This section provides details for each class and property defined by PPROC.
4.1. Classes
Accepted tenderc
back to ToC or Class ToC
IRI: http://contsem.unizar.es/def/sector-publico/pproc#AcceptedTender
- has super-classes
-
Tender
c
- is disjoint with
-
Excluded tender
c
IRI: http://www.w3.org/2004/02/skos/core#Concept
- is defined by
-
http://www.w3.org/2004/02/skos/core#
- is in range of
-
Additional object of contract
op,Information kind
op, Main object of contract
op, Object
op, Procedure type
op, Urgency type
op
- has members
-
Administrative information
ni, Competitive dialogue
ni, Emergency
ni, Express
ni, Minor
ni, Negotiated
ni, Negotiated with publicity
ni, Negotiated without publicity
ni, Regular
ni, Regular open
ni, Restricted
ni, Simple open
ni, Technical information
ni
Contract procedurec
back to ToC or Class ToC
IRI: http://contsem.unizar.es/def/sector-publico/pproc#ContractProcedureSpecifications
- is in domain of
-
Assumption protecting the chosen procedure type
dp, Briefing
op, Contracting body agreement
op, Contract additional obligations
op, Contract bodies
op, Contract activities
op, Early tramitation
dp, Electronic auction
op, Maximum number of invitations
dp, Minimum number of invitations
dp, Notice
op, Procedure type
op, Start date of the tender dossier
dp, Tender admission meeting
op, Tender information provider
op, Tender submission location
op, Tender submission mode
dp, Time-limit for submission of tenders or requests to participate
dp, Urgency type
op
- is in range of
-
Contract procedure specifications
op
Contracting body agreementc
back to ToC or Class ToC
IRI: http://contsem.unizar.es/def/sector-publico/pproc#ContractingBodyAgreement
- is in domain of
-
Resolution document reference
op
- is in range of
-
Award agreement
op, Contracting body agreement
op
Dynamic purchasing system conclusion contractc
back to ToC or Class ToC
IRI: http://contsem.unizar.es/def/sector-publico/pproc#DynamicPurchasingSystemConclusionContract
- has super-classes
-
Conclusion contract
c
Dynamic purchasing system derivative contractc
back to ToC or Class ToC
IRI: http://contsem.unizar.es/def/sector-publico/pproc#DynamicPurchasingSystemDerivativeContract
- has super-classes
-
Derivative contract
c
Excluded tenderc
back to ToC or Class ToC
IRI: http://contsem.unizar.es/def/sector-publico/pproc#ExcludedTender
- has super-classes
-
Tender
c
- is disjoint with
-
Accepted tender
c
Expert committeec
back to ToC or Class ToC
IRI: http://contsem.unizar.es/def/sector-publico/pproc#ExpertCommittee
- has super-classes
-
Tender committee
c
Extendable contractc
back to ToC or Class ToC
IRI: http://contsem.unizar.es/def/sector-publico/pproc#ExtendableContract
- has super-classes
-
Public contract
c
Framework conclusion contractc
back to ToC or Class ToC
IRI: http://contsem.unizar.es/def/sector-publico/pproc#FrameworkConclusionContract
- has super-classes
-
Conclusion contract
c
Framework derivative contractc
back to ToC or Class ToC
IRI: http://contsem.unizar.es/def/sector-publico/pproc#FrameworkDerivativeContract
- has super-classes
-
Derivative contract
c
Harmonized contractc
back to ToC or Class ToC
IRI: http://contsem.unizar.es/def/sector-publico/pproc#HarmonizedContract
- has super-classes
-
Public contract
c
Legal remedyc
back to ToC or Class ToC
IRI: http://contsem.unizar.es/def/sector-publico/pproc#LegalRemedy
- has super-classes
-
Remedy
c
Multiannual contractc
back to ToC or Class ToC
IRI: http://contsem.unizar.es/def/sector-publico/pproc#MultiannualContract
- has super-classes
-
Public contract
c
Objective award criterionc
back to ToC or Class ToC
IRI: http://contsem.unizar.es/def/sector-publico/pproc#ObjectiveAwardCriterion
- has super-classes
-
Award criterion
c
Ordinary administrative remedyc
back to ToC or Class ToC
IRI: http://contsem.unizar.es/def/sector-publico/pproc#OrdinaryAdministrativeRemedy
- has super-classes
-
Remedy
c
Postal addressc
back to ToC or Class ToC
IRI: http://schema.org/PostalAddress
- is defined by
-
http://schema.org/
Public contractc
back to ToC or Class ToC
IRI: http://contsem.unizar.es/def/sector-publico/pproc#Contract
- has super-classes
-
Contract
c
- has sub-classes
-
Conclusion contract
c, Contract with lots
c, Contract without lots
c, Derivative contract
c, Extendable contract
c, Harmonized contract
c, Lot
c, Mixed contract
c, Multiannual contract
c, Private contract
c, Public services management contract
c, Public works concession contract
c, Public-private partnership contract
c, Services contract
c, Special administrative contract
c, Supplies contract
c, Works contract
c, Precomercial procurement
c
- is in domain of
-
Actual duration
dp, Additional document reference
op, Complementary contract
op, Contract modification
op, Contract or procedure extinction
op, Contract procedure specifications
op, Contracting body
op, Delegating authority
op, Framework agreement
op, Legal document reference
op, Number of lots
dp, Managing department
op, Object of the contract
op, Remedy
op, Technical document reference
op, Tender briefing
op, Tender requirements
op, Tenderers requirements
op
- is in range of
-
Complementary contract
op
Public services management contractc
back to ToC or Class ToC
IRI: http://contsem.unizar.es/def/sector-publico/pproc#PublicServicesManagementContract
- has super-classes
-
Public contract
c
- has sub-classes
-
Agreement contract
c, Concession contract
c, Mixed capital company contract
c, Shared result agreement contract
c
- is disjoint with
-
Mixed contract
c, Private contract
c, Public-private partnership contract
c, Public works concession contract
c, Services contract
c, Special administrative contract
c, Supplies contract
c, Works contract
c, Precomercial procurement
c
Special administrative remedyc
back to ToC or Class ToC
IRI: http://contsem.unizar.es/def/sector-publico/pproc#SpecialAdministrativeRemedy
- has super-classes
-
Remedy
c
Subjective award criterionc
back to ToC or Class ToC
IRI: http://contsem.unizar.es/def/sector-publico/pproc#SubjectiveAwardCriterion
- has super-classes
-
Award criterion
c
Supplies contractc
back to ToC or Class ToC
IRI: http://contsem.unizar.es/def/sector-publico/pproc#SuppliesContract
- has super-classes
-
Public contract
c
- has sub-classes
-
Buy contract
c, Lease contract
c, Rent contract
c
- is disjoint with
-
Mixed contract
c, Private contract
c, Public-private partnership contract
c, Public services management contract
c, Public works concession contract
c, Services contract
c, Special administrative contract
c, Works contract
c, Precomercial procurement
c
Technical committeec
back to ToC or Class ToC
IRI: http://contsem.unizar.es/def/sector-publico/pproc#TechnicalCommittee
- has super-classes
-
Tender committee
c
IRI: http://purl.org/procurement/public-contracts#Tender
- is defined by
-
http://purl.org/procurement/public-contracts#
- has sub-classes
-
Accepted tender
c, Awarded tender
c, Excluded tender
c, Formalized tender
c
- is in domain of
-
Award agreement
op, Criterion score
op, Date of award
dp, Formalized date
dp, Item
op, Offered duration
dp, Offered end date
dp, Other award terms
dp
4.2. Object Properties
IRI: http://contsem.unizar.es/def/sector-publico/pproc#additionalDocumentReference
IRI: http://contsem.unizar.es/def/sector-publico/pproc#alternateMember
IRI: http://contsem.unizar.es/def/sector-publico/pproc#awardAgreement
IRI: http://contsem.unizar.es/def/sector-publico/pproc#briefing
IRI: http://contsem.unizar.es/def/sector-publico/pproc#committee
IRI: http://contsem.unizar.es/def/sector-publico/pproc#complementaryContract
Contract additional obligationsop
back to ToC or Object Property ToC
IRI: http://contsem.unizar.es/def/sector-publico/pproc#contractAdditionalObligations
IRI: http://contsem.unizar.es/def/sector-publico/pproc#contractBodies
IRI: http://contsem.unizar.es/def/sector-publico/pproc#budgetPrice
IRI: http://contsem.unizar.es/def/sector-publico/pproc#contractEconomicConditions
IRI: http://contsem.unizar.es/def/sector-publico/pproc#contractExecutionConditions
IRI: http://contsem.unizar.es/def/sector-publico/pproc#contractModification
Contract modification conditionsop
back to ToC or Object Property ToC
IRI: http://contsem.unizar.es/def/sector-publico/pproc#contractModificationConditions
Contract or procedure extinctionop
back to ToC or Object Property ToC
IRI: http://contsem.unizar.es/def/sector-publico/pproc#contractOrProcedureExtinction
Contract procedure specificationsop
back to ToC or Object Property ToC
IRI: http://contsem.unizar.es/def/sector-publico/pproc#contractProcedureSpecifications
IRI: http://contsem.unizar.es/def/sector-publico/pproc#contractActivities
IRI: http://contsem.unizar.es/def/sector-publico/pproc#contractResolution
IRI: http://contsem.unizar.es/def/sector-publico/pproc#contractTemporalConditions
IRI: http://contsem.unizar.es/def/sector-publico/pproc#contractingBody
IRI: http://contsem.unizar.es/def/sector-publico/pproc#contractingBodyAgreement
IRI: http://contsem.unizar.es/def/sector-publico/pproc#criterion
IRI: http://contsem.unizar.es/def/sector-publico/pproc#criterionScore
IRI: http://contsem.unizar.es/def/sector-publico/pproc#delegatingAuthority
IRI: http://contsem.unizar.es/def/sector-publico/pproc#documentReference
IRI: http://contsem.unizar.es/def/sector-publico/pproc#electronicAuction
IRI: http://contsem.unizar.es/def/sector-publico/pproc#electronicAuctionPhase
IRI: http://contsem.unizar.es/def/sector-publico/pproc#electronicAuctionWeb
IRI: http://contsem.unizar.es/def/sector-publico/pproc#feePrice
IRI: http://contsem.unizar.es/def/sector-publico/pproc#frameworkAgreement
Framework agreement derivative contractop
back to ToC or Object Property ToC
IRI: http://contsem.unizar.es/def/sector-publico/pproc#frameworkAgreementDerivativeContract
IRI: http://contsem.unizar.es/def/sector-publico/pproc#fullMember
IRI: http://contsem.unizar.es/def/sector-publico/pproc#legalDocumentReference
IRI: http://contsem.unizar.es/def/sector-publico/pproc#lot
IRI: http://contsem.unizar.es/def/sector-publico/pproc#mainObject
- Backward compatible with:
-
http://purl.org/procurement/public-contracts#mainObject (visualise it with LODE)
IRI: http://contsem.unizar.es/def/sector-publico/pproc#managingDepartment
IRI: http://contsem.unizar.es/def/sector-publico/pproc#minutesDocumentReference
IRI: http://contsem.unizar.es/def/sector-publico/pproc#notice
IRI: http://contsem.unizar.es/def/sector-publico/pproc#noticeWeb
has characteristics: functional
- has domain
-
Notice
c
- has range
-
Document
c
IRI: http://contsem.unizar.es/def/sector-publico/pproc#contractObject
IRI: http://contsem.unizar.es/def/sector-publico/pproc#price
IRI: http://contsem.unizar.es/def/sector-publico/pproc#procedureResignation
IRI: http://contsem.unizar.es/def/sector-publico/pproc#procedureType
IRI: http://contsem.unizar.es/def/sector-publico/pproc#procedureVoid
IRI: http://contsem.unizar.es/def/sector-publico/pproc#procedureWaive
IRI: http://contsem.unizar.es/def/sector-publico/pproc#remedy
IRI: http://contsem.unizar.es/def/sector-publico/pproc#resolutionDocumentReference
IRI: http://contsem.unizar.es/def/sector-publico/pproc#technicalDocumentReference
IRI: http://contsem.unizar.es/def/sector-publico/pproc#tenderAdmissionMeeting
IRI: http://contsem.unizar.es/def/sector-publico/pproc#tenderBriefing
IRI: http://contsem.unizar.es/def/sector-publico/pproc#tenderMeeting
IRI: http://contsem.unizar.es/def/sector-publico/pproc#tenderRequirements
IRI: http://contsem.unizar.es/def/sector-publico/pproc#tenderSubmissionLocation
IRI: http://contsem.unizar.es/def/sector-publico/pproc#tenderersRequirements
IRI: http://contsem.unizar.es/def/sector-publico/pproc#urgencyType
4.3. Data Properties
IRI: http://contsem.unizar.es/def/sector-publico/pproc#actualDuration
IRI: http://contsem.unizar.es/def/sector-publico/pproc#advertisementAmount
Assumption protecting the chosen procedure typedp
back to ToC or Data Property ToC
IRI: http://contsem.unizar.es/def/sector-publico/pproc#assumptionProtectingProcedureType
Compulsory means for executiondp
back to ToC or Data Property ToC
IRI: http://contsem.unizar.es/def/sector-publico/pproc#compulsoryMeansForExecution
IRI: http://contsem.unizar.es/def/sector-publico/pproc#constructionSubsidies
IRI: http://contsem.unizar.es/def/sector-publico/pproc#criterionEvaluationMode
Criterion maximum and minimum scoredp
back to ToC or Data Property ToC
IRI: http://contsem.unizar.es/def/sector-publico/pproc#criterionMaxAndMinScores
IRI: http://purl.org/dc/terms/date
- is defined by
-
http://purl.org/dc/terms/
- has sub-properties
-
Date of award
dp, Date of notice publication
dp, Estimated end date
dp, Formalized date
dp, Lodged remedy date
dp, Notice sent date
dp, Offered end date
dp, Remedy resolution date
dp, Start date of the tender dossier
dp, Tender committee appointment date
dp, Time-limit for submission of tenders or requests to participate
dp, Actual end date
dp
Date of notice publicationdp
back to ToC or Data Property ToC
IRI: http://contsem.unizar.es/def/sector-publico/pproc#noticeDate
has characteristics: functional
- has super-properties
-
Date
dp
- has domain
-
Notice
c
- has range
-
xsd:date
IRI: http://contsem.unizar.es/def/sector-publico/pproc#duration
IRI: http://contsem.unizar.es/def/sector-publico/pproc#durationChange
IRI: http://contsem.unizar.es/def/sector-publico/pproc#earlyTramitation
IRI: http://contsem.unizar.es/def/sector-publico/pproc#estimatedDuration
IRI: http://contsem.unizar.es/def/sector-publico/pproc#estimatedEndDate
IRI: http://contsem.unizar.es/def/sector-publico/pproc#endMode
IRI: http://contsem.unizar.es/def/sector-publico/pproc#executionRequeriments
Expected cause modificationdp
back to ToC or Data Property ToC
IRI: http://contsem.unizar.es/def/sector-publico/pproc#expectedCauseModification
IRI: http://contsem.unizar.es/def/sector-publico/pproc#extinctionCause
IRI: http://contsem.unizar.es/def/sector-publico/pproc#finalFinancialGuarantee
Final financial guarantee durationdp
back to ToC or Data Property ToC
IRI: http://contsem.unizar.es/def/sector-publico/pproc#finalFinancialGuaranteeDuration
IRI: http://contsem.unizar.es/def/sector-publico/pproc#isNegotiable
has characteristics: functional
- has domain
-
Award criterion
c
- has range
-
xsd:boolean
IRI: http://contsem.unizar.es/def/sector-publico/pproc#lodgedRemedyDate
has characteristics: functional
- has super-properties
-
Date
dp
- has domain
-
Remedy
c
- has range
-
xsd:date
IRI: http://contsem.unizar.es/def/sector-publico/pproc#numberOfLots
has characteristics: functional
- has domain
-
Public contract
c
- has range
-
xsd:nonNegativeInteger
IRI: http://contsem.unizar.es/def/sector-publico/pproc#maxBudgetChange
Maximum final price changedp
back to ToC or Data Property ToC
IRI: http://contsem.unizar.es/def/sector-publico/pproc#maxFinalPriceChange
Maximum number of invitationsdp
back to ToC or Data Property ToC
IRI: http://contsem.unizar.es/def/sector-publico/pproc#maxInvitations
Maximum number of operatorsdp
back to ToC or Data Property ToC
IRI: http://contsem.unizar.es/def/sector-publico/pproc#maxNumberOfOperators
IRI: http://contsem.unizar.es/def/sector-publico/pproc#maxSubcontracting
Minimum number of invitationsdp
back to ToC or Data Property ToC
IRI: http://contsem.unizar.es/def/sector-publico/pproc#minInvitations
Minimum number of operatorsdp
back to ToC or Data Property ToC
IRI: http://contsem.unizar.es/def/sector-publico/pproc#minNumberOfOperators
IRI: http://contsem.unizar.es/def/sector-publico/pproc#minSubcontracting
IRI: http://contsem.unizar.es/def/sector-publico/pproc#modificationReason
IRI: http://contsem.unizar.es/def/sector-publico/pproc#modificationScope
IRI: http://contsem.unizar.es/def/sector-publico/pproc#noticeSentDate
has characteristics: functional
- has super-properties
-
Date
dp
- has domain
-
Notice
c
- has range
-
xsd:date
IRI: http://contsem.unizar.es/def/sector-publico/pproc#noticeSite
- has domain
-
Notice
c
- has range
-
xsd:string
IRI: http://contsem.unizar.es/def/sector-publico/pproc#offeredDuration
has characteristics: functional
- has super-properties
-
Duration
dp
- has domain
-
Tender
c
IRI: http://contsem.unizar.es/def/sector-publico/pproc#offeredEndDate
has characteristics: functional
- has super-properties
-
Date
dp
- has domain
-
Tender
c
- has range
-
xsd:date
IRI: http://contsem.unizar.es/def/sector-publico/pproc#otherAbilityRequisites
IRI: http://contsem.unizar.es/def/sector-publico/pproc#otherAwardTerms
- has domain
-
Tender
c
- has range
-
xsd:string
IRI: http://contsem.unizar.es/def/sector-publico/pproc#otherGuarantee
IRI: http://schema.org/postalAddress
- is defined by
-
http://schema.org/
IRI: http://contsem.unizar.es/def/sector-publico/pproc#pricePercentageChange
IRI: http://contsem.unizar.es/def/sector-publico/pproc#priceReviewAllowable
IRI: http://contsem.unizar.es/def/sector-publico/pproc#priceReviewIndex
Prorogation number expecteddp
back to ToC or Data Property ToC
IRI: http://contsem.unizar.es/def/sector-publico/pproc#prorogationsExpected
Provisional financial guaranteedp
back to ToC or Data Property ToC
IRI: http://contsem.unizar.es/def/sector-publico/pproc#provisionalFinancialGuarantee
IRI: http://contsem.unizar.es/def/sector-publico/pproc#recurrentRemedy
- has domain
-
Remedy
c
- has range
-
xsd:string
IRI: http://contsem.unizar.es/def/sector-publico/pproc#remedyInterposedTo
- has domain
-
Remedy
c
- has range
-
xsd:string
IRI: http://contsem.unizar.es/def/sector-publico/pproc#remedyReason
- has domain
-
Remedy
c
- has range
-
xsd:string
IRI: http://contsem.unizar.es/def/sector-publico/pproc#remedyResolution
- has domain
-
Remedy
c
- has range
-
xsd:string
IRI: http://contsem.unizar.es/def/sector-publico/pproc#remedyResolutionDate
has characteristics: functional
- has super-properties
-
Date
dp
- has domain
-
Remedy
c
- has range
-
xsd:date
IRI: http://contsem.unizar.es/def/sector-publico/pproc#remedyResult
- has domain
-
Remedy
c
- has range
-
xsd:string
IRI: http://contsem.unizar.es/def/sector-publico/pproc#requiredClassification
Required economic and financial standingdp
back to ToC or Data Property ToC
IRI: http://contsem.unizar.es/def/sector-publico/pproc#requiredEconomicAndFinancialStanding
Required technical and professional abilitydp
back to ToC or Data Property ToC
IRI: http://contsem.unizar.es/def/sector-publico/pproc#requiredTechnicalAndProfessionalAbility
Reserved contract restrictionsdp
back to ToC or Data Property ToC
IRI: http://contsem.unizar.es/def/sector-publico/pproc#reservedContractRestrictions
IRI: http://contsem.unizar.es/def/sector-publico/pproc#score
has characteristics: functional
- has domain
-
Criterion score
c
- has range
-
xsd:float
Start date of the tender dossierdp
back to ToC or Data Property ToC
IRI: http://contsem.unizar.es/def/sector-publico/pproc#tenderDossierStartDate
has characteristics: functional
- has super-properties
-
Date
dp
- has domain
-
Contract procedure
c
- has range
-
xsd:date
Tender committee appointment datedp
back to ToC or Data Property ToC
IRI: http://contsem.unizar.es/def/sector-publico/pproc#tenderCommitteeAppointmentDate
has characteristics: functional
- has super-properties
-
Date
dp
- has domain
-
Tender committee
c
- has range
-
xsd:date
IRI: http://contsem.unizar.es/def/sector-publico/pproc#tenderCommitteeRole
has characteristics: functional
- has domain
-
Committee member
c
- has range
-
xsd:string
IRI: http://contsem.unizar.es/def/sector-publico/pproc#tenderDocumentNeeds
Tender manteinance durationdp
back to ToC or Data Property ToC
IRI: http://contsem.unizar.es/def/sector-publico/pproc#tenderMaintenanceDuration
IRI: http://contsem.unizar.es/def/sector-publico/pproc#tenderPurpose
IRI: http://contsem.unizar.es/def/sector-publico/pproc#tenderSubmissionMode
Tender submission supported languagedp
back to ToC or Data Property ToC
IRI: http://contsem.unizar.es/def/sector-publico/pproc#tenderSubmissionSupportedLanguage
Time-limit for submission of tenders or requests to participatedp
back to ToC or Data Property ToC
IRI: http://contsem.unizar.es/def/sector-publico/pproc#tenderDeadline
has characteristics: functional
- has super-properties
-
Date
dp
- has domain
-
Contract procedure
c
- has range
-
xsd:dateTime
IRI: http://contsem.unizar.es/def/sector-publico/pproc#variantAdmission
has characteristics: functional
- has domain
-
Contract object
c
- has range
-
xsd:boolean
IRI: http://contsem.unizar.es/def/sector-publico/pproc#variantDescription
Class describing the tenders accepted in the procurement public contract.


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ClockWork Script Builder is a .Net library (2.0) to make the building of scripts more readable and structured.
An extendible architecture lets developers add script building blocks (Script Items) for languages such as the ones provided for javascript (Js) and xml (Xs).
Recently I started playing with ExtJs and I ended up needing to build large chunks of javascript from .Net code. I've never found a nice way to construct scripts in C# so this time I decided to write a library to help.
In its simplest form it is a way to join a bunch of strings together so that each is writen on a new line...
Script script = Sb.Script( "line 1;", "line 2;", "line 3;" ); string result = script.Render(); Console.WriteLine(result);
Results in the following output...
line 1; line 2; line 3;
However theres a lot more to it. Scripts don't just understand strings but accept any type of object. In particular, objects based on an IScriptItem are specifically designed to work with scripts and can be writen by anyone to extend scripting abilities.
This example demonstrates the use of some core layout items.
Script script = Sb.Script( Sb.Line("1","2","3","4","5",";"), Sb.Line("1","2","3","4","5",";"), Sb.Indent( Sb.Line("indented ","1","2","3","4","5",";"), Sb.Line("indented ","1","2","3","4","5",";"), Sb.Script( Sb.Line("Some objects"), Sb.Line("Number = ", 47), Sb.Line("True = ", true), Sb.Line("Now is = ", DateTime.Now) ) ) ); string result = script.Render(); Console.WriteLine(result);
Results in the following output...
12345; 12345; indented 12345; indented 12345; Some objects Number = 47 True = True Now is = 23/08/2008 11:23:00 AM
You will have noticed all the Script items are created using "Sb.". To make scripts easier to write and read I have created helper classes for each set of script items. They provide static methods that will create instances of script items for you.
I have currently developed the following sets of script items to help in writing scripts
| Script Set | Description | Helper Class |
| Core | Core Script Items to enable constructing formatted scripts | ClockWork.ScriptBuilder.Sb |
| JavaScript | Items to help construct standard Javascript elements such as Objects, Arrays, Lists, Functions, Calls, Blocks, Statements | ClockWork.ScriptBuilder.JavaScript.Js |
| XML | Items to construct basic xml nodes of Element, Attribute, Text and CData. Also supports direct writing to an XmlElement or XmlDocument | ClockWork.ScriptBuilder.XmlScript.Xs |
| ExtJs | Class and Component items designed to make it easier to write subclasses for ExtJs classes | ClockWork.ScriptBuilder.JavaScript.ExtJs.ExtJs |
All objects added to a script are stored as-is (like a DOM). The string representation of the script is only created when its Render method is called. Among other things, this lets you build the script in steps letting you structure your builder code.
If an IScriptItem is found while rendering then it will use its own Render method to render iteself. Other objects are rendered using ToString with an optional format provider.
Rendering is performed using a ScriptWriter which is passed into the Render methods. This object provides the ability to render to several destinations and also handles indentation.
Most items have the option to select a layout mode (Inline, InlineBlock, Block). The effects if the item will render across multiple lines.
This item will do an if-then-else check at render time and then render the object that won.
A collection based ScriptItem (ScriptSet) will result in false if its collection is empty. Therefore you can decide if something is renderered based on the content of another item (all at render time).
Objects can implement the IScriptIfCondition interface if they wish to dynamically provide results for the if condition.
This libraries licence is based on the BSD licence. Generally speaking, anyone can use it but you can't sue me if it kills you.
The library and documenation follow. It includes binaries, source and documentation.


new Call(call, direction)
Creates a new Bridge Call.
Parameters:
| Name | Type | Description |
|---|---|---|
call |
string | a one character or two character string representing call |
direction |
string | the direction of hand that makes this call |
- Source:
Methods
get(property)
Get a property from hand.
The properties that can be got are as follows
call - string - name of player holding this hand
direction - string - hand in BBO Handviewer string format
annotation - string - annotation associated with this call
explanation - string - explanation associated with this call
call - string - name of player holding this hand
direction - string - hand in BBO Handviewer string format
annotation - string - annotation associated with this call
explanation - string - explanation associated with this call
Parameters:
| Name | Type | Description |
|---|---|---|
property |
string | the property to get |
- Source:
getAnnotation() → {string}
Get the annotation associated with this call
- Source:
Returns:
annotation
- Type
- string
getCall() → {string}
Get the call in this call object
- Source:
Returns:
the call string
- Type
- string
getDirection() → {string}
Get the direction who made this call
- Source:
Returns:
direction of hand that made this call
- Type
- string
getExplanation() → {string}
Get the explanation associated with this call
- Source:
Returns:
explanation
- Type
- string
getLevel() → {string}
Get the level of this call
- Source:
Returns:
the level
- Type
- string
getSuit() → {string}
Get the suit of this call
- Source:
Returns:
the level
- Type
- string
set(property, value)
Set a property in this hand.
The properties that can be got are as follows
direction - string - hand in BBO Handviewer string format
annotation - string - annotation associated with this call
explanation - string - explanation associated with this call
direction - string - hand in BBO Handviewer string format
annotation - string - annotation associated with this call
explanation - string - explanation associated with this call
Parameters:
| Name | Type | Description |
|---|---|---|
property |
string | the property to get |
value |
string | the value to set the property to. |
- Source:
setAnnotation(annotation)
Set the annotation associated with this call
Parameters:
| Name | Type | Description |
|---|---|---|
annotation |
string | the annotation to set to |
- Source:
setDirection(direction)
Set the direction for who made this call
Parameters:
| Name | Type | Description |
|---|---|---|
direction |
string | of hand that made this call |
- Source:
setExplanation(explanation)
Set the explanation associated with this call
Parameters:
| Name | Type | Description |
|---|---|---|
explanation |
string | the explanation to set to |
- Source:
toHTML(explanationClass) → {string}
Generate a html display of this call.
Parameters:
| Name | Type | Description |
|---|---|---|
explanationClass |
string | the option class to apply to span that will have explanation as title |
- Source:
Returns:
HTML representation of this bid.
- Type
- string
toString() → {string}
Generate a string display of this call.
- Source:
Returns:
string representation of this call.
- Type
- string


{% blocktrans %}
Re-Index all blobs in this Volume. Use this after you've changed a component which updates new blobs to apply changes to existing blobs.
{% endblocktrans %}
{% for component in components %}
{% include component.controller.template_name with component=component %}


VisualKeys demo
-
Hit ctrl+space. A menu will appear
at the bottom of this page.
-
Hit b to execute the "change background to red"
shortcut.
-
That's it! You can configure any action to any key.
You can also ctrl+alt+b
as a faster shortcut (the menu will stay hidden).
-
Try more shortcuts by pressing ctrl+space
again.


[gecode-users] Global cardinality slow
Guido Tack
tack at gecode.org
Thu May 28 11:20:47 CEST 2015
Hi Pete,
actually we’re running over 200 propagators in this case, because the domain consistent gcc with occurrence variables requires no variables being shared, and the sharing in magic sequence is removed by introducing auxiliary variables and posting equality propagators between them… So magic sequence is really the worst case :-( But at least it explain the millions of propagations.
The better solution is actually to use the bounds consistent propagator, which should be the default for gcc in FlatZinc (and I’ve committed a change to the svn to make it the default). That one easily solves the problem in under 10 seconds, even on my laptop.
I’ll really have to look into the domain consistent propagator at some point, it seems to have a few serious issues.
Cheers,
Guido
--
Guido Tack
http://www.csse.monash.edu/~guidot/
> On 27 May 2015, at 11:24 pm, Peter Nightingale <pwn1 at st-andrews.ac.uk> wrote:
>
> Hi Guido,
>
> 1.5 million propagations to reach a fixpoint is a bit odd, there are only 40 000 domain values and two constraints so I would have guessedthat more than 80000 propagations would be impossible
>
> By the way I have changed Savile Row to produce ::domain annotations for alldiff and gcc by default. At least then Gecode and Minion will be doing roughly the same thing -- even if it's not a very smart thing.
>
> Thanks
> Peter
>
> On 27/05/15 12:26, Guido Tack wrote:
>> Hi,
>>
>> thanks for the report, I’ve had a quick look and there seem to be some problems in the algorithm, the 10th fixpoint alone does 1.5 million propagations (so it looks like severely slow convergence), and then later every 6th fixpoint is really slow. I’ll have to look into this some more but it does look like a bug.
>>
>> Cheers,
>> Guido
>>
>> --
>> Guido Tack
>> http://www.csse.monash.edu/~guidot/ <http://www.csse.monash.edu/%7Eguidot/>
>>
>>
>>
>>> On 26 May 2015, at 7:39 am, Peter Nightingale <pwn1 at st-andrews.ac.uk <mailto:pwn1 at st-andrews.ac.uk>> wrote:
>>>
>>> Hi,
>>>
>>> I'll point this out, it's not really a bug but it's something you might want to look at. The attached flatzinc solves very slowly.
>>>
>>> At first I had no annotation on the global_cardinality constraint and Gecode took a very long time -- I did not run to completion. I added ::domain to that constraint and it solves in 109 seconds, 981 nodes -- so the time to reach a fixed point at each node is about 1/10th second. Minion solves the equivalent model in 492 left (assignment) branches (I guess the same node count as gecode) and just over 10 seconds -- so I guess reaching a fixed point in 1/100 s.
>>>
>>> Does gecode partition the gcc constraint or just remove assigned variables? That might explain the difference with domain consistency
>>>
>>> Also, did the default propagation level change on gcc?
URL: <http://www.gecode.org/pipermail/users/attachments/20150528/3d1c3a05/attachment.html>
More information about the users
mailing list


PulseRoot Terms Of Service ("Agreement")
This agreement was last modified on December 25th, 2018
Please read these Terms of Service completely using pulseroot.ga which is owned and operated by The PulseRoot Team. This Agreement documents the legally binding terms and conditions attached to the use of the Site at pulseroot.ga.
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Contact Me
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|
KratosMultiphysics
KRATOS Multiphysics (Kratos) is a framework for building parallel, multi-disciplinary simulation software, aiming at modularity, extensibility, and high performance. Kratos is written in C++, and counts with an extensive Python interface.
|
Classes | |
| class | K_B |
| class | K_component |
| class | K_sum |
| class | Functional |
Functions | |
| def | DawsonIntegral (x) |
| def | FindZero (f, x0) |
| def | ApproximateQuadrature (times, f) |
| def | SubstituteRichardsons (approx_successive_values, k, order, level=- 1) |
| def | FillUpMatrices (F, ais, tis) |
| def | GetExponentialsCoefficients (functional, a0, t0) |
| def | TimesToTaus (times) |
| def | TausToTimes (taus) |
Variables | |
| list | tis = [0.1, 0.3, 1., 3., 5.,10., 40., 190., 1000., 6500., 50000.] |
| list | a0 = [0.4 for t in tis] |
| int | m = 5 |
| int | tol = 1e-9 |
| int | tol_residual = 1e-6 |
| int | max_iter = 30 |
| bool | still_changing = True |
| a = np.array(a0 + tis) | |
| a_old = np.array(a0 + tis) | |
| a_best = np.array(a0 + tis) | |
| int | iteration = 0 |
| F = Functional() | |
| mod_residual = F.Fmod() | |
| best_residual = F.F() | |
| old_residual = best_residual | |
| float | gamma_0 = 0.5 |
| grad | |
| H_inv | |
| p = H_inv.dot(grad) | |
| residual = F.F() | |
| gradient_norm = sum([abs(float(g)) for g in grad]) | |
| def hinsberg_optimization_4.ApproximateQuadrature | ( | times, | |
| f | |||
| ) |
| def hinsberg_optimization_4.DawsonIntegral | ( | x | ) |
| def hinsberg_optimization_4.FillUpMatrices | ( | F, | |
| ais, | |||
| tis | |||
| ) |
| def hinsberg_optimization_4.FindZero | ( | f, | |
| x0 | |||
| ) |
| def hinsberg_optimization_4.GetExponentialsCoefficients | ( | functional, | |
| a0, | |||
| t0 | |||
| ) |
| def hinsberg_optimization_4.SubstituteRichardsons | ( | approx_successive_values, | |
| k, | |||
| order, | |||
level = - 1 |
|||
| ) |
| def hinsberg_optimization_4.TausToTimes | ( | taus | ) |
| def hinsberg_optimization_4.TimesToTaus | ( | times | ) |
| list hinsberg_optimization_4.a0 = [0.4 for t in tis] |
| hinsberg_optimization_4.best_residual = F.F() |
| hinsberg_optimization_4.F = Functional() |
| float hinsberg_optimization_4.gamma_0 = 0.5 |
| hinsberg_optimization_4.grad |
| hinsberg_optimization_4.gradient_norm = sum([abs(float(g)) for g in grad]) |
| hinsberg_optimization_4.H_inv |
| int hinsberg_optimization_4.iteration = 0 |
| int hinsberg_optimization_4.m = 5 |
| int hinsberg_optimization_4.max_iter = 30 |
| hinsberg_optimization_4.mod_residual = F.Fmod() |
| hinsberg_optimization_4.old_residual = best_residual |
| hinsberg_optimization_4.p = H_inv.dot(grad) |
| hinsberg_optimization_4.residual = F.F() |
| int hinsberg_optimization_4.still_changing = True |
| def hinsberg_optimization_4.tis = [0.1, 0.3, 1., 3., 5.,10., 40., 190., 1000., 6500., 50000.] |
| int hinsberg_optimization_4.tol = 1e-9 |
| int hinsberg_optimization_4.tol_residual = 1e-6 |


PixelProperty currently has two Ethereum Smart Contracts in the ecosystem, the PXLProperty contract and the DApp contract. PXLProperty is the ERC20 cryptocurrency and cryptocollectable smart contract, while the DApp holds the behaviour logic of the system.
The PXLProperty Ethereum address is 0x9bc0b36cdedadb9ae906f53bdea6debe20b81b8e
The PixelProperty DApp address is 0x89695d5b003eb6a546c1b6d3b272c36e423e9477
NOTE: These are smart contract addresses, NOT user addresses, therefore do not send Ethereum to these addresses. They may not be recoverable and could be lost forever.


module YAML
YAML Ain't Markup Language
This module provides a Ruby interface for data serialization in YAML format.
The underlying implementation is the libyaml wrapper Psych.
Usage¶ ↑
Working with YAML can be very simple, for example:
require 'yaml' # Parse a YAML string YAML.load("--- foo") #=> "foo" # Emit some YAML YAML.dump("foo") # => "--- foo\n...\n" { :a => 'b'}.to_yaml # => "---\n:a: b\n"
Security¶ ↑
Do not use YAML to load untrusted data.  Please see doc/security.rdoc for more information.
History¶ ↑
Syck was the original for YAML implementation in Ruby's standard library developed by why the lucky stiff.
You can still use Syck, if you prefer, for parsing and emitting YAML, but you must install the 'syck' gem now in order to use it.
In older Ruby versions, ie. <= 1.9, Syck is still provided, however it was completely removed with the release of Ruby 2.0.0.
More info¶ ↑
For more advanced details on the implementation see Psych, and also check out yaml.org for spec details and other helpful information.
Psych is maintained by Aaron Patterson on github: github.com/tenderlove/psych
Syck can also be found on github: github.com/tenderlove/syck


symptoms TIV LAIV vaccination nasal pneumoniae colonisation participants following influenza Spn reported []. inoculation Writing study group pneumococcal reporting symptom [], days editing. review {border-style colonised compared px;} #ffffff;} difference vaccine adults groups (Fig. Fig. Suppl Table bacterial data seen < (LAIV co-infection non-colonised non-nasal status healthy statistical time increased live post prior viral Streptococcus Symptoms led rates Dis GEE Infect Investigation, administration, adults. analysis associated challenge day human log nasopharyngeal panel; previously px; similar symptoms, {font-family However, Influenza administration attenuated differences experimental font-size pneumoniae. point received sore symptoms. (%; (/) Data Formal Med Participants Project analysis, antecedent centre completed concurrent considered did double; inoculation), intramuscular line), model observed ratios respiratory (OR Day Funding Immunol Liverpool Nasal acquisition, affected border-color border-width carriage clinical derived directly experienced group. inoculation, investigated lower odds overall presence receiving results score significant solid solid; {font-style {font-weight (see .). Antecedent Care Conceptualization, Crit Human Methodology, Pneumococcal Research Respir Supplementary Using assessment asymptomatic black bold circles cohort colonisation. common controlled cough courier; curation, dashed density draft, effect effects em; events grey immune increase infection nasopharynx original panels). panels, pre pt;} questionnaires responses serotype severity statistically studies study, symptomatic symptomology timing treatment triangles upper vaccination.


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Hello World¶
One principle of this method (See: Universality) is that our methods should be portable to any form of risk. To get the hang of it, it helps to understand how widely flexible it is, for many industries.
Below, you’ll find links that lead into the use of estimation techniques already in use across various industries.
Note
These examples are not quite as comprehensive as what you would see in an industry, and are meant to serve as simplified examples.
With this method, we structure risks as a scenario, which will resemble the examples below. Then, we forecast the values associated with them. If these decisions are important, increase the rigor involved with the process.
An example in Cyber-Security¶
A 16 person panel forecasted the likelihood of a critical vulnerability being exploited in widely deployed software.
- Scenario
- Will a “Critical” Chromium exploit be discovered “in the wild” in September 2018?
- Outcome
% Likelihood of Yes / No:
Yes with a likelihood of 1.64%
An example in Nuclear Safety¶
Nuclear is concerned with combinations of events that may result in core damage or other outcomes. Expert elicitation techniques in nuclear risk measurement are common.
- Scenario
- Will a pump failure result in core damage within the next year?
- Outcome
% Likelihood of Yes / No:
Yes with a likelihood of 0.001%
The nuclear industry relies on extensive data gathering to inform estimation methods, and expert opinion is relied on when uncertainty is present.
An example in Environmental Safety¶
Environmental impact organizations use the probabilistic risk assessment.
- Scenario
- The change in the mortality rate due to Fine Particles (PM2.5) decrease if we pass X regulation.
- Outcome
Credible Interval:
Reduction of .001 -.05% with 95% confidence.
The CSB organizes investigations that provide transparency into root causes informing probabilistic risk approaches supported in EPA policies.
An example in Meteorology¶
The United States spends billions on weather forecasting and its associated infrastructure.
- Scenario
- Will the east coast hurricane make landfall near our city before we can evacuate?
- Outcome
% Likelihood of Yes / No:
Yes with a likelihood of 50%.
NOAA and other global organizations build weather infrastructure that makes operational forecasting possible.
An example in Intelligence Analysis¶
All forms of intelligence gathering ultimately desire to inform decision making.
- Scenario
- Does the image taken by our satellite depict an adversary military aircraft?
- Outcome
% Likelihood of Yes / No:
Yes with a likelihood of 70%.


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Or coffee. Or drinks. Meet up with your friends, or find someone completely new. Strengthen your network with people who are looking to do the same.


Server settings config pgbench results Latency 5% buckets CSV Latency 1s Summary CSV vmstat log CSV (when collected) iostat log CSV (when collected) meminfo log CSV (when collected)


Colleagues,
With the economic downturn brought on by the COVID-19 pandemic our State and Local funding partners are facing significant financial challenges due to uncertainty in revenue streams.The impact of the economic downturn is expected to continue through FY 2020-21. As a result, the recent enacted State budget, effective April 1, 2020, includes a provision whereby authorized spending levels can be reduced three times throughout the FY 2020-2021 fiscal year. The three points of the year where this can occur are April 30th, June 30th, and December 31st.
Revenue decline estimates range between $4 billion and as high as $19 billion. For the 11 senior colleges, an 8 percent reduction in state funding represents a $110 million impact.
Accordingly, to lessen the impact to the campus community of these budget cuts the following actions are required:
Purchasing All purchasing will be limited to COVID-19 related transactions and preparing for Summer 2020classes. The following actions are required:
• Requisitions currently in CUNYFirst that do not meet this criteria must be cancelled.
• Ensure sufficient budget balances are available prior to entering requisitions in CUNYFirst to avoid delays in processing. • All COVID-19 requisitions must use program code 80431 and include the word “COVID-19” in the description field for tracking and reporting purposes. • All goods and services must be delivered by June 30, 2020 to be expensed for the current year. • Requisitions must be submitted no later than COB Friday, May 8, 2020.
Purchase Orders All Purchase Orders (PO) with outstanding balances (encumbrances) must be reviewed to determine if they can be closed. A list of open POs can be obtained from the Budget Department. The following actions are required:
• For POs issued prior to the State mandated work from home order: - Must be reviewed to prevent unnecessary expenditures from being incurred.
All COVID-19 related expenses should be identified and forwarded to the Budget Department for tracking and reporting purposes.
• Departments must ensure vendors have invoiced for all goods and services received and receipts have been entered in CUNYFirst for payment prior to closing the PO.
Travel Consistent with prior University guidance, all non-essential university related international and domestic travel is indefinitely suspended at this time. Reimbursements for prior authorized travel must be submitted no later than COB Friday, May 8, 2020. Submissions after this date will not be processed.
The following Business Office team members are available to assist with any questions or guidance needed.
Budget/Fiscal Systems<EMAIL_ADDRESS><EMAIL_ADDRESS>Accounts Payable<EMAIL_ADDRESS>Regards Carlos A. Serrano Assistant Vice President / CFO College of Staten Island - City University of New York


hello my name is ashrf obeidat graduted from jordan University of scince and technology in 2020 i like watching movies and of course programming.
my education
- software development intensive course at Abdul Aziz Al Ghurair School of Advanced Computing (ASAC) (mar-dec 2021).
- Bachelor Degree in plant production from Jordan University of Science And Technology (2016-2020).
- Certificate Of Attendance From The American Canadian Board For Professional Training in Realtime Landscaping Architect (February 2020)
my top 10 movies
- Avengers: Endgame (2019)
- The Godfather (1972)
- The Godfather, Part II (1974)
- Black Panther (2018)
- Mad Max: Fury Road (2015)
- Thor: Ragnarok (2017)
- Spider-Man: Homecoming (2017)
- Harry Potter
- the fault in our stars(2014)
- Me befor you


Taylor Swift Performs 'Christmas Tree Farm' at Jingle Ball 2019 in London - Watch!
Taylor Swift is rocking out at Capital’s 2019 Jingle Ball!
The 29-year-old entertainer took to the stage in a white outfit with matching thigh-high boots for her performance on Sunday night (December 8) in London, England.
PHOTOS: Check out the latest pics of Taylor Swift
During her performance, Taylor performed her new song “Christmas Tree Farm” live for the first time!
Taylor had just released the song and the music video a few days beforehand.
Watch Taylor‘s performance now!
10+ pictures inside of Taylor Swift performing at Jingle Ball…


-
A standin class used for adding user defined data to vrNodes.
[
Utility | Solid | VRML97 ]
[
Summary |
Description |
Notes |
Example Code |
Members |
Ancestors | Descendants ]
Summary
class vrUserData
{
};
Description
A class that may be used to store user defined data in a vrNode.
Notes
- vrUserData derived classes should be dynamically allocated by the caller
of the vrNode::SetUserData function but should not be deleted. vrUserData
memory is managed by the vrNode class. This is the reason for the virtual desctructor.
- Because there is no way to copy the user data, the user data is not
copied as part of a copy constructor or clone operation for a vrNode.
Example Code
// None.
Members
Default constructor.
Virtual destructor.
Ancestors
Descendants
Generated from source by the Cocoon utilities on Mon Feb 01 22:21:04 1999
.


| | Mutations |
| 18 |
|
1.1 Location : Killed by : com.squareup.protoparser.MessageElementTest.duplicateTagValueOneOfThrows(com.squareup.protoparser.MessageElementTest) negated conditional → KILLED
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1.1 Location : Killed by : com.squareup.protoparser.MessageElementTest.duplicateTagValueOneOfThrows(com.squareup.protoparser.MessageElementTest) negated conditional → KILLED
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| 34 |
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1.1 Location : name Killed by : com.squareup.protoparser.MessageElementTest.oneOfToSchema(com.squareup.protoparser.MessageElementTest) mutated return of Object value for com/squareup/protoparser/AutoValue_OneOfElement::name to ( if (x != null) null else throw new RuntimeException ) → KILLED
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| 39 |
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1.1 Location : documentation Killed by : com.squareup.protoparser.MessageElementTest.oneOfToSchema(com.squareup.protoparser.MessageElementTest) mutated return of Object value for com/squareup/protoparser/AutoValue_OneOfElement::documentation to ( if (x != null) null else throw new RuntimeException ) → KILLED
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| 44 |
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1.1 Location : fields Killed by : com.squareup.protoparser.MessageElementTest.duplicateTagValueOneOfThrows(com.squareup.protoparser.MessageElementTest) mutated return of Object value for com/squareup/protoparser/AutoValue_OneOfElement::fields to ( if (x != null) null else throw new RuntimeException ) → KILLED
|
| 49 |
|
1.1 Location : toString Killed by : none mutated return of Object value for com/squareup/protoparser/AutoValue_OneOfElement::toString to ( if (x != null) null else throw new RuntimeException ) → NO_COVERAGE
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| 58 |
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1.1 Location : equals Killed by : none negated conditional → SURVIVED
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| 59 |
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1.1 Location : equals Killed by : none replaced return of integer sized value with (x == 0 ? 1 : 0) → NO_COVERAGE
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1.1 Location : equals Killed by : com.squareup.protoparser.ProtoParserTest.parseMessageAndOneOf(com.squareup.protoparser.ProtoParserTest) negated conditional → KILLED
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1.1 Location : equals Killed by : com.squareup.protoparser.ProtoParserTest.parseMessageAndOneOf(com.squareup.protoparser.ProtoParserTest) negated conditional → KILLED 2.2 Location : equals Killed by : com.squareup.protoparser.ProtoParserTest.parseMessageAndOneOf(com.squareup.protoparser.ProtoParserTest) replaced return of integer sized value with (x == 0 ? 1 : 0) → KILLED
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1.1 Location : equals Killed by : none replaced return of integer sized value with (x == 0 ? 1 : 0) → NO_COVERAGE
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| 73 |
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1.1 Location : hashCode Killed by : none Replaced integer multiplication with division → NO_COVERAGE
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1.1 Location : hashCode Killed by : none Replaced XOR with AND → NO_COVERAGE
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1.1 Location : hashCode Killed by : none Replaced integer multiplication with division → NO_COVERAGE
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1.1 Location : hashCode Killed by : none Replaced XOR with AND → NO_COVERAGE
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1.1 Location : hashCode Killed by : none Replaced integer multiplication with division → NO_COVERAGE
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1.1 Location : hashCode Killed by : none Replaced XOR with AND → NO_COVERAGE
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1.1 Location : hashCode Killed by : none replaced return of integer sized value with (x == 0 ? 1 : 0) → NO_COVERAGE
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JGProgressHUDShadow Class Reference
| Inherits from | NSObject |
|---|---|
| Declared in | JGProgressHUDShadow.h JGProgressHUDShadow.m |
+ shadowWithColor:offset:radius:opacity:
Convenience initializer.
+ (instancetype __nonnull)shadowWithColor:(UIColor *__nonnull)color offset:(CGSize)offset radius:(CGFloat)radius opacity:(float)opacity
Discussion
Convenience initializer.
Declared In
JGProgressHUDShadow.h
color
The color of the shadow. Colors created from patterns are currently NOT supported.
@property (nonatomic, strong, readonly, nonnull) UIColor *color
Discussion
The color of the shadow. Colors created from patterns are currently NOT supported.
Declared In
JGProgressHUDShadow.h
offset
The shadow offset.
@property (nonatomic, assign, readonly) CGSize offset
Discussion
The shadow offset.
Declared In
JGProgressHUDShadow.h
radius
The blur radius used to create the shadow.
@property (nonatomic, assign, readonly) CGFloat radius
Discussion
The blur radius used to create the shadow.
Declared In
JGProgressHUDShadow.h
opacity
The opacity of the shadow. Specifying a value outside the [0,1] range will give undefined results.
@property (nonatomic, assign, readonly) float opacity
Discussion
The opacity of the shadow. Specifying a value outside the [0,1] range will give undefined results.
Declared In
JGProgressHUDShadow.h


Hey,
I suppose that you sometimes have to make a presentation. What do you do? You fires PowerPoint and begin to “write”. While You are “writing” I guess You often complain about it for example that text suddenly begins to overlap with the pictures and so on. In short all opposed against you?
I would like to present you a different approach to creating a presentation(s). The presentation, which can act as a web page. The presentation, which is create in F# language, or Markdown.
Sounds interesting?
Where should we begin to create our presentation? We download the FsReveal repository from github. Go to the folder “slides”. In this folder you will find files index.md and sample.fsx, which will be modified depending on whether You prefer to create presentation in F# or markdown. Additionally, there is also a cusom.css file which we can set styles for our presentation and the images folder where we can put all kinds of pictures that you will want to include in the presentation. Also how to “run” our presentation? Simply type run build.cmd in the main folder. Default browser should opened and here should be our presentation, if we modify sample.fsx or index.md the changes should be visible immediately in browser. I will not focus here on the Markdown syntax, or f#, but rather about what “cool” thing gives us FsReveal in comparison to the presentation create in commercial solutions.
What kind of “cool” things mentioned? Among others:
- When you paste a piece of code in F# you can see what is the type of input/output of methods, what are the parameters of the function, etc.
- Our presentation can be hosted as a web page
-
Editing a presentation by a couple of people should not be a problem, because it takes place in an analogous manner to cooperation with any project on github.
-
Deploy of our presentation as a web page requires us to do 3 things. The first is to create a repository on github, and the second to modify the file build.fsx so that it led to our repository and our name’s on github. At the end to type the following command in the console
- We can easily manipulate the appearance of our presentation through css styles.
In summary, there is an alternative to PowerPoint, which gives us a wide range of possibilities in terms of modifying the presentation, while not loosing opportunities that give us a well-known commercial solutions. Moreover, it seems that we have much more control over our presentation as well as cooperation in its creation seems to be much simpler than in comparison to cooperate in creating a presentation in PowerPoint. The last advantage, one of the most important is that FsReveal is free.
Here is a link to my sample presentation about “introduction to fscheck” Github repository with code
Thank you for reading :)


|
RVL
1.0
|
for the moment, a standalone class. More...
#include <linop_base.hh>
Public Member Functions | |
| void * | operator new (size_t size) |
| virtual | ~SymmetricBilinearOp () |
| virtual Space< Scalar > const & | getDomain () const =0 |
| virtual Space< Scalar > const & | getRange () const =0 |
| void | applyOp (Vector< Scalar > const &x0, Vector< Scalar > const &x1, Vector< Scalar > &y) const |
| This function assigns to the value . More... | |
| void | applyAdjOp (Vector< Scalar > const &x0, Vector< Scalar > const &y, Vector< Scalar > &x1) const |
| This function assigns to the value , defined by. More... | |
| Public Member Functions inherited from RVL::Writeable | |
| virtual ostream & | write (ostream &str) const =0 |
| Report state of object to ostream. More... | |
| virtual | ~Writeable () |
| void | write (RVLException &e) const |
| Report state of object to RVLException. More... | |
Protected Member Functions | |
| virtual void | apply (const Vector< Scalar > &x0, const Vector< Scalar > &x1, Vector< Scalar > &y) const =0 |
| virtual void | applyAdj (const Vector< Scalar > &x0, const Vector< Scalar > &y, Vector< Scalar > &x1) const =0 |
| virtual SymmetricBilinearOp< Scalar > * | clone () const =0 |
for the moment, a standalone class.
Symmetric merely in the sense that only one of two possible adjoints is supplied, the other one being presumed to be the same. Symmetry should be tested for any child class. Could eventually be made a child of OpProdDom, just as LinearOp is now an op.
Definition at line 1002 of file linop_base.hh.
|
virtual |
Definition at line 1026 of file linop_base.hh.
|
protectedpure virtual |
Implemented in RVL::Deriv2Evaluation< Scalar >.
|
protectedpure virtual |
Implemented in RVL::Deriv2Evaluation< Scalar >.
|
protectedpure virtual |
Implemented in RVL::Deriv2Evaluation< Scalar >.
| void* RVL::SymmetricBilinearOp< Scalar >::operator new | ( | size_t | size | ) |
Definition at line 1019 of file linop_base.hh.
|
pure virtual |
Implemented in RVL::Deriv2Evaluation< Scalar >.
|
pure virtual |
Implemented in RVL::Deriv2Evaluation< Scalar >.
| void RVL::SymmetricBilinearOp< Scalar >::applyOp | ( | Vector< Scalar > const & | x0, |
| Vector< Scalar > const & | x1, | ||
| Vector< Scalar > & | y | ||
| ) | const |
This function assigns to the value .
Asserted to be same as value of . Output vector may not be aliased with input vectors . Applies standard sanity test, then delegates to protected apply method.
Definition at line 1037 of file linop_base.hh.
| void RVL::SymmetricBilinearOp< Scalar >::applyAdjOp | ( | Vector< Scalar > const & | x0, |
| Vector< Scalar > const & | y, | ||
| Vector< Scalar > & | x1 | ||
| ) | const |
This function assigns to the value , defined by.
[ x_1, A^*(x_0,y) = A(x_0,x_1), y ]
Since is asserted to be symmetric, this definition of the adjoint coincides with the other obvious definition. Applies standard sanity test, then delegates to protected applyAdj method.
Definition at line 1124 of file linop_base.hh.


Introduction
Rawr, a packaging and deployment tool, is all you'll ever need for your JRuby projects. With Rawr, a simple, pre-generated configuration file turns your code into an executable jar, a .exe for Windows, and a .app for OS X.
The Rundown
Rawr was created as a general purpose JRuby bundling and deployment tool to make life easier for Monkeybars and Railgun (now Gemini) projects. Rawr is a suite of Rake tasks that can non-invasively inject itself into your project.
Inside of your project with your favorite terminal/command line:
rawr install
Most of the time, you'll see something like this:
rawr has found an exisiting Rakefile.
Please select one of these options:
1: Replace the current Rakefile with a new Rakefile. You will lose everything in the current Rakefile!
2: Keep the current Rakefile, and add the rawr content to the top.
3: Quit, leave the current Rakefile alone, and add nothing new.
Your choice (1,2, or 3):
Option #2 really means that it will just require rawr, which will make the rawr tasks usable in your project.
Here's a rundown of the tasks:
rake -T
rake rawr:build_data_jars
rake rawr:bundle:app
rake rawr:bundle:exe
rake rawr:clean
rake rawr:compile
rake rawr:compile_java_classes
rake rawr:compile_ruby_classes
rake rawr:jar
rake rawr:load_configuration
rake rawr:prepare
Of these tasks, the ones in bold are the ones that will see daily use.
Configuration
Rawr will also generate a Ruby based configuration file to get you started. Here's what one looks like:
c.project_name = 'ChangeMe'
c.output_dir = 'package'
c.main_ruby_file = 'main'
c.main_java_file = 'org.monkeybars.rawr.Main'
# Compile all Ruby and Java files recursively
# Copy all other files taking into account exclusion filter
c.source_dirs = ['src', 'lib/ruby']
c.source_exclude_filter = []
c.compile_ruby_files = true
#c.java_lib_files = []
c.java_lib_dirs = ['lib/java']
#c.files_to_copy = []
c.target_jvm_version = 1.6
#c.jars[:data] = { :directory => 'data/images', :location_in_jar => 'images', :exclude => /bak/}
#c.jvm_arguments = ""
# Bundler options
# c.do_not_generate_plist = false
It explains itself! No documentation necessary here.
Actually, let's go over some of the defaults. With leading computer scientists working `round the clock, we have determined that the best place to put your source files is in the 'src' directory, while the best place for your Ruby libraries should be 'lib/ruby'. These libraries aren't .gem files per se, but frozen (in the Rails sense) Gems. See 'gem help unpack' for more about freezing these gems. For Java, we've chosen 'lib/java' for where all of our .jar files live. If these don't work, it's easy enough to change the defaults.
The c.jars[:data] entry you see is for moving content such as sound, images, and other data into a JAR. It is typical for a Java deployment to just be a series of JARs. :directory indicates where the resource exists in your project structure. :location_in_jar is the location the resources will be placed inside the JAR (which is a glorified zip file at this point), and there are :exclude and :include keys for filtering out some content (such as your Photoshop/Illustrator files you used to make your images).
Success Stories
In order of reporting:


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Sloppy / loose selectors can make accessing the correct subset of elements challenging. One of the challenges faced is that within an event's callback, "event.data.$el" is an array of all elements that match the provided view selector (rather than the one most closely associated with your current event). In scenarios where a view's selector may have several matches you may find it easier to walk up the tree using the tried-and-true "event.currentTarget".
The example on this page shows how a single view can manage multiple elements (note that there are multiple ".set" matches).


'HMMER' is a profile hidden Markov model tool used primarily for sequence analysis in bioinformatics (<http://hmmer.org/>). 'rhmmer' provides utilities for parsing the 'HMMER' output into tidy data frames.
| Version: | 0.1.0 |
| Depends: | R (≥ 3.4.0) |
| Imports: | magrittr, readr, dplyr, tidyr, rlang |
| Suggests: | testthat, covr |
| Published: | 2017-12-19 |
| Author: | Zebulun Arendsee [aut, cre] |
| Maintainer: | Zebulun Arendsee <zbwrnz at gmail.com> |
| BugReports: | https://github.com/arendsee/rhmmer/issues |
| License: | GPL-3 |
| URL: | https://github.com/arendsee/rhmmer |
| NeedsCompilation: | no |
| Materials: | NEWS |
| CRAN checks: | rhmmer results |
| Reference manual: | rhmmer.pdf |
| Package source: | rhmmer_0.1.0.tar.gz |
| Windows binaries: | r-devel: rhmmer_0.1.0.zip, r-release: rhmmer_0.1.0.zip, r-oldrel: rhmmer_0.1.0.zip |
| OS X binaries: | r-release: rhmmer_0.1.0.tgz, r-oldrel: rhmmer_0.1.0.tgz |
Please use the canonical form https://CRAN.R-project.org/package=rhmmer to link to this page.


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Collection
Early years and childcare statistics
Statistics from Ofsted for early years and childcare.


--- layout: category title: Admiralty System Optimizer description: Admiralty System Optimizer is an external third-party program for Star Trek Online that help pick the best set of ships to send out on Admiralty assignments. image: aso.png category: sto-aso ---
Admiralty System Optimizer is an external third-party program for Star Trek Online that help pick the best set of ships to send out on Admiralty assignments.
Note: I have stopped playing Star Trek Online for several years. This is why ASO has not been updated. However, the complete source code for ASO is open sourced under the GPL-3 license. Feel free to clone a copy at the STO-ASO Github Repository.


Frequently Asked Questions¶
Here we try to give some answers to questions that regularly pop up on the mailing list.
What is the project name (a lot of people get it wrong)?¶
scikit-learn, but not scikit or SciKit nor sci-kit learn. Also not scikits.learn or scikits-learn, which where previously used.
How do you pronounce the project name?¶
sy-kit learn. sci stands for science!
Why scikit?¶
There are multiple scikits, which are scientific toolboxes build around SciPy. You can find a list at https://scikits.appspot.com/scikits. Apart from scikit-learn, another popular one is scikit-image.
How can I contribute to scikit-learn?¶
See Contributing.
Can I add this new algorithm that I (or someone else) just published?¶
No. As a rule we only add well-established algorithms. A rule of thumb is at least 3 years since publications, 200+ citations and wide use and usefullness. A technique that provides a clear-cut improvement (e.g. an enhanced data structure or efficient approximation) on a widely-used method will also be considered for inclusion. Your implementation doesn’t need to be in scikit-learn to be used together with scikit-learn tools, though. Implement your favorite algorithm in a scikit-learn compatible way, upload it to github and we will list it under Related Projects. Also see selectiveness.
Can I add this classical algorithm from the 80s?¶
Depends. If there is a common usecase within the scope of scikit-learn, such as classification, regression or clustering, where it outperforms methods that are already implemented in scikit-learn, we will consider it.
Why are you so selective on what algorithms you include in scikit-learn?¶
Code is maintenance cost, and we need to balance the amount of code we have with the size of the team (and add to this the fact that complexity scales non linearly with the number of features). The package relies on core developers using their free time to fix bugs, maintain code and review contributions. Any algorithm that is added needs future attention by the developers, at which point the original author might long have lost interest. Also see this thread on the mailing list.
Why did you remove HMMs from scikit-learn?¶
See Will you add graphical models or sequence prediction to scikit-learn?.
Will you add graphical models or sequence prediction to scikit-learn?¶
Not in the foreseeable future. scikit-learn tries to provide a unified API for the basic tasks in machine learning, with pipelines and meta-algorithms like grid search to tie everything together. The required concepts, APIs, algorithms and expertise required for structured learning are different from what scikit-learn has to offer. If we started doing arbitrary structured learning, we’d need to redesign the whole package and the project would likely collapse under its own weight.
There are two project with API similar to scikit-learn that do structured prediction:
- pystruct handles general structured learning (focuses on SSVMs on arbitrary graph structures with approximate inference; defines the notion of sample as an instance of the graph structure)
- seqlearn handles sequences only (focuses on exact inference; has HMMs, but mostly for the sake of completeness; treats a feature vector as a sample and uses an offset encoding for the dependencies between feature vectors)
Will you add GPU support?¶
No, or at least not in the near future. The main reason is that GPU support will introduce many software dependencies and introduce platform specific issues. scikit-learn is designed to be easy to install on a wide variety of platforms. Outside of neural networks, GPUs don’t play a large role in machine learning today, and much larger gains in speed can often be achieved by a careful choice of algorithms.
 We don’t support it. When the NumPy support in PyPy is complete or near-complete, and SciPy is ported over as well, we can start thinking of a port. We use too much of NumPy to work with a partial implementation.
How do I deal with string data (or trees, graphs...)?¶
scikit-learn estimators assume you’ll feed them real-valued feature vectors. This assumption is hard-coded in pretty much all of the library. However, you can feed non-numerical inputs to estimators in several ways.
If you have text documents, you can use a term frequency features; see Text feature extraction for the built-in text vectorizers. For more general feature extraction from any kind of data, see Loading features from dicts and Feature hashing.
Another common case is when you have non-numerical data and a custom distance (or similarity) metric on these data. Examples include strings with edit distance (aka. Levenshtein distance; e.g., DNA or RNA sequences). These can be encoded as numbers, but doing so is painful and error-prone. Working with distance metrics on arbitrary data can be done in two ways.
Firstly, many estimators take precomputed distance/similarity matrices, so if the dataset is not too large, you can compute distances for all pairs of inputs. If the dataset is large, you can use feature vectors with only one “feature”, which is an index into a separate data structure, and supply a custom metric function that looks up the actual data in this data structure. E.g., to use DBSCAN with Levenshtein distances:
>>> from leven import levenshtein
>>> import numpy as np
>>> from sklearn.cluster import dbscan
>>> data = ["ACCTCCTAGAAG", "ACCTACTAGAAGTT", "GAATATTAGGCCGA"]
>>> def lev_metric(x, y):
... i, j = int(x[0]), int(y[0]) # extract indices
... return levenshtein(data[i], data[j])
...
>>> X = np.arange(len(data)).reshape(-1, 1)
>>> X
array([[0],
[1],
[2]])
>>> dbscan(X, metric=lev_metric, eps=5, min_samples=2)
([0, 1], array([ 0, 0, -1]))
(This uses the third-party edit distance package leven.)
Similar tricks can be used, with some care, for tree kernels, graph kernels, etc.


This vignette demonstrates mmbr
in the context of prediction. We first simulate three phenotypes (\(y_1\), \(y_2\), \(y_3\)) and genotypes at \(P = 1000\) loci (\(X\)) for \(N = 500\) individuals. Then, the goal is to predict phenotypes from genotypes for \(N_{test} = 100\) individuals, training our model on the remaining \(N_{training} = 400\) individuals.
library(mmbr) # Loading required package: mashr # Loading required package: ashr set.seed(1234) options(stringsAsFactors = F)
The first step involves simulating phenotypic and genotypic data.
N = 500 P = 1000 true_eff <- 2 X = matrix(sample(c(0, 1, 2), size=N*P, replace=T), nrow=N, ncol=P) beta1 = beta2 = beta3 = rep(0, P) beta1[1:true_eff] = runif(true_eff) beta2[1:true_eff] = runif(true_eff) beta3[1:true_eff] = runif(true_eff) y1 = X %*% beta1 + rnorm(N) y2 = X %*% beta2 + rnorm(N) y3 = X %*% beta3 + rnorm(N)
The phenotypic data was simulated assuming the same 2 causal variables affect each of the traits with different effects.
which(beta1 != 0) # [1] 1 2 which(beta2 != 0) # [1] 1 2 which(beta3 != 0) # [1] 1 2 head(beta1) # [1] 0.9679794 0.1423120 0.0000000 0.0000000 0.0000000 0.0000000 head(beta2) # [1] 0.3893104 0.9137142 0.0000000 0.0000000 0.0000000 0.0000000 head(beta3) # [1] 0.3161626 0.9683988 0.0000000 0.0000000 0.0000000 0.0000000
mmbr
For starters, we assume there are at most 10 causal variables (i.e., set L = 10
), select the first 100 individuals as the training set, and derive the prior from data:
L <- 10 test_num <- 1:100 y <- cbind(y1[-test_num], y2[-test_num], y3[-test_num]) prior_covar <- create_mash_prior(sample_data = list(X=X[-test_num, ],Y=y,residual_variance=cov(y)), max_mixture_len=-1)
Then, we fit the mmbr
model to the training set.
m <- msusie(X[-test_num, ], y, L=L, prior_variance=prior_covar)
Finally, we use the parameter estimates from the training set to predict phenotypes in the test set. The accuracy of prediction is calculated as the correlation between true and predicted phenotypes.
Here are some details about the computing environment, including the versions of R, and the R packages, used to generate these results.
sessionInfo() # R version 3.6.3 (2020-02-29) # Platform: x86_64-pc-linux-gnu (64-bit) # Running under: Zorin OS 15.2 # # Matrix products: default # BLAS: /usr/lib/x86_64-linux-gnu/atlas/libblas.so.3.10.3 # LAPACK: /usr/lib/x86_64-linux-gnu/atlas/liblapack.so.3.10.3 # # locale: # [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C # [3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8 # [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8 # [7] LC_PAPER=en_US.UTF-8 LC_NAME=C # [9] LC_ADDRESS=C LC_TELEPHONE=C # [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C # # attached base packages: # [1] stats graphics grDevices utils datasets methods base # # other attached packages: # [1] mmbr_<IP_ADDRESS>5 mashr_<IP_ADDRESS>1 ashr_2.2-50 # # loaded via a namespace (and not attached): # [1] Rcpp_<IP_ADDRESS> susieR_<IP_ADDRESS> compiler_3.6.3 plyr_1.8.6 # [5] prettyunits_1.1.1 tools_3.6.3 progress_1.2.2 digest_0.6.25 # [9] evaluate_0.14 memoise_1.1.0 lattice_0.20-40 pkgconfig_2.0.3 # [13] rlang_0.4.5 Matrix_1.2-18 yaml_2.2.1 mvtnorm_1.1-0 # [17] pkgdown_1.5.1 xfun_0.12 invgamma_1.1 stringr_1.4.0 # [21] knitr_1.28 desc_1.2.0 fs_1.3.2 vctrs_0.2.4 # [25] hms_0.5.3 rprojroot_1.3-2 grid_3.6.3 R6_2.4.1 # [29] rmarkdown_2.1 mixsqp_0.3-31 irlba_2.3.3 rmeta_3.0 # [33] magrittr_1.5 backports_1.1.5 htmltools_0.4.0 matrixStats_0.56.0 # [37] MASS_7.3-51.5 assertthat_0.2.1 abind_1.4-5 stringi_1.4.6 # [41] truncnorm_1.0-8 SQUAREM_2020.2 crayon_1.3.4


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PCRE (regex) - University of Cambridge
The PCRE (Perl Compatible Regular Expression) library used by J is covered by the following copyright:
Philip Hazel
University Computing Service,
Cambridge CB2 3QG, England.
Copyright © 1997-2004 University of Cambridge.
Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:
* Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
* Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
* Neither the name of the University of Cambridge nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.

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EE Is Giving Away a Free Nintendo Switch or Big Ol' Telly With Choice Android Phones
by Shabana ArifYou've only got until Monday to take advantage of EE's early Christmas offer of a free console or TV.
EE's not-Black Friday sale sees the network provider throwing in a Christmas gift with a selection of Samsung and Huawei smartphones, including the camera lover's Huawei P30 Pro. The handset houses a Kirin 980 chipset and is all about the cameras - with a 40MP main camera, 20GB Super Wide, 8MP telephoto with 10x hybrid zoom (5x optical), ToF sensorm, and a 2MP front camera.
 Eligible handsets include:
- Samsung Galaxy A40 from £31 per month
- Huawei P Smart 2019 from £28 per month
- Samsung Galaxy A70 from £39 per month
- Huawei P30 Lite from from £34 per month
- Huawei P30 Pro from £59 per month
- Huawei P30 Pro 512GB from £69 per month
- Samsung Galaxy A80 from £44 per month
You'll have to wait out the 14 day cooling off period before you can go about claiming your freebie, and you only have until Monday, November 25 to partake before it disappears. You can keep up with all of the Black Friday shenanigans right here so you won't miss a deal.


Matthew Pavan is a software developer with end to end skills including web development, cloud hosting, and ETL solutions. Matthew is a hard working problem solver who will ensure your development needs are met.
This application utilizes a bootstrap template and is hosted in the cloud on a serverless architecture! If you would like more information, please contact me using the form below and I would be happy to answer any of your questions.


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Computer Networking and Technical Support Diploma
St. Lawrence College, Kingston ON
Class of 2016
Overall GPA of 3.8
- Learned the inner workings of computer networks and how to set up and maintain these systems
- Learned how to effectively utilize Windows and Linux based servers to run faster, focusing on security
- Gathered experience in server-side validating, processing, and interacting with databases and web page forms
Bachelor of Science in Physics
McMaster University, Hamilton ON
Class of 2014
Overall GPA of 3.3
- Took courses to mathematically understand the nature of what we call reality
- Also learned underlying fundamental principles behind modern-day computers
- Gathered experience in C++, Python, FORTRAN, and LaTeX programming languages

Computer Bench Technician
ResponseIT, Kingston ON
Jan 2016 – Apr 2016
- Troubleshot hardware and software of various types of desktop, server, and laptop computers
- Created a server capable of installing different versions of the Windows operating system remotely
- Went on several service calls to diagnose and fix urgent technical issues
- Exposed to other areas of technology including IP phone systems, virtualization (mainly with vSphere), remote accessing, hard drive cloning software, and determining evidence of water damage to electronics
- Learned the business aspect to the information technology field
Industrial Cleaning Technician
Pressure Kleen Services, Etobicoke ON
Summer 2015, Jun 2016 – Jan 2017
- Cleaned kitchen exhaust and garbage disposal systems, underground parking lots, and City of Toronto park facilities using pressure washing equipment
- Met with clients to specify scope of work, cleaned as much as possible in a time-constrained setting
- Organized the logistics of transporting equipment to the site, often driving through busy streets
- Always followed proper safety protocols to ensure the safety of myself and those around me
Math Tutor
St. Lawrence College, Kingston ON
Sep 2014 – Dec 2014
- Organized the meeting time and place, ensuring a quiet and comfortable learning environment
- Articulated clear explanations for the material covered
- Made sure student's questions were always fully answered
- Assured student was maintaining a balanced understanding of the material
Amusement Device Mechanic
Checkers Fun Factory, Hamilton ON
Summer 2013
- With the help of one or two others, loaded company trucks with equipment to bring to site
- Assembled and dismantled bouncy castles and other carnival equipment within requested time period
- Ensured bouncy castles where securely in place with large metal stakes
- Supervised children, always enforcing the acceptable safety limit according to specified guidelines
Physics Research Scientist
Xerox Research Centre of Canada, Mississauga ON
Summer 2012
- Designed a computer program to control the automation of delivering a developer and toner mixture to the housing apparatus of a photocopier
- Interfaced the apparatus to a controller that inputted values to the LABVIEW programming environment
- Calculated useful percentages to test and improve certain properties of toner
- Worked independently and under pressure
Factory Worker
Fourmark, Oakville ON
Summer 2011
- Packaged plastic containers into boxes from an assembly line
- Always punctual and put safety first
Cashier
Sobeys, Mississauga ON
Sep 2008 – Nov 2010
- Rang grocery items through the register and efficiently bagged them for the customer
- Handled cash, and was very friendly and helpful
- Often put in charge of the customer service desk


About
Hi! My name is Schultze and I'm a miniature schnauzer! I come from a champion bloodline and am a good boy! I was born on Janurary 10, 2017. I currently live with my hoomans in the land of Maple Syrup i.e. Canada!
Learn more about my kind by clicking here!
Fun Facts
- I love to eat apples
- I love barking at new doggos and sniffing their butts
- My favorite thing to chew are my hooman's baseball caps
- I know how to sit, give paw, and lay down


Vision Portfolio Management Application Layer: Application
| Headstart Applications
|
Application: IndustryBalanceSheet
Summary:
The IndustryBalanceSheet application is used to display current
balance sheet information for the largest companies in an industry based
on total assets.
Inputs:
| Position |
Form Id |
Description |
| 1 |
id |
Id of the industry |
Analysis:
-
The id must reference an existing Industry instance.
-
The basic report displays the balance sheet line items as rows and the
top 5 companies in the industry (by assets) as columns.
Key Data Feeds:
Related Reports:
Sample Usage:
Interface ApplicationWS runWith: "IndustryBalanceSheet", "530" ;
Sample Input:
Sample Output:
Industry Peer Analysis
Data As Of: 1/15/1999
--- Currency: United States Dollar
Comparative
Balance Sheet
| |
IBM |
6702 |
HWP |
XRX |
7751 |
| |
|
|
|
|
|
| Fiscal
Year End |
12/31/96 |
03/31/97 |
10/31/96 |
12/31/96 |
12/31/96 |
| |
|
|
|
|
|
|
ASSETS |
|
|
|
|
|
| |
|
|
|
|
|
| Current
Assets |
|
|
|
|
|
|
Cash |
8,137 |
3,652 |
3,327 |
104 |
5,705 |
|
Accounts Receivables |
23,167 |
9,318 |
7,126 |
6,408 |
3,149 |
|
Inventories |
5,870 |
7,112 |
6,401 |
1,972 |
4,521 |
|
Other Current Assets |
3,521 |
1,399 |
1,137 |
1,668 |
1,670 |
| |
-------- |
-------- |
-------- |
-------- |
-------- |
| Total
Current Assets |
40,695 |
21,482 |
17,991 |
10,152 |
15,046 |
| |
|
|
|
|
|
| Net
Plant |
17,407 |
10,187 |
5,536 |
2,256 |
5,394 |
| Invest
& Advnces - Equity |
NA |
2,651 |
0 |
1,282 |
NA |
| Invest
& Advnces - Other |
NA |
1,278 |
NA |
6,986 |
690 |
| Intangible
Assets |
1,067 |
0 |
288 |
623 |
0 |
| Other
Assets |
21,963 |
2,588 |
3,884 |
5,519 |
1,012 |
| |
|
|
|
|
|
| Total
Assets |
81,132 |
38,186 |
27,699 |
26,818 |
22,142 |
| |
======== |
======== |
======== |
======== |
======== |
| |
|
|
|
|
|
| |
|
|
|
|
|
|
LIABILITIES AND NET WORTH |
|
|
|
|
|
| |
|
|
|
|
|
| Debt
In Cur Liabilities |
12,957 |
7,011 |
2,125 |
3,536 |
4,897 |
| Accounts
Payable |
4,767 |
6,087 |
2,375 |
577 |
3,417 |
| Income
Taxes Payable |
3,029 |
601 |
1,514 |
0 |
632 |
| Other
Current Liabilities |
13,247 |
4,427 |
4,609 |
3,091 |
1,339 |
| |
-------- |
-------- |
-------- |
-------- |
-------- |
| Total
Current Liabilities |
34,000 |
18,127 |
10,623 |
7,204 |
10,285 |
| |
|
|
|
|
|
| Total
Lt Debt |
9,872 |
NA |
2,579 |
8,424 |
NA |
| Other
Liabilities |
14,005 |
2,188 |
1,059 |
5,753 |
499 |
| Def
Taxes And ITC |
1,627 |
161 |
0 |
0 |
-351 |
| Minority
Interest |
NA |
1,351 |
0 |
843 |
1,594 |
| |
-------- |
-------- |
-------- |
-------- |
-------- |
| Total
Liabilities |
59,504 |
21,827 |
14,261 |
22,224 |
12,027 |
| |
|
|
|
|
|
|
Preferred Stock |
253 |
0 |
0 |
227 |
0 |
|
Common Equity |
21,375 |
9,543 |
13,438 |
4,367 |
8,459 |
| |
-------- |
-------- |
-------- |
-------- |
-------- |
| Total
Stockholder's Equity |
21,628 |
16,359 |
13,438 |
4,594 |
10,115 |
| |
|
|
|
|
|
| Total
Liab. + Net Worth |
81,132 |
38,186 |
27,699 |
26,818 |
22,142 |
| |
======== |
======== |
======== |
======== |
======== |
| Copyright © 1999 Innovative Systems Techniques, Inc.
| Updated January 28, 1999
|


Alki Beach LocationGouramie dhufish, sea devil crocodile icefish grouper gizzard shad smoothtongue kokanee zebra danio. Common tunny bamboo shark zebra loach sawtooth eel; ghost pipefish; Rattail zebra bullhead shark. Hoki snapper, long-whiskered catfish candlefish soldierfish ling cod; cavefish, snake eel. Tripletail; nurse shark pygmy sunfish orange roughy northern lampfish burma danio leatherjacket titan triggerfish gurnard collared dogfish blue danio scythe butterfish. |
|
1st and PikeLyretail sergeant major red snapper eel whitefish nase houndshark, shortnose chimaera channel catfish Asiatic glassfish beluga sturgeon barbel danio.  Southern flounder stickleback trumpetfish píntano cherry salmon pricklefish bango--sea bass bluntnose minnow soapfish hillstream loach gulper eel. Canthigaster rostrata velvet-belly shark sillago mud catfish Black mackerel. |
|
Seattle CenterGouramie dhufish, sea devil crocodile icefish grouper gizzard shad smoothtongue kokanee zebra danio. Common tunny bamboo shark zebra loach sawtooth eel; ghost pipefish; Rattail zebra bullhead shark. Hoki snapper, long-whiskered catfish candlefish soldierfish ling cod; cavefish, snake eel. Tripletail; nurse shark pygmy sunfish orange roughy northern lampfish burma danio leatherjacket titan triggerfish gurnard collared dogfish blue danio scythe butterfish. |
|
Capitol HillMola mola dartfish suckermouth armored catfish wrasse pencilfish barbel red snapper rockfish lenok trumpetfish soapfish stingfish pelican gulper tarpon; stoneroller minnow. Stonecat morwong, moonfish jewelfish striped bass queen parrotfish. Rough pomfret dory, zebra danio, pikeperch longnose sucker Black angelfish Dolly Varden trout ghost flathead mooneye sea lamprey. |
|
SeaTacSpringfish sawfish pike characid snailfish, garibaldi red snapper lemon sole alewife. Blind shark grenadier southern flounder weatherfish white shark rock cod slipmouth. Snake mudhead coolie loach flagtail cuchia baikal oilfish walu, tope finback cat shark velvet-belly shark. Modoc sucker shell-ear alligatorfish sea dragon blacktip reef shark mouthbrooder marine hatchetfish tubeshoulder dragon goby Black pickerel. |
We are a Seattle based bakery pushing the margins of baking!!!


– A Jekyll-based personal blog of publishing articles, Oct 2015
This is a personal blog I made myself to publish my articles, hoping to build a platform to share my ideas with other people. In turn, I can receive reader’s feedback to improve myself, which is also a impulse to push me forward. After finishing
the user research and drawing very simple sketch, I designed and coded the website simultaneously by HTML/CSS/Javascript.
 More than 10 articles has been forwarded by several media platforms or websites, which received good comments and feedback. Furthermore,
the page view of each article is approximately 1000 now.
Personal Blog
– A static portfolio demonstration site, Oct 2014
This is my undergraduate portfolio site. Because I want to show all projects I have done during my undergraduate years to recruiters, I built the site all by myself, which includes 6 projects in total. Each project has four parts: name, introduction, access (account number & passcode) and link.
Features include:
Easy, quick deployment: SAE Cloud server, SVN controls version
I built the site within 3 days during which I learned a lot Front-end coding skills. Most importantly, I realized how to write well-designed codes to reduce workload while increase performance. Meanwhile, the process of design honed my mindset of thinking from user’s viewpoint, such as how to design interesting website that user would like to use.
Static Blog
– A static self-introduction blog, May 2014
This is my first self-designed website. Back then, I just began studying Front-end for 3 months. And because I was studying in Germany, I wanted to write a website to memorize the half year as an exchange student.
The site mainly has 5 parts: scene, song, story, fun and about, which records my according interests.
Features include:
Easy, quick deployment: SAE Cloud server
Well-organized codes: CCS3, original Process-oriented Javascript coding
The site took me about 2 months in total to finish. This was the first time I learned Process-oriented programming (you can check the code of the plane game) which trained my rational thinking a lot, especially how to transfer human language to machine language. Above all, this experience built my confidence that I have ability to design and code stuff through self-studying.
Shopping Site
– A second hand products shopping website, Dec 2015
When I came to University of Kansas, I found many Chinese have the demand to buy second hand products but they lack the channel to find related information. To better help local Chinese, I determined to built information sharing website, through which people can publish products information, search given products, and browse products by category. Therefore, I asked 2 friends to work with together: one is full-stack developer, one is responsible for marketing. And my main job is to manage the team, design the product & interface, improve the usability and maintain relationships with customers.
Our team just published the Beta 1.0. We are planning to develop new functions based on user feedback. So far, we have already 103 loyal customers covering 20% of all Chinese students of KU, and the sessions of website is gradually rising up as well. My goal is to have at least cover 80% of all Chinese students of KU. By then, I would like transfer the site to a profit site. Now, it is non-profit.
Exchange Site
– A bonus point exchange mobile website, Feb 2015
This is a project that I was wholly responsible for when I interned for user experience designer at YiFang Information Co., Ltd. Customers can use bonus point they acquired to exchange real goods on this website. My main job contains user research, analysis for competitive products, product & interface design and interaction prototype design (by Axure). Meanwhile, I needed to cooperate with my manager, user interface designers, and Front-end & Back-end developers to maximize the benefits of the company. To better make the site into practice, I assisted the operation manager to streamline the exchange process.
Features include:
Responsive design: @media attributes
Single page application: Sass, AngularJS, connect Back-end by using restfulAPI, PHP
The website was finished well before the deadline, exceeding my manager’s expectation. And it is still used by the company, which runs well.
Convergent Network Interface
– A harmonious future interface visionDec 2015
This is the final project of interaction design course. We four students work as a team trying to understand how people mentally represent themselves and their interests in the world in relation to their use of technology to meet their needs, interests and desires. We Built personas and scenarios based upon data collected from potential users first. Then we organized ideas through wireframes and interactive video made by Sketch & Invison. By the way, we used Mural, Google docs adn Google Hangout to collaborate with each other.


Hello!
Welcome to your pubhook starter site!
This site uses Web Starter Kit's SASS components for base styling.
Read how to Get Started with WSK or check out the included Style Guide that also reflects the changes you make to WSK's base styles.
Get Started with pubhook.
For a full overview of the components of a pubhook project please check the Github Repo.
{% endblock %}


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The next cosmology seminar takes place on Thursday 7th of April, seminar room E349 at 11am. Our guest speaker will be Fabien Lacasa from the Institut d’Astrophysique Spatiale (Orsay, France).
At 11:00, room E349, Fabien Lacasa (IAS), will be talking about
Cosmology with the cosmic web: the high resolution promise
The large scale structure of the Universe, the cosmic web, is a key probe for late-time cosmology, and is indeed targeted by several of the major observational efforts in the coming decades. However, its analysis is hampered by the complex non-linear dynamics it undergoes as structure grow. A lot of efforts has focused on the impact of non-linearity on the observables, in particular the power spectrum. However, the non-linearity also affects error bars, and thus the information content, by generating non-Gaussian tails that induce new covariance term. After sufficient introduction, I will present a first exhaustive derivation of the covariance of the galaxy angular power spectrum. The impact will then be presented for a baseline cosmological analysis up to mildly non-linear scale, showing decreasing returns. By contrast, I will finally show that there is a large motivation to jump more boldly and push into the strongly non-linear regime at high resolution.


Ceremony
Saturday, September 1st, 20186:00 - 6:45 PM
The Harbor Room, Upstairs
8 Norwood Court
Gloucester, MA 01930
....................
Reception
Saturday, September 1st, 20187:00 - 10:30 PM
The Harbor Room, On The Dock
8 Norwood Court
Gloucester, MA 01930
....................


Mountain biodiversity science
GMBA supports and facilitates mountain biodiversity science via working groups and individual projects. It promotes inter-and transdisciplinary science in various thematic areas.
Mountain biodiversity science: thematic priorities
Mountain biodiversity assessment and monitoring
Globally integrated assessment and monitoring of biodiversity
(species, populations, traits) requires interdisciplinary research and a
close collaboration between observational, remote sensing, and
modelling communities that are collecting and using spatio-temporally
explicit biodiversity or environmental data to capture, report on, and
predict ongoing changes, and to develop integrated knowledge products
(e.g. map layers).
Current efforts focus on providing the mountain biodiversity community
with a platform for mountain biodiversity data visualization, on
supporting long-term monitoring efforts, and on bridging gaps with the
remote sensing community.
Current working groups
- Species distribution modeling and remote sensing
- Promoting Long-Term Ecological Research (LTER) in mountains
- Mountain biodiversity assessment
Past working groups
Mountain biodiversity and global change
Natural disasters in the form of landslides, floods, and avalanches
strike mountains each year, affecting well-defined areas, their habitat
diversity, and their ecosystem dynamics. Habitat and community
regeneration after such natural disturbances is generally relatively
fast. In contrast, climate change and human impact dominate large areas
with often irreversible effects. Of all global change impacts on
mountain biodiversity, land use is likely the most important factor.
Current efforts focus on improving existing knowledge on the protection,
management, and sustainable use of mountain biodiversity in the face of
global change, and on mountain social-ecological systems.
Current working groups
Past working groups
Mountain biodiversity and opportunities for sustainable development
Developing effective valuation, policy, governance, and management
approaches to safeguard the biodiversity underpinning human well-being
in mountains and achieve international sustainable development agendas
requires a common understanding of the interactions between nature and
people particular to given mountain ranges.
Current efforts focus on improving existing knowledge on the importance
of mountain biodiversity for ecosystem functions and services, and
ultimately for human well-being in mountains and beyond.
Current working group
Current project


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Software Developer at Imprint Africa
Imprint Africa is a tech firm keen on availing technology to SMEs whose lack of access
keeps them from participating in global trade and scaling to their fullest potential.
Technology -
Wordpress, Figma, Angular, HTML, Sass, CSS, Flutter, Shopify


--- layout: post title: "Kindle Now Available in Australia (and the rest of the world)" ---
Kindle Now Available in Australia (and the rest of the world)
This is very exciting. I love to read but paying $20 for shipping and having to wait 3 weeks for a book to arrive from Amazon is crazy. Books are unwieldy and the iPhone makes a decent intermediate device but is far from ideal for reading in long stretches. I’ve really come to enjoy reading anything via Instapaper which bodes well for a device dedicated to reading.
I know the basics but I’d held off reading too much about it because I knew it wasn’t a possibility. Time to dive into some reviews, starting with this one from Matt Haughey.