The Shape Expressions (ShEx) language describes RDF graph structures.
A shape
describes the triples touching nodes in RDF graphs.
These descriptions identify predicates and their associated cardinalities and datatypes.
ShEx shapes can be used to communicate data structures associated with some process or interface, generate or validate data, or drive user interfaces.
This document introduces ShEx to people familiar with basic concepts of RDF and SPARQL. This primer develops examples from an issue tracking application to introduce all major features of ShEx, including the construction of shapes and their correspondence with RDF graphs. This primer is a possible companion to the language specification that serves as a language reference and full specification.
Most applications that share data do so using prescribed data structures. While RDFS and OWL enable one to make assertions about the objects in some domain, ShEx describes data structures. ShEx "schemas" provide:
The example snippets in this document use ShExC and JSON [[json-ld]] notation. The reader should be familiar with basic RDF concepts [[rdf11-concepts]] such as triples and JSON [[json]].
This document uses a running example illustrated by the following graph in which an Issue which is submitted by some person and potentially assigned to the same person or someone else.
These issues can have a status of unassigned
or assigned
.
The rest of this document shows shapes which describe the issue data consumable by some application, including the submitter and the person to which the issue is assigned. Examples include data, both conforming and not.
The following namespace prefixes are frequently used in this document:
| Prefix | Namespace | |
|---|---|---|
| rdf: | http://www.w3.org/1999/02/22-rdf-syntax-ns# | |
| xsd: | http://www.w3.org/2001/XMLSchema# | |
| example namespaces | Used in | |
| foaf: | http://xmlns.com/foaf/0.1/ | Friend Of A Friend ontology |
| ex: | http://ex.example/ns# | random application ontology |
| my: | http://my.example/ns# | shape declarations |
| inst: | http://inst.example/ns# | instance data |
| test: | http://shex.io/extensions/Test/ | Test language for semantic actions |
This schemas in this Primer are available in Shape Expressions Compact Syntax (ShExC) and JSON.
ShEx's facilities for describing the structure of graphs are based on rules that describe triples in a graph.
These rules are evaluated against particular nodes in the instance data; these are called focus nodes
.
Each rule identifies a predicate and describes the expected triples with the focus node
as a subject and the corresponding predicate.
These descriptions include how many such triples are required/permitted, and what kinds of objects are expected.
The rules can be written in ShExC or JSON (recall that you can press 'c' or 'j') as a set of properties on a triple constraint
.
This example consists of a single shape declaration
for a shape called my:UserShape.
A validation process tests selected nodes in the instance data, focus nodes
, against this shape.
The shape in this example consists of a single triple constraint
on the property foaf:name.
The only value-constraint
in this example is that the object of any foaf:name triple must be an RDF literal with a datatype of xsd:string.
# schema (ShExC) my:UserShape { foaf:name xsd:string }
// schema (JSON) { my:UserShape: { "type": "Shape", "expression": { "type": "TripleConstraint", "predicate": "foaf:name", "value": { "type": "NodeConstraint", "datatype": "xsd:string" } } } }
A conforming node in an RDF graph would have exactly one foaf:name property and we expect to have a datatype of xsd:string. Regular expression conventions are used to specify cardinality:
We assume you have identified the nodes you wish to validate as some shape. The node inst:User1 in the following graph conforms to this simple shape:
# passing data inst:User1 foaf:name "Bob Smith"^^xsd:string .
Nodes with the wrong number of foaf:name properties or with foaf:name properties that were not of datatype xsd:string do not match the shape my:UserShape:
# failing data inst:User2 foaf:name "Joe Jones"^^xsd:string ; foaf:name "Joseph Jones"^^xsd:string . inst:User3 foaf:name "Bob Smith"^^xsd:anyURI .
Note that in Turtle (and other RDF representations), literals expressed with no datatype are interpreted as being of type xsd:string
so the following is also valid data:
# passing data inst:User1 foaf:name "Bob Smith" .
This section introduces some vocabulary which will help us discuss ShEx and the validation process.
In the examples in section 3, we examined tested the nodes inst:User1, inst:User2 and inst:User3 against my:UserShape.
We treated each one in turn as the focus node
and tested the triples involving that node against the triple constraint
in the shape.
This triple constraint had a single value constraint
; a literal datatype
constraint asserting that the object of a matching triple was of type xsd:string
.
Triple constraints
can include combinations of the following constraints:
literal datatype
: identifies the datatype of an RDF literal, e.g.
my:UserShape {
foaf:name xsd:string
}
{ "my:UserShape": { "type": "Shape",
"expression": {
"type": "TripleConstraint", "predicate": "foaf:name",
"value": { "type": "NodeConstraint", "datatype": "xsd:string" } } } }
literal facets
: applies XML Schema constraining facets, e.g.
my:UserShape {
ex:shoeSize xsd:float MinInclusive 5.5 maxInclusive 12.5
}
{ "my:UserShape": { "type": "Shape",
"expression": { "type": "TripleConstraint", "predicate": "ex:shoeSize",
"value": { "type": "NodeConstraint", "datatype": "http://www.w3.org/2001/XMLSchema#float",
"mininclusive": 5.5, "maxinclusive": 12.5 } } } }
These numeric facets
apply only to numeric RDF literals: MinInclusive
, MinExclusive
, MaxInclusive
, MaxExclusive
, TotalDigits
, FractionDigits
.
These string facets
apply only to all RDF literals: Length
, MinLength
, MaxLength
, Pattern
.
Facets names are not case-sensitive in ShExC.
node kind
: identifies the kind of RDF node (IRI, RDF literal, or Blank Node), e.g.
my:UserShape {
foaf:mbox IRI
}
{ "my:UserShape": { "type": "Shape",
"expression": {
"type": "TripleConstraint", "predicate": "foaf:mbox",
"value": { "type": "NodeConstraint", "nodeKind": "IRI" } } } }
The following node kinds correspond to RDF node types: Literal
, IRI
, BNode
.
The node kind NonLiteral
identifies the union of IRI
s and BNode
s.
Node kinds are not case-sensitive in ShExC.
value set
: enumerates specific expected values, e.g.
my:IssueShape {
ex:state [ex:unassigned ex:assigned]
}
{ "my:IssueShape": { "type": "Shape",
"expression": { "type": "TripleConstraint", "predicate": "ex:status",
"value": { "type": "NodeConstraint", "values": [ "ex:unassigned", "ex:assigned" ] } } } }
See the Value Sets description below for details.
value shape
: asserts that the object is described by another shape, e.g.
my:IssueShape {
ex:reportedBy @my:UserShape
}
{ "my:IssueShape": { "type": "Shape",
"expression": { "type": "TripleConstraint", "predicate": "ex:reportedBy",
"value": { "type": "ShapeRef", "reference": "my:PersonShape" } } } }
The above examples include only a single Triple Constraint
in each shape.
Most realistic shape declarations will include multiple constraints.
In ShExC, triple constraints are separated by a ','.
my:IssueShape { ex:state [ex:unassigned ex:assigned]; ex:reportedBy @my:UserShape }
To illustrate this, we can declare a schema for the data described in the introduction. (Mousing over the the following list items items will highlight the corresponding elements in the example text.) Our first example issue must doesn't include ex:reproducedBy as illustrated in the image above, but it must have:
value set
ex:unassigned or ex:assigned,value shape
referencing my:UserShape.The user referenced by the ex:reportedBy property must have:
literal datatype
of xsd:stringnode kind
of IRI.# schema (ShExC) my:IssueShape { ex:state [ex:unassigned ex:assigned]; ex:reportedBy @my:UserShape } my:UserShape { foaf:name xsd:string; foaf:mbox IRI+ }
// schema (JSON) { "type": "Schema", "shapes": { "my:IssueShape": { "type": "Shape", "expression": { "type": "group", "expressions": [ { "type": "TripleConstraint", "predicate": "ex:state", "value": { "type": "NodeConstraint", "values": [ "ex:unassigned", "ex:assigned" ] } }, { "type": "TripleConstraint", "predicate": "ex:reportedBy", "value": { "type": "ShapeRef", "reference": "my:UserShape" } } ] } }, "my:UserShape": { "type": "Shape", "expression": { "type": "group", "expressions": [ { "type": "TripleConstraint", "predicate": "foaf:name", "value": { "type": "NodeConstraint", "datatype": "xsd:string" } }, { "type": "TripleConstraint", "predicate": "foaf:mbox", "value": { "type": "NodeConstraint", "nodeKind": "iri" }, "min": 1, "max": "*" } ] } } } }
# passing data PREFIX ex: http://ex.example/# PREFIX foaf: http://xmlns.com/foaf/ PREFIX xsd: http://www.w3.org/2001/XMLSchema# inst:Issue1 a ex:Issue ; ex:state ex:unassigned ; ex:reportedBy inst:User2 . inst:User2 a foaf:Person ; foaf:name "Bob Smith" ; foaf:mbox<EMAIL_ADDRESS>; foaf:mbox<EMAIL_ADDRESS>.
# failing data PREFIX ex: http://ex.example/# PREFIX foaf: http://xmlns.com/foaf/ PREFIX xsd: http://www.w3.org/2001/XMLSchema# inst:Issue3 a ex:Issue ; ex:state ex:unsinged ; ex:reportedBy inst:User4 . inst:User4 a foaf:Person ; foaf:name "Bob Smith", "Robert Smith" ; foaf:mbox<EMAIL_ADDRESS>; foaf:mbox<EMAIL_ADDRESS>.
In the top example, inst:Issue1 conforms to my:IssueShape because every predicate identified in my:IssueShape corresponds to a triple with a subject of inst:Issue1.
Most schema language offer a way to express choices. We can extend our first example to include a more flexible user which includes given and family names.
In this example, a user has:
The user must have exactly one foaf:mbox.
# schema (ShExC) my:UserShape { ( foaf:name xsd:string | foaf:givenName xsd:string+; foaf:familyName xsd:string ); foaf:mbox IRI }
// schema (JSON) { "my:UserShape": { "type": "Shape", "expression": { "type": "group", "expressions": [ { "type": "OneOf", "expressions": [ { "type": "TripleConstraint", "predicate": "foaf:name", "value": { "type": "NodeConstraint", "datatype": "xsd:string" } }, { "type": "group", "expressions": [ { "type": "TripleConstraint", "predicate": "foaf:givenName", "value": { "type": "NodeConstraint", "datatype": "xsd:string" }, "min": 1, "max": "*" }, { "type": "TripleConstraint", "predicate": "foaf:familyName", "value": { "type": "NodeConstraint", "datatype": "xsd:string" } } ] } ] }, { "type": "TripleConstraint", "predicate": "foaf:mbox", "value": { "type": "NodeConstraint", "datatype": "IRI" } } ] } } }
# passing data inst:User1 a foaf:Person ; foaf:name "Alice Walker" ; foaf:mbox<EMAIL_ADDRESS>. inst:User2 a foaf:Person ; foaf:givenName "Robert" ; foaf:givenName "Paris" ; foaf:familyName "Moses" ; foaf:mbox<EMAIL_ADDRESS>.
# failing data inst:User3 a foaf:Person ; foaf:givenName "Smith" ; # error: no familyName foaf:mbox<EMAIL_ADDRESS>. inst:User4 a foaf:Person ; foaf:name "A" ; # error: both name and given/family name foaf:givenName "B" ; foaf:familyName "C" ; foaf:mbox<EMAIL_ADDRESS>.
We've seen several examples of ShExC. Here we'll describe more completely the structure of a ShExC schema.
As in Turtle, Trig and SPARQL, comments in ShExC are prefixed by a #
character.
There are no comments in JSON, though there are some diabolical workarounds leveraging overwritten object keys.
# schema (ShExC) my:UserShape { # a user has ( # either foaf:name xsd:string # a full name | # or foaf:givenName xsd:string+;# one or more given names foaf:familyName xsd:string # and a family name ); foaf:mbox IRI # and always an mbox. }
# schema (JSON) { "my:UserShape": { "type": "a user has", "type": "Shape", "expression": { "type": "group", "expressions": [ { "type": " either" "type": "OneOf", "expressions": [ { "type": " a full name" "type": "TripleConstraint", "predicate": "foaf:name", "value": { "type": "NodeConstraint", "datatype": "xsd:string" } }, { "type": " or" "type": "group", "expressions": [ { "type": " one or more given names" "type": "TripleConstraint", "predicate": "foaf:givenName", "value": { "type": "NodeConstraint", "datatype": "xsd:string" }, "min": 1, "max": "*" }, { "type": " and a family name" "type": "TripleConstraint", "predicate": "foaf:familyName", "value": { "type": "NodeConstraint", "datatype": "xsd:string" } } ] } ] }, { "type": "and always an mbox." "type": "TripleConstraint", "predicate": "foaf:mbox", "value": { "type": "NodeConstraint", "datatype": "IRI" } } ] } } }
The terms ("terminals", to a language geek) in ShEx are the same as those in Turtle. The following list summarizes which terminals are allows where in the ShEx grammar:
Shape labels
(seen in shape declaration and value shapes) are IRIs or blank nodes.Constraint labels
(see value class definitions and value class references described below in Labeled Constraints) are also IRIs or blank nodes.a
is shorthand for rdf:type
.
Literal datatypes
are IRIs.IRIs are parsed as they are in Turtle, respecting the current namespace prefix mapping and base directives.
An additional non-RDF term called a stem
appears in value sets.
In the examples so far, every shape has had an IRI or a blank node for a label. Every shape in ShEx has some label. It is possible to write ShExC without a label, in which case the label is a fresh blank node, different from every other blank node in your schema.
InShExC, the example in Simple Expressions could be rewritten with the my:IssueShape embedded inline in "{}"s. The JSON representation of ShEx has no corresponding shortcut; it has instead a reference to a shape whose label is a blank node allocated by the parser.
# schema (ShExC) my:IssueShape { ex:state [ex:unassigned ex:assigned]; ex:reportedBy { foaf:name xsd:string; foaf:mbox IRI+ } }
// schema (JSON) { "type": "Schema", "shapes": { "my:IssueShape": { "type": "Shape", "expression": { "type": "group", "expressions": [ { "type": "TripleConstraint", "predicate": "ex:state", "value": { "type": "NodeConstraint", "values": [ "ex:unassigned", "ex:assigned" ] } }, { "type": "TripleConstraint", "predicate": "ex:reportedBy", "value": { "type": "ShapeRef", "reference": "_:b1" } } ] } }, "_:b1": { "type": "Shape", "expression": { "type": "group", "expressions": [ { "type": "TripleConstraint", "predicate": "foaf:name", "value": { "type": "NodeConstraint", "datatype": "xsd:string" } }, { "type": "TripleConstraint", "predicate": "foaf:mbox", "value": { "type": "NodeConstraint", "nodeKind": "iri" }, "min": 1, "max": "*" } ] } } } }
So far, the examples have all included exactly one value constraint. In fact, they can be combined in sensible combinations. For example, imagine that we want to assert that the issue is identified by an IRI matching a certain pattern, and conforming to a particular shape.
# schema (ShExC) my:IssueShape { ex:state [ex:accepted ex:resolved]; ex:reproducedBy IRI @my:EmployeeShape PATTERN "^http://hr.example/id#[0-9]+" } my:EmployeeShape { foaf:name xsd:string; ex:department [ex:ProgrammingDepartment] }
// schema (JSON) { "my:IssueShape": { "type": "Shape", "expression": { "type": "group", "expressions": [ { "type": "TripleConstraint", "predicate": "ex:state", "value": { "type": "NodeConstraint", "values": [ "ex:accepted", "ex:resolved" ] } }, { "type": "TripleConstraint", "predicate": "ex:reproducedBy", "value": { "type": "ShapeRef", "reference": "my:TesterShape" } } ] } }, "my:EmployeeShape": { "type": "Shape", "expression": { "type": "group", "expressions": [ { "type": "TripleConstraint", "predicate": "foaf:name", "value": { "type": "NodeConstraint", "datatype": "xsd:string" } }, { "type": "TripleConstraint", "predicate": "ex:department", "value": { "type": "NodeConstraint", "values": [ "ex:Programming" ] } } ] } } }
# passing data inst:Issue1 ex:state ex:accepted ; ex:reproducedBy http://hr.example/id#123 . http://hr.example/id#123 foaf:name xsd:string ; ex:department ex:ProgrammingDepartment .
# failing data inst:Issue1 ex:state ex:accepted ; ex:reproducedBy http://hr.example/id#abc . http://hr.example/id#abc foaf:name xsd:string ; ex:department ex:ProgrammingDepartment .
It may be convenient to factor out the value constraints for instance if they are referenced more than once.
ShExC's value class definitions
permit one to write a definition and reference it in value class references
.
Here, both ex:reproducedBy and ex:assignedTo are value class references to $my:EmployeeConstraint, which asserts that the object is an IRI matching a specific pattern, and which matches my:EmployeeShape.
# schema (ShExC) $my:EmployeeConstraint = IRI @my:EmployeeShape PATTERN "^http://hr.example/id#[0-9]+" my:IssueShape { ex:state [ex:accepted ex:resolved]; ex:reproducedBy $my:EmployeeConstraint; ex:assignedTo $my:EmployeeConstraint } my:EmployeeShape { foaf:name xsd:string; ex:department [ex:ProgrammingDepartment] }
// schema (JSON) { "my:IssueShape": { "type": "Shape", "expression": { "type": "group", "expressions": [ { "type": "TripleConstraint", "predicate": "ex:state", "value": { "type": "NodeConstraint", "values": [ "ex:accepted", "ex:resolved" ] } }, { "type": "TripleConstraint", "predicate": "ex:reproducedBy", "value": { "type": "ShapeRef", "reference": "my:TesterShape" } }, { "type": "TripleConstraint", "predicate": "ex:assignedTo", "value": { "type": "ShapeRef", "reference": "my:EmployeeShape" } } ] } }, "my:EmployeeShape": { "type": "Shape", "expression": { "type": "group", "expressions": [ { "type": "TripleConstraint", "predicate": "foaf:name", "value": { "type": "NodeConstraint", "datatype": "xsd:string" } }, { "type": "TripleConstraint", "predicate": "ex:department", "value": { "type": "NodeConstraint", "values": [ "ex:Programming" ] } } ] } } }
# passing data inst:Issue1 ex:state ex:accepted ; ex:reproducedBy http://hr.example/id#123 ; ex:assignedTo http://hr.example/id#456 . http://hr.example/id#123 foaf:name xsd:string ; ex:department ex:ProgrammingDepartment . http://hr.example/id#456 foaf:name xsd:string ; ex:department ex:ProgrammingDepartment .
# failing data inst:Issue1 ex:state ex:accepted ; ex:reproducedBy http://hr.example/id#123 ; ex:assignedTo http://hr.example/id#abc . http://hr.example/id#123 foaf:name xsd:string ; ex:department ex:ProgrammingDepartment . http://hr.example/id#abc foaf:name xsd:string ; ex:department ex:HRDepartment .
Semantic actions
are pieces of arbitrary code attached to expressions in a shape.
They can be used to signal a validation failure or perform operations with side effects.
(The name "semantic action" comes from their serving a same role as semantic actions in parsers like Antlr or Yacc.)
Below is an example from a standard extension called "Test" which can only print(msg)
or fail(msg)
:
# schema (ShExC) my:IssueShape { ex:state [ex:unassigned ex:assigned]; ex:reportedBy @my:UserShape } my:UserShape { ( foaf:name xsd:string %test:{ print(o) %} | foaf:givenName xsd:string+; foaf:familyName xsd:string %test:{ fail("doomed") %} ); foaf:mbox IRI }
// schema (JSON) { "type": "Schema", "shapes": { "my:IssueShape": { "type": "Shape", "expression": { "type": "group", "expressions": [ { "type": "TripleConstraint", "predicate": "ex:state", "value": { "type": "NodeConstraint", "values": [ "ex:unassigned", "ex:assigned" ] } }, { "type": "TripleConstraint", "predicate": "ex:reportedBy", "value": { "type": "ShapeRef", "reference": "my:UserShape" } } ] } }, "my:UserShape": { "type": "Shape", "expression": { "type": "group", "expressions": [ { "type": "OneOf", "expressions": [ { "type": "TripleConstraint", "predicate": "foaf:name", "value": { "type": "NodeConstraint", "datatype": "xsd:string" }, "semActs": [ { "type": "SemAct", "name": "test:", "code": " print(o) " } ] }, { "type": "group", "expressions": [ { "type": "TripleConstraint", "predicate": "foaf:givenName", "value": { "type": "NodeConstraint", "datatype": "xsd:string" }, "min": 1, "max": "*" }, { "type": "TripleConstraint", "predicate": "foaf:familyName", "value": { "type": "NodeConstraint", "datatype": "xsd:string" }, "semActs": [ { "type": "SemAct", "name": "test:", "code": " fail(\"doomed\") " } ] } ] } ] }, { "type": "TripleConstraint", "predicate": "foaf:mbox", "value": { "type": "NodeConstraint", "nodeKind": "iri" } } ] } } } }
# passing data PREFIX ex: http://ex.example/# PREFIX foaf: http://xmlns.com/foaf/ PREFIX xsd: http://www.w3.org/2001/XMLSchema# inst:Issue1 a ex:Issue ; ex:state ex:unassigned ; ex:reportedBy inst:User2 . inst:User2 a foaf:Person ; foaf:name "Bob Smith" ; foaf:mbox<EMAIL_ADDRESS>; foaf:mbox<EMAIL_ADDRESS>.
# failing data PREFIX ex: http://ex.example/# PREFIX foaf: http://xmlns.com/foaf/ PREFIX xsd: http://www.w3.org/2001/XMLSchema# inst:Issue3 a ex:Issue ; ex:state ex:unsinged ; ex:reportedBy inst:User4 . inst:User4 a foaf:Person ; foaf:name "Bob Smith", "Robert Smith" ; foaf:mbox<EMAIL_ADDRESS>; foaf:mbox<EMAIL_ADDRESS>.
Triple constraints
can be inverse and negated.
Multiple triple constraints on the same property are interpreted as additive; each triple constraint is independently fulfilled by different triples in the instance data.
Here we change the first example so that instead of an issue having an ex:reportedBy identifying a node corresponding to my:UserShape, the user node has a predicate ex:reportedIssue which identifies the issue. We don't want to assert that every node matching my:UserShape has reported an issue; we simply want to make sure that for every issue, there is some user who reported it.
The direction of the arc is changed by prefixing the triple constraint
with a "^" in ShExC or "inverse": true in JSON:
# schema (ShExC) my:IssueShape { ex:state [ex:unassigned ex:assigned]; ^ex:reportedIssue @my:UserShape } my:UserShape { foaf:name xsd:string; foaf:mbox IRI+ }
// schema (JSON) { "type": "Schema", "shapes": { "my:IssueShape": { "type": "Shape", "expression": { "type": "group", "expressions": [ { "type": "TripleConstraint", "predicate": "ex:state", "value": { "type": "NodeConstraint", "values": [ "ex:unassigned", "ex:assigned" ] } }, { "type": "TripleConstraint", "predicate": "ex:reportedIssue", "inverse": true, "value": { "type": "ShapeRef", "reference": "my:IssueShape" } } ] } }, "my:UserShape": { "type": "Shape", "expression": { "type": "group", "expressions": [ { "type": "TripleConstraint", "predicate": "foaf:name", "value": { "type": "NodeConstraint", "datatype": "xsd:string" } }, { "type": "TripleConstraint", "predicate": "foaf:mbox", "value": { "type": "NodeConstraint", "nodeKind": "iri" }, "min": 1, "max": "*" } ] } } } }
# passing data inst:Issue1 a ex:Issue ; ex:state ex:unassigned . inst:User2 a foaf:Person ; foaf:name "Bob Smith" ; ex:reportedIssue inst:Issue1 ; foaf:mbox<EMAIL_ADDRESS>; foaf:mbox<EMAIL_ADDRESS>.
# failing data inst:Issue2 a ex:Issue ; ex:state ex:unassigned ; ex:reportedIssue inst:User4 . inst:User4 a foaf:Person ; foaf:name "Bob Smith" ; foaf:mbox<EMAIL_ADDRESS>; foaf:mbox<EMAIL_ADDRESS>.
# failing data inst:Issue3 a ex:Issue ; ex:state ex:unassigned ; ex:reportedBy inst:User5 . # missing ex:reportedIssue with object inst:Issue3 inst:User5 a foaf:Person ; foaf:name "Bob Smith" ; foaf:mbox<EMAIL_ADDRESS>; foaf:mbox<EMAIL_ADDRESS>.
Note that the passing data contains the triple:
inst:User2 ex:reportedIssue inst:Issue1
while the failing data contains the triple:
inst:Issue1 ex:reportedIssue inst:User2
Note that placing a regular triple constraint
on my:UserShape would require that all users have reported an issue, and is thus different from using the inverse property on my:IssueShape.
In this example, inst:User6 would fail to match my:UserShape:
# schema (ShExC) my:IssueShape { ex:state [ex:unassigned ex:assigned] } my:UserShape { foaf:name xsd:string; foaf:mbox IRI+; ex:reportedIssue @my:UserShape }
// schema (JSON) { "type": "Schema", "shapes": { "my:IssueShape": { "type": "Shape", "expression": { "type": "group", "expressions": [ { "type": "TripleConstraint", "predicate": "ex:state", "value": { "type": "NodeConstraint", "values": [ "ex:unassigned", "ex:assigned" ] } } ] } }, "my:UserShape": { "type": "Shape", "expression": { "type": "group", "expressions": [ { "type": "TripleConstraint", "predicate": "foaf:name", "value": { "type": "NodeConstraint", "datatype": "xsd:string" } }, { "type": "TripleConstraint", "predicate": "foaf:mbox", "value": { "type": "NodeConstraint", "nodeKind": "iri" }, "min": 1, "max": "*" }, { "type": "TripleConstraint", "predicate": "ex:reportedIssue", "inverse": false, "value": { "type": "ShapeRef", "reference": "my:IssueShape" } } ] } } } }
# passing and failing data inst:Issue4 a ex:Issue ; ex:state ex:unassigned . inst:User6 a foaf:Person ; # fails my:UserShape foaf:name "Bob Smith" ; foaf:mbox<EMAIL_ADDRESS>; foaf:mbox<EMAIL_ADDRESS>. inst:User7 a foaf:Person ; foaf:name "Bob Smith" ; ex:reportedIssue inst:Issue4 ; foaf:mbox<EMAIL_ADDRESS>; foaf:mbox<EMAIL_ADDRESS>.
Sometimes we want to say what's not in a schema as well as what's in it. For instance, we may want to say that a SolitaryIssueShape is not a component of anything else, nor does it have components:
# schema (ShExC) my:SolitaryIssueShape { ex:state [ex:unassigned ex:assigned]; !^ex:component .; !ex:component . }
// schema (JSON)
TODO
# passing and failing data inst:Issue1 a ex:Issue ; rdfs:label "smokes too much" ; ex:state ex:unassigned . # inst:Issue2 fails my:SolitaryIssueShape inst:Issue2 a ex:Issue ; dc:creator "Alice" ; ex:state ex:unassigned ; ex:component inst:Issue3 . # inst:Issue3 fails my:SolitaryIssueShape inst:Issue3 a ex:Issue ; rdfs:label "smokes too much" ; ex:state ex:unassigned .
inst:Issue2 fails because it has an "outgoing" component triple
inst:Issue2 ex:component inst:Issue3 .
which violates this constraint:
!ex:component .
and inst:Issue3 fails because the same triple is an "incoming" component triple, violating this constraint:
!^ex:component .
The use of generic predicates sometimes leads to their being used multiple times in the same shape. In this example, we want to make sure that an issue that is ex:accepted or ex:resolved has been reproduced by a tester and a programmer:
# schema (ShExC) my:IssueShape { ex:state [ex:accepted ex:resolved]; ex:reproducedBy @my:TesterShape; # Make sure it's checked by testing ex:reproducedBy @my:ProgrammerShape # and by a programmer. } my:TesterShape { foaf:name xsd:string; ex:role [ex:testingRole] } my:ProgrammerShape { foaf:name xsd:string; ex:department [ex:ProgrammingDepartment] }
// schema (JSON) { "my:IssueShape": { "type": "Shape", "expression": { "type": "group", "expressions": [ { "type": "TripleConstraint", "predicate": "ex:state", "value": { "type": "NodeConstraint", "values": [ "ex:accepted", "ex:resolved" ] } }, { "type": "TripleConstraint", "predicate": "ex:reproducedBy", "value": { "type": "ShapeRef", "reference": "my:TesterShape" } }, { "type": "TripleConstraint", "predicate": "ex:reproducedBy", "value": { "type": "ShapeRef", "reference": "my:ProgrammerShape" } } ] } }, "my:TesterShape": { "type": "Shape", "expression": { "type": "group", "expressions": [ { "type": "TripleConstraint", "predicate": "foaf:name", "value": { "type": "NodeConstraint", "datatype": "xsd:string" } }, { "type": "TripleConstraint", "predicate": "ex:role", "value": { "type": "NodeConstraint", "values": [ "ex:testingRole" ] } } ] } }, "my:ProgrammerShape": { "type": "Shape", "expression": { "type": "group", "expressions": [ { "type": "TripleConstraint", "predicate": "foaf:name", "value": { "type": "NodeConstraint", "datatype": "xsd:string" } }, { "type": "TripleConstraint", "predicate": "ex:department", "value": { "type": "NodeConstraint", "values": [ "ex:Programming" ] } } ] } } }
# passing data inst:Issue1 ex:state ex:accepted ; ex:reproducedBy inst:Tester2 ; ex:reproducedBy inst:Programmer3 . inst:Tester2 foaf:name xsd:string ; ex:role ex:testingRole . inst:Programmer3 foaf:name xsd:string ; ex:department ex:ProgrammingDepartment .
# failing data inst:Issue1 ex:state ex:accepted ; ex:reproducedBy inst:Tester2 ; ex:reproducedBy inst:Tester4 . inst:Tester2 foaf:name xsd:string ; ex:role ex:testingRole . inst:Tester4 foaf:name xsd:string ; ex:role ex:testingRole .
There are two proposed strategies for validation:
partition
- no triple can be used to satisfy more than one constraint.
conjunction
- triples are allowed to satisfy more than one constraint.
These two strategies are equivalent when no triple satisfies more than one constraint. In the example above, depending on the strategy being used, someone acting as both a programmer and a tester might or might not allow to satisfy the schema.
Below are three variants of the example above. These each fail when evaluated by one of the strategies. Below each example is a workaround which works for the failing validation strategy.
One individual acting as both tester and programmer.
inst:Issue1 ex:state ex:accepted ; ex:reproducedBy inst:Testgrammer23 . inst:Testgrammer23 foaf:name xsd:string ; ex:role ex:testingRole ; ex:department ex:ProgrammingDepartment .
fails partition
, workaround is:
# schema (ShExC) my:IssueShape { ex:state [ex:accepted ex:resolved]; ( ex:reproducedBy @my:TesterShape; ex:reproducedBy @my:ProgrammerShape | ex:reproducedBy @my:TesterShape AND @my:ProgrammerShape ) }
TODO
One individual acts can be both a tester and a programmer, another is only a tester.
# one tester and one combination inst:Issue1 ex:state ex:accepted ; ex:reproducedBy inst:Tester2 ; ex:reproducedBy inst:Testgrammer23 . inst:Tester2 foaf:name xsd:string ; ex:role ex:testingRole . inst:Testgrammer23 foaf:name xsd:string ; ex:role ex:testingRole ; ex:department ex:ProgrammingDepartment .
fails conjunction
, workaround is:
# schema (ShExC) my:IssueShape { ex:state [ex:accepted ex:resolved]; ( ex:reproducedBy @my:TesterShape; ex:reproducedBy @my:ProgrammerShape | ex:reproducedBy @my:TesterShape AND NOT @my:ProgrammerShape ex:reproducedBy @my:TesterShape AND @my:ProgrammerShape | ex:reproducedBy @my:ProgrammerShape AND NOT @my:TesterShape ex:reproducedBy @my:ProgrammerShape AND @my:TesterShape ) }
TODO
Two individuals can act as both a tester and a programmer.
# two combinations inst:Issue1 ex:state ex:accepted ; ex:reproducedBy inst:Testgrammer23 ; ex:reproducedBy inst:Testgrammer45 . inst:Testgrammer23 foaf:name xsd:string ; ex:role ex:testingRole ; ex:department ex:ProgrammingDepartment . inst:Testgrammer45 foaf:name xsd:string ; ex:role ex:testingRole ; ex:department ex:ProgrammingDepartment .
fails conjunction
, workaround is:
# schema (ShExC) my:IssueShape { ex:state [ex:accepted ex:resolved]; ( ex:reproducedBy @my:TesterShape; ex:reproducedBy @my:ProgrammerShape | ex:reproducedBy @my:TesterShape AND @my:ProgrammerShape{2} ) }
The behavior in these cases currently uses the partition
strategy.
Please send feedback to<EMAIL_ADDRESS>with advice and use cases, if the conjunction
strategy is better suited for your use cases.
Services backed by an RDF triple store may accept and ignore triples which are not mentioned in the schema (presuming the schema identifies the triples that the service understands and manipulates). Likewise, some SPARQL endpoints may be best described as providing data in a particular schema, but also likely to have additional data not mentioned in the schema. On the other end of the spectrum may be services or databases which accept or emit only the structures described in the schema. ShEx can describe these constraints.
As described above in Additive Property Declarations, triple constraint
constrain all triples with the given predicate to match one of the triple constraints
.
This is called "closing a property".
It is often useful to open a property to permit instances of it which are not included in the schema.
Here is a predicate that is closed by some mention of it in an expression:
# schema (ShExC) my:IssueShape { a [ex:Employee]; a [foaf:Person] }
// schema (JSON) { "type": "Schema", "shapes": { "my:IssueShape": { "type": "Shape", "expression": { "type": "group", "expressions": [ { "type": "TripleConstraint", "predicate": "rdf:type", "value": { "type": "NodeConstraint", "values": [ "ex:Employee" ] } }, { "type": "TripleConstraint", "predicate": "ex:reportedBy", "value": { "type": "NodeConstraint", "values": [ "foaf:Person" ] } } ] } } } }
# failing data inst:User4 a foaf:Person, ex:Employee, ex:Manager.
The data with the extra
inst:User4 a ex:Manager .
arc can accepted by adding rdf:type (or a
) as an "EXTRA" predicate, permitting any number of additional arcs with that predicate:
# schema (ShExC) my:IssueShape EXTRA a { a [ex:Employee]; a [foaf:Person] }
// schema (JSON) { "type": "Schema", "shapes": { "my:IssueShape": { "type": "Shape", "expression": { "type": "group", "expressions": [ { "type": "TripleConstraint", "predicate": "rdf:type", "value": { "type": "NodeConstraint", "values": [ "ex:Employee" ] } }, { "type": "TripleConstraint", "predicate": "ex:reportedBy", "value": { "type": "NodeConstraint", "values": [ "foaf:Person" ] } } ] } } } }
# passing data inst:User4 a foaf:Person, ex:Employee, ex:Manager.
Shapes can close not only the predicates listed in their expressions, but all other predicates as well with the keyword "CLOSED":
# schema (ShExC) my:UserShape { foaf:name xsd:string; foaf:mbox IRI+ }
// schema (JSON) { "type": "Schema", "shapes": { "my:UserShape": { "type": "Shape", "expression": { "type": "group", "expressions": [ { "type": "TripleConstraint", "predicate": "foaf:name", "value": { "type": "NodeConstraint", "datatype": "xsd:string" } }, { "type": "TripleConstraint", "predicate": "foaf:mbox", "value": { "type": "NodeConstraint", "nodeKind": "iri" }, "min": 1, "max": "*" } ] } } } }
# passing data inst:User4 foaf:knows inst:User2 . inst:User2 a foaf:Person ; rdfs:label "Robert Smith's person record" ; foaf:name "Bob Smith" ; foaf:mbox<EMAIL_ADDRESS>; foaf:mbox<EMAIL_ADDRESS>.
# schema (ShExC) my:UserShape CLOSED { foaf:name xsd:string; foaf:mbox IRI+ }
// schema (JSON) { "type": "Schema", "shapes": { "my:UserShape": { "type": "Shape", "expression": { "type": "group", "expressions": [ { "type": "TripleConstraint", "predicate": "foaf:name", "value": { "type": "NodeConstraint", "datatype": "xsd:string" } }, { "type": "TripleConstraint", "predicate": "foaf:mbox", "value": { "type": "NodeConstraint", "nodeKind": "iri" }, "min": 1, "max": "*" } ] } } } }
# failing data inst:User4 foaf:knows inst:User2 . inst:User2 a foaf:Person ; rdfs:label "Robert Smith's person record" ; foaf:name "Bob Smith" ; foaf:mbox<EMAIL_ADDRESS>; foaf:mbox<EMAIL_ADDRESS>.
Only triples with the focus node
as a subject are subject to the constraints of closed shapes
.
# schema (ShExC) my:UserShape CLOSED { foaf:name xsd:string; foaf:mbox IRI+ }
// schema (JSON) { "type": "Schema", "shapes": { "my:UserShape": { "type": "Shape", "expression": { "type": "group", "expressions": [ { "type": "TripleConstraint", "predicate": "foaf:name", "value": { "type": "NodeConstraint", "datatype": "xsd:string" } }, { "type": "TripleConstraint", "predicate": "foaf:mbox", "value": { "type": "NodeConstraint", "nodeKind": "iri" }, "min": 1, "max": "*" } ] } } } }
# passing data inst:User4 foaf:knows inst:User2 . inst:User2 a foaf:Person ; rdfs:label "Robert Smith's person record" ; foaf:name "Bob Smith" ; foaf:mbox<EMAIL_ADDRESS>; foaf:mbox<EMAIL_ADDRESS>.
As described above in Vocabulary, value sets
in a value constraint
enumerate permissible values for some property.
my:IssueShape {
ex:state [ex:unassigned ex:assigned]
}
{ "my:IssueShape": { "type": "Shape",
"expression": { "type": "TripleConstraint", "predicate": "ex:status",
"value": { "type": "NodeConstraint", "values": [ "ex:unassigned", "ex:assigned" ] } } } }
The above examples could also be literals, e.g.
my:IssueShape {
ex:state ["unassigned" "assigned"]
}
{ "my:IssueShape": { "type": "Shape",
"expression": { "type": "TripleConstraint", "predicate": "ex:status",
"value": { "type": "NodeConstraint", "values": [ "\"unassigned\'", "\"assigned\"" ] } } } }
Fixed values are represented as value sets with one member. For example, a required type triple can be expressed like:
my:UserShape {
rdf:type [foaf:Person]
}
{ "my:IssueShape": { "type": "Shape",
"expression": { "type": "TripleConstraint", "predicate": "rdf:type",
"value": { "type": "NodeConstraint", "values": [ "foaf:Person" ] } } } }
or using the keyword a
:
my:UserShape { a [foaf:Person] }
{ "my:IssueShape": { "type": "Shape",
"expression": { "type": "TripleConstraint", "predicate": "a",
"value": { "type": "NodeConstraint", "values": [ "foaf:Person" ] } } } }
A value set can also contain IRI ranges
.
A range can be an IRI (in any valid IRI form) followed by "~
", which indicates that the range includes all IRIs starting with that IRI:
# schema (ShExC) PREFIX ex: <http://a.example/#> PREFIX excodes: <http://a.example/codes#> PREFIX exmisc: <http://aux.example/misc#> my:UserShape { ex:status [ excodes:~ auxterms:~ ] }
// schema (JSON) { "my:UserShape": { "type": "Shape", "expression": { "type": "TripleConstraint", "predicate": "ex:status", "value": { "type": "NodeConstraint", "values": [ "excodes:unassigned", "excodes:assigned" ] } } } }
# passing data inst:Shape2 ex:status excodes:resolved .
# failing data - ex:done not in any range inst:Shape5 ex:status ex:done.
Since an IRI range matched multiple IRIs, one may wish to exclude contained IRIs or IRI ranges.
For example we may wish to include IRI exclusion
A value set can also contain IRI ranges
.
A range can be an IRI (in any valid IRI form) followed by "~
", which indicates that the range includes all IRIs starting with that IRI:
# schema (ShExC) PREFIX ex: <http://a.example/#> PREFIX excodes: <http://a.example/codes#> PREFIX auxterms: <http://aux.example/terms#> my:UserShape { ex:status [ excodes:~ - excodes:unassigned - excodes:assigned auxterms:~ - <http://aux.example/terms#med_>~ ] }
// schema (JSON) { "my:UserShape": { "type": "Shape", "expression": { "type": "TripleConstraint", "predicate": "ex:status", "value": { "type": "NodeConstraint", "values": [ "excodes:unassigned", "excodes:assigned" ] } } } }
# passing data inst:Shape2 ex:status excodes:resolved .
# failing data - excodes:assigned prohibited inst:Shape3 ex:status excodes:assigned.
# failing data - auxterms:med_… prohibited inst:Shape4 ex:status auxterms:med_sniffles.
# failing data - ex:done not in any range inst:Shape5 ex:status ex:done.
You can also use a ".
" with some IRI exclusions
in order to say that anything is permitted except those exclusions.
# schema (ShExC) my:UserShape { ex:status [ . - excodes:unassigned - excodes:assigned ] }
// schema (JSON) { "my:UserShape": { "type": "Shape", "expression": { "type": "TripleConstraint", "predicate": "ex:status", "value": { "type": "NodeConstraint", "values": [ "excodes:unassigned", "excodes:assigned" ] } } } }
# passing data inst:Shape2 ex:status ex:random .
# failing data - excodes:assigned prohibited inst:Shape3 ex:status excodes:assigned.
When ShEx is used for validation, the results have a defined JSON representation which captures all expressions which passed validation and all triple patterns which matched some triples in the tested data.
This structure reports the tree traversed in a successful validation, using the same expression structures as the JSON representation of ShEx.
Each validated triple constraint
includes the matching triple, including the tree reported from validating any value shapes
in the triple constraint.
The semantics of ShEx are defined in terms of validating a node in some graph as a shape some schema. Here are a few ways one might associate nodes with shapes:
It is current unclear to what extend ShEx can be represented in SHACL. Some of the obvious differences are captured as issues:
Constrain the length of a foaf:name to be >= 3 and <= 255:
# schema (ShExC) my:UserShape { foaf:name xsd:string MinLength 3 MaxLength 255 }
// schema (JSON) { "my:UserShape": { "type": "Shape", "expression": { "type": "TripleConstraint", "predicate": "foaf:name", "value": { "type": "NodeConstraint", "datatype": "xsd:string", "minlength": 3, "maxlength": 255 } } } }
# passing data inst:User2 foaf:name "Bob Smith" .
# failing data inst:User9 foaf:name "BS".
[for editors] current switches:
(j
)son vs. shex(c
).


The counting density describes the number of data on a certain
test
area, (counting calotte). These
calottes are arranged on a grid (counting grid)
in the Lambert projection.
The method
was
introduced by W. Schmidt (1925).
In this plot contour lines are drawn between areas of increasing counting densities.


Preparation time
less than 30 mins
Cooking time
10 to 30 mins
Serves
Serves 2
For the lobster and fillet steak, preheat the grill high. Cut the lobster in half and remove the tail and claw meat, chop it up and place back into the tail shells.
Heat a griddle pan until hot and lightly oil the steak. Cook on each side for 3 minutes, or until cooked to your liking. Set aside to rest in a warm place.
In the meantime place the butter and dulse (or watercress) in a bowl and mix. Place the lobster tails on a grill tray, dot some of the butter on top and place under the grill for 1-2 minutes or until the butter is melted and the lobster meat is hot.
For the straw fries and salad, heat a deep-fat fryer to 180C, or half fill a large deep pan with vegetable oil and heat until a piece of bread turns golden-brown when dropped in the oil. (CAUTION: Hot oil can be very dangerous. Do not leave unattended.)
Lower the chips into the fryer and cook for 5 minutes, or until golden-brown and crisp. Drain on kitchen paper.
Place the Little Gem lettuce in a large bowl. Mix the remaining salad ingredients together then pour over the lettuce.
To serve, place the lobster tails on serving plates with the steak alongside. Place the chips in bowls along with the salad. Put a knob of butter on each steak just before serving.


Dynamic Movement Training uses the body's natural movement patterns through three dimensional exercises.
Involve your whole body by challenging your cardiovascular, muscular and neural systems at the same time.
Movements can just use your body weight or be loaded for greater benefits.
The more dynamically you move, the better you'll feel and perform.
Combine dynamic strength, fitness and functional training to excercise three times more effectively.
Improve muscular control, use more energy for accelerated weight loss and build performance in everyday life and sports.
Dynamic movement training is important to help you maintain a healthy body and healthy mind.
Whatever you want from a workout, make DMT part of your training programme for quicker and mre effetive results.


Below are some simple tips you can try using to manage your levels of stress:
- Engage in physical activity, being active and getting you blood pumping helps restore both your mind and body to be calm and relaxed.
- Meditation, deep breathing and concentrated stretching can help alleviate physical stress or tension you may unknowingly have. Even consider massage or book an appointment with a chiropractor as a lot of body imbalances/tension/injuries can affect the mind.
- Engage with other people, You may have a friend, family member or work colleague with whom you can talk to in order to relieve yourself of stressful thoughts. This may be thought of as venting however if its someone you trust or someone who cares for you they should be able to understand and try to help your situation.
 It is common for people to associate stress with bad eating habits which in turn will make you feel worse, so consider more variety as well as avoiding the junk. Lastly resting a healthy 7-8 hours a night can really do wonders on your mood and energy. This may seem obvious but some people just brush it off not understanding the importance of letting your brain rest in order to have proper function.
- Be more honest to yourself, try to put yourself first and make your own choices, having people decide for you or being forced into a decision you don't want to make can be a real factor to causing stress to some people. The point is just to think by yourself for yourself so that you can have more control over what you do in your life.
- Avoid stimulants and depressants, stimulants like Caffeine and Nicotine will make you feel more alert but they make your body do unnecessary work which can increase your levels of stress.  Instead try drinking herbal teas, natural juices and generally keep hydrated.
- The last point is an underlying one which is present in all of the previous points, which is to engage. Meaning if you don't actively try to change your situation and instead consequentially worsen it, your levels of stress will only get worse and it will be harder to relieve yourself of stress.
Disclaimer
The intention of this application is to help those in stressful situations relieve that stress and taking advice from this app can generally help people with stress. However it is alway recommended that you seek professional help when the stress is starting to take a noticeable toll.
Useful Links
In the section below there are links provided which you can use to further support yourself in harder times especially when stress persists and may develop into possible mental health problems or drug dependencies as a coping mechanism.


The day has come. The postponed CITCS College Orientation day was finally held.
We still have to attent our first subjects before going to the theater for the orientation.
The orientation went by like Eh -_-... I went home to do some homeworks. I will try to finish 3 websites today wish me luck.
All Souls Day. The right day to visit the graves of our beloved departure.(Not on All Saints day. I think.)
As I mentioned, there should be no classes today. But there are no announcements so I went to school.
First subject is a laboratory class. The internet is down so we could not work on our projects. The day just went by with me looking like this-_-.
All Saints Day came and I have no plan for the day. I washed my clothes and as I finish my father arrived from somewhere I don't know about.
I finished my laundry and laid down for a moment to try to get a little rest. Then I was disturb by a starting engine. I went to check it out. I saw my father starting the car then asked, "I'm going to km4 wanna come?" he said. I nodded then took a quick shower and changed.
We went to km4 and the roads were pretty much free. No traffic at all, all the shops are closed and there are only few peoples around.
Then we arrived. For me it was pretty much a reunion with people I have'nt seen for almost a year. Kids grew, Aunts still beautiful as always and uncles having a time of their lives drinking and laughing.


2020 Ford Mach-E: Mustang-inspired EV spied wearing minimal camouflage
Ford's first all-electric SUV has been caught in the wild just nine days out from its official launch.
by Scott Collie- shares
The all-electric Ford Mach-E crossover has been spied wearing nothing but a skimpy wrap, as the Blue Oval gears up for its launch on November 17.
Ford has teased Mustang-inspired SUV with a number of shadowy sketches, but this is our first proper look at the electric crossover in production spec.
Up front, the Mach-E has a closed-over grille and slim, aggressive headlamps clearly inspired by those of the current Mustang. There's also a hint of Nissan Ariya Concept about the headlamps.
The Mustang inspiration is even stronger at the rear, where Ford has given its first pure-electric SUV a set of pumped-up guards and transplanted the two-door muscle car's taillights.
Although it's covered at the moment, we could see a gloss black trim piece linking the taillights – once again, inspired by the Mustang.
As with electric crossovers like the Tesla Model X and Audi e-tron, it appears the Mach-E will get a sloping roofline to aid aerodynamics and, by extension, range.
When it goes on sale in the USA next year, the Mach-E will have a claimed driving range of around 595km on the more stringent WLTP test cycle. That puts it ahead of the Tesla Model X, which only manages 580km on the lenient NEDC test cycle, and cars like the Audi e-tron (400km on WLTP).
Described as an "all-electric performance SUV", the Mach-E is expected to spawn more powerful variants after launch.
Ford says Mach-E owners will have access to a charging network of 12,000 high-speed public locations, with more than 35,000 charge points in North America.
The car will support 120V and 240V home outlets if you're happy to charge more slowly, although the company will also offer a 'Connected Charge Station' home fast charger.
The Mach-E will be launched on November 17 in the USA. Stay tuned for more in the lead up to its launch.
Will the Ford Mach-E come to Australia?
It remains to be seen if the Mach-E will be offered in Australia, with no official word on offer ahead of the electric SUV's unveiling.
So far, the company has limited its local electrification plans to the upcoming Escape plug-in hybrid, but a push towards a wider EV offering could kick off with a model like the Mach-E. CarAdvice has contacted Ford Australia.
Click on the images for the full gallery.
1
10
nextprevious
2020 Ford Mach-E: Mustang-inspired EV spied wearing minimal camouflage


Genesis 41:27
And the seven thin and ill favored kine that came up after them are seven years; and the seven empty ears blasted with the east wind shall be seven years of famine.


Start of the video
Middle of the video
End of the video
Do not modify
lowercase
Capitalise sentence
Capitalise Words
Donate!


title=First Post date=2015-10-14 type=post tags=blog status=published ~~~~~~
Just discovered JBake and decided to use it for skysail.
package org.jbake;
public class Oven {
public static void main(String[] args) {
System.out.print("Baking!");
}
}


Select all the necessary tasks for the workflow, in any order, to create the workflow level tasks pool.
Re-order the selected tasks, by drag-drop to finalize the order in which they will be executed.
Define and wire the input and output parameters for all the selected and order fixated tasks.
Provide the workflow metadata like name, version, description to create the workflow with the defined tasks.


Installation¶
Install mlcomp package
pip install mlcomp mlcomp init mlcomp migrate
Setup your environment
A Configuration file automatically created at ~/mlcomp/configs/.env
Environment variables:
ROOT_FOLDER - folder to save mlcomp files: configs, db, tasks, etc
TOKEN - site security token. Please change it to any string
DB_TYPE. Either SQLITE or POSTGRESQL
POSTGRES_DB. PostgreSql db name
POSTGRES_USER. PostgreSql user
POSTGRES_PASSWORD. PostgreSql password
POSTGRES_HOST. PostgreSql host
PGDATA. PostgreSql db files location
REDIS_HOST. Redis host
REDIS_PORT. Redis port
REDIS_PASSWORD. Redis password
WEB_HOST. mlcomp site host. <IP_ADDRESS> means it is available from everywhere
WEB_PORT. mlcomp site port
CONSOLE_LOG_LEVEL. log level for output to the console
DB_LOG_LEVEL. log level for output to the database
IP. Ip of a worker. The worker must be accessible from other workers by these IP/PORT
PORT. Port of a worker. The worker must be accessible from other workers by these IP/PORT (SSH protocol)
MASTER_PORT_RANGE. distributed port range for a worker. 29500-29510 means that if this worker will be a master in a distributed learning, it will use the first free port from this range. Ranges of different workers must be not overlapping.
NCCL_SOCKET_IFNAME. NCCL network interface.
Run db, redis, mlcomp-server, mlcomp-workers:
Variant 1: minimal(if you have 1 computer)
Run all necessary(mlcomp-server, mlcomp-workers, redis-server), it uses SQLITE:
mlcomp-server start
Variant 2: full
Change your Environment variables to use PostgreSql
Install rsync on each worker computer
sudo apt-get install rsync
Ensure every computer is available by SSH protocol with IP/PORT you specified in the .env file.
rsync will perform the following commands:
to upload
rsync -vhru -e "ssh -p {target.port} -o StrictHostKeyChecking=no" \ {folder}/ {target.user}@{target.ip}:{folder}/ --perms --chmod=777
to download
rsync -vhru -e "ssh -p {source.port} -o StrictHostKeyChecking=no" \ {source.user}@{source.ip}:{folder}/ {folder}/ --perms --chmod=777
Install apex for distributed learning
To Run postgresql, redis-server, mlcomp-server, execute on your server-computer:
cd ~/mlcomp/configs/ docker-compose -f server-compose.yml up -d
Run on each worker computer:
mlcomp-worker start


1 reference to Hashtable_ctor
System.Management.Automation (1)
engine\parser\Compiler.cs (1)
6487
Expression.New(ordered ? CachedReflectionInfo.OrderedDictionary_ctor : CachedReflectionInfo.
Hashtable_ctor
,


Tusen ganger god natt / 1,000 Times Good Night
Fail Safe is a TV movie starring Walter Cronkite, Richard Dreyfuss, and Noah Wyle. Cold War tensions climb to a fever pitch when a U.S. bomber is accidentally ordered to drop a nuclear warhead on Moscow.


?The
New
York
copyright
reserved
Botanical
Garden
Miscanthus
sinensis
Anderss,
var.
purpurascens
(Anderss.)
Rendle
Herbarium,
Institute
of
Botany,
the
Chinese
Academy
of
Sciences,
Beijing
(PE)
flACy
HERBARIUM,
TEXAS
A&M
UNIVERSITY
[is
can
thus
sinensis
Ander
'Y-
Frank
W.
Gould
PâRE
DUSS,
HERBU5R
DE
LA
GUADELOUPE.
a
"1
Qd.
jhrr*
uA
^
/
└whoą/
0
└╚╚ă╚╚ti-
└du-
/f
A?
New
York
Botanical
Garden
itomio
1604110
Legend -
Level of confidence that token is an accurately-transcribed word
extremely low
very low
low
undetermined
medium
high
very high


abstract fun verify(): Unit
Verifies this transaction and runs contract code. At this stage it is assumed that signatures have already been verified.
The contract verification logic is run in a custom classloader created for the current transaction.


§431:16-215 Tax exemptions. The association shall be exempt from payment of all fees and all taxes levied by this State or any of its subdivisions, except taxes levied on real property. [L 1987, c 347, pt of §2]


IBM Search standards
Web user interface where user can query ESW product master data which has been loaded to the RDH repository.
Search Type: Offering Licensed Function Supply Function Orderable Supply ESW Slice Group Material Master BOM Object Dependency Def Offering / Licensed Function Offering / ESW Slice Group Offering / Supply Function Offering / Orderable Supply Supply Function / Orderable Supply
Offering ID: *
Search By: ID Name
Search Mask:
New Tab description


| Interface | Description |
|---|---|
| OnEngineInitListener |
Represents a listener to provide notification of the engine status upon completion of
initialization.
|
| PositioningManager.OnPositionChangedListener |
Represents an interface for position update listeners.
|
| Class | Description |
|---|---|
| GeoBoundingBox |
Represents a rectangular area in a geographic coordinate system.
|
| GeoCoordinate |
Represents a WGS84 coordinate with double precision.
|
| GeoPolygon |
Represents a
GeoPolygon a polygon object defined in terms of the geographic coordinates of its vertices. |
| GeoPolyline |
Interface representing a
GeoPolyline . |
| GeoPosition |
Represents position, speed, and heading information as provided by a positioning device.
|
| Image |
Encapsulates an image file.
|
| MapActivity | Deprecated
As of SDK 3.3, replaced by
MapFragment . |
| MapEngine |
MapEngine manages all mapping resources and services provided in this SDK. |
| PositioningManager |
Represents a manager for information received from positioning devices, such
as updates to the current position and the average speed.
|
| RoadElement | |
| ViewObject |
Represents the base class implementation for all objects that are selectable from a view.
|
| ViewRect |
Represents a rectangle defined by the top-left corner's coordinate and the width and height of
the rectangle.
|
| Enum | Description |
|---|---|
| CopyrightLogoPosition |
Represents values that describe on-display view positions for the HERE copyright logo.
|
| Image.Type |
This helps the application know the base type of the
Image . |
| OnEngineInitListener.Error |
Represents values describing initialization errors.
|
| PositioningManager.LocationMethod |
Represents values describing the location method.
|
| PositioningManager.LocationStatus |
Represents values describing the location status of a particular location method.
|
| RoadElement.Attribute |
Defined values for different road attributes
|
| RoadElement.FormOfWay |
Form of Way Types
|
| RoadElement.PluralType |
Plural type identifies when a Junction is made up of multiple Road Elements.
|
| ViewObject.Type |
Represents values describing various types of selectable view objects.
|


You can't use Bandcamp while you are offline.
If you have downloaded your music, you can find it in your library folder.


Contents
Script to launch the labyrinth simulation.
This script allows you to run a complete simulation of the labyrinth without graphical interface and with picture and video generation.
It stops according to the stop conditions that are entered in the script.
% for a clean workspace, not obligatory clear close all
%%%%%%%%%%%%%%%%%%%% PARAMETERS %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
Number of iterations. (static dimension)
n= 100;
states of laby (static dimension) where all the out{} genereted will be stored.
labyState=cell(n,9); etat =0; % static dimension etatS=0; % static dimension
Initialization Of labyrinth Select if there is an escape or no
noEscape = 0;
Initial laby state
Structure containing all element to initialize the labyrinth. It is described as follows :
- "walls.V_i" for Vertical Walls,
- "walls.H_i" for Horizontal Walls,
- "pacman_i" for Pacman Initial position and
- "ghost_i" for ghost Initial Position. (Dimensions can change)
labyInit.wallsV_i = [1 0 1 0; 1 1 0 1; 0 0 0 0; 0 1 1 1; 1 0 0 0];% dimension can change labyInit.wallsH_i = [0 0 0 1 0; 0 1 0 1 0; 0 1 0 1 0; 0 1 0 0 1]; % dimension can change % % labyInit.wallsV_i = [1 1; % 0 1; % 0 0]; % dimension can change % labyInit.wallsH_i = [1 0 0; % 1 0 0]; % d
size of lab (static dimension)
Ms = max(size(labyInit.wallsH_i));
Pacman position (static dimension)
labyInit.pacman_i = [2, 1];
Escape position (static dimension)
labyInit.escape_i = {[5 5], 0};
Commands
Initial value of walls command
=0 : begin with right move
=1 : begin with up move
wallsInit.wallsCommand_i = 0;
Initial value of pacman command
%(if command change, dimension can change, else not) % pacmanInit.pacmanCommand_i= zeros(1,5);
initial value of stop
stopInit.escape = 0; stopInit.pacman = 0;
%%%%%%%%%%%%%%%%%%%%%%%%% MAIN SCRIPT %%%%%%%%%%%%%%%%%%%%%%%%%%%%
For count iteration of loop
i = 1 ;
For break condition
SimulationStopped = 0;
Creation of needed class
wrapper = Wrapper(11, 9, labyInit, wallsInit, pacmanInit, stopInit);
Connection of all the commands
wrapper=wrapper.updateConnexion(1,1); % walls wrapper=wrapper.updateConnexion(3,1); % pacman
Empty in vector for the simulation
in = zeros(1,11);
The first 'step' is the labyrinth at the begining
labyState(1,:)=wrapper.get_out(); i=i+1;
The loop will run until i>n or one stop condition stop the simulation
while (i<=n && ~SimulationStopped) wrapper = wrapper.orderer(in); labyState(i,:)= wrapper.get_out(); stop=wrapper.get_stop(); %%%%%%%%%%%%%% stop condition %%%%%%%%%%%%%%%%%%%%%%% if (sum(stop)~=0) SimulationStopped = 1; end i = i + 1; %pause %%%%%%%%%%%%%%%%%% end
log message (terminal)
fprintf('End of simulation :\n'); if(i>n) % sim finish fprintf('\t The simulation was not stopped (%d steps)\n',n); else %sim break fprintf('\t the simulation have been stopped at the %d step on %d\n',i,n); if(stop(1)) fprintf('\t>Pacman escaped\n'); end if(stop(3)) fprintf('\t>Pacman trapped\n'); end end n = i-1; % new number of iteration;
End of simulation : the simulation have been stopped at the 23 step on 100 >Pacman trapped
Create picture for each iteration and Video in file data
CreatePituresAndVideo_textured(n, labyInit.escape_i, labyState);


| info-namespace |
nla |
| namespace-title |
Namespace of identifiers for the
National Library of Australia's digital & digitised collections |
| registration-date |
2004-09-27 |
| namespace-authority |
| organisation-name |
National Library
of Australia |
| organisation-address |
Parkes Place,
Canberra, ACT, 2600, Australia |
| organisation-uri |
www.nla.gov.au |
| contact-person |
Tony Boston |
| contact-email |
<EMAIL_ADDRESS>|
| contact-tel |
+61 2 6262 1111 |
|
| identifier-syntax |
| description |
Each identifier starts with <info:nla/collection-id>, where the <collection-id> represents one of the following sub-namespaces. The syntax of the remainder of the identifier following the sub-namespace varies according to the type of object.
Manuscripts: /ms-<ms collection no.>-<series no.>-<item no.>-<sequence no.>-<tile no.>-<role code>
Example:
info:nla/ms-ms9-1-s1-e
which is currently resolvable as:
http://nla.gov.au/nla.ms-ms9-1-s1-e (examination copy of the first page of the first item in series 1 of the papers of Sir Joseph Banks.)
Oral History: /oh-<trc collection no.>-<series no.>-<item no.>-<part no.>-<sequence no.>-<piece no.>-<fragment no.>-<role code>
Example:
info:nla/oh-0234-0003-0001-m
which is currently resolvable as:
http://nla.gov.au/nla.oh-0234-0003-0001-m (master recording of the first tape in series 3 of TRC0234)
Maps: /map-<item no.>-<part no.>-<sequence no.>-<tile no.>-<subTile no.>-<role code>
Example:
info:nla/map-rm2099-t
which is currently resolvable as:
http://nla.gov.au/nla.map-rm2099-t (a thumbnail copy of rare map number 2099)
Pictures: /pic-<item no.>-<part no.>-<sequence no.>-<role code>
Example:
info:nla/nla.pic-an6729917-t
which is currently resolvable as:
http://nla.gov.au/nla.pic-an6729917-t (a thumbnail copy of a single picture from the Ellis Rowan collection)
Music: /mus-<item no.>-<sequence no.>-<role code>
Example:
info:nla/nla.mus-an7579855-s2
which is currently resolvable as:
http://nla.gov.au/nla.mus-an7579855-s2 (an unnumbered title page that is the second image in the group representing music item 7579855)
Monographs (gen=General Collection; aus=Australian Collection): /gen-<work no.>-<chapter no.>-<section no.>-<sequence no.>-<role code> .aus-<work no.>-<chapter no.>-<section no.>-<sequence no.>-<role code>
Example:
info:nla/nla.gen-isbn0590353403-2-s1-v
which is currently resolvable as:
http://nla.gov.au/nla.gen-isbn0590353403-2-s1-v (a view copy of the first page of chapter 2 the book with this ISBN)
Serials (gen=General Collection; aus=Australian Collection): /gen-<serial identifier>-<issue vol.>-<issue no.>-<issue part>-<issue date>-<subUnit no.>-<sequence no.>-<role code> .aus-<serial identifier>-<issue vol.>-<issue no.>-<issue part>-<issue date>-<subUnit no.>-<sequence no.>-<role code>
Example:
info:nla/nla.aus-issn10399992-s1-v
which is currently resolvable as:
http://nla.gov.au/nla.aus-issn10399992-s1-v (a view copy of the first page of the serial with this ISSN)
|
| uri |
|
|
| identifier-normalization |
|
| namespace-information |
| description |
To identify a born-digital or a digitised object in the managed digital collections of the National Library of Australia, an intelligent identifier has been constructed which utilises a sub-namespace to encode the collection type and, based on the type, rules for accessing component parts of the object. |
| uri |
http://www.nla.gov.au/nla/staffpaper/2002/boston2.html |
|


The SOAL framework is published under Apache License Version 2.0
Related projects
MetaDslx
MetaDslx is a lightweight metamodeling framework for .NET and Java. It helps implementing domain specific languages.
MetaDslx makes it easier to create compilers for the textual concrete syntax using ANTLR4. MetaDslx extends the ANTLR4 grammars with annotations on rules and elements, which make semantic parsing easier. MetaDslx also comes with a user friendly template-based code generator.


{% extends 'sculpture/base.html' %} {% block title %} MyCRSBI{% endblock %} {% block breadcrumb %}
Create a MyCRSBI account and login to use all its features and to save your notes and comments.
Only you can see your personalised content: comments, tags, and saved searches.
These tags and comments will then be saved in your MyCRSBI area of the website for you to refer back to anytime you login. No one else has access to these notes. The MyCRSBI material is private to your login.
You haven't commented on any sites yet.
{% endif %}You don't appear to have tagged any sites yet.
{% endif %}Editor Notes
{{ site.editor_notes }}
Fieldworker Notes
{{ site.fieldworker_notes }}


Class IS_ONE_OF_EMPTY
source code
gluon.validators.Validator --+
|
IS_ONE_OF_EMPTY
Filtered version of IS_IN_DB():
validates a given value as key of another table, filtered by the
'filterby' field for one of the 'filter_opts' options (=a selective
IS_IN_DB())
NB Filtering isn't active in GQL.
For the dropdown representation:
'label' can be a string template for the record, or a set of field
names of the fields to be used as option labels, or a function or lambda
to create an option label from the respective record (which has to return
a string, of course). The function will take the record as an
argument
No 'options' method as designed to be called next to an Autocomplete
field so don't download a large dropdown unnecessarily.
|
|
| __init__(self,
dbset,
field,
label=None,
filterby=None,
filter_opts=None,
not_filterby=None,
not_filter_opts=None,
error_message="invalid value!",
orderby=None,
groupby=None,
cache=None,
multiple=False,
zero="",
sort=False,
_and=None) |
source code
|
|
|
|
|
|
|
set_filter(self,
filterby=None,
filter_opts=None,
not_filterby=None,
not_filter_opts=None)
This can be called from prep to apply a filter base on data in the
record or the primary resource id. |
source code
|
|
|
|
|
|
|
|
__init__(self,
dbset,
field,
label=None,
filterby=None,
filter_opts=None,
not_filterby=None,
not_filter_opts=None,
error_message="invalid value!",
orderby=None,
groupby=None,
cache=None,
multiple=False,
zero="",
sort=False,
_and=None)
(Constructor)
| source code
|
|
set_filter(self,
filterby=None,
filter_opts=None,
not_filterby=None,
not_filter_opts=None)
| source code
|
This can be called from prep to apply a filter base on data in the
record or the primary resource id.
|


Lying about 6 miles south of Piraeus, Kalamaki is in a rather shabby suburb of Athens.
Position 37º54.68'N', 23º42.03'E.
Moor where there is space. The designated visitors' quay is usually occupied with local boats. Asking at the office is often no help! Shelter is excellent with winds from all directions.
This marina is not situated in the best of areas, being located in the rather dreary suburbs of Athens. Not the safest of places to either leave the boat or to walk around alone at night. Neither is it quiet, as there is a very loud disco/bar on site! At least, now the new airport is open, the noise from the old one near by is much reduced.
One report states: "the only civilised toilet facilities are retained by the marina authorities for their own use so all the yachts use on-board facilities and dump their sewage in the marina".
Last updated August 2009.


Sprite.SetPosition
Syntax
Sprite.SetPosition (spriteID, x, y : int,
centered : boolean)
Description
Moves the sprite specified by spriteID to the location specified by (x, y). If centered is true, then the sprite is centered on (x, y). Otherwise (x, y) specifies the lower-left corner of the sprite.
Example
See Sprite.Hide for an example of Sprite.SetPosition.
Status
Exported qualified.
This means that you can only call the function by calling Sprite.SetPosition, not by calling SetPosition.
See also
Sprite.New.


week1
week2
week3
week4
week5
sub1
sub2
sub3
sub4
sub5
sub6
vertical1
vertical1
vertical1
vertical1
vertical1
hello world
this is a modified panel
by cg


Sparse arrays interpreted as multivariate polynomials.
| Version: | 1.0-3 |
| Depends: | methods |
| Imports: | Rcpp (≥ 0.12.3), partitions, magic |
| LinkingTo: | Rcpp |
| Suggests: | polynom |
| Published: | 2017-05-25 |
| Author: | Robin K. S. Hankin |
| Maintainer: | Robin K. S. Hankin <hankin.robin at gmail.com> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | yes |
| SystemRequirements: | C++11 |
| CRAN checks: | spray results |
| Reference manual: | spray.pdf |
| Vignettes: |
A vignette for the spray package |
| Package source: | spray_1.0-3.tar.gz |
| Windows binaries: | r-devel: spray_1.0-3.zip, r-release: spray_1.0-3.zip, r-oldrel: spray_1.0-3.zip |
| OS X binaries: | r-release: spray_1.0-3.tgz, r-oldrel: spray_1.0-3.tgz |
| Old sources: | spray archive |
Please use the canonical form https://CRAN.R-project.org/package=spray to link to this page.


Everything else from the 80s has aged. The Rapid GT Classic has only matured. Like a fine claret or a really good boob job, each passing year adds something mysterious to its allure. Sure, that new sports coupé is half the weight, and it has a cleaner transmission. But trust us: get inside this vintage, experience the kind of technique and self-assurance only time can bestow, and you'll never waste your time on a younger model again.
SELECT FROM AVAILABLE COLORS TO ORDER
Vehicle Stats
{{statistic.title}}


VARIABLES & CONSTANTS
A variable is nothing but a name given to a storage area that our programs can
manipulate. Each variable in C has a specific type, which determines the size and layout of
the variable's memory; the range of values that can be stored within that memory; and the
set of operations that can be applied to the variable.
Variable names can contain alphabets numbers and underscore. Variable name never starts with a
number and its case sensitive also. These are the predefined types :
| TYPE | DESCRIPTION |
|---|---|
| Char | Typically a single octet(one byte). This is an integer type. |
| Int | The most natural size of integer for the machine. |
| Float | A single-precision floating point value. |
| Double | A double-precision floating point value. |
| Void | Represents the absence of type. |
DECLARATION
A variable declaration provides assurance to the compiler that there is one variable existing with
the given type and name. A variable declaration has its meaning at the time of
compilation only, compiler needs actual variable declaration at the time of linking of the program.
The syntax for declaration is:
data_type variable_name ;
#include// Variable definition: extern int a, b; extern int c; extern float f; int main () { // Variable definition: int a, b; int c; float f; // actual initialization a =10;
L AND R VALUE
lvalue: An expression that is an lvalue may appear as either the left-hand or right-hand
side of an assignment.
rvalue: An expression that is an rvalue may appear on the right- but not left-hand side
of an assignment.
In an assignment the lvalue comes at the left side and rvalue at the right side.
Ex: int g=20 ;
Here r value is 20 and the l value is the memory
location/address value
of the variable.
CONSTANTS
The constants refer to fixed values that the program may not alter during its
execution. These fixed values are also called literals.
Constants can be defined by two methods:
- Variable constant with help of const keyword
- Constants with #define preprocessor
const
Syntax : const data_type variable_name;
#includeint main() { const int LENGTH = 10; const int WIDTH = 5; const char NEWLINE = '\n'; int area; area = LENGTH * WIDTH; printf("value of area : %d", area); printf("%c", NEWLINE); return 0; }
Output: value of area : 50
#define
This is used in code for making general constant value where the value assigned to the quantity which could
be anything.
#define pi 3.14159


Updated on May 13, 2016
This hackathon is being sponsored by Microsoft India in partnership with the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) - India, T-Hub and aWhere, Inc.
In order to make the best decisions possible in a changing climate, farmers and agricultural value chain actors need access to comprehensive information about forecasted weather, ideal dates for planting and interventions, seed varieties, and potential return on investment. But this information is often difficult to compile and communicate in insightful ways.
To address these challenges, Hack4Farming Hyderabad will focus on weather, systems modeling, and their potential impacts on the Indian agriculture sector. Hackathon teams will explore how to leverage new modeling techniques (from ICRISAT researchers), weather data (from aWhere) and Intelligent Cloud (from Microsoft) to address these information gaps, and in so doing benefit agriculture stakeholders such as seed producers, service providers, and farmers across India.
As the climate becomes more volatile, it is more difficult for Indian agriculture practitioners to make the right decisions about farm and value chain management, operations and risk assessment. Decisions made without the benefit of timely and targeted information in turn increase the vulnerability of farmers and Indian food security to today’s less predictable weather events.
Using the expert knowledge available in your team and available tools/datasets, design a solution that can address at least one informational gap in Indian agriculture. This solution should identify the information gap, provide a prototype or proof of concept for the solution, and address the sustainability of the solution through a business plan, proposal outline, or other mechanism.
| Time | Session |
|---|---|
| Day 1 - May 12th | |
| 9:00 am - 10:00 am | Event Registration |
| 10:00 am - 11:15 am | Opening Remarks and Partner Presentations |
| 11:15 am - 12:30 pm | Hackathon Stage 1: Team Brainstorming |
| 12:30 pm | Lunch |
| 1:30 pm - 8:00 pm | Hackathon Stage 2: Initial Coding and Prototyping |
| Day 2 - May 13th | |
| 8:30 am - 12:30 pm | Stage 3: Hacking/Presentation Drafting |
| 12:30 pm | Lunch |
| 1:30 pm - 3:00 pm | Stage 4: Presentation preparations |
| 3:00 pm - 5:00 pm | Presentation of projects, Judging, Outcome announcements |
This hackathon will be held at the ICRISAT campus in Hyderabad, India.
Hackathons provide a great environment to connect and create. As a result, teams often emerge with new contacts, new skills and/or ideas they’d like to develop further.
The hackathon team with the best idea leveraging modeling and weather data to serve smallholder farmers (as determined by a panel of impartial judges) will receive a shared cash prize of $2,000. The winning team will also be offered business and sector-specific mentorship services with startup incubator T-Hub, to help develop their idea into a viable business or product.
A startup evangelist and advisor, Rama Iyer is the Senior Vice President, Strategic Alliances at T-Hub. He is a business and technology leader with over 20 years of experience, who has been at the helm of incubators, creating global and strategic relationships while also advising venture funds.
Rama has worked with telecom giants like Nortel, Ericsson, Cisco and Polycom among others. Over his vast work experience, he has helped global organisations level APAC talent and marketplace to enhance their presence and build a bigger market-place for their global products, solutions and services.
At T-Hub, Rama is structuring and nurturing strategic alliances while also creating CoE programs that can help the startup community. With a keen interest in creating a better ecosystem for startups, Rama is always spotted interacting with startups and sharing his bright ideas with them.
Anil Bhansali is the Managing Director of Microsoft India (R&D) Pvt. Ltd. and the General Manager of the Cloud and Enterprise engineering teams at Microsoft India Development Center (MSIDC). A veteran of over 22 years at Microsoft, Anil began his career here in Redmond in 1991 as part of the Office division, where he worked on MS Excel for multiple releases. He was the Partner Development Manager in the Office Shared Services Team that worked on SharePoint Team Services V1.0 and Windows SharePoint Service version 2.0.
Anil relocated to India in 2003 as Director of the Windows Live Platforms Services Group. He established and drove several engineering efforts at MSIDC before taking over leadership of the Windows feature engineering group in 2006. Anil has a bachelor’s and a master’s degree in computer science from Stony Brook University. In his spare time, Anil loves to travel, run marathons, and spend time with his family.
David Bergvinson has a PhD in plant biochemistry from Ottawa University and is the Director General of ICRISAT.
David has 20 years of experience in maize biochemistry, pathology and entomology. Prior to joining ICRISAT, he was with the International Maize and Wheat Improvement Center (CIMMYT) as Senior Scientist (Entomologist) where he coordinated the entomology research for both maize and wheat at CIMMYT’s headquarters and provided technical support to regional offices. Later at the Bill & Melinda Gates Foundation as Senior Program Officer, Science and Technology, Agricultural Development he was involved in the development and management of crop improvement grants that involved public (national and international) research organizations, private sector and civil society organizations to develop stress-tolerant, farmer-preferred varieties. He also made significant contributions to the Agricultural Development strategy at the Foundation.
We are seeking systems modelers, agriculture stakeholders (including representatives from seed companies, insurance companies, production companies, and many more), and programmers, developers, and data scientists from Hyderabad’s growing base of hackers and technology experts to join our hackathon teams. Teams will compete to develop the best solution to bridge the information gap in Indian agriculture.
If you'd like to participate, please sign-up using the following form and we'll reach out to you!
The Resources Kit for participants is available here.
Twitter:
• Follow and tweet the hashtag #hack4farming on Twitter
• Follow @MicrosoftIndia, @ICRISAT, @THubHyd, @aWhere
Facebook:
• Follow and like posts about the hackathon at the Microsoft India Facebook page
• Follow and like posts about the hackathon at the ICRISAT page
You can view the outputs of past hackathons, and the team presentations here.
Contact us if you have a question the FAQs page hasn't covered.


SMOOTH Perform windowed smoothing on a vector using mathematical functions SYNTAX Y = smooth(X,FRAME) Y = smooth(X,FRAME,MODE) DESCRIPTION Y = smooth(X,FRAME) smooths the input vector X by calculating the running RMS over a series of frames. FRAME specifies the frame characteristics; it can be set to: a scalar - this will be used as the length of the frame, the window will be rectangular a vector - this specifies the shape of the analysis window, the frame length will be length(frame). Y = smooth(X,FRAME,MODE) allows the user to specify a different mathematical smoothing function. The options are: 'rms' - calculates the running rms (default) 'mean' - calculates the running mean (moving average filter) 'median' - calculates the running median NOTE: SMOOTH uses a vectorized implementation that may be slow when X and/or FRAME_LENGTH are very large. The number of elements that are used for calculation is length(X)*FRAME_LENGTH. The algorithm vectorizes the operation by creating a matrix of indexes and extracting its diagonals. E.g. for a vector of length 4 and frame_length of 2, the algorithm creates a temporary zero-padded matix x2 from which it creates a set of indexes: 1 1 2 2 3 3 4 4 5 5 6 6 It then extracts the diagonals where -length(x2)+frame_length<=k<=0, yielding: 1 2 2 3 3 4 4 5 this is used to index x2; operations are then perfromed along the rows.
0001 function y = smooth(x,frame,mode) 0002 0003 % SMOOTH Perform windowed smoothing on a vector using mathematical functions 0004 % 0005 % SYNTAX 0006 % 0007 % Y = smooth(X,FRAME) 0008 % Y = smooth(X,FRAME,MODE) 0009 % 0010 % 0011 % DESCRIPTION 0012 % 0013 % Y = smooth(X,FRAME) smooths the input vector X by calculating the running 0014 % RMS over a series of frames. FRAME specifies the frame characteristics; 0015 % it can be set to: 0016 % 0017 % a scalar - this will be used as the length of the frame, the window will 0018 % be rectangular 0019 % a vector - this specifies the shape of the analysis window, the frame 0020 % length will be length(frame). 0021 % 0022 % Y = smooth(X,FRAME,MODE) allows the user to specify a different 0023 % mathematical smoothing function. The options are: 0024 % 0025 % 'rms' - calculates the running rms (default) 0026 % 'mean' - calculates the running mean (moving average filter) 0027 % 'median' - calculates the running median 0028 % 0029 % NOTE: SMOOTH uses a vectorized implementation that may be slow when X 0030 % and/or FRAME_LENGTH are very large. The number of elements that are used 0031 % for calculation is length(X)*FRAME_LENGTH. The algorithm vectorizes the 0032 % operation by creating a matrix of indexes and extracting its diagonals. 0033 % E.g. for a vector of length 4 and frame_length of 2, the algorithm 0034 % creates a temporary zero-padded matix x2 from which it creates a set of 0035 % indexes: 0036 % 0037 % 1 1 0038 % 2 2 0039 % 3 3 0040 % 4 4 0041 % 5 5 0042 % 6 6 0043 % 0044 % It then extracts the diagonals where -length(x2)+frame_length<=k<=0, 0045 % yielding: 0046 % 0047 % 1 2 0048 % 2 3 0049 % 3 4 0050 % 4 5 0051 % 0052 % this is used to index x2; operations are then perfromed along the rows. 0053 0054 %% Gather inputs 0055 0056 if ~isvector(x) 0057 error('''x'' must be a vector') 0058 end 0059 0060 if isscalar(frame) 0061 frame_length = frame; 0062 window = ones(frame_length,1); 0063 elseif isvector(frame) 0064 window = frame; 0065 frame_length = length(frame); 0066 else 0067 error('''frame'' must be a vector or a scalar') 0068 end 0069 0070 if nargin<3 0071 mode = 'rms'; 0072 end 0073 0074 %% Smooth 0075 0076 % zero pad 0077 x2 = [zeros(ceil((frame_length)/2)-1,1); x(:); zeros(floor(frame_length/2),1)]; 0078 0079 % get indexes 0080 index = spdiags(repmat((1:length(x2))',[1 frame_length]),0:-1:-length(x2)+frame_length); 0081 0082 window = repmat(window,[1 length(x)]); 0083 0084 % do calculations 0085 switch lower(mode) 0086 case 'rms' 0087 y = sqrt(mean((window.*x2(index)).^2)); 0088 case 'median' 0089 y = median((window.*x2(index))); 0090 case 'mean' 0091 y = mean((window.*x2(index))); 0092 otherwise 0093 error('Unknown ''mode'' specified') 0094 end 0095 0096 % transpose if necessary 0097 if size(y,1)~=size(x,1) 0098 y = y'; 0099 end


|
Perl Weekly
Issue #191 - 2015-03-23 - Hackathon after Hackathon
latest | archive | by Gabor Szabo
|
|
Hi,
There are two Hackathons going to take place in close proximity in time, but quite far away. One in Berlin and the other one in New York. The former is the traditional annual QA Hackathon with a number of people flying in from various other places of the globe, therefore they still need help with some funding. I am happy to tell you that thanks to the growing number of advertisers in the Perl Weekly, and thanks to the people who contribute to the Perl Weekly via Gratipay I could use some of that money to sponsor the QA Hackathon! (The still need some more.)
In any case, enjoy the articles!
|
|
|
|
Sponsors
|
InsideSales.com - Pass our "Perl Challenge" & Win a $100 Amazon Gift Card
Our yummy Perl codebase handles millions of emails in production each week! We're growing like crazy, doubling in revenue and size annually. We want you to join our team in Utah. Pass our "Perl Challenge" to win a $100 Amazon gift card and an interview. Hires will receive a sizable signing bonus.
|
|
|
|
Announcements
|
|
|
Articles
|
Accelerating Perl
by Timm Murray (TMURRAY)
With the Raspberry Pi and other SoC (System on a Chip) devices it is time for Perl to start using accelometers. There aren't a lot of CPAN modules doing this, but Device::LSM303DLHC handling the LSM303DLHC chip can provide access to the readings. Let's see what can you do with it?
|
|
|
|
|
How you average numbers matters
by Sinan Unur (NANIS)
We all know (or should know) that computations in a computer are not exact, but when Sinan puts it in front of us it is still very disturbing.
|
|
|
Testing
|
Test::More in serious need of review, be afraid!
by Chad Granum (EXODIST)
Exodist is planning to release a new version of Test::More to CPAN. If that version breaks some a CPAN module, that CPAN module will become uninstallable. (Well, sort of.). Not only that. If the new version starts to report success when something failed then your code might be full of bugs while everything looks fine. In case you want to neither of this will happen, you can put some energy into looking at the changes and testing the new version.
|
|
|
The Perl QA Hackathon is still looking for Sponsors
by Olaf Alders (OALDERS)
The QA Hackathon is an excellent event and dispite its name it is not only about Quality Assurnce. It became a more generice event when some of the people maintaining the core infrastructure needed for the Perl world get together for some much needed face-to-face conversation. I had the luck participating in two of such events, and now I had the privilage to even provide some funds to run the event. If you, or your company relies on Perl, this is a very good place to ensure the continous improvement of the whole ecosystem around Perl.
|
|
|
Dancer + Jasmine
by Yanick Champoux (YANICK)
Absolutely awesome! Yanick had to test his Angular.js based code. So what did he do? He wrote a plugin for Perl Dancer. Jasmine is a behavior-driven development framework for testing JavaScript code. The new Dancer::Plugin::Test::Jasmine allows you to integrate the tests written in Jasmin with the test you write for your Perl-based back-end.
|
|
|
|
|
Code
|
Loading module conditionally (and other options)
by Steven Haryanto (SHARYANTO)
'use MyModule if $cond;' won't do what you might expect. So what can you do? (... and what < href="http://www.reddit.com/r/perl/comments/2zojah/loading_modules_conditionally_and_other_options/">Redditors think about this.)
|
|
Twitter Mass Unfollower in Perl
Sometimes automated tests can cause you to add many unwanted twitter accounts following many other people. This simple Perl script helps you stop following everyone.
|
|
Web
|
|
|
CPAN
|
A Year of CPAN Uploads
by Barbie (BARBIE)
There are some really crazy people out there. For example Barbie, who has been uploading modules to CPAN every day for more than a year now.  The Perl Weekly maintains a list of Perl events. Enjoy yourself!
|
You know, you could get the Perl Weekly right in your mailbox. Every Week. Free of charge!
|


I believe learning takes place in a social constructivist framework which implies my role as an educator is to empower and motivate students to build their own understanding of a subject. My main ideas behind this were formed from reading [1].
Further to this, I believe it is important to be able to offer a rationale for all my pedagogic practice. Using a particular approach because of a traditional context is not a sufficient and valid reason. This does not preclude my use of traditional methods. An excellent text regarding evidence based practice in learning is [2] (a book I would recommend to all students).
Based on a wide range of evidence (for example [3, 4]) I aim to create an active learning framework in my courses. My favored definition of active learning is from [4]:
"Active learning is generally defined as any instructional method that engages students in the learning process. In short active learning requires students to do meaningful learning activities and think about what they are doing."
My classes are a flipped learning environment [5] making use of web technologies for the transfer of content ensuring class meetings can be used appropriately for:
Whilst these approaches are not traditional they constitute evidence based practice [2, 3, 4, 6] and I hope that one day they will in fact be traditional.
There might be some doubt as to the effectiveness of active learning approaches: for example [7] is a paper where no specific effectiveness of active learning was found in a particular class. Inciting curiosity and engagement are still known to be beneficial to students' learning. Indeed in [8] the greatest predictors of academic performance are identified not as general intelligence [9], but personality factors such as conscientiousness and openness. Thus my main role and indeed responsibility is to help students gain an interest and enthusiasm for the subject. This is something I continuously strive to get better at.
Furthermore, I am conscious that some students would feel excluded by my approaches. Indeed: a lifetime of education in passive learning environments is not something that will be immediately broken, thus:
I aim to continuously reflect on my practice, for example publishing peer reviewed articles such as [10]. Importantly, as in all evidence based practice, when the evidence indicates that I should change my practice: I will.
Mail<EMAIL_ADDRESS>Mastodon: @vinceknight@fosstodon Photo: lo hi CV: tex
Source code: @drvinceknight Powered by: Python Mathjax Github pages Skeleton css


Jurisdiction
The East Coast and Midwest (USA)
The West Coast and South (USA)
Australia
Austria
Belgium
Chile
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Latvia
Lithuania
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovakia
Slovenia
Spain
South Korea
Sweden
Switzerland
Turkey
United Kingdom


{% load i18n %} {% url 'vms_vms' as url_vms %} {% url 'acc_account_data' as url_account_data %} {% url 'hlp_help' as url_help %} {% blocktrans %}
System documentation can be found at project's site.
In case you encounter any troubles while using the system, please visit the Help section.
{% endblocktrans %}


Providing resources and analysis to understand how COVID-19 affects work, labor and employment.
– Rob Manfred, Commissioner of Major League Baseball
Learn more about research from Eli Friedman, associate professor and chair of ILR’s Department of International and Comparative Labor.
The Martin P. Catherwood Library is the most comprehensive resource on labor and employment in North America, offering expert research support through reference services, instruction, online guides and access to premier collections.


Dear User,
The bug reported by you has been fixed.
The incident ticket number generated was {{ticket}}.
Please check whether you are still facing the same issue.
If you are still facing the same issue, please report the bug and please drop a detailed email regarding it.
Please continue to report bugs so that we can make your user experience better.
Thank You.
Regards,
Team SRMS


The \vline command will draw a vertical line extending the full height and depth of its row. An \hfill command can be used to move the line to the edge of the column. It can also be used in an @-expression.
See also: array,
tabular
Return to LaTeX Table of Contents


Tech Reflection Pt 2
What is grid based design
Grid based design is a website design method, you devide the screen into 12 columns and use them as a guide to know where to place your content
What is all the hype about responsive webpages
Today we have so many different devices that have web browsing capability and they are all diffrent sizes and have diffrent display requirements, making your web page "responsive" will allow it to be displayed well on diffrent devices
Semantic Structure
this is using the html tags to organise the information on your page according to their prominence. For example you would use the h1 tag for the title of your webpage and then down to h2 for the heading of the first article and the h3 for any headings within that article ect.
Other things to note:
using media queries to change css. CSS media queries can change the display according to what size display the end user has. They work by setting a condition, when that condition is met the display is prompted to change ie. then a user loads up a website on there iphone the display is detected as being a certain size lets say 400px, the condion in the media querie says " if the screen is smaller than 500px change the display to look like...." so the end user is seeing a diffrent version of the website than another viewing it on their pc monitor


We invited you to celebrate our wedding
Some Description...Some Description...Some Description...Some Description...Some Description...Some Description...Some Description...Some Description...Some Description...
Some Description...Some Description...Some Description...Some Description...Some Description...Some Description...Some Description...Some Description...Some Description...
Some Text
something
Engagement Details
Marriage Life
Details
Details
Details
Details
Your Blessings And Wishes Are Needed...


The following ratio is plotted:
The line with m = 1 separates a cluster field with
m>1
from a girdle field with
m<1.
Distributions between the isotropic case and clusters lie on
the
ordinate. Distributions between the isotropic case and great circle
ditributions are on the abscissa. Since the degree of preferred
orientation increases with the distance from the zero point, the ratio
is a measure for preferred orientation.
The table on the right side shows the c-values calculated from
the
eigenvalues. The c-value lies between 1 (isotropic) and (max. degree of
preferred orientation.
In the menus "Colour" and "Symbols" the colour and symbol of the
plotted
points can be changed.
The menu "Diagram" contains the same
options as in all other programs.


Form
input
input with form text
We never share your email with other.
input disabled
input with label
username
input file
textarea
select
One
Two
Three
select multiple
One
Two
Three
select small
One
Two
Three
Check
Default checkbox
Checked checkbox
Check inline
Default checkbox
Checked checkbox
Check disabled
Default checkbox
Checked checkbox
Radio
Default radio
Default checked radio
Radio disable
Default radio
Default checked radio


pycopancore.model_components.exploit_social_learning.implementation package¶
Submodules¶
pycopancore.model_components.exploit_social_learning.implementation.culture module¶
Culture process taxon mixing class exploit_social_learning.
Bases:
pycopancore.model_components.exploit_social_learning.interface.Culture
Culture process taxon mixin for exploit_social_learning.
Change strategy of agent_i to agent_j’s.
Change the strategy of agent_i to the strategy of agent_j depending on their respective harvest rates and the imitation tendency according to a sigmoidal function.
Parameters: - agent_i (Agent (Individual or SocialSystem)) – Agent i whose strategy is to be changed to agent j’s strategy
- agent_j (Agent (Individual or SocialSystem)) – Agent j whose strategy is imitated
Check if the model has run into a consensus state.
The model is in a consensus state if in each connected component all agents use the same strategy. In this case, there will be no more change of strategies since the agents are only connected to agents with the same strategy.
Returns: consensus – True if model is into consensus state, otherwise False Return type: bool
Return the agent with the closest waiting time.
Choose from all agents the one with the smallest update_time.
Reconnect agent_i from agent_j and connect it to k.
Disconnect agent_i from agent_j and connect agent_i to a randomly chosen agent_k with the same strategy, agent_i.strategy == agent_k.strategy.
Parameters: - agent_i (Agent (Individual or SocialSystem)) –
- agent_j (Agent (Individual or SocialSystem)) –
Set next time step when agent is to be called again.
Set the attribute update_time of agent to old_update_time + new_update_time, where new_update_time is again drawn from an exponential distribution.
Parameters: agent (Agent (Individual or SocialSystem)) – The agent whose new update_time should be drawn and set.
Execute the social update.
Parameters: t (float) – time
Return the next time step is to be called.
This function is used to get to know when the step function is to be called. :param t: time :type t: float
pycopancore.model_components.exploit_social_learning.implementation.individual module¶
Individual entity type of the component exploit_social_learning.
Bases:
pycopancore.model_components.exploit_social_learning.interface.Individual
Define properties of exploit_social_learning individual.
Make objects sortable.
Deactivate an individual.
Compute a random harvest rate of individual.
This method should be overwritten with a method of the class simple_extraction.individual.
Reactivate an individual.
pycopancore.model_components.exploit_social_learning.implementation.world module¶
The exploit_social_learning.world class.
In this module the exploit_social_learning World mixing class inherits from World_ in that basic variables and parameters are defined.
Bases:
pycopancore.model_components.exploit_social_learning.interface.World
,pycopancore.model_components.abstract.world.World
Define properties of exploit_social_learning.world.
Inherits from I.World as the interface with all necessary variables and parameters.
Return a list of the neighbors of agent.
Parameters: Agent (agent) – Returns: neighbors Return type: A list of all neighbors of agent
Return a list of all agents that are not connected to agent.
Parameters: Agent (agent) – Returns: non_neighbors Return type: A list of all agents that are no neighbors of agent
Return a random neighbor of agent.
Parameters: Agent (agent) – Returns: Return type: neighbor Agent
Return True if agent has a neighbor and False if not.
Parameters: Agent (agent) – Returns: Return type: boolean
Module contents¶
Model component implementation subpackage exploit_social_learning.


Products
A Miracle in the Making. Recognize your employees' achievements and excellence with a Personalized Award Program. From modern crystal awards to classic trophies, plaques, medals and ribbons. Unique Corporate Executive gifts for all occasions. Rapid custom engraving of logos, signatures, and wording. Individualized nameplates, clocks, pen sets, letter openers and multi-plate plaques. Wedding gifts receive Free tray engraving of your wedding invitation when you mention this site. Near the University of Akron in Ohio. Go for the Gold! Tell your favorite country club about our golf treasures.
Trophies
Crystal Awards
Plaques
Miracle Custom Awards & Gifts
294 East Exchange Street
Akron, OH 44304
Phone:<PHONE_NUMBER>
Fax:<PHONE_NUMBER>
E-mail<EMAIL_ADDRESS>Most products ship in 10 working days by either U.S. mail, UPS, or Express Delivery. Standard shipping charges and any applicable tax apply.


INSTRUCTIONS
- Hover the mouse to move the left paddle.
- Position the paddle properly to hit the ball.
- Increase or decrease the speed of the ball based on the part of the paddle that hits the ball.
- First to reach 3 points wins!
- Left click to restart the game after the game gets over.