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children iterator
children qname iterator
children with specific attribute iterator
comment
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Parameter Container
Neethi_assertion_builder
Rp_algoruthmsuite
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Rp_asymmetric_binding
Rp_asymmetric_binding_builder
Rp_binding_commons
Rp_bootstrap_policy_builder
Rp_defines
Rp_element
Rp_encryption_token_builder
Rp_header
Rp_https_token
Rp_https_token_builder
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Trust10
Rp_layout
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Rp_policy_creator
Rp_property
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Rp_rampart_config
Rp_rampart_config_builder
Rp_recipient_token_builder
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Rp_secpolicy_builder
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Rp_signature_token_builder
Rp_signed_encrypted_elements
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Rp_supporting_tokens
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Rp_assymmetric_symmetric_binding_commons
Rp_symmetric_binding
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Rp_token
Rp_token_identifier
Rp_transport_binding
Rp_transport_binding_builder
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Rp_trust10_builder
Rp_username_token
Rp_username_token_builder
Wss10
Rp_wss10_builder
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Rp_wss11_builder
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Rp_x509_token_builder
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Demo: Various Client-side and Server-side Methods for Obtaining Cross Origin Data from NPR
What kind of NPR information do you want to view?
Show listing
For:
All topics
All music genres
All programs
Format:
XML
JSON
Method:
GET
POST
Show articles
Topic:
Afghanistan
Economy
Education
Political demographics
Method:
GET JSON from client
GET JSON from node.js using data attribute *
GET JSON from node.js using query argument *
POST from node.js using query string *
* When data is requested via node.js, the API key can remain private.


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It’s important to us to keep SRCCON small enough to feel friendly and conversational, but we also care about getting the ideas and conversations that take place at SRCCON into the wider world. The most important way this happens is when attendees return to their home newsrooms and put their new skills and approaches to work, but we are also documenting SRCCON as extensively as possible.
We had a live-captioning team transcribe 26 sessions at SRCCON. Live streams were available during these sessions, and links to the cleaned-up archives appear below.
During and after SRCCON, we have a documentation team writing up session summaries, collecting resource lists, and more. We’ll be publishing the write-ups on Source in the weeks that follow the conference, and also collecting write-ups and blog posts from attendees.


{% extends "base1.html" %} {% block title %}About Us · {{ block.super }}{% endblock %} {% block breadcrumb-wrapper %}{% endblock %} {% block content %}
SEO nowadays is in high demand as it is a need of the hour. These are the services given by expert service provider in which practices of Search Engine Optimization are being used in order to increase the number of visitors on the website by having the higher rank on search engine. If anyone wants their website to come on the top of the search engine then they have to optimize it as per google algorithm.
Now the question arises that why we need Optimization Service so the answer is whenever anyone have any kind of doubt they just go on search engines and just write a keyword to know the best-associated answer with it and as soon as we enter, the list comes in front of our eyes and have we ever bothered how this listing or how this priority has been done on the search engine. So if we want our website to come on the top of the list, then there comes the use of search engine optimization.
What are the advantages of SEO? Why someone should go with SEO Services?
By optimizing, The website gets the higher ranking on search engines and The traffic on our website will also increase along with it. It will admire for competitors, and along with all these, it will also take the business to another level and its even very cost effective marketing tactics.
Here are some advantages
• Time-Saving
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• Bring in MORE Customers
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Adbazzar is the best in Punjab because:
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We have a wide range of employees and clients too, and we had a good and sought understanding of the strategies that work best.
2. Massive Experience
We have massive experience in this field and know how to take out the result, and we have also helped a lot our previous customers with the SEO service
3. Proper & Safe
We will provide the proper and safe SEO service because we know every in and out.
4. Help You, Get Rid of Spammers
We are aware of the fact that SEO invites hacking spamming and it can be risky also so we know how to get rid of these negative consequences and keep our website ranked higher on the search engines
5. Professional & Trained Experts
Adbazzar has well-skilled employees and an excellent and hard-working, vigorous team. We provide resources at a lower cost. Adbazzar has experienced and efficient team that gives you guaranteed results.
6. Improve Your Local search
Proximity, Relevance, and Prominence are the three key points for Local optimization of your business.
Either business is big or small they all need a presence and existence online and that is the way to grow our business.
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• Help Your website in getting quality, relevant backlinks


Play Spark React
About This Application
This application demonstrates how to integrate Play and Apache Spark together, using Spark SQL to perform a non-trivial query. The application has a minimal user interface as well, mapping coordinates to the Google Map API with React and a Bootstrap Toolbar from the React Bootstrap project.
This project uses data from the World Ocean Database (WOD), maintained by the (US) National Oceanic and Atmospheric Administration. It reads a small subset of WOD data that has been downloaded and parsed separately (specifically, Moored Buoys (MRB) data from around Japan) and determines possible locations for ゴジラ (Godzilla), a potentially fictious marine animal.
At a high level, when the application is started, for example, via Activator, a Spark instance is created in memory, and a Play-based web application is started.
When you navigate your browser to http://localhost:9000, a request is made to the server, and a response is generated using a Play template. This template returns HTML and loads React via requirejs. A JS request to http://localhost:9000/locations/ (plus a number - for example, http://localhost:9000/locations/13) is serviced by a Play controller function that makes a request to Spark to execute a job and return the results. Assuming that a valid request is made and all goes well, a JSON response will be returned.
Results are retrieved from Spark as a Spark DataFrame, and are mapped to a list of Location classes before being converted to JSON as the response.
The User Interface
The Refinement toolbar buttons change the threshold of deviation from the average temperature required to "get a hit". Low refinement results in more markers, high refinement only one. The default is medium.
Spark
Configuration is provided in the application.conf file. When the Akka system starts, Spark is booted as well.
Data is provided in the data.json file. To spare you the trouble, it looks like this only bigger:
{"$type": "noaa.parser.Entry","castNumber": 10071185,"cruiseId": "JP-0","date": "2000-01-12","latitude": 34.5667,"longitude": 139.8667,"depth": 0.0,"temperature": 17.94}
{"$type": "noaa.parser.Entry","castNumber": 10071185,"cruiseId": "JP-0","date": "2000-01-12","latitude": 34.5667,"longitude": 139.8667,"depth": 50.0,"temperature": 17.83}
{"$type": "noaa.parser.Entry","castNumber": 10071185,"cruiseId": "JP-0","date": "2000-01-12","latitude": 34.5667,"longitude": 139.8667,"depth": 99.0,"temperature": 17.78}
The main prerogative of this application is to demonstrate a simple application using Play and Spark. In this specific case we are starting Spark in the same JVM as the Play app server. In a production setting, you will not want to run Spark in this manner.
The master-uri in the configuration file can be changed to reference a standalone Spark cluster. However, you may or may not want to load the test data into it, so consider that before doing so.
The Client
Facebook React provides a framework for building nice a component-based user interface. This application uses the JavaScript syntax extension, JSX. The code for the client is located in the public directory. Requirejs is used for dependency management, the requirejs configuration is located in main.js.
main.js loads and initializes app.jsx.
App.jsx is responsible for making the ajax call for location data (using JQuery), and creating the two React components- the Toolbar and the Map.
Map.jsx creates the Google Map and places LatLng locations and Markers. It responds to changes in location data automatically because it is owned by the App component.
Toolbar.jsx creates an extremely simple Bootstrap toolbar. The onclick events of the toolbar call the filter function in app.jsx, passing hardcoded values used in the server-side service to refine the query for data.


public class DBManager
extends java.lang.Object
implements com.couchbase.lite.replicator.Replication.ChangeListener
TMMCard
objects from the NoSQL database.
Note that some of the methods in this class make network accesses, which
should be done asynchronously. Since we only make calls to a DB on localhost,
we should not have any network latency so we simply block on the network
threads. If this class is used with an actual remote DB (it can be configured
to do this quite easily), then this approach could cause major freezing due
to network failure/latency. Care should then be exercised to account for the
latency in such a situation.| Modifier and Type | Class and Description |
|---|---|
private class |
DBManager.AttachmentDownloader
The Class AttachmentDownloader.
|
private class |
DBManager.DBDeleter
The Class DBDeleter.
|
private class |
DBManager.JSONGetter
The Class JSONGetter.
|
private class |
DBManager.RawJSONGetter
The Class RawJSONGetter.
|
| Modifier and Type | Field and Description |
|---|---|
static java.lang.String |
AUDIO_BACKGROUND_PATH
The JSON field identifier for the background image file path contained in
the audiocard JSON document.
|
static java.lang.String |
AUDIO_CLIP_PATH
The JSON field identifier for the path to the audio file contained in the
JSON audiocard document.
|
static java.lang.String |
AUDIO_LENGTH
The JSON field identifier for the length of the audio clip of the JSON
audiocard document.
|
private com.couchbase.lite.Database |
database
The NoSQL database: an instance of couchbase lite.
|
static java.lang.String |
DB_ARRAY
The JSON field identifier for the items in the database.
|
private java.lang.String |
dbName
The database name.
|
static java.lang.String |
DOC_ID
The JSON field identifier for the id of a document item on the DB.
|
static java.lang.String |
LOCAL_DB_URL
The Constant LOCAL_DB_URL.
|
private com.couchbase.lite.Manager |
manager
The NoSQL database manager.
|
static java.lang.String |
MASTER_SERVER_URL
The Constant MASTER_SERVER_URL.
|
static int |
port
The port number that the NoSQL DBs are running on.
|
static java.lang.String |
PRIORITY
The JSON field identifier for the priority of the JSON document.
|
static java.lang.String |
SERVER_API_INFO
The JSON field identifier for the API info of the server item in the
database.
|
static java.lang.String |
SERVER_FIRST_USED
The JSON field identifier for the time of first use of the JSON server
object from the database.
|
static java.lang.String |
SERVER_LAST_USED
The JSON field identifier for the time of last use of the JSON server
object from the database.
|
static java.lang.String |
SERVER_NAME
The JSON field identifier for the name of the JSON server object from the
database.
|
static java.lang.String |
SOURCE
The the JSON field identifier for the source server of the card JSON
document from the database.
|
private boolean |
synced
Boolean flag used to indicate when the database has finished its
synchronization process with the master.
|
static java.lang.String |
TAG
The Constant TAG.
|
static java.lang.String |
TEXT_CARD_IC_NAME
The JSON field identifier for the icon image filename contained in the
textcard JSON document.
|
static java.lang.String |
TEXT_CARD_IC_PATH
The JSON field identifier for the path of the icon image file for the
textcard contained in the JSON document.
|
static java.lang.String |
TEXT_CONTENT_IMG
The JSON field identifier for the JSON representation of the textelement
class.
|
static java.lang.String |
TEXT_CONTENT_TEXT
The JSON field identifier for the JSON representation of the textelement
class.
|
static java.lang.String |
TEXT_CONTENT_TYPE
The JSON field identifier for the JSON representation of the textelement
class.
|
static java.lang.String |
TEXT_CONTENTS
The JSON field identifier for the array of
TextElement JSON
objects contained in the textcard of this JSON document. |
static java.lang.String |
TEXT_LINE1
The JSON field identifier for the first (top) line of text in the
textcard contained in the JSON document.
|
static java.lang.String |
TEXT_LINE2
The JSON field identifier for the second (middle) line of text in the
textcard contained in the JSON document.
|
static java.lang.String |
TEXT_LINE3
The JSON field identifier for the third (bottom) line of text in the
textcard contained in the JSON document.
|
static java.lang.String |
TITLE
The JSON field identifier for the title of the card JSON document in the
database.
|
static java.lang.String |
TYPE
The JSON field identifier for the type of card contained in the JSON
document.
|
static java.lang.String |
UUID
The JSON field identifier for the UUID of an item from the database.
|
static java.lang.String |
UUID_GETTER_PATH
The Constant UUID_GETTER_PATH.
|
static java.lang.String |
VIDEO_PLAY_COUNT
The the JSON field identifier for the play count field in the videocard
JSON document.
|
static java.lang.String |
VIDEO_SS_PATH
The the JSON field identifier for the path of the screenshot image file
for the video card contained in the JSON document, if it exists.
|
static java.lang.String |
VIDEO_YOUTUBE_TAG
TThe the JSON field identifier for the youtube tag of the videocard
contained in the JSON document.
|
| Constructor and Description |
|---|
DBManager(Context context)
Instantiates a new DB manager.
|
| Modifier and Type | Method and Description |
|---|---|
boolean |
addCard(TMMCard toAdd)
Adds a
TMMCard to the database. |
void |
changed(com.couchbase.lite.replicator.Replication.ChangeEvent event) |
void |
close()
Closes the database.
|
private AudioCard |
convertJSONToAudioCard(JSONObject obj)
Creates an
AudioCard object from the JSONObject. |
TMMCard |
convertJSONToCard(JSONObject obj)
Creates a
TMMCard object from the JSONObject. |
private TextCard |
convertJSONToTextCard(JSONObject obj)
Creates a
TextCard object from the JSONObject. |
private VideoCard |
convertJSONToVideoCard(JSONObject obj)
Creates a
VideoCard object from the JSONObject. |
boolean |
createNewDB(java.lang.String dbname)
Creates a new database with the specified name locally, then synchronizes
the new database with the remote repository.
|
boolean |
deleteCardfromDB(TMMCard todel)
Delete the specified card from the database.
|
boolean |
deleteDB(boolean areYouSure)
Deletes the database currently open in this db manager.
|
private boolean |
downloadAudioCardAttachments(AudioCard cardToDl)
Download all attachments for specified
AudioCard object. |
private boolean |
downloadTextCardAttachments(TextCard cardToDl)
Download all attachments for specified
TextCard object. |
private boolean |
downloadVideoCardAttachments(VideoCard cardToDl)
Download all attachments for specified
VideoCard object. |
TMMCard |
findCardById(java.lang.String uuid)
Find a card in the database by UUID.
|
java.util.ArrayList<TMMCard> |
findCardsbyServer()
Retrieve all the cards from the currently open database in the DBManager
object.
|
private boolean |
getAllAttachments(TMMCard cardWithNoAttachments)
Downloads local copies of all the attachments for the card passed to this
method.
|
java.util.ArrayList<TMMCard> |
getAllCards()
Gets ALL cards from all servers, sorted by priority.
|
JSONObject |
getDocumentAsJSON(java.lang.String serverURLsansPort,
int port,
java.lang.String dbName,
java.lang.String UUID)
Obtains a single document from a couchDB with a given database name and
UUID.
|
java.lang.String |
getEntireDbAsJSON()
Get the entire contents of the currently open database as a JSON string.
|
JSONObject[] |
getEntireDbAsJSON(java.lang.String serverURLsansPort,
int port,
java.lang.String dbName)
Obtains every document in a couchDB in the form of a JSON object.
|
JSONObject |
getJSONRepresentation(TMMCard toCheck)
Gets the JSON representation of the specified TMMCard.
|
java.lang.String |
getName()
Gets the name of the currently open database contained in this manager.
|
java.lang.String |
getRawJSON(java.lang.String URL)
Retrieves an unparsed JSON string from a couchDB database.
|
private boolean |
getSingleAttachment(java.lang.String attachmentName,
java.lang.String uuidOfDoc,
java.lang.String pathToStore)
Gets the single attachment.
|
private java.lang.String |
getUUID()
Gets a new uuid from the database to use for the addition of new material
to the DB.
|
boolean |
isSynced()
Checks if the database currently open in the manager is synchronized with
the master database.
|
boolean |
open(java.lang.String dbName,
Context context)
Opens the database with the name specified, and synchronizes it.
|
private int |
startCBLListener(int suggestedListenPort)
Starts a local Couchbase lite NoSQL DB listening on the specified port.
|
protected void |
startDatabase(com.couchbase.lite.Manager manager,
java.lang.String databaseName)
Starts database.
|
private void |
startSync(boolean pushLocalChanges)
Starts the background synchronization of the local database in either one
or two directions.
|
private boolean |
uploadCardAttachments(TMMCard toAdd,
JSONObject jsonObject)
Upload all card attachments for a single
TMMCard . |
private boolean |
uploadSingleAttachment(byte[] data,
JSONObject jsonObject,
java.lang.String fileName,
java.lang.String contentType)
Upload single attachment to the JSONObject passed in.
|
private com.couchbase.lite.Database database
private com.couchbase.lite.Manager manager
private java.lang.String dbName
public static final java.lang.String TAG
public static final java.lang.String MASTER_SERVER_URL
public static final java.lang.String LOCAL_DB_URL
public static final java.lang.String UUID_GETTER_PATH
public static final int port
public static final java.lang.String DB_ARRAY
public static final java.lang.String DOC_ID
public static final java.lang.String TYPE
public static final java.lang.String UUID
public static final java.lang.String PRIORITY
public static final java.lang.String TITLE
public static final java.lang.String SOURCE
public static final java.lang.String SERVER_NAME
public static final java.lang.String SERVER_API_INFO
public static final java.lang.String SERVER_FIRST_USED
public static final java.lang.String SERVER_LAST_USED
public static final java.lang.String AUDIO_LENGTH
public static final java.lang.String AUDIO_CLIP_PATH
public static final java.lang.String AUDIO_BACKGROUND_PATH
public static final java.lang.String TEXT_CARD_IC_NAME
public static final java.lang.String TEXT_CARD_IC_PATH
public static final java.lang.String TEXT_LINE1
public static final java.lang.String TEXT_LINE2
public static final java.lang.String TEXT_LINE3
public static final java.lang.String TEXT_CONTENTS
TextElement
JSON
objects contained in the textcard of this JSON document.public static final java.lang.String TEXT_CONTENT_TYPE
public static final java.lang.String TEXT_CONTENT_TEXT
public static final java.lang.String TEXT_CONTENT_IMG
public static final java.lang.String VIDEO_SS_PATH
public static final java.lang.String VIDEO_PLAY_COUNT
public static final java.lang.String VIDEO_YOUTUBE_TAG
private boolean synced
public DBManager(Context context) throws java.io.IOException
context
- The application context. Used to obtain a writable private
directory.java.io.IOException
- Signals that an I/O exception has occurred.public boolean isSynced()
public java.lang.String getName()
public boolean open(java.lang.String dbName, Context context) throws java.io.IOException, com.couchbase.lite.CouchbaseLiteException
dbName
- The name of the database to open (if it exists) or create if
it does not exist.context
- The current context to use for the opening of the database.java.io.IOException
- Signals that an I/O exception has occurred.com.couchbase.lite.CouchbaseLiteException
- Signals that an exception with the local NoSQL DB has been
thrown during initialization and/or sync.private int startCBLListener(int suggestedListenPort) throws java.io.IOException, com.couchbase.lite.CouchbaseLiteException
suggestedListenPort
- The number of the suggested port to listen on.java.io.IOException
- Signals that an I/O exception has occurred.com.couchbase.lite.CouchbaseLiteException
- Signals that an exception with the local NoSQL DB has been
thrown during initialization.protected void startDatabase(com.couchbase.lite.Manager manager, java.lang.String databaseName) throws com.couchbase.lite.CouchbaseLiteException
manager
- the managerdatabaseName
- the database namecom.couchbase.lite.CouchbaseLiteException
- the couchbase lite exceptionpublic void close()
private void startSync(boolean pushLocalChanges)
pushLocalChanges
- Set to true to push changes made to the local database to the
master database.public void changed(com.couchbase.lite.replicator.Replication.ChangeEvent event)
changed
in interface com.couchbase.lite.replicator.Replication.ChangeListener
public JSONObject[] getEntireDbAsJSON(java.lang.String serverURLsansPort, int port, java.lang.String dbName)
serverURLsansPort
- The URL of the server (without the port).port
- The port number of the server.dbName
- The name of the database (in this case project). NOT A URLpublic JSONObject getDocumentAsJSON(java.lang.String serverURLsansPort, int port, java.lang.String dbName, java.lang.String UUID)
serverURLsansPort
- The URL of the server (without the port).port
- The port number of the server.dbName
- The name of the database (in this case project).UUID
- The String UUID of the requested document.public java.lang.String getRawJSON(java.lang.String URL)
URL
- The URL of the document wanted from the database.public TMMCard convertJSONToCard(JSONObject obj)
TMMCard
object from the JSONObject.private VideoCard convertJSONToVideoCard(JSONObject obj)
VideoCard
object from the JSONObject. A helper method
for the above convertJSONToCard() method.private AudioCard convertJSONToAudioCard(JSONObject obj)
AudioCard
object from the JSONObject. A helper method
for the above convertJSONToCard() method.private TextCard convertJSONToTextCard(JSONObject obj)
TextCard
object from the JSONObject. A helper method
for the above convertJSONToCard() method.private boolean getAllAttachments(TMMCard cardWithNoAttachments)
cardWithNoAttachments
- The TMMCard
object with all attachment paths set, but
no actual files at those paths.private boolean downloadVideoCardAttachments(VideoCard cardToDl)
VideoCard
object.
Attachments will be saved at paths designated in parameter object. This
is a helper method for the above getAllAttachments() method.cardToDl
- The VideoCard
object with paths for attachments set,
but no actual attachment files at those paths.private boolean downloadAudioCardAttachments(AudioCard cardToDl)
AudioCard
object.
Attachments will be saved at paths designated in parameter object. This
is a helper method for the above getAllAttachments() method.cardToDl
- The AudioCard
object with paths for attachments set,
but no actual attachment files at those paths.private boolean downloadTextCardAttachments(TextCard cardToDl)
TextCard
object.
Attachments will be saved at paths designated in parameter object. This
is a helper method for the above getAllAttachments() method.cardToDl
- The TextCard
object with paths for attachments set,
but no actual attachment files at those paths.private boolean getSingleAttachment(java.lang.String attachmentName, java.lang.String uuidOfDoc, java.lang.String pathToStore)
attachmentName
- The name of the attachment to download, NOT the path.uuidOfDoc
- The UUID of the parent document of the attachment.pathToStore
- The local filesystem path to store the downloaded attachment
file.public boolean deleteDB(boolean areYouSure)
areYouSure
- Just to check that you know what you are doingpublic TMMCard findCardById(java.lang.String uuid)
uuid
- The UUID of the card to retrieve. If it is not an exact match
to an actual UUID, then the call will fail.TMMCard
with the specified UUID retrieved from the
database.public JSONObject getJSONRepresentation(TMMCard toCheck)
toCheck
- The card to obtain the JSON representation from the DB of.public boolean addCard(TMMCard toAdd) throws org.codehaus.jackson.JsonGenerationException, org.codehaus.jackson.map.JsonMappingException, java.io.IOException
TMMCard
to the database.toAdd
- The TMMCard
to add to the database.java.io.IOException
- Thrown if the is an IO problem while adding the card.org.codehaus.jackson.map.JsonMappingException
- Thrown if there is a problem mapping the card object to a
JSON string to store in the DB.org.codehaus.jackson.JsonGenerationException
- Thrown if there is a problem generating the JSON form of the
card.private java.lang.String getUUID()
private boolean uploadCardAttachments(TMMCard toAdd, JSONObject jsonObject) throws java.io.IOException
TMMCard
.toAdd
- The card containing valid paths to the files to be uploaded.jsonObject
- The JSON object returned when the card was added to the
database. This is used to revise and access the card in the DB
to add the attachments.java.io.IOException
- Signals that an I/O exception has occurred.private boolean uploadSingleAttachment(byte[] data, JSONObject jsonObject, java.lang.String fileName, java.lang.String contentType)
data
- The binary representation of the attachment to store in the
database.jsonObject
- The JSON Object containing the identifier and revision number
of the document to which the attachment will be uploaded.fileName
- The attachment's filename, which is what it will be called
after it is attached.contentType
- The MIME-type, useful for browsers wishing to view the
content.public java.lang.String getEntireDbAsJSON()
public boolean deleteCardfromDB(TMMCard todel)
todel
- The TMMCard
object to delete from the database.public boolean createNewDB(java.lang.String dbname) throws java.lang.IllegalStateException, java.io.IOException
dbname
- The name of the database to create.java.lang.IllegalStateException
- Thrown if the input stream cannot be read properly. s * @throws
IOException Signals that an I/O exception has occurred.java.io.IOException
public java.util.ArrayList<TMMCard> getAllCards()
TMMCard
objects that consists of every
card from every database maintained locally by the app.


--- title: Factory Defect Statistics keywords: fastai sidebar: home_sidebar nb_path: "notebooks/factory_defect_statistics.ipynb" ---
There are 2 factories producing tablets: one produces tablets with probability of defect 20%, another with probability of defect 80%
We have ordered single shipment having 2 tablets and received the entire shipment from the factory chosen evenly.
We opened the first tablet and it has a defect, what is the probability that the second tablet having defect as well ?
Assumptions:
"""
ans = 0.5 * case 1 + 0.5* case_2
s.t:
case 1 [factory 1] = P(exactly 2 defects from factory 1)
case 2 [factory 2] = P(exactly 2 defects from factory 2)
"""
print()
case_1 = sp.stats.binom.pmf(k=2, n=2, p=0.2)
print(f"case_1: {case_1}")
case_2 = sp.stats.binom.pmf(k=2, n=2, p=0.8)
print(f"case_2: {case_2}")
ans = 0.5*case_1 + 0.5*case_2
print(f"ans:{ans}")
class Simulator:
def __init__(self):
np.random.seed(1123)
self.factory_defect_rate = {
0: 0.2,
1: 0.8,
}
self.stats = defaultdict(int)
def choose_factory(self):
return np.random.randint(2, size=1)[0]
def is_defect(self, factory):
defect_rate = self.factory_defect_rate[factory]
x = np.random.random()
if x <= defect_rate:
return True
else:
return False
def produce_shipment(self, shipment_size=2):
factory = self.choose_factory()
res = []
for item in range(shipment_size):
is_defect = self.is_defect(factory)
res.append(is_defect)
if is_defect:
# (factory, item, is_defective)
self.stats[(factory, item, 1)] += 1
else:
# (factory, item, defective)
self.stats[(factory, item, 0)] += 1
# case when both tablets are defective
if res == [True,True]:
self.stats[(factory, 'match')] += 1
def run(self, trials):
for trial in range(trials):
self.produce_shipment()
self.stats['trials'] = trials
simulator = Simulator()
simulator.run(trials=10000)
ans = (simulator.stats[(0, 'match')] + simulator.stats[(1, 'match')])/simulator.stats['trials']
print(f"ans:{ans}")
simulator.stats
"""
{(0, 0, 0): 4074,
(0, 0, 1): 1013,
(0, 1, 0): 4070,
(0, 1, 1): 1017,
(1, 0, 0): 1008,
(1, 0, 1): 3905,
(1, 1, 0): 966,
(1, 1, 1): 3947,
'trials': 10000})
"""


{% extends 'om/base.html' %} {% load static %} {% block styles %} {% endblock %} {% block content %}
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My skills is : - Teamwork - Microsoft Office tools - Problem solving - Internet explorer - Attention to details - Adaptability - Ability to motivate others - Ability to explain complex things simply - Coordinating with others - Written and verbal communication - Researching and analyzing - Public speaking - Time management - SPSS
I don't have any experience because I dont get any chance to work


Shawarma Palace!
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{{invoice.paymentDirectDeposit}} |
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If you see this page, the nginx web server is successfully installed and working.
Further configuration is required to get the static page served.


{% extends "base.html" %} {% block content %}
Are you sure you want to delete {{athlete.name_fl()}}? Type in first and last name to confirm deletion.


--- layout: default ---
So now I've got an understanding of how to add new pages to this site without making it too complicated. I think...
A short list of ideas for future Ryan
A Paragraph.


Bootplates version {{ vm.version }} Running diagnostics ........Done Bootstrap {{ "detected ..." + vm.bootstrapVersion }} Angularjs {{ "detected ..." + vm.angularVersion }}


Lesson 2A-L2 Filtering
This lesson is about removing noise to recover real information. The method of averaging over nearby bins to get real info is called correlation filtering, there are also two types of averaging:
- Moving average, which is to take uniform average of nearby bins as real info
- Weighted moving average, which is to assign weights onto nearby bins and then take average. Also called cross correlation. A gaussian filter is usually being used.
- Matlab gaussian filter function:
‘'’matlab
h = fspecial(‘gaussian’, hsize, sigma);
surf(h)
imagesc(h);
outim = imfilter(im, h)
‘’’
Lesson 2A-L3 Linearity and convolution
- Linearity: An operator H (or system) is linear if two properties hold (f1, f2 are functions, a is a constant): 1. Additivity: H(f1 + f2) = H(f1) + H(f2); 2. Multiplicative scaling (Homogeneity of degree 1): H(af1) = aH(f1)
- But there’s a problem with correlation that, when you input a pulse function, the result after applying matrix multiplication would be mirror to the matrix function. So, we need to apply convolution.
- Boundary issues: there are several options to deal with boundaries: original, circular, replicate, symmetric.
- Sharpening filter: 2 times pulse filter - blurry filter
- Median filter, non-linear but edge preserving, can be used to filter through sparse random noise (‘salt and pepper’ noise), can be called smoothing operator.
Lesson 2A-L4 Filters as templates
- Matching a piece of picture onto the entire pictures uses a method called ‘normalized correlation’, actually it’s all about calculating chi squared… Or finding a subsequence in a sequence requires further knowledge in algorithms.
- This is especially useful in detecting some template in a complicated figure (term: template matching). Could be used in alphabet recognition, face recognition, these kinds of computer vision application areas.
Lesson 2A-L5 Edge detection: Gradients
- Edges are important in recogniting an object in an image
- Origin of edges: surface normal discontinuity, depth discontinuity, surface color discontinuity, illumination discontinuity. Edge detection is important in coverting image to curves that matter.
- Edge detection basic idea: looking for a neighborhood with strong signs of change.
- Edge is a place of rapid change in the image intensity function. So finding edges is somehow related to finding local extremes in derivatives.
- Basic idea: 1. define differential operators: when applied to the image, it returns some derivatives. 2. We apply these operators as masks/kernels that compute the image gradient function. 3. Threshold this gradient function to select the edges.
- Gradient points in the direction of most rapid increase in the intensity, in computer science, we need to do discrete gradient. So, horizongtal gradient would become df/dx = [f(x+1, y) - f(x, y)]/1
- discrete gradient operator to deal with images would look like and Sobel operator is like
- Some well-known gradient operators: Sobel, Prewitt, Roberts. Matlab filter function: filt = fspecial(‘sobel’), which applies sobel operator.
- Keep in mind the difference between correlation and convolution in image processing.
- But in real world, due to noises the gradient operator may fail somehow, so we may need to do smoothing first, or smoothing after gradient operator. (It’s a bit like in signal system, all about operators). Varying filter rather than filtering after filtering usually saves time and space.


A
Lists / Swap
Artour Babaev
Logged in as student
Lists / Swap
Problem:
Swap
Points:
2
Instructions:
Rewrite java using python.
print("Hello World")
Python <IP_ADDRESS> Awaiting Input.


{% extends "iframe_base.html" %}
{% comment %}
This template fires a jquery event 'signup-login' on document of the parent.
Intended to be used on success for an iframed-signin.
This assumes jquery has been loaded in the parent's JS space.
{% endcomment %}
{% block main_content %}
{% endblock main_content %}


BudgeTron
Real Time Household Shared Expense Tracking
Expense Entry
(current)
Reporting
Expense Entry
Roommate Name
Arsh
Michael
Natarajan
Patrick
Purchase Date (MM/DD/YYYY)
Item Name
Store Name
Store Location
Purchase Amount
Submit
Summary of Expenses


Pasting raw code into a chat or forum hurts readability and makes it harder for people to help you. The reasons for this are listed below:
Computer code is always rendered using a monospace typeface. This means each character is a set width. W is the same width as I for example. When programmers see code that's not rendered with a monospace typeface, such as in a chat app or internet forum, it's not how they're used to reading code and makes it a little harder to read quickly.
Code and discussion should be visually separate. If you're describing a problem in a piece of code then write the code directly underneath without using code blocks, it can be difficult to distinguish where the explanation ends and the code begins.
Most platforms that use Markdown code blocks also support syntax highlighting for common programming languages and file formats! By using a code block with highlighting, it makes the code more readable by programmers who are accustomed to reading code in their editors.
Most platforms have settled on Markdown as the preferred formatting language:
```js (async function(){ let books = await getAllBooks(); console.log(books); })(); ```
Notice how js
follows the ```
, this indicates
which syntax highlighting to use.
Hopefully this has been informative. Now whenever you're helping someone and they share some code or error messages directly into the chat without using a code block, help them anyway but direct them here so they don't make the same mistake next time!
Other similar problems: Don't Post Text as an Image, Don't Ask to Ask, Just Ask, The XY Problem, No Hello.
Further reading: How do I ask a good question?, How To Ask Questions The Smart Way.


public class MTRandom
extends java.util.Random
A Java implementation of the MT19937 (Mersenne Twister) pseudo random number generator algorithm based upon the original C code by Makoto Matsumoto and Takuji Nishimura (see http://www.math.sci.hiroshima-u.ac.jp/~m-mat/MT/emt.html for more information.
As a subclass of java.util.Random this class provides a single canonical method next() for generating bits in the pseudo random number sequence. Anyone using this class should invoke the public inherited methods (nextInt(), nextFloat etc.) to obtain values as normal. This class should provide a drop-in replacement for the standard implementation of java.util.Random with the additional advantage of having a far longer period and the ability to use a far larger seed value.
This is not a cryptographically strong source of randomness and should not be used for cryptographic systems or in any other situation where true random numbers are required.
This software is licensed under the CC-GNU LGPL.
| Constructor | Description |
|---|---|
MTRandom() |
The default constructor for an instance of MTRandom.
|
MTRandom(boolean compatible) |
This version of the constructor can be used to implement identical
behaviour to the original C code version of this algorithm including
exactly replicating the case where the seed value had not been set
prior to calling genrand_int32.
|
MTRandom(byte[] buf) |
This version of the constructor initialises the class with the
given byte array.
|
MTRandom(int[] buf) |
This version of the constructor initialises the class with the
given integer array.
|
MTRandom(long seed) |
This version of the constructor simply initialises the class with
the given 64 bit seed value.
|
| Modifier and Type | Method | Description |
|---|---|---|
protected int |
next(int bits) |
This method forms the basis for generating a pseudo random number
sequence from this class.
|
static int[] |
pack(byte[] buf) |
This simply utility method can be used in cases where a byte
array of seed data is to be used to repeatedly re-seed the
random number sequence.
|
void |
setSeed(byte[] buf) |
This method resets the state of this instance using the byte
array of seed data provided.
|
void |
setSeed(int[] buf) |
This method resets the state of this instance using the integer
array of seed data provided.
|
void |
setSeed(long seed) |
This method resets the state of this instance using the 64
bits of seed data provided.
|
public MTRandom()
public MTRandom(boolean compatible)
If the compatibility flag is set to true, then the algorithm will be seeded with the same default value as was used in the original C code. Furthermore the setSeed() method, which must take a 64 bit long value, will be limited to using only the lower 32 bits of the seed to facilitate seamless migration of existing C code into Java where identical behaviour is required.
Whilst useful for ensuring backwards compatibility, it is advised that this feature not be used unless specifically required, due to the reduction in strength of the seed value.
compatible
- Compatibility flag for replicating original
behaviour.public MTRandom(long seed)
seed
- The seed value with which to initialise this class.public MTRandom(byte[] buf)
buf
- The non-empty byte array of seed information.java.lang.NullPointerException
- if the buffer is null.java.lang.IllegalArgumentException
- if the buffer has zero length.public MTRandom(int[] buf)
buf
- The non-empty integer array of seed information.java.lang.NullPointerException
- if the buffer is null.java.lang.IllegalArgumentException
- if the buffer has zero length.public final void setSeed(long seed)
If this instance was initialised in 'compatibility' mode then this method will only use the lower 32 bits of any seed value passed in and will match the behaviour of the original C code exactly with respect to state initialisation.
setSeed
in class java.util.Random
seed
- The 64 bit value used to initialise the random
number generator state.public final void setSeed(byte[] buf)
buf
- The non-empty byte array of seed information.java.lang.NullPointerException
- if the buffer is null.java.lang.IllegalArgumentException
- if the buffer has zero length.public final void setSeed(int[] buf)
buf
- The non-empty integer array of seed information.java.lang.NullPointerException
- if the buffer is null.java.lang.IllegalArgumentException
- if the buffer has zero length.protected final int next(int bits)
Note that where the number of bits requested is not equal to 32 then bits will simply be masked out from the top of the returned integer value. That is to say that:
mt.setSeed(12345); int foo = mt.nextInt(16) + (mt.nextInt(16) << 16);will not give the same result as
mt.setSeed(12345); int foo = mt.nextInt(32);
next
in class java.util.Random
bits
- The number of significant bits desired in the output.public static int[] pack(byte[] buf)
If the length of the byte array is not a multiple of 4 then it is implicitly padded with zeros as necessary. For example:
byte[] { 0x01, 0x02, 0x03, 0x04, 0x05, 0x06 }becomes
int[] { 0x04030201, 0x00000605 }
Note that this method will not complain if the given byte array is empty and will produce an empty integer array, but the setSeed() method will throw an exception if the empty integer array is passed to it.
buf
- The non-null byte array to be packed.java.lang.NullPointerException
- if the given byte array is null.Copyright © 2020 University of Waikato, Hamilton, NZ. All Rights Reserved.


{% extends "base.html" %} {% import "snippets.html" as snippets %} {% block title %}Install Nuvola Player • {{ super() }}{% endblock %} {% block content %}
Nuvola Player are provided as cross-distribution Flatpak packages. They should work on every Linux distribution.
{% if not distro_spec %}Follow installation instructions to install Nuvola Player on:


German pensions deal shows coalition is working: ruling parties
BERLIN (Reuters) - A deal on a higher basic pension for low-income workers that Germany’s ruling parties clinched on Sunday shows their alliance can deliver results and should carry on governing, senior officials from both camps said.
Disagreement over the basic pension, or Grundrente, was the latest issue to test the awkward coalition between Chancellor Angela Merkel’s conservatives and their Social Democrat (SPD) partners, until they broke the deadlock on Sunday.
The SPD needed to secure a deal it could sell as a social milestone at a Dec. 6-8 party congress, where it will decide whether to stay in the coalition. Some members, worried by the party’s falling ratings, want to rebuild in opposition.
Failing to reach a deal would have threatened the collapse of the government. But Labour Minister Hubertus Heil called the pension package “a good solution” and said it showed the coalition could deliver results.
“And if the coalition in this country is dealing with what concerns people then, in my view, it should continue to work,” he told broadcaster ARD on Monday. “It was a good day. It showed the ability to act,” he added of Sunday’s agreement.
The package, sealed during talks that lasted more than six hours, also includes lower contributions to the public unemployment insurance scheme and the creation of an investment fund to support local high-tech start-ups.
Markus Soeder, leader of Merkel’s Bavarian CSU allies, said on Sunday: “In my view, there is no reason any more to discuss the continued existence (of the coalition).”


Don't need empty line if div at the beginning of the file.
Here is a paragraph.
And another.
Here is a paragraph.
Here is a paragraph.
Here is a paragraph.
Here is a paragraph.
This is a warning.
This is a warning within a warning.
::::::::::::::::::
Bonjour
This is a warning.
Aurevoir
This is a warning.


Before Change
ax.set_title("raw data")
fig.tight_layout()
pylab.show()
After Change
// or use a some convolutions to increase the number of channels
// before the the UNet.
from inferno.extensions.layers import ConvReLU2D
model_a = torch.nn.Sequential(
ConvReLU2D(in_channels=image_channels, out_channels=5, kernel_size=3),
ResBlockUNet(dim=2, in_channels=5, out_channels=pred_channels, activated=False,
res_block_kwargs=dict(batchnorm=True,size=2)) ,
RemoveSingletonDimension(dim=1)
// torch.nn.Sigmoid()
)


Coronavirus disease (COVID-19) outbreak in Finland
This is a map visualising the data of the number of confirmed cases of coronavirus disease Covid-19 in Finland. The first case in Finland was reported on Feb 26, 2020 and since then the numbers have been rapidly rising.
Confirmed
Recovered
Deaths
Hospitalised
In ICU
More resources and links:
- Finnish Institute for Health and Welfare (THL)
- Coronavirus disease (COVID-19) advice for the public (World Health Organization)
- Latest news (YLE)
- 2020 coronavirus pandemic in Finland (Wikipedia)
Infections, recoveries & deaths by day
| Infected | Recovered | Deaths | Hospitalised | In ICU | Healthcare District |
|---|


Development And Demonstration Of Trace Metals Database
EPA Grant Number: R827649C001Subproject: this is subproject number 001 , established and managed by the Center Director under grant R827649
(EPA does not fund or establish subprojects; EPA awards and manages the overall grant for this center).
Center: Center for Air Toxic Metals® (CATM®)
Center Director: Groenewold, Gerald
Title: Development And Demonstration Of Trace Metals Database
Investigators: Folkedahl, Bruce C. , Beard, Roy B. , Benson, Steven A. , Galbreath, Kevin C. , Hanson, Paul R. , Hassett, J. , Holmes, Karen , Jensen, John , Laudal, Dennis L. , Maki, Andrew B. , Miller, Stanley J. , Olson, Edwin S. , Pavlish, John H. , Peck, Wes D. , Zygarlicke, Christopher J.
Institution: University of North Dakota
EPA Project Officer: Stelz, Bill
Project Period: October 15, 1999 through October 14, 2002
Project Amount: Refer to main center abstract for funding details.
RFA: Center for Air Toxic Metals (CATM) (1998) RFA Text | Recipients Lists
Research Category: Targeted Research
Objective:
The enormous amount of data generated in response to the increased awareness and concern regarding trace element transformation, analysis, and control is of marginal use if it is not easily accessible. To address the need for a more convenient and efficient method to utilize this ever-growing pool of data, a relational database and associated user interface were developed (Program Area 4). Information currently in the database was derived from compiled reports and test results from a variety of commercial, federal, and academic sources, including data derived from the ongoing CATM technical projects pertaining to trace element transformation, analysis, and control (Program Areas l-3) . The database has been demonstrated at various conferences and expositions and is also promoted during the Trace Elements Short Course (Program Area 5) as a tool to predict trace element emissions from fuel conversion and emission control systems.
Goals associated with this project are directed toward the development, maintenance, and improvement of tools used in the decision-making process involved in management, operation, and long-term planning of issues related to air toxic metals. Specific goals set and met in this year are as follows:
- Collection and critical review of new data
- Enhancement and debugging of the graphical user interface (GUI)
- Initial development and integration of a GIS with the CATM database
- Presentation of the use and capabilities of the CATM database at a national convention focusing on issues of air toxic metals
Approach:
The CATM database was developed to serve as a centralized storage media for air toxic metals data, accessible internally through the local area network and externally through the Internet. The information in the database is organized in three major categories: analytical, engineering, and materials. The database uses a samples-based approach; i.e., a sample must contain analytical information to be included in the database. Engineering information in and of itself is not included in the database, but is entered only in association with sample information. This approach was used so that the database remains focused on trace element emissions, as there are other databases containing strictly engineering or strictly analytical information. The CATM database links this information together, such that queries regarding samples can be related to engineering and/or analytical information along with geographical information coupled in a GIS system.
The application was designed so that navigating through the database is intuitive for the user. In addition, the intended users of the database-plant operators, researchers, government personnel, plant managers, etc.-were considered. Overall, the application was designed to be simple and user-friendly, yet provide a variety of data presentations to serve a specified variety of end users.
Here is an example of how the database may be applied in researching a specific topic:
Question: Since coal-cleaning processes commonly remove a substantial amount of pyrite, could we also expect removal of As and Hg?
Approach: Use the database to correlate the Fe concentration of a number of coals with their Hg and As contents. In addition, compare the As and Hg concentrations of pulverizer rejects produced during coal processing to the resulting feed coal (pulverizer rejects are commonly high in pyrite).
The ongoing collection and input of data are extremely important for the CATM database. Industrial participation will greatly benefit the database, as well as participation from other research organizations and government agencies. In dealing with new sources of data, especially industrial data, confidentiality and security features of the database are designed to satisfy the submitter of data. Security features are implemented as necessary to ensure the level of confidentiality requested by the submitter.
Progress
The first version of the database application was completed in 1996. Data from nine full- and several bench- and pilot-scale systems were entered in the database. The bench- and pilot-scale data have been verified for input errors. Four more sets of system and analytical data have been added and are in the process of being verified for input errors. Data entry is an ongoing process that will continue throughout the CATM project.
Information in the database has been used to create an initial GIS system to display toxic metal emission data according to geographic location. The introduction of these data facilitates the usefulness and integration potential of the information contained in the CATM database. Readily available and consistent location identification data of permanent and full-scale facilities will support the development of environmental risk management strategies and assessments. The ability to link the geographical information within the CATM database with a commercially available GIS will be demonstrated.
The database was developed using client/server technology. Client/server technology allows for a physical separation between the residence of the data and the residence of the application. The data are stored in a database engine on a separate UNIX workstation that functions as a server. Traditional relational database management system design strategies were used to optimize data storage and retrieval. The application was created with PowerBuilder (PowerSoft, Inc.), a Windows-based, high-performance, object-oriented development tool. The application resides on users' individual computers and represents the client side of the architecture. The application presents the users with options for querying and displaying data through user-friendly forms and reports. Data are retrieved from the database through structured query language (SQL) calls to the server and displayed via the application on the user's PC. This arrangement takes advantage of the processing ability of the client's PC to perform functions such as sorting and arranging data that have been retrieved from the server. The server is optimized to interpret the SQL statements and perform database management functions.
The CATM application allows the user to develop very complex queries and provides many features for the display and manipulation of the retrieved data. To access the database through the Internet, a user must have access to an Internet provider and must be able to run a SLIP (serial line interface protocol) connection. (In most cases, if a user has an Internet provider, SLIP can be downloaded as freeware.) Once the SLIP connection is made, the user simply initiates the CATM application. This arrangement provides the users with all of the processing power of their PCS, i.e., speed. The only transfer of information over the Internet is the SQL statement sent to the server and the resulting data retrieved from the server and sent back to the clients' PCs. All of the other processing is executed on the individual PC. This is very important, as quick response time is essential for those using the database.
The Facility for Analysis of Chemical Thermodynamics (FACT) model has been acquired by the EERC to quantify chemical equilibria in various combustion and gasification systems. The FACT model is a comprehensive thermodynamic model that performs chemical equilibrium calculations for systems consisting of solid, liquid, gaseous, and/or aqueous phases. It contains a thermochemical database with more than 6500 species; 24 elements and 550 product species can participate in one equilibrium reaction; over 90 binary, ternary, and higher-order solutions are available to represent systems with nonideal mixing, such as slag and glass; FACT has the capability to model open systems (gas or liquids can be removed from the system in discrete intervals) to represent quasi-kinetic systems; options are available for systems to contain aqueous species, nonideal gases, and plasma ions.
New or improved thermodynamic data can be easily added to the FACT database. The EERC has added over a dozen new compounds, mainly on trace elements. Optimized solutions have been added for a number of (nonstoichiometric) ash minerals. The FACT model contains graphical tools to display input data and results and to assist in the optimization of user-defined solutions. A special feature of the FACT code is the construction of phase diagrams that are helpful in identifying metastable equilibria. A composition can be graphed as a function of temperature, pressure, or compound concentration. Spreadsheet macros have been developed to link these output files and display the results in 2-D and 3-D graphs.
Rationale:
The CATM database has been established to facilitate research on the prevention, transformation, behavior, and control of toxic metal emissions from energy-producing and incineration systems. The primary applications of the database are to aid in the development of methods to predict the fate of metals in fossil fuel systems, determine the effectiveness of control devices, assist in identifying new control technologies, and provide source-emission data that can be used to assess health risks. The database provides an interactive user application from which users can quickly and efficiently access and display information relevant to their particular need or area of concern. The data are maintained in a relational database engine at the EERC; however, the application has been designed such that the data are accessible through the Internet.
Publications and Presentations:
Publications have been submitted on this subproject: View all 33 publications for this subproject | View all 235 publications for this centerJournal Articles:
Journal Articles have been submitted on this subproject: View all 4 journal articles for this subproject | View all 39 journal articles for this centerSupplemental Keywords:
RFA, Economic, Social, & Behavioral Science Research Program, Scientific Discipline, Air, Ecosystem Protection/Environmental Exposure & Risk, air toxics, exploratory research environmental biology, Environmental Chemistry, Ecosystem/Assessment/Indicators, Chemical Mixtures - Environmental Exposure & Risk, Ecosystem Protection, Ecological Effects - Environmental Exposure & Risk, Ecological Effects - Human Health, decision-making, Environmental Engineering, Economics & Decision Making, Ecological Indicators, mercury, decision analysis, environmental decision making, decision making, toxic metals, chemical databases, trace metals database, modelsProgress and Final Reports:
2001 Progress Report2002 Progress Report
Final Report
Main Center Abstract and Reports:
R827649 Center for Air Toxic Metals® (CATM®) Subprojects under this Center: (EPA does not fund or establish subprojects; EPA awards and manages the overall grant for this center).
R827649C001 Development And Demonstration Of Trace Metals Database
R827649C002 Nickel Speciation Of Residual Oil Ash
R827649C003 Atmospheric Deposition: Air Toxics At Lake Superior
R827649C004 Novel Approaches For Prevention And Control For Trace Metals
R827649C005 Wet Scrubber System
R827649C006 Technology Commercialization And Education
R827649C007 Development Of Speciation And Sampling Tools For Mercury In Flue Gas
R827649C008 Process Impacts On Trace Element Speciation
R827649C009 Mercury Transformations in Coal Combustion Flue Gas
R827649C010 Nickel, Chromium, and Arsenic Speciation of Ambient Particulate Matter in the Vicinity of an Oil-Fired Utility Boiler
R827649C011 Transition Metal Speciation of Fossil Fuel Combustion Flue Gases
R827649C012 Fundamental Study of the Impact of SCR on Mercury Speciation
R827649C013 Development of Mercury Sampling and Analytical Techniques
R827649C014 Longer-Term Testing of Continuous Mercury Monitors
R827649C015 Long-Term Mercury Monitoring at North Dakota Power Plants
R827649C016 Development of a Laser Absorption Continuous Mercury Monitor
R827649C017 Development of Mercury Control Technologies
R827649C018 Developing SCR Technology Options for Mercury Oxidation in Western Fuels
R827649C019 Modeling Mercury Speciation in Coal Combustion Systems
R827649C020 Stability of Mercury in Coal Combustion By-Products and Sorbents
R827649C021 Mercury in Alternative Fuels
R827649C022 Studies of Mercury Metabolism and Selenium Physiology


#assign n0_intro="active"> <#assign n1_configuration="active">
io.ebean.Database can automatically be configured via properties in application.yaml
,
application.properties
etc.
The default database name is db
so the minimal configuration looks like:
## H2 setup - In memory datasource: db: username: sa password: sa url: jdbc:h2:mem:myapp
datasource: db: username: my_app password: my_password url: jdbc:postgresql://localhost:5432/my_app
Generally we want Ebean to run migrations on startup and we have ebean.migration.run
set to true
.
Generally for Postgres we set ebean.dbSchema
to match the database username when
we want database tables etc to be in that named schema rather than the public
schema.
ebean: dbSchema: my_app # use this schema rather than public migration: run: true # run database migrations on startup datasource: db: username: my_app password: ${myPassword} url: jdbc:postgresql://${myDatabaseHost}:5432/my_app ## Expects system properties to be set for: ## myPassword and myDatabaseHost
When using multiple databases we set multiple datasource configurations.
The non-default databases have a name. For example, if we have a second
database called "other"
we configure a second datasource
like below:
ebean: dbSchema: my_app # use this schema rather than public migration: run: true # run database migrations on startup datasource: db: username: my_app password: ${myPassword2} url: jdbc:postgresql://${myDatabaseHost2}:5432/my_app other: username: other_username password: ${otherPassword} url: jdbc:postgresql://${otherDatabaseHost}:5432/other_dbname
We can obtain the "other" database instance by it's name:
<#include "/_common/lang-buttons.html"/>// obtain "other" database by its name Database otherDatabase = DB.byName("other");
// obtain "other" database by its name val otherDatabase = DB.byName("other");
Goto docs / multi-database for more details on using multiple databases
with @DbName
, Model and Finder.
We can programmatically create a Database instance using DatabaseFactory and DatabaseConfig.
<#include "/_common/lang-buttons.html"/>// datasource DataSourceConfig dataSourceConfig = new DataSourceConfig(); dataSourceConfig.setUsername("sa"); dataSourceConfig.setPassword(""); dataSourceConfig.setUrl("jdbc:h2:mem:myapp;"); // configuration ... DatabaseConfig config = new DatabaseConfig(); config.setDataSourceConfig(dataSourceConfig); ... // create database instance Database database = DatabaseFactory.create(config);
// datasource val dataSourceConfig = new DataSourceConfig() dataSourceConfig.setUsername("sa") dataSourceConfig.setPassword("") dataSourceConfig.setUrl("jdbc:h2:mem:myapp;") // configuration ... val config = new DatabaseConfig(); config.setDataSourceConfig(dataSourceConfig) ... // create database instance val database = DatabaseFactory.create(config)
We can set ddl.generation and ddl.run true for simple testing against in memory H2 or a provided database instance (especially if our application is read only).
ebean: ddl: generate: true run: true # initSql: test-init.sql # seedSql: test-seed.sql datasource: db: username: sa password: sa url: jdbc:h2:mem:myapp
ebean-test
was built to help with testing against the target database
(Postgres, MySql, MariaDB, SQLServer, Oracle ...).
Docker especially can be used to programmatically setup and initialise the database for testing
purposes.
Testing against the full featured target database(s) comes with a number of advantages in terms of testing and coverage that we talk about at docs / testing.
ebean-test reads the configuration in
src/test/resources/application-test.yaml
.
See the example below:
ebean: test: platform: postgres # h2, postgres, mysql, ... ddlMode: dropCreate # none | dropCreate | migration dbName: my_app
ebean-test hooks into the Ebean startup and configures the datasource based on
ebean.test.platform
and configures the DDL generation and execution
based on ebean.test.ddlMode
(plus start, setup and wait for docker
container(s) as necessary when using docker test containers).
Using ebean-test is the recommended approach
for testing as it puts us in a position where we can easily change the database used for testing.
For example, changing from testing against H2 to testing against Postgres docker container
is as simple as changing ebean.test.platform
to postgres
.
Refer to docs / testing for more details.
<@next_edit "First Entity" "/docs/intro/first-entity" "/docs/intro/configuration/index.html"/>


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today’s Very Short List:
culture 14 Jan 2015
During Shannon Bahrke’s skiing career, she brought home 2 Olympic Medals, 7 World Cup Wins, 1 Overall World Cup Title and 6 National Titles. Since her retirement in 2010, Shannon and her husband founded Silver Bean Coffee Co. in Deer Valley, UT. This year, she became Montage Deer Valley
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* The FIS Freestyle Ski World Cup just took place last weekend at Deer Valley. The aerial finals
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This page enables you to save the current configuration of the simulator locally (under a specific name) so that you may load it next time you use FRISCjs. Currently, a configuration consists of the FRISC assembly program defined in the editor, the CPU speed, memory size and the set of defined I/O units. In the future, the configuration might be extended to include defined breakpoints, CPU state, etc. Furthermore, this page enables you to export configurations in text format so that they can be shared (e.g. via e-mail) and saved externally (e.g. as a GitHub gist), and import previously exported configurations. In order to save/load and import/export, the simulator must be in a stopped state.
This page contains examples for using FRISCjs. Each example is given as a brief description and a link to a configuration which can be loaded using the Load/Save tab. Just copy/paste the configuration into the import box and click "Import".
This most basic example adds values from registers R0 and R1 and stores the result into R2.
This example doesn't do anything useful, but contains every FRISC instruction. Useful for testing and debugging.
This example uses a FRISC CT IO unit for simple counting - an in-memory counter is incremented for every 400 periods of the FRISC CT unit. The configuration contains a FRISC CT unit configured at 1000Hz.
This example uses a FRISC PIO IO unit for reading 40 data items. The configuration contains a FRISC PIO unit configured at 1000Hz.
This example uses a FRISC DMA IO unit for transferring 1000 4-byte words from an IO unit mapped on 0xFFFF3330 to memory starting from location 0x4000, using halting transfer mode.
FRISCjs is a simulator of the FRISC processor written in JavaScript. FRISC is a simple, educational RISC processor developed at the University of Zagreb, Faculty of Electrical Engineering and Computing. The simulator has two parts: a FRISC assembler (built using PEGjs) which translates FRISC assembly code to machine code and a FRISC CPU simulator which executes machine code. This Web application is a graphical interface for the simulator, while there also exists a console interface which runs on NodeJS.
The complete source code for FRISCjs and this Web application is available on GitHub. Please use the GitHub issue tracker for reporting bugs and feature requests.
FRISCjs was developed by Ivan Zuzak. License: Apache 2.0. Contributors: Ivan Budiselic, Stanko Krtalic.
FRISCjs is built with many open-source projects: PEGjs, NodeJS, jQuery, Bootstrap, Ace, Mustache and Keymaster.


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#include <DistanceCalculator.hpp>
◆ AlphabetType
◆ CorrectionType
| Enumerator |
|---|
| not_assigned | |
| none | |
| JukesCantor | |
| Kimura2 | |
| FastTree | |
◆ DistanceCalculator()
| DistanceCalculator::DistanceCalculator |
( |
std::string ** |
A, |
|
|
AlphabetType |
alphType, |
|
|
CorrectionType |
corrType, |
|
|
int |
numberOfSequences, |
|
|
bool |
useSSE |
|
) |
| |
◆ ~DistanceCalculator()
| DistanceCalculator::~DistanceCalculator |
( |
| ) |
|
◆ calc()
| double DistanceCalculator::calc |
( |
int |
a, |
|
|
int |
b |
|
) |
| |
◆ getInverseAlphabet()
| int * DistanceCalculator::getInverseAlphabet |
( |
std::string |
alph, |
|
|
int |
length |
|
) |
| |
|
static |
◆ testDifferenceCluster()
| double DistanceCalculator::testDifferenceCluster |
( |
int |
a, |
|
|
int |
b |
|
) |
| |
| std::string** DistanceCalculator::A |
◆ aa_chars
| std::string DistanceCalculator::aa_chars |
◆ alph_type
◆ convertedSequences
| unsigned int** DistanceCalculator::convertedSequences |
◆ corr_type
◆ COUNTS_MASK
| __m128i DistanceCalculator::COUNTS_MASK |
◆ DECOMPRESSED_GAPS
| __m128i DistanceCalculator::DECOMPRESSED_GAPS |
◆ dna_chars
| std::string DistanceCalculator::dna_chars |
◆ gapInTheSequences
| unsigned int** DistanceCalculator::gapInTheSequences |
◆ GAPS_COUNT_MASK
| __m128i DistanceCalculator::GAPS_COUNT_MASK |
◆ lengthOfSequences
| int DistanceCalculator::lengthOfSequences |
◆ newCalculation
| bool DistanceCalculator::newCalculation |
◆ numberOfSequences
| int DistanceCalculator::numberOfSequences |
◆ TRANSITIONS_MASK
| __m128i DistanceCalculator::TRANSITIONS_MASK |
◆ TRANSVERSIONS_MASK
| __m128i DistanceCalculator::TRANSVERSIONS_MASK |
◆ VALUES_0
| __m128i DistanceCalculator::VALUES_0 |
◆ VALUES_1
| __m128i DistanceCalculator::VALUES_1 |
◆ VALUES_2
| __m128i DistanceCalculator::VALUES_2 |
◆ VALUES_3
| __m128i DistanceCalculator::VALUES_3 |
◆ VALUES_4
| __m128i DistanceCalculator::VALUES_4 |
◆ VALUES_5
| __m128i DistanceCalculator::VALUES_5 |
◆ VALUES_6
| __m128i DistanceCalculator::VALUES_6 |
◆ VALUES_7
| __m128i DistanceCalculator::VALUES_7 |
◆ x128
| __m128i DistanceCalculator::x128 |
◆ zero
| __m128i DistanceCalculator::zero |
The documentation for this class was generated from the following files:


Full name:
org.jibx:maven-jibx-plugin:1.2.2:test-schema-codegen
Description:
Attributes:
test-compile
.generate-test-sources
.| Name | Type | Since | Description |
|---|---|---|---|
| directory | String |
- |
The directory which contains XSD files. Default value is: ${basedir}/src/test/config . |
| verbose | boolean |
- |
Control flag for verbose processing reports. Default value is: false . |
| Name | Type | Since | Description |
|---|---|---|---|
| customizations | ArrayList |
- |
Include pattern for customization files. |
| defaultNamespace | String |
- |
Namespace applied in code generation when no-namespaced schema
definitions are found (to generate no-namespaced schemas as though
they were included in a particular namespace) |
| defaultPackage | String |
- |
Default package for code generated from schema definitions with no
namespace. |
| excludes | ArrayList |
- |
Exclude pattern for binding files. |
| includeBindings | ArrayList |
- |
Include existing bindings and use mappings from the bindings for
matching schema global definitions. (this is the basis for modular
code generation) Include base bindings as follows: <includeBindings> <includeBinding>base-binding.xml</includeBinding> </includeBindings> Note: Relative paths start at ${basedir}. |
| includes | ArrayList |
- |
Include pattern for schema files. Note: Uses the standard filter format described in the plexus DirectoryScanner. Defaults value is: *.xsd. |
| options | Map |
- |
Extra options to be given for customization via CLI.
Enter extra customizations or other command-line
options. The extra customizations are described on the CodeGen customizations page The single character CodeGen commands may also be supplied here. For example, to include a base binding file (-i) and prefer-inline code, supply the following options: <options> |
| targetDirectory | String |
- |
Target directory where to generate Java source files. Default value is: ${basedir}/target/generated-test-sources . |
java.util.ArrayList
No
${customizations}
java.lang.String
No
java.lang.String
No
java.lang.String
Yes
${directory}
${basedir}/src/test/config
java.util.ArrayList
No
${excludes}
java.util.ArrayList
No
${includeBindings}
java.util.ArrayList
No
${includes}
<options>
<i>base-binding.xml</i>
<prefer-inline>true</prefer-inline>
</options>
java.util.Map
No
java.lang.String
No
${targetDirectory}
${basedir}/target/generated-test-sources
boolean
Yes
${verbose}
false


The AudioMixer is an Asset that can be referenced by AudioSources to provide more complex routing and mixing of the audio signal generated from AudioSources. It does this category based mixing via the AudioGroup hierarchy that is constructed by the user inside the Asset.
DSP effects and other audio mastering concepts can be applied to the audio signal as it is routed from the AudioSource to the AudioListener.
http://en.wikipedia.org/wiki/Audio_mixing
Audio routing is the process of taking a number of input audio signals and outputting 1 or more output signals. The term signal here refers to a continuous stream of digital audio data, which can be broken down into digital audio channels (such as stereo or 5.1 (6 channels)).
Internally there is usually some work on these signals being done, such as mixing, applying effects, attenuation etc. For various reasons that will be covered, this is an important aspect of audio processing and this is what the AudioMixer is designed to allow you to do.
With the exception of Sends and Returns (which will be covered later), the AudioMixer contains AudioGroups that allow any number of input signals, mix those signals and have exactly 1 output.
In the land of audio processing, this routing and mixing is usually done ORTHOGONAL to the scene graph hierarchy, as audio behaves and designers interact with audio very differently to objects and concepts shown in the scene.
In previous versions of Unity, the concept of routing and mixing was not available. Users were able to place AudioSources within the scene, and the audio signal that they produced (via AudioClips for example) was routed directly to the AudioListener, where all the audio signals were mixed together at one point. Remember here that this is happening orthogonal to the scene graph and no matter where your AudioSources are in the scene,
AudioMixers now sit between the AudioSource and the AudioListener in the audio signal processing space and allow you to take the output signal from the AudioSource perform whatever routing and mixing operations they wish until finally all audio is output to the AudioListener and is heard from the speakers.
Mixing and routing allows you to categorise the audio within their game into whatever concepts they desire. Once sound is mixed together into these categories, effects and other operations can be applied to these categories as a whole. This is powerful not only applying game logic changes to the various sound categories, but also for allowing designers to tweak the various aspects of the mix to perform whats knows as “Mastering” of the entire soundscape dynamically at runtime.
Some sound concepts are related to the scene graph and the 3D world. The most obvious of those is the application of attenuation based on 3D distance, relative speed to the AudioListener and environmental Reverb effects.
As these operations are related to the scene and not to the categories of sounds in an AudioMixer, the effects are applied at the AudioSource, before the signal enters an AudioMixer. For example, the attenuation applied to an AudioSource based on its distance from the AudioListener is applied to the signal before it leaves the AudioSource and is routed into an AudioMixer.
As stated above, AudioMixers allow you to effectively categorise types of sounds and do stuff to these categories. This is an important concept, because without such categorisations, the entire soundscape quickly becomes a mess of indistinguishable noise as every sound is played back equally and without any mixing applied to them. With concepts such as ducking, categories of sounds can also influence each other, adding additional richness to the mix.
Examples of operations that designers might want to do on a category are;
These categories are really quite game specific and vary between different projects, but an example of such categorisation might be described as follows;
The category hierarchy of this layout would look something like this:
Note that the scene graph layout would look nothing like the layout for sound categories.
Mixing and routing of the games sounds can also be used to create the immersion the designer is looking for. For example, reverb can be applied to all of the game sounds and the music attenuated to create the feeling of being in a cave.
The AudioMixer can be used effectively to create moods within the game. Using concepts such as snapshots (explained later) and other different mixers within a game, the game can transition its mood easily and emote the player into feeling what the designer wishes, which is super powerful in the immersion of the game.
The AudioMixer is used to control the overall mix of all the sounds within a game. These AudioMixers control the global mix and can be seen as the static singleton mix that sound instances are routed through.
In other worlds, the AudioMixers are always present through the lifetime of a scene, and sound instances are created and destroyed as the game progresses and play through these global AudioMixers.
Snapshots allow you to capture the state of an AudioMixer, and transition between these different states as the game progresses. This is a great way to define moods or themes of the mix and have those moods change as the player progresses through the game.
Snapshots capture the values of all of the parameters within the AudioMixer;
Combining Snapshots with game logic is a great way to change many aspects of the soundscape.


About Us
Here at Salmon Cookies we are family-friendly, super duper awesome, and make the most delicious fish flavored cookies you'll ever taste! Swamp-eel nibbler Pacific albacore European chub common tunny pearlfish archerfish sand knifefish sábalo lake chub. Barbel longnose chimaera cuchia hoki Peter's elephantnose fish broadband dogfish, "rough pomfret; common tunny horn shark." Menhaden loach goby pikeperch marblefish: four-eyed fish lungfish stingray. Blue gourami, Australian lungfish fathead sculpin. Rudderfish, Bitterling, smoothtongue, ghost pipefish killifish, "burrowing goby slipmouth mudskipper African glass catfish." Pigfish wolf-herring tilefish, arrowtooth eel European minnow silver dollar oilfish mudskipper roundhead, leopard danio ruffe scaleless black dragonfish. Loach goby flathead woody sculpin slimehead Rasbora clown triggerfish freshwater hatchetfish. Fire bar danio wrasse morwong sabertooth: Mozambique tilapia round whitefish toadfish peamouth. Eagle ray Rio Grande perch lyretail pufferfish round whitefish Moorish idol king-of-the-salmon, Billfish mahi-mahi alooh, "bull shark Russian sturgeon pearl danio, sargassum fish." Queen triggerfish wrymouth pricklefish daggertooth pike conger.  Saw shark Dolly Varden trout Australian grayling. Mola hawkfish Oriental loach splitfin inanga gouramie Australian herring codling fusilier fish bamboo shark banjo catfish galjoen fish, speckled trout: skipping goby. Spanish mackerel jewfish northern Stargazer baikal oilfish dorab gianttail pike conger electric ray. Redmouth whalefish fingerfish cardinalfish, longfin dragonfish trunkfish Pacific albacore powen tope burbot, cutthroat eel jewel tetra, silverside pomfret silverside black bass. Collared dogfish Blobfish, "mosquitofish turbot, yellowbelly tail catfish, silver driftfish rice eel roosterfish porcupinefish ling." Sabertooth fish Russian sturgeon velvet-belly shark; tiger shark orangestriped triggerfish, whitetip reef shark combfish airbreathing catfish nibbler Chinook salmon. Sandperch zebra turkeyfish Razorback sucker milkfish pirate perch sixgill ray; false cat shark; dragon goby; golden loach pencil catfish, vendace omnom.


Resume
- Education
- 3+ Years at University of Texas at San Antonio
- Codeup Elite Professional School for Computer Programming
- Technical Skills
- Beginning PHP
- HTML5
- CSS
- Personal Skills
- Very fast learner
- Curious when it comes to new ideas and questions
- Enjoys a dynamic workplace with ever-changing expectations
- Always looking for a new challenge to conquer
- Loves learning new things


{% extends "base.html" %} {% block content %}
This is a simple Python Flask demo web app, to be used with Azure, Docker and other demos & lab exercises. The source is on GitHub, and pre-built Docker images are available on Dockerhub
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title = "Demonstration" url = "/" layout = "default" ==
This is the Hydro Raindrop demo theme that will show you how to integrate Hydro Raindrop to your OctoberCMS powered website.
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Rainbow's Hyunyoung claps back at a malicious commenter online accusing her of getting her breasts done
by kevanimeweirdIt's been three years since Rainbow had disbanded but that doesn't seem to affect the girl's friendship as they all remained close and always come together to celebrate the group's anniversary.
Well, this year might have been different, even though we are happy to see them hanging out together for celebrating their anniversary. This year the group decided to take a different approach and decided to release a song titled "Aurora" in celebration of their tenth anniversary. Which was dropped last week, I hope you guys have a chance to listened to it, it's a really great song. If you haven't you can check it out here:
However, not everything is so gloomy. It appears Rainbow's maknae Hyunyoung is now facing accusations by a malicious commenter that claims that the singer has got her breasts done, Rainbow's Hyunyoung recently updated her Instagram account with a selfie along with the hashtags #Rainbow #10years # soyellow and #photoessay.
In the photos, you can clearly see Hyungyoung is rocking a yellow plaid dress with matching yellow sunglasses. Her hair is in pigtail hairstyle which goes great along with her dress.
While her photo is getting praise with positive comments by her fans, one malicious commenter makes a rant on her photo and demanding the former idol to cover up.
"By posting a photo of yourself that makes it so obvious that you got a boob job, is that your way of telling everyone you a boob job? If it's obvious, you should cover-up".
But nonetheless the idol clap-backed at the malicious commenter with a classy response, she responded saying,
"I'm sorry, but if you didn't write this comment to tell everyone that your brain is empty, I suggest you delete it".


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Home-made pipe bomb seized during raid on Rockingham house
A man will face court today after a pipe bomb was uncovered during a police raid south of Perth earlier this week.
Detectives were searching the home on Harrison Street in Rockingham on Tuesday when the homemade explosive device was allegedly found on a shelf in the living room.
Police bomb technicians were called to x-ray the device, which contained gas cylinders, nuts and bolts.
It will be alleged police found a flask containing ammonium nitrate - which is commonly used in the manufacturing of explosives - and two detonators.
Police also allegedly found cannabis, methylamphetamine and a homemade taser.
A 30-year-old Rockingham man is due to appear in the Perth Magistrate’s Court today charged with various drugs and weapons offences.


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Behavioral Health Services is a not-for-profit community-based healthcare organization providing substance abuse, mental health, drug-free transitional living, older adult services, HIV/AIDS education and prevention, and other related health service to the residents of Southern California.
BHS' mission is to transform lives by offering hope and opportunities for recovery, wellness, and independence.
Since 1973, BHS has provided inpatient detoxification and residential and outpatient treatment services to substance abusers.
Over the past thirty-four years BHS expanded services to meet the comprehensive needs of its clients, and now provides services from 11 sites located throughout Los Angeles County. These sites include two free-standing chemical dependency recovery centers with medical detoxification and residential/outpatient treatment, two residential treatment facilities, seven outpatient facilities, and two transitional living facilities. The BHS continuum of care includes four community assessment center sites, prevention programs for adolescents and older adults; geriatric case management and home care services for frail elderly and disabled adults.