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Sergio Saponara

Alessandro De  Gloria Editors

Applications in Electronics

Pervading Industry, Environment and Society APPLEPIES 2018

LectureNotesinElectricalEngineering

Volume550

SeriesEditors

LeopoldoAngrisani,DepartmentofElectricalandInformationTechnologiesEngineering,UniversityofNapoli FedericoII,Napoli,Italy

MarcoArteaga,DepartamentdeControlyRobótica,UniversidadNacionalAutónomadeMéxico,Coyoacán, Mexico

BijayaKetanPanigrahi,ElectricalEngineering,IndianInstituteofTechnologyDelhi,NewDelhi,Delhi,India SamarjitChakraborty,FakultätfürElektrotechnikundInformationstechnik,TUMünchen,München,Germany

JimingChen,ZhejiangUniversity,Hangzhou,Zhejiang,China

ShanbenChen,MaterialsScience&Engineering,ShanghaiJiaoTongUniversity,Shanghai,China

TanKayChen,DepartmentofElectricalandComputerEngineering,NationalUniversityofSingapore, Singapore,Singapore

RüdigerDillmann,HumanoidsandIntelligentSystemsLab,KarlsruheInstituteforTechnology,Karlsruhe, Baden-Württemberg,Germany

HaibinDuan,BeijingUniversityofAeronauticsandAstronautics,Beijing,China GianluigiFerrari,Università diParma,Parma,Italy

ManuelFerre,CentreforAutomationandRoboticsCAR(UPM-CSIC),UniversidadPolitécnicadeMadrid, Madrid,Madrid,Spain

SandraHirche,DepartmentofElectricalEngineeringandInformationScience,TechnischeUniversität München,München,Germany

FaryarJabbari,DepartmentofMechanicalandAerospaceEngineering,UniversityofCalifornia,Irvine,CA, USA

LiminJia,StateKeyLaboratoryofRailTrafficControlandSafety,BeijingJiaotongUniversity,Beijing,China

JanuszKacprzyk,SystemsResearchInstitute,PolishAcademyofSciences,Warsaw,Poland AlaaKhamis,GermanUniversityinEgyptElTagamoaElKhames,NewCairoCity,Egypt TorstenKroeger,StanfordUniversity,Stanford,CA,USA

QilianLiang,DepartmentofElectricalEngineering,UniversityofTexasatArlington,Arlington,TX,USA FerranMartin,Departamentd’EnginyeriaElectrònica,UniversitatAutònomadeBarcelona,Bellaterra, Barcelona,Spain

TanCherMing,CollegeofEngineering,NanyangTechnologicalUniversity,Singapore,Singapore WolfgangMinker,InstituteofInformationTechnology,UniversityofUlm,Ulm,Germany

PradeepMisra,DepartmentofElectricalEngineering,WrightStateUniversity,Dayton,OH,USA SebastianMöller,QualityandUsabilityLab,TUBerlin,Berlin,Germany

SubhasMukhopadhyay,SchoolofEngineering&AdvancedTechnology,MasseyUniversity,Palmerston North,Manawatu-Wanganui,NewZealand

Cun-ZhengNing,ElectricalEngineering,ArizonaStateUniversity,Tempe,AZ,USA

ToyoakiNishida,GraduateSchoolofInformatics,KyotoUniversity,Kyoto,Kyoto,Japan FedericaPascucci,DipartimentodiIngegneria,Università degliStudi “RomaTre”,Rome,Italy

YongQin,StateKeyLaboratoryofRailTrafficControlandSafety,BeijingJiaotongUniversity,Beijing,China GanWoonSeng,SchoolofElectrical&ElectronicEngineering,NanyangTechnologicalUniversity, Singapore,Singapore

JoachimSpeidel,InstituteofTelecommunications,UniversitätStuttgart,Stuttgart,Baden-Württemberg, Germany

GermanoVeiga,CampusdaFEUP,INESCPorto,Porto,Portugal

HaitaoWu,AcademyofOpto-electronics,ChineseAcademyofSciences,Beijing,China

JunjieJamesZhang,Charlotte,NC,USA

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ApplicationsinElectronics PervadingIndustry, EnvironmentandSociety

APPLEPIES2018

ISSN1876-1100ISSN1876-1119(electronic)

LectureNotesinElectricalEngineering

ISBN978-3-030-11972-0ISBN978-3-030-11973-7(eBook) https://doi.org/10.1007/978-3-030-11973-7

LibraryofCongressControlNumber:2019931542

© SpringerNatureSwitzerlandAG2019

Thisworkissubjecttocopyright.AllrightsarereservedbythePublisher,whetherthewholeorpart ofthematerialisconcerned,specificallytherightsoftranslation,reprinting,reuseofillustrations, recitation,broadcasting,reproductiononmicrofilmsorinanyotherphysicalway,andtransmission orinformationstorageandretrieval,electronicadaptation,computersoftware,orbysimilarordissimilar methodologynowknownorhereafterdeveloped.

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ThisSpringerimprintispublishedbytheregisteredcompanySpringerNatureSwitzerlandAG Theregisteredcompanyaddressis:Gewerbestrasse11,6330Cham,Switzerland

Preface

The2018editionoftheConferenceon “ApplicationsinElectronicsPervading Industry,EnvironmentandSociety” washeldinPisa,Italy,onSeptember26–27, 2018,attheCongressCenter “LeBenedettine ” oftheUniversityofPisa.

Theconferencehadthetechnicaland/or financialsupportofUniversityofPisa, UniversityofGenoa,SIE(ItalianAssociationforElectronics),andINTEL.

Theconference,activesince2002,offersanoverviewofElectronicapplications inseveraldomains,demonstratinghowElectronicshasbecomepervasiveandever moreembeddedineverydayobjectsandprocesses.

Inthisedition,about60paperswereacceptedafterareviewprocess,with3 independentreviewsforeachpaper,organizedin8oralsessionsand2poster sessions.Theoralsessionsinvolvedcontributionson AutomotiveElectronics chairedbyProf.M.Grammatikakis, Healthcare&Bio-electronicSystems chaired byProf.A.Solanas, TechnologyandTesting chairedbyDr.T.Erlbacher, Sensors &Transducers chairedbyProf.R.Berta, SignalProcessingSystems chairedby Prof.A.Mansour, WirelessCircuitsandSystems chairedbyProf.E.Ragonese, PowerandThermalElectronics chairedbyProf.M.Conti,and DigitalCircuitsand Systems chairedbyProf.M.Martina.ProfessorF.BellottiandM.RuoRoch chairedthepostersessions.

Theconferencehostedalsothreespecialevents,introducedbyProf.S.Saponara:

• Keynotelecture FromSiliconGatetoMicroprocessorstoAItoConsciousness , heldbyFedericoFaggin,thefatherofthemicroprocessor.

• Roundtable LegacyinAppliedElectronics&Systems withcontributionsfrom multinationalelectronicindustries(Intel,Sitael,HankingElectronics,and AMS).

• Roundtable PerspectivesinEmbeddedandHighPerformanceComputing with contributionsfromSTMicroelectronics,BarcelonaSuperComputing,E4, FagginFoundation,EuropeanProcessorInitiative,andrepresentativeoftheEU commission.

Theproposedpapers,collectedinthisbook,andthetalksandroundtablesofthe specialevents,provethatthecomputing,storage,andnetworkingcapabilitiesof todayelectronicsystemsissuchthattheirapplicationscanfulfilltheneedsof humankindintermsofmobility,health,connectivity,energymanagement,smart production,ambientintelligence,andsmartliving.

Toexploitsuchcapabilities,multidisciplinaryknowledgeandexpertiseare neededtosupportavirtuousiterativecyclefromuserneedstothedesign,prototypingandtestingofnewproductsandservices.Thelatteraremoreandmore characterizedbyadigitalcore.

Thedesignandtestingcyclesgothroughthewholesystemengineeringprocess, whichincludesanalysisofusers’ needs,specifi cationdefinition,veri ficationplan definition,softwareandhardwareco-design,labandusertestingandverification, maintenancemanagement,andlife-cyclemanagementofelectronicsapplications. Thedesignofelectronics-enabledsystemsshouldprovidekeyfeaturessuchas innovation,highperformance,real-timeoperations,andimplementationswith low-costandreducedbudgetsintermsofsize,weight,andpowerconsumption.To succeedinthis,oneofthemostimportantfactorsistheadoptionofasuiteddesign flowandrelatedCAD(Computer-AssistedDesign)tools.Platform-baseddesign andmeetinthemiddlebetweentop-downandbottom-updesign flowsareneeded toful fillthetime-andcost-relatedchallengesofnowadaysmarketscenarios.

AllthesechallengingaspectscallfortheimportanceoftheroleofAcademiaasa placewherenewgenerationsofdesignerscanlearnandpracticewith cutting-the-edgetechnologicaltoolsandarestimulatedtodevisesolutionsfor challengescomingfromavarietyofapplicationdomains,suchashealthcare, transportation,education,tourism,entertainment,culturalheritage,andenergy.

TheAPPLEPIES2018conferencewantstoreportanddiscussseveralexamples ofdesignsandbecomeareferencepointinthe fieldofelectronicssystemsdesign andapplications,tryingto fillatscientificandtechnologicalR&Dlevelagapthat themostfarsightedindustrieshavealreadyindicatedandarestrivingtocover. Pisa,ItalySergioSaponara

PartIAutomotiveElectronics

RaspberryPi3PerformanceCharacterizationinanArtificialVision AutomotiveApplication 3 AhmadKobeissi,FrancescoBellotti,RiccardoBerta andAlessandroDeGloria

AnalysisofCybersecurityWeaknessinAutomotiveIn-Vehicle NetworkingandHardwareAcceleratorsforReal-Time Cryptography ............................................. 11

LucaBaldanzi,LucaCrocetti,MatteoBertolucci,LucaFanucci andSergioSaponara

TestingFacilityfortheCharacterizationoftheIntegration ofE-VehiclesintoSmartGridinPresenceofRenewableEnergy 19 PaoloFerrari,AlessandraFlammini,MarcoPasetti,StefanoRinaldi, FlavioSimonciniandEmilianoSisinni

On-the-FlySecureGroupCommunicationonCANBus 27 M.D.Grammatikakis,N.Mouzakitis,E.Ntallaris,V.Piperaki,K.Patelis andG.Vougioukalos

PartIIHealthcareandBio-electronicSystems

NeuromuscularDisordersAssessmentbyFPGA-BasedSVM Classi ficationofSynchronizedEEG/EMG .......................

37 DanielaDeVenutoandGiovanniMezzina

FunctionalNearInfraredSpectroscopySystemValidation forSimultaneousEEG-FNIRSMeasurements ....................

45 G.C.Giaconia,G.Greco,L.Mistretta,R.Rizzo,A.Merla, A.M.Chiarelli,F.ZappasodiandG.Edlinger

Electro-PhotonicChip-ScaleMicrosystemforLabel-FreeSingle BacteriaMonitoring 53

FrancescoDell’Olio,DonatoConteduca,MicheleCito,GiuseppeBrunetti, CaterinaCiminelli,ThomasF.KraussandMarioN.Armenise

HGIS:AHealthcare-OrientedApproachtoGeographicInformation Systems ................................................. 59

EdgarBatista,AntoniMartínez-Ballest é,MartaPeña,XavierSingla andAgustiSolanas

PartIIITechnologyandTestingIssues

MainParasiticEffectsinContactlessWaferTesting 69 AlessandroFinocchiaro,GiovanniGirlando,AlessandroMotta, AlbertoPaganiandGiuseppePalmisano

StudyofLow-DoseLong-ExposureGammaRadiationEffectsonInP DBRCavityLasersfromGenericIntegrationTechnology 77 F.Gambini,N.Andriolli,V.Nurra,M.Chiesa,F.PetroniandS.Faralli

TechnologicalAdvancesTowards4H-SiCJBSDiodesforWindPower Applications .............................................. 83

JonasBuettner,TobiasErlbacherandAntonBauer

PartIVSensorsandTransducers

AScalable2D,LowPowerAirflowProbeforUnmannedVehicle andWSNApplications ...................................... 93

PaoloBruschi,AndreaRiaandMassimoPiotto

ElectronicsSystemforVelocityProfileEmulation 101 DarioRusso,ValentinoMeacciandStefanoRicci

AnUltra-LowCostTriboelectricFlowmeter 109 AlessandroBertacchiniandPaoloPavan

Electro-ThermalCharacterizationandModelingofa4-Wire MicroheaterforLab-on-ChipSystems 117 AndreaScorzoni,PisanaPlacidi,PaoloValigiandNicolaLovecchio

PartVSignalProcessingSystems

TowardtheRealTimeImplementationofthe2-DFrequency-Domain VectorDopplerMethod ..................................... 129

StefanoRossi,MatteoLenge,AlessandroDallai,AlessandroRamalli andEnricoBoni

AFieldExperimentofRainfallIntensityEstimationBased ontheAnalysisofSatellite-to-EarthMicrowaveLinkAttenuation 137 M.Colli,M.Stagnaro,A.Caridi,L.G.Lanza,A.Randazzo,M.Pastorino, D.D.CavigliaandA.Delucchi

AFaceRecognitionSystemUsingOff-the-ShelfFeatureExtractors andanAd-HocClassifi er .................................... 145

StefanoMarsi,LucaDeBortoli,FrancescoGuzzi,JhilikBhattacharya, FrancescoCicala,SergioCarrato,AlfredoCanziani andGiovanniRamponi

TwiddleFactorGenerationUsingChebyshevPolynomialsandHDL forFrequencyDomainBeamforming ...........................

GhattasAkkad,AliMansour,BacharElHassan,FredericLeRoy andMohamadNajem

PartVIWirelessCircuitsandSystems

ALoRaWANWirelessSensorNetworkforDataCenter

TommasoPolonelli,DavideBrunelli,AndreaBartoliniandLucaBenini WirelessLowEnergySystemArchitectureforEvent-DrivenSurface

FabioRossi,PaoloMottoRos,StefanoSapienza,PaoloBonato, EmilioBizziandDaniloDemarchi

ActivityMonitoringandPhaseDetectionUsingaPortable EMG/ECGSystem .........................................

WulhelmDanielScherz,RalfSeepold,NatividadMartínezMadrid, PaoloCrippa,GiorgioBiagetti,LauraFalaschettiandClaudioTurchetti

TransformerDesignfor77-GHzDown-Converterin28-nm FD-SOICMOSTechnology

AndreaCavarra,ClaudioNocera,GiuseppePapotto,EgidioRagonese andGiuseppePalmisano

PartVIIPowerandThermalElectronics

InvestigatinganActiveCoolingSystemPoweredbyaThermoelectric Generator ................................................

PietroTosato,MaurizioRossiandDavideBrunelli

ASmartTorqueControlforaHighEfficiency4WDElectric Vehicle ..................................................

AntonioCordopatriandGiuseppeCocorullo

ExperimentalAnalysisofBatteryManagementSystemAlgorithms ofLi-ionBatteries

221 FedericoGarbuglia,MatteoUnterhorst,LucaBuccolini,SimoneOrcioni andMassimoConti

PartVIIIDigitalCircuitsandSystems

DesignofLow-PowerApproximateLMSFilters withPrecision-Scalability ....................................

237 DarjnEsposito,GennaroDiMeo,DavideDeCaro,AntonioG.M.Strollo andEttoreNapoli

AnOptimizedPartial-Distortion-EliminationBasedSum-of-AbsoluteDifferencesArchitectureforHigh-Efficiency-Video-Coding 245 PaoloSelvo,MaurizioMasera,RiccardoPeloso,GuidoMasera, MuhammadShafi queandMaurizioMartina

EfficientEnsembleMachineLearningImplementationonFPGA UsingPartialReconfiguration 253 GianCarloCardarilli,LucaDiNunzio,RoccoFazzolari,DanieleGiardino, MarcoMatta,MarcoRe,FrancescaSilvestriandSergioSpanò SynthesisTimeReconfi gurableFloatingPointUnitforTransprecision Computing ...............................................

GiuliaStazi,FedericaSilvestri,AntonioMastrandrea,MauroOlivieri andFrancescoMenichelli

RadiationHardnessbyDesignTechniquesfor1GradTIDRad-Hard Systemsin65nmStandardCMOSTechnologies ..................

261

269 GabrieleCiarpi,SergioSaponara,GuidoMagazzù andFabrizioPalla

PartIXPosterSession

Context-AwareEnvironmentsinPassengerTrainTransportation Systems:Ideas,FeasibilityandRisks 279 FranciscoFalcone,CostasPatsakisandAgustiSolanas

AutomaticPerishableGoodsShelfLifeOptimization inNo-RefrigeratedWarehousesbyUsingaWSN-Based Architecture ..............................................

DanielaDeVenutoandGiovanniMezzina

FPGA-BasedMultiCycleParallelArchitectureforReal-Time ProcessinginUltrasoundApplications ..........................

287

295 ValentinoMeacci,EnricoBoni,AlessandroDallai,AlessandroRamalli, MonicaScaringella,FrancescoGuidi,DarioRussoandStefanoRicci

AdaptiveTuningSystemandParameterEstimationofaDigitally ControlledBoostConverterwithSTM32 303

GianpaoloVitale,AntoninoPagano,LeonardoMistretta andGiuseppeCostantinoGiaconia

DevelopingaMachineLearningLibraryforMicrocontrollers ........ 313 AndreaParodi,FrancescoBellotti,RiccardoBerta andAlessandroDeGloria

TheCaseforRISC-VinSpace ................................ 319 StefanoDiMascio,AlessandraMenicucci,GianlucaFurano, ClaudioMonteleoneandMarcoOttavi

Encoder-MotorMisalignmentCompensationforClosed-LoopHybrid StepperMotorControl 327 StefanoRicci,ValentinoMeacci,DarioRussoandRiccardoMatera

FullyIntegratedGalvanicallyIsolatedDC-DCConverters BasedonInductiveCoupling 335 EgidioRagonese,AlessandroParisi,NunzioSpina andGiuseppePalmisano

ADistributedConditionMonitoringSystemfortheNon-invasive TemperatureMeasurementofHeatFluidsCirculating inTurbomachineryPipesBasedonSelf-PoweredSensingNodes ...... 343 TommasoAddabbo,EliaLandi,RiccardoMoretti,MarcoMugnaini, LorenzoParriandMarcoTani

TowardsSubseaNon-ohmicPowerTransferviaaCapacitor-Like Structure ................................................

AnwarMohamed,ValentinaPalazzi,SunnyKumar,FedericoAlimenti, PaoloMezzanotteandLucaRoselli

349

ARobustSensingNodeforWirelessMonitoringofDrinking WaterQuality 359 LorenzoMezzera,MicheleDiMauro,MarcoTizzoni,AndreaTurolla, ManuelaAntonelliandMarcoCarminati

Doubly-BalancedGilbertCellDown-ConversionMixerinAMS 0.35 lmSiGeCMOSforMode-1MB-OFDMUWBReceivers 367 S.Cammarata,G.Fieramosca,B.Neri,F.BarontiandS.Saponara

EfficientImplementationofRecurrentNeuralNetwork Accelerators .............................................. 375

VidaAbdolzadehandNicolaPetra

UltrasoundMeasurementofthePeakBloodFlowBased onaDopplerSpectrumModel ................................ 383 RiccardoMatera,DavidVilkomersonandStefanoRicci

EmbeddedSystemtoRecognizeMovementandBreathinginAssisted LivingEnvironments 391

EvaRodríguezdeTrujillo,RalfSeepold,MaksymGaiduk, NatividadMartínezMadrid,SimoneOrcioniandMassimoConti

EnergyHarvestingwithCurrentSensorstoSustainEmbedded IoTPlatforms ............................................. 399

MatteoNardelloandDavideBrunelli

APXIBasedImplementationofaTLK2711EquivalentInterface ..... 407 PietroNannipieri,LucaDelloSterpaio,AntoninoMarino andLucaFanucci

AnFPGA-BasedReal-TimeAcquisitionSystemforaDistributed AcousticSensorBasedon U-OTDR 415 FrancescoMartina,YonasMuanenda,StefanoFaralli andFabrizioDiPasquale

Sound-BasedDetectionandRangingSystemasExampleApplication ofaRapidPrototypingandLow-CostTechnologyforBoard-Level ElectronicSystemsEducation 421

StefanoDiPascoli,GabrieleCiarpiandSergioSaponara ApproximateMemorySupportforLinuxEarlyAllocators inARMArchitectures ...................................... 429 GiuliaStazi,AntonioMastrandrea,MauroOlivieri andFrancescoMenichelli

FullyDigitalLow-PowerImplementationofanAudioFront-End forPortableApplications .................................... 437 GabrieleMeoni,LucaPilato,GabrieleCiarpi,AlessandroPalla andLucaFanucci

ComparisonandImplementationofVariableFractionalDelayFilters forWidebandDigitalBeamforming 445 GianCarloCardarilli,DanieleGiardino,MarcoMatta,MarcoRe, FrancescaSilvestri,LorenzoSimoneandSergioSpanò

AutonomousSailSurfaceBoats,DesignandTestingResults oftheMOUNTAINSPrototype 453 EnricoBoni,MarcoMontagniandLucaPugi

ALowCostALSandVLCCircuitforSolidStateLighting ......... 461 MassimoRuoRochandMaurizioMartina

ChamberlinState-VariableFilterStructureinFPGAforMusical Applications .............................................. 469

AdrianaRicci,MattiaSilvestrini,MassimoConti,MarcoCaldari andFrancoRipa

BrakeBlendingandOptimalTorqueAllocationStrategies forInnovativeElectricPowertrains 477

LucaPugi,TommasoFavilli,LorenzoBerzi,EdoardoLocorotondo andMarcoPierini

SmartCoaster:AnExampleofIoTDesignandImplementation ...... 485 MaurizioRossi,MatteoNardelloandDavideBrunelli

IPGeneratorToolforEfficientHardwareAcceleration ofSelf-organizingMaps ..................................... 493

DanieleGiardino,MarcoMatta,MarcoRe,FrancescaSilvestri andSergioSpanò

AuthorIndex 501

RaspberryPi3Performance

CharacterizationinanArtificialVision AutomotiveApplication

AhmadKobeissi,FrancescoBellotti,RiccardoBerta andAlessandroDeGloria

Abstract Artificialvisionisakeyfactorfornewgenerationautomotivesystems. Thispaperfocusesonamoduleaimedatmaximizingtheenergyflowbetweenthe transmittingandreceivinggrids,inthecontextofdynamicwirelesschargingofelectricalvehicles.Theoutputofthemodulehelpsthedrivertokeepaprecisealignment betweenthevehicleandthecharginggridsintheroad.Themodulewasdeveloped usinglowcostandopenhardwareandsoftwarecomponents.Thispaperprovides acharacterizationoftheembeddedsystemfromaperformancepointofview,consideringvariousparameters,suchasCPUload,memoryfootprint,andenergyconsumption,inviewofassessingtheRaspberryPiasaplatformforembeddedrapid prototypingandcomputinginautomotiveenvironment.

1Introduction

Alsothankstothepowerofdeeplearningtechnologies,artificialvisionisakey factorfornewgenerationautomotivesystemsreachinghigherautomationlevels[1]. Thispaperconsidersaparticularvisionapplication,fordynamicwirelesscharging ofelectricalvehicles[2, 3].InthiscontextofInductivePowerTransfer(IPT),it isnecessarytopreciselyalignthereceivingcoil,placedunderthevehicle,andthe transmittingcoils,thatareburiedintheasphaltinaspecificroadlane[4].Thegoal istomaximizetheenergyflowbetweenthecoils,keepingthedisplacementwithin

A.Kobeissi(B) F.Bellotti R.Berta A.DeGloria DITEN,UniversitàDegliStudiDiGenova,ViaOperaPia11/a,16145Genoa,Italy

e-mail: ahmad.kobeissi@elios.unige.it

F.Bellotti

e-mail: franz@elios.unige.it

R.Berta

e-mail: berta@elios.unige.it

A.DeGloria

e-mail: ADG@elios.unige.it

©SpringerNatureSwitzerlandAG2019

S.SaponaraandA.DeGloria(eds.), ApplicationsinElectronics PervadingIndustry,EnvironmentandSociety,LectureNotesinElectrical Engineering550, https://doi.org/10.1007/978-3-030-11973-7_1

±20cm.(withrespecttoawidthofthetransmitterof50cm),ashighermisalignments typicallycausedropsinenergytransfer[5].

InthecontextoftheFabricproject[6],wehavedevelopedasubsystemaimedat helpingthedrivertokeepaprecisealignmentbetweenthevehicleandthecharging gridsintheroad.

Thesub-systemwasdevelopedusinglowcostandopenhardwareandsoftware componentsandgaveusanopportunitytoassesstheRaspberryPiasaplatformfor embeddedrapidprototyping.Thispaperpresentsourdevelopmentexperienceand focusesonprovidingacharacterizationoftheRaspberryPi3single-boardPC[7] fromaperformancepointofview,consideringvariousparameters,suchasCPUload andmemoryfootprint,instructionpercycle,energyconsumption.

2RelatedWork

Carmanufacturersarestrivingtobuildsmartvehicles,exploitingmassiveamounts ofdatafromawidevarietyofhardwarecomponents,includingsensors,onboard cameras,andfurtherexternalsources[8].Thesedataareprocessedonthecloud oron-board.Alsoaccordingtotheemergingedge-computingparadigm[9, 10],it islikelythatagrowingamountofcomputationwillbedoneon-board,bymeans oflow-costandenergyefficient(lowenergy)microcomputerdevices,suchasthe RaspberryPi[11],thathaverecentlyspreadinseveralapplicationdomains(e.g., inhigh-precisionagriculture[12]).Hassan[13]stressesthat“Thedramaticdropin priceofcomputinghardware,coupledwiththerecentbreakthroughsinembedded systemsdesignthatenabledtheintegrationofhigh-levelsoftwareandlow-level electronics[…]hasledtothedevelopmentofdifferentvarietiesofuser-friendly InternetofThings(IoT)hardwaredevelopmentplatformsforIoTprototyping”.

Heetal.[14]investigatedperformanceoftheRaspberrypi2B+graphicsin termsofelectricalpowerandenergy.Theymeasuredpowerconsumptiondifference betweenGPUrenderingandsoftwarerendering,usingdifferentbenchmarks.Results showedthatthenumberofframesrenderedpersecondincreasesdramaticallywhen hardwarerenderingisused,asdoeselectricalpower.Theyalsofoundthat—dueto thevelocityofthehardware—thetotalenergyconsumedperrenderedframewas lowerdespitetheelectricalpowerduringhardwarerenderingbeinghigher.Nunes etal.[15]analyzedtheexecutionbehaviorandpowerconsumptionofwebservices onRaspberryPiB.Inthispaper,wefocusonthenewRaspberryPi3board,and oncharacterizingitsbehaviorwhilerunninganartificialvisionprogram,inorderto quantitativelyassessthisopenplatforminanautomotiveembeddedenvironment.

3SystemArchitecture

Fromthehardwareviewpoint,ourgridalignmentsysteminvolvedavideocamera (Logitechc920),ahighdefinition(1920 × 1080)webcamtocapture30framesper secondoftheroadaheadasshowninFig. 1.Mountedonthetop-middleofthe windshieldusingasuctioncup,thecameraisconnectedtoaserver-nodedevicethe RaspberryPi3B[7],oraregularPC,bothofwhichrunpythononWindowsor LinuxOS.Inthedevelopmentphase,asworkingwiththePi3modulerequireda monitor,mouse,andkeyboardformonitoring,tracing,andeditingthecode,weused anordinarylaptopforconvenience[18].Forthefinalsystemrelease,thelaptopwas seamlesslyreplacedwithaPi3board.OurlaptopwasaSamsungChronos770Z5E with3rdgenIntelCorei7,8GBofmainmemoryRAM,andanAMDRadeonHD 8870Mgraphicscardwith2GBofdedicatedRAM.

Fig.1 Schemaofthegrid alignmentsystem

Thecorefunctionsofthesystemrunontheserver-nodeandarewritteninpython. WeusedJupyterNotebook[16]asexecutionenvironment,andtheOpenCVlibrary forgraphicprocessing[17].

Threestepsformulateeachframe’sprocessing:objectspotting,clusteringandline detection,andmiddlepointestimation.Theobjectswesettorecognizearethegrid andthelane.Thegridistheprimepriority;weswitchtolanebordersrecognitionin casethegridfailstoberecognized.Sinceitisunknownbeforehandwhetheragrid couldberecognizedornot,weimplementedaparallelimageprocessingpipelineon twocopiesofeachframe,oneforgridrecognitionandanotherforlanerecognition.

Foreachobject,wesetspecificcolourmasksandregionmasks.Twocolour masks,orfilters,weredefinedforthegrids—oneislightgreyandtheotherdark grey—correspondingtothedifferentgrids’possiblecolors.Forthelanelines,we consideredthetwointernationallystandardizedlanecolours:whiteandyellow.

Next,thealgorithmstartsaparallelprocessingpipelinewherelow-passfiltersare appliedtothetwoinstancesoftheoriginalframe.Forgriddetection,weapplya median-blurfilter,whileweuseaGaussianfilterforlanelinedetection.

Afterthat,bothinstancesundergoedgedetectionusingtheCannyalgorithmthat shapesoutthecontourofthegridandofthelanelines.Then,regionmasksselection isperformed.Thegridregionmaskiscentred,whilelanelinesmaskiscomposedof twoseparateregionsattherightandleftsidesoftheframe.

Aftertheframeinstancesarecroppedbytheregionmasks,theybecomereadyfor Houghlinesestimation,inwhichatransformfunctionisperformedtoproduceevery possiblestraightlinewithinspecificslopeandbiasparameters.Theseparametersare adjustedtofitthedepthperceptionofthedimensionsoftheroad.Aconcentration ofHoughlineswouldformineachregion,signifyingtherecognitionofgridorlane borders.Aclusteringalgorithmidentifieseachconcentration,thenamedianlineis computedforeachcluster.Thus,eachcoupleofnear-symmetriclinesareassociated togetherasanobject(gridorlane)representation.

Thelanerecognitionsometimesfailswhenthevehicleistooclosetoanemptygap ofthecentraldashedline.Totacklethissituationwedevelopedafunctionbasedon therecognitionofasingleline.Thefunctionimplementsasimpleonlineestimation algorithmthatestimatesthedistancebetweenthetwolane-borderstotheprovisional gridcentreusingtheprevious10frameswithtruerecognitionofbothborderlines.

Asmentionedbefore,thepriorityinimageprocessingisforgriddetection.Ifagrid wasrecognizedinitsownregion,thealgorithmdefinesthetwolinesrepresentingthe rightandleftsidesofthegridaccordingtoavaliditycheckincludingtheparameters: lineslopeandbias.Then,amiddlelinecanbegenerated,thecentreofwhichis ourestimationforthegridcentrecoordinates.Theoffsetcannowbecomputedas thedifferencebetweentheestimatedgridcentreandtheframemiddle.Intheother pipeline,theoffsetisthelanecentre,whichweusetocomputetheestimatedgrid centre.Theoffsetthatiscomputedatthisstagebyeitherpipelineisapixelmetric andneedstobeconvertedtocentimeters.

Oncetheoffsetiscomputed,itsvalueissentoverWIFItothetabletdeviceplaced onthevehicledashboard,whereanAndroidappdisplaystheoffsetasapointeron alineargauge.APOSTHTTPrequestisalsosenttoaprivateonlineserverwith thegridmisalignmentestimation,itsdirection,andthevehiclechargingstateas payloads.

4Experiment

WeusedthedevelopedsoftwareasabenchmarktoassessperformanceoftheRPi 3system.Weperformedseveralmeasurements,thatarereportedinTable 2.Details aboutthetargetsystemareprovidedinTable 1.

Asmonitors,weusedh-top,aUSBPowerGaugeandConky.Since,forthesakeof simplicity,weemployedthesameRPiboardasthemeasuringandmeasuredsystem aswell,weexpectthattheactualabsoluteperformanceshouldbeslightlybetter.

Wetriedourgridalignmentassistancesystem(GAAS),infourconfigurations, varyingthesizeoftheconvolutionalkernel,whichisusedforfilteringeachframe withtheGaussianandthemedian-blurfilter.Thecontributionoftheonlineestimatingalgorithmwasnegligible.Resultsarethesameateachframe,accordingto thefunctioningoftheGAASprogram,andwecanseethatthe5 × 5configuration allowsachievingthesamehighaccuracy(approximately80%ofthetimeprediction iswithina10cm.error,while100%within20cm.)asthe7 × 7kernel,butthe utilizationoftheresourcesismuchlower,leavingspacealsoforotherapplications. AccuracywasmeasuredinroadtestsperformedinSusa(To),Italy,attheMotorOasi safedrivetrack,withadynamicwirelesschargingexperimentalvansetupbythe

Table1 RaspberryPi3 systeminformation

Feature Value Notes

Processor: ARMv7rev4 @1.20GHz’

Cores 4

Graphics: LLVMpipe

OpenGL 3.3Mesa13.0.3 Gallium0.4 (LLVM3.9128 bits)

Screen 1824 × 984HDMI Samsung S22C300H

MotherBoard: BCM2835Pi3 ModelBRev1.2

Memory: 860MB

Disk: 32GBSD

File-system: ext4

OS: Raspbian9.4

Kernel 4.14.52-v7+arm71

Table2 PerformancemetricsforGAASandotherbenchmarks

14%—chromiun (jupyter)20%

GAAS(3 × 3) 22%(python20%)

16%—chromiun (jupyter)21%

18%—chromiun (jupyter)20%

19%—chromiun (jupyter)19%

3%

× 5)

× 7)

GAAS(9 × 9)

Youtube (1080) 33%(chromium 28%)

29%(minecraft 23%)

Walfram Math. (AutocorrTest “uptolag 100”) 51%(Test45%)

Fabricproject.The3 × 3versionalmostkeepsthecamerasourcerate(30FPS),but withunacceptableaccuracy.The7 × 7versionhasanon-negligibleFPSratedrop, differentlyfromthe5 × 5kernel.The9 × 9sizehasthehighestaccuracy,reaching evenhigherresolutionvalues(3cm.,onalaptop),butleadingtofullutilizationof theCPUuptoacrashintheRPi.WebelievethattheuseoftheGPUmayimprove performance,butresultsachievedwiththe5 × 5version–thatweusedintheroad tests—arealreadywithinthesetspecifications[5].

Wealsoconsideredsomeotherbenchmarks,doingvideoplaying(Youtube),gaming(Minecraft)andintensivecomputation(WalframMathematica).Wecouldnotice that,inourcase,theCPUisthebottleneck,whileintheothercasesCPUutilization isquitelimited.ThisisanotherindicatorthatacustomutilizationoftheGPUby GAASshouldleadtobetterresults.

5Conclusions

ThispaperhasinvestigatedthebehaviorofaRaspberryPi3singlePCboardwhile runninganartificialvisionprogram,inviewofaquantitativeassessmentofthisopen platforminanautomotiveembeddedenvironment.Thebenchmarkprogram—performinggridalignmentforthedynamicwirelesschargingofelectricvehicles—involvedvarioussignalprocessingfunctionsandasimpleonlineestimationalgorithm. TothebestofourknowledgeitisthefirstperformancecharacterizationofaRaspberryPi3inautomotiveenvironment.

ResultshaveshownthatthebottleneckofthesystemisrepresentedbytheCPU. AcustomexploitationoftheGPUshouldleadtobetterresults,evenifresultswith aproperfilterkernelsizeconfigurationallowshowthatthesystemhasbeenable toreachthetargetaccuracy[5]whileleavingroomforotherpossibleconcurrent applications,andwithenergydemandssimilartostateoftheartprograms.

Fromthedevelopmentviewpoint,thechoiceofpythonhasbeenveryeffective,as itallowedaseamlesstransitionbetweenthedesktopandembeddedenvironments. Forfuturework,resultssuggestimplementingaGPU-targetedversionofthesystem.Moreover,furtheranalysiswithotherbenchmarksandplatformsareneededin ordertobetterassessthepotentialofopenhardwaresystemsforembeddedapplicationsinautomotive.

Acknowledgements WewouldliketothanktheFABRICcoordinator,Prof.AngelosAmditisand allthecolleaguesthatallowedasuccessfulperformanceoftheproject. ThisworkwassupportedinpartbytheEU,undertheFeasibilityAnalysisandDevelopmentof on-roadchargingsolutionsforfutureelectricvehicles(FABRIC)integratedproject(FP7-SST-2013RTD-1605405).

10A.Kobeissietal.

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2.Ruffo,R.,Cirimele,V.,Diana,M.,Khalilian,M.,LaGanga,A.,Guglielmi,P.:Sensorless controlofthechargingprocessofadynamicinductivepowertransfersystemwithaninterleaved nine-phaseboostconverter.IEEETrans.Industr.Electron. 65(10),7630–7639(2018)

3.Tavakoli,R.,Pantic,Z.,Analysis,designanddemonstrationofa25-kWdynamicwireless chargingsystemforroadwayelectricvehicles.IEEEJ.Emerg.Sel.TopicsPowerElectron. https://doi.org/10.1109/jestpe.2017.2761763

4.Hwang,K.,Park,J.,Kim,D.,Park,H.H.,Kwon,J.H.,Kwak,S.I.,Ahn,S.:Autonomouscoil alignmentsystemusingfuzzysteeringcontrolforelectricvehicleswithdynamicwireless charging.MathProbl.Eng.ArticleID205285,14p(2015). https://doi.org/10.1155/2015/ 205285

5.Cirimele,V.,Smiai,O.,Guglielmi,P.,Bellotti,F.,Berta,R.,DeGloria,A.:Maximizingpower transferfordynamicwirelesschargingelectricvehicles.In:InternationalConferenceonApplicationsinElectronicsPervadingIndustry,EnvironmentandSociety,APPLEPIES2016,Rome. LectureNotesinElectricalEngineering,vol.429,pp.59–65(2017). https://doi.org/10.1007/ 978-3-319-55071-8_8

6.Amditis,A.Karaseitanidis,G.,Damousis,I.,Guglielmi,P.,Cirimele,V.:Dynamicwireless chargingformoreefficientFEVS:thefabricprojectconcept,MedPower2014,Athens,pp.1–6 (2014)

7.RaspberryPi3ModelB. https://www.raspberrypi.org/products/raspberry-pi-3-model-b/

8.Marosi,A.C.,Lovas,R.,Kisari,Á.,Simonyi,E.:AnovelIoTplatformfortheeraofconnected cars.In:2018IEEEinternationalconferenceonfutureIoTtechnologies(FutureIoT),Eger, pp.1–11(2018)

9.Shi,W.,Cao,J.,Zhang,Q.,Li,Y.,Xu,L.:Edgecomputing:visionandchallenges.IEEE InternetThingsJ 3(5),637–646(2016)

10.Fan,Q.,Ansari,N.:Applicationawareworkloadallocationforedgecomputing-basedIoT. IEEEInternetThingsJ. 5(3),2146–2153(2018)

11.Hajdarevic,K.,Konjicija,S.,Subasi,A.:AlowenergyAPRS-ISclient-serverinfrastructureimplementationusingRaspberryPi.In:201422ndTelecommunicationsForumTelfor (TELFOR),Belgrade,pp.296–299(2014)

12.Cimino,D.,Ferrero,A.,Queirolo,L.,Bellotti,F.,Berta,R.,DeGloria,A.:Alow-cost, open-sourcecyberphysicalsystemforautomated,remotelycontrolledprecisionagriculture, In:ProceedingsofApplicationsinElectronicsPervadingIndustry,EnvironmentandSociety (APPLEPIES),LectureNotesinElectricalEngineering,Rome,Sept.215.Springer,Cham

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14.He,Q.,SegeeB.,Weaver,V.:RaspberryPi2B+GPUPower,Performance,andEnergy Implications.In:2016InternationalConferenceonComputationalScienceandComputational Intelligence(CSCI),LasVegas,NV,pp.163–167(2016)

15.Nunes,L.H.,etal.:PerformanceandenergyevaluationofRESTfulwebservicesinRaspberry Pi.In:2014IEEE33rdInternationalPerformanceComputingandCommunicationsConference (IPCCC),Austin,TX,pp.1–9(2014)

16.JupyterNotebook. https://jupyter.org/

17.Beyeler,M.,OpenCVwithPythonBlueprints,Packt(2015)

18.Kobeissi,A.,Bellotti,F.,Berta,R.,DeGloria,A.:IoTgridalignmentassistantsystemfor dynamicwirelesschargingofelectricvehicles.In:5thInternationalWorkshoponIntelligent TransportationandConnectedVehiclesTechnologies(ITCVT2018),Valencia,Spain(2018)

AnalysisofCybersecurityWeakness inAutomotiveIn-VehicleNetworking

andHardwareAccelerators forReal-TimeCryptography

LucaBaldanzi,LucaCrocetti,MatteoBertolucci,LucaFanucci andSergioSaponara

Abstract Theworkanalysesthecybersecurityweaknessinstate-of-artautomotive in-vehiclenetworksanddiscussespossiblecountermeasuresatarchitecturelevel. Duetostringentreal-timeconstraints(throughputandlatency)offail-safeautomotive applications,hardwareacceleratorsareneeded.Ahardwareacceleratordesignfor AES(AdvancedEncryptionStandard)-128/256calculation,thelatterbeingalready consideredpost-quantumresistant,isalsopresentedtogetherwithimplementation resultsinFPGAand45nmCMOStechnology.

Keywords HWaccelerators · Automotivecybersecurity · AES(AdvancedEncryptionStandard)

1Introduction

Modernautomotivesystemsfeatureseveralnetworkedarchitecturesandon-board communicationbuses.Theamountofexchangeddataandthein-vehiclenetworks trafficinabsenceofpropersecuritymechanismsprovideawiderangeofattack surfaces,makingtheautomotivesystemsvulnerabletothemanytypicalcybersecuritythreatsandcybersecurityattacks,asdatasniffing,datatampering,unauthorized

L.Baldanzi(B) · L.Crocetti · M.Bertolucci · L.Fanucci · S.Saponara DepartmentofInformationEngineering(DII),UniversityofPisa, viaG.Caruso16,56122Pisa,Italy

e-mail: luca.baldanzi@ing.unipi.it

L.Crocetti

e-mail: luca.crocetti@for.unipi.it

M.Bertolucci

e-mail: bertolucci.matteo@gmail.com

L.Fanucci

e-mail: luca.fanucci@unipi.it

S.Saponara

e-mail: sergio.saponara@unipi.it

©SpringerNatureSwitzerlandAG2019

S.SaponaraandA.DeGloria(eds.), ApplicationsinElectronics PervadingIndustry,EnvironmentandSociety,LectureNotesinElectrical Engineering550, https://doi.org/10.1007/978-3-030-11973-7_2

accesses,etc.Duetostringentreal-time(throughputandlatency)constraintsoffailsafeautomotiveapplications,hardwareacceleratorsareneeded.Tothisaim,Sect. 4 presentsthedesignofahardwareacceleratordesignforAES(AdvancedEncryptionStandard)-128/256calculation,thelatterbeingalreadyconsideredpost-quantum resistant.Theworkpresentedinthispaperaddressessuchissuesanditisorganized asitfollows.Section 2 analysesthecybersecuritythreatsinstate-of-artautomotive in-vehiclenetworksandSect. 3 discussespossiblecountermeasuresatarchitecture level.ImplementationresultsfortheAESacceleratorinFPGAand45nmCMOS technologyarediscussedinSect. 5.ConclusionsaredrawninSect. 6

2CybersecurityWeaknessandCountermeasures forOn-BoardNetworkingAutomotiveSystems

Thispaperreferstoon-boardembeddedandnetworkedautomotivesystems,and hencethisSectionisfocusedoncybersecurityissuesandcountermeasuresforinvehiclenetworks.Othercybersecurityaspects,suchthoserelatedtoVehicle-toEverything(V2X)connectivity,cloud-basedtrafficandfleetmanagements,justto nameafew,areoutofscopeofthiswork.Securebydesignin-vehiclenetworking shouldensureseveralproperties,suchasdataintegrity,confidentiality,authentication andavailability.However,severalsecurityvulnerabilities[1–8]characterizecurrent in-vehiclenetworkingtechnologies,usingControllerAreaNetwork(CAN)and/or CAN-FDasabackbone,andaplethoraofotherinterconnectingtechnologiesfor specificsubsystems(e.g.,LIN,LocalInterconnectionNetwork,forlocalinterconnectionoflowdata-ratenodes,MOST,MediaOrientedSystemsTransport,forinfotainmentwithUSBandBluetoothuserinterfaces,andFlexRayforlatency-critical functions).Thenet-spanningdataexchangeviavariousgatewaydevicespotentially allowsaccesstoanyvehicularbusfromeveryotherexistingbussystem.Indeed, eachLIN,CANorMOSTcontrollerispotentiallyabletosendmessagestoany otherexistingcarcontroller[9, 10].Withoutparticularpreventivemeasures,asinglecompromisedbussystemendangersthewholevehiclecommunicationnetwork. WhereasattacksonLINormultimedianetworksmayresultinthefailureofpower windowsornavigationsoftware,successfulattacksonCANorFlexRaynetworks mayresultinmalfunctioningofsomeimportantdrivingassistantsthatleadstoseriousimpairmentsofdrivingsafety.WhiletheuseofCyclicRedundancyCheck(CRC) ensuresdataintegrity,thebroadcastnatureofCAN/CAN-FDorFlexRayisariskin termsofconfidentiality,asanattackedElectronicControlUnit(ECU)canmonitor alldatapassingonthebus.Moreover,sincenewECUscanbeaddedinaplug-andplayway(assigningthemanewidentifier)withoutmodifyingthealreadyinstalled ECUs,andsincethedatalinklayerdoesnotprovideanymechanismforsignature andtransmissionencryption,thereisahighriskofauthenticationvulnerabilityand unauthorizedaccesstotheCANbusandtothetrafficcontentoverit.Datasniffing andmanipulation,jammingandDenial-of-Service(DoS)areonlyfewofthepossi-

bleattackstothebackbonebusortothelocalbusthatcouldleadtosystemfailure ortofunctionalfailure,respectively.Moreover,utilizingtheCANmechanismsfor automaticfaultlocalization,maliciousCANframescandeterminethedisconnection ofeverysinglecontrollerbypostingseveralwell-directederrorflags.Similartothe CANautomaticfaultlocalization,thebusguardianinFlexRaycanbeutilizedfor thewell-directeddeactivationofanycontrollerbyappropriatefakederrormessages. Attacksonthecommontimebase,whichwouldmaketheFlexRaynetworkcompletelyinoperative,arealsofeasiblebypostingpropermaliciousSYNCmessages onthebus.Moreover,theintroductionofwell-directedsleepframesdeactivatesthe correspondingpower-savingcapableFlexRaycontrollers.

3CountermeasuresforOn-BoardNetworking AutomotiveSystems

Aspossiblecountermeasures,thefollowingtechniquesareforeseenandarelikely toappearinthenewgenerationofcarconnectivitydevices:

• Toclusterthesubnetworksandrelatedsubsystemsinsecurityislands,separated bygatewayswithembeddedcybersecurityfunctionalities,sothatanattackona non-safetyrelatedbus,likeLINorMOST,cannotpropagatetothesafety-related functionsconnectedtoFlexRayorCAN[3].Thisapproachwillalsobeapplied tothefuturearchitecturesbasedonAutomotiveEthernet[11].

• Toembedcybersecurityhardwareacceleratorsinnewautomotivecomputingunits tosustainmessageencryptioninreal-time.ThisisthereasonwhyinSects. 4 and 5 weareproposinganewdigitalmacrocell,thatimplementsreal-timesecuritytechniqueslikethesymmetric-keyalgorithmAES.Morecomplexalgorithmslikethe EllipticCurveDigitalSignatureAlgorithm(ECDSA)forpublic-keycryptographyarealsounderdevelopment[12, 13].TheuseofHW-basedco-processors isrequiredbystringentlatencyandenergy-efficiencyrequirementsthatarenot achievablewithsoftware-basedimplementations.

• Toembedsignaturemechanismsforcontrollerauthenticationinnewautomotive computingunits.Authenticationofallsendersisneededtoensurethatonlyvalid controllersareabletocommunicateonautomotivebussystems[3, 12, 14, 15]. Allunauthorizedmessagesmaythenbeprocessedseparatelyorimmediatelydiscarded.Everycontrollerthereforeneedsacertificatetoauthenticateitselfagainst thegatewayasavalidsender.Forexample,asproposedin[3],acertificatemay consistofthecontrolleridentifierID,thepublickeyandtheauthorizationsofthe respectivecontroller.Thegateway,inturn,shouldsecurelyholdalistofpublic keysofallaccreditedOEMsfortheconsideredvehicle.Eachcontrollercertificate isdigitallysignedbytheOEMwiththerelevantsecretkey.Thegatewayagainuses thecorrespondingpublickeyoftheOEMtoverifythevalidityofthecontroller certificate.Iftheauthenticationprocesssucceeds,therelevantcontrollerisadded tothegatewayslistofvalidcontrollers.

• ToclustertheECUsindifferenttrustableclassesdependingonhoweasilythey canbeattacked.Forexample,in[16]asecurityframeworkforvehicularsystems, calledVeCure,isproposed,whichcanfundamentallysolvethemessageauthenticationissueoftheCANbus.EachnodethatsendsaCANpacketneedstosend alsothemessageauthenticationcodepacket(8bytes).TheECUsaresplitinto twocategories,namely,theLow-trustandtheHigh-trustgroups.ECUsthathave externalinterfaces,e.g.,OBD-IIortelematicsareputinthelow-trustgroup.The High-trustgroupECUsshareasecretsymmetrickeytoauthenticateeachincoming andoutgoingmessage.

• Toimplementintrusiondetectionmechanismsbasedonthephysicalorpacketlayer features.Forexample,aclock-basedintrusiondetectionsystematphysicallayer isproposedin[5].Similarly,anin-vehiclenetworktrafficmonitoringtechniqueis proposedin[17]todetecttheincreasedtransmissionratesofmanipulatedmessage streams.

• Toimplementgatewayfirewalls.Forexample,asproposedin[3],ifthevehicular controllersarecapableofimplementingdigitalsignatures,thefirewallrulesare basedontheauthorizationsgiveninthecertificatesofeverycontroller.Therefore, onlytheauthorizedcontrollersareabletosendvalidmessagestothehighsafetycriticalin-vehiclebussystems.Ifthevehicularcontrollersdonothavetheabilities tousedigitalsignatures,thefirewallcanbeestablishedonlyontheauthorizations ofeachsubnet.However,controllersoflessrestrictednetworkssuchasLINor MOSTshouldgenerallybepreventedfromsendingmessagestothehighsafetyrelevantbussystemsasCANorFlexRay.Simplifiedfirewall-likefunctionalities canbealsoimplementedineachend-nodeandnotonlyinthegateways,withthe so-calledDataDiode[18].

4AES-128/256HWAcceleratorDesignforReal-Time EmbeddedCryptography

TheAESisasymmetric-keyblockcipheralgorithmthatprocessesdatablocksof 128bitswiththreedifferentkeysizes:128bits(AES-128),192bits(AES-192)and 256bit(AES-256)[19].TheAESisaniterativealgorithmandeachiterationofthe algorithmiscalled“round”.Thenumberofroundsdependsbythekeysize:10rounds fortheAES-128,12roundsfortheAES-192and14roundsfortheAES-256.Each roundconsistsoffourdifferentsteps:anon-lineartransformationbysubstitution (SubBytes),apermutation(ShiftRows),alineartransformationbymixingdata(MixColumns)andthecombinationofthedatawiththeroundkey(AddRoundKey).Each oneofthesetransformationsisinvertibleandthisallowtorevertthemodifications oftheAESalgorithmandthereforetodecryptdata.

Anadditionalalgorithm,calledKeyExpansion,derivesthekeysforeachrounds startingformtheinitialCipherKey.Figure 1 showstheAESalgorithmbymeansof graphicalrepresentationoftheroundsandtheirtransformations.

Fig.1 AESencryptionalgorithm,thenumberofrounds ( N ) dependsontheCipherKeysize: N =10for128-bitCipherKey(AES-128), N =12for192-bitCipherKey(AES-192)and N =14 for256-bitCipherKey(AES-256)

Theinter-roundpipelinedarchitectureisoneofthemostdiffusedapproachfor aco-processorimplementingtheAESalgorithm,becauseitallowstoreachavery highefficiencyintermsofarea/latencytrade-off.Sucharchitectureconsistsinimplementingasingleroundwithallitsinternaltransformationsandusingititerativelyby meansofabuffertostoretheintermediateresults.Figure 2 illustratestheinter-round pipelinedarchitecturefortheAESco-processor.

AlsotheKeyExpansionalgorithmisiterativeandderivestheroundkeysalong roundswithtransformationssimilartotheonesperformedbytheAESalgorithm, exceptforthelineardatamixingtransformationwhichisnotexecuted.Thusan architecturesimilartotheoneillustratedbyFig. 2 wellfitsalsoforthemodule implementingtheKeyExpansionalgorithm.

Fig.2 Inter-roundpipelinedarchitectureforanAEShardwareaccelerator

Table1 AESHWacceleratorsynthesisresults.LEstandsforLogicElement,that,fortheStratix IVFPGAcanbebothanadaptiveLUT(ALUT),i.e.acombinationallogicresource,ora1-bit register.kGEstandsforkiloGateEquivalent,referringto1GateEquivalentasa4transistorsgate. Thedatareportedinthe‘Latency’and‘Throughput’rowsandseparatedbythe/characterrefer, respectively,totheAES-128andtotheAES-256algorithmsexecution

Feature FPGAtechnology 45nmCMOStechnology

Logicresources/area 8063LEs(4.4%) 19kGE

Maximumfrequency 145MHz 460MHz

Latency 11/15clockcycles

Throughput

1.69/1.24Gbps 5.35/3.93Gbps

5AES-128/256HWAcceleratorImplementationResults inFPGAand45nmCMOSTechnology

ConsideringthelogicresourcesoverheadrequiredtohandletheAES-192algorithm case,withrespecttothesecuritylevelofferedbysuchalgorithm,asingleAES hardwareacceleratorabletosupportboththeciphersAES-128andAES-256and boththeencryptionanddecryptionalgorithmshasbeenimplemented,thusoffering averyhighsecuritylevelbymeansoftheAES-256algorithm,whichisalready declaredtoberesistanttopost-quantumcrypto-analysis[20].

TheAEShardwareacceleratorhasbeensynthesizedonaStratixIVFPGA (EP4SGX230KF40C2)andonthe45nmCMOStechnologyprovidedbytheNanGateFreePDK45OpenCellLibrarystandard-celllibrary.Table 1 showsthemain features.

AsreportedinTable 1,incaseofimplementationontheStratixIV,theAEShardwareacceleratorlogicresourcesisof8063LEs,thatcorrespondstothe4.4%ofthe totalamountofavailablelogicresourcesoftheFPGA.AnyLEoftheStratixIV FPGAcanbeeitheracombinationallogicelement(ALUT,AdaptiveLUT)or1-bit registeroracombinationofALUTandregisters.3656LEsareusedaspurecombinationallogicelements,262aspureregisters,202asacombinationofcombinational andsequentiallogicand3943LEareusedforroutingandinterconnection.

6Conclusions

TheimplementedAEShardwareacceleratorcanbeusedasco-processortosecure theautomotivein-vehiclenetworks,ensuringthedataconfidentialitywithahigh levelofsecurity(AES-256)andmatchingthestringentreal-timerequirementsofthe automotivearea.Thankstoitsreducedlatency(i.e.23.9nsincaseofAES-128or 32.6nsincaseofAES-256)anditshighthroughput(refertoTable 1)itcanlargely supportmanyofthemostdiffusedandsafety-criticalin-vehiclenetworks,suchasthe

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CHAPTER VII

CORRECTION OF SPEECH DEFECTS

In addition to the ordinary faults and failings in speech possessed by many in common, there are the special and specific defects, such as stammering, stuttering, lisping, and the like. Every defective is to be pitied, as many professions and occupations are of such a nature as practically to bar men and women who cannot speak well. There are the social and ethical handicaps, also, to be considered, as well as that of economics. The defective speech of a child renders him the butt of his playmates’ rude and often brutal jokes. The sensitive is thus driven away from society. He becomes a solitary and not infrequently his life is ruined.

Speaking of the stutterer, one who is not afflicted by this disease (for so authorities have determined it to be), cannot realize what a terrible life he lives. Dr. Scripture, of Columbia University, New York City, who is one of the greatest authorities on this subject, says: “One boy often threw himself on the floor, begging his mother to tell him how to die. Another boy asked for a letter to his father, telling him to keep the other children from laughing at him. Many stutterers become so sensitive that they imagine everybody is constantly making fun of them. The life of a stutterer is usually so full of sorrow that it can hardly be said to be worth living.”[3]

The speech delinquent is shy, timid, super-sensitive, constantly harboring the thought that people are laughing at him. He gradually shuns society, lives unto himself, and in many instances becomes morally depraved. He contracts a morbid outlook upon life in general, and often is driven to criminality. This statement is no exaggeration. The Board of Education in New York City, after thorough investigation, found that “one school child in four suffers from speech defect,” and that “among boy criminals, nine in ten suffer from the same malady.”

In the Grand Rapids schools classes for the sole purpose of correcting speech defects were organized.

The mechanical arrangement was as follows: Twelve classes were arranged for in five different schools with a half hour a day for each class. The children were grouped according to age, kind of defect, etc., and a teacher with special training for the correction of speech was sent from school to school to give the instruction.

Our plans for this year (1918) are practically the same as for last excepting that we have more special teachers and will be able to reach a greater number of schools and give more time to individual cases.... During the school year of 1916-17, we had under instruction 107 children and obtained the following results:

This year we will have under instruction of our special teachers about 250 children, and in addition to this we hope to work for correction and prevention of speech-defects in general by giving instruction in voice culture and corrective phonetics to all of the children of the primary grades. This work will be done by the grade teachers under the supervision of the speech department.[4]

T P

A person with a slight impediment in his speech, due probably to some minor organic disorder, could be much helped by the average

teacher, if the latter would give this subject of speech serious consideration. Of course there are cases where, from birth, the child’s speech organs have been impaired, and again, disease or some surgical operation may have caused interference with their proper functioning. In such cases as these a speech specialist is needed and often medical aid as well.

We do not presume to suggest with any degree of authority just what to do and what not to do in such extremities, but rather to present a few fundamental and tried principles which have proved successful in many cases. There are two classes whose speech defects are due to some mental cause—the Stammerers and the Stutterers.

C S

The stammerer finds it extremely difficult to begin to make any audible vocal sound. He stares blankly at you with a very slight, if any, suggestion that he is trying to speak. For the time being he is a mute, with no power to speak, and yet with every means of speaking. This is a pitiful condition in which to be.

The next stage finds the stammerer able, after a snapping of his fingers, or bending of his knees, or lifting up of a foot, or swinging his arms, or after some similar bodily action, to speak along smoothly with no suggestion of an impediment for a considerable period of time, after which he again lapses into silence. The following characteristics are common to most stammerers:

1. He is inclined to speak too fast when started.

2. He has no control over his breathing.

3. He often endeavors to speak during inhalation instead of during exhalation.

4. He is extremely sensitive, always fearing that he is making a mistake.

5. His face usually carries an expression of bitter sorrow and despair.

6. He is usually intensely grateful to any one for a kind word of help.

7. He tries with the utmost skill to conceal his defect.

8. He is usually weak physically.

9. He is usually of a nervous temperament.

10. He usually possesses splendid courage and high ideals, which too often are destroyed because he cannot accomplish them with this weight of halting speech about his neck.

T S

The stutterer, unlike the stammerer, is able to make an audible sound at will. His difficulty lies in his inability to say more than one sound until he has repeated the initial sound from six to fifteen times. It seems that he must get up a certain amount of speech momentum: “B-b-b-bring me th-th-th-that b-b-b-book.” Or, “W-w-w-well, I think it is a v-v-v-very fine day.”

In a large measure the causes of stuttering and stammering are identical. Stammering is stuttering in the superlative degree. What is true of the stammerer is also true of the stutterer, with the exception that the stutterer is less melancholy, and less conscious of his defect.

For both, or either, practice in simple exercises is very necessary, but before specific training is given, the defective should be interviewed concerning his health. If a boy or girl is not given sufficient food and proper food (and such is often the case), there is small chance for speech improvement. Oftentimes it is found that these speech delinquents are playing too hard and wasting the nervous energy which should be utilized in mastering their vocal impediment.

The most successful way of handling these problems is to have the defectives placed in separate classes according to their particular needs and ages. Then get a physician’s diagnosis of each individual case. This diagnosis generally gives the special teacher the knowledge necessary for intelligent correction. The teacher must be patient, gentle, sympathetic and yet determined. She herself must possess ease and real enjoyment in speaking.

Practice Exercises

1. Speech defectives must first learn how to relax. They should spend at least ten minutes daily at home lying flat on their backs concentrating the mind on separate parts until the whole body is completely relaxed. This relaxation exercise can and should be carried on daily. At school, a similar though modified exercise should be attempted.

2. They must master diaphragmatic breathing. This exercise should follow the relaxation exercise, for the best results are obtained while lying on the back; the next best while sitting erect.

(a) Inhale slowly, filling lower lobes of lungs first, and then the upper part of chest. While doing this count ten mentally; exhale, counting ten mentally. Repeat five times.

(b) Inhale ten counts again, hold breath five counts, exhale ten counts. Repeat five times.

(c) Inhale slightly, then purse lips to impede the air as it passes out; now give one short puff with spasmodic contraction of abdomen. Repeat five times, inhaling slightly before each puff.

(d) Inhale deeply, then give one long puff with continuous contraction of the abdomen. Repeat five times, inhaling deeply before each puff.

3. Tone production should follow breathing exercises.

(a) Count orally 1-1-1-1-1 with spasmodic abdominal contraction. Repeat five times. Be sure that breath is taken in after each count.

(b) Count orally 1-1-1-1-1 with continuous abdominal contraction. Repeat five times.

(c) Inhale deeply and count orally 1 to 10, stressing every other count. Some students cannot do this unless the teacher keeps time with ruler as a baton, striking some object. Others can only do this by walking slowly, repeating a count on every other footfall. Repeat five times.

(d) Select a lyric with marked rhythm and read in concert in sing-song style. Repeat each stanza five times, giving marked pulsation to each accented syllable. Tennyson’s “Song of the Brook” is especially good for this purpose.

(e) Take a simple prose selection and mark it off in thought groups, and then read slowly and measuredly in concert, giving a fairly long pause between each group. Hamlet’s “Instructions to the Players,” and Lincoln’s “Gettysburg Address” are splendid for such work.

When the defective has learned to speak fluently memorized work, then he should be taught confidence in simple conversational exercises. This work should be, so far as possible, voluntary on the part of the pupil. Let the class form a circle, each one sitting with a sense of ease and relaxation and then, as they are inclined, take part in conversing on some simple, interesting topic. Some will have to be urged to participate while others find great delight in such work.

In regard to training in enunciation, this work has been found to be more successful when given late in the development of the defective. After he has gained confidence in speech ability and cultivated, to some degree, real enjoyment in voice production, he is better prepared to consider this more or less purely technical training. In very extreme cases, however, it will be found necessary to begin speech instruction with him as you would teach a child. Such

students must be taught the proper control of lips, tongue and jaw, as though they had never learned speech at all.

Experts who have devoted a lifetime to the study of speech evils and their remedy find a large variety of causes for them, as well as immense diversity in manifestation. One may seem to be born with a tendency to stammering, stuttering or lisping; another can trace the habit to a fright, to imitation, to some exhaustive disease, to nervous timidity, to self-consciousness. But whatever the cause, or however the evil manifests itself, it is a living nightmare, a dreadful, everpresent burden to its victim. Hence parents and teachers should seriously endeavor to correct the habit as speedily as it is discovered. For if it be long-continued it is almost sure to produce shyness, timidity, lack of necessary self-reliance, even moroseness, sullenness and other consequences of perpetual unhappiness.

At the outset let it be understood clearly that all harshness, unkindness, or severity of treatment in word or deed, adds to the evil and renders it more difficult of eradication. The victim of the habit is to be sympathized with, and lovingly encouraged. Yet promptness, firmness and persistency are essential in the production of a cure. The following suggestions should be put into practice, but seldom or never in the presence of strangers, or at any time when they would heighten the sufferer’s embarrassment. They must also be followed with happy cheerfulness.

1. When a victim of one of these habits begins to stammer or stutter, stop him immediately, and say pleasantly but firmly and crisply, “Stop!” Then command: “Take a deep breath! Now hold it! Now think of what you want to say—each word!” Then allow the stutterer to let out his breath; then inhale again deeply, and begin his speech. If he fails, see that he begins again. Practice this as often as you can. Exercises can also be made up, following the same procedure, that will be of incalculable benefit, as, for instance, taking a deep breath, then repeating as much of the alphabet as is possible before breathing again.

2. Cultivate slowness of speech. Insist upon words being spoken slowly, with great distinctness and clearness of articulation. The

moment stuttering begins, issue the commands: “Stop! Deep breath; think; breathe out, breathe in; now!” Let the teacher say his words very slowly and constantly encourage the pupil to do the same.

3. Cultivate the habit of rapid thinking. This can be done by a series of exercises played as games if necessary. For instance: “The Game of Names.” The teacher says, “Flower!” The pupil replies, “Rose.” If the teacher has a list ready he can call out his names as quickly as possible, such as, Animal, Tree, Water, Bird, Dog, etc., while the pupil responds, Horse, Oak, River, Sparrow, Bulldog, etc. The interest can be increased by repeating a generic term, requiring a different species for answer. Flower, Animal, Tree, Water, etc., can have a score or more of different answers.

Another exercise in prompt thinking is that of “Association of Ideas.” The teacher gives out a name—whatever occurs to him—as, for instance, “Tree.” The pupil immediately responds, “Leaves.” Then the teacher may add, “Autumn,” and the pupil, “Poetry,” and so on. Or the associations may all be required from the pupil. The words used as starters should be carefully chosen, of course, to meet the mental condition of the pupil; such words as Baby, Doll, Mamma, Bed, House, etc., being good for children of tender years.

Another excellent exercise is that of “Contrasts or Differences,” where the teacher says, “Boy,” and the pupil responds, “Girl.” “Black” calls forth “white,” “heavy” is responded to by “light,” etc.

Equally good is “Finishing Quotations” or “lines”—provided, of course, the pupil is old enough for such a mental exercise. For instance, the teacher says, “Everything is not gold,” while the pupil should respond, “That glitters.” “My country,” would bring out “’Tis of thee,” or “Right or wrong.”

Anything that quickens the intellect and demands ready response is of material help, but the teacher must not forget that, in this mental-promptness exercise, slow and deliberate speech also are essential on his part and that of the pupil.

4. Whenever it is found that a pupil stammers or stutters over a word beginning with a consonant, as, for instance, “bread,” require

him to drop out the initial letter and say “read,” or even “ead.” Such words as pie, Tommy, tub, butter, top, bank, tumble, tell, nut, lap, can be used. Let him say, “ie,” “ommy,” “ub,” etc. Then when he is sure of this part of the word, let him, after taking a deep breath, try the full word, saying it again, but always slowly and distinctly.

5. Teach the pupil to sing his sentences. Begin with some simple salutation, as, “Where are you going?” and let it be sung to the notes:

Listen | MusicXML

Where are you going? I’m go-ing home

Then let a response be sung reversing the music, “I’m going home.” “How do you do?” “Where are your father and your mother?” “How far is it to the market?” are sentences that can be sung. The teacher should invent his own music and words, but insist upon slow, deliberate utterances of tone and word. This is a wonderful help in certain kinds of cases.

6. There are certain simple exercises or calisthenics that materially aid in strengthening the muscles of the head, neck, throat, jaw, etc. The teacher can utilize these according to his best judgment. Any book of calisthenic or physical exercises will suggest those most useful.

7. But above all, in seeking a cure of these distressing evils, use the psychical or spiritual remedy Give the pupil confidence that God never intended him to be cursed by a stammering, stuttering, or lisping tongue. He is the child of an Infinite and Loving Father. All good is his, if he will learn how to take it. Urge him to restful, trustful reliance upon the tender help of the Great Power outside of himself, in conjunction with the efforts you and he together are making to effect a cure.

To the teacher who needs thorough preparation upon this subject we can commend heartily Dr. E. W. Scripture’s book “Stuttering and Lisping,” published by the Macmillan Company, New York.

CHAPTER VIII

ENUNCIATION AND PRONUNCIATION

The study of the subject of enunciation should come comparatively late in the development of the pupil, say, beginning with the fifth grade. There are other fundamentals that the pupil should be well grounded in before any definite concentration of effort should be put upon enunciation.

The majority of children and adults are backward in mastering the art of correct speaking, therefore, if the teacher begins by expecting the pupil to be accurate in enunciation, which is really one of the finishing touches, he is in danger of deadening forever the desire for self-expression and enjoyment in speaking.

Pronunciation should precede any drill in enunciation. The pupil is quick to grasp correctness in right pronunciation, and desires it fully, but he cares little for enunciation. Most pupils will shy just a little when you tell them that the proper way to pronounce, or rather to enunciate the word education is ed-u-ca-tion and not ed-ji-ca-tion. Or, take the vowel (a) as in ask, which should be pronounced (ạ). Invariably the untutored will give the vowel the extreme flat sound of (ă) as in hăt, and will think that he is affected if he give it the proper soft, broad sound. He will likely think this even if you compromise with the sounds.

So our policy has been to forego acute criticism in enunciation until the student has acquired considerable momentum in speechdesire. In other words, we are more interested, during his early studies, that he develop and cultivate the desire and will to express, than that he express himself accurately. Then, later, we gradually call his attention to his slovenly speech. Above all things let us beware of quenching the sacred fire of spontaneity, for without that all speech loses its charm and power. Is it not better that the student be stimulated to speech action, even though it be imperfect in some—

even in many—respects, than that he be conscious of all his defects and never speak at all?

Clearness and precision in enunciation and pronunciation mark the genuineness and strength of one’s character. Even the brightest person, if he mispronounce his words, is accused of mediocrity and is suspected of being unaccustomed to the society of refined and cultured people. There should be daily systematic drill in childhood when correct speech habits are most quickly and firmly established. Another great advantage of early training is that this is the period when the student is least self-conscious.

There are three essentials for clear and exact enunciation and pronunciation: First, an acute ear; second, diligent practice; and third, constant vigilance. These three essentials should be kept constantly in mind in carrying out the following exercises. We should first see that the student’s ear can detect the correct, pure resonances, and then pursue vigorous practice in them. At first this kind of exercise is tedious and irksome, but with accomplishment comes keen pleasure.

Let us begin with the vowel sounds. For the word exercises we shall take words often mispronounced as well as poorly enunciated. Thus we shall be doing two important things: cultivating the ear, and improving word production.

E O

The vowels are either long, short, or diphthongal. The resonances of the long vowels begin at the back, passing through the middle, to the front of the mouth. Thus:

The above represents the approximate and relative openings of the mouth in long vowels.

You notice the mouth aperture is narrow at the back, wide in the middle and narrow again at the front. For practice AW and AH and OO are the most valuable because the two chief difficulties of the student are; first, to open his mouth wide enough, and second, to keep his speech forward on the lips. Usually his speech is throaty. Practice the following in concert and individually in order to secure freedom in controlling the mouth:

1. Repeat E A AW AH O OO consecutively on the same pitch.

2. Change the pitch and repeat on each note of the scale.

3. Give a decided rising inflection to each vowel sound.

4. Give a decided falling inflection to each vowel sound.

5. Give a decided circumflex inflection to each vowel sound.

6. Blend them altogether by the straight inflection in a singing tone.

7. Laugh them He He He He, Ha Ha Ha Ha, Haw Haw Haw Haw, Hah Hah Hah Hah, Ho Ho Ho Ho, Hoo Hoo Hoo Hoo.

E T

In pronunciation there is a right and a wrong way. Some people are so desirous of appearing exact in this matter that they often introduce superfluous sounds. For example, such persons pronounce evil—ē´vĭl, instead of ē´vl; towards—tō-wŏrdz´ instead of tō´-erdz.

This habit of introducing an extra sound that is unnecessary reflects upon the learning of the individual quite as much as the neglecting of a sound that is necessary. Let us not attempt to foster extravagant niceties of speech, but let us cultivate in ourselves and our pupils an appreciation of, and a desire for, pure, substantial, and impressively spoken English, showing them that the real beauty of our language lies in its simplicity and its inherent, convincing power.

E

E P

Take up the exercises below in the following manner: First, discover the correct position of tongue, lips and jaw for producing the particular sound under consideration. Second, repeat the sound many times. See that you use your organs of speech properly in regard to the positions indicated at the beginning of each vowel exercise. After the repetition of each sound, let lips, tongue and jaw relax to normal position. Third, in repeating the words be sure the ictus or vocal stroke is properly and decidedly placed.

The main purpose is to develop pure vowel resonance, but inflectional freedom may be cultivated at the same time, if great care is taken not to interfere with the correct vocal positions of tongue, lips and jaw. Beware of a tendency in this direction. (See discussion of Inflection in another part of this book.)

K P

In showing the correct pronunciation of words in the following exercises, the simplest method has been adopted. The words are rewritten with a set of letters which have invariably the same sound and are familiar to everyone.

Webster’s New International Dictionary and Phyfe’s Words Often Mispronounced are the principal authorities consulted. The authors are greatly indebted to these works for help in determining correct pronunciation. The following table gives the diacritical marks used in the following pages:

ē ēve

[.=e] d[.=e]pend

ĕ bĕt ẽ hẽr e recent ī glīde

[.=i] [.=i]dea ĭ ĭt ō gō

[.=o] [.=o]bey ô absôrb ŏ hŏt ū blūe

[.=u] [.=u]nite û sûrge ŭ bŭt oo ooze oo book

Transcriber’s Note: [.=a] etc were printed as the letter with a macron above and a dot above that. These particular diacriticals are not used on any of the following pages, so the decision was taken not to attempt to represent them in any other way, because there are no corresponding precomposed characters in Unicode and font support for combining marks is often poor

The Vowel Sound as in “Awe”

Note: Tongue sags low and should not move; contact[5] is just a little over half way back of the middle of the mouth; mouth wide; lips well rounded. alder al´der, not ăl´der. almost—al´most, not al´must. also al´so, not ŏl´so.

always al´wāz, not al´wuz.

auction ak´shun, not ŏk´shun.

audience—a´dĭ-ens, not ŏ´jens.

cauliflower—ka´li-flow-er, not kŏ´li-flour.

caldron—kal´drun, not kŏ´drun.

Chaucer—Chau´ser, not Chŏw´ser.

Chicago—Shi-ca´gō, not Shi-kŏ´gō.

cornet—kôr´net, not kôr-net´.

exorbitant—egz-ôr´bi-tant.

falcon—fô´kn, not fŏl´kun. for—fôr, not fur.

ordeal—ôr´dēl, not ôr-dēl´.

ordinary—ôr´dĭn-ā-rĭ.

The Vowel Sound as in “Star”

Note: Tongue sags and is widened; contact is low and in center; mouth open wide; lips relaxed almost normally.

arctic—ärk´tĭk, not är´tĭk.

arduous—är´dū-ŭs.

armistice—är´mĭs-tĭs, not är-mĭs´tĭs.

bazar—ba-zär´.

encore—än-kor´, not ĕn´kor.

en route—än root´, not ĕn rout. far—fär, not fŭr.

father—fä´thẽr.

soprano—sō-prä´nō, not sō-prăn´ŏ.

staunch—stänch, not stănch.

taunt—tänt, not tănt.

tzar—zär.

tarlatan—tär´la-tan, not tarl´tan.

Parsifal—pär´sif-äl.

partisan—pär´ti-zăn.

particularly—pär-tik´yū-lẽr-lĭ.

The Vowel Sound as in “Ask”

Note: Tongue sags and is a trifle narrower than the above resonance in ä; mouth open wide; lips relaxed.

asked—åskt, not ăskt, nor ăst.

aversion—å-vẽr´shun, not a-ver´zhun.

bass (fish)—bås, not băs.

bath—båth, not băth.

chant—chånt, not chănt.

contrast (vb.)—kon-tråst´, not kon´trăst.

draft—dråft, not drăft.

draught—dråft, not drăft.

glass—glås, not glăs.

grant—grånt, not grănt.

grasp—gråsp, not grăsp.

mast—måst, not măst.

isinglass—ī´zĭng-glåss, not ī-zŭn´glăs.

pianist—pi-ån´ĭst, not pe´a-nist.

aft—åft, not ăft.

casket—kås´ket, not kăs´ket.

The Vowel Sound as in “Can”

Note: Tongue sags and widens; contact is front; mouth open moderately wide.

accept—ăk-sĕpt´, not ĕk-sept´.

accurate—ăk´kū-rat, not ăk´kẽr-ĭt.

algebra—ăl´je-bra, not ăl´je-brā.

ally—ăl-li´, not ăl´li (n) and (vb).

and—ănd, not ŭn, nor änd.

bade—băd, not bāde.

calcium—kăl´sĭ-ŭm, not kăl´shĭ-ŭm.

camera—kăm´e-ra.

canyon—kăn´yun.

catchup—kăch´up, not kĕch´up.

chasm—kăz´m, not kăz´um.

exact—egz-ăkt´, not eks-ăkt´.

flannel—flăn´nĕl, not flăn´nĕn.

harass—hăr´ăs, not har-răs´.

maritime—măr´ĭ-tĭm, not mâr´ĭ-tĭm.

olfactory—ŏl-făk´tō-rĭ, not ŏl-făk´trĭ.

The Vowel Sound as in “Fade”

Note: This is a diphthongal or double sound beginning on arch of tongue in middle of mouth and moving forward to just back of upper front teeth; mouth is open wide for first resonance but narrows for second.

aeronaut—ā´ẽr-ō-nat.

amiable—ā´mĭ-a-bl.

apparatus—ăp-pa-rā´tŭs, not ăp-pa-ră´tus.

apricot—ā´prĭ-cŏt, not ă´prĭ-cŏt.

chaos—kā´ōs.

Danish—dā´nĭsh, not dă´nĭsh.

data—dā´ta, not dă´ta.

disgrace—dĭs-grās´.

heinous—hā´nŭs, not hē´nŭs.

naked—nā´kĕd, not nĕ´kĕd.

acorn—ā´kŭrn, not ā´kŏrn.

patriotic—pā´trĭ-ŏt-ĭk, not păt´rĭ-ŏt-ĭk.

plague—plāg, not plĕg.

slake—slāk, not slăk.

wary—wā´rĭ, not wâ´ri.

ignoramus—ĭg-nō-rā´mŭs, not ĭg-nō-ră´mŭs.

The Vowel Sound as in “Led”

Note: Tongue arched; contact at top of arch; mouth moderately open; lips relaxed.

access—ăk´sĕs, or ăk-sĕs´.

address—(n) and (vb) ad-drĕs´.

cemetery—sĕm´ē-tĕr-ĭ, not sĕmĭ-trĭ.

centennial—sĕn-tĕn´nĭ-al.

equipage—ĕk´wĭ-pāj, not ĕ-kwĭp´ĕj.

equitable—ĕk´wĭ-ta-bl, no ĕ-kwĭ´ta-bl.

every—ĕv´ẽr-ĭ, not ĕv´rĭ.

evident—ĕv´ĭ-dĕnt, not ĕv´ĭ-dŭnt.

excellent—ĕk´sĕl-ĕnt, not ĕk´slŭnt.

preface—(n) and (vb) prĕf´ās.

legislature—lĕj´ĭs-lāt-yŭr

exit—ĕks´it, not ĕgz´it.

exist—ĕgz-ĭst´, not ĕks´ĭst.

irreparable—ĭr-rĕp´a-ra-ble, not ĭr-rē-păr´a-bl.

generally—jĕn´ẽr-al-ĭ.

instead—ĭn-stĕd´, not ĭn-stĭd´.

The Vowel Sound as in “We”

Note: Tongue arched to upper forward position; mouth aperture narrow. This is a single vowel resonance.

adhesive—ăd-hē´sĭv, not ăd-hē´zĭv.

aerial—ā-ē´rĭ-al.

appreciate—ap-prē´shĭ-āt, not ap-prē´sĭ-āt.

esprit—es-prē´.

evil—ē´vl, not ē´vĭl.

fealty—fē´al-tĭ.

fetish—fē´tish.

genii—jē´nĭ-ī.

grievous—grē´vŭs, not grē´vĭ-ŭs.

guarantee—găr-ăn-tē´.

ideal—ī-dē´al, not ī´dēl.

immediately—im-mē´dĭ-at-lĭ.

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