| Top |
| typedef | SoupMessageHeaders |
| enum | SoupMessageHeadersType |
| SoupMessageHeadersIter | |
| enum | SoupEncoding |
| enum | SoupExpectation |
| SoupRange |
SoupMessageHeaders represents the HTTP message headers associated with a request or response.
SoupMessageHeaders *
soup_message_headers_new (SoupMessageHeadersType type
);
Creates a SoupMessageHeaders. (SoupMessage does this automatically for its own headers. You would only need to use this method if you are manually parsing or generating message headers.)
void
soup_message_headers_free (SoupMessageHeaders *hdrs
);
Frees hdrs
.
void soup_message_headers_append (SoupMessageHeaders *hdrs
,const char *name
,const char *value
);
Appends a new header with name name
and value value
to hdrs
. (If
there is an existing header with name name
, then this creates a
second one, which is only allowed for list-valued headers; see also
soup_message_headers_replace()
.)
The caller is expected to make sure that name
and value
are
syntactically correct.
void soup_message_headers_replace (SoupMessageHeaders *hdrs
,const char *name
,const char *value
);
Replaces the value of the header name
in hdrs
with value
. (See
also soup_message_headers_append()
.)
The caller is expected to make sure that name
and value
are
syntactically correct.
void soup_message_headers_remove (SoupMessageHeaders *hdrs
,const char *name
);
Removes name
from hdrs
. If there are multiple values for name
,
they are all removed.
void
soup_message_headers_clear (SoupMessageHeaders *hdrs
);
Clears hdrs
.
void
soup_message_headers_clean_connection_headers
(SoupMessageHeaders *hdrs
);
Removes all the headers listed in the Connection header.
Since 2.36
const char * soup_message_headers_get_one (SoupMessageHeaders *hdrs
,const char *name
);
Gets the value of header name
in hdrs
. Use this for headers whose
values are not comma-delimited lists, and
which therefore can only appear at most once in the headers. For
list-valued headers, use soup_message_headers_get_list()
.
If hdrs
does erroneously contain multiple copies of the header, it
is not defined which one will be returned. (Ideally, it will return
whichever one makes libsoup most compatible with other HTTP
implementations.)
Since 2.28
const char * soup_message_headers_get_list (SoupMessageHeaders *hdrs
,const char *name
);
Gets the value of header name
in hdrs
. Use this for headers whose
values are comma-delimited lists, and which are therefore allowed
to appear multiple times in the headers. For non-list-valued
headers, use soup_message_headers_get_one()
.
If name
appears multiple times in hdrs
,
soup_message_headers_get_list()
will concatenate all of the values
together, separated by commas. This is sometimes awkward to parse
(eg, WWW-Authenticate, Set-Cookie), but you have to be able to deal
with it anyway, because the HTTP spec explicitly states that this
transformation is allowed, and so an upstream proxy could do the
same thing.
Since 2.28
const char * soup_message_headers_get (SoupMessageHeaders *hdrs
,const char *name
);
soup_message_headers_get
is deprecated and should not be used in newly-written code.
Use soup_message_headers_get_one()
or
soup_message_headers_get_list()
instead.
Gets the value of header name
in hdrs
.
This method was supposed to work correctly for both single-valued
and list-valued headers, but because some HTTP clients/servers
mistakenly send multiple copies of headers that are supposed to be
single-valued, it sometimes returns incorrect results. To fix this,
the methods soup_message_headers_get_one()
and
soup_message_headers_get_list()
were introduced, so callers can
explicitly state which behavior they are expecting.
void (*SoupMessageHeadersForeachFunc) (const char *name
,const char *value
,gpointer user_data
);
The callback passed to soup_message_headers_foreach()
.
name |
the header name |
|
value |
the header value |
|
user_data |
the data passed to |
void soup_message_headers_foreach (SoupMessageHeaders *hdrs
,SoupMessageHeadersForeachFunc func
,gpointer user_data
);
Calls func
once for each header value in hdrs
.
Beware that unlike soup_message_headers_get()
, this processes the
headers in exactly the way they were added, rather than
concatenating multiple same-named headers into a single value.
(This is intentional; it ensures that if you call
soup_message_headers_append()
multiple times with the same name,
then the I/O code will output multiple copies of the header when
sending the message to the remote implementation, which may be
required for interoperability in some cases.)
You may not modify the headers from func
.
void soup_message_headers_iter_init (SoupMessageHeadersIter *iter
,SoupMessageHeaders *hdrs
);
Initializes iter
for iterating hdrs
.
gboolean soup_message_headers_iter_next (SoupMessageHeadersIter *iter
,const char **name
,const char **value
);
Yields the next name/value pair in the SoupMessageHeaders
being
iterated by iter
. If iter
has already yielded the last header,
then soup_message_headers_iter_next()
will return FALSE
and name
and value
will be unchanged.
SoupEncoding
soup_message_headers_get_encoding (SoupMessageHeaders *hdrs
);
Gets the message body encoding that hdrs
declare. This may not
always correspond to the encoding used on the wire; eg, a HEAD
response may declare a Content-Length or Transfer-Encoding, but
it will never actually include a body.
void soup_message_headers_set_encoding (SoupMessageHeaders *hdrs
,SoupEncoding encoding
);
Sets the message body encoding that hdrs
will declare. In particular,
you should use this if you are going to send a request or response in
chunked encoding.
goffset
soup_message_headers_get_content_length
(SoupMessageHeaders *hdrs
);
Gets the message body length that hdrs
declare. This will only
be non-0 if soup_message_headers_get_encoding()
returns
SOUP_ENCODING_CONTENT_LENGTH
.
void soup_message_headers_set_content_length (SoupMessageHeaders *hdrs
,goffset content_length
);
Sets the message body length that hdrs
will declare, and sets
hdrs
's encoding to SOUP_ENCODING_CONTENT_LENGTH
.
You do not normally need to call this; if hdrs
is set to use
Content-Length encoding, libsoup will automatically set its
Content-Length header for you immediately before sending the
headers. One situation in which this method is useful is when
generating the response to a HEAD request; Calling
soup_message_headers_set_content_length()
allows you to put the
correct content length into the response without needing to waste
memory by filling in a response body which won't actually be sent.
SoupExpectation
soup_message_headers_get_expectations (SoupMessageHeaders *hdrs
);
Gets the expectations declared by hdrs
's "Expect" header.
Currently this will either be SOUP_EXPECTATION_CONTINUE
or
SOUP_EXPECTATION_UNRECOGNIZED
.
void soup_message_headers_set_expectations (SoupMessageHeaders *hdrs
,SoupExpectation expectations
);
Sets hdrs
's "Expect" header according to expectations
.
Currently SOUP_EXPECTATION_CONTINUE
is the only known expectation
value. You should set this value on a request if you are sending a
large message body (eg, via POST or PUT), and want to give the
server a chance to reject the request after seeing just the headers
(eg, because it will require authentication before allowing you to
post, or because you're POSTing to a URL that doesn't exist). This
saves you from having to transmit the large request body when the
server is just going to ignore it anyway.
const char * soup_message_headers_get_content_type (SoupMessageHeaders *hdrs
,GHashTable **params
);
Looks up the "Content-Type" header in hdrs
, parses it, and returns
its value in *content_type
and *params
. params
can be NULL
if you
are only interested in the content type itself.
hdrs |
||
params |
return location for the Content-Type parameters (eg, "charset"), or
|
[out][element-type utf8 utf8][allow-none][transfer full] |
a string with the value of the "Content-Type" header
or NULL if hdrs
does not contain that header or it cannot be
parsed (in which case *params
will be unchanged).
Since 2.26
void soup_message_headers_set_content_type (SoupMessageHeaders *hdrs
,const char *content_type
,GHashTable *params
);
Sets the "Content-Type" header in hdrs
to content_type
,
optionally with additional parameters specified in params
.
hdrs |
||
content_type |
the MIME type |
|
params |
additional
parameters, or |
[allow-none][element-type utf8 utf8] |
Since 2.26
gboolean soup_message_headers_get_content_disposition (SoupMessageHeaders *hdrs
,char **disposition
,GHashTable **params
);
Looks up the "Content-Disposition" header in hdrs
, parses it, and
returns its value in *disposition
and *params
. params
can be
NULL
if you are only interested in the disposition-type.
In HTTP, the most common use of this header is to set a
disposition-type of "attachment", to suggest to the browser that a
response should be saved to disk rather than displayed in the
browser. If params
contains a "filename" parameter, this is a
suggestion of a filename to use. (If the parameter value in the
header contains an absolute or relative path, libsoup will truncate
it down to just the final path component, so you do not need to
test this yourself.)
Content-Disposition is also used in "multipart/form-data", however this is handled automatically by SoupMultipart and the associated form methods.
hdrs |
||
disposition |
return location for the
disposition-type, or |
[out][transfer full] |
params |
return
location for the Content-Disposition parameters, or |
[out][transfer full][element-type utf8 utf8] |
TRUE
if hdrs
contains a "Content-Disposition"
header, FALSE
if not (in which case *disposition
and *params
will be unchanged).
Since 2.26
void soup_message_headers_set_content_disposition (SoupMessageHeaders *hdrs
,const char *disposition
,GHashTable *params
);
Sets the "Content-Disposition" header in hdrs
to disposition
,
optionally with additional parameters specified in params
.
See soup_message_headers_get_content_disposition()
for a discussion
of how Content-Disposition is used in HTTP.
hdrs |
||
disposition |
the disposition-type |
|
params |
additional
parameters, or |
[allow-none][element-type utf8 utf8] |
Since 2.26
gboolean soup_message_headers_get_ranges (SoupMessageHeaders *hdrs
,goffset total_length
,SoupRange **ranges
,int *length
);
Parses hdrs
's Range header and returns an array of the requested
byte ranges. The returned array must be freed with
soup_message_headers_free_ranges()
.
If total_length
is non-0, its value will be used to adjust the
returned ranges to have explicit start and end values, and the
returned ranges will be sorted and non-overlapping. If
total_length
is 0, then some ranges may have an end value of -1,
as described under SoupRange, and some of the ranges may be
redundant.
Beware that even if given a total_length
, this function does not
check that the ranges are satisfiable.
SoupServer has built-in handling for range requests. If your
server handler returns a SOUP_STATUS_OK
response containing the
complete response body (rather than pausing the message and
returning some of the response body later), and there is a Range
header in the request, then libsoup will automatically convert the
response to a SOUP_STATUS_PARTIAL_CONTENT
response containing only
the range(s) requested by the client.
The only time you need to process the Range header yourself is if
either you need to stream the response body rather than returning
it all at once, or you do not already have the complete response
body available, and only want to generate the parts that were
actually requested by the client.
hdrs |
||
total_length |
the total_length of the response body |
|
ranges |
return location for an array of SoupRange. |
[out] |
length |
the length of the returned array |
TRUE
if hdrs
contained a syntactically-valid
"Range" header, FALSE
otherwise (in which case range
and length
will not be set).
Since 2.26
void soup_message_headers_set_ranges (SoupMessageHeaders *hdrs
,SoupRange *ranges
,int length
);
Sets hdrs
's Range header to request the indicated ranges. (If you
only want to request a single range, you can use
soup_message_headers_set_range()
.)
Since 2.26
void soup_message_headers_set_range (SoupMessageHeaders *hdrs
,goffset start
,goffset end
);
Sets hdrs
's Range header to request the indicated range.
start
and end
are interpreted as in a SoupRange.
If you need to request multiple ranges, use
soup_message_headers_set_ranges()
.
Since 2.26
void soup_message_headers_free_ranges (SoupMessageHeaders *hdrs
,SoupRange *ranges
);
Frees the array of ranges returned from soup_message_headers_get_ranges()
.
Since 2.26
gboolean soup_message_headers_get_content_range (SoupMessageHeaders *hdrs
,goffset *start
,goffset *end
,goffset *total_length
);
Parses hdrs
's Content-Range header and returns it in start
,
end
, and total_length
. If the total length field in the header
was specified as "*", then total_length
will be set to -1.
hdrs |
||
start |
return value for the start of the range |
|
end |
return value for the end of the range |
|
total_length |
return value for the total length of the resource,
or |
TRUE
if hdrs
contained a "Content-Range" header
containing a byte range which could be parsed, FALSE
otherwise.
Since 2.26
void soup_message_headers_set_content_range (SoupMessageHeaders *hdrs
,goffset start
,goffset end
,goffset total_length
);
Sets hdrs
's Content-Range header according to the given values.
(Note that total_length
is the total length of the entire resource
that this is a range of, not simply end
- start
+ 1.)
SoupServer has built-in handling for range requests, and you do
not normally need to call this function youself. See
soup_message_headers_get_ranges()
for more details.
hdrs |
||
start |
the start of the range |
|
end |
the end of the range |
|
total_length |
the total length of the resource, or -1 if unknown |
Since 2.26
typedef struct SoupMessageHeaders SoupMessageHeaders;
The HTTP message headers associated with a request or response.
Value passed to soup_message_headers_new()
to set certain default
behaviors.
typedef struct { } SoupMessageHeadersIter;
An opaque type used to iterate over a SoupMessageHeaders
structure.
After intializing the iterator with
soup_message_headers_iter_init()
, call
soup_message_headers_iter_next()
to fetch data from it.
You may not modify the headers while iterating over them.
How a message body is encoded for transport
|
unknown / error |
||
|
no body is present (which is not the same as a 0-length body, and only occurs in certain places) |
||
|
Content-Length encoding |
||
|
Response body ends when the connection is closed |
||
|
chunked encoding (currently only supported for response) |
||
|
multipart/byteranges (Reserved for future use: NOT CURRENTLY IMPLEMENTED) |
typedef struct { goffset start; goffset end; } SoupRange;
Represents a byte range as used in the Range header.
If end
is non-negative, then start
and end
represent the bounds
of of the range, counting from 0. (Eg, the first 500 bytes would be
represented as start
= 0 and end
= 499.)
If end
is -1 and start
is non-negative, then this represents a
range starting at start
and ending with the last byte of the
requested resource body. (Eg, all but the first 500 bytes would be
start
= 500, and end
= -1.)
If end
is -1 and start
is negative, then it represents a "suffix
range", referring to the last -start
bytes of the resource body.
(Eg, the last 500 bytes would be start
= -500 and end
= -1.)
Since 2.26


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TensorFlow is a an open source library for numerical computation, specializing in machine learning applications. In this codelab, you will learn how to install and run TensorFlow on a single machine, and will predict deaths on Game of Thrones data using the tutorial Wide+Deep Learning Network.
This codelab presents wide+deep learning model execution taking into account Game of Thrones data for Death classification & prediction . The aim of this Codelab is to dig into wide+deep neural network model to combine the benefits of memorization+generalization models, in which wide model is directly relevant to features and deep model improves the diversity of recommended systems.
The wide+deep learning tutorial comes within census data so we have been working with an analogous dataset taking into consideration Game of Thrones .
In the next sections you will know how the dataset works ,how to implement the wide+deep learning model and finally some conclusions about the experimentation with the model, and more in detail . Besides and listed, you will learn how to:
The GoT dataset was compiled from a kaggle dataset and transformed to offer more information using Game of Thrones wiki . Before going into a deeper data analysis, we would like to offer a view about the power of search with Answer the public tool. Using this visualization about the main five W some questions could be underlined about game of Thrones using the searches in US and UK
These visualization flashlights the public interest about Game of Thrones deaths related to WHY,WHAT,WHEN and HOW. In most of the searches there comes an interest about why all characters die, in which book each character die or in which TV season as well as searches about video compilations . Also we might find comparisons to Walking Death.
In a first general approach, we can see that searches about Game of Thrones Deaths are related to which deaths are packaged in each book or season. The question ‘HOW’ might offer us a more practical approach about people searching for compilation of deaths, Youtube videos about it.
During this 0 point we will serve as company for Tensorflow Codelab based on Game of Thrones Data, in order to provide a Neural Network model to classify the probability of Death of Game of Thrones characters with wide+deep model . There is some data theory we will dive in when implementing the model, but first we will dig a little bit in the data in order to know more about the behaviour of our dataset
You can download the data from the button below. The original dataset has been released in Kaggle and we have been filling the information in Game of Thrones wiki focusing on title, culture .
In one first approach of the dataset we extract the following useful information about the dataset, wich we consider a significant first approach for finding correlations and relationships in between variables
NUMBER OF CHARACTERS : 1946
MEDIAN OF AGE : 27
CORRELATION BETWEEN Number of Death Relationships and Popularity : 0.663
Here we have some graphics that show correlation among data , having into account that most of them show relationships in between popularity and other characteristics . Game of Thrones character ecosystem shows a diverse culture approach that prints a diverse atmosphere , without a doubt it really brings to the table a rich atmosphere to enjoy. Among all cultures, the most significant are Valyrian - as House Targaryen members- , Northmen -like watchmen -that has the highest value in culture with 143 characters, and Andals - like House Lannister. On this first approach of Histogram of popularity , more than 750 characters , about 40 % are ranged with 0 popularity ; being the most popular character listed – less than 20 , about a 1.02 % - the following, described together within . However, the median of popularity is 0.03344
With this graph we would like to enlighten us to solve the following questions
Is there a relationship in between the popularity of a character and the number of death Characters?
As you can see the popularity listed as 1 there is a constant interval that goes from 1 to 10 deaths. Also there is presence in more than 15 deaths
On the Y axis we can find a score that goes from 0 to 1 and gives us an idea of the popularity of the current character and scored on the X axis the number of death relationships that go from 0 to 14. The visualization of this graph drops some conclusions upon us :
0) Most popularity characters are ranked from 0 to 0.6 and have 0 dead relationships .
1) We could draw an exponential classify curve that give us a certain pattern and given the following conclusions .
--Most of unpopular characters have no dead relationships
--There is a linear incremental number of dead relationships once the character is very popular
--A very popular character with a high number of dead relations can be considered an outlier .
As we dig into the data, so do we within the question we actually want to solve...How is popularity related to Death in Game of Thrones?.
##TO-DO : EDIT STYLEThis first approach has been great ! Now let´s move into installing Tensorflow and have a deeper understanding with wide+deep learning model to gain more knowledge .
Follow installation instructions for the following platforms
Linux
linuxMac
MacWindows
WindowsFrom Source
From SourceHere we cover Linux installation but you can see different . So , since the v1 release, you can type
$ pip install tensorflow # Python 2.7; CPU support (no GPU support)
$ pip3 install tensorflow # Python 3.n; CPU support (no GPU support)
$ pip install tensorflow-gpu # Python 2.7; GPU support
$ pip3 install tensorflow-gpu # Python 3.n; GPU support
Great! Now you should have your instalation complete. You can test in your console typing in python
>>> import tensorflow as tf
>>> hello = tf.constant('Hello, Tensorflow!')
>>> sess = tf.Session()
>>> sess.run(hello)
'Hello, Tensorflow!'
You can download the code and the data below. We suggest you to download both and put them in the same folder . We will be explaining afterwards in each model which part of the codes matches with each part of wide + deep learning model . Once you have it downloaded into your computer, you can play with it .
It should contain the file wide+deep_Tensorflow_GOT and the file GOT_data.csv
data_set = ‘your_path_here’
~ $ python 'program' --training_mode learn_runner --model_dir /Base directory for output models --model_type 'wide_n_deep' --steps 200
~ $ tensorboard --logdir =/tmp/model/
During the next session we will explain the architecture of the Wid+Deep learning model having into consideration the published paper by Google. We also recommend the talk given by Heng-Tze Cheng at Tensorflow Dev Summit 2017 .
Image from wide+deep tutorial
The aim of this model is to combine the benefits of memorization+generalization models, in wich wide model is directly relevant to features and deep model improves the diversity of recommended systems. The abstraction of concepts in this text comes from the paper wide + deep learning for recommender systems paper
With less feature engineering, deep neural networks can generalize better to unseen feature combinations through low-dimensional dense embeddings learned for the sparse features. However, deep neural networks with embeddings can over-generalize and recommend less relevant items when the user-item interactions are sparse and high-rank.
Wide+Deep learning combines the benefits the Memorization and generalization , which is a current challenge for learning systems. Each part of the nets shows it challenges as well, so in Wide net we can find crossed columns and in deep learning we can find embeddings as the most significant concepts operating in each part of the Network .
Categorical variables are also known as discrete or qualitative variables. Categorical variables can be further categorized as either nominal, ordinal or dichotomous. Nominal variables are variables that have two or more categories, but which do not have an intrinsic order. Continuos variables are those that refers to continuous values such as numbers
CATEGORICAL_COLUMN_NAMES = only_existing([
'male',
'culture',
'mother',
'father',
'title',
'heir',
'house',
'spouse',
'numDeadRelations',
'boolDeadRelations',
], COLUMNS)
CONTINUOUS_COLUMNS = only_existing([
'age',
'popularity',
'dateOfBirth',
], COLUMNS)
Memorization -Wide Model- Comes with learning the frequent co-ocurrence of features and exploiting the correlation available in the historical data. It is directly relevant to features . It can be achieved effectively using cross-product transformations over sparse features. Memorization is directly relevant to features.
The linear classifier digs into continuous features . In a practical approach you could say that this model is suitable for continuous -often numerical data- which already can be made some sense of. This model needs manual feature engineering for crossed relationships between columns.
Beyond you can find how we approach the linear classifier in the exercise : We define the linear variables in the columns We execute the linear classifier Here the design of the net comes with the combination of features that can combine the information in order to offer a suitable conclusion
Image from wide+deep tutorial
if FLAGS.model_type == "wide":
m = tf.contrib.learn.LinearClassifier(model_dir=model_dir,
feature_columns=wide_columns)
Image from wide+deep tutorial
Generalization - Deep Model- the model is a Feedfoward neural network that works with categorical features . there exist Transitivity of correlation and explores feature combinations that have never or rarely occurred in the past. It improves the diversity of recommended items . This generalization can be added by using features that are less granular . So at the end this model is great for combining two different models of classification using neural Networks. You can see how this model has been working with
elif FLAGS.model_type == "deep":
m = tf.contrib.learn.DNNClassifier(model_dir=model_dir,
feature_columns=deep_columns,
hidden_units=[100, 50])
The wide models and deep models are combined by summing up their final output log odds as the prediction, then feeding the prediction to a logistic loss function. All the graph definition and variable allocations have already been handled for you under the hood, so you simply need to create a DNNLinearCombinedClassifier:
In this case, there are two layers with 100 and 50 neurons each. You can select your own number of layers and neurons
else:
m = tf.contrib.learn.DNNLinearCombinedClassifier(
model_dir=model_dir,
linear_feature_columns=wide_columns,
dnn_feature_columns=deep_columns,
dnn_hidden_units=[100, 50],
fix_global_step_increment_bug = True,
)
return m
The Optimizer base class provides methods to compute gradients for a loss and apply gradients to variables. A collection of subclasses implement classic optimization algorithms such as GradientDescent and Adagrad.
Optimizers are a detailed part of neural net design that can offer a real performance difference among the neural net models. You can find documentation about Tensorflow optimizers hereIf we had to underline a concept about optimizers it would be the learning_rate .We could define the learning_rate as a value used by the learning algorithm to determine how quickly the weights are adjusted. It determines the adquisition time for neurons with weights that are trained using the algortihm.
Bellow we describe the parameters and the main characteristics of the optimizers wich you can try in the model. Note that the model has been defined as bellow and optimizers have been changed for that model :
The code has been executed taking into account serveral models for the same dataset ; You can find the table bellow in wich we print the accuracy and other significant data about each part of the model : Please, take into account that all the modifications are inside m= tf.contrib.learn.DNNLinearCombinedClassifier tensorflow class and the design has been modeled with the wide and the deep settings . Please, to know more about this function visit the awesome documentation.
Wide+deep learning is great for large scale datasets that take into account both categorical and continuous features that include a numerical and embeding form . Having a self critical mode, we might have used a more large dataset with more Game of Thrones characters although the nature of the dataset is great for continuous and categorical clasification.
The accuracy of the model changes by design taking into account the hidden units of the model, the activation function, and the optimizers. Having more or less layers and hidden units does not imply that the functioning of the model might be better or worse .
Choosing the wide and deep learning settings carefully taking into account the problems they usually solve is also a useful task to take , as well as the learning rate.
The best result of the model is pasted with the accuracy as follows :
You can help us with the results of changing the model, generalizing in hypothesis :
In the model, if you increase the hidden layers and combine the number of neurons , the accuracy of the model increases or decreases? .
Please, fill your model conclussions in this FormTake this feedback form to tell us more about how useful it was and dig into it if you want to know more
Code :
Santiago SaavedraCodelab documentation and images :
Gema ParreñoSpecial thanks to :
FranSpecial thanks to :
Flipper83


Event causes some actions to be taken when a certain amount of time
has
passed. {frequency} is the amount of time in seconds to pass before
firing
the event. You can create as many events as you like. Duplicate
frequencies
are valid; so you could create several events to fire every 10 seconds.
Typing /event by itself will list all the events you have defined.
When you
list the events you are also shown the time left before the event
fires.
001: {Jumper} {F:30} {T:14} {jump}
This is an example of an event listing. This first parameter is
the name of
the event. F: shows you the frequency you have set for the
event. T: shows
how much time is left before the event gets fired. The last part
contains the
event actions to be taken when the event is fired.
/event {Jumper} {30} {jump}
This will create an event called Jumper that jumps every 30 seconds.
Click here to return to previous page.


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Fake News Buster: No visit to shrine after poll results
by Bangalore Mirror BureauTHE CLAIM
A video of Shiv Sena MLA Aaditya Thackeray is being shared with a claim that he visited Ajmer Sharif Dargah after recently getting elected from Worli constituency in Mumbai.
SO, WHAT’S THE TRUTH?
The video and image are at least four months old. The leader had visited the shrine in June this year.


In 1982, Sam Raimi's first tongue-in-cheek horror film, "The Evil Dead", was released in theatres, and proved notable in receiving a rave review from Stephen King after its premiere at the Cannes Film Festival. The concept behind it was that a hidden force was unleashed in the woods, ready to devour anything in its path, including a group of young people staying in a remote cabin. The film was successful enough as a low-budget sleeper to spawn two sequels, each with a bigger budget than the next and all directed by Sam Raimi. What we have is a trilogy of horror, growing more tongue-in-cheek and goofy with each sequel. Below is a brief look at each film.
The Evil Dead - I will not say that "The Evil Dead" is one of the best horror films ever made - it is not - but it is often repulsive, humorous and full of major shocks to the system to make any true horror fan happy.
Bruce Campbell plays Ash, one of the group of college students who travel on an Oldsmobile to some remote cabin in the desolate woods of Michigan. In the opening sequence, a whirlwind force travels through lakes, swamps, and trees ready to attack the Oldsmobile. Things careen out of control briefly, yet the students manage to make it to the cabin, even going through a decrepit bridge. But nightfall comes, and one of them makes the mistake of reading from an old copy of the Book of the Dead (entitled "Necronomicon," a nod to H.P. Lovecraft) and before you know it, evil spirits are unleashed and zombies are made.  Naturally, Ash is the one that makes it out alive.
There is plenty of blood and gore, and there is an inventive use of a pencil as a weapon. The film certainly is cheap-looking and barely audible in certain scenes, and some of the makeup and special-effects are practically garden variety. The strength of "The Evil Dead" is in the straightforward directing by Raimi and the astoundingly good cinematography by Tom Philo - the latter makes every shot eerie and menacing. There is a sense of claustrophobia to the film, a sort of latter-day "Night of the Living Dead" where hiding in an isolated cabin can prevent one from dealing with unseen forces. Naturally, these forces find their way in the cabin.
"The Evil Dead" also has some superb moments of horror and humor, particularly the scene where one girl stares into a window (we only see the back of her head) as she is able to read all the cards that her group is playing before turning around and screaming...well, you get the idea. I also like the vines attacking one girl in the forest and being dragged across thousands of twigs, while one of the "shemps" inserts itself in an area...well, you know the scene, need I repeat it? Some of the sexual connotations I could have lived without but still there is enough going on here to make anyone squeamish about going into the woods again. "The Evil Dead" is goofy horror to be sure, but fun nonetheless.
Evil Dead 2: Dead by Dawn - Here is an example of not so much a sequel, but a remake of the original. With a bigger budget and even better special-effects, Raimi continues where the original left off, and brings us even more gore and humor.
At the end of the original, Ash was pursued by that evil force in the woods. Now he is back in the cabin enduring more torture by these unseen forces. There is a moment where his right hand takes on a life of its own, and Ash chops it off with a chainsaw. Needless to say, the hand scurries, hides and makes fun of Ash in ways that are so funny that the film's haunting momentum pauses and becomes more of a horror-comedy than a pure horror film. We see Ash's reflection in a mirror having a life of its own, dancing skeletons by the pale moonlight, giggling deer heads, heads being squashed in vises, lots of blood spilling into the screen from every direction (though nothing like the distasteful "Dead-Alive" by Peter Jackson from 1993), and ghouls and zombies yelling things like "I am going to take your soul!"
 She thinks Ash may have killed her father, I mean, what would you think if you saw a man draped with blood and holding a chainsaw? But Raimi continues to make us feel the claustrophobia of being isolated and facing demonic forces beyond our own control. The humor and horror pays off, and the final sequence is certainly a doozy.
Army of Darkness - Ash is back again, now he is stuck in the 13th century fighting Deadites and more ghouls and zombies! Huh? Well, you see at the end of "Evil Dead 2," Ash was transported back into time before being able to finish an incantation that would have ended the evil spell. He and his beloved Oldsmobile landed in some foreign land in the 13th century, and now he is subject to the physical torture of some medieval lords. Ash does so well battling Deadites to the death that he is considered by the people to be their savior against the armies of darkness. Ash's goal, however, is to retrieve the Book of the Dead and get back home to his S-mart job where they "shop Smart!" There is also a love interest, a medieval damsel-in-distress, Sheila (Embeth Davidtz, who later appeared in "Schindler's List"), who convinces him to help her people.
"Army of Darkness" is hardly horror, it is an out-and-out campy comedy with plenty of thrills per second, and less blood and gore than the previous entries. It is practically a new version of Ray Harryhausen's "Jason and the Argonauts," albeit less sophisticated in its content if not its form. Ash is like Marty McFly in "Back to the Future," saying such anachronistic lines as "Groovy!" or "Give me some sugar baby." There are still some moments to treasure such as the Evil Ash sequence, the evil Ash Liliputians formed by reflective shards of glass, and Ash screwing up the simple line from "The Day the Earth Stood Still" ("Klattu Barada Nikto") while trying to choose the real Book of the Dead in a scene that echoes Indiana Jones.
It is a fun-filled 82 minutes, but some of the gags are desperate and repetitive, and we start to get the feeling that Ash has had enough of battling demons, ghosts, and the vast army of skeletons. Probably Raimi has had enough as well, considering the ending has been changed radically from its more downbeat finish. Still, if nothing else, "Army of Darkness" led the way to more anachronistic, self-aware medieval stories, especially the recent TV series "Hercules" and "Xena," both winking at the audience in its complete absurdity and anachronisms.
For more reviews, check out JERRY AT THE MOVIES at http://buffs.moviething.com/buffs/faust/
E-mail me with any questions, comments or general complaints at<EMAIL_ADDRESS>or at<EMAIL_ADDRESS>The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
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Related links: index of all rec.arts.movies.reviews reviews


@(message: String) @Main("Home") {
Monday, February 23
Periods 1-7
Tuesday, February 24
Periods 1, 3, 5, 7
Wednesday, February 25
Periods 2, 4, 6
Thursday, February 26
Periods 1, 3, 5, 7
Friday, February 27
Periods 2, 4, PTP, 6


Class QCOMTiledRendering
- java.lang.Object
-
- org.lwjgl.opengles.QCOMTiledRendering
-
public class QCOMTiledRendering extends java.lang.Object
Native bindings to the QCOM_tiled_rendering extension.In the handheld graphics space, a typical challenge is achieving efficient rendering performance given the different characteristics of the various types of graphics memory. Some types of memory ("slow" memory) are less expensive but have low bandwidth, higher latency, and/or higher power consumption, while other types ("fast" memory) are more expensive but have higher bandwidth, lower latency, and/or lower power consumption. In many cases, it is more efficient for a graphics processing unit (GPU) to render directly to fast memory, but at most common display resolutions it is not practical for a device to contain enough fast memory to accommodate both the full color and depth/stencil buffers (the frame buffer). In some devices, this problem can be addressed by providing both types of memory; a large amount of slow memory that is sufficient to store the entire frame buffer, and a small, dedicated amount of fast memory that allows the GPU to render with optimal performance. The challenge lies in finding a way for the GPU to render to fast memory when it is not large enough to contain the actual frame buffer.
One approach to solving this problem is to design the GPU and/or driver using a tiled rendering architecture. With this approach the render target is subdivided into a number of individual tiles, which are sized to fit within the available amount of fast memory. Under normal operation, the entire scene will be rendered to each individual tile using a multi-pass technique, in which primitives that lie entirely outside of the tile being rendered are trivially discarded. After each tile has been rendered, its contents are saved out to the actual frame buffer in slow memory (a process referred to as the "resolve"). The resolve introduces significant overhead, both for the CPU and the GPU. However, even with this additional overhead, rendering using this method is usually more efficient than rendering directly to slow memory.
This extension allows the application to specify a rectangular tile rendering area and have full control over the resolves for that area. The information given to the driver through this API can be used to perform various optimizations in the driver and hardware. One example optimization is being able to reduce the size or number of the resolves. Another optimization might be to reduce the number of passes needed in the tiling approach mentioned above. Even traditional rendering GPUs that don't use tiles may benefit from this extension depending on their implemention of certain common GPU operations.
One typical use case could involve an application only rendering to select portions of the render target using this technique (which shall be referred to as "application tiling"), leaving all other portions of the render target untouched. Therefore, in order to preserve the contents of the untouched portions of the render target, the application must request an EGL (or other context management API) configuration with a non-destructive swap. A destructive swap may only be used safely if the application renders to the entire area of the render target during each frame (otherwise the contents of the untouched portions of the frame buffer will be undefined).
Additionally, care must be taken to avoid the cost of mixing rendering with and without application tiling within a single frame. Rendering without application tiling ("normal" rendering) is most efficient when all of the rendering for the entire scene can be encompassed within a single resolve. If any portions of the scene are rendered prior to that resolve (such as via a prior resolve, or via application tiling), then that resolve becomes much more heavyweight. When this occurs, prior to rendering each tile the fast memory must be populated with the existing contents of the frame buffer region corresponding to that tile. This operation can double the cost of resolves, so it is recommended that applications avoid mixing application tiling and normal rendering within a single frame. If both rendering methods must be used in the same frame, then the most efficient approach is to perform all normal rendering first, followed by rendering done with application tiling. An implicit resolve will occur (if needed) at the start of application tiling, so any pending normal rendering operations will be flushed at the time application tiling is initiated. This extension provides interfaces for the application to communicate to the driver whether or not rendering done with application tiling depends on the existing contents of the specified tile, and whether or not the rendered contents of the specified tile need to be preserved upon completion. This mechanism can be used to obtain optimal performance, e.g. when the application knows that every pixel in a tile will be completely rendered or when the resulting contents of the depth/stencil buffers do not need to be preserved.
-
-
Field Summary
-
Method Summary
All Methods Static Methods Concrete Methods Modifier and Type Method and Description static void
glEndTilingQCOM(int preserveMask)
static void
glStartTilingQCOM(int x, int y, int width, int height, int preserveMask)
-
-
-
Field Detail
-
GL_COLOR_BUFFER_BIT0_QCOM
public static final int GL_COLOR_BUFFER_BIT0_QCOM
Accepted by thepreserveMask
parameter of StartTilingQCOM and EndTilingQCOM.- See Also:
- Constant Field Values
-
GL_COLOR_BUFFER_BIT1_QCOM
public static final int GL_COLOR_BUFFER_BIT1_QCOM
Accepted by thepreserveMask
parameter of StartTilingQCOM and EndTilingQCOM.- See Also:
- Constant Field Values
-
GL_COLOR_BUFFER_BIT2_QCOM
public static final int GL_COLOR_BUFFER_BIT2_QCOM
Accepted by thepreserveMask
parameter of StartTilingQCOM and EndTilingQCOM.- See Also:
- Constant Field Values
-
GL_COLOR_BUFFER_BIT3_QCOM
public static final int GL_COLOR_BUFFER_BIT3_QCOM
Accepted by thepreserveMask
parameter of StartTilingQCOM and EndTilingQCOM.- See Also:
- Constant Field Values
-
GL_COLOR_BUFFER_BIT4_QCOM
public static final int GL_COLOR_BUFFER_BIT4_QCOM
Accepted by thepreserveMask
parameter of StartTilingQCOM and EndTilingQCOM.- See Also:
- Constant Field Values
-
GL_COLOR_BUFFER_BIT5_QCOM
public static final int GL_COLOR_BUFFER_BIT5_QCOM
Accepted by thepreserveMask
parameter of StartTilingQCOM and EndTilingQCOM.- See Also:
- Constant Field Values
-
GL_COLOR_BUFFER_BIT6_QCOM
public static final int GL_COLOR_BUFFER_BIT6_QCOM
Accepted by thepreserveMask
parameter of StartTilingQCOM and EndTilingQCOM.- See Also:
- Constant Field Values
-
GL_COLOR_BUFFER_BIT7_QCOM
public static final int GL_COLOR_BUFFER_BIT7_QCOM
Accepted by thepreserveMask
parameter of StartTilingQCOM and EndTilingQCOM.- See Also:
- Constant Field Values
-
GL_DEPTH_BUFFER_BIT0_QCOM
public static final int GL_DEPTH_BUFFER_BIT0_QCOM
Accepted by thepreserveMask
parameter of StartTilingQCOM and EndTilingQCOM.- See Also:
- Constant Field Values
-
GL_DEPTH_BUFFER_BIT1_QCOM
public static final int GL_DEPTH_BUFFER_BIT1_QCOM
Accepted by thepreserveMask
parameter of StartTilingQCOM and EndTilingQCOM.- See Also:
- Constant Field Values
-
GL_DEPTH_BUFFER_BIT2_QCOM
public static final int GL_DEPTH_BUFFER_BIT2_QCOM
Accepted by thepreserveMask
parameter of StartTilingQCOM and EndTilingQCOM.- See Also:
- Constant Field Values
-
GL_DEPTH_BUFFER_BIT3_QCOM
public static final int GL_DEPTH_BUFFER_BIT3_QCOM
Accepted by thepreserveMask
parameter of StartTilingQCOM and EndTilingQCOM.- See Also:
- Constant Field Values
-
GL_DEPTH_BUFFER_BIT4_QCOM
public static final int GL_DEPTH_BUFFER_BIT4_QCOM
Accepted by thepreserveMask
parameter of StartTilingQCOM and EndTilingQCOM.- See Also:
- Constant Field Values
-
GL_DEPTH_BUFFER_BIT5_QCOM
public static final int GL_DEPTH_BUFFER_BIT5_QCOM
Accepted by thepreserveMask
parameter of StartTilingQCOM and EndTilingQCOM.- See Also:
- Constant Field Values
-
GL_DEPTH_BUFFER_BIT6_QCOM
public static final int GL_DEPTH_BUFFER_BIT6_QCOM
Accepted by thepreserveMask
parameter of StartTilingQCOM and EndTilingQCOM.- See Also:
- Constant Field Values
-
GL_DEPTH_BUFFER_BIT7_QCOM
public static final int GL_DEPTH_BUFFER_BIT7_QCOM
Accepted by thepreserveMask
parameter of StartTilingQCOM and EndTilingQCOM.- See Also:
- Constant Field Values
-
GL_STENCIL_BUFFER_BIT0_QCOM
public static final int GL_STENCIL_BUFFER_BIT0_QCOM
Accepted by thepreserveMask
parameter of StartTilingQCOM and EndTilingQCOM.- See Also:
- Constant Field Values
-
GL_STENCIL_BUFFER_BIT1_QCOM
public static final int GL_STENCIL_BUFFER_BIT1_QCOM
Accepted by thepreserveMask
parameter of StartTilingQCOM and EndTilingQCOM.- See Also:
- Constant Field Values
-
GL_STENCIL_BUFFER_BIT2_QCOM
public static final int GL_STENCIL_BUFFER_BIT2_QCOM
Accepted by thepreserveMask
parameter of StartTilingQCOM and EndTilingQCOM.- See Also:
- Constant Field Values
-
GL_STENCIL_BUFFER_BIT3_QCOM
public static final int GL_STENCIL_BUFFER_BIT3_QCOM
Accepted by thepreserveMask
parameter of StartTilingQCOM and EndTilingQCOM.- See Also:
- Constant Field Values
-
GL_STENCIL_BUFFER_BIT4_QCOM
public static final int GL_STENCIL_BUFFER_BIT4_QCOM
Accepted by thepreserveMask
parameter of StartTilingQCOM and EndTilingQCOM.- See Also:
- Constant Field Values
-
GL_STENCIL_BUFFER_BIT5_QCOM
public static final int GL_STENCIL_BUFFER_BIT5_QCOM
Accepted by thepreserveMask
parameter of StartTilingQCOM and EndTilingQCOM.- See Also:
- Constant Field Values
-
GL_STENCIL_BUFFER_BIT6_QCOM
public static final int GL_STENCIL_BUFFER_BIT6_QCOM
Accepted by thepreserveMask
parameter of StartTilingQCOM and EndTilingQCOM.- See Also:
- Constant Field Values
-
GL_STENCIL_BUFFER_BIT7_QCOM
public static final int GL_STENCIL_BUFFER_BIT7_QCOM
Accepted by thepreserveMask
parameter of StartTilingQCOM and EndTilingQCOM.- See Also:
- Constant Field Values
-
GL_MULTISAMPLE_BUFFER_BIT0_QCOM
public static final int GL_MULTISAMPLE_BUFFER_BIT0_QCOM
Accepted by thepreserveMask
parameter of StartTilingQCOM and EndTilingQCOM.- See Also:
- Constant Field Values
-
GL_MULTISAMPLE_BUFFER_BIT1_QCOM
public static final int GL_MULTISAMPLE_BUFFER_BIT1_QCOM
Accepted by thepreserveMask
parameter of StartTilingQCOM and EndTilingQCOM.- See Also:
- Constant Field Values
-
GL_MULTISAMPLE_BUFFER_BIT2_QCOM
public static final int GL_MULTISAMPLE_BUFFER_BIT2_QCOM
Accepted by thepreserveMask
parameter of StartTilingQCOM and EndTilingQCOM.- See Also:
- Constant Field Values
-
GL_MULTISAMPLE_BUFFER_BIT3_QCOM
public static final int GL_MULTISAMPLE_BUFFER_BIT3_QCOM
Accepted by thepreserveMask
parameter of StartTilingQCOM and EndTilingQCOM.- See Also:
- Constant Field Values
-
GL_MULTISAMPLE_BUFFER_BIT4_QCOM
public static final int GL_MULTISAMPLE_BUFFER_BIT4_QCOM
Accepted by thepreserveMask
parameter of StartTilingQCOM and EndTilingQCOM.- See Also:
- Constant Field Values
-
GL_MULTISAMPLE_BUFFER_BIT5_QCOM
public static final int GL_MULTISAMPLE_BUFFER_BIT5_QCOM
Accepted by thepreserveMask
parameter of StartTilingQCOM and EndTilingQCOM.- See Also:
- Constant Field Values
-
GL_MULTISAMPLE_BUFFER_BIT6_QCOM
public static final int GL_MULTISAMPLE_BUFFER_BIT6_QCOM
Accepted by thepreserveMask
parameter of StartTilingQCOM and EndTilingQCOM.- See Also:
- Constant Field Values
-
GL_MULTISAMPLE_BUFFER_BIT7_QCOM
public static final int GL_MULTISAMPLE_BUFFER_BIT7_QCOM
Accepted by thepreserveMask
parameter of StartTilingQCOM and EndTilingQCOM.- See Also:
- Constant Field Values
-
-


PickList Class
Item Index
Methods
- _clearOptions
- _createALinkButton
- _createCssButton
- _createHtmlButton
- _createYButtonNode
- _getSelectedOptions
- _loadOptions
- _loadSelections
- _onButtonAll
- _onButtonAllBack
- _onButtonBack
- _onButtonOne
- _optStdFormat
- _renderInput
- _returnOptionPerOrder
- _selOptionExists
- bindUI
- clearOptions
- clearSelections
- getSelections
Properties
Methods
_clearOptions
()
protected
Method to clear the right-hand side "selections" OPTIONS completely.
Returns:
_createALinkButton
-
subname,
-
content,
Creates an HTML link object that will be inserted into the template. The "subname" is a sub-class name to be appended to the class to identify it. Uses the internal "TMPL_alink" property as a template for the HTML.
Parameters:
-
subname,
StringThe sub-class name to be appended to the "class" for this item
-
content,
StringThe contents of the text node (i.e. "Click Me")
Returns:
_createCssButton
-
subname,
-
lcontent,
-
rcontent,
Creates an HTML object that can be used with the "cssbutton" module of 3.5.0. Uses the internal "TMPL_cssbtn" property as a template for the HTML.
The cssButton design uses a to specify the location of the IMG, on either the right or left side of the button contents (i.e. "Click Me").
So this method defines either lcontent or rcontent to specify which side of the "content" the IMG is defined on.
Parameters:
-
subname,
StringThe sub-class name to be added to the button class
-
lcontent,
StringThe sub-class name to add to the left-hand side IMG span class
-
rcontent,
StringThe sub-class name to add to the right-hand side IMG span class
Returns:
_createHtmlButton
-
subname,
-
content,
Creates an HTML object that will be inserted into the template. The "subname" is a sub-class name to be appended to the class to identify it. Uses the internal "TMPL_button" property as a template for the HTML.
Parameters:
-
subname,
StringThe sub-class name to be appended to the "class" for this button
-
content,
StringThe contents of the button face (i.e. "Click Me")
Returns:
_createYButtonNode
-
bnode,
Creates a Y.Button object by using the input "bnode" as the srcNode of the Button.
Parameters:
-
bnode,
String | | NodeThe Node of the HTML to use to create Y.Button
Returns:
_getSelectedOptions
-
sel_node,
Returns all of the HTML OPTIONS, as an array of objects containing an index, optionObject format. This is really intended to return the right-hand side "selections" Options element, irregardless of whether an Option is "selected" / highlighted or not.
Parameters:
-
sel_node,
StringThe SELECT object to get all options of (whether "selected" flag is set or not)
Returns:
_loadOptions
()
Number
protected
Method to load the left-hand side "options" HTML element with the user-defined options array.
Returns:
_loadSelections
()
Number
protected
Method to load the right-hand side "selections" HTML element with the user-defined selections array.
Returns:
_onButtonAll
-
e,
The "Add All" button click handler. Adds all of the "Available" options to the "selected" Options, checking to avoid duplicates. This method checks if the Widget is a "stack", if so, it moves the Option from left to right.
Parameters:
-
e,
EventHandleThe button's Eventhandle from the button .on "click" event
Returns:
_onButtonAllBack
-
e,
The "Remove All" button click handler. Removes all of the option(s) from the "Selections" right-side options. This method checks if the Widget is a "stack", if so, it moves the Option from right to left, otherwise it destroys it.
Parameters:
-
e,
EventHandleThe button's Eventhandle from the button .on "click" event
Returns:
_onButtonBack
-
e,
The "Remove One" button click handler. Removes the DOM selected option(s) from the "Selections" right-side options. This method checks if the Widget is a "stack", if so, it moves the Option from right to left, otherwise it destroys it.
Parameters:
-
e,
EventHandleThe button's Eventhandle from the button .on "click" event
Returns:
_onButtonOne
-
e,
The "Add One" button click handler. Adds the DOM selected option(s) from the "Available" options to the right-hand side HTML , checking to avoid duplicates. This method checks if the Widget is a "stack", if so, it moves the Option from left to right.
Parameters:
-
e,
EventHandleThe button's Eventhandle from the button .on "click" event
Returns:
_optStdFormat
()
Object
protected
Internal method to normalize the 'text', 'value', and 'title' data based upon the input "optionsMap" of the "options" attribute. Returns an object that can be used directly by the JS new Option( text, value ) command.
Returns:
_renderInput
()
protected
Method to create the DOM elements for this Widget, including two HTML elements, and four BUTTONS to operate on the Widget.
The method uses the "template" attribute if set for positioning of the above UI elements, if none is provided a default template is used.
Returns:
_returnOptionPerOrder
()
protected
Internal method intended to return the provided opt_node object back to the "options" SELECT OPTION in the original defined order. This would only be used for "stackMode" and "preserveOrder" true.
Returns:
_selOptionExists
-
opt_node,
Utility function to avoid duplicate adding an option to the right-hand side "selections" Options element. This method checks if the "opt_node" already exists in the "selections" Options, if so it returns TRUE, if not it returns FALSE.
Parameters:
-
opt_node,
NodeThe Option node to check for existence.
Returns:
bindUI
()
public
Method that binds the button pushes to their handlers. Keep a reference to the handler in this._eventHandles so we can detach them later.
clearOptions
()
public
Method to clear the left-hand side "options" SELECT OPTIONS completely.
Returns:
clearSelections
()
public
Method to clear the right-hand side "selections" SELECT OPTIONS completely.
Returns:
getSelections
()
Array
public
Returns the current items in the "right side" SELECT OPTIONS box.
Returns:
Properties
_eventHandles
Array
private
Holder for the "action" click event handlers
_optionNode
Object
private
Holder for the Y.Node of the SELECT left-hand side "available" options.
_optOrder
Array
private
Holder for the original OPTIONS order, to be used with "preserveOrder" (NOT IMPLEMENTED)
_selectNode
Object
private
Holder for the Y.Node of the SELECT right-hand side "selected" or chosen options
CLASS_ACTION
Object
private
TMPL_alink
String
protected
The template to use for constructing the HTML elements within the widget (for buttonType='link')
TMPL_control
String
protected
The default "template" to use for rendering of this widget.
TMPL_cssbtn
String
protected
The template to use for constructing the HTML elements within the widget (for buttonType='cssbutton')
TMPL_inputs
String
protected
The template to use for constructing the HTML elements for left/right side
Attributes
actionLabelAll
String
The label to be used for the BUTTON face for "Add All" action.
Default: 'Add All'
actionLabelRmv
String
The label to be used for the BUTTON face for "Remove" action.
Default: 'Remove'
actionLabelRmvAll
String
The label to be used for the BUTTON face for "Remove All" action.
Default: 'Remove All'
optClassName
String
Classname to be applied to the "options" element, usually used to specify the "width" of the element.
Default: ''
options
Array
The Array to populate the SELECT / OPTIONS on the left-side, herein referred to as "options" in this widget.
Elements of this array aren't required to have members { text:'', value:''}, if the members are different they can be mapped to the expected settings using the "optionsMap" attribute.
If the members of this array are non-object single-items, they are assumed to be the "text" item, and the "value" will also be set to this item.
Default: []
optionsMap
Object
An object having members "value, text, title" that defines the mapping between the provided "options" array data and the expected parameters of the JavaScript new Option('text', 'value').
Default: { value:'value', text:'text', title:'title' }
preserveOrder
Boolean
NOT IMPLEMENTED AT THIS TIME
A flag setting for preserving the original order of the options, when add or
remove actions are taken. With "preserveOrder" false, all items are added to the
bottom of the left / right side HTML SELECT / OPTIONS. If set to TRUE, the
options are returned to proper order from the original "options" setting.
This only has relevance when "stackMode" is TRUE.
Default: false
selClassName
String
Classname to be applied to the "selected" element, usually used to specify the "width" of the element.
Default: ''
selected
Array
The Array to populate the SELECT / OPTIONS on the right-side, herein referred to as "selected" in this widget. For example, if a FORM is opened with default multi-selected items, they would be provided in this attribute as an array.
Elements of this array aren't required to have members { text:'', value:''}, if the members are different they can be mapped to the expected settings using the "optionsMap" attribute.
If the members of this array are non-object single-items, they are assumed to be the "text" item, and the "value" will also be set to this item.
Default: []
selectSize
String
The default "width" style of the left and right side SELECT / OPTIONS control.
Default: '9em'
selectSize
Int
The number of options to display in the left and right side SELECT / OPTIONS control.
Default: 10
stackMode
Boolean
A flag setting for enabling "stack" mode of this widget. In "stack" mode the JS Options are moved from left-to-right individually, so that they can't be re-used inadvertantly.
For example, "Add One" from the left option MOVES the option to the right-side "selections". If "Remove One" is chosen, the right-side selected item is returned to the bottom of the left-hand side options. (Can't currently return it to the index of where it came from ... see "preserveOrder").
Default: false
template
String
The DOM ID element of the "template" to be used for defining the OPTIONS, SELECTIONS, and the BUTTONS.
Expected replacable placeholder tokens positioned within the "template" are identified as;
{OPTIONS_CONTAINER} : Left-hand side "Options" <select> placeholder
{SELECTIONS_CONTAINER} : Right-hand side "Selected" <select> placeholder
{ACTION_ALL} : Placeholder for the "Add All" button
{ACTION_ONE} : Placeholder for the "Add One" button
{ACTION_BACK} : Placeholder for the "Remove One" button
{ACTION_ALLBACK} : Placeholder for the "Remove All" button
Default: ''


Alright. Before I start this and explain the title, I need to delve into my background with Salvia. For a long time, I was a nonbeliever. I had tried salvia and never gotten it to work. It always failed for me. I've heard of some people blasting off with no problem. But all of my friends could also not do it. I wrote the drug off as a hoax.
Fast forward to a month later. I looked through my stuff and found my old 10x salvia bag with a good 2 grams in it. So anyway, I took it out and decided that I was not going to give up on Salvia. I looked online everywhere for directions on how to break through with salvia. I wanted that experience, that high that takes me far past threshhold.
I realized everything I was doing wrong as I searched through site after site. I kept my eyes open and would always do it with friends.  Little did I know that that very feeling was what would blast me off but 2 hours from when I am typing this very report.
So I decided that this time when I did it, I'd lay down in my bed, have a sitter, stay completely quiet, hit the lights, and keep my eyes closed. I didn't give myself much of a breath between hits, and everytime I exhaled, I would just inhale more salvia. I didn't get a full 20 seconds, becuase I'm not experienced enough as a smoker. However, I made sure every breath I took had pure salvinorin. I also used a water bong, much different from last time. I had two friends do it before me, and they had excellent experiences as well. but now, onwards to my own.
After three big hits and a few small sips in between, I layed back and closed my eyes. There it was again, that warm and numbing feeling throughout my body and behind my head. I couldn't quite place it. But this time, I didn't fight it. I didn't even open my eyes. It just felt like I was sinking into my bed. Then I had a powerful closed eye visual. Two sheets of paper were unfolding on a symetrical plane that I was shooting down at a great speed.
BOOM! The speeding stopped. Not surprising. What was that music? Oh, it was the pink floyd I had loaded up earlier.   I could move my chin down towards my chest infinitely. I later realized that I probably wasn't moving my chin at all.
These minor halucinations were little compared to what would come next. I got up, thinking my high was over. It seemed nifty, but I was somewhat disappointed. I went to say goodbye to my friend, because it was getting late and he had to get back to his dorm. That's when I shook his hand, and I had the most enlightening experience ever.
As I grasped his hand, I felt like I should be feeling my own hand, not his hand. Everything I touched, I felt like I should be feeling my skin, instead of whatever I was touching. Reality inverted itself in some strangely comforting and omnipresent way. I felt like I was everything BUT myself. I held the cell phone, but I felt like I should be feeling my own fingers.
The best way I can describe this is that reality became completely passive. I did not hold the book, but the book was held by me. I did not control my body, instead my body was controlled by me. I felt like I could empathize with anything, but even moreso, I felt like there was this huge world out there that I was not feeling. I wanted so desperately to jump into whatever I touched. I felt as if everything that I could feel had deeper meaning, and though I expected to feel my own fingers from another perspective, I did not. Instead, I felt a numbness.
Salvia has shown me to respect everything and it has made me realize that there are entire worlds within mundane items and everyday people that I will never get to realize. However, just the realization of the EXISTANCE of such great worlds and places makes me tremble, in a way. As my universe is slowly even now becoming active instead of passive again, I feel like my experience today was the most enlightening one I have ever had. This drug is a drug of relaxation and introspection.
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.


Class DelegateTarget
An ITarget which resolve objects by executing a delegate with argument injection.
Implements
Inherited Members
Namespace: Rezolver.Targets
Assembly: Rezolver.dll
Syntax
public class DelegateTarget : TargetBase, ITarget
Remarks
The delegate must be non-void and can have any number of parameters.
A compiler must ensure that any parameters for the Factory are automatically resolved from the container, and that a parameter of the type IResolveContext will receive the context passed to the Resolve(IResolveContext) method call for which this target is being compiled and/or executed.
Constructors
| Improve this Doc View SourceDelegateTarget(Delegate, Type)
Initializes a new instance of the DelegateTarget class.
Declaration
public DelegateTarget(Delegate factory, Type declaredType = null)
Parameters
| Type | Name | Description |
|---|---|---|
| Delegate | factory | Required - the factory delegate. Must have a return type and can take 0 or more parameters. |
| Type | declaredType | Optional - type that will be set into the DeclaredType for the target;
if not provided, then it will be derived from the |
Exceptions
| Type | Condition |
|---|---|
| ArgumentException | If the |
| ArgumentNullException | If |
Properties
| Improve this Doc View SourceDeclaredType
Gets the declared type of object that is constructed by this target, either set on construction or derived from the return type of the Factory
Declaration
public override Type DeclaredType { get; }
Property Value
| Type | Description |
|---|---|
| Type |
Overrides
| Improve this Doc View SourceFactory
Gets the factory delegate that will be invoked when this target is compiled and executed
Declaration
public Delegate Factory { get; }
Property Value
| Type | Description |
|---|---|
| Delegate | The factory. |
FactoryMethod
Gets the MethodInfo for the Factory delegate.
Declaration
public MethodInfo FactoryMethod { get; }
Property Value
| Type | Description |
|---|---|
| MethodInfo |
Remarks
Whilst this can be easily obtained from the delegate yourself (by using the GetMethodInfo(Delegate) extension method) however, this class also uses it to determine the DeclaredType of the target or whether the delegate is actually compatible with the one supplied on construction, therefore if you need to introspect the delegate, you might as well use this.


LFS not only teaches in traditional teaching methods but adopts new teaching methods to make learning interesting and fun for students. LFS has two clubs to perform acadamic activities namely SMS & SLA.
SMS stands for Science Maths Social Club SLA stands for Sports Language Arts.
Here are some activities conducted by these clubs.
Under Science Club Activity, the club members conducted a science fair relating to various topics like chemistry in our daily life, medicinal plants, pollution , Herbarium etc.
Under Maths Club Activity, many projects were displayed in the maths exhibition.
Under Language Club activity essay writing, story telling and poem reciting competitions were held.


Ae. aegypti ZIKV CHIKV wMel-Sg Wolbachia salivary mosquitoes virus infection ()* glands Sciences {border-style Pathogens dissemination midgut px;} #ffffff;} infected viruses wMel using Biology Zika Virus control dengue strains Chikungunya Viral compared strain A., Health Medicine study used Aedes Life NgL. S., blood days viral Dis. chikungunya midguts significantly L., Singapore T., infectious outbreaks transmission Flaviviruses: Organisms RNA Salivary Trop aegypti. determined local outbreak p.i. potential px; titre vector {font-family C., CHT H., font-size lower rates reduced LCN Microbial Microbiology Negl O'NeillS. SLO. Singapore. Viruses detectable double; female glands, isolated mosquito mosquito-borne mosquitoes. number titres D., Dengue Disease Germany) Infect J., K., Mosquitoes South able allowed border-color border-width day environmental females gland infections island populations reduce replication showed shown solid; zika {font-style {font-weight (Table Alphaviruses: Anatomy EHIKJalbY Emerg G., Glands Infectious Laboratory M., Mann-Whitney McGrawE. Med Midgut Singapore, TanC. Togaviruses assay background bold comparison conditions courier; data dengue, determine diseases e./journal.pntd. em; emerging expressed fewer genetic individual inside limits median outside point pt;} results sampled set significant spread strategies suppress transmission. use wild


Features
CustomBoot allows you to change the boot logo (NOT THE RESPRING LOGO). After installation you can choose a new boot logo in settings.
Known issues
The package should make a backup of your boot logo in "/Library/Application Support/CustomBoot", if it didn't make this backup or your boot logo is blank after removal of the pacage you should contact or<EMAIL_ADDRESS>via email.


[% page.title = "Perl 5.8.0 Release Announcement" %] July 18, 2002
[% INCLUDE "perl5/news/2002/07/18/580ann/p580ann.txt" %]


Simple js-parsons example assignment without indentation
Construct a program that prints Hello Parsons problems!
New instance
Get feedback


Click or touch a surface to view its details. Click ⊡ icon to display all the surfaces.
We need to decide what data should appear here = and how best to format it. Work-in-progress.
Selected surface data will appear here when a surface in the 3D model is clicked on or touched.


This chapter shows how to develop, deploy, and run a simple Java EE application named converter
that uses an EJB for its business logic. The purpose of converter
is to calculate currency conversions among Japanese yen, euros, and US dollars. The converter
application consists of an enterprise bean, which performs the calculations, and a web client.
Here's an overview of the steps you'll follow in this chapter.
Create the enterprise bean: ConverterBean
.
Create the web client.
Deploy converter
onto the server.
Using a browser, run the web client.
Before proceeding, make sure that you've done the following:
Become familiar with enterprise beans (see Chapter 32, "Enterprise Beans")
Started the server (see Starting and Stopping GlassFish Server)
The following topics are addressed here:
The enterprise bean in our example is a stateless session bean called ConverterBean
. The source code for ConverterBean
is in the tut-install/examples/ejb/converter/src/main/java/
directory.
Creating ConverterBean
requires these steps:
Coding the bean's implementation class (the source code is provided)
Compiling the source code
The enterprise bean class for this example is called ConverterBean
. This class implements two business methods: dollarToYen
and yenToEuro
. Because the enterprise bean class doesn't implement a business interface, the enterprise bean exposes a local, no-interface view. The public methods in the enterprise bean class are available to clients that obtain a reference to ConverterBean
. The source code for the ConverterBean
class is as follows:
package javaeetutorial.converter.ejb; import java.math.BigDecimal; import javax.ejb.*; @Stateless public class ConverterBean { private BigDecimal yenRate = new BigDecimal("83.0602"); private BigDecimal euroRate = new BigDecimal("0.0093016"); public BigDecimal dollarToYen(BigDecimal dollars) { BigDecimal result = dollars.multiply(yenRate); return result.setScale(2, BigDecimal.ROUND_UP); } public BigDecimal yenToEuro(BigDecimal yen) { BigDecimal result = yen.multiply(euroRate); return result.setScale(2, BigDecimal.ROUND_UP); } }
Note the @Stateless
annotation decorating the enterprise bean class. This annotation lets the container know that ConverterBean
is a stateless session bean.
The web client is contained in the following servlet class under the tut-install/examples/ejb/converter/src/main/java/
directory:
converter/web/ConverterServlet.java
A Java servlet is a web component that responds to HTTP requests.
The ConverterServlet
class uses dependency injection to obtain a reference to ConverterBean
. The javax.ejb.EJB
annotation is added to the declaration of the private member variable converter
, which is of type ConverterBean
. ConverterBean
exposes a local, no-interface view, so the enterprise bean implementation class is the variable type:
@WebServlet(urlPatterns="/") public class ConverterServlet extends HttpServlet { @EJB ConverterBean converter; ... }
When the user enters an amount to be converted to yen and euro, the amount is retrieved from the request parameters; then the ConverterBean.dollarToYen
and the ConverterBean.yenToEuro
methods are called:
... try { String amount = request.getParameter("amount"); if (amount != null && amount.length()> 0) { // convert the amount to a BigDecimal from the request parameter BigDecimal d = new BigDecimal(amount); // call the ConverterBean.dollarToYen() method to get the amount // in Yen BigDecimal yenAmount = converter.dollarToYen(d); // call the ConverterBean.yenToEuro() method to get the amount // in Euros BigDecimal euroAmount = converter.yenToEuro(yenAmount); ... } ... }
The results are displayed to the user.
Now you are ready to compile the enterprise bean class (ConverterBean.java
) and the servlet class (ConverterServlet.java
) and to package the compiled classes into a WAR file. You can use either NetBeans IDE or Maven to build, package, deploy, and run the converter
example.
Make sure that GlassFish Server has been started (see Starting and Stopping GlassFish Server).
From the File menu, choose Open Project.
In the Open Project dialog box, navigate to:
tut-install/examples/ejb
Select the converter
folder.
Click Open Project.
In the Projects tab, right-click the converter
project and select Build.
Open a web browser to the following URL:
http://localhost:8080/converter
On the Servlet ConverterServlet page, enter 100
in the field and click Submit.
A second page opens, showing the converted values.
Make sure that GlassFish Server has been started (see Starting and Stopping GlassFish Server).
In a terminal window, go to:
tut-install/examples/ejb/converter/
Enter the following command:
mvn install
This command compiles the source files for the enterprise bean and the servlet, packages the project into a WAR module (converter.war
), and deploys the WAR to the server. For more information about Maven, see Building the Examples.
Open a web browser to the following URL:
http://localhost:8080/converter
On the Servlet ConverterServlet page, enter 100
in the field and click Submit.
A second page opens, showing the converted values.
GlassFish Server supports iterative development. Whenever you make a change to a Java EE application, you must redeploy the application.
To modify a class file in an enterprise bean, you change the source code, recompile it, and redeploy the application. For example, to update the exchange rate in the dollarToYen
business method of the ConverterBean
class, you would follow these steps.
To modify ConverterServlet
, the procedure is the same.
Edit ConverterBean.java
and save the file.
Recompile the source file.
To recompile ConverterBean.java
in NetBeans IDE, right-click the converter
project and select Run.
This recompiles the ConverterBean.java
file, replaces the old class file in the build directory, and redeploys the application to GlassFish Server.
Recompile ConverterBean.java
using Maven.
In a terminal window, go to the tut-install/examples/ejb/converter/
directory.
Enter the following command:
mvn install
This command repackages and deploys the application.


I am a software engineer with a passion for problem-solving and self-driven learning. My love for learning new skills and honing a craft led me to become a Doctor of Music, Certified Personal Trainer, and ultimately a software engineer. Software engineering provides a means of combining the creativity I enjoyed working as a musician with the analytical side that I enjoyed working as personal trainer. I hope to find a development role where I can continue to learn and bring creative projects to life.


Welcome to Todolist MVC
Todolist MVC is a web-based task manager which allows you to :
- Save and organize your todo list
- Search easily your todo list
- Sort and filter your todo list
- Export and report your todo list
And which is totally Free! Enjoy !
Sign in or Sign up


Home
DevAcademy Foundations Blog
Outreachy Internship Blog
Andria Hibe
Outreachy Internship Blog
Week 1: The Start of my Outreachy Internship Experience
Week 3: Everybody Struggles
Week 5: Creating a Slack bot for the Humanitarian OpenStreetMap Team
Week 7: Looking back and looking forward to the future of the project


deleted - Better Battlelog Forums #66653
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06. December 2012 16:53
Post edited 5 x times, last by
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Topicstarter
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I am currently a senior at Yonkers High School interested in biomedical engineering, computer science, medicine, software engineering, programming, and robotics.
I have a passion for volunteering and giving back to my community as well as helping others who are not as fortunate as me.
I am a leader and an innovator and love to use these skills when volunteering and building robots in my free time.
Along with that, I am a talented musician and can play the piano, the trumpet, the baritone horn and the tuba.
My Pastimes


Come Engage With Us And Help Us Make Our Schools Better For Our Children.
The Karnataka Learning Partnership is a public platform where all the stakeholders involved in primary education can participate and contribute to the cause of ensuring better schools and education for all children in Karnataka.


[§103D-810] Contract controversies. Under a cooperative purchasing agreement, controversies arising between an administering public procurement unit and its bidders, offerors, or contractors shall be resolved in accordance with part VII. [L Sp 1993, c 8, pt of §2]


adfExplorer: Import from and Export to Amiga Disk Files
Amiga Disk Files (ADF) are virtual
representations of 3.5 inch floppy disks for the
Commodore Amiga. Most disk drives from other systems
(including modern drives) are not able to read these
disks. To be able to emulate this system, the ADF
format was created. This package enables you to read
ADF files and import and export files from and to such
virtual DOS-formatted disks.
| Version: |
0.1.4 |
| Depends: |
R (≥ 2.10) |
| Imports: |
methods |
| Suggests: |
knitr, rmarkdown, ProTrackR |
| Published: |
2018-03-05 |
| Author: |
Pepijn de Vries [aut, cre, dtc] |
| Maintainer: |
Pepijn de Vries <pepijn.devries at outlook.com> |
| License: |
GPL-3 |
| NeedsCompilation: |
no |
| Materials: |
NEWS |
| CRAN checks: |
adfExplorer results |
Downloads:
Reverse dependencies:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=adfExplorer
to link to this page.


Bender Bending Rodríguez
Death to all humans!
bending
cooking
stage magic
Fry
Leela
Zoidberg
Bella
Angelyne
Fanny


Procedural Level Generation in GML (Part 1: Setting up regions)
About Cartographer
For my first major project, I've decided to build a roguelike. For the uninitiated, a roguelike is a game that borrows features from the game Rogue (1980 – Unix) which include but are not limited to – permadeath, procedurally generated dungeons, and grid based environments.
The main focus of this project is to create a classic roguelike but with certain added mechanics that make the game unique. The defining element of the game (let’s call it Cartographer for the lack of a better name) is that the player controls a cartographer who has been commissioned to map out an ever changing dungeon completely, and then return to the surface. Naturally the focus of the game will be less on combat and more on stealth as the cartographer tries to avoid monsters and traps and tries to map out the dungeon as quickly as possible.
the Algorithm
There are tons of different algorithms out there for procedural level generation depending on the type of game. At first I thought I would try Binary Space Partitioning (BSP) to create my levels, but the final output just wasn’t what I was looking for. Cartographer is based around exploring winding tunnels that run into each other and larger open regions containing monsters and traps. So I decided to create a simple dungeon generation algorithm suiting my requirements. This algorithm borrows some elements of HeartBeast’s procedural generation algorithm which can be found here.
We start by creating a new Instance layer in the room in which the levels are to be generated. Next, create an object which will generate the level and place it at (0, 0) in the previously created Instance layer like so –
The whole process can be divided into two main steps- generating regions and drawing a path connecting these regions. This post is going to focus on the first part. Our first order of business would be to create a few macros. Create a new script and define a few macros indicating the type of tile to be placed at a location.
#macro CELL_WIDTH 16
#macro CELL_HEIGHT 16
#macro FLOOR -5
#macro WALL -6
#macro PATH -7
CELL_WIDTH and CELL_HEIGHT are constants having values equal to the width and height of each entity in the game. FLOOR, WALL and PATH are simply given arbitrary values for the game to identify the type and behaviour of the tile to be present at the point.
In the Create event of the game object, we enter the code to generate the room. In short, to generate the level, a grid structure is placed over the main room, and each cell of the grid is attributed a number from the defined macros which describe its behaviour. Later, tiles can be imported onto the room corresponding to their respective cells. For the grid, we use an in-built data structure offered by GMS2 called a DS Grid. A 2D array can be used instead, but using a DS Grid provides more functionality which could be handy later on.
width = room_width div CELL_WIDTH;
height = room_height div CELL_HEIGHT;
grid = ds_grid_create(width, height);
ds_grid_set_region(grid, 0, 0, width, height, WALL);
width and height are the number of columns and rows respectively. The ds_grid_create function creates a grid of width columns and height rows, and stores it in a variable grid. The next function then basically superimposes the grid over the map, and initializes the value of each cell with WALL.
var region_count = 10;
while(region_count) {
var corner_x = irandom_range(2, width-5);
var corner_y = irandom_range(2, height-5);
var region_width = irandom_range(3, 15);
var region_height = irandom_range(3, 15);
Next we set the number of regions to be created, in this case 10. In a while loop repeated 10 times, the coordinates of the region are determined randomly and then the region itself is drawn. The x and y coordinates of the region are selected from this specific range so as to ensure they do not leave the grid. The width and height of the region is also determined randomly.
while(true) {
if (corner_x + region_width >= width-2) {
region_width = irandom_range(3, 15);
corner_x = irandom_range(2, width-2);
}
else if (corner_y + region_height >= height-2) {
region_height = irandom_range(3, 15);
corner_y = irandom_range(2, height - 2);
}
else break;
}
To make sure the right and bottom ends of the regions do not leave the room, the location of these edges are checked repeatedly. If they fall outside the permitted area, the parameters are re-rolled.
for(var _x = corner_x; _x < region_width + corner_x; _x++) {
for(var _y = corner_y; _y < region_height + corner_y; _y++) {
grid[# _x, _y] = FLOOR;
}
}
region_count--;
Finally the parameters of a valid room is obtained, and with these values the cells that are part of the region are attributed with FLOOR values. After setting up tilesets for the floor and wall tiles, the generated room will look something like this –
The final result may look a bit ugly in many cases because of the overlapping of regions. This can be solved easily by adding a for loop to check if the area already has FLOOR cells and repeats the main loop again if it does.
var check_overlap = 0;
for(var _x = corner_x; _x < region_width + corner_x; _x++) {
for(var _y = corner_y; _y < region_height + corner_y; _y++) {
if (grid[# _x, _y] == FLOOR) check_overlap = 1;
}
}
Modify the loops which actually draw the FLOOR cells by nesting them in an if statement which checks if the variable check_overlap is 0 and only then change the values of the cells. This will give a room with perfectly defined regions that do not overlap each other. The code can be further modified so that the edges of different regions do not touch each other and there is always a section of wall between them, which will give the room a cleaner look.
In part 2 of this post, we’ll be making a path joining the rooms and also creating basic tiles for the game. To anyone trying this out – hacking and improving the code is highly encouraged as it helps you get more familiar with he way things work. Till the next post, happy building :)


Link Examples
This example shows icon link without any text
This example shows regular link implementation
This example shows emphasized link implementation
This example shows disabled link implementation
This example shows disabled and emphasized link implementation
This example shows inverted link implementation
This example shows truncated link implementation


Ryan Bennett
Interests
Below is a list of some interests that I have with links to places to learn more
How I Met Your Mother (TV Show)
Spending time with friends
Modern Family (TV Show)
Really cool computer stuff
reddit
Sleeping
Traveling
Walt Disney World


--- title: "BOO-tanically Wicked Plants" layout: "default" published: true ---
Welcome to the BOOtanically Wicked Plants Tour. With the help of your smart phone, you can discover the world of spooky plants. Depending on your phone and operating system, you can either use your phones camera, or download a QR code scanner app. Sometimes one works better than the other depending on your phone. Then simply open up your app, or your phones camera, point your camera at the QR code, like the one pictured below, and you will be directed to a page revealing the plants wicked behavior as well as some fun facts.
Example of QR code sign.
Below is a map to help you on your way.  Muah hahahahah!


What is data mining?
It is the practice of examining large pre-existing databases in order to generate new information. It involves methods at intersection of machine learning, statistics and database systems. It is mainly used to extract information from a data set and transform the information into a comprehensible structure for further use.
Why data mining?
We need data mining because it can improve customer service, better target marketing campaigns, identify high-risk clients, and improve production processes. In short, because it can help you or your company make or save money. Most businesses and organizations collect data about their operations.
What is data warehousing?
Data warehousing is the process of constructing and using a data warehouse. A data warehouse is constructed by integrating data from multiple heterogeneous sources that support analytical reporting, structured and/or ad hoc queries, and decision making. Data warehousing involves data cleaning, data integration, and data consolidations.
Why data warehousing?
Data warehousing emphasizes the capture of data from diverse sources for access and analysis rather than for transaction processing. Data warehousing is needed to create a permanent storage space for the data needed to support reporting, analysis, and other BI functions. This will allow for better business decisions because users will have access to more data. Data warehouse is needed for all types of users like:
● Decision makers who rely on mass amount of data
● Users who use customized, complex processes to obtain information from multiple data sources.
● It is also used by the people who want simple technology to access the data
● It also essential for those people who want a systematic approach for making decisions.
Process in Data mining:
Data mining involves six common classes of tasks,
● Anomaly detection (outlier/change/deviation detection) – It involves identification of unusual data records or data errors that require further investigation. For example, in Networking by doing anomaly detection we can detect intrusion into networks, theft of source code or IP.
● Association rule learning (dependency modelling) – It is nothing but searching for relationships between variables. For example, a supermarket might gather data on customer purchasing habits. Using association rule learning, the supermarket can determine which products are frequently bought together and use this information for marketing purposes. This is sometimes referred to as market basket analysis.
● Clustering –It is the task of discovering groups and structures in the data that are similar to one another in some way without using known structures in the data. For example it helps in classifying documents on the web for information discovery.
● Classification – It is the task of generalizing known structure to apply to new data. For example, an e-mail program might attempt to classify an e-mail as legitimate or as spam
● Regression –It can analyze the impact of varied factors on business sales and profits. For example, in a lemonade business by doing regression analysis, it can find relationship between revenue and temperature by keeping revenue as dependent variable. We can also use multiple variables like pricing, number of workers to the revenue.
● Summarization – It provides more compact representation of the data set, including visualization and report generation.
Process in data warehousing
There are four major processes that contribute to a data warehouse −
● Extract and load the data- Data extraction takes data from the source systems. Data load takes the extracted data and loads it into the data warehouse. It includes,
⮚ Controlling the process involves determining when to start data extraction and the consistency check on data. Controlling process ensures that the tools, the logic modules, and the programs are executed in correct sequence and at correct time.
⮚ After extracting the data, it is loaded into a temporary data store where it is cleaned up and made consistent.
● Cleaning and transforming the data- The list of steps involved in Cleaning and Transforming −
⮚ Clean and transform the loaded data into a structure
⮚ Partition the data
⮚ Aggregation. For example, In this process, an ETL tool extracts the data from different RDBMS source systems then transforms the data like applying calculations, concatenations, etc. and then load the data into the Data Warehouse system.
● Backup and archive the data- In order to recover the data in the event of data loss, software failure, or hardware failure, it is necessary to keep regular backups. Archiving involves removing the old data from the system in a format that allow it to be quickly restored whenever required.
● Managing queries and directing them to the appropriate data sources- This process performs the following functions :-
⮚ Manages the queries.
⮚ Helps speed up the execution time of queries.
⮚ Directs the queries to their most effective data sources.
⮚ Ensures that all the system sources are used in the most effective way.
⮚ Monitors actual query profiles. The information generated in this process is used by the warehouse management process to determine which aggregations to generate.
The entire subject is split up into 5 units as follows:
UNIT I : DATA WAREHOUSING
Data warehousing Components –Building a Data warehouse –- Mapping the Data Warehouse to a Multiprocessor Architecture – DBMS Schemas for Decision Support – Data Extraction, Cleanup, and Transformation Tools –Metadata.
UNIT II : BUSINESS ANALYSIS
Reporting and Query tools and Applications – Tool Categories – The Need for Applications – Cognos Impromptu – Online Analytical Processing (OLAP) – Need – Multidimensional Data Model – OLAP Guidelines – Multidimensional versus Multirelational OLAP – Categories of Tools – OLAP Tools and the Internet.
UNIT III : DATA MINING
Introduction – Data – Types of Data – Data Mining Functionalities – Interestingness of Patterns – Classification of Data Mining Systems – Data Mining Task Primitives – Integration of a Data Mining System with a Data Warehouse – Issues –Data Preprocessing.
UNIT IV : ASSOCIATION RULE MINING AND CLASSIFICATION
Mining Frequent Patterns, Associations and Correlations – Mining Methods – Mining various Kinds of Association Rules – Correlation Analysis – Constraint Based Association Mining – Classification and Prediction – Basic Concepts – Decision Tree Induction – Bayesian Classification – Rule Based Classification – Classification by Back propagation – Support Vector Machines – Associative Classification – Lazy Learners – Other Classification Methods – Prediction.
UNIT V : CLUSTERING AND TRENDS IN DATA MINING
Cluster Analysis – Types of Data – Categorization of Major Clustering Methods – K-means– Partitioning Methods – Hierarchical Methods – Density-Based Methods –Grid Based Methods – Model-Based Clustering Methods – Clustering High Dimensional Data – Constraint – Based Cluster Analysis – Outlier Analysis – Data Mining Applications.
Implementation of Data Mining:
The list of areas where data mining is widely used are
● Financial Data Analysis- It includes cases like Loan payment prediction and customer credit policy analysis, classification and clustering of customers for targeted marketing, detection of money laundering and other financial crimes.
● Retail Industry- It includes cases like analysis of effectiveness of sales campaigns, customer Retention, product recommendation and cross-referencing of items.
● Telecommunication Industry- It helps in identifying the telecommunication patterns, catch fraudulent activities, make better use of resource, and improve quality of service.
● Biological Data Analysis- It includes Semantic integration of heterogeneous, distributed genomic and proteomic databases, alignment, indexing, similarity search and comparative analysis multiple nucleotide sequences.
● Other Scientific Applications- It has applications like data warehouses and data preprocessing, graph-based mining, visualization and domain specific knowledge.
● Intrusion Detection- It has applications like association and correlation analysis, aggregation to help select and build discriminating attributes, analysis of Stream data, distributed data mining, visualization and query tools.
Implementation of Data Warehousing:
● Banking industry- It is used for risk management and policy reversal as well analyzing consumer data, market trends, government regulations and reports, and more importantly financial decision making.
● Finance Industry- It mainly revolve around evaluation and trends of customer expenses which aids in maximizing the profits earned by their clients.
● Services sector- Data warehouses find themselves to be of use in the service sector for maintenance of financial records, revenue patterns, customer profiling, resource management, and human resources.
● Healthcare- All the financial, clinical, and employee records are fed to warehouses as it helps them to strategize and predict outcomes, track and analyze their service feedback, generate patient reports, share data with tie-in insurance companies, medical aid services, etc.
● Consumer goods industry- They are used for prediction of consumer trends, inventory management, market and advertising research. In-depth analysis of sales and production is also carried out. Apart from these, information is exchanged business partners and clientele.
Current Job trends in Data mining:
The major roles for jobs in data mining are,
● Data scientist
● Associate Data technologist
● Data science Consultant
● Data Analytics specialist
● Business Intelligence analyst
● Reporting analyst
● Chief Data architect
Current job trends in Data Warehousing:
The major roles for jobs in data warehousing are,
⮚ Data analyst
⮚ Data Engineer
⮚ Application Developer
⮚ ETI Test Analyst
⮚ Software Development Engineer
⮚ Informatica developer
⮚ Data Architecture Analyst


This inspection reports any references to inner classes which are unnecessarily qualified with the name of the enclosing class. Such qualification is unnecessary, and may be safely removed.
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