viewPort, GeometryList receivers, Camera shadowCam, Vector3f[] points, GeometryList splitOccluders, float shadowMapSize)
Updates the shadow camera to properly contain the given points (which contain the eye camera frustum corners) and the shadow occluder objects collected through the traverse of the scene hierarchy
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getGeometriesInCamFrustum
public static void getGeometriesInCamFrustum(GeometryList inputGeometryList, Camera camera, GeometryList outputGeometryList)
Populates the outputGeometryList with the geometry of the inputGeometryList that are in the frustum of the given camera- Parameters:
inputGeometryList
- The list containing all geometries to check against the camera frustumcamera
- the camera to check geometries againstoutputGeometryList
- the list of all geometries that are in the camera frustum
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getGeometriesInCamFrustum
public static void getGeometriesInCamFrustum(Spatial rootScene, Camera camera, RenderQueue.ShadowMode mode, GeometryList outputGeometryList)
Populates the outputGeometryList with the rootScene children geometries that are in the frustum of the given camera- Parameters:
rootScene
- the rootNode of the scene to traversecamera
- the camera to check geometries againstoutputGeometryList
- the list of all geometries that are in the camera frustum
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getGeometriesInLightRadius
public static void getGeometriesInLightRadius(GeometryList inputGeometryList, Camera[] cameras, GeometryList outputGeometryList)
Populates the outputGeometryList with the geometry of the inputGeometryList that are in the radius of a light. The array of camera must be an array of 6 cameras initialized so they represent the light viewspace of a pointlight- Parameters:
inputGeometryList
- The list containing all geometries to check against the camera frustumcameras
- the camera array to check geometries againstoutputGeometryList
- the list of all geometries that are in the camera frustum
-
getLitGeometriesInViewPort
public static void getLitGeometriesInViewPort(Spatial rootScene, Camera vpCamera, Camera[] cameras, RenderQueue.ShadowMode mode, GeometryList outputGeometryList)
Populates the outputGeometryList with the geometries of the children of OccludersExtractor.rootScene node that are both in the frustum of the given vpCamera and some camera inside cameras array. The array of cameras must be initialized to represent the light viewspace of some light like pointLight or spotLight- Parameters:
rootScene
-vpCamera
- the viewPort cameracameras
- the camera array to check geometries against, representing the light viewspaceoutputGeometryList
- the output list of all geometries that are in the camera frustum
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m/d/y
nn-nnnn
Drop Timing HTML Exports Here (anything in yellow is editable, and stuff cleans up for printing)
X
Y.yy
Z.zz
Add invoice level items here (ex: Tax 6%, Shipping $22, Coupon -$50, Discount -10%)
T.xx


Since the Culture's biological population commonly live as long as 400 years and have no need to work, they face the difficulty of giving meaning to their lives when the Minds and other intelligent machines can do almost anything better than the biological population can. Many try—few successfully—to join Contact, the Culture's combined diplomatic / military / government service, and fewer still are invited to the even more elite Special Circumstances (SC), Contact's secret service and special operations division. Normal Culture citizens vicariously derive meaning from their existence via the works of Contact and SC.
Banks described the Culture as
"some incredibly rich lady of leisure who does good, charitable works...

The same need to find a purpose for existence led the Culture as a whole to embark voluntarily on its only full-scale war, to stop the expansion of the theocratic and militaristic Idirans—otherwise the Culture's economic and technological advancement would have been a pointless exercise in hedonism.
All of the stories feature the tension between the Culture's humane, anarcho-communist ideals and its need to intervene in the affairs of less enlightened and often less advanced civilisations. The first Culture novel, Consider Phlebas, describes an episode in the Idiran War, which the Culture's Minds foresaw would cause billions of deaths on both sides, but which their utilitarian calculations predicted would be the best course in the long term. The Idiran War serves as a recurring reference point in most of the subsequent novels, influencing the Culture's development for centuries and dividing its residents—both humanoids and AI Minds—along the pacifist and interventionist ideals.
In subsequent novels, the Culture—particularly SC and, to a lesser degree, Contact—continue to employ subterfuge, espionage, and even direct action (collectively called "dirty tricks") in order to protect itself and spread the Culture's "good works" and ideals.  Though each of these individual actions would horrify the average Culture citizen, the Culture's Minds tend to justify these actions in terms of lives saved in the long-term, perhaps over the course of several hundred years. The Culture is willing to use not only preemptive, but also retaliatory actions in order to deter future hostile actions against itself. Banks commented that in order to prevent atrocities, "even the Culture throws away its usual moral rule-book." Andrew M. Butler noted that, "Having established the peaceful, utopian, game-playing tendencies of the Culture, ... in later volumes the Culture’s dirty tricks are more exposed."
The Culture stories have been described as "eerily prescient". Consider Phlebas explicitly presents a clash of civilizations, although this phrase was used by Samuel P. Huntington and earlier authors. This is highlighted by the novel's description of the Idirans' expansion as a "jihad" and by its epigraphic verse from the Koran, "Idolatry is worse than carnage". However, it was as much a "holy war" from the Culture's point of view. Throughout the series, Contact and Special Circumstances show themselves willing to intervene, sometimes forcefully, in other civilizations to make them more Culture-like.
Much of Look to Windward is a commentary on the Idiran-Culture war, from a viewpoint 800 years later, mainly reflecting grief over both personal and large-scale losses and guilt over actions taken in the war. It combines these with similar reflections on the catastrophic miscarriage of the Culture's attempt to dissolve the Chelgrians' oppressive caste system. In neither case, however, does distress over the consequences of Culture policy lead its representatives to reject that policy. The book illustrates the limitations of power, and also points out that Minds and other AIs are as vulnerable as biological persons to grief, guilt and regrets.


This plugin is an ROR extension to support enumerations in the database schema using the enum type in MySQL or column constraints in other databases. Currently only MySQL has been implemented, but other connection adapters can easily be extended to check for column constraints and then parse out the possible values.
This makes it very easy to implement and maintain controlled vocabularies in the database schema without having to change the validations and the view. I have made an effort to make the modifications without modifying the core classes, but I have not been extreamly successful. I have had to make some modifications that are version dependent and then put some exception handlers to make the backward compatible.
This is not the ideal solution and could cause some performance issues in the helpers. The core code still works with both 1.1 and 1.2 without modification.
To install using the plugin script:
script/plugin install enum-column
To manually install using Subversion, do the following. In your vendor/plugins
directory,
type the following:
svn checkout svn://rubyforge.org/var/svn/enum-column
Otherwize download the latest zip or tarball and unpack it in your vendor/plugins
directory.
When you create your schema, specify the constraint as a limit:
create_table :enumerations, :force => true do |t| t.column :severity, :enum, :limit => [:low, :medium, :high, :critical], :default => :medium t.column :color, :enum, :limit => [:red, :blue, :green, :yellow] ... end
You can then automatically validate this column using:
validates_columns :severity, :color
The rest will be handled for you. All enumerated values will be given as symbols.
@e = Enumeration.new @e.severity = :low
In the controller:
@e = Enumeration.new
The enumerates list of values will be specified as follows:
<%= input 'e', 'severity' %>
Will create a select/option list:
<select id="e_severity" name="e[severity]"> <option value="low">low</option> <option value="medium" selected="selected">medium</option> <option value="high">high</option> <option value="critical">critical</option> </select>
You can also create a set of radio buttons using the following helper:
<%= enum_radio('e', 'severity') %=>
Will produce the following group of radio buttons:
low: <input id="test_severity_low" name="test[severity]" type="radio" value="low" /> medium: <input checked="checked" id="test_severity_medium" name="test[severity]" type="radio" value="medium" /> high: <input id="test_severity_high" name="test[severity]" type="radio" value="high" /> critical: <input id="test_severity_critical" name="test[severity]" type="radio" value="critical" />
You can always use the column reflection to get the list of possible values from the database column.
Enumeration.columns_hash['color'].values Will yield: [:red, :blue, :green, :yellow]


CASE STUDY
Category
UX/UI Design
Whole recipes is a mobile aplication concept that combines dietary needs with day-to-day requirements to offer a selection of recipes completely adapted to any moment. Users can look for a recipe according to their preferences, and follow a step-by-step guide supported with a short video to prepare the meal.
WHAT WE ALREADY KNOW
Here we have some important facts regarding how dietary habits are changing in Spain.
Plant-based diets are growing across the entire world, and indeed in Spain.
Around an 8% of the spanish population over the age of 18 years consider themselves as flexitarians.
The number of vegan people has exponentially increased over the past years.
The number of celiacs diagnosed in Spain increases a 15% per year.
Feeding intolerance has become a public health problem that affects more than two million people in Spain.
RESEARCH
The research was based on surveys, interviews and investigation about dietary problems, behaviors and users needs. Before conducting the interviews, I listed out potential questions that may be asked during the session. These questions were centered on the following topics.
Over 65 people participated and their answers stablished a key pattern to bring the research to the next stage. More than 25% of the people had a disease or a special dietary requirement, the majority were concerned about food and already used tools to help themselves improve their habits.
Analyzing the research results some patterns and pain points came to light:
Users feel frustated because dietary needs limit the access to all kind of recipes.
They want to eat well and have good habits but the lack of time and habits already acquired make them fall into routine.
users are interested in searching for recipes but sometimes they find difficult to put it into practice because they don't understand the cooking process and these recipes have a lot of ingredients hard to find in the closest supermarket.
The lack of ideas is a big matter, they need a clear guidance where to start. Simplicity wins.
USER PERSONA
Based on the the previous research, we can introduce Lucía. She is 32, lives in Madrid and works full time in an advertising agency as an Email Marketing Manager. She is a woman of firm beliefs who cares for her feed and has been following a veggie diet for ten years. Lucía usually cooks at home and brings her meal to work, this way ensures eating well and saves money. But it's not always like that, sometimes she finds difficult to eat healthier because overwork and the lack of time and ideas makes her have a poorly balanced diet and fall into a feed routine.
DEFINING THE PROBLEM: problem statement
At this point, the problem has already arisen. Lucía, that follows a specific diet and usually cooks at home, needs new and fresh recipe ideas, not very complex and with easy to find ingredients, so eating a healthful diet according to her preferences becomes easier.
SOLVING THE PROBLEM: solving statement
The idea is to provide recipes completely adapted to the user on a mobile application because it's easier to use in the kitchen. The user needs to be at the beginning of the research process, taking decisions to avoid future frustations. These decisions will include selecting restricted ingredients and choosing dietary needs when signing up. Also, when preparing the meal, users can filter by level of difficulty of the recipe, time available for cooking and ingredients on hand, so the app can display an accurate research according to their current needs.
INFORMATION ARCHITECTURE
In order to understand how a user interacts with the app to perform tasks, let's illustrate the sitemap. It was esential to keep it simple, as if the user had used it before. To achieve this goal a deep navigation was avoided, and the focus was placed on the main feature: look for recipes that match the dietary needs and preferences of the user.
WIREFRAMES
The next step was to create low-fidelity wireframes of the app in order to be able to test with users the sooner the better, and have feedback of the whole process done so far. The fedback received in the session was very useful to simplify the flow and to avoid distractinfg elements that weren't essential for the MVP that was being created. This process allowed me to move formard to the next step, to develop a high-fidelity prototye.
HIGH-FIDELITY PROTOTYPE
This high-fidelity prototype based on the feedback received helped me and the users to have a better idea of the actual imagery. At this point, a new test was conducted and this time, I gathered more positive feedback. It's always good to test changes and have new feedback that will make the project go in the right direction.
SIGN UP WORKFLOW
The user can choose either to sign up in the app or not. If decides to do it, the app will ask which type of diet is following to avoid those ingredients in the suggested recipes. The app will also ask if there's any extra ingredient that the user wants to avoid. these preferences will automatically be saved and could be changed at any time from the profile area.
SEARCH TOOL & FAVOURITES WORKFLOW
The home screen provides a clear direction where to start. And the search tool is located here. All kind of suggestion are displayed according to the preferences that the user set up when siging up. If the user didn't do the enrollment the home screen will show up recipes based on most popular categories, best rated or random occasions.
The user can search for recipes quickly and easy and get relevant results using auto complete but even more, he can refine the search using the filters. The level of the recipe can be set up here, the time available for cooking and the ingredients that the recipe should include because the user has them on hand.
PROFILE WORKFLOW
The user has access to this area from the navbar manu. It is easy to change the initial preferences set up when signing up from here.


|
LaraCraft
|
Go to the source code of this file.
Namespaces | |
| glm | |
Functions | |
| template<typename T , precision P> | |
| GLM_FUNC_DECL detail::tmat4x4< T, P > | glm::translate (detail::tvec3< T, P > const &v) |
| template<typename T , precision P> | |
| GLM_FUNC_DECL detail::tmat4x4< T, P > | glm::rotate (T angle, detail::tvec3< T, P > const &v) |
| template<typename T , precision P> | |
| GLM_FUNC_DECL detail::tmat4x4< T, P > | glm::scale (detail::tvec3< T, P > const &v) |
OpenGL Mathematics (glm.g-truc.net)
Copyright (c) 2005 - 2014 G-Truc Creation (www.g-truc.net) Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
 IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
Definition in file transform.hpp.


| DOSE: |
2 hits |
oral |
LSD |
(gel tab) |
| |
1 hit |
oral |
LSD |
(liquid) |
I drove to Eau Claire, WI (I am a student at the University of Wisconsin in Madison) with a friend for the weekend. It was one of those situations where a person has a preconceived expectation of an entertaining experience; the three hour car ride was filled with this sort of enthused anticipation.
When we arrived, I was greeted by friends and we decided to wait until the next evening to take the acid. By the next night we were ready. We had two sugar cubes and two gel tabs. (One of the gel tabs, however, was cut abnormally large.) My friend was an acid virgin and decided to take only one of the sugar cubes - this left one sugar cube and the two gel tabs for me. I had taken acid several times before and wasn't going to complain. I was reading Tom Wolfe's 'The Electric Kool-Aid Acid Test' at the time, so I figured it would be historically clever to dissolve the sugar cubes in cherry Kool-Aid. I remember searching the foreign kitchen for 'the appropriate glasses' from which to drink the electric Kool-Aid. As I opened the cupboard doors, an image struck me like an ethereal sign from the drug god: two sparkling martini glasses!
The cubes took about half an hour to completely dissolve. When they did, we drank up. (The acid, as I had expected, was tasteless in the Kool-Aid.) There is a sort of mystique to taking acid, because there is no turning back. Plus, you never really know, unless you made the acid, how much you're taking.  A little piece of blotter can have a shit-load of acid on it. After about a half hour, my friend was obviously experiencing some effects: a big smile, intermittently unstoppable laughter. He also claimed to have vague 'trails.'
My acid took longer to kick in - about an hour. And for that first hour, I had the same effects. Nothing unusual I thought, and I was happy. About twenty minutes later, the trip began to get slightly more intense - I began to develop what John Lennon called 'kaleidoscope eyes.' Everything in the room began to have hints of reds, yellows and blues. This was very exciting, and I was very happy. Two to three hours passed and everyone (they had all been only under the influence of alcohol) retired to their rooms to sleep. My friend did the same - his trip was obviously fairly uneventful. I went upstairs to sit in a friend's room. This guy lived there and is a tropical freak. His room resembles a jungle (especially on three hits of acid). So, I sat there and looked around. Alone.
This is when things started to go awry. First of all, I now know it's a bad idea to trip alone unless you have something significantly distracting to do. Secondly, this room was not user-friendly. Oh yeah, this guy had three pet snakes, too. Shit. Everything in this bizarre room began to move and change color. Simple things that normally remain simple began to take on severely different characteristics. There were colorful, moving geometric designs in broad air. One interesting point: I remember thinking that, even
though I was beginning to become frightened, the geometric designs you see on acid when you concentrate on something are very beautiful - they are indescribable and no artist could possibly reproduce them well enough to do them justice. This is why I am not going to try to explain my hallucinations to you. Other things are interesting, however, and easy enough to explain. For example, this guy had a mural of fish, and when I looked at it, the fish were actually swimming around. It didn't think this sort of thing was actually
possible. I had never really believed people when they had described things like this.
Hallucinations can be fun. The down side is that acid messes with your thinking process as well. I tried to write down what I was feeling, but by the time I had written down three words, I had forgotten what I was trying to say. It gives you a strange sense of paranoia as well. You seem to think something bad is going to happen to you. And you usually believe yourself. But why not? This is an easy thing to do, when nothing you have seen in the past four hours has been real.
After about eight to ten hours, I seemed to be peaking.  After awhile I was able to realize that it would all end in time, but minutes seemed like hours. I wanted to sleep - my body was tired, but my mind was racing. And, of course, I couldn't sleep, but this came as no surprise. I remember trying however: It was awful - the hallucinations I saw when I closed my eyes were worse than the ones I saw when my eyes were open. I woke up one of my friends to talk with me, to keep me from going
insane. I couldn't look at him though - his face started to turn into awful things. It would become all contorted, and his hair turned into tentacles which began moving toward me.
Finally the drug wore off. I still couldn't sleep though; I had that strange physical feeling where you're tired but you can't sleep, and you just accept it. I was almost happy. I remember thinking on the ride back to Madison - a voyage which was as metaphorical as it was literal; from utter craziness and a lack of reality back home to sanctuary and reality - that although my experience was very frightening, I still wouldn't call it a 'bad trip.' I had experienced things that most straight people will never experience in three lifetimes. I tried to tell people about it as I am trying to explain it here, but you really can't because it is an indescribable experience: 'I can't explain; you would not understand. This is not how I am.' I don't know if I would have done it having known the consequences. I don't know if I will do it again now knowing the consequences. I probably will.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


Links - "Some Favorite Sites, Vol 1"
Through the course of a day I browse to a lot of sites. I bookmark a large number of those, and probably revisited a small portion of the sites using them. Where does that leave me? I don't really know...that would require more browsing. So here is couple of the ones that I do look at on a weekly basis:
- Coding Horror - Daily articles about a full range of topics relating to programming and computer science. A quick way to learn something new each day.
- A List Apart - Great articles on design, development, and web standards. One of the top sites for this type of information.
- Joel on Software - Joel runs Fog Creek, a software company in NYC. Lately his articles haven't been as useful to me...but his archives are gold. He actually has two books published that are just reprints of his blog articles.
- XKCD - A webcomic of romance, sarcasm, math, and language. You have to be a geek to enjoy these...I showed a couple to my wife and she didn't get any of them. I guess that is a good thing.
- Smashing Magazine - Great daily finds on here, from free fonts to best designs. Browse their archives for a quick way to get ideas on your next project.
- David Seah - Hard to really describe the articles he writes, but if you are searching on how to be better at what ever you do I think they might be helpful for you. Productivity, Printable CEO Series, design work and more just to list a couple.


Store
Mac
iPod
iPhone
iPad
iTunes
Support
What will your verse be?
Everything has something to share. See how people are using iPad in their unique ways to add to the world's story.
Watch the "your verse" film and explore the stories.


In this blog I'll use Automator to help you apply a filter to your images.
Add a Filter to Images
Some people like to apply filters to images. Such as...
However some of these conversions are very simple, and some would be repetitive. It would be very costly for human to do such kind of small jobs so many times. If we can find a robot to do these boring things for us, that would be wonderful.
So today we will use Automator to finish it.
Let's begin.
Open Automator.
Choose File->New. Choose Application(this time we use application as an example).
When using Application, the files dragged on it are considered as input.
Search on the Search Bar: filter, and drag Apply Quartz Composition Filter to Image Files to the right area.
You will receive a warning prompt, because your action may modify the original file. Just click Add.
Now you will get a Copy File Items action before your transmission action.
Choose Desktop in the Drop-down menu to make sure the modified images are stored on the Desktop.
Click on the Option button of Apply Quartz Composition Filter to Image Files and check Show this action when the workflow runs to make this window show when you are using this workflow because you may want to choose which type of conversion to be implemented(you may even make the last action show to change the save location).
Save it(I saved it as Apply Filter to Images.app) in Desktop folder.
Now let's have a test.
Drag an image on the app we created.
Choose which type of filter to apply(I chose ASCII Art). You can modify the parameters on the right panel.
TA-DA...
If you want the background to be black, you can add one more Apply Quartz Composition Filter to Image Files action in your application and choose Color Invert when you select the effect. Here I just drag the converted image to the App we created again to do it.
TA-DA...
You can drag multiple images to the App as well.
And I chose X-Ray...
If you want to know more, just try it yourself! It supports about 30 kinds of conversion. However, this is not a professional level of image modification. If you need more accurate and precise modification, please use more professional softwares.
Finally
If you are interested in Automator, try it yourself!
There is no requirement to programming experience, but it will save you a lot of time.
Anyway, it's cool right?
P.S. Wish Automator makes your life better.
(Please use this link to share: http://zhuxinqi.space/blog/macwithautomator3.html)
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Clear Pizza
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'Water soluble?' you say about the diazepam Valium. Yes, it is true! [editor's note: Diazepam is soluble indeed, but only very slightly, about 1000mg/350ml water] Valuim is water soluble, so one can insufflate the crushed pill through the nose. The tender mucas membranes in the nasal chamber absorb the drug.
This was the chat my friend, T#2, and I, T#1, had tonight, after a long night of other endevores in synthed pleasures. Our stomachs had seen the wrath of a night of over-stimulation. Valium, taken orally or nasally, would have made things worse than things already were. Myself and my good friend, T2, on the horrible way down from our night of headonism, were in need of sedation. But, alas, how were we to get the valiums in our blood stream?
Pondering our pressing predictiment, I alluded to a time when I experienced the 'candy kid secret', using another water soluble subtance. . . MDMA. Skip the stomach and cram! Yes, there are mucas membranes in one's anus. At the end of our digestive tract, lies a spounge where water (and other substances) are efficently absorbed.  I had gotten the courage to cram a very large MDMA pill (white buddah) months earlier. I logically figued that the valium pill would be absorbed through the mucas membranes of the colon area. At this point, our twitch was becoming more urgent, and our minds were getting the better of us.
 I relaized the absurdity of the feminine position I held. So, placing the small blue pill at the end of my pinky, I inserted the two into the depths of my anal cavity. Not too pleasent, but not too painful either. Looking in-between my seperated butt cheeks, I noticed the blue pill being sucked in as the colon closed shut. Yucky... smelly finger. Within minutes, I felt the calming effects of the downer ease my cracked out mind. My stomach, having been by-passed, did not even know that it's worst nightmare had been avoided.
So, after an extensive search on anally supposited valium on the net, no similar experiences were located. This information may help those who need to come down, but who's weak stomachs can not take any more chemicals.
Good Luck and Good Vibes.
-T and T
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


a)
Suppose be the matrix representing the transitive closure, in such way that is 1 if there exists a path from to, otherwise 0.
• When a new edge is added into the graph, then check whether there is a possible path through the new edge. If there is a possible path, then update the matrix according to that.
• The algorithm must contain only two loops which iterate based on the vertex V, because it must be.
Consider the algorithm of transitive closure which updates the transitive closure for each update into the graph.
TRANSITIVE-CLOSURE (u, v)
// iterate loop for all the vertices of graph
1. for
// iterate loop for another vertices of graph
2. do for
// if path from vertex p to u and v to q exists
3. do if
// updating new edge into the matrix
4. then
In this algorithm after adding an edge it may affect the whole matrix so this program updates each necessary index of matrix after adding an edge.
Since to traverse the whole matrix and checking whether to update the value or not, it requires two nested loops.
Since there are two ‘for’ loops iterating with , the complexity of the above algorithm is .
Consider the following procedure to update the transitive closure of a graph when a new edge is added to.
Consider a graph with no edges as shown below.
Initially there is no edge in the graph, so, the matrix will be in the form of, if and otherwise 0.
Now, add the edges to the graph and compute the transitive closure using TRANSITIVE-CLOSURE algorithm.
• Suppose, first edge connect the vertex 2 and 1, then for and, the conditionand becomes true so, and.
• So,, in this case, which is becomes one.
Now, the new graph and corresponding matrix is given below:
So,, in this case, which is becomes one.
If the next adding edge is, then the two conditions become true. Now, becomes 1 since there is a path from 3 to 1.
New graph and its transitive closure are as shown below:
So,, in this case, which is becomes one.
Similarly, the TRANSITIVE-CLOSURE algorithm can be repeated to update the transitive closure matrix A for any edge that is added into the graph.
b)
Consider a straight line graph having n vertices and algorithm TRANSITIVE-CLOSURE mentioned above (part a):
The transitive closure of the given graph will be as below:
• In the above matrix, it can be seen that before adding any new edge, there are total entries and the transitive closure of the given graph is 1.
• The entries, which are above from the main diagonal contains 1 as a value.
Insert a new edge that connects the first and last vertex of the graph as shown below:
Then, the above graph will become a cyclic graph. Now, all the edges are reachable from every other edge.
Then all the entries will become 1.
So,
Entries must be needed to update the transitive closure. Thus, the time required to update the transitive closure is.
c)
If a graph has n vertices, then there are maximum edges or edges which can be added to the graph.
• For adding one edge, the algorithm TRANSITIVE-CLOSURE defined in part (a) will take time thus to add edges, the above mentioned algorithm will take time.
• Above algorithm is inefficient if there is already a path from p to v or v to q.
Consider the graph as shown below along with its transitive closure:
The matrix for the above graph is as shown below:
Add the edge to the graph, there is no need to update the transitive closure because there is already a path from 3 to 1 through the vertex 2. So, the loop over q in above algorithm is redundant when.
• Below algorithm gives the updated transitive closure matrix after inserting the new edges to the graph.
• For updating the matrix, logical “and” operator used. After this checking process, updates are performed accordingly.
TRANSITIVE-CLOSURE-UPDATE (u, v)
// iterate loop for all the vertices of graph
1. for
2. do if
// iterate loop for all the vertices of graph
3. then for
4. do if
5. then
Explanation of the above algorithm:
It is known that there can’t be greater than edges in the graph, therefore, .
• Now, the addition of insertions, so total time taken in the first given two lines of the above algorithm is or, because
• In the line numbers 3, 4 and 5, which takes time, for n insertions are executed only times.
• It can be easily seen that the execution of the last three lines are performed only when, and in this case, the line number 5, sets.
• So, the 0 entries’ number in is reduced minimum 1 every time when the last three lines of the code run’s.
• Since, there exists only entries inand these lines can run maximum times.
Hence, the above procedure takes time to update the transitive closure for any sequence of n insertions.
a.
The asymptotic running times for INSERT, EXTRACT-MIN and DECRESAE-KEY, as a function of d and the number n of elements in a d-ary min heap are , and respectively. The amortized costs for these operations in a Fibonacci heap are as follows: , , respectively.
b.
The shortest paths can be computed from a single source on an -dense directed graph with no negative-weight edges in time by choosing .
Implement Dijkstra’s algorithm using d-ary min-heap.
Thus, the run time will be for constant , .
c.
The all-pairs shortest problem on an -dense directed graph with no negative-weight edges can be solved in time by running the algorithm made by using Dijkstra’s algorithm. This algorithm will run once for each vertex of the graph.
d.
The all-pairs shortest-paths problem can be solved in time on an -dense directed graph that may have negative weight edges but has no negative weight cycles by creating the graph G that has all non-negative edge weights.


Cheap terrace house in Selly Oak up for sale for just £5,000
This three bedroomed terrace is on the market from just £5,000 at an auction taking place at Aston Villa football club
by Cathrina Hulse-BMIf you're a house-hunter looking for a great doer-upper for your cash then take a look at this three-bed mid terrace located in the popular student area of Selly Oak.
The guide price is £5,000 for the bargain home in Dunstall Grove which is being advertised on property website Rightmove and is set to be sold in the next Bond Wolf Auction at Aston Villa Football Club on December 11.
Other terraced houses in the road have sold for up to £112,000.
For your money, you'll get two reception rooms, WC and wet room and kitchen all on the ground floor.
Upstairs there are three bedrooms while the property benefits from a gas fired central heating system and partial double glazing.
The house stands behind a driveway and garden and is offered with vacant possession.
Reception room one
In the reception room one, you will find a rather room complete with patterned carpet, net curtains and armchair, the room is ripe for redecoration.
There are also wooden built-in cupboards.
There's plenty of potential in a second reception room which boasts two recessed alcoves with uplighting.
Overlooking the garden, the kitchen at Dunstall Drive is a decent size and offers plenty of opportunity to update.
It presently has a cooker and small table with cream work surfaces. The floor is covered with a terracotta lino.
Follow Cathrina Hulse on social media
Cathrina Hulse is a multi-media journalist for Birmingham Live and Birmingham Mail.
Follow Cathrina here
Follow Cathrina on Facebook here
Read more of Cathrina's stories here
Have you got a story? Email<EMAIL_ADDRESS>or call 0121 234 5552
There's plenty of space in this downstairs facility which is currently a wet room complete with shower and sink.
It could easily be converted into a bathroom with bath and modern shower to suit a family.
Bedroom one
If buyers can see past the clutter in this bedroom, there's lots of potential to modernise.
Its new owner would also enjoy plenty of space and light.
Bedroom two
This bedroom is a great size and would be perfect for a child or teenager with its space and blank canvas.
Best ignore the gaudy carpet though!
Garden
At first glance the garden appears desperately wild and overgrown but the groundwork has been laid to produce a really good sized garden - perfect for a family.
There is plenty of foliage and mature trees with a sturdy fence separating neighbours.
To contact Bond Wolfe Auctions Birmingham call 0121 396 0172.


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Twisted Pair
Developer guides
: documentation on using Twisted Pair to develop your own applications


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model.minion_type
enum
MinionType
: byte;
Minion type.
unknown
Default value.
orcWoodcutter
A melee fighter. No so strong as orc warrior, but still dangerous.
fetishBlowdart
A magical creature with sharp darts.
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Ddoc
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