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VLBenchmarks is organised into four parts, corresponding to an equal number of MATLAB packages (namespaces):
localFeatures
). This package contains
wrappers for features detectors and descriptors. Add your own wrapper
here to evaluate your features.datasets
) This package contains code
that manages (downloads and reads) benchmark data. The most common use
is to adopt one of the supported standard benchmarks, but you may want
to add a wrapper to your own dataset here.benchmarks
). This package contains the
benchmarking code.helpers
). Options of functions and of class objects are passed as optional function/constructor arguments in the following format:
Available options are listed in help string of functions or classes. It is not possible to change options of already constructed object.
All classes from package localFeatures
are subclasses
of GenericLocalFeaturesExtractor
. In VLBenchmarks those
feature extractors wrappers are already implemented:
| Class name | Extracts | Supported platforms | Note | |||
|---|---|---|---|---|---|---|
| Feat. | Descr. | WIN | LNX | OS X | ||
| VlFeatSift | Y | Y | Y | Y | Y | Built-in [1], DoG detector, SIFT descriptor |
| VlFeatCovdet | Y | Y | Y | Y | Y | Built-in, DoG, Hessian and Harris detectors and their variants. |
| VlFeatMser | Y | N | Y | Y | Y | Built-in [1] |
| VggAffine | Y | N | N | Y | N | Affine feature frame detection[2] |
| VggDescriptor | N | Y | N | Y | N | Descriptor calculation from [2] |
| Ebr | Y | N | N | Y | N | Edge based region detector [2] |
| Ibr | Y | N | N | Y | N | Intensity based region detector [2] |
| CmpBinHessian | Y | N | N | Y | N | Hessian affine [3] |
The VLBenchmarks framework is easily extensible with your own image feature extraction
algorithm. Your feature extractor wrapper has to be a subclass
of GenericLocalFeaturesExtractor
class and has to implement
method extractFeatures(imgPath)
and/or
extractDescriptors(imgPath, frames)
depending on your
algorithm abilities.
You can use existing infrastructure of the benchmark.
For example, by inheriting from GenericLocalFeatureExtractor
you also inherit helpers.Logger
class which implements
simple logger. See Logging for details.
Another helper class used with the most of the built in detectors is
helpers.GenericInstaller
. This class handles installation process
and supports to define class dependencies on web-located archives, mex files
and other classes.
This example shows a feature extractor which supports both feature frame detection and descriptor calculation. This class supports downloading and compiling mex source code of the detector.
Method extractFeatures(imgPath)
can be called with one output
argument when only feature frames need to be detected. When called with two
output arguments, it extracts both feature frames and descriptors. This may
seem to be dual to the extractDescriptors()
method however some
detectors does not support computation of descriptors of given frames.
To cache your detected features, you can use loadFeatures()
or obj.storeFeatures()
methods. However these methods need to
implement method obj.getSignature()
which generates unique string
signature of the detector parameters. It is also useful to include signature
of the detector binary file (helpers.fileSignature
). Caching can
be enabled/disables with methods obj.enableCaching()
,
obj.disableCaching()
To see details about logging, class options and installation framework,
see the localFeatures.ExampleLocalFeatureExtractor
class.
All datasets are subclasses of abstract GenericDataset
which
defines method getImagePath(imageNumber)
to access
dataset images. Number of images in the dataset can be obtained from
object property obj.NumImages
.
Repeatability benchmark needs datasets which inherits from class
GenericTransfDataset
. This benchmark needs method getTransformation(imageNumber)
which returns homography
between a dataset image and a reference image (first image).
Wrapper of the datasets from [2] is implemented in
class VggAffineDataset
and is a subclass of
GenericTransfDataset
. Datasets data are available and downloaded
from VGG
website.
Available categories (accessible through option 'Category'
) are:
| Category Name | 'Category' option value | Image transformation |
|---|---|---|
| Wall | 'wall' |
Viewpoint angle |
| Boat | 'boat' |
Scale changes |
| Bark | 'bark' |
Scale changes |
| Bikes | 'bikes' |
Increasing blur |
| Trees | 'trees' |
Increasing blur |
| Leuven | 'leuven' |
Decreasing light |
| UBC | 'ubc' |
JPEG compression |
For the retrieval benchmark VggRetrievalDataset
wraps around
datasets introduced in [4], [5]
These datasets provide both a set of images and a set of queries. Each query
is specified by the query image, a bounding box and
three subset of images:
A query is accessible through method getQuery(queryNum)
which
returns a structure with the following format:
The image subsets are numeric arrays with image IDs. To obtain a path of a certain image from these subsets, you can simply call:
Number of all images in the dataset is stored in property
obj.NumQueries
.
Currently, two dataset categories are available:
| Category Name | 'Category' option value | Number of images | Number of queries | Source |
|---|---|---|---|---|
| The Oxford Buildings Dataset [4] | 'oxbuild' |
5062 | 55 | link |
| The Paris Dataset[5] | 'paris' |
6412 | 55 | link |
These datasets usually contain thousands of images. It is possible to work only with its subset specified by these constructor parameters:
Subsets are sampled used uniform random sampling. You can change the
particular sampling by changing the seed of random number generator with
parameter SamplingSeed
.
All benchmark classes are subclasses of abstract class
GenericBenchmark
.
Currently three benchmarks are implemented.
RepeatabilityBenchmark
is based on tests introduced in
[2]. For details about this test see the
help string of the RetrievalBenchmark
class or see
repeatability tutorial.
Because this test is mostly reimplementing the original test, wrapper of the
original benchmark IjcvOriginalBenchmark
is also available. This
class directly calls the repeatability.m
script.
RetrievalBenchmark
class implements simple retrieval benchmark
of image features detectors. For details see help string of the class or see
image retrieval benchmark tutorial.
Currently the image retrieval benchmark depends on the Yael library which is not available for Microsoft Windows platforms.
The way how to parallelise is different for the repeatability and retrieval benchmark but both approaches use Matlab Parallel Computing Toolbox. For details about this toolbox, see its documentation.
Parallelisation of the repeatability benchmark can be done
by interchanging for
with parfor
in any level,
e.g.:
This is possible thanks to the fact that the cache system depends only on the file system context and does not share any variables. However it does not implement any synchronisation mechanisms. If the loops are properly designed, each process works with different data. However cache autoclear has to be disabled as it can produce situations when two processes are trying to delete the same files.
The image retrieval benchmark is already parallelised and the class
RetrievalBenchmark
uses several parfor loops for both features
extraction and KNN search.
In the case of KNN search you can advantage both from symmetric processing and distributed computing as the Yael KNN uses OpenMP to run its algorithms in multiple threads.
Package helpers contains several classes and functions which are used in
the rest of the project. Logger
and DataCache
classes are used almost in all classes therefore are described more in the
following text.
This project extensively caches its results using key-value caching system.
The key string is usually created based on the properties of input data and
processing algorithm. Data itself can be any Matlab data object and are stored
as *.mat
files in directory ./data/cache
. The
target filename is created as MD5 sum of the key.
Binary data are usually distinguished by a signature of the source file. File signature contains the file name and last modification date of the file. This is also used for algorithm binaries. Among that, the signature usually contain algorithm parameters as their values affect the results.
Caching is implemented in class helpers.DataCache
and has only
static methods, in order to be able to use it in parallel where no memory is
shared among processes. This class implements the following methods:
data = DataCache.getData(key)
Get data identified by a
string key. If the data has not been found, return [].storeData(data,key)
Store data identified by key.res = hasData(key)
Check whether data are cached.removeData(key)
Remove particular data from the cache.clearCache()
Delete the last recently used data to limit
the overall size of the cached data to DataCache.maxDataSize
limit.
deleteAllCachedData()
Delete all cached data.disableAutoClear()
Temporarily disable the autoclear
function. Cannot be called in parallel function as it creates a lock file.
enableAutoClear()
Enable autoClear after disableAutoClear.
Cannot be called in parallel part of code as it deletes a lock file.The caching properties can be changed only in the
helpers/DataCache.m
source code by changing the class constant
properties:
maxDataSize
Maximal storage space occupied by
cached data in Bytes.dataPath
Directory where to store cached datadataFileVersion
Version of the .mat file used for data
storage. See 'help save' for details.autoClear
Check whether storage size has not exceeded
the allowed size after each storeData method call. If so, the last recently
used data are removeddisable
Globally disable caching.Please note that the standard Matlab behaviour is to set these values only once when the class file is loaded for the first time. Therefore to apply the options you must call:
Caching system implements a way how to limit the overall size of the
cached data, further denoted as an autoclear function. It
checks the size of the files in the cache directory and removes the last recently used
items (based on the file modification date) to limit the storage usage.
To globally disable autoclear set the class property
helpers.DataCache.autoClear
to false. You can also disable it
temporarily by calling method helpers.DataCache.disableAutoclear()
which creates a lock file.
It is recommended to call this method before running parallel code to prevent
two processes to delete the same files.
Cache can be disabled globally by setting the constant property
helpers.DataCache.autoClear
to true. Also several framework
classes implements methods disableCaching()
and
enableCaching()
to control the caching behaviour of a single
class.
Cache does not support data invalidation. However to invalidate cached data of a certain detector you can use a simple trick to change the detector binary modification date:
As the cache depends heavily on a file system it is basically limited by a number of files in a single directory which depends on your operating system. Big directory structures can lead to slow file operations and therefore the cache operations can take longer. Thus it is recommended to clear the cache once a while (specially when using network file system).
Several classes in the framework uses logging implemented
in class helper.Logger
class. This class supports both sending
the events to std output or writing them to a log file.
Following events, inspired by the apache Log4j framework, are supported:
| Event name | 'VerboseLevel' value | Usage |
|---|---|---|
| TRACE | 3 |
finer-grained informational events than the DEBUG. |
| DEBUG | 2 |
Information useful for debugging. |
| INFO | 1 |
Informational messages about the application progress. |
| WARN | 0 |
Logs potentially harmful situations. Calls
warn command to show the backtrace. |
| ERROR | -1 |
Several errors which does not allow application
to continue. Calls Matlab error function. |
The verbose level can be set both globally editing
the constant properties of class helpers.Logger
or locally for each object which inherits the Logger
class by providing the 'OptionName',OptionValue
parameters
to the class constructor call. Supported options are:
If you want to change the format of the log output, just adjust the methods
helpers.Logger.displayLog
and
helpers.Logger.logToFile
according to your
aesthetic preferences.
You can also use logger on your class as well simply by specifying the
helpers.Logger
as a superclass. Here is a simple template how
to do it and how to properly configure the logger:
And constructing your object you will get:
When your computation are being computed with several processes, possibly
on several computers, having a single logging file may lead to inconsistent
data. That is why we would like to create separate files for each Matlab
process. This is generally a difficult task as the parfor
environment does not include any information about the process.
But simple trick can be used. Matlab creates default values for
object properties only once when the file is loaded for the first time.
And in classic matlabpool each lab has got its own MATLAB process,
therefore a log file name in the helpers.Logger
can be set for
example to:
To test we can call the following code:
You can see that each process generated the random string only once.
If the parfor would be distributed on more computers, the
hostname()
value would change as well.


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A matroid set is defined as the ordered structure which fulfills the following conditions:
1. The set S must be a finite set.
2. The set contains at least one value in it and is formed from the sub-sets of S such that if and then. If it satisfies this property then is called as hereditary. Must contain empty set.
3. If, andthen for an item such that. It is called as exchange property.
Proof of first property:
It is already given that in, S is a finite set so that it follows the (1) property of matriod.
Proof of second property:
It is also given that is a set which contain all the subsets of S. This implies that also contain the empty set.
Suppose B is a subset of S which lies in and also. Therefore, A is also a subset of. This can be shown by following example:
Suppose S is a finite set.
Therefore all the subset of S that lies in are as follow:
Suppose B isand A is subset of B so A can be or. The subset A is also a member of. Thereforesatisfies the 2nd property of matriod.
Proof of third property:
Suppose A is and B is are the subset lies in. The number of elements in A is less than B that is. There exist element x which exist in B but not in A that is element 2. The subset that is is also a part of.
Thereforesatisfies the 3rd property of matriod.
The satisfies all three properties of matriod.
Therefore, is a matriod.
A matroid set is defined as the ordered structure which fulfills the following conditions:
1. The set S must be a finite set.
2. The set contains at least one value in it and is formed from the sub-sets of S such that if and then. If it satisfies this property then is called as hereditary. Must contain empty set.
3. If, andthen for an item such that. It is called as exchange property.
The following three conditions must be satisfied in order to show is Metroid:
• S is a finite set; it is because S contains the set of columns of T.
• Suppose , therefore the column of B matrix are linearly independent. If A is subset of B that is. Then, A must be linearly independent therefore, .
Hence, is hereditary.
• In order to proof the exchange property, suppose A and B are subset of and .
The columns of A are linearly independent. Now, in order to calculate the rank takes these columns as matrix. The maximal set of linear independent columns is the rank of any matrix. Therefore the rank of A becomes:
Similarly, the rank for B becomes:
Because, therefore
…… (1)
Use contradiction to proof the exchange property that is there is column d in B which does not form linearly combination with columns of A. Therefore is linearly independent.
At first suppose the columns of B form linear combination with columns of A. This means the column space of B form subspace for columns space A.
So, according to matrix property that if column space of X is subspace of Y then.
Therefore, rank of B is less than rank of A. This contradicts the equation (1). So, B’s columns are not linear combination of A’s column.
Therefore, satisfies the exchange property. The, satisfy all three properties of matriod. Hence is a matriod.
It is required to show that if (S, I) is a matroid, then (S, ) is a matroid. So, first show that is non-empty. Let the maximal element of be A, then because S-(S-A) = which is maximum in .
Suppose that , then there must exist so that , however S-B so
Lastly, the exchange property is required to be proved. If B exists, and |B|<|A|, so an element y can be found out in A-B that can be added to B. In this scenario, there exists two cases:
Case 1: |A|=|B|+1
Case 2: Let X be a maximal independent set of I which is contained in S-A. Pick a set having size |X|-1 from the independent set contained in S-B, let the set be Y. So there exists some such that is maximal independent set in I
Thus, is independent in
Consider a finite set S which is to be partition into number of subsets with at least one element in them now defining a structure such that. Proving that the structure is matroid.
Matroid set is defined as the ordered structure which fulfills the conditions as:
1. The set S in matroid set is finite.
2. The set I contains at least one value in it and is formed from the sub-sets of S such that if and then.
3. If, andthen for an item such that
For a setto be a matroid set it must fulfill the properties of the matroid set which is as follows:
Now, , after that the rank of the function is as given below:
Thus, the rank function of the matroid is as follow some properties is as given below:
Thus, from the above three functions, concluded that the following cases is as follows:
1. is a finite non-empty set. (Non-empty because the partitions of are non-empty)
2. is non-empty, as mentioned in the problem. If , then contains either one or no element from the partition. And any subset of will also, therefore contain either one or no element from the partition. So, is hereditary.
3. If andand, which means has at least one element more than . This element must belong to some partition of whose element is not in set(as ). If such an element is added to, it will still fulfill the property of containing at most one element from a partition.
Since the structure fulfills all the properties of the matroid set so is matroid.
Hence the structure, made up of the finite set S which is to be partition into number of subsets with at least one element in and is matroid.
Transforming the weight function of a weighted matroid problem to a standard weighted matroid problem:
The weighted Matroid set is defined as the ordered structure with weight function which fulfills the conditions:
1. The set S in matroid set is finite.
2. The set I contains minimum one value in it and is formed from the sub-sets of S such that if and then.
3. If, andthen for an item such that
• The input to the GREEDY algorithm that solves matroid problem is a set and, and it returns an optimal independent subset such that is maximized.
• The algorithm considers each element in the order of non-increasing weight and adds it to the solution set , if is independent.
• Now, the new weights function as follows:
• Here, is a number greater than the highest weight of any of the edges in the graph.
• Now, all for a matroid with positive edges are zero. So, as the value increased the value of is decreased, because is constant.
Hence, any algorithm that will maximize weight function will minimize that is the standard weight function.


The AnimationMixer is a player for animations on a particular object in
the scene. When multiple objects in the scene are animated independently,
one AnimationMixer may be used for each object.
For an overview of the different elements of the three.js animation system
see the "Animation System" article in the "Next Steps" section of the
manual.
[page:Object3D rootObject] - the object whose animations shall be played
by this mixer.
The global mixer time (in seconds; starting with `0` on the mixer's creation).
A scaling factor for the global [page:.time mixer time].
Note: Setting the mixer's timeScale to `0` and later back to `1` is a
possibility to pause/unpause all actions that are controlled by this
mixer.
Returns an [page:AnimationAction] for the passed clip, optionally using a
root object different from the mixer's default root. The first parameter
can be either an [page:AnimationClip] object or the name of an
AnimationClip.
If an action fitting the clip and root parameters doesn't yet exist, it
will be created by this method. Calling this method several times with the
same clip and root parameters always returns the same clip instance.
Returns an existing [page:AnimationAction] for the passed clip, optionally
using a root object different from the mixer's default root.
The first parameter can be either an [page:AnimationClip] object or the
name of an AnimationClip.
Returns this mixer's root object.
Deactivates all previously scheduled actions on this mixer.
Advances the global mixer time and updates the animation.
This is usually done in the render loop, passing [page:Clock.getDelta clock.getDelta] scaled by the mixer's [page:.timeScale timeScale].
Sets the global mixer to a specific time and updates the animation
accordingly.
This is useful when you need to jump to an exact time in an animation. The
input parameter will be scaled by the mixer's [page:.timeScale timeScale].
Deallocates all memory resources for a clip. Before using this method make sure to call [page:AnimationAction.stop]() for all related actions.
Deallocates all memory resources for a root object. Before using this method make sure to call [page:AnimationAction.stop]() for all related actions.
Deallocates all memory resources for an action. Before using this method make sure to call [page:AnimationAction.stop]() to deactivate the action.
[link:https://github.com/mrdoob/three.js/blob/master/src/[path].js src/[path].js]


You may use the examples, or include a chemical name in the SMILES search application.
SMILES (Simplified Molecular Input Line Entry System) is a chemical notation that provides a chemical structure in a way that can be used to create SVG molecular drawings.


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If you have an training accuracy of 90%, and you are not happy with that, what do you do? Collect more data? Try other algos? Collect more diverse data? How to decide what to do?
Have a single real number metric to compare various algos.
You may combined precision and recall (say by using harmonic mean of the two).
Some metrics could be satisficing, e.g. running time of classification should be within a threshold. Others would be optimizing.
Dev and test set should come from the same distribution and should reflect the data you want to do well on.
When data was less abundant, 60/20/20 would be good training/dev/test was good split. In data abundant neural net scenario, 98/1/1 is good distribution. Test set should be just good enough to give high confidence in overall performance of system. Some people just omit test set too.
Sometimes you may wish to change metric mid way. While building cat vs no cat image, may be in a "better" classfier, pornographic images are classified as cat images. So, you need to change cost function to penalizing this misclassification heavily.
For perception problems, human level performance is close to bayes' error. You should try to consider the best human level performance possible. Eg. in radiology an expert radiologist could be better than average radiologist and team of experts may better than a single expert. You should consider the way which gives lowest possible error.
You should compute all these errors and that will help you decide how to improve your algorithm.
Tasks where machines can outperform humans: online ads, loan approvals, product recommendations, logistics. (Structured data, not natural perception problems)
Also, in some speech recognition, image recognition and radilogy tasks, computers surpass single human performance.
When training error is not good enough, you manually examine mispredictions. You should examine a subset of mispredictions and examine manually the reason for errors. Is it that dogs are being mislabeled as cats? Or is it that lion/cheetah are mislabelled as cats? Or is it that blurry images are mislabelled as cats? Figure out prominent reason and try to solve that. If lots of dogs are being mislabelled as cats, make sense to put more dog images in training set.
Sometimes data could have mislabelled examples. Some mislabels in training set are okay, because NN algos are robust to that, as long as errors are random. In dev/test you should first estimate how much boost you would get by correcting the labels, and then correct the labels if you find that will give you a boost. If you fix dev set, fix test set too. You should ideally fix the examples that your algo got right because of misprediction. But it is not easy for accurate algos, as there would be large number of items to examine.
You understand data and challenges only when you iterate. Build first system quickly and use bias/variance analysis to prioritize next steps.
DL algos are data hungry. Teams want to shove in as much as data as they can get hold of. For example, you can get images from internet, or you can purchse data. You can use data from various sources to train, but dev/test set data should only contain the examples which are representative of your use case.
When your training and dev set are from different distributions, training error and dev error difference may not reflect variance. It may just be that training test is easy. To catch this difference, you can have training dev set carved out of training set. Now:
What if you have data mismatch problem? Perform manual inspection. May be lot of dev/test are noisy (in a speech recognition system). In that case you can add noise in training set. But be careful: if you have 10K hour worth of training data, you should add 10K hour worth of noise too. If you just repeat 1hr worth of noise, you will overfit. Note that to human ear all noise will appear the same, but machine will overfit. Similarly for computer vision, you can synthesize images with background cars etc.
Say you have trained image recognition NN. We want to adapt it to radiology. What we can do is to chop off the last layer, replace it as per new task (with randomly initialized weights) and relearn the weights. This works because lot of low level learning like detecting edges and shapes can be transferred.
When does it makes sense? You transfer from task A to task B, when
Learn multiple classifications at once. For example, you may need to detect if an image has (a) pedestrians, (b) cars, (c) stop signs, (d) traffic lights. In this case, in final layer, you will have four neurons. Loss function will be sum of losses over different predictions. If in some training examples, label is unavailable for some variables, you skip computing the particular component in the loss for those particular examples. It makese sense when
Multi task learning is used much less often than tranfer learning. People just train different NNs.
Various stages of traditional ML are replaced by 1 NN. Eg. in speech recognition, people tranform input audio clip to features, then to phonemes, then to words and then to transcript. In DL you directly map input to output.
Sometimes, you break the process in some parts. Example, if you want to detect a person in a photo, you can do it in two phases (a) First detect where the face is (b) Then detect who the person is.
In machine translation, say English to French, end to end learning works well because there is a lot of learning data.


An alert dialog is a modal view that includes an optional title, a message and buttons, positioned in the middle of the display.
An alert dialog is created using Titanium.UI.createAlertDialog
.
Although this dialog always appears in the middle of the display (not touching the edges), other aspects of its aesthetics and the way the user interacts with it are different for each platform, as described below.
Android
On Android, the default alert dialog displays text information, via a title and message, without
any buttons. As the user can use the system hardware back
button to dismiss it, a button is
optional.
Buttons are shown if the buttonNames
property is defined, and are rendered horizontally below
the message.
To create a custom layout, a view may be added and, in turn, a hierarchy of views added to that child view.
iOS
On iOS, the default alert dialog displays text information, via a title and message, with a single button to allow it to be dismissed.
Buttons are defined using the buttonNames
property and are rendered vertically below
the message.
On iOS 4.0 and later, alert dialogs are automatically cancelled when the application is paused/suspended.
Global Alias
A global method alert()
is aliased to this object, and can be invoked with a single message.
For example
alert('this is a message');
This will generate an alert with a title of "Alert" and an "OK" button.
Caveats
Multiple alerts should not be shown at once.
The title
and ok
properties cannot be changed while the alert dialog is being displayed. On
Android only, you can change the message
property while the alert dialog is being displayed.
| click | Fired when a button in the dialog is clicked. |
Adds the specified callback as an event listener for the named event.
Arguments
| name | [String] | Name of the event. |
| callback | [Callback<Object>] | Callback function to invoke when the event is fired. |
Applies the properties to the proxy.
Arguments
| props | [Dictionary] | A dictionary of properties to apply. |
Fires a synthesized event to any registered listeners.
Arguments
| name | [String] | Name of the event. |
| event | [Dictionary] | A dictionary of keys and values to add to the Titanium.Event object sent to the listeners. |
Gets the value of the androidView property.
Gets the value of the buttonNames property.
Gets the value of the cancel property.
Gets the value of the message property.
Gets the value of the ok property.
Gets the value of the title property.
Removes the specified callback as an event listener for the named event.
Arguments
| name | [String] | Name of the event. |
| callback | [Callback<Object>] | Callback function to remove. Must be the same function passed to addEventListener. |
Sets the value of the androidView property.
Arguments
| androidView | [Titanium.UI.View] | New value for the property. |
Sets the value of the cancel property.
Arguments
| cancel | [Number] | New value for the property. |
Sets the value of the message property.
Arguments
| message | [String] | New value for the property. |
Sets the value of the ok property.
Arguments
| ok | [String] | New value for the property. |
Sets the value of the title property.
Arguments
| title | [String] | New value for the property. |
Event properties
| cancel |
[BooleanNumber] Boolean type on Android and Mobile Web; Number on iOS. On Android and Mobile Web, indicates whether the cancel button was clicked, in which
case returns On iOS, the value of the cancel property is
returned, if defined, or See the |
| index |
[Number] Index of the button that was clicked. |
| source |
[Object] Source object that fired the event. |
| type |
[String] Name of the event fired. |


--- layout: page title: "Section 2: Dalvik Thread Model" ---
In the multi-thread environment, how to identify a certain thread is a challenging work. For the reason that the threads may be created in different order, we cannot recognize them by their absolute order of creation. However, each thread should create its children (threads) in the same order, if the code stays the same between two execution. In this way, we can use the thread's position in its family tree to locate one certain thread.
Let's see an example. A create B1,B2; B1 create C1; B2 create C2,C3. So we get the following creation tree:
A |--------| | | B1 B2 | |-----------| C1 C2 C3However, the absolute creation order may be different. The following two sequences are both valid, for instance.
There are several ways to identify the certain threads. Take the easiest way as an example: we can define a unique identifier ID(T) for a thread T and its reincarnation inductively, as follows. If T is the initial thread of Java program, then ID(T) = [1]. Otherwise, suppose that T is the kth thread created by its parent. And its parent thread can be retrieved by function parent(T). Then we have
ID(T) = ID(parent(T))+[K]
Here the operation "+" has the same meaning in java which means a string concatenation.
Consider the above scenario, the ID for the threads are as following:
A: [1]
B1: [1][1]
B2: [1][2]
C1: [1][1][1]
C2: [1][2][1]
C3: [1][2][2]
However, the previous naive way of identification has some drawbacks.
In order to bypass the above disadvantages, a more efficient and elegant methodolgy is using a hash value to identify each thread. In detail, the system gives each thread a hash value based on its parent's hash and its ordinal number of creation. The hash value of thread T, which is the Kth child of its parent, can be calculated by the formula:
ID(T) = hash(ID(parent(T)),K)
The hash function can be any types of hash you want.
Consider the above scenario, we assume thread "A" have a hash value v1 as its identification.
A: v1
B1: v2 = hash(v1,1)
B2: v3 = hash(v1,2)
C1: hash(v2,1)
C2: hash(v3,1)
C3: hash(v3,2)
In this case, we have fix-length identifications with more fast and easy ways to generate and compare them.
In this part, you should design your own way of thread identification and implement it into the Dalvik VM. To verify the validaty of your scheme, you should print the identification each time when the thread is created. In our test apk, the thread will print their id through the "adb logcat". If your work is correct, you will see some similar result as following:
In the above snapshot, we can find out that the "add-x" and "mul-x" are created in different order. However, our identifiers, which is printed after the sentence "I'm add-x" or "I'm mul-x", keep the same.


{% extends "base.html" %} {% block title %}
Medieval catalogues > SECULAR INSTITUTIONS: Hospitals, Towns, and the Professions > Boston guild > Inventory of goods, 1523 × 1524
{% endif %}5 identified entries found.
All data was derived from the List of Identifications by Professor Richard Sharpe.
{% if not printing %}
A key to codes used in the List is available (opens in new tab).{% endif %}


Police respond to Queens Center mall after dispute breaks out among crowd of 200 kids
by WABCELMHURST, Queens (WABC) -- Police responded to the Queens Center mall on Friday after a fight between a hundreds of kids.
Authorities were called to the scene around 1 p.m. for crowd control.
Police say approximately 200 kids had gathered at the mall and there was some sort of dispute.
No injuries were reported and the mall was not closed, but police encouraged the public to stay away from the scene while they assessed the situation.
No arrests have been made.


Quick reference for polyhedra in Sage#
Author: Jean-Philippe Labbé<EMAIL_ADDRESS>Vincent Delecroix<EMAIL_ADDRESS>List of Polyhedron methods#
H and V-representation
|
ring on which the polyhedron is defined |
|
ambient vector space or free module |
|
vector space or free module used for the vectors of the H-representation |
|
vector space or free module used for the vectors of the V-representation |
|
number of elements in the H-representation (sum of the number of equations and inequalities) |
|
number of elements in the V-representation (sum of vertices, rays and lines) |
|
number of equations |
|
number of inequalities |
|
number of vertices |
|
number of rays |
|
number of lines |
|
number of facets |
Polyhedron boolean properties:
|
tests emptyness |
|
tests whether a polyhedra is the whole ambient space |
|
tests if the polyhedron has the same dimension as the ambient space |
|
tests whether two polyhedra are combinatorially isomorphic |
|
tests compactness, or boundedness of a polyhedron |
|
tests whether a polyhedron is a lattice polytope |
tests whether the polyhedron is inscribed in a sphere |
|
tests if the polyhedron can be used to produce another given polyhedron using a Minkowski sum. |
|
|
tests whether the polyhedron has full skeleton until half of the dimension (or up to a certain dimension) |
tests if the polar of a lattice polytope is also a lattice polytope (only for |
|
|
checks whether the degree of all vertices is equal to the dimension of the polytope |
|
test whether a polytope is a simplex |
|
checks whether all faces of the polyhedron are simplices |
|
tests whether self is a Lawrence polytope |
|
tests whether the polytope is self-dual |
|
test whether the polytope is a pyramid over one of its facets |
|
test whether the polytope is combinatorially equivalent to a bipyramid over some polytope |
|
test whether the polytope is combinatorially equivalent to a prism of some polytope |
Enumerative properties
|
the dimension of the ambient vector space |
|
the dimension of the polytope |
|
alias of dim |
|
the \(f\)-vector (number of faces of each dimension) |
|
the flag-\(f\)-vector (number of chains of faces) |
|
highest cardinality for which all \(k\)-subsets of the vertices are faces of the polyhedron |
|
highest cardinality for which all \(k\)-faces are simplices |
|
highest cardinality for which the polar is \(k\)-simplicial |
Implementation properties
|
gives the backend used |
|
gives the base ring used |
|
changes the base ring |
Transforming polyhedra
|
Minkowski sum of two polyhedra |
|
Minkowski difference of two polyhedra |
Minkowski decomposition (only for |
|
|
cartesian product of two polyhedra |
|
intersection of two polyhedra |
|
join of two polyhedra |
|
convex hull of the union of two polyhedra |
|
constructs an affinely equivalent full-dimensional polyhedron |
constructs a geometric realization of the barycentric subdivision |
|
|
scalar dilation |
|
truncates a specific face |
|
returns the face splitting of a face of self |
|
the one-point suspension over a vertex of self (face splitting of a vertex) |
|
stack a face of the polyhedron |
|
returns an encompassing lattice polytope. |
|
returns the polar of a polytope (needs to be compact) |
|
prism over a polyhedron (increases both the dimension of the polyhedron and the dimension of the ambient space) |
|
pyramid over a polyhedron (increases both the dimension of the polyhedron and the dimension of the ambient space) |
|
bipyramid over a polyhedron (increases both the dimension of the polyhedron and the dimension of the ambient) |
|
translates by a given vector |
|
truncates all vertices simultaneously |
|
returns the Lawrence extension of self on a given point |
|
returns the Lawrence polytope of self |
|
returns the wedge over a face of self |
Combinatorics
|
the combinatorial polyhedron |
|
the face lattice |
|
the hasse diagram |
|
the automorphism group of the underlying combinatorial polytope |
|
underlying graph |
|
digraph (orientation of edges determined by a linear form) |
|
bipartite digraph given vertex-facet adjacency |
|
adjacency matrix |
|
incidence matrix |
|
slack matrix |
|
adjacency matrix of the facets |
|
adjacency matrix of the vertices |
Integral points
the Ehrhart polynomial for |
|
the Ehrhart polynomial for |
|
the Ehrhart quasipolynomial for |
|
|
the \(h^*\)-vector for polytopes with integral vertices |
|
list of integral points |
|
number of integral points |
|
get the i-th integral point without computing all interior lattice points |
checks whether the origin is an interior lattice point and compactness (only for |
|
|
get a random integral point |
Getting related geometric objects
|
returns the smallest affine subspace containing the polyhedron |
returns the boundary complex of simplicial compact polyhedron |
|
returns the average of the vertices of the polyhedron |
|
|
returns the center of the mass |
|
returns the sum of the center and the rays |
|
returns a maximal chain of faces |
returns the fan spanned by the faces of the polyhedron |
|
|
a generator over the faces |
|
the list of faces |
|
the list of facets |
|
smallest face containing specified Vrepresentatives |
|
largest face contained in specified Hrepresentatives |
returns the fan spanned by the normals of the supporting hyperplanes of the polyhedron |
|
|
returns the (affine) Gale transform of the vertices of the polyhedron |
returns the hyperplane arrangement given by the defining facets of the polyhedron |
|
transform the polyhedra into a Linear Program |
|
|
returns a triangulation of the polyhedron |
returns an iterator of the fibrations of the lattice polytope (only for |
Other
|
generator for bounded edges |
returns the vertices of an encompassing cube |
|
|
tests whether the polyhedron contains a vector |
|
tests whether the polyhedron contains a vector in its interior using the ambient topology |
|
tests whether the polyhedron contains a vector in its relative interior |
returns the translation vector between two translation of two polyhedron (only for |
|
|
computes the integral of a polynomial over the polyhedron |
returns the radius of the smallest sphere containing the polyhedron |
|
returns the square of the radius of the smallest sphere containing the polyhedron |
|
|
computes different volumes of the polyhedron |
|
returns the restricted automorphism group |
returns the lattice automorphism group. Only for |


N |
App\Khan\Bootstrap |
|
C |
KhanController | |
C |
KhanModel | |
N |
App\Khan\Component\Cdn |
|
C |
Cdn | |
N |
App\Khan\Component\Container |
|
C |
ServiceContainer | |
N |
App\Khan\Component\DB |
|
C |
DB | |
C |
Model | |
N |
App\Khan\Component\Encrypt |
|
C |
Encrypt | |
N |
App\Khan\Component\Hooks |
|
C |
Hooks | |
N |
App\Khan\Component\HttpFoundation |
|
C |
AcceptHeader | Represents an Accept-* header. |
C |
AcceptHeaderItem | Represents an Accept-* header item. |
C |
ApacheRequest | Request represents an HTTP request from an Apache server. |
C |
BinaryFileResponse | BinaryFileResponse represents an HTTP response delivering a file. |
C |
Cookie | Represents a cookie. |
C |
ExpressionRequestMatcher | ExpressionRequestMatcher uses an expression to match a Request. |
C |
FileBag | FileBag is a container for uploaded files. |
N |
App\Khan\Component\HttpFoundation\File |
|
C |
File | A file in the file system. |
C |
UploadedFile | A file uploaded through a form. |
N |
App\Khan\Component\HttpFoundation |
|
C |
HeaderBag | HeaderBag is a container for HTTP headers. |
C |
IpUtils | Http utility functions. |
C |
JsonResponse | Response represents an HTTP response in JSON format. |
C |
ParameterBag | ParameterBag is a container for key/value pairs. |
C |
RedirectResponse | RedirectResponse represents an HTTP response doing a redirect. |
C |
Request | Request represents an HTTP request. |
C |
RequestMatcher | RequestMatcher compares a pre-defined set of checks against a Request instance. |
I |
RequestMatcherInterface | RequestMatcherInterface is an interface for strategies to match a Request. |
C |
RequestStack | Request stack that controls the lifecycle of requests. |
C |
Response | Response represents an HTTP response. |
C |
ResponseHeaderBag | ResponseHeaderBag is a container for Response HTTP headers. |
C |
ServerBag | ServerBag is a container for HTTP headers from the $_SERVER variable. |
C |
StreamedResponse | StreamedResponse represents a streamed HTTP response. |
N |
App\Khan\Component\Mime |
|
C |
Mime | |
N |
App\Khan\Component\Router\Components |
|
T |
CsrfToken | |
N |
App\Khan\Component\Router\Http\Interfaces |
|
I |
Request | |
I |
Response | |
N |
App\Khan\Component\Router\Http |
|
T |
Middlewares | |
C |
Request | Request Class and Interface Implement |
C |
Response | |
N |
App\Khan\Component\Router\RegexEngine |
|
T |
RegexEngine | |
N |
App\Khan\Component\Router\Router |
|
C |
ConfigureRoute | |
C |
GroupRouter | |
C |
Resource | |
C |
Responser | |
C |
Router | |
T |
Temporary | |
N |
App\Khan\Component\Socket |
|
C |
Socket | |
N |
App\Khan\Component\Strategy |
|
C |
Strategy | |
N |
App\Khan\Component\Stream |
|
C |
StreamServer | |
N |
App\Khan\Component\Validate |
|
C |
Data | |
N |
App\Khan\Contracts\Libraries |
|
I |
Libraries | |
N |
App\Khan\Contracts\Middlewares |
|
I |
Middleware | |
N |
App\Khan |
|
C |
Khan | Class Core Run Project |
C |
KhanFactory | Create khan class in factory |
N |
App\Khan\Libraries |
|
C |
Cache | |
C |
Files | |
C |
Image | |
C |
||
C |
Request | |
C |
Session | |
N |
||
C |
Build | |
N |
Command |
|
C |
ApiCommand | |
N |
Command\Bot |
|
C |
Bot | |
C |
BotBuild | |
N |
Command |
|
C |
ControllerCommand | |
C |
CreateCommand | |
C |
GulpCommand | |
C |
JsCommand | |
C |
KhanCommand | |
C |
LiveCommand | |
C |
MakeCommand | |
C |
MiddlewareCommand | |
C |
ModelCommand | |
C |
ReactCommand | |
C |
SassCommand | |
C |
ServerCommand | |
C |
StrategyCommand | |
C |
ViewCommand | |
C |
VueCommand | |
N |
Middlewares |
|
C |
CheckLogin | |
N |
MyApp |
|
C |
AuthController | |
N |
StrategysAuth |
|
C |
AuthStrategy | |
C |
strategyName | |
N |
Symfony\Component\HttpFoundation\Exception |
|
C |
ConflictingHeadersException | The HTTP request contains headers with conflicting information. |
I |
RequestExceptionInterface | Interface for Request exceptions. |
C |
SuspiciousOperationException | Raised when a user has performed an operation that should be considered suspicious from a security perspective. |
N |
Symfony\Component\HttpFoundation\File\Exception |
|
C |
AccessDeniedException | Thrown when the access on a file was denied. |
C |
CannotWriteFileException | Thrown when an UPLOAD_ERR_CANT_WRITE error occurred with UploadedFile. |
C |
ExtensionFileException | Thrown when an UPLOAD_ERR_EXTENSION error occurred with UploadedFile. |
C |
FileException | Thrown when an error occurred in the component File. |
C |
FileNotFoundException | Thrown when a file was not found. |
C |
FormSizeFileException | Thrown when an UPLOAD_ERR_FORM_SIZE error occurred with UploadedFile. |
C |
IniSizeFileException | Thrown when an UPLOAD_ERR_INI_SIZE error occurred with UploadedFile. |
C |
NoFileException | Thrown when an UPLOAD_ERR_NO_FILE error occurred with UploadedFile. |
C |
NoTmpDirFileException | Thrown when an UPLOAD_ERR_NO_TMP_DIR error occurred with UploadedFile. |
C |
PartialFileException | Thrown when an UPLOAD_ERR_PARTIAL error occurred with UploadedFile. |
C |
UnexpectedTypeException | |
C |
UploadException | Thrown when an error occurred during file upload. |
N |
Symfony\Component\HttpFoundation\File\MimeType |
|
C |
ExtensionGuesser | A singleton mime type to file extension guesser. |
I |
ExtensionGuesserInterface | Guesses the file extension corresponding to a given mime type. |
C |
FileBinaryMimeTypeGuesser | Guesses the mime type with the binary "file" (only available on *nix). |
C |
FileinfoMimeTypeGuesser | Guesses the mime type using the PECL extension FileInfo. |
C |
MimeTypeExtensionGuesser | Provides a best-guess mapping of mime type to file extension. |
C |
MimeTypeGuesser | A singleton mime type guesser. |
I |
MimeTypeGuesserInterface | Guesses the mime type of a file. |
N |
Symfony\Component\HttpFoundation\File |
|
C |
Stream | A PHP stream of unknown size. |
N |
Symfony\Component\HttpFoundation\Session\Attribute |
|
C |
AttributeBag | This class relates to session attribute storage. |
I |
AttributeBagInterface | Attributes store. |
C |
NamespacedAttributeBag | This class provides structured storage of session attributes using a name spacing character in the key. |
N |
Symfony\Component\HttpFoundation\Session\Flash |
|
C |
AutoExpireFlashBag | AutoExpireFlashBag flash message container. |
C |
FlashBag | FlashBag flash message container. |
I |
FlashBagInterface | FlashBagInterface. |
N |
Symfony\Component\HttpFoundation\Session |
|
C |
Session | |
I |
SessionBagInterface | Session Bag store. |
C |
SessionBagProxy | |
I |
SessionInterface | Interface for the session. |
N |
Symfony\Component\HttpFoundation\Session\Storage\Handler |
|
C |
AbstractSessionHandler | This abstract session handler provides a generic implementation of the PHP 7.0 SessionUpdateTimestampHandlerInterface, enabling strict and lazy session handling. |
C |
MemcachedSessionHandler | Memcached based session storage handler based on the Memcached class provided by the PHP memcached extension. |
C |
MigratingSessionHandler | Migrating session handler for migrating from one handler to another. It reads from the current handler and writes both the current and new ones. |
C |
MongoDbSessionHandler | Session handler using the mongodb/mongodb package and MongoDB driver extension. |
C |
NativeFileSessionHandler | Native session handler using PHP's built in file storage. |
C |
NullSessionHandler | Can be used in unit testing or in a situations where persisted sessions are not desired. |
C |
PdoSessionHandler | Session handler using a PDO connection to read and write data. |
C |
RedisSessionHandler | Redis based session storage handler based on the Redis class provided by the PHP redis extension. |
C |
StrictSessionHandler | Adds basic SessionUpdateTimestampHandlerInterface behaviors to another SessionHandlerInterface . |
N |
Symfony\Component\HttpFoundation\Session\Storage |
|
C |
MetadataBag | Metadata container. |
C |
MockArraySessionStorage | MockArraySessionStorage mocks the session for unit tests. |
C |
MockFileSessionStorage | MockFileSessionStorage is used to mock sessions for functional testing when done in a single PHP process. |
C |
NativeSessionStorage | This provides a base class for session attribute storage. |
C |
PhpBridgeSessionStorage | Allows session to be started by PHP and managed by Symfony. |
N |
Symfony\Component\HttpFoundation\Session\Storage\Proxy |
|
C |
AbstractProxy | |
C |
SessionHandlerProxy | |
N |
Symfony\Component\HttpFoundation\Session\Storage |
|
I |
SessionStorageInterface | StorageInterface. |
N |
Symfony\Component\HttpFoundation\Tests |
|
C |
AcceptHeaderItemTest | |
C |
AcceptHeaderTest | |
C |
ApacheRequestTest | |
C |
BinaryFileResponseTest | |
C |
CookieTest | CookieTest. |
C |
DefaultResponse | |
C |
ExpressionRequestMatcherTest | |
C |
FileBagTest | FileBagTest. |
N |
Symfony\Component\HttpFoundation\Tests\File |
|
C |
FakeFile | |
C |
FileTest | |
N |
Symfony\Component\HttpFoundation\Tests\File\MimeType |
|
C |
MimeTypeTest | |
N |
Symfony\Component\HttpFoundation\Tests\File |
|
C |
UploadedFileTest | |
N |
Symfony\Component\HttpFoundation\Tests |
|
C |
HeaderBagTest | |
C |
IpUtilsTest | |
C |
JsonResponseTest | |
C |
JsonSerializableObject | |
C |
NewRequest | |
C |
ParameterBagTest | |
C |
RedirectResponseTest | |
C |
RequestContentProxy | |
C |
RequestMatcherTest | |
C |
RequestStackTest | |
C |
RequestTest | |
C |
ResponseHeaderBagTest | |
C |
ResponseTest | |
C |
ResponseTestCase | |
C |
ServerBagTest | ServerBagTest. |
N |
Symfony\Component\HttpFoundation\Tests\Session\Attribute |
|
C |
AttributeBagTest | Tests AttributeBag. |
C |
NamespacedAttributeBagTest | Tests NamespacedAttributeBag. |
N |
Symfony\Component\HttpFoundation\Tests\Session\Flash |
|
C |
AutoExpireFlashBagTest | AutoExpireFlashBagTest. |
C |
FlashBagTest | FlashBagTest. |
N |
Symfony\Component\HttpFoundation\Tests\Session |
|
C |
SessionTest | SessionTest. |
N |
Symfony\Component\HttpFoundation\Tests\Session\Storage\Handler |
|
C |
AbstractRedisSessionHandlerTestCase | |
C |
AbstractSessionHandlerTest | |
C |
MemcachedSessionHandlerTest | |
C |
MigratingSessionHandlerTest | |
C |
MockPdo | |
C |
MongoDbSessionHandlerTest | |
C |
NativeFileSessionHandlerTest | Test class for NativeFileSessionHandler. |
C |
NullSessionHandlerTest | Test class for NullSessionHandler. |
C |
PdoSessionHandlerTest | |
C |
PredisClusterSessionHandlerTest | |
C |
PredisSessionHandlerTest | |
C |
RedisArraySessionHandlerTest | |
C |
RedisSessionHandlerTest | |
C |
StrictSessionHandlerTest | |
N |
Symfony\Component\HttpFoundation\Tests\Session\Storage |
|
C |
MetadataBagTest | Test class for MetadataBag. |
C |
MockArraySessionStorageTest | Test class for MockArraySessionStorage. |
C |
MockFileSessionStorageTest | Test class for MockFileSessionStorage. |
C |
NativeSessionStorageTest | Test class for NativeSessionStorage. |
C |
PhpBridgeSessionStorageTest | Test class for PhpSessionStorage. |
N |
Symfony\Component\HttpFoundation\Tests\Session\Storage\Proxy |
|
C |
AbstractProxyTest | Test class for AbstractProxy. |
C |
SessionHandlerProxyTest | Tests for SessionHandlerProxy class. |
N |
Symfony\Component\HttpFoundation\Tests |
|
C |
StreamedResponseTest | |
C |
StringableObject |


--- layout: post title: Emma Speaks at Church, Jan 2011 categories: [] tags: - emma - family status: publish type: post published: true meta: _original_post_id: '' _original_import_author: John Duprey author: ---
Emma spoke at church service last month. She did well.
[youtube http://www.youtube.com/watch?v=JEACybHzeeI?wmode=transparent]


The Spry Textarea Validation Widget is used to validate a textarea, mostly checking for content existence or content length.
The widget structure is as follows:
<widget container> <input textarea>
<message container(s)>
</widget container>
The Textarea Validation Widget supports one text area per widget.
The markup used in this structure can be most any HTML, as long as it follows the rules for nesting.
Using the provided files, the default mark up is:

<textarea name="textarea3" id="textarea3" cols="32" rows="5"></textarea>
The value is required.
Widget Constructors are small pieces of javascript that activate the markup into the working widget. These scripts must come AFTER the markup on the page, since the markup needs to exist before the constructor fires.

A basic constructor specifies the name of the widget and identifies the ID of the main markup container. The name of the widget is used to identify the widget for functions and methods.

Constructor options allow users to specify certain attributes of the widget.
Constructor options follow the ID parameter, wrapped in curly braces {}. Options are name:value pairs, separated by a colon (:).

| Option | Values | Default | Description |
|---|---|---|---|
| counterID | string | null | This options specifies the markup container that will display the couter. It should be an empty container within the widget. |
| counterType | 'chars_count' or 'chars_remaining' | null | Determines whether the counter counts the number of typed characters or counts the number of characters remaining before hitting the maxChars value. 'chars_remaing' must be used in conjuction with the 'maxChars' option. |
| hint | string | null | The defined string will show in the textarea when the page loads. It will be removed when the user starts typing within the field. |
| isRequired | true or false | true | Determines whether any checkboxes need to be checked. Set to 'false' to bypass validation. |
| maxChars | number | null | Determines the maximum number of characters that can be used with the textarea. |
| minChars | number | null | Determines the minimum number of characters that can be used with the textarea. |
| useCharacterMasking | true or false | null | Used only in conjunction with 'maxChars', this option will prevent the user from typing in more than the maximum number of characters. |
| validateOn | "blur", "change" | submit | The widget always validates onSubmit. onBlur and onChange can be added with this option. Both can be applied with an array ['blur', 'change'] |
requiredClass |
class name | null | Overrides the "textareaRequiredState" built-in value . |
validClass |
class name | null | Overrides the "textareaValidState" built-in value. |
focusClass |
class name | null | Overrides the "textareaFocusState" built-in value.. |
invalidCharsMinClass |
class name | null | Overrides the "textareaMinCharsState" built-in value. |
invalidCharsMaxClass |
class name | null | Overrides the "textareaMaxCharsState" built-in value. |
textareaFlashClass |
class name | null | Overrides the "textareaFlashState" built-in value. |
hintClass |
class name | null | Overrides the "textareaHintState" built-in value. |

Recall that javascript is case sensitive.
Reset the widget to its original state.
widgetName.reset();
Reset Textarea
Validates the current state of the widget.
widgetName.validate();
Validate Textarea
Copyright © 2007. Adobe Systems Incorporated.
All rights reserved.


HEATHERS A film review by Ken Johnson Copyright 1992 Ken Johnson
102 min., R, Comedy, 1989 Director: Michael Lehmann Cast: Christian Slater, Winona Ryder, Shannen Doherty, Lisanne Falk, Kim Walker, Penelope Milford, Glenn Shadix, Lance Fenton, Renee Estevez
At high school Winona Ryder is part of a clique composed of three other girls all with the first name Heather (Shannen Doherty, Lisanne Falk, and Kim Walker). Ryder meets weird unpopular Christian Slater in the school cafeteria. He is tired of the three Heathers running the lives of everybody at school so he proposes that he and Ryder kill them off in a way that looks like suicide. They start with Walker. After they kill her, she becomes more of an idol than before and Ryder starts to have second thoughts about Slater's crazy idea.
HEATHERS is a very good black comedy about high school life, for those who haven't forgotten high school or for those who are still in high school. I think to really get the meaning behind the film you must be in high school, or have already gone through high school. Younger viewers, I feel, will not get the enjoyment from the film. The use of suicide may offend some viewers, so if this is a touchy subject with you this may not be the film for you to see. On a scale of zero to five, I give HEATHERS a four. HEATHERS is rated R for explicit language, violence, and adult situations.
HEATHERS covers the hard subject of cliques, not just in high school but every where. At least in my high school, the cliques run the school, and someone from one clique usually doesn't associate with someone from another clique, which is not the way it should be.
The main problem, I feel, with HEATHERS is that the film gets ecxessively unrealistic. Christian Slater over does his role just a little bit. He seems to be trying to impersonate Jack Nicholson and he isn't the best at it. Slater would have done a better job if he put a little bit more of himself into the role. Winona Ryder's character is not the brightest person. She just goes into Slater's crazy ideas without thinking of what might happen. Ryder puts in a great performance and I feel does a better job than Slater. Shannen Doherty (of "Beverly Hills, 90210"), Lisanne Falk, and Kim Walker all do a great job as the three Heathers.
The film is rather well written, but as I mentioned earlier, the film does get rather unrealistic in some places. The part that I think was the biggest rip-off was the ending. I felt it was just slapped in with no consideration for those watching the film. This I feel really hurt the film, and I wish that somebody had tried harder to make the ending better.
Ken J<EMAIL_ADDRESS>.
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


## -*- coding: utf-8 -*- <% n = 0 def processDate(day, month, year) : #days = ['1st', '2nd', '3rd', '4th', '5th', '6th', '7th', '8th', '9th', '10th','11th', '12th', '13th', '14th', '15th', '16th', '17th', '18th', '19th', '20th', '21st', '22nd', '23rd','24th'] if day == 1 : str_day = '1st' elif day == 2 : str_day = '2nd' elif day == 3 : str_day = '3rd' elif day == 21 : str_day = '21st' elif day == 22 : str_day = '22nd' elif day == 23 : str_day = '23rd' elif day == 31 : str_day = '31st' else : str_day = str(day)+'th' months = ['january', 'february', 'march', 'april', 'may', 'june', 'july', 'august', 'september', 'october', 'november', 'december'] return 'on '+ months[month-1] + ' ' + str_day + ', ' + str(year) %>


IFTSTransaction
Transaction.
Almost methods are the same interface as IndexedFTS and IFTSArrayPromise. Probably this class is faster than other classes in most cases.
Please be careful, IFTSTransaction are sometimes makes a big cache. Should not keep many transactions if not need.
Constructor Summary
| Public Constructor | ||
| public |
constructor(db: IndexedFTS, transaction: IDBTransaction) |
Member Summary
| Public Members | ||
| public |
db: IndexedDB |
|
| public |
Promise for await closing transaction. |
|
| public |
transaction: IDBTransaction |
Method Summary
| Public Methods | ||
| public |
between(column: object, lower: object, upper: object): IFTSArrayPromise Get contents that have property is between argument values. |
|
| public |
delete(keys: object): Promise<IFTSTransaction> Delete contents from database. |
|
| public |
equals(column: object, value: object): IFTSArrayPromise Get contents that have fully matched property. |
|
| public |
Filtering elements by function and returns IFTSArrayPromise. |
|
| public |
Get content by primary key. |
|
| public |
Get all contents. |
|
| public |
Get N-Gram set from index. |
|
| public |
Get word set from index. |
|
| public |
greater(column: object, value: object): IFTSArrayPromise Get contents that have property greater than value. |
|
| public |
greaterOrEquals(column: object, value: object): IFTSArrayPromise Get contents that have property greater than value or equals value. |
|
| public |
lower(column: object, value: object): IFTSArrayPromise Get contents that have property lower than value. |
|
| public |
lowerOrEquals(column: object, value: object): IFTSArrayPromise Get contents that have property lower than value or equals value. |
|
| public |
Do something process for each elements and returns IFTSArrayPromise. |
|
| public |
put(contents: object): Promise<IFTSTransaction> Put contents into database. |
|
| public |
Get contents that have matched property by full-text search. |
|
| public |
searchWord(columns: object | object[], query: string, options: object): IFTSArrayPromise Find contents that have fully matched word in property. |
|
| public |
sort(column: object, order: 'asc' | 'desc', offset: Number, limit: Number): IFTSArrayPromise Sort and get all contents. |
Public Constructors
public constructor(db: IndexedFTS, transaction: IDBTransaction) source
Params:
| Name | Type | Attribute | Description |
| db | IndexedFTS | database. |
|
| transaction | IDBTransaction | transaction of IndexedDB. |
Public Methods
public between(column: object, lower: object, upper: object): IFTSArrayPromise source
Get contents that have property is between argument values.
public delete(keys: object): Promise<IFTSTransaction> source
Delete contents from database.
Params:
| Name | Type | Attribute | Description |
| keys | object | key of contents. allowed multiple arguments. |
Return:
| Promise<IFTSTransaction> | returns self for chain. Will reject with InvalidKeyError if keys included null or undefined. |
public equals(column: object, value: object): IFTSArrayPromise source
Get contents that have fully matched property.
public filter(fun: function(content: object, index: Number): object): IFTSArrayPromise source
Filtering elements by function and returns IFTSArrayPromise.
WARNING: This method won't use the index. Other methods(eg. IFTSTransaction#equals or IFTSTransaction#lower may faster than this.
public get(key: object): Promise<object|undefined> source
Get content by primary key.
Params:
| Name | Type | Attribute | Description |
| key | object | the key of content. |
Return:
| Promise<object|undefined> | content. promise will reject with InvalidKeyError if keys included null or undefined. result value will be undefined if not found. |
public getNGrams(column: string, options: object): Promise<Map<string, number>> source
Get N-Gram set from index.
public getWords(column: string, options: object): Promise<Map<string, number>> source
Get word set from index.
public greater(column: object, value: object): IFTSArrayPromise source
Get contents that have property greater than value.
public greaterOrEquals(column: object, value: object): IFTSArrayPromise source
Get contents that have property greater than value or equals value.
public lower(column: object, value: object): IFTSArrayPromise source
Get contents that have property lower than value.
public lowerOrEquals(column: object, value: object): IFTSArrayPromise source
Get contents that have property lower than value or equals value.
public map(fun: function(content: object, index: Number): object): IFTSArrayPromise source
Do something process for each elements and returns IFTSArrayPromise.
NOTE: This method doesn't fast. May better do filtering before doing map if need filtering.
public put(contents: object): Promise<IFTSTransaction> source
Put contents into database.
Params:
| Name | Type | Attribute | Description |
| contents | object | contents for save. allowed multiple arguments. |
public search(columns: object | object[], query: string, options: object): IFTSArrayPromise source
Get contents that have matched property by full-text search.
All target columns have to made ngram index when created database. If you didn't made ngram index, you can use IFTSArrayPromise#search (but this way is very slow).
public searchWord(columns: object | object[], query: string, options: object): IFTSArrayPromise source
Find contents that have fully matched word in property.
All target columns have to made word index when created database. If you didn't made word index, you can use IFTSArrayPromise#searchWord (but this way is very slow).
public sort(column: object, order: 'asc' | 'desc', offset: Number, limit: Number): IFTSArrayPromise source
Sort and get all contents.


Welcome!
Please wait while the web-app attempts to log you in, this won't take long.
Please wait while the web-app attempts to log you in, this won't take long.
The audio client is only available for players who are online in the
server.
Use /audio to obtain a URL
The audio client is only available for players who are online in the server.
Use
/audio
to obtain a URL
Keep this tab open in the background since it'll be used to play audio related to your in-game actions. You can manually change your volume here, or in game using /volume (volume)
You are now connected with your Hue Bridge, {{name}}.
You may now link up to three lights that the server will control. Usually from right to left.
Back to the player
This server has support for Proximity Voice Chat, which allows you to talk with players within a * block radius. Would you like to enable this feature and give access to
your microphone?
You can always mute your microphone, mute other users or close the voice chat whenever you
want.


You can use this app with a custom link. Please paste a direct link to any video hosted on the internet.
{{errorParsingLink}}


These are all of the awesome projects that I made in creative coding class!!!
My Projects:
Spider Web Project!!!
In this project a spider draws a web! Click for more webs!
Beats Per Minute Project
This project measures the beats per minute of the number one song from the years 1970 to 2000. They are arranged based on beats per minute and year. The color is on a beats per minute scale and the size is measured on a beats per minute
scale.
3D and Virtual Reality Project
This is a super cool virtual reality project where I make flowers fall from the sky!


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2 2 200 sqm
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South Coogee, NSW
2 2 200 sqm
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Kingsford, NSW
2 2 200 sqm
If you’re thinking of buying a new property it’s always a good idea to know how much your current property is worth. Simply click the button below to book a time.