Copyright © 2009 W3C® (MIT, ERCIM, Keio), All Rights Reserved. W3C liability, trademark and document use rules apply.
This is a First Public Working Draft of a feature requirement documents for the continued SPARQL language development. This document is expected to change in response to public input and working group decisions.
This section describes the status of this document at the time of its publication. Other documents may supersede this document. A list of current W3C publications and the latest revision of this technical report can be found in the W3C technical reports index at http://www.w3.org/TR/.
The SPARQL Working Group seeks public feedback on this Working Draft. Please send your comments to<EMAIL_ADDRESS>(public archive). If possible, please offer specific changes to the text that would address your concern.
Publication as a Working Draft does not imply endorsement by the W3C Membership. This is a draft document and may be updated, replaced or obsoleted by other documents at any time. It is inappropriate to cite this document as other than work in progress.
This document was produced by a group operating under the 5 February 2004 W3C Patent Policy. This document is informative only. W3C maintains a public list of any patent disclosures made in connection with the deliverables of the group; that page also includes instructions for disclosing a patent. An individual who has actual knowledge of a patent which the individual believes contains Essential Claim(s) must disclose the information in accordance with section 6 of the W3C Patent Policy.
Table of Contents |
This document provides an overview of the main new features of SPARQL and their rationale. This is an update to SPARQL adding several new features that have been agreed by the SPARQL WG. These language features were determined based on real applications and user and tool-developer experience.
The following features have been agreed by the SPARQL WG. These features have been grouped into Required and Time-permitting features as follows.
In the remainder of this document we will present the new features according to the nomenclature agreed by the Working Group:
Each feature is described in a common pattern as follows:
This current working draft details only one required features, but motivation and a description is also provided for the time-permitting features.
Aggregate functions allow operations such as counting, numerical min/max/average and so on, by operating over columns of results. They are currently not taken into account in SPARQL and then require additional scripting to parse query results and get these informations, e.g. the number of triples that satisfy a particular statement. Hence, a language extension is needed.
In SPARQL/Query 1.0 (original SPARQL), query patterns yield a solution set (effectively a table of solutions) from which certain columns are projected and returned as the result of the query. Aggregates provides the ability to partition a solution set into one or more groups based on rows that share specified values, and then to create a new solution set which contains one row per aggregated group. Each solution in this new aggregate solution set may contain either variables whose values are constant throughout the group or aggregate functions that can be applied to the rows in a group to yield a single value. Common aggregate functions include COUNT, SUM, MIN, and MAX.
Aggregate functions are commonly required to perform a slew of application and data-analysis tasks, such as:
Applications can typically take a SPARQL/Query 1.0 solution set and calculate aggregate values themselves. Enabling SPARQL engines to calculate aggregates, however, results in moving work from the application to the SPARQL engine, and will usually result in significantly smaller solution sets being returned to the application.
The following systems are known by the WG at the time of publication to support one or more aggregate functions:
Several aggregate functions are widely implemented, and implementations tend to project out results like for example:
SELECT COUNT(?person) AS ?alices WHERE { ?person :name "Alice" . }
return the number of times the a triple of the form _ :name "Alice" appears in the source data.
SELECT AVG(?value) AS ?average WHERE { ?good a :Widget ; :value ?value . }
Related issues raised by the WG:
This feature is considered as Required by the WG.
It is sometimes necessary to nest the results of a query within another query. It currently requires to get the results of a first query, parse them with dedicated scripts, and then launch the second query. The Subquery feature would allow to do such nesting in a single SPARQL query.
In SPARQL/Query 1.0 (original SPARQL), to nest the result of a
first query into another one, one has to rely on dedicated
script(s) and run separate queries. For instance, to identify
all the people that Alice knows and a single name for each of
them, the following script should be done (in PHP, assuming the
do_query
function allows to run a SPARQL query and
get the results as an array of PHP objects)
$query = " SELECT ?person WHERE { :Alice :knows ?person . }"; $res = do_query($query); foreach ($res as $r) { $person = $r->person->value; $query = "SELECT ?name WHERE { ?person foaf:name ?name . } LIMIT 1"; }
The Subquery feature will provide a way to nest the results of a query within another query. That feature could be used, for instance, in the following use cases:
The query form of subqueries has not yet been decided by the WG (see issues below).
The following implementations are known by the WG at the time of publication to provide a way to run subqueries:
For instance, the following query is possible in ARQ, and is equivalent to the script mentioned before.
SELECT ?person ?name WHERE { :Alice foaf:knows ?person . { SELECT ?name WHERE { ?person foaf:name ?name } LIMIT 1 } }
Related issues raised by the WG:
This feature is considered as Required by the WG.
In SPARQL/Query 1.0 (original SPARQL), Negation by failure
is possible by combining OPTIONAL
,
FILTER
and !BOUND
. It is yet difficult
to write and can be a burden for learning and using SPARQL.
Hence, dedicated language constructs for expressing negation are
desired, as users requested, which the WG agrees with.
Various tasks, such as data validation and social network
analysis, can require the checking of whether certain triples do
or don't exist in the graph. Checking the absence of triples is a
form of negation, called Negation by failure (since it
checks if a pattern does not match, and not if it does not exist
following the open-world assumption) and is already possible in
SPARQL/Query 1.0 (original SPARQL), using FILTER
,
OPTIONAL
and !BOUND()
, as follows (to
retrieve the ?name
of ?x
for which no
foaf:knows
value exists, i.e. identify the name of
people who do not know anyone).
PREFIX foaf: <http://xmlns.com/foaf/0.1/> SELECT ?name WHERE { ?x foaf:givenName ?name . OPTIONAL { ?x foaf:knows ?who } . FILTER (!BOUND(?who)) }
Yet, this is not very intuitive to write and learn for users nor does it cater for efficient implementations of negation. Hence, the Negation feature to be included will provide the support for testing the absence of a match to a query pattern. Negation can be used in the following use cases:
The feature would introduce a new operator into the algebra or a new function for filters. Any existing queries do not use these operators and are therefore unaffected.
The following implementations are known by the WG at the time of publication to support Negation by failure:
UNSAID
keyword,
that was proposed during the first SPARQL WG but
not addressed at that timeMINUS
operatorNOT EXISTS
operator (UNSAID
) being an alias for itNOT EXISTS
operator to identify table without a given record
The following example uses SeRQL's MINUS
syntax to find the names
of all people that do not know anyone, in a similar way to the
previous query
SELECT x FROM {x} foaf:givenName {name} MINUS SELECT x FROM {x} foaf:givenName {name} ; foaf:knows {who} USING NAMESPACE foaf = <http://xmlns.com/foaf/0.1/>
The following example uses the UNSAID syntax:
PREFIX foaf: <http://xmlns.com/foaf/0.1/> SELECT ?x WHERE { ?x foaf:givenName ?name UNSAID { ?x foaf:knows ?who } }
Related issues raised by the WG:
This feature is considered as Required by the WG.
Being able to return the values of expressions over result bindings, rather than just RDF terms in the store.
In SPARQL/Query 1.0 (original SPARQL), projection queries (SELECT queries) may only project out variables bound in the query. Because variables can only be bound via triple pattern matching, there is no way to project out values that are not matched in the underlying RDF data set. Projecting expressions represents the ability for SPARQL SELECT queries to project any SPARQL expression, rather than only variables. A projected expression might be a variable, a constant URI, a constant literal, or an arbitrary expression (including function calls) on variables and constants. Functions could include both SPARQL built-in functions and extension functions supported by an implementation.
There are many use cases that motivate the ability to project expressions rather than just variables in SPARQL queries. In general, the motivation is to return values that do not occur in the graphs that comprise a query's RDF data set. Specific examples include:
TODO: More mention should be made of the connection with subqueries, as the two can be used together to answer many usecases.
The following systems are known by the WG at the time of publication to support some uses of project expressions:
We wish to find names, and whether the person is over 18.
SELECT ?name (?age > 18) AS over18 WHERE { ?person :name ?name ; :age ?age . }
Another example, we wish to find the full name of everyone who is interested in trees.
PREFIX foaf: <http://xmlns.com/foaf/0.1/> PREFIX : <http://www.example.org/> SELECT fn:string-join(?givenName, ' ', ?surname) AS ?fullName WHERE { ?person foaf:givenname ?givenName ; foaf:surname ?surname ; foaf:interest :trees . }
This example has made use of a concatenation function from XPath-Functions. Which functions will be available for value construction in SPARQL is an open issue that will be dealt with on a time-permitting basis.
To return an RDF graph where the first and family names are concatenated to a full name we can use a query similar to the SELECT example from the previous query as a subquery and use a project expression like this:
PREFIX foaf: <http://xmlns.com/foaf/0.1/> CONSTRUCT { ?x foaf:name ?fullName } WHERE { { SELECT fn:string-join(?gn, " ", ?sn) AS ?fullName WHERE { foaf:givenname ?gn ; foaf:surname ?sn . } } }
TODO: It should be established whether any implementations support both subqueries and fn:string-join()
The WG has noted that project expressions
This feature is considered as Required by the WG.
Certain limitations of the SPARQL/Query 1.0 language syntax cause unnecessary barriers for learning and using SPARQL.
Time-permitting, the SPARQL Working Group will consider extending SPARQL/Query's syntax to include:
This feature is considered as time-permitting only by the WG.
Many classes of query over RDF graphs require searching data structures that are hierarchical and involve arbitrary-length paths through the graphs. Examples include:
SPARQL/Query 1.0 can express queries over fixed-length paths within RDF graphs. SPARQL/Query 1.0 can also express queries over arbitrary but bounded-length paths via repeated UNION constructs. SPARQL/Query 1.0 cannot express queries that require traversing hierarchical structures via unbounded, arbitrary-length paths.
Time-permitting, the SPARQL Working Group will define the syntax and semantics of property paths, a mechanism for expressing arbitrary-length paths of predicates within SPARQL triple patterns.
This feature is considered as time-permitting only by the WG.
Many SPARQL implementations support functions beyond those required by the SPARQL/Query 1.0 specification. There is little to no interoperability between the names and semantics of these functions for common tasks such as string manipulation.
Time-permitting, the SPARQL WG will define URIs and semantics for a set of functions commonly supported by existing SPARQL implementations.
See Working Group issue: ISSUE-2 - http://www.w3.org/2009/sparql/tracker/issues/2
This feature is considered as time-permitting only by the WG.
SPARQL is a concise query language to retrieve and join information from multiple RDF graphs via a single query. In many cases, the different RDF graphs are stored behind distinct SPARQL endpoints.
Federated query is the ability to take a query and provide solutions based on information from many different sources. It is a hard problem in its most general form and is the subject of continuing (and continuous) research. A building block is the ability to have one query be able to issue a query on another SPARQL endpoint during query execution.
Time-permitting, the SPARQL Working Group will define the syntax and semantics for handling a basic class of federated queries in which the SPARQL endpoints to use in executing portions of the query are explicitly given by the query author.
This feature is considered as time-permitting only by the WG.
Given the variety of SPARQL implementations, and differences in datasets and extension functions, a method of discovering a SPARQL endpoint's capabilities and summary information of its data in a machine-readable way is needed.
Many SPARQL implementations support a variety of SPARQL extensions (many proposed here for standardization), extension functions (for use in FILTERs), and different entailment regimes. Moreover, the differences in datasets provided by SPARQL endpoints is often hard to grasp without some existing knowledge of the underlying data. This proposal suggests that these differences may be described by the endpoints themselves, detailing both (1) the capabilities of the endpoint and (2) the data contained in the endpoint.
The Service description features can be used in the following uses-cases:
The following services are known by the WG at the time of publication to support the Service description feature
"X-Endpoint-Description:"
and the URI given is relative to the endpoint: /description
.
The following service description is an example of what is provided when querying
powered by RDF::Query using about=1
HTTP parameters, e.g.
http://example.org/sparql?about=1
.
@prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> . @prefix sd: <http://darq.sf.net/dose/0.1#> . @prefix saddle: <http://www.w3.org/2005/03/saddle/#> . @prefix sparql: <http://kasei.example/2008/04/sparql#> . @prefix void: <http://rdfs.org/ns/void#> . [] a sd:Service ; rdfs:label "SPARQL Endpoint for example.org" ; sd:url <http://example.org/sparql> ; sd:totalTriples 12729 ; saddle:queryLanguage [ rdfs:label "SPARQL" ; saddle:spec <http://www.w3.org/TR/rdf-sparql-query/> ] ; saddle:queryLanguage [ rdfs:label "RDQL" ; saddle:spec <http://www.w3.org/Submission/RDQL/> ] ; saddle:resultFormat [ rdfs:label "SPARQL Query Results XML" ; saddle:mediaType "application/sparql-results+xml" ; saddle:spec <http://www.w3.org/TR/rdf-sparql-XMLres/ ] ; saddle:resultFormat [ rdfs:label "RDF/XML" ; saddle:mediaType "application/rdf+xml" ; saddle:spec <http://www.w3.org/1999/02/22-rdf-syntax-ns#> ] ; saddle:resultFormat [ rdfs:label "SPARQL Query Results JSON" ; saddle:mediaType "application/sparql-results+json" ; saddle:spec <http://www.w3.org/TR/rdf-sparql-json-res/> ] ; sparql:extensionFunction <java:com.hp.hpl.jena.query.function.library.sha1sum> ; sparql:extensionFunction <java:com.ldodds.sparql.Distance> ; sparql:sparqlExtension <http://kasei.example/2008/04/sparql-extension/service> ; sparql:sparqlExtension <http://kasei.example/2008/04/sparql-extension/unsaid> ; sparql:sparqlExtension <http://kasei.example/2008/04/sparql-extension/federate_bindings> .
The serviceDescription issue was previously postponed by the DAWG.
This feature is considered as Required by the WG.
The Working Group has resolved to specify a SPARQL/Update language, but may also pursue a HTTP based graph update via the protocol. This issue is orthogonal to the SPARQL/Update language. Whether or not there will be a concrete mapping between SPARQL/Update and HTTP based graph update is currently under discussion in the working group.
To change an RDF graph (either adding, updating or removing statements as well as adding statements from one graph to another or to the default graph of a triple store) one would currently have to use a programming language and one of several APIs. In other query languages, notably SQL, there are mechanisms to change the data in the database. To allow RDF graphs to be manipulated the same way and avoid using third-party APIs, a language extension is needed.
This feature is a language extension to express updates to an RDF graph or to an RDF store. As such, it uses the SPARQL in both style and detail, reduces the learning curve for developers and reduces implementation costs.
The following facilities are expected to be provided by the SPARQL/Update 1.0 language:
The [SPARUL] Member Submission, that contains several examples, have been widely implemented and is considered a starting point for the present work.
The two following examples illustrates some of the features:
PREFIX dc: <http://purl.org/dc/elements/1.1/> INSERT DATA { <http://example/book3> dc:title "A new book" ; dc:creator "A.N.Other" . }
DELETE { ?book ?p ?v } WHERE { ?book dc:date ?date . FILTER ( ?date < "2000-01-01T00:00:00"^^xsd:dateTime ) ?book ?p ?v } }
The following systems are known by the WG to support the [SPARUL] Member Submission at the time of publication:
Related issues raised by the WG:
This feature is considered as Required by the WG.
By making it possible to update an RDF graph using RESTful HTTP methods, it becomes possible to use either a SPARQL endpoint or a plain Web server to update RDF data.
It should be possible to manipulate RDF graphs using HTTP verbs, notably PUT, POST and DELETE. By this, clients doesn't need to know the SPARQL language to update graphs when it is not needed.
The following systems are known by the WG at the time of publication to support a RESTful update protocol.
This feature is under discussion in the WG.
Many software systems that support entailment regimes such as OWL dialects and RDF Schema extend the semantics of SPARQL Basic Graph Pattern matching to apply to entailments other than simple entailment. The formal semantics of these SPARQL/Query extensions are not standardized, and query writers cannot currently be guaranteed interoperable behavior when working with multiple query engines that extend SPARQL with the same entailment regime.
SPARQL/Query 1.0 defines a mechanism to adapt SPARQL to entailment regimes beyond simple entailment by providing necessary conditions on re-defining the meaning of SPARQL Basic Graph Pattern matching. Time-permitting, the SPARQL WG will use the existing framework to define the semantics of SPARQL queries for one or more of these entailment frameworks:
This feature is considered as time-permitting only by the WG.
The editors would like to thank the SPARQL Working Group for their valuable input for this document.


Welcome to the Dashboard
This is your ARN Number : @arn
@if(client == None){Sorry, there is a problem with the service
When you have registered clients they will be displayed here. You currently have no clients, please
click above to add client
} else {
| CRN | Business name | Business type | Contact details | Remove Client |
|---|---|---|---|---|
| @c.crn | @c.businessName | @c.businessType | @c.contactNumber | Remove |


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goog.net.xpc.IframePollingTransport.receiveCb_()
Callback that wraps receive_ to be used in timers.
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code » | |
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goog.net.xpc.IframePollingTransport.receive_()
Polls all receivers.
|
code » | |
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goog.net.xpc.IframePollingTransport.startRcvTimer_()
Starts the polling loop.
|
code » |
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The string used to prefix all iframe names and IDs.
|
Code » | |
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Long polling interval.
|
Code » | |
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Short polling interval.
|
Code » | |
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Period how long to use TIME_POLL_SHORT_ before raising polling-interval
to TIME_POLL_LONG_ after an activity.
|
Code » | |
|
goog.net.xpc.IframePollingTransport.receivers_
:
Array holding all Receiver-instances.
|
Code » |


Index of all npm documentation
node package manager
Add a registry user account
Display npm bin folder
Bugs for a package in a web browser maybe
Build a package
REMOVED
Manipulates packages cache
Changes
npm's "funny" coding style
Tab Completion for npm
Manage the npm configuration file
Deprecate a version of a package
Developer Guide
Handling Module Name Disputes
Docs for a package in a web browser maybe
Edit an installed package
Browse an installed package
Frequently Asked Questions
Folder Structures Used by npm
Search npm help documentation
Get help on npm
Interactively create a package.json file
Install a package
Specifics of npm's package.json handling
Symlink a package folder
List installed packages
node package manager
Check for outdated packages
Manage package owners
Create a tarball from a package
Display prefix
Remove extraneous packages
Publish a package
Rebuild a package
The JavaScript Package Registry
Cleaning the Slate
Start a package
Display npm root
Run arbitrary package scripts
How npm handles the "scripts" field
Search for packages
The semantic versioner for npm
Lock down dependency versions
Mark your favorite packages
Start a package
Stop a package
Add a package as a git submodule
Tag a published version
Test a package
Remove a package
Remove a package from the registry
Update a package
Bump a package version
View registry info
Display npm username
Display npm bin folder
Bugs for a package in a web browser maybe
npm commands
Manage the npm configuration files
Deprecate a version of a package
Docs for a package in a web browser maybe
Edit an installed package
Browse an installed package
Search the help pages
Interactively create a package.json file
install a package programmatically
Symlink a package folder
Load config settings
List installed packages
node package manager
Check for outdated packages
Manage package owners
Create a tarball from a package
Display prefix
Remove extraneous packages
Publish a package
Rebuild a package
Start a package
Display npm root
Run arbitrary package scripts
Search for packages
programmatically generate package shrinkwrap file
Start a package
Stop a package
Add a package as a git submodule
Tag a published version
Test a package
uninstall a package programmatically
Remove a package from the registry
Update a package
Bump a package version
View registry info
Display npm username


When,Where,and how you want it
.01
when where you want it
.02
When,Where,and how you want it
.03
When,Where,and how you want it
.04
When,Where,and how you want it
Explore !! Explore !! Explore !!
Explore !! Explore !! Explore !!
Excellent Website really happy with the productAndrew Williums
Excellent Website really happy with the productJames
Excellent Website really happy with the productMicheal France
It was popularised in the 1960s with the release.
Copyright © 2016 Residence. All Rights Reserved | Design By W3layouts


?New
York
Botanical
Garden
Ib052fl0
IMAGED
Paspalum
bakeri
Hack.
Great
Abaco:
Green
Turtle
Cay,
on
edge
of
coppice
along
roadway
between
Bluff
House
and
New
Plymouth,
east
of
White
Sound.
November
26,
1976
D.
S.
Correli
S
H.B.
Correli
47669
Herbarium
FAIRCHILD
TROPICAL
GARDEN
1605280
Legend -
Level of confidence that token is an accurately-transcribed word
extremely low
very low
low
undetermined
medium
high
very high


Welcome to my home page. Menu's and content will be updated periodically as projects are completed. Check back regularly for updates
Updated (9/5/2016) - Added Program 1 to menu.


INVITATION
We invite you to share the joy with us as the wedding of
Mr. Martin Mamdouh
&
Mrs. Eriny Usama
takes place on
14-1-2021,
at Archangel Michael church in Sheraton
fas fa-map-marker-alt
We invite you together with your family!
We expect your blessing more than anything on
our wedding day.

The joy of this wedding is incomplete without your presence in it.
You have shared in our lives
with your friendship. Let’s share the joy together.
© 14-1-2021 — Made with 💜 by Martin Mamdouh


Player 1 0.0000
Player 2 0.0000
Player 3 0.0000
Player 4 0.0000
Player 5 0.0000
Player 6 0.0000
Player 7 0.0000
Player 8 0.0000
Player 9 0.0000
Player 10 0.0000


Frequently Asked Questions (FAQs)¶
Connecting to the board¶
I can’t connect to my board¶
Check the board is powered on (Red LED LD13) and that the bitstream has been loaded (Green “DONE” LED LD12)
Your board and PC/laptop must be on the same network, or have a direct network connection. Check that you can ping the board (hostname, or IP address) from a command prompt or terminal on your host PC
>ping pynq
or
>ping <IP_ADDRESS>
(The default IP address of the board is : <IP_ADDRESS>)
Log on to the board through a terminal, and check the system is running. i.e. that the Linux shell is accessible. See below for details on logging on with a terminal.
From a terminal, check you can ping the board from your host PC, and also ping your host PC from the board
If you can’t ping the board, or the host PC, check your network settings.
- You must ensure board your PC and board are connected to the same network, and have IP addresses in the same range. If your network cables is connected directly to your PC/laptop and board, you may need to set a static IP address for your PC/laptop manually. See the Appendix: Assign your PC/Laptop a static ip address
- If you have a proxy setup, you may need to add a rule to bypass the board hostname/ip address.
- If you are using a docking station, when your laptop is docked, the Ethernet port on the PC may be disabled.
My board is not powering on (No Red LED)¶
The board can be powered by USB cable, or power adapter (7 - 15V V 2.1mm centre-positive barrel jack). Make sure Jumper JP5 is set to USB or REG (for power adapter). If powering the board via USB, make sure the USB port is fully powered. Laptops in low power mode may reduce the available power to a USB port.
The bitstream is not loading (No Green LED)¶
- Check the Micro-SD card is inserted correctly (the socket is spring loaded, so push it in until you feel it click into place).
- Check jumper JP4 is set to SD (board boots from Micro SD card).
- Connect a terminal and verify that the Linux boot starts.
If the Linux boot does not start, or fails, you may need to flash the Micro SD card with the PYNQ-Z1 image.
The hostname of the board is not resolving/not found¶
It may take the hostname (pynq) some time to resolve on your network. If you know the IP address of the board, it may be faster to use the IP address to navigate to the Jupyter portal instead of the hostname.
e.g. In your browser, go to:
http://<IP_ADDRESS>:9090
You need to know the IP address of the board first. You can find the IP by connecting a terminal to the board. You can run ifconfig in the Linux shell on the board to check the network settings. Check the settings for eth0 and look for an IP address.
I don’t have an Ethernet port on my PC/Laptop¶
If you don’t have an Ethernet port, you can get a USB to Ethernet adapter.
If you have a wireless router with Ethernet ports (LAN), you can connect your PYNQ-Z1 board to an Ethernet port on your router, and connect to it from your PC using WiFi. (You may need to change settings on your Router to enable the Wireless network to communicate with your LAN - check your equipment documentation for details.)
You can also connect a WiFi dongle to the board, and set up the board to connect to the wireless network. Your host PC can then connect to the same wireless network to connect to the board.
How do I setup my computer to connect to the board?¶
If you are connecting your board to your network (i.e. you have plugged the Ethernet cable into the board, and the other end into a network switch, or home router), then you should not need to setup anything on your computer. Usually, both your computer, and board will be assigned an IP address automatically, and they will be able to communicate with each other.
If you connect your board directly to your computer with an ethernet cable, then you need to make sure that they have IP addresses in the same range. The board will assign itself a static IP address (by default <IP_ADDRESS>), and you will need to assign a static IP address in the same range to the computer. This allows your computer and board to communicate to each other over the Ethernet cable.
I can’t connect to the Jupyter portal¶
My Board is powered on, and I see the Red and Green LEDs, but I can’t connect to the Jupyter Portal, or see the Samba shared drive:
By default, the board has DHCP enabled. If you plug the board into a home router, or network switch connected to your network, it should be allocated an IP address automatically. If not, it should fall back to a static IP address of <IP_ADDRESS>
If you plug the Ethernet cable directly to your computer, you will need to configure your network card to have an IP in the same address range. e.g. <IP_ADDRESS>
My board is connected, and I have verified the IP addresses on the board and my network interface, but I cannot connect to the board.
VPN¶
If your PC/laptop is connected to a VPN, and your board is not on the same VPN network, this will block access to local IP addresses. You need to disable the VPN, or set it to bypass the board address.
Proxy¶
If your board is connected to a network that uses a proxy, you need to set the proxy variables on the board
set http_proxy=my_http_proxy:8080 set https_proxy=my_https_proxy:8080
How do I connect to the board using a terminal?¶
To do this, you need to connect to the board using a terminal.
To connect a terminal: Connect a Micro USB cable to the board and your PC/Laptop, and use a terminal emulator (puTTY, TeraTerm etc) to connect to the board.
Terminal Settings:
- 115200 baud
- 8 data bits
- 1 stop bit
- No Parity
- No Flow Control
Once you connect to the board, you can configure the network interface in Linux
Board/Jupyter settings¶
How do I modify the board settings?¶
Linux is installed on the board. Connect to the board using a terminal, and change the settings as you would for any other Linux machine.
How do I find the IP address of the board?¶
Connect to the board using a terminal (see above) and type ‘hostname -I’ to find the IP address for the eth0 Ethernet adapter or the WiFi dongle.
How do I set/change the static IP address on the board?¶
The Static IP address is set in /etc/dhcp/dhclient.conf
- you can modify the board’s static IP here.
How do I find my hostname?¶
Connect to the board using a terminal and run hostname
How do I change the hostname?¶
If you have multiple boards on the same network, you should give them different host names. You can run the following script to change the hostname:
sudo /home/xilinx/scripts/hostname.sh NEW_HOST_NAME
What is the user account and password?¶
Username and password for all Linux, jupyter and samba logins are: xilinx/xilinx
I can’t log in to the Jupyter portal with Safari on Mac OS¶
This is a known issue with Safari and is related to Safari not authenticating the Jupyter password properly. To workaround, you can use another browser, or disable the password
How do I enable/disable the Jupyter notebook password¶
The Jupyter configuration file can be found at
/root/.jupyter/jupyter_notebook_config.py
You can add or comment out the c.NotebookApp.password to bypass the password authentication when connecting to the Jupyter Portal.
c.NotebookApp.password =u'sha1:6c2164fc2b22:ed55ecf07fc0f985ab46561483c0e888e8964ae6'
How do I change the Jupyter notebook password¶
A hashed password is saved in the Jupyter Notebook configuration file.
/root/.jupyter/jupyter_notebook_config.py
You can create a hashed password using the function IPython.lib.passwd():
from IPython.lib import passwd password = passwd("secret") 6c2164fc2b22:ed55ecf07fc0f985ab46561483c0e888e8964ae6
You can then add or modify the line in the jupyter_notebook_config.py file
c.NotebookApp.password =u'sha1:6c2164fc2b22:ed55ecf07fc0f985ab46561483c0e888e8964ae6'
General Questions¶
Does Pynq support Python 2.7?¶
Python 2.7 is loaded on Zynq and Python 2.7 scripts can be executed. Pynq, however, is based on Python 3.4. No attempts have been made to ensure backward compatibility with Python 2.7.
Where can I get the PYNQ-Z1 image?¶
You can Download the PYNQ-Z1 image here
How do I write the Micro SD card image¶
You can find instructions in the Appendix: Writing the SD card image
What type of Micro SD card do I need?¶
We recommend you use a card at least 8GB in size and at least class 4 speed rating.


Protein, highly complex substance that is present in all living organisms. Proteins are of great nutritional value and are directly involved in the chemical processes essential for life read more
Antibody, also called immunoglobulin, a protective protein produced by the immune system in response to the presence of a foreign substance, called an antigen read more
Donor is the one who donates the blood and Recipient is the one who receives blood.
Sometimes a loved one may want to donate a kidney but their blood type is incompatible. Some transplant centers will help incompatible pairs of recipient/donors through a process called paired exchange, which involves two living donors and two recipients read more
National Blood Transfusion Council is the government organiastion decicated to information on Blood Transfusion Services and Resources for citizens of India and the general public.
NBTC portalA blood transfusion is a routine medical procedure in which donated blood is provided to you through a narrow tube placed within a vein in your arm. This potentially life-saving procedure can help replace blood lost due to surgery or injury.


2DGameSDK
1.0
2D Game Engine in C++ based on SFML
- g -
Game() :
game::Game
GameObject() :
game::GameObject
GameWorld() :
game::GameWorld
Get() :
game::ResourceCache< TResource >
GetAccumulatedTransform() :
game::DynamicEntity
,
game::Entity
,
game::KinematicEntity
,
game::StaticEntity
GetAllEntities() :
game::SceneGraph
GetAudio() :
game::AssetManager
GetAudioController() :
game::Game
,
game::GameBase
GetBounds() :
game::BoundedFollowCameraController
,
game::CameraController
,
game::DefaultCameraController
,
game::GameWorld
GetCameraController() :
game::Game
,
game::GameBase
GetCombinedTransform() :
game::DynamicEntity
,
game::Entity
,
game::KinematicEntity
,
game::StaticEntity
GetEventController() :
game::StateManager
,
game::StateManagerBase
GetForce() :
game::DynamicEntity
getGame() :
game::GameObject
,
game::Shape< TPhysics >
GetId() :
game::GameObject
,
game::Observable< TData >
,
game::ObservableBase
GetName() :
game::TileLayer
GetNumber() :
game::TileLayer
GetObject() :
game::StateManager
,
game::StateManagerBase
GetObjectType() :
game::GameObject
GetOptions() :
game::Game
,
game::GameBase
GetOverlayDisplay() :
game::Game
,
game::GameBase
GetPhysicalAngle() :
game::PoseConverter
GetPhysicalDimension() :
game::PoseConverter
GetPhysicalPos() :
game::GraphicTools
,
game::PoseConverter
GetPhysicalPose() :
game::PoseConverter
GetPhysicalWorld() :
game::Game
,
game::GameBase
getPhysics() :
game::Shape< TPhysics >
GetPoseConverter() :
game::Game
,
game::GameBase
GetRectBoundary() :
game::GraphicTools
GetRefBody() :
game::Shape< TPhysics >
GetRefShape() :
game::Shape< TPhysics >
GetRefSpace() :
game::Shape< TPhysics >
GetRenderer() :
game::DynamicEntity
,
game::KinematicEntity
,
game::StaticEntity
GetRenderMutex() :
game::StateManager
,
game::StateManagerBase
GetScene() :
game::Game
,
game::GameBase
,
game::StateManager
,
game::StateManagerBase
GetSprite() :
game::SingleSpriteRenderStrategy
GetStateManager() :
game::Game
,
game::GameBase
GetTarget() :
game::CollisionTarget
GetTexture() :
game::AssetManager
GetTransform() :
game::DynamicEntity
,
game::Entity
,
game::KinematicEntity
,
game::StaticEntity
GetType() :
game::CollisionTarget
,
game::Entity
,
game::Projectile
,
game::Shape< TPhysics >
GetVelocity() :
game::DynamicEntity
GetView() :
game::BoundedFollowCameraController
,
game::CameraController
,
game::DefaultCameraController
,
game::Game
GetVisualAngle() :
game::PoseConverter
GetVisualDimension() :
game::PoseConverter
GetVisualPos() :
game::GraphicTools
,
game::PoseConverter
GetVisualPose() :
game::PoseConverter
getVisualPosition() :
game::Shape< TPhysics >
getVisualRotation() :
game::Shape< TPhysics >
GetVisualScale() :
game::PoseConverter
GetVisualTransform() :
game::PoseConverter
GetWindow() :
game::Game
,
game::GameBase
GetWorld() :
game::Game
,
game::GameBase
,
game::StateManager
,
game::StateManagerBase
GetZIndex() :
game::Effect
,
game::Entity
,
game::Projectile
,
game::TileLayer
,
game::VisualObject
Generated by
1.8.15


BREAKING Nigel Farage begs Boris Johnson for massive general election alliance - or else
The craven Brexit Party leader laid out his terms for a wildly unrealistic deal he claimed could see the Tories stand aside in up to 150 seats
by Dan Bloom, Oliver Milne, https://www.facebook.com/mirrordanbloom, https://www.mirror.co.uk/authors/oliver-milne/Nigel Farage today begged Boris Johnson for a massive "leave alliance" which could see Tory and Brexit Party candidates stand down to back each other at the general election .
The seven-time failed Westminster candidate declared he was "more than willing to compromise" - if the Tory dumps his "dreadful" Brexit deal and pivots to no-deal instead.
That, he claimed, could involve up to 150 Tory candidates stepping aside in seats where they have little hope - in exchange for the Brexit Party not contesting any other Tory seats.
If not, Mr Farage claimed, "we will contest every single seat in England Scotland and Wales".
He threatened: "Please don’t doubt we are ready... Next Monday we have 500 candidates coming to London and they will all be signing their candidate forms on that day."
Yet a deal looks unlikely after a senior member of Johnson's team told journalists Farage was not a "fit and proper person" and "should never be allowed anywhere near government."
And Mr Farage stumbled when asked for the details of what a leave alliance would actually mean in practice - and whether candidates would truly pull out.
Asked if it could mean asking Tory candidates to stand aside in 150 seats, Mr Farage said he'd offered the "upper end" but it was a negotiation.
He said: "It could be a non aggression pact. There are lots of different ways this could be done."
The comments came at a press conference to launch the Brexit Party campaign today.
This breaking news story is being updated.


|
Contiki 2.5
|
TCP/IP support in Contiki is implemented using the uIP TCP/IP stack. More...
Files | |
| file | tcpip.h |
Header for the Contiki/uIP interface. | |
Defines | |
| #define | UIP_APPCALL tcpip_uipcall |
| The name of the application function that uIP should call in response to TCP/IP events. | |
Variables | |
| CCIF process_event_t | tcpip_event |
| The uIP event. | |
TCP functions | |
| CCIF void | tcp_attach (struct uip_conn *conn, void *appstate) |
| Attach a TCP connection to the current process. | |
| CCIF void | tcp_listen (u16_t port) |
| Open a TCP port. | |
| CCIF void | tcp_unlisten (u16_t port) |
| Close a listening TCP port. | |
| CCIF struct uip_conn * | tcp_connect (uip_ipaddr_t *ripaddr, u16_t port, void *appstate) |
| Open a TCP connection to the specified IP address and port. | |
| void | tcpip_poll_tcp (struct uip_conn *conn) |
| Cause a specified TCP connection to be polled. | |
| #define | tcp_markconn(conn, appstate) tcp_attach(conn, appstate) |
UDP functions | |
| void | udp_attach (struct uip_udp_conn *conn, void *appstate) |
| Attach the current process to a UDP connection. | |
| CCIF struct uip_udp_conn * | udp_new (const uip_ipaddr_t *ripaddr, u16_t port, void *appstate) |
| Create a new UDP connection. | |
| struct uip_udp_conn * | udp_broadcast_new (u16_t port, void *appstate) |
| Create a new UDP broadcast connection. | |
| CCIF void | tcpip_poll_udp (struct uip_udp_conn *conn) |
| Cause a specified UDP connection to be polled. | |
| #define | udp_markconn(conn, appstate) udp_attach(conn, appstate) |
| #define | udp_bind(conn, port) uip_udp_bind(conn, port) |
| Bind a UDP connection to a local port. | |
TCP/IP packet processing | |
| unsigned char | tcpip_do_forwarding |
| This function does address resolution and then calls tcpip_output. | |
| unsigned char | tcpip_is_forwarding |
| CCIF void | tcpip_input (void) |
| Deliver an incoming packet to the TCP/IP stack. | |
| u8_t | tcpip_output (void) |
| Output packet to layer 2 The eventual parameter is the MAC address of the destination. | |
| void | tcpip_set_outputfunc (u8_t(*f)(void)) |
| #define | tcpip_set_forwarding(forwarding) tcpip_do_forwarding = (forwarding) |
TCP/IP support in Contiki is implemented using the uIP TCP/IP stack.
For sending and receiving data, Contiki uses the functions provided by the uIP module, but Contiki adds a set of functions for connection management. The connection management functions make sure that the uIP TCP/IP connections are connected to the correct process.
Contiki also includes an optional protosocket library that provides an API similar to the BSD socket API.
| #define udp_bind | ( | conn, | |
| port | |||
| ) | uip_udp_bind(conn, port) |
Bind a UDP connection to a local port.
This function binds a UDP connection to a specified local port.
When a connection is created with udp_new(), it gets a local port number assigned automatically. If the application needs to bind the connection to a specified local port, this function should be used.
| conn | A pointer to the UDP connection that is to be bound. |
| port | The port number in network byte order to which to bind the connection. |
Definition at line 262 of file tcpip.h.
Referenced by simple_udp_register(), and udp_broadcast_new().
| CCIF void tcp_attach | ( | struct uip_conn * | conn, |
| void * | appstate | ||
| ) |
Attach a TCP connection to the current process.
This function attaches the current process to a TCP connection. Each TCP connection must be attached to a process in order for the process to be able to receive and send data. Additionally, this function can add a pointer with connection state to the connection.
| conn | A pointer to the TCP connection. |
| appstate | An opaque pointer that will be passed to the process whenever an event occurs on the connection. |
| CCIF struct uip_conn* tcp_connect | ( | uip_ipaddr_t * | ripaddr, |
| u16_t | port, | ||
| void * | appstate | ||
| ) | [read] |
Open a TCP connection to the specified IP address and port.
This function opens a TCP connection to the specified port at the host specified with an IP address. Additionally, an opaque pointer can be attached to the connection. This pointer will be sent together with uIP events to the process.
| ripaddr | Pointer to the IP address of the remote host. |
| port | Port number in network byte order. |
| appstate | Pointer to application defined data. |
| CCIF void tcp_listen | ( | u16_t | port | ) |
Open a TCP port.
This function opens a TCP port for listening. When a TCP connection request occurs for the port, the process will be sent a tcpip_event with the new connection request.
| port | The port number in network byte order. |
| CCIF void tcp_unlisten | ( | u16_t | port | ) |
Close a listening TCP port.
This function closes a listening TCP port.
| port | The port number in network byte order. |
| CCIF void tcpip_input | ( | void | ) |
Deliver an incoming packet to the TCP/IP stack.
This function is called by network device drivers to deliver an incoming packet to the TCP/IP stack. The incoming packet must be present in the uip_buf buffer, and the length of the packet must be in the global uip_len variable.
Definition at line 540 of file tcpip.c.
References NULL, process_post_synch(), uip_ext_len, and uip_len.
Referenced by mac_ethernetToLowpan().
| void tcpip_poll_tcp | ( | struct uip_conn * | conn | ) |
Cause a specified TCP connection to be polled.
This function causes uIP to poll the specified TCP connection. The function is used when the application has data that is to be sent immediately and do not wish to wait for the periodic uIP polling mechanism.
| conn | A pointer to the TCP connection that should be polled. |
| CCIF void tcpip_poll_udp | ( | struct uip_udp_conn * | conn | ) |
Cause a specified UDP connection to be polled.
This function causes uIP to poll the specified UDP connection. The function is used when the application has data that is to be sent immediately and do not wish to wait for the periodic uIP polling mechanism.
| conn | A pointer to the UDP connection that should be polled. |
Definition at line 690 of file tcpip.c.
References process_post().
Referenced by resolv_query().
| void udp_attach | ( | struct uip_udp_conn * | conn, |
| void * | appstate | ||
| ) |
Attach the current process to a UDP connection.
This function attaches the current process to a UDP connection. Each UDP connection must have a process attached to it in order for the process to be able to receive and send data over the connection. Additionally, this function can add a pointer with connection state to the connection.
| conn | A pointer to the UDP connection. |
| appstate | An opaque pointer that will be passed to the process whenever an event occurs on the connection. |
Definition at line 309 of file tcpip.c.
References uip_udp_conn::appstate, and PROCESS_CURRENT.
| struct uip_udp_conn* udp_broadcast_new | ( | u16_t | port, |
| void * | appstate | ||
| ) | [read] |
Create a new UDP broadcast connection.
This function creates a new (link-local) broadcast UDP connection to a specified port.
| port | Port number in network byte order. |
| appstate | Pointer to application defined data. |
Definition at line 338 of file tcpip.c.
References NULL, udp_bind, udp_new(), and uip_ipaddr.
| CCIF struct uip_udp_conn* udp_new | ( | const uip_ipaddr_t * | ripaddr, |
| u16_t | port, | ||
| void * | appstate | ||
| ) | [read] |
Create a new UDP connection.
This function creates a new UDP connection with the specified remote endpoint.
| ripaddr | Pointer to the IP address of the remote host. |
| port | Port number in network byte order. |
| appstate | Pointer to application defined data. |
Definition at line 320 of file tcpip.c.
References uip_udp_conn::appstate, NULL, PROCESS_CURRENT, and uip_udp_new().
Referenced by simple_udp_register(), and udp_broadcast_new().
| unsigned char tcpip_do_forwarding |
This function does address resolution and then calls tcpip_output.
Is forwarding generally enabled?
| CCIF process_event_t tcpip_event |


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// Example: CCompiledMesh scene; void create_scene() { CMesh mesh; CGeomBuilder::I().sphere(mesh, 10, 20); CGeomBuilder::I().cone(mesh, 20); CGeomCompiler::I().compile(mesh, scene); }
Definition at line 172 of file CGeomCompiler.h.
Public Member Functions | |
| void | compile (CMesh &mesh, CCompiledMesh &out) |
| void | compile (CMesh &mesh, CCompiledMesh &base, CCompiledMesh &index) |
| void | removeDuplicateIndices (CCompiledMesh &mesh) |
Static Public Member Functions | |
| static CGeomCompiler & | I () |
|
|
Use this function to get a reference to the geometry compiler singleton object. Definition at line 188 of file CGeomCompiler.h. |
|
|
Compile the mesh into an CCompiledMesh object. The compiler will merge identical vertices, create shared edges, etc, etc... |


|
|
Container_bptreeDesign and implementation of B+ trees |
This section provides a brief discussion of the properties and implementation
details of B+ trees of the namespace container_bptree
. It aims to help
programmers to better understand the specifics of new containers and how to use
them in algorithms.
A B+ tree is a data structure, which supports efficient search, retrieval and update operations of stored information. A B+ tree can be regarded as an improved variant of a B-tree, which was originally developed for systems with external storage [2].
The main problem of these B-trees is their inefficiency in range queries and sequential processing of data. In a B-tree representing a sorted list a tree traversal algorithm, which finds a next element, in the worst case visits O(log N) nodes at different levels of the tree. Crossing levels in these trees has a very high cost due to a huge difference in access time between the disks and RAM.
For B-trees in main memory, as well as for red-black trees, the cost of crossing levels is significantly lower than in external storage trees and sequential processing is relatively fast. Nevertheless, the structure of nodes remains the same and some adjacent elements of a sorted list are connected through a path of length O(log N). Thus, sequential processing in these trees is less efficient than in linear data structures, which guarantee that an algorithm can move to the next or previous element in constant time.
A B+ tree solves these efficiency problems by combining two data structures with different properties. User data are stored in a linear structure such as a linked list, which implements simple and efficient sequential access to the data. The other data structure is a B-tree, which is connected to the linear structure. This tree stores only keys and supports fast search and random access to the data.
In systems for external searching B+ trees can have very complex structures;
for example, one node can implement another data structure such as a binary search tree.
A B+ tree designed to work in main memory can be implemented as a dynamically allocated
data structure with the complexity reduced to minimal in order to support required
algorithms and interfaces only. All B+ trees of the namespace container_bptree
are level-linked variants of this data structure,
for more details see [3] and below.
Level-linked B+ trees are particularly attractive for the development of new STL
variants of containers, since they can be implemented in RAM using simple linear
topologies of linked lists not only for external nodes, but also for any other level
of a tree. Thus, algorithms gain the advantage of efficient access to data stored
in both external and internal nodes.
The implementation of a B+ tree requires different types of nodes, since user data
are stored only in external nodes arranged into a linear data structure. In B+ trees
of the namespace container_bptree
an external node is represented by a type,
which is named light node. A node of this type stores the minimum of required data:
a container element and three links to neighbour nodes. An internal node is represented
by a heavy node. A node of this type contains four links to support a level-linked
variant of a B+ tree and special implementation data, which improve the performance
of algorithms. Instead of a key, a heavy node stores a pointer to a light node.
This pointer is used both for connectivity and for access to a container element.
The name heavy node has been selected, since a node of this type stores more information than a light node. Nevertheless, in applications it is possible that a light node requires more space than a heavy node. The size of a light node depends on the size of a container element stored in the node, whereas the size of a heavy node is constant, since this node includes only a pointer to a light node.
The B+ trees of the namespace container_bptree
are implemented as
multi-linked data structures using a representation similar to leftmost child,
right sibling representation of a multi-way tree. Each internal node of these B+ trees
contains four links pointing to its right sibling, left sibling, parent and leftmost
child. This connectivity arranges the children of each node into a doubly linked list
and gives the advantage of simple and fast sequential access to data in these nodes.
External nodes, which are children of an internal node, are also arranged into a
doubly linked list. Unlike internal nodes, external nodes do not contain redundant
links to children; however, they support links to parents. This type of link improves
the efficiency of the bottom up processing, which updates cached algorithmic data in
internal nodes, when a tree is modified. An internal node can be a parent to the
children, which are a group of either internal or external nodes. In the latter case,
a link to the leftmost child is supported through a pointer to an external node, which
is also used to obtain a value of a container element.
For a B+ tree with a minimum degree of a node t (t >= 2) the bounds on the number of children are defined and implemented as follows. Each internal node can have at most 2t children and at least t children. The number of children for an internal node can be less than t if this node is the root, including the case when the total number of user elements stored in external nodes is also less than t.
This analysis can help estimate the memory consumption of the B+ trees of
the namespace container_bptree
. The obtained values of the space
consumption can be compared with the values for other data structures to make
the best choice of a data structure for a user algorithm.
The space requirement sz_total
for a B+ trees of the namespace
container_bptree
is defined by the formula:
sz_total = n_elems * sz_node_ext + n_int_nodes * sz_node_int ;
here n_elems
is the number of elements of a container stored
in external nodes of a B+ tree. The number of internal nodes n_int_nodes
in the asymptotic limit is given by the sum of the geometric progression:
n_int_nodes = n_elems / ( n_children - 1 ) ;
For the worst case analysis the parameter n_children
should be equal to
the minimum degree of a B+ tree t. For the average value of n_int_nodes
the parameter n_children
is equal to ( t + 2t ) / 2 = 1.5t.
The size of an external node sz_node_ext
is the same for every
variant of the B+ trees:
sz_node_ext = sz_element + 3*sz_pointer ;
The size of an internal node sz_node_int
is specific to a B+ tree variant.
In the current version of the library container_bptree
it has the following values:
sz_node_int_bp_tree = 5*sz_pointer + sz_size_t ; sz_node_int_bp_tree_idx = sz_node_int_bp_tree ; sz_node_int_bp_tree_idx_acc = sz_node_int_bp_tree_idx + sz_element ;
here:
sz_element - the size of a type of a container element, sz_pointer - the size of a pointer, sz_size_t - the size of the type size_t .
For practical estimates of the space requirement for a B+ tree of the namespace
container_bptree
the following simplified model can be used. The minimum value
can be obtained using the space consumption of external nodes only:
sz_total = n_elem*sz_node_ext
.
For the second approximation the number of internal nodes can be set 0.1*n_elems
,
since on average one internal node has n_children = (8+16)/2 = 12
. Thus, the improved
value of the space consumption can be calculated by the formula:
sz_total = n_elems * ( sz_node_ext + 0.1 * sz_node_int ) ;
here the value of sz_node_int
is specific to a B+ tree as discussed above.
The increase in the space consumption sz_augment
for the support of a new augmenting
data element that is added to internal nodes only can be also estimated using ten per cent factor
for the number of internal nodes:
sz_augment = 0.1 * n_elems * sz_aug_elem ;
here sz_aug_elem
is the size of a type of an augmenting data element.
The effect of the increased space requirement on the performance of the augmented B+ trees
of the namespace container_bptree
is discussed in the document
Performance of basic algorithms, the section
"Effect of augmenting on performance of B+ trees".
In a B+ tree all external nodes have the same depth. This property makes a B+ tree globally balanced and allows the modification of the structure, which is known as a level-linked B+ tree [3]. A B+ tree of this type arranges internal nodes of one level into a linked list.
In current implementation of the namespace container_bptree
, in order to
make a B+ tree level-linked, it is sufficient to connect the rightmost internal node
of a child group with the leftmost internal node of the next child group at the same
level. The deepest level of the tree is a doubly linked list with user data stored in
external nodes. Thus, the whole data structure looks like a set of parallel horizontal
linked lists. Note also that, formally, level-linked B+ trees are graphs.
Level-linked connectivity provides algorithms the advantage of efficient sequential access to internal nodes and to data stored in these nodes at every level of the tree. It reduces the maximum cost of visiting a neighbour node at the same level from O(log N) using a tree traversal algorithm to O(1) using a level link.
As an algorithm moves up the tree, the number of nodes in every level decreases with the mean frequency 3t/2. At the same time, the number of external nodes with container elements connected to an internal node through child-parent links increases by the same factor. Thus, an algorithm can use the upper levels of the tree in order to vary the length and precision of the data iteration step between two internal nodes of the same level.
One of the attractive properties of B+ trees is a high degree of freedom in choosing formats and specific implementation data, which can be stored in internal nodes, in order to improve the performance of search algorithms. This property allows various schemes of data association with internal nodes, leaving an unmodified structure of external nodes with user information. In particular, some variants of B+ trees for external searching store small size keys, which are not necessarily exact values of corresponding data. This approach increases the amount of information stored in internal nodes, reduces the frequency of disk read operations and thus improves performance of these systems. Although the choice of a data scheme has some effect on the space usage, it does not change the theoretical limit of the space requirement to store a B+ tree, which is O(N). Balanced B+ trees grow and contract in the same way regardless of a specific data scheme.
The B+ trees of the namespace container_bptree
are designed to extend
functionality of search trees. This is why, in contrast to space optimized search trees,
internal nodes of these B+ trees store additional implementation data, which are used by
new algorithms. The new functionality and improved efficiency are achieved at the cost of
the increased space requirement.
The other feature of the selected data scheme, which also results in an additional space
usage, is a partial duplication of data in internal nodes, since a parent node and its
leftmost child point to the same node and container element in a list of external nodes.
This data scheme particularly suits well the level-linked structure of B+ trees of the
namespace container_bptree
. It is probably a bit simpler for the implementation
of STL variants of containers and algorithms than the standard data scheme used in
search B and B+ trees [2].
Storing additional data in internal nodes and hence losing space is justified only if
this can make an improvement to an algorithm. The first means by which the B+ trees of
the namespace container_bptree
improve performance is that they store only those
data, which make redundant calculations and re-calculations of data used by an algorithm.
This method applies the technique, which is described in [4],
see the chapter "Augmenting Data Structures". The second means is the use of efficient access
to the pre-calculated data through the level-linked structure of a B+ tree.
In every B+ tree of the namespace container_bptree
an internal node contains
a data member, which is a counter of the nodes of the tree. This counter has different
purposes in these data structures.
In the class bp_tree
this datum represents the number of children, which
can be a group of either internal or external nodes.
In the classes bp_tree_idx
and bp_tree_idx_acc
this counter
represents the number of external nodes with user elements stored in a container. For internal
nodes the value of this parameter in a parent node is equal to the sum of counters stored in
its children. For the deepest level of internal nodes this parameter represents the number of
children in a group of external nodes. This detail is useful to improve the performance of
methods, which modify trees of the namespace container_bptree
.
The values of the counters of container elements, which are stored in internal nodes, reflect the structural relationships between the nodes of the tree. These values are independent of specific user data stored in the nodes of the tree. An algorithm can efficiently obtain and update these counters using links between nodes of the tree. The counters data along with the connectivity of nodes can be regarded as an independent substructure of indices. This substructure provides efficient support for algorithms, which require an index value of a container element, and for random access iterators.
STL variants of containers based on the class bp_tree_idx_acc
support the
efficient algorithm accumulate()
, which has computational cost O(log N)
in the worst case. This performance has been achieved by adding to every internal node a
new datum, which represents a sum of consecutive elements stored in external nodes. For the
deepest level of internal nodes a parent stores a sum of values of the container elements of
its external child nodes. For all other levels of the internal nodes of the tree every parent
stores a sum, which is equal to a sum of sum values stored in its children. When an algorithm
moves up the tree from a child to its parent, it obtains a sum value of a quickly increasing
number of container elements stored in external nodes.
Figure 1. The substructure of sums of a B+ tree of the
namespace container_bptree .
Squares represent external nodes with values of container elements, circles - internal nodes, solid lines - undirected edges, arrows - directed child-parent edges. A value in an internal parent node is a sum of values shown in its children. |
Unlike the substructure of indices, the substructure of sums depends on the values of container elements stored in the external nodes of the tree. However, specific values of sum data in internal nodes are also affected by the structural relationship between nodes. For this reason, the substructures of indices and sums have a very close similarity. In the case when each element of a container has the value 1, these two substructures become identical. In this respect, the substructure of sums supersedes the substructures of indices.
The ability of the class bp_tree_idx_acc
to simultaneously support two
substructures of two data sets associated with container elements enables the development
of more efficient algorithms and solutions. For examples using both index and sum substructures,
see the discussion of the efficient algorithm accumulate()
in the next section
"Basic Algorithms" and the discussion regarding the calculation of the mean value
in the section Classes of containers and B+ trees.
In every B+ tree of the namespace container_bptree
insert and erase methods
for a single element are typical bottom up algorithms, which have computational cost
O(log N) in the worst case [2].
The only specific requirements to these methods are that they must maintain valid algorithm
data stored in internal nodes as described in [4].
Search methods are top down algorithms with the same logarithmic cost.
The class bp_tree_idx_acc
implements the algorithm accumulate()
,
which has logarithmic computational cost in the worst case. This algorithm is basically a finger
search [3], which takes advantage of the level-linked structure of this B+ tree. The start and
end positions of container elements are specified by two input iterators, which provide pointers
to corresponding external nodes. The algorithm uses a substructure of indices in order to find
between these two external nodes a path, which has the minimum or close to the minimum number
of edges. For distant external nodes the path goes through internal nodes, which store
pre-calculated sums of container elements. The required sum of consecutive elements is obtained
by summing up values of elements in external nodes and cached sum values in internal nodes
when this algorithm moves to a next node at the same level of a tree or, in other words, passes
through a horizontal link.
Note that one implementation of the member function bp_tree_idx_acc::accumulate()
supports all STL variants of containers: ordered and unordered, with unique and multiple values
of elements. This implementation is generic, because it takes advantage of the substructure of
efficient indexing, which maps non-negative integers into container elements. Thus, at the
implementation level of this efficient algorithm any container is processed as a sequence.
This algorithm is yet another demonstration of the powerful potential and effectiveness of the
concept of a sequence in the practically important area of the support of STL containers and
algorithms.
The finger search algorithm has cost O(log D), where D is the number of
consecutive container elements. This cost is better than the cost of a tree search, which
is O(log N), where N is the number of container elements. This fact makes the
alternative search based algorithm accumulate()
less efficient than the finger
search algorithm. However, performance is not the main reason why this algorithm has been
selected to implement the fast member function accumulate()
. For practical
applications, it is very important to calculate a sum of elements with the best possible
accuracy. The finger search algorithm provides the accuracy, which is practically the same as
that of standard algorithm accumulate()
, which sums up values of container
elements in a sequential order.
Revised 08 December, 2011
Copyright © 2011
Vadim Stadnik
<EMAIL_ADDRESS>Distributed under the Boost Software License, Version 1.0. (See accompanying file LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)


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--- title: "Keynote: Kathleen McKeown" updated: 2016-06-30 02:00:00 layout: default group: program menu: sub ordered: 3 status: published ---
Kathleen McKeown is Professor of Computer Science at Columbia University, where she is also Director of the Institute for Data Sciences and Engineering. A long-time researcher in information extraction and natural language processing, she is currently the lead investigator of the North East Big Data Hub, a new multi-institutional collaboration on big data research with major concentration in Health, Energy, Finance, Cities/Regions, Discovery Science, and Education.
At the Intersection of Data Science and Language
Data science holds the promise to solve many of society’s most pressing challenges, but much of the necessary data is locked within the volumes of unstructured data on the web including language, speech and video. In this talk, I will describe how data science approaches are being used in research projects that draw from language data along a continuum from fact to fiction. I will present research on predicting the future impact of a scientific concept—represented as a technical term—based on the information available in recently published research articles, research on learning from knowledge of past disasters, as seen through the lens of the media and on the use of data science in understanding subjective, personal narratives. In these projects we will see how data drawn from the web and semantics play a role.


TYPES OF SEASON
SUMMER(img.1):-
Out of six seasons, summer rules the hottest part. Summer season in India starts in the month of March (end) and lasts until the end of May>. In this period, the rays of the sun fall perpendicularly over the lands.
In late nights and early mornings,there would be a fall in temperature making a pleasant environment and during middays,
there would be high temperature due to the intense heat outside.
WINTER(img.2):-
Winter is the most frigid season of all time. It is one of the six seasons that come to pass in India. This season typically
begins from December and lasts till February>. During winter season in India,days are smaller and the nights become more lasting. In the course of this period, the temperature, humidity, and rainfall are low.
SPRING(img.3):-
Spring refers to the season between winter and summer. With the advent of February, the bleak winter season in India emerges
into the pleasant spring. Spring season in India differs from country to country. In India, spring is usually from February to April. In most western countries, spring season in India begins from March to May as it depends on their weather conditions and temperatures.
MONSOON(img.4):-
The monsoon season in India usually starts from June and lasts till Mid-September. It is also named as the “South West Monsoon”
season. When Monsoon season in India arrives after the tyrannical heat of the summer season in India, then greenery spreads
all over. Cold winds run everywhere, crops flit in the fields, the faces of farmers begin to glow.


North America, third largest of the world’s continents, lying for the most part between the Arctic Circle and the Tropic of Cancer. It extends for more than 5,000 miles (8,000 km) to within 500 miles (800 km) of both the North Pole and the Equator and has an east-west extent of 5,000 miles. It covers an area of 9,355,000 square miles (24,230,000 square km).
North America has a diverse array of wildlife species and is home to an estimated 457 mammals, 914 birds 662 reptiles more than 300 amphibians and 4,000 known arachnids. As of November 1, 2009, the United States Fish and Wildlife Service listed approximately 1,200 animals and 750 plants as endangered or threatened in North America.
The New World vulture species, the California condor (Gymnogyps californianus), became extinct from the wild in 1987. Indiscriminate poaching, habitat destruction, and death by lead poisoning led to this decline. With only a few birds remaining, the US government ordered the capture of all the remaining wild birds before they too completely disappeared. 27 wild birds were captured and subjected to breeding programs at the San Diego Zoo and the Los Angeles Zoo. In 1991, some condors were reintroduced into the wild. Today, the bird inhabits range in parts of California and Utah in the US and Baja California in Mexico. The California condor is presently labeled as critically endangered by the IUCN.
A critically endangered species of bee, the H.J. Franklin’s bumblebee (Bombus franklini) occupies an extremely narrow range in western US. There are some claims that the bee is already extinct in the wild. The bee plays a crucial role in plant pollination of a significant number of wildflower species like horsemint and lupines. In 2006, the last sighting of Franklin’s bumblebee was reported. Habitat degradation, heavy use of pesticides, and high levels of commercial exploitation of the bees leading to pathogen spillage are some of the factors that have led to the rapid decline in Franklin’s bumblebee population in the US.
A critically endangered species, the giant sea bass (Stereolepis gigas) is found in the waters of the eastern NorthPacific between the Humboldt Bay and the Gulf of California. These fish occupy relatively shallow waters of the ocean in the tidal zones, near the shores and kelp forests. Commercial and sports fisheries have largely depleted the numbers of this species over a period of decades. Since 1982, all forms of harvesting of this fish species has been banned by the California Department of Fish and Game. There is a general belief that the population of the giant sea-bass is recovering though sufficient proof supporting this claim is still lacking.
One of the most threatened species of marine turtles, the Kemp’s Ridley sea turtle (), is a critically endangered species primarily found in the waters of the Atlantic off the eastern coast US and Mexico in theAtlantic Ocean and the Gulf of Mexico. The turtle was extensively poached for its meat before it was assigned a protected status. Presently, the death of these turtles by entanglement in fishing gear (the bycatch phenomenon), water pollution, and habitat loss are the major factors leading to the rapid decline of this species. The Kemp’s Ridley sea turtle has a protected status in both the US and Mexico. The TED or turtle excluder device was innovated for use in fishing practices to allow the turtles to escape being caught by trawlers and other fishing gear. Captive breeding of these turtles, and in turn the reintroduction of these captive-bred populations into the wild, was also carried out.


AEAD (EverCrypt_AEAD.h
)¶
This API is:
agile
multiplexing: portable C (Chacha-Poly only); AVX (Chacha-Poly); AVX2 (Chacha-Poly); ADX + BMI2 (AES128-GCM, AES256-GCM)
stateful
Possible values for the agility argument (Hacl_Spec.h
) :
#define Spec_Agile_AEAD_AES128_GCM 0
#define Spec_Agile_AEAD_AES256_GCM 1
#define Spec_Agile_AEAD_CHACHA20_POLY1305 2
#define Spec_Agile_AEAD_AES128_CCM 3
#define Spec_Agile_AEAD_AES256_CCM 4
#define Spec_Agile_AEAD_AES128_CCM8 5
#define Spec_Agile_AEAD_AES256_CCM8 6
Supported values for the agility argument: Spec_Agile_AEAD_AES128_GCM
,
Spec_Agile_AEAD_AES256_GCM
, Spec_Agile_AEAD_CHACHA20_POLY1305
State management¶
Clients are first expected to allocate persistent state, which performs key
expansion and precomputes internal data for AES-GCM. EverCrypt.AEAD
supports
IV reduction, meaning that IV lengths must satisfy the iv_length
predicate
in Spec.Agile.AEAD.fsti
.
EverCrypt_Error_error_code
EverCrypt_AEAD_create_in(Spec_Agile_AEAD_alg a, EverCrypt_AEAD_state_s **dst, uint8_t *k1);
The type EverCrypt_AEAD_state_s
is a C abstract type which cannot be
allocated by clients, as is it an incomplete struct type. Therefore, the
expected usage for initialization is:
EverCrypt_AEAD_state_s *dst;
EverCrypt_Error_error ret =
EverCrypt_AEAD_create_in(Spec_Agile_AEAD_CHACHA20_POLY1305, &dst, key);
Possible error codes can be determined by looking at the original F* signature
for create_in
; at the time of writing, the function may return Success
,
or UnsupportedAlgorithm
. All other cases are eliminated via the _ ->
False
in the post-condition.
UnsupportedAlgorithm
may be returned because of an unsupported algorithm
(e.g. AES-CCM) , or because no implementation is available for the target
platform (e.g. AES-GCM without ADX+BMI2).
State must be freed via the free
function:
void EverCrypt_AEAD_free(EverCrypt_AEAD_state_s *s);
Encryption and decryption¶
Both encryption and decryption take a piece of state which holds the key; a piece of state may be reused as many times as desired.
Encryption has a substantial amount of preconditions; see encrypt_pre
in
EverCrypt.AEAD.fsti
, and Reading F* preconditions for a primer on
deciphering F* code.
At the time of writing, encrypt
may return either Success
or
InvalidKey
. The latter is returned if and only if the s
parameter is
NULL
.
EverCrypt_Error_error_code
EverCrypt_AEAD_encrypt(
EverCrypt_AEAD_state_s *s,
uint8_t *iv,
uint32_t iv_len,
uint8_t *ad,
uint32_t ad_len,
uint8_t *plain,
uint32_t plain_len,
uint8_t *cipher,
uint8_t *tag
);
Note
There is no length parameter for the tag; looking at the source
EverCrypt.AEAD.fsti
, one can see a precondition of the form B.length tag
= tag_length a
, i.e. the length of the tag
array must be of a suitable
length for the algorithm a
. See Spec.Agile.AEAD.fsti
for the
definition of tag_length
. Unverified clients are strongly encouraged
to perform a run-time check!
EverCrypt_Error_error_code
EverCrypt_AEAD_decrypt(
EverCrypt_AEAD_state_s *s,
uint8_t *iv,
uint32_t iv_len,
uint8_t *ad,
uint32_t ad_len,
uint8_t *cipher,
uint32_t cipher_len,
uint8_t *tag,
uint8_t *dst
);


oxford - april 19
We have 100 tickets on sale before the speakers are announced. Be quick, we sold the conference out last year in 3 weeks. These will go fast.
Buy nowThe rest of the tickets will be on sale when the speakers are announced in late October.
We will not use your email address for evil.
Would you like to propose a talk? Call for speakers closes on the 11th of October.
Propose a talkIs there someone you'd love to hear speak? Someone you think we should contact?
Suggest away!


Example codes¶
This section illustrates ways of describing layout generator codes efficiently. While other examples focus on describing the generation flow with specific circuit examples (and codes might be outdated), examples in this section are written in the with the newest APIs and coding styles, in order to help users to build their codes in the most effective way. Codes will be kept updated, as new features and codes added.
Code example 1: low-level building block generations using primitive templates¶
This example is about making basic functional elements (i.e. logic gates, amplifiers) using primitive templates.
Code example 2: high-level building block / top generations¶
This example is about making a block in higher level, composed of basic elements described in the example 1 (i.e. register files, ADC samplers).


34 {
35 Log("Importing music from: " + musicImportDir);
37
38 DirectoryInfo importDir = new DirectoryInfo(musicImportDir);
39 FileInfo[] brstmFiles = importDir.GetFiles("*.brstm", SearchOption.AllDirectories);
40 if (brstmFiles.Length == 0)
41 {
42 MessageBox.Show("No *.brstm files were found in the selected directory!");
43 return;
44 }
45
46 DialogResult confirmResult = MessageBox.Show("About to import from: " + musicImportDir
47 + "\nThis will overwrite info.pac, mu_menumain and the GCT codeset. "
48 + "It is recommended to make a backup before continuing."
49 + "\nDo you want to continue?",
50 "Confirm Import", MessageBoxButtons.OKCancel);
51 if (confirmResult != DialogResult.OK)
52 {
53 return;
54 }
55
56 prog.ProgressTitle = "Importing songs...";
57 prog.InProgressLabel = "Importing songs...";
58 prog.ProgressCompletionAt = 100;
59
60 BackgroundWorker bgw = SetupBackgroundImport(brstmFiles, prog);
61 bgw.RunWorkerAsync();
62
63 prog.ShowDialog();
64 }
void ClearLog()
Definition: ProgressDialog.cs:57


|
SdCardLogHandlerRK
|
Library for writing rotating logs to SD card on the Particle Photon and Electron
The full browsable API documentation is here.
The official location for this library is: https://github.com/rickkas7/SdCardLogHandlerRK.
It's in the Particle community libraries as: SdCardLogHandlerRK.
It's also possible (as of version 0.0.5) to use this to write an arbitrary stream of data, not hooked into the logging API. See SdCardPrintHandler, below.
You'll need a SD card reader, presumably a Micro SD card reader. Make sure you get one that's compatible with the 3.3V logic levels used on the Photon and Electron. Some readers designed for the Arduino expect the 5V logic levels used by the original Arduino. I use this one from Sparkfun but there are others. This one from Adafruit works as well.
The SD card reader connects via the SPI interface. There are two SPI interfaces on the Photon and Electron and you can use either. Note that each SPI device must have a separate SS (sometimes called CS) pin. While it's listed in the table below as A2 (or D5), you can use any GPIO pin.
Primary SPI (SPI object)
Secondary SPI (SPI1 object)
In the picture above:
| Device | SPI Name | SD Reader | Color |
|---|---|---|---|
| A2 | SS | /CS | Yellow |
| A3 | SCK | SCK | Orange |
| A4 | MISO | DO | Blue |
| A5 | MOSI | DI | Green |
| 3V3 | VCC | Red | |
| GND | GND | Black | |
| CD |
You can also use the Adafruit AdaLogger FeatherWing. It contains an SD card reader and a RTC (real-time clock).
It connects to primary SPI (SPI object). The default connection is D5 for the SD card CS pin. It's possible to cut a trace and add a jumper wire to change the CS pin.
This library uses the Logging API that was added in system firmware 0.6.0.
For example:
It does not remap Serial, so if you're using Serial.print for logging, you should switch to using Log.info instead.
The library creates a directory (default: "logs") at the top level of the SD card and stores the log files in that. Each log file is a .txt file 6-digit number beginning with 000001.txt.
The default log file is 1 MB (1000000 bytes), but you can reconfigure this. The actual size will be slightly larger than that, as the log is rotated when it exceeds the limit, and the file will always contain a whole log entry.
When rotated, the default is to keep 10 log files, but this is configurable. The oldest is deleted when the maximum number is reached.
By default, SdCardLogHandler writes to Serial as well, like SerialLogHandler. This can be reconfigured.
This is the example program:
You normally initialize the SdFat library by creating a global object for it. For example:
If you are using SPI1 (the D pins) instead, use:
Note that you should not call sd.begin()
in setup! The begin call is done by the SdCardLogHandler because it needs to be done earlier than setup, and also every time the card is ejected.
If you need to check for a successful call to begin in your code, instead using logHandler.getLastBeginResult()
. You might do this before using the SD card in your code. If there is no SD card inserted, the result will be false.
Normally you initialize the SdCardLogHandler by creating a global object like this:
sd
is the SdFat
object, as described in the previous sectionSD_CHIP_SELECT
is the pin connected to the CS/SS pin. In the code above, SD_CHIP_SELECT
is set to A2.SPI_FULL_SPEED
determines the speed to use, either full or SPI_HALF_SPEED
.There are also two optional parameters:
The next optional parameter allows you to set the logging level.
LOG_LEVEL_ALL
: special value that can be used to enable logging of all messagesLOG_LEVEL_TRACE
: verbose output for debugging purposesLOG_LEVEL_INFO
: regular information messagesLOG_LEVEL_WARN
: warnings and non-critical errorsLOG_LEVEL_ERROR
: error messagesLOG_LEVEL_NONE
: special value that can be used to disable logging of any messagesAnd finally, you can use logging categories as well to set the level for certain categories:
That example defaults to INFO but app.network events would be at TRACE level.
Instead of using SdCardLogHandler, you can use SdCardPrintHandler. This works like SdCardLogHandler, except it does not hook into the system log handler. This makes it useful for logging arbitrary data, and not have system logs mixed in.
You can use any of the print, println, or printf methods to print to the log file. The same circular log file structure is used, and the card is only written to after a
or println. A line is never broken up across multiple files.
The options below work with both SdCardLogHandler and SdCardPrintHandler.
There are also options available to control how logging is done. For example, if you want to change the default log file size to (approximately) 50000 bytes:
You can chain these together fluent-style to change multiple settings:
By default, SdCardLogHandler writes the log entries to Serial like SerialLogHandler. You can turn this off by using:
Or if you want to log to Serial1 (or another port) instead:
Normally, a sync operation is done after each log entry, which maximizes the chance the the log entry will be written out to SD card successfully. However, this will slow down operation if you do a lot of logging. You can have the SdFat library manage its own sync, which happens about every 512 bytes of log messages, by turning off sync after every entry:
Finally, when the SD card is ejected, a check for being inserted is only done at most every 10 seconds. This is because there's a timeout operation that makes the operation slow, and doing it on every log entry would make the performance very bad. You can change this interval by using:
The value is in milliseconds; that changes the value from 10 seconds to 30 seconds.


Ahom Star keyboard is designed for Ahom language which is a part of the Tai Kadai language family spoken by the Tai Ahom people of Assam and Northeast India.
In order to type the arabic numeral (i.e. 1, 2, 3 etc), press the hash key ( Shift + 3 ) and then any corresponding Ahom numeral.
On mobile phone, keys with a little dot on the top right can be pressed and held for more keys.
© HemantaGogoi Ngi Mon


You can also
change the name for your pack on this screen and
change the settings for all cards in the pack in one go.
Use the
icon to see which
images you want to use for image mode and the icon
for all other settings.
Help
Bulk changes
You can change the settings of all cards in this pack in one go. Choose
the setting you want to change from the dropdown and select the value
you want to change it to. Make sure that you are not overriding settings
unintentionally.


Description
The Direct Manipulation Sample 3 demonstrates dragging container objects from a source window to a target window. The application takes advantage of overriding the IContainerObject::objectCopy() function. Classed used included IDMHandler, IContainerControl, and IContainerObject.
Concept
Sample program demonstrates direct manipulation between two container controls in the same process.
Task
From the source container, select a container object and drag to the target container. You can drag parent and child container objects.
Supported
Supported
Supported


Web Service: GeoInfo
A project for the Web Services PS 703128 from Elias and Bernhard.
Test our webservice »
Description
- The service should help students to learn more about differences and similarities between countries.
- The user can choose a country from a map and a topic and then gets current indicators to the topic from the world bank.
- The web service can be used as a quick, interactive alternative to world almanachs like the famous Fischer Weltalmanach-book.
Used Web Services
SOAP
REST
Used Technologies
- Java, Maven 2
- Version control with Git and GitHub
- REST-Framework: Jersey
- Web-container: Grizzly
- Cache-Implementation: Google Guava
- JavaScript-Framework: jQuery
- CSS-Framework: Twitter Bootstrap
- Google Maps


Built By Moroccan Devs
Awesome stuff built by Moroccan developers.
Created by
@arkhamvev
and
@thekroniker
{% include navigation.html %}
{{ content }}


Building Reactive Play application with RethinkDB
This is a CRUD application, backed by a RethinkDB database. It demonstrates:
- Handling asynchronous results, Handling time-outs
- Achieving, Futures to use more idiomatic error handling.
- Accessing RethinkDB, using Java ReQL command reference.
- Achieving, table pagination and sorting functionality using interactive FooTable plugin.
- Replaced the embedded JS & CSS libraries with WebJars.
- Play and Scala-based template engine implementation
- Integrating with a CSS framework (Twitter Bootstrap). Twitter Bootstrap requires a different form layout to the
default one that the Play form helper generates, so this application also provides an example of integrating a
custom form input constructor.
- Used Bootswatch with Twitter Bootstrap to improve the look and feel of the application
Dependency
The rethinkdb-driver is distributed using Maven Central so it can be easily added as a library dependency in your
Play Application's SBT build scripts, as follows:
libraryDependencies += "com.rethinkdb" % "rethinkdb-driver" % "2.2-beta-1"
RethinkDb
- Installing RethinkDB : install
- Installing the Java driver : rethinkdb-driver
- Ten-minute guide with RethinkDB and Java : RethinkDB Java
- Start RethinkDB using
rethinkdb
command and hit http://localhost:8080/
- Create
play_rethinkdb
database and table r_employees
with default configuration
Usage of RethinkDB Java driver
You can use the drivers from Java like this:
import com.rethinkdb.RethinkDB;
import com.rethinkdb.gen.exc.ReqlError;
import com.rethinkdb.gen.exc.ReqlQueryLogicError;
import com.rethinkdb.model.MapObject;
import com.rethinkdb.net.Connection;
public static final RethinkDB r = RethinkDB.r;
Connection conn = r.connection().hostname("localhost").port(28015).connect();
r.db("test").tableCreate("tv_shows").run(conn);
r.table("tv_shows").insert(r.hashMap("name", "Star Trek TNG")).run(conn);
Please check RConnection.scala and RDatabase.scala
Now Play
- The Github code for the project is at : play-rethinkdb
- Clone the project into local system
- To run the Play framework 2.4.x, you need JDK 8 or later
- Install Typesafe Activator if you do not have it already. You can get it from here: http://www.playframework.com/download
- Execute
activator clean compile
to build the product
- Execute
activator run
to execute the product
- play-rethinkdb should now be accessible at localhost:9000
References


{% extends "cvbapp/base.html" %} {% load static %} {% block addHead %} {% endblock %} {% block content %}
In order to create and participate in Vision Session, please sign up and sign in:
To search for a vision session enter the term you would like to search for, select your search term type, and then click the search button:
To access a vision session, simply click the access button to the right of the name and description:
To create a vision session click the create button and fill out the form:
When a session is created users can use the ‘Step 2’ section to enter their Vision Statement suggestion:
Once the owner of the session progresses to step three, everyone can expand a list of list of all suggested statement. The owner of the session will be able to submit a draft vision statement, which encapsulates all the suggestions:
In step 4, the owner can set a time and date for an online chat. Everyone is provided a link to the chatroom, where the Vision Statement can be discussed:
In step 5, the owner finalizes the Vision Statement and creates a report detailing the decisions made:
Finally, in step 6 anyone can export a summary of the Vision Building process to a pdf:


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| Date | Event | Group | Stage Time | Location |
|---|---|---|---|---|
| 01/25/2019 | Alice Irene's Restaurant | Red Bridge Trio | Marionville, MO | |
| 01/26/2019 | Christian Healthcare South | The Mayfields | Lebanon, MO | |
| 02/23/2019 | Alice Irene's Restaurant | Red Bridge | Marionville, MO | |
| 03/02/2019 | Mark & Gene's 13th Annual Fundraiser (Convoy of Hope) | Red Bridge | Springfield, MO | |
| 04/06/2019 | Route 66 Antique Mall- Spring Open House & Swap Meet | The Mayfields | Phillipsburg, MO | |
| 04/11/2019 | Thursday Night Music (at Douglas County Veterans Assoc) | Red Bridge | Ava, MO | |
| 04/20/2019 | Webb City Farmer's Market (Season Opening) | The Mayfields | Webb City, MO | |
| 04/27/2019 | Christian Healthcare South | The Mayfields | Lebanon, MO | |
| 05/05/2019 | Baker Creek Seed- Spring Plating Festival | The Mayfields | Mansfield, MO | |
| 05/06/2019 | Baker Creek Seed- Spring Plating Festival | The Mayfields | Mansfield, MO | |
| 05/11/2019 | Disabled American Veterans (Chapeter 62) Benefit | The Mayfields | Buffalo, MO | |
| 05/18/2019 | Fair Grove Library- Summer Reading Kickoff | Red Bridge | Fair Grove, MO | |
| 05/19/2019 | St. Joseph Church Summerfest | Red Bridge | Billings, MO | |
| 05/25/2019 | Route 66 Antique Mall- 20th Anniversary Memorial Sale & Swap Meet | The Mayfields | Phillipsburg, MO | |
| 06/08/2019 | Newburg Days Festival | Red Bridge | Newburg, MO | |
| 06/08/2019 | Pickin' in the Park Festival (11:00 AM-8:45PM) | Red Bridge | Walnut Grove, MO | |
| 06/29/2019 | Peaceful Bend Winery | The Mayfields | Steelville, MO | |
| 07/06/2019 | Red Moose Vinyard | The Mayfields | Salem, MO | |
| 07/11/2019 | Newton County Fair | The Mayfields | Neosho, MO | |
| 07/13/2019 | Webb City Farmer's Market | The Mayfields | Webb City, MO | |
| 07/27/2019 | Christian Healthcare South | The Mayfields | Lebanon, MO | |
| 09/07/2019 | The Historic Star Theater | Red Bridge | Willow Springs, MO | |
| 09/28/2019 | Carl Junction Bluegrass Festival | Red Bridge | Carl Junction, MO | |
| 10/5/2019 | Blackshire Distillery at Hermann Farm | The Mayfields | Hermann, MO | |
| 10/12/2019 | Blackshire Distillery at Hermann Farm | The Mayfields | Hermann, MO | |
| 10/26/2019 | Christian Healthcare South | The Mayfields | Lebanon, MO | |
| 11/2/2019 | Red Moose Vinyard | The Mayfields | Salem, MO | |
| 11/30/2019 | Red Moose Vinyard (Christmas Cheer) | The Mayfields | Salem, MO |
Historic Red Bridge crossing Bull Creek southeast of
Ozark, Missouri
Book Us Anytime
<EMAIL_ADDRESS>417-840-2548
Yall don't forget about cowboy church every Sunday morning at 10:00 AM at the Finley River Cowboy Church on Hwy EE in Highlandville Missouri. Featuring the Pastor JR Rantz from the Pulpit! AND you even get to sing along with us, country/bluegrass style!
We hope to see you soon!!!


publications
Also see Google Scholar and Semantic Scholar
2023
- FrontierA Novel Framework to Study Community-level Social and Physical Impacts of Hurricane-induced Winds through Synthetic Scenario AnalysisFrontier in Built Environment, ASCE 2023
- JPSENGTopology-Based Resilience Metrics for Seismic Performance Evaluation and Recovery Analysis of Water Distribution SystemsJournal of Pipeline Systems Engineering and Practice, ASCE 2023
2022
- Infrast SysVirtual Testbeds for Community Resilience Analysis: State of the Art Review, Consensus Study, and RecommendationsNatural Hazards Review, ASCE 2022
- Struc. Eng.Machine Learning for Risk and Resilience Assessment in Structural Engineering: Progress and Future TrendsJournal of Structural Engineering, ASCE 2022
- Infrast SysA Community Capitals Framework for Linking Buildings and Organizations for Enhancing Community Resilience through the Built EnvironmentJournal of Infrastructure Systems, ASCE 2021
2021
- ASCE/ASMETime-Dependent Reliability Analysis of Buried Water Distribution Network: Combined Finite-Element and Probabilistic ApproachASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering 2021
- Struc SafetyFailure Risk Analysis of Pipelines using Data-Driven Machine Learning AlgorithmsStructural Safety 2021
- Building EngFirst level seismic risk assessment of old unreinforced masonry (URM) using fuzzy synthetic evaluationJournal of Building Engineering 2021
- JWRPMAsset Management Decision Support Model for Water Distribution Systems: Impact of Water Pipe Failure on Road and Water NetworksJournal of Water Resources Planning and Management, ASCE 2021
2020
- SI EngPost-Disaster Sequential Recovery Planning for Water Distribution Systems using Topological and Hydraulic MetricsJournal of Structure and Infrastructure Engineering 2020
- JPSENGFramework for Seismic Damage and Renewal Cost Analysis of BuriedWater PipelinesJournal of Pipeline Systems Engineering and Practice, ASCE 2020
- JPSENGSeismic Functionality and Resilience Analysis of Water Distribution SystemsJournal of Pipeline Systems Engineering and Practice, ASCE 2020URL
Reserchgate Editor Choice Article - IJDRREvaluation of Natural Hazard Risk for Coastal Districts of Bangladesh Using the INFORM ApproachInternational Journal of Disaster Risk Reduction 2020
2019
- JWRPMReliability Analysis ofWater Distribution Systems using Physical Probabilistic Pipe Failure MethodJournal of Water Resources Planning and Management, ASCE 2019
- IJDRRSeismic Damage Assessment Using GIS and RADIUS: A Case Study of Sylhet City, BangladeshInternational Journal of Disaster Risk Reduction 2019
2018
- Infrast SysPerformance Evaluation of Water Distribution Systems and AssetManagement: State-of-the-Art ReviewsJournal of Infrastructure Systems, ASCE 2018
- PhD


In a staggered start race all drivers can choose their favourite car
regardless of its performance.
I set calculate different start times according to previously
measured average speeds of the cars.
Ideally all cars will meet again just before the finish line.
Should be fun!
Just tell me the vehicle class, and then I'll show you a link that your players
have to go to, so they can enter their car.
{% bootstrap_field ssrform.vehicle_class show_label=False %}
How many laps? about {{ five_laps_duration }}
{% bootstrap_field ssrform.laps show_label=False %}
Which algorithm to use?
{% bootstrap_field ssrform.algorithm show_label=False %}
You can also enter some text here for your participants to read, if you like.
{% bootstrap_field ssrform.comment show_label=False %}
{% csrf_token %}


PheWAS association plot for APOE variants. A grey line is drawn at Positions p = 5 x 10 −5 (a score of about 4.3), which is a threshold for significance after controlling for the Family-Wise-Error-Rate (FWER) using Bonferroni correction. (a) rs429358; (b) rs7412.


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Unicore
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