The aim of the study is to examine whether gadget addiction influences adolescent’s family
functioning and its dimensions. Data were collected from 226 adolescents aged 12-18 years old.
We used Smartphone Addiction Scale Short Version (SAS-SV) developed by Kwon et al.
(2013) to measure gadget addiction and Family Assessment Device (FAD) developed by Epstein
et al. (1983) to measure family functioning.
Through great books, workshops, and services, more people each month are beginning to use these techniques to solve crucial problems and build great tools.
How do leading companies manage design in their businesses? Our in-depth study of the design processes used in eleven global brands gives real insights into the way design operates in these firms, and delivers usable lessons for all designers and managers.
Racial justice is the
systematic fair treatment of
people of all races, resulting in
equitable opportunities and
outcomes for all
When political dissent threatens the racial hierarchy, positive and negative, foreseeable and
unforeseeable, glorious and infamous outcomes can transpire
There are fantastic benefits to embracing technology and working
securely online in health and social care. Technology allows greater and
faster information sharing, so we can improve the quality of care and
support which we provide e.g. personalised care planning, transfers of
care, viewing medications, etc. Individuals can fully participate and have
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Potatoes are usually planted in April into warm, loose soil.
The planter moves along the beds planting the potatoes in rows.
1
3NirEyal.Hooked:Howtobuildhabit-formingp
3NirEyal.Hooked:Howtobuildhabit-formingproducts.Penguin,2014ThePowersofHabit4,RichardThalerandCassSunsteinÕsworkon4CharlesDuhigg.Thepowerofhabit:Whywedowhatwedoinlifeandbusiness,volume34.Rand
2
omHouse,2012ChoiceArchitectureinNudge5,D
omHouse,2012ChoiceArchitectureinNudge5,DanArielyÕsworkonBehavioral5RichardHThalerandCassRSunstein.Nudge:Improvingdecisionsabouthealth,wealth,andhappiness.HeinOnline,1999EconomicsinPredictably
3
Irrational6,DanielKahnemanÕspioneering6D
Irrational6,DanielKahnemanÕspioneering6DanAriely.Predictablyirrational.HarperCollinsNewYork,2009workondecisionmakinginThinkingFastandSlow7,RobertCialdiniÕs7DanielKahneman.Thinking,fastandslow
4
.Macmillan,2011Inßuence
It
omputationalN
.Macmillan,2011Inßuence
It
omputationalNeuroscienceRecentresearchhasmadestridesinunderstandingthebrainÕsmotivationmachinery.Thestudyofbrainstructures,chemicals,andcircuitsresponsibleforhowwel
5
earnfromexperience21have21particularlyfr
earnfromexperience21have21particularlyfromreinforcementmadesigniÞcantprogressinthepastdecadefrombasicresearch,medicine,andevenartiÞcialintelligenceandroboticsresearch.Wenowhaveclearerundersta
6
ndingsofhowthebrainformshabits,
muchchea
ndingsofhowthebrainformshabits,
muchcheaperthanyoucouldhavein
themutually-reinforcingrelationshipbetweenacademicscience,high-techcompanies,ispushingtomakesthesetoolseasiertouse.frameworksaref
7
reelyavailable,anyonecanstartusingpatter
reelyavailable,anyonecanstartusingpatterndetectors,predictionengines,andautomationpipelinesthatmighthave,10yearsago,takenseveralPhDÕsworthofinnovation,andonlybeenusablebythehandfulofexpertswh
8
obuiltthem.Bettertoo,dozensoffreevideoco
obuiltthem.Bettertoo,dozensoffreevideocoursesfromleadinguniversitieshelpanyone,globally,startbuildingsophisticatedmachinesthatlearn.2323DaltontookAndrewNgÕsduringgraduateschool.100%recommende
9
d.Today,yourappcansenseauserÕsbehavior.I
d.Today,yourappcansenseauserÕsbehavior.ItcansendthatdatatotheCloudinstantly.ThatdatacanbeprocessedbyPersuasiveAIdesignedtomodifytheirbehavior.ThatAIcaninstantlyrecommendtoyourapphowtomodifyit
10
sdigitalenvironment(itsUX)toinducethatus
sdigitalenvironment(itsUX)toinducethatusertochangehisbehavior.Allofthiscanbebuilt-andoperated-cheaplyandscalably-touchingnotonlythatuserÕsmindbutmillionsofmindsgloballyeverysecond.2424thisisl
11
iterallywhatwedoat
BehavioralDesigncanbe
iterallywhatwedoat
BehavioralDesigncanbeanextremelystrongdrivingforceinbuildingthatworldwhenusedwithinastrongethicalframework.Asfaraswecantell,thereareatleasttwomajorethicalquestionsunderpinn
12
ingBehavioralDesign.1.)IsanyBehavioralDe
ingBehavioralDesign.1.)IsanyBehavioralDesignethicalatall?2.)IsthisparticularuseofBehavioralDesignethical?ÒBehavioralDesignpatternsaredarkorlightdependingonhowyouusethem.DonÕtletthevillainsbet
13
heonlyoneswithsuperpowers.Ó!BehavioralDe
heonlyoneswithsuperpowers.Ó!BehavioralDesignisasetoftechniquesforpersuasion.Itisatechniqueofcoercion.Whenusedproperly,BehavioralDesigntakesadvantageofcognitivebiasestomakeparticularbehaviorsm
14
orelikely:itdoesnotforcecertainactions.I
orelikely:itdoesnotforcecertainactions.Itdoesnotuseviolenceorthreatstochangebehavior.ItdoesnotliterallyrestrictsomeoneÕsabilitytoactornot.Itmerelyprovidestestable,provablewaytoincreasethechan
15
cesthatbehaviorschange:itdoesnotforcecha
cesthatbehaviorschange:itdoesnotforcechange.ItisaTechnologyofBehavior,notaTechnologyofForce.Tothatextent,thetechniquesofBehavioralDesign,andDesignersthemselves,mustrespectpersonsÕintrinsicrig
16
htstofreedomof
AlignmentwithSocialGood3.
htstofreedomof
AlignmentwithSocialGood3.AlignmentwithaUserÕsDesires1.TransparencyBehavioralDesign,andourusesofit,aremostethically-aligned
behaviors.AmbientCommunicationOften,youÕllneedtoprese
17
ntcomplexordenseinformationtosomeone.Amb
ntcomplexordenseinformationtosomeone.AmbientCommunicationprescribesthatusingnon-textcommunication,suchascolor,size,texture,pattern,motion,sound,vibration,ortimecanhelpyoucommunicatecomplexcon
18
tentto
roupStructureIfyourAppconnectspeo
tentto
roupStructureIfyourAppconnectspeopletooneanother,howdoyouknowthebestwayeachuserwouldprefertoexperiencethissocialcomponent?Differentusersexhibitdifferentpreferencesfortheirinteractionsw
19
itheachother:somefeelmostmotivatedalone,
itheachother:somefeelmostmotivatedalone,othersinsmallgroupsofpeers,andsomeinthefullgazeofpublic.OptimalGroupStructureproposesthatthereexistpredictable,optimalscopesandnaturesofinteractivitybe
20
tweenappusersthatwillbestmotivatethemtoc
tweenappusersthatwillbestmotivatethemtochangetheirbehavior.PersonalizationYoumayhaveheardofthehypothesisthatstudentshaveÒlearningstyles,Ó34andthatstudentslearnbestwhenmaterialisadaptedto34Vis
21
ual,Auditory,Tactile,Converger,etc.thats
ual,Auditory,Tactile,Converger,etc.thatstyle.ThathypothesishasbeensoundlyrepeatedlyfalsiÞed.3535ScottOLilienfeld,StevenJayLynn,JohnRuscio,andBarryLBeyerstein.
)mentallyassociatedtotheperforma
22
nceaparticularaction.Youcanthinkofitlike
nceaparticularaction.YoucanthinkofitliketheÒIfthis�ÐthenthatÓpairingofacuetoanaction:ifsensecue,thendoaction.Non-BehavioralDesignersonlyfocusontheactionasthewhole
understandingwhethero
23
rnotauserwillact.HisMATModel3838Dr.FoggÕ
rnotauserwillact.HisMATModel3838Dr.FoggÕsMATModel,onlinesuggeststhatusersperformahabitwhentheyhaveadequate[M]otivation,[A]bility,andinthepresenceofaSynthetic[T]rigger.AsaBehavioralDesigner,yo
24
uneedtobalancehowmotivatedauserisagainst
uneedtobalancehowmotivatedauserisagainsthowdifÞcultataskis.Ifanactionistoohard,theuserwonÕtdoit.Iftheactionistooeasy,thenyouÕvewastedtheuserÕsmotivationalpotential.Theywerereadytodosomethingh
25
ard,butyoudidnÕtaskenoughfromthem.Ideall
ard,butyoudidnÕtaskenoughfromthem.Ideally,yourproductshouldpresentasyntheticcueforanactionthatsomeoneisabletoperformwhentheyÕremotivatedtoact.SomeActionsareeasiertoturnintouserhabitsthanother
26
s.WhenweatBoundlessMindhelpourclientside
s.WhenweatBoundlessMindhelpourclientsidentifywhatactionsinsidetheirappwouldbebesttoturnintoahabit,weusethefollowingcriteria:1.SmallActionsarebetterthanlargeActionsFavorashortactionthatcanbequ
27
icklyaccomplishedoversomethingthattakesa
icklyaccomplishedoversomethingthattakesalotoftime,rigour,focus,energy,orotherscarceresources.Theuserisalmostalwaysbusy.Theyhavetimeforyourapp-andyourhabit-solongasitcouldalreadyÞtintotheirlif
28
e.2.SpecificActionsarebetterthangeneral,
e.2.SpecificActionsarebetterthangeneral,largerbehaviorsWhatuserbehaviorsinyourapplendthemselveswelltobecomingahabit?What
RememberthatonefoodordrinkyoujustCANÕThaveanymorebecauseofthatonetimei
29
tmadeyoureaaaallysick?Yeah.ThatÕsthekind
tmadeyoureaaaallysick?Yeah.ThatÕsthekindofone-shotlearningthebrainÕsgoodatfor
TotheBehavioralDesigner,ÒrewardÓdoesnÕtjustmeansomeprizeearned.ÒRewardÓisbroaderthanagiftorabonusorathingwecanmea
30
sureindollars.AsBehavioralscientistsandB
sureindollars.AsBehavioralscientistsandBehavioralDesigners
OneofSkinnerspigeonsinanoperantchamber.Whenthelightcameon(cue),abirdwouldpeckatthebutton(action)andthebuttonwouldclick(feedback).AtÞ
31
rstbirdsdidthismerelybychance.Butasfoodp
rstbirdsdidthismerelybychance.Butasfoodpellets(reward)beganbeingreleasedaftersomepecks-unexpectedly-thebirdsquicklylearned.Somebirdsgotapelleteverypeck.Somegotpelletsveryrarely.Some,inbetween
32
.Somegotapelleteveryfewminutes,somegotap
.Somegotapelleteveryfewminutes,somegotapelletatrandomtimes.Somegotapelletafterevery3rdpeck.Somegotapelletafterarandomnumberofpecks.Skinnernoticedsomethingfascinating.Somebirdsstartedpeckingmu
33
ch,muchmorethanothers.!"#$Thepelletswere
ch,muchmorethanothers.!"#$Thepelletswereallthesame.Thebirdswerelargelysimilartooneanother.Sowhataccountsforthedifference?Hefoundthatthepatternofpeck"pelletorpeck"no-pellet47waschangingtheirpe
34
cking.47HecalledtheseÔschedulesofreinfor
cking.47HecalledtheseÔschedulesofreinforcementÕThebirdsthatreceivedpelletsafteraseeminglyrandomnumberofpecks(whathecalledaVariableRatioreinforcementschedule)learnedtoassociatethesyntheticcuel
35
ightwiththebutton-peckactionmuchfasterth
ightwiththebutton-peckactionmuchfasterthananyoftheothergroupsofbirds.Andtheypeckedmuch,muchmore.Theirfuturepeckingwasbeingactivelyprogrammedbytheconsequencesoftheiractions(overwhichheheldcont
36
rol.)NotonlydidSkinnerhaveevidencethatbe
rol.)NotonlydidSkinnerhaveevidencethatbehaviorisshapedbyreward,hefoundthatthepatternofreward-whenandhowitÕsgiven-wascriticaltoshapingbehavior.AfewyearsearlieratMcGillUniversity,Drs.OldsandMil
37
nertookamoredirectapproachtoshapingbehav
nertookamoredirectapproachtoshapingbehavior.Theyskippedthetaste-budsentirelyandinsteadplacedelectrodesdirectlyintoratsÕbrains.48ElectricalstimulationintheSeptumbrainregionwould48SpeciÞcally,t
38
heyplacedtheelectrodesintoabrainregionkn
heyplacedtheelectrodesintoabrainregionknownastheSeptum(locatedimmediatelybeneaththeBasalGangliaÕsmainpleasurecenter).causetheemotionalsensationofpleasurefortherats.Thentheygavetheratsasmallle
39
vertheycouldpush.Thatleverwouldsendaburs
vertheycouldpush.ThatleverwouldsendaburstofelectricitytotheSeptum.Andman,theratÕsLOVEDthatlever.Infact,theratswouldpressithundredsoftimesanhour.Sometimeseventhousandsof
RewardsoftheHuntReward
40
softheHuntsatisfyourdesireforconquest.Th
softheHuntsatisfyourdesireforconquest.Thegainsofvictory.Thesetiecloselytotheprimaryreinforcersthatourbrainsevolvedbecausetheymostcloselymimicreality(hence,thenameHunt.)BehavioralDesignersofte
41
nuseRewardsoftheHuntingames,insettingswi
nuseRewardsoftheHuntingames,insettingswithcompetition,and(surprisingly),insituationswherethenextblastofdopaminemightbejustafewswipesaway.5252WeÕrelookingatyou,Tinder.Dotheuseractionsinyourapp
42
haveanobviouscomponentofcompetition?Dous
haveanobviouscomponentofcompetition?Dousersseekinsideyourapp?Arethecorebehaviorsyouneedtoincreasepartofagame?Partofachase?Ifso,whatsortofRewardoftheHuntcanyouimplementtosurpriseanddelightthem
43
?R
maximizegainsfromyourcurrentusers,ita
?R
maximizegainsfromyourcurrentusers,itactivelyhelpsyougrow
DevelopingaCultureofExperimentation,aworkenvironmentwherepeopleareinformed,empowered,andrewardedforexperimentation,iscriticalforsuc
44
cess.AsManagement,itÕsyourjobtocreatethe
cess.AsManagement,itÕsyourjobtocreatetheemotionalandoperationalspacethathelpsProduct,Design,andEngineeringTeamsexperiment.Forthemtobecreative,takerisks,andlearnastheyiterate.IfyouÕreusingaLea
45
norAgiledevelopmentmethodology,muchofthi
norAgiledevelopmentmethodology,muchofthismightfeelintuitive.TrackingexperimentationandtinkeringasaninternalperformancemetriccanshowyouifyouÕresucceedinginbuildingaCulturethatencouragespeoplet
46
oexperimentandlearn,andforgivesandunders
oexperimentandlearn,andforgivesandunderstandswhenthingsgosideways.
Goal3:PushNotiÞcationsareOwnedbyProduct,notbyMarketing.Forhistoricalreasons,MarketingandMessagingTeamsoftenownresponsibility
47
foraProductÕsuserretention.Thisismostcom
foraProductÕsuserretention.ThisismostcommoninteamsthatstartedaftertheadventoftheWeb,butbeforetheriseofMobile.BeforeMobile,theseteamsusedemailtore-engagelostusers,ormarketnewproductstoretained
48
users.WhenPushNotiÞcationscameout,itseem
users.WhenPushNotiÞcationscameout,itseemedlikeanaturalÞt:PushNotiÞcationswerejustre-engagementemails,butfaster.SothesameMessagingandMarketingTeamsbecameresponsiblefordesigningandsendingPushNo
49
tiÞcations,andbyextension,userretention.
tiÞcations,andbyextension,userretention.. ! . . . Weunderstandhowthiscametobe,wejustthinkitÕsaterriblesetup.ThisturnedPushNotiÞcationsintoachannelforspam.Spamthatjusthappenedtob
50
eclosertousersÕbrains.ItcreatedthePush-o
eclosertousersÕbrains.ItcreatedthePush-overloadworldweliveintoday.ItexplainswhyPusharejustoftentreatedassmallercrappieradvertisements,insteadofthoughtofascues.
Segmenting
arerun.Werecommendse
51
gmentingaportionofyouruserbasetoconducta
gmentingaportionofyouruserbasetoconductarolloutexperiment.Deploythenewchangestothatsegment.MeasurehowuserbehaviorKPIsarechangingovertime,andhowthesechangesaredifferentbetweenthewholeuserbasea
52
ndtheexperimentalsegment(or,betweenacont
ndtheexperimentalsegment(or,betweenacontrolgroupandatreatmentgroupintheexperimentalsegment).IfsheseesstatisticallysigniÞcantchangesinuserbehaviorthatcorrelatewiththechange(andnoothermodiÞcati
53
ons,norchance),thatÕsasignalthattheinter
ons,norchance),thatÕsasignalthattheinterventionisworkingasdesigned!Sheshouldfeelempoweredscalingoutthedeployedchangetotheentireuserpopulation.Repeat!Often!IfthemeasuredbehavioralKPIsarenÕtcha
54
nging,orarechanginginwaysthatsuggestthey
nging,orarechanginginwaysthatsuggesttheyÕrehurtingengagementandretention,shecanrollbackthedeployment,documentwhathappened,explorerootcauses,andreturnagainwithadifferentexperiment.Noharmdone:s
55
omethingextremelyvaluablewaslearned.
Int
omethingextremelyvaluablewaslearned.
Inthisexample,aKPIyoumightconsidertrackingforthisteammaybehowsubtleofachangeinuserengagementcanbeaccuratelypredictedbythetooltheyÕredeveloping.Astheyexper
56
imentanditerateandexperimentanditerate,y
imentanditerateandexperimentanditerate,youcouldexpectthemtomakesomequantiÞableprogresstowardimprovingthetoolÕsprecisionandaccuracyatpredictinguserengagementchanges.If,evenwithmorework,theirto
57
olÕspredictionsdonÕtbecomemoreaccuratewi
olÕspredictionsdonÕtbecomemoreaccuratewithtime,itÕslikelythatÕsasgoodasthemeasureisgoingtoget,andtheteamshouldstartworkingonadifferentgoal.BecausetheyÕrelargelyoperatingattheedgeofbothhumanun
58
derstanding,andtechnology,theirworkwillo
derstanding,andtechnology,theirworkwilloftenresembleacademicresearchmorethananything.Because,tobefair,theyÕreliterallybuildingtoolsnooneÕsevermadetosolveproblemsnooneconsideredsolvable.CutÔem
59
someslack.Considerfosteringcollaboration
someslack.ConsiderfosteringcollaborationsbetweentheseDataScienceTeamsandotherinternalteamswitheventslikeinternalsymposiaanddatahackathons.Thesewillgivethedatascientistsvisibilityonwhatproblem
60
sotherteamsareseeing,andshowtheotherteam
sotherteamsareseeing,andshowtheotherteamswhatkindofproblemstheDataScienceTeamisabletosolve.Also,Ô20%timeÕthatallowstheDataScienceTeamfreedomtotinkercancreatethekindofinnovationthatmanagementd
61
idnÕtknowtoaskfor.6767Alotofgreatscience
idnÕtknowtoaskfor.6767Alotofgreatsciencestartswithabeeranddoodles.Trustus.WeÕre
ehavioraliststoFloatOnceyourProductteamhasincorporatedBehavioralDesigndeeplyintotheirprocessesandtools,theBehav
62
orialistsandpolymathsyouÕvestaffedupwith
orialistsandpolymathsyouÕvestaffedupwithshouldbeallowedtodissociatefromtheProductTeamtofocustheirattentiononyourotherbusinessprocesses.Grantthemtheirownbudget,aplacethemorthogonaltoyourstanda
63
rdorganizationchart(perhapsreportingtoaC
rdorganizationchart(perhapsreportingtoaCTOorCOO),butnoimmediateabilitytoforcechanges.Treatthemlikeunderpowered,in-houseconsultants.TheirfreedomtounhookfromProductandobservehowotherhuman-facin
64
gpartsofthebusinessoperatewillnotjustspr
gpartsofthebusinessoperatewillnotjustspreadthesetechniquesandtheirimpacttotherestofyouroperations,itwillencouragethetypeoflateralthinkingthatwilldrivefutureinnovationbackwithintheProductTeami
65
tself.OnceotherteamsarefamiliarwiththeBe
tself.OnceotherteamsarefamiliarwiththeBehaviorTeam,andtrusthasbeenestablished,encouragetheBehaviorTeamtoproviderecommendationstotheseotherbusinessunits,andincentivizethe
certainpredictableway
66
s.Inthischapter,weexploreseveralexamples
s.Inthischapter,weexploreseveralexamplesofProductsandEnvironmentsyouÕrealreadyfamiliarwith,andhighlighttheBehavioralDesigntechniquestheyÕveusedtoengineerhowpeoplebehave.ReinforcementLearninga
67
ndCues:FacebookFacebookhasmasterfullyemp
ndCues:FacebookFacebookhasmasterfullyemployedBehavioralDesigntechniquestobuildoneofthemosthabit-formingproductsonanyoneÕsphone.WhiletheyÕveusedseveraldifferenttechniques,wefocushereontwo:Rein
68
forcementLearningandCues,whichtheyÕvecom
forcementLearningandCues,whichtheyÕvecombinedtogetheranimplementationofCARModel.ÒPINGÓyouhaveanewnotiÞcation!CananyonereallyresisttheurgetoopentheappandseewhatÕsinside?!ThatnotiÞcationstartst
69
henextchainofeventstounfold:youunlockyou
henextchainofeventstounfold:youunlockyourphone,ÞndtheFacebookApp,andopenit.AsdescribedbytheCARModel,youÕrepresentedwithaSyntheticCue(acuedesignedbyFacebookthattheycontrol),andyouperformthedes
70
iredtargetAction.Then,whenyouopentheapp,
iredtargetAction.Then,whenyouopentheapp,therearenotiÞcationswaitingforyou.And,maybe,oneofthenotiÞcationsisdelightful!Here,FacebookemployedReinforcementLearningtocarefullyinduce
AtBoundlessMin
71
d,weexploredthisconceptwithourapp,Space.
d,weexploredthisconceptwithourapp,Space.WewereinterestedinhelpingpeopleregaincontroloftherelationshipstheyhavewithappsbychangingtheimpactoftheCARModel.StimulusDevaluationoperatesbyincreasingt
72
hetimedelaybetweenanactionandthereinforc
hetimedelaybetweenanactionandthereinforcementthatauserreceivesforthatinteraction.AsdiscussedinChapters2
rewardingstimuli,whiledecreasingthechancethattherewardcan
,theleadingcausesofdeathwerei
73
nfectiousdiseases.Men,women,andchildrens
nfectiousdiseases.Men,women,andchildrensufferedTyphoid,Pneumonia,Fever,Tuberculosis,andInßuenza.Wediedofpathogens70inourwaterandfoodandurbanairfromwhichwe70forwhichwebarelyhadnamesyethadlittl
74
echoicebuttosuccumb.Andthensomethingbrav
echoicebuttosuccumb.Andthensomethingbravehappened.WetookseriouslytodevelopingarigorousTechnologyoftheBody.Tomodernmedicine,sanitization,andvaccination.Wechallengedourpreviouslyheldnormsofthes
75
anctityofbody,andmenandwomenworldwidein
anctityofbody,andmenandwomenworldwidein
BJFogg.PersuasiveTechnology:UsingComputerstoChangeWhatWeThinkandDo.MorganKaufmann,2002.BillGates.Gatesnotes.URLhttps://www.gatesnotes.com/.JohnGeake.Ne
Pursley Forte Design Systems pursleyForteDScom INTRODUCTION Recently behavioral design and synthesis as seen a re emergence in the design comm unity especially in the design of cutting edge imaging consumer electronics and digital signal processing
Through great books, workshops, and services, more people each month are beginning to use these techniques to solve crucial problems and build great tools.
The design of digital 57356lters in olv es three basic steps The sp eci57356cation of the desired prop erties of the system The appro ximation of these sp eci57356cations using causal discretetime system The realization of these sp eci57356cations u
Synthesis of Control Circuits. by A. . . Steininger. and J. . Lechner. Vienna University of Technology. Lecture "Advanced Digital Design" . © A. Steininger & J. Lechner / TU Vienna. 2. Outline.
Asynchronous EDA. by A. . . Steininger. , J. . Lechner. and R. . Najvirt. Vienna University of Technology. Lecture "Advanced Digital Design" . © A. Steininger & J. Lechner & R. Najvirt / TU Vienna.
DataPath. Engine Group Project. Matt Slowik. Porting DPE to Xilinx FPGA environment, Component Integration. test_dpe_top.v. dpe_top.v. DP. RQS. QS. CTL. t. op.v. driver. User application. top_debug.v.
GALS Design. Andreas Steininger. Vienna University of Technology. Lecture "Advanced Digital Design". © A. Steininger & M. Delvai / TU Vienna. 2. Outline. Global . synchrony. & . clock. . distribution.
Visual Design – Project 1. Collages & Photography. Project Overview. To produce quality images for print, web, & video, you need to understand essential graphic design principles & how digital images are created.
© 2014 Project Lead The Way, Inc.. Digital Electronics. What are Digital Devices?. 2. A digital device contains an electrical circuit that uses discrete (exact) values in its design and function.. These discrete values are usually zero’s (0) and one’s (1)..
Tinoosh. . Mohsenin. CMPE . 650. Spring . 2013. Today. Administrative items. Syllabus . and course overview. Digital . systems and optimization overview. 2. Course Communication. Email. Urgent . announcements.
Shogren. , J. F. and L. O. Taylor (. 2008. ).. About the authors . Jason . Shogren. . Stroock. . Professor of Natural Resource Conservation and Management, Economics & Finance, College of Business University of Wyoming.
Description Methods. by A. . . Steininger. , J. . Lechner. and R. . Najvirt. Vienna University of Technology. Lecture "Advanced Digital Design" . © A. Steininger & J. Lechner / TU Vienna. 2. Outline.
Richard Wilson. The Centre For Design Innovation. Horizon Scotland. The Enterprise Park. Forres. Moray. IV36 2AB. UK. Horizon Scotland. CENTRE FOR DESIGN INNOVATION. Where is the CDI. Disconnected?.
Xerox Design for Digital Satis64257 ed customers Thats the key to growing your business When it comes to digital printing your customers want great quality fast turnaround and no surprises Our Design for Digital Training Class helps ensure you can d
Design Science Research Process. as an approach to addressing. Digital Fluency . for Academic staff at. Open University of . T. anzania. Brenda Mallinson. 24-25 June 2014. Design Science Research explored -.
Expand patient care and improve practice efficiency. the care team is better able to meet the needs of the . patient. .. When . medical services. meet . behavioral and lifestyle issues. ,. 2. higher quality patient care.
1 Digital control system design Sampleddata closedloop ZOH ZOH equivalence ZOH ZOH 2014525 132 brPage 2br Zeroorder hold equivalence transfer function ZOH ZOH Input 0 0 u step step Output Ts We now sample this and take the transform ZOH Ts 1 201
Key messages about Digital Technologies. Digital Technologies is a new curriculum (F to 10). Digital Technologies is as much about using different ways of thinking as it is using different digital systems .
Conditioned Reflex Mimic Circuit Design. Gengyu. Yang. 2013.5.10. Outline. Introduction. Digital Circuit Design. Circuit . Design Using RRAM. Comparison and Discussion. Conclusion. Outline. Introduction.
. Makey. & Scratch. My Take on STEM… . I am presuming it is STEM if we use a minimum of two areas.. Need to ensure chosen areas hit are at an appropriate level. . Units/lessons will not be equally spread across chosen areas..
