1. Download and install camCoder installer from http://camstudio.org/
2. Open camCoder.
3. Set “Video Option” and “Cursor Option”
4. Start recording by press button “record”
5. Stop recording by press button “stop”
6. Save the recording and play using media player. The file extension is .avi but we can convert to another extension.

CamStudio tutorial on youtube:

# Jena Rules

@prefix caIN: <file:ontology/indoorNav.owl#> .

@prefix temporal: <file:ontology/temporal.owl#> .

@include <OWL>.

SQWRL (Semantic Query-Enhanced Web Rule Language; pronounced squirrel) is a SWRL-based query language that can be used to query OWL ontologies. SQWRL provides SQL-like operations to format knowledge retrieved from an OWL ontology. SQWRL does not alter SWRL’s semantics and uses the standard SWRL presentation syntax supported by the SWRLTab.

Below is the example of SWRL syntax to infer visitor’s location.

representedBy(?visitor ?sensor) ^

isMovingTo(?sensor,?location)

–> isLocatedIn(?visitor, ?location)

‘?visitor’, ‘?sensor’ and ‘?location’ are the name of variable. Each variable in SWRL is beginned with question mark (‘?’). ‘representedBy’, ‘isMovingto’ and ‘isLocatedIn’ are the name of property. ”^” represent AND relationship. ”–>” is read as THEN. Above rule is human readable syntax. From above rule we can say if a visitor representedBy a sensor and a sensor is moving to a location then we can infer new knowledge a visitor is located in location.

Following syntax is XML Concrete Syntax for SWRL. The XML Concrete Syntax is a combination of the OWL Web Ontology Language XML Presentation Syntax with the RuleML XML syntax.

<ruleml:imp>

<ruleml:_rlab ruleml:href=”#userLoc”/>

<ruleml:_body>

<swrlx:individualPropertyAtom swrlx:property=”representedBy”>

<ruleml:var>visitor</ruleml:var>

<ruleml:var>sensor</ruleml:var>

</swrlx:individualPropertyAtom>

<swrlx:individualPropertyAtom swrlx:property=”isMovingTo”>

<ruleml:var>sensor</ruleml:var>

<ruleml:var>location</ruleml:var>

</swrlx:individualPropertyAtom>

</ruleml:_body>

<ruleml:_head>

<swrlx:individualPropertyAtom swrlx:property=”isLocatedIn”>

<ruleml:var>visitor</ruleml:var>

<ruleml:var>location</ruleml:var>

</swrlx:individualPropertyAtom>

</ruleml:_head>

</ruleml:imp>

The Ontology root element of the OWL XML Presentation Syntax is extended to include “imp” (implication rule) and “var” (variable declaration) axioms as found under the rulebase root of RuleML. Variable (var) axioms are statements about variables, indicating that the given string is to be used as a variable. A var axiom simply defines the existence of a variable. This is taken from the RuleML namespace.From this XML COncrete Syntax rule we can see there are 3 variables: visitor, sensor and location.

Rule axioms (imp elements) are similar to SubClassOf axioms. They are taken from the RuleML namespace. A rule axiom can be read as a logical implication between the antecedent (_body) and consequent (_head). Both _body and _head are lists of atoms and are read as the conjunction of the component atoms. Atoms can be formed from unary predicates (classes), binary predicates (properties), equalities or inequalities.

An alternative formulation for the userLoc rule given in this example would be to assert that if visitor representedBy sensor and sensor isMovingTo location, then visitor isLocatedIn location.

The next step is to create an instance of QueryExecution, a class that represents a single execution of a query. To obtain a QueryExecution, call QueryExecutionFactory.create(query, model), passing in the Query to execute and the Model to run it against. Because the data for the query is provided programmatically, the query does not need a FROM clause.

There are several different execute methods on QueryExecution, each performing a different type of query (see the sidebar entitled “Other types of SPARQL queries” for more information). For a simple SELECT query, call execSelect(), which returns a ResultSet. The ResultSet allows you to iterate over each QuerySolution returned by the query, providing access to each bound variable’s value. Alternatively, ResultSetFormatter can be used to output query results in various formats.

Example :

// Open the bloggers RDF graph from the filesystem
InputStream in = new FileInputStream(new File(“bloggers.rdf”));

// Create an empty in-memory model and populate it from the graph
Model model = ModelFactory.createMemModelMaker().createModel();
model.read(in,null); // null base URI, since model URIs are absolute
in.close();

// Create a new query
String queryString =
“PREFIX foaf: <http://xmlns.com/foaf/0.1/> ” +
“SELECT ?url ” +
“WHERE {” +
“      ?contributor foaf:name \”Jon Foobar\” . ” +
“      ?contributor foaf:weblog ?url . ” +
“      }”;

Query query = QueryFactory.create(queryString);

// Execute the query and obtain results
QueryExecution qe = QueryExecutionFactory.create(query, model);
ResultSet results = qe.execSelect();

// Output query results
ResultSetFormatter.out(System.out, results, query);

// Important – free up resources used running the query
qe.close();

Source : http://www-128.ibm.com/developerworks/library/j-sparql/

In this talk, Professor Harold Boley also introduces about POSL selectors, unification, webizing, typing, and implementation. Webizing takes up and extends the use of URIs in N3. From POSL website, i find information that for humans, the POSL language is faster to write and easier to read than any XML syntax. However, since a parser and a generator map the POSL syntax to Object-Oriented RuleML and back, the machine advantages of XML can be preserved.

 Thanks to Prof. Boley for your great talk

Resources :

1. Profesor Harold Boley Talk today
2. POSL description

Event(?e)  ∧
hasStartTime(?e, ?t1)  ∧
hasEndTime(?e, ?t2)  ∧
temporal:duration(?d, ?t1, ?t2, temporal:Minutes)
  → hasDuration(?e, ?d)

?d is return value in a minute .

1. http://www.semanticfocus.com/blog/entry/title/introduction-to-the-semantic-web-vision-and-technologies-part-1-overview/ : an overview of semantic web
2. http://www.semanticfocus.com/blog/entry/title/introduction-to-semantic-web-vision-and-technologies-part-4-protege-101-screencast/ : Tutorial to create ontology in Protege using video presentation (part 1)
3. http://www.semanticfocus.com/blog/entry/title/introduction-to-semantic-web-vision-and-technologies-part-5-building-owl-ontologies-using-protege-4-screencast/ : Tutorial to create ontology in Protege using video presentation (part 2)

And for the complete information just visit http://www.semanticfocus.com

I really got that this tutorial is usefull a lot, even for beginner.

I can create my first agent using jade. I have install eclipse 3.2 and jdk 1.4. and prepare jade before running it. This step by step using jade in eclipse:

• Open eclipse 3.2
• Create new project, i create project with yuhana_agent as name
• Create new package, i give it name : indoorNav
• Import all jade library:
  • right click on project name, choose property
  • choose libraries tab and press button “Add External JARS”, and select all jade libraries and click OK
  • choose Order and Export Tab, make sure all libraries are checked.
  • click OK
• Create new class give HelloWorld.class for a name and write the code like this code :

                  import jade.core.Agent;

                  public class HelloWorld extends Agent{

                                  public void setup(){    

                                         System.out.println(“Hello Yuhana, my name is : “ +getAID().getName());

                                   }

                        }

• Open Run Dialog by right click on project, choose Run As and choose Open Run Dialog. Give name MyFirstAgent for name of Run Configuration. In Main Tab, choose project name, write jade.Boot as main class and don’t forget to check checkbox include system libraries when searching for main class.  See figure 1.

Figure 1. Main Class Setting

• For next step choose (x)=Argument Tab, write -gui <main_class_name> <nickname>:<package_name>.<class_name> in program argument Tab. Example: i give yuhana as nickname, indoorNav as package and HelloWorld as class, so write -gui jade.Boot yuhana:indoorNav.HelloWorld on program argument as shown in figure 2.

Figure 2. Argument Setting

• Run the program, see the result in figure 3 and RMA agent dialog appear as shown in figure 4. If program succes our new agent appear in this dialog. There are 3 default agent (RMA, ams and da agent). See agent yuhana appear in that figure.

Figure 3. Result of the program in console

Figure 4. Agent Dialog

How to do programming in Jade, please visit this

another related resources : http://agents.cs.bath.ac.uk/cm30174/jade/ and http://mia.ece.uic.edu/~papers/MediaBot/CLOntoSupport.pdf