Temeljna svrha i cilj ovoga rada bilo je ispitati koliko su potrošači skloni dijeljenju svojih turističkih iskustva s drugima te putem kojih medija. Osim navedenog, drugi cilj provedenog istraživanja bilo je utvrditi koliko su potrošačima važna iskustva i komentari drugih posjetitelja u procesu donošenja odluke o kupnji. Istraživanje je provedeno metodom ispitivanja, a kao instrument korišten je anketni upitnik sastavljen od 22 pitanja. Utvrđivanjem problema istraživanja, postavljene su tri hipoteze. Od tri hipoteze, u potpunosti je dokazana samo prva koja pretpostavlja da su potrošačima tuđa iskustva i komentari od velike važnosti kod planiranja i odabira putovanja. Druga hipoteza je djelomično potvrđena, tj. potvrđeno je da su potrošači skloni dijeliti svoja iskustva s drugima u situaciji kada su jako zadovoljni dok s druge strane nije potvrđeno kako su potrošači skloni dijeliti svoja iskustva u situaciji kada su nezadovoljni uslugom ili proizvodom. Na kraju, potvrđena je i treća hipoteza koja pretpostavlja kako su potrošači skloni dijeljenju vlastitog turističkog iskustva putem više društvenih medija, iako je utvrđeno kako najveći broj ispitanika ne dijeli svoja turistička iskustva. Istraživano je i mišljenje ispitanika o turističkoj destinaciji iz snova, a iznenađujuće, najveći broj ispitanika je navelo hrvatske destinacije kao svoje destinacije iz snova kao i one koje su im dosada pružile najnezaboravnije turističko iskustvo. Potrebno je provesti detaljnija istraživanja kako bi se detaljnije istražilo novije društvene medije koji su dostupni potrošačima za dijeljenje svog iskustva

Kremer, T

Michel, H

Müller-Petke, M

Irons, T

Hermans, Thomas

Duglosh, R

Nguyen, F

English

Đuričković, Ivona

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See	discussions,	stats,	and	author	profiles	for	this	publication	at:	https://www.researchgate.net/publication/324543574Improving	the	accuracy	of	1D	SNMR	surveysusing	the	multi-central-loop	configurationPoster	·	April	2018DOI:	10.13140/RG.2.2.29003.28967CITATIONS06	authors,	including:Some	of	the	authors	of	this	publication	are	also	working	on	these	related	projects:SUITE4D	View	projectENIGMA	ITN	View	projectThomas	KremerInstitut	de	Physique	du	Globe	de	Paris6	PUBLICATIONS			4	CITATIONS			SEE	PROFILETrevor	IronsUniversity	of	Utah37	PUBLICATIONS			71	CITATIONS			SEE	PROFILEThomas	HermansGhent	University58	PUBLICATIONS			288	CITATIONS			SEE	PROFILEFrederic	NguyenUniversity	of	Liège114	PUBLICATIONS			791	CITATIONS			SEE	PROFILEAll	content	following	this	page	was	uploaded	by	Thomas	Kremer	on	16	April	2018.The	user	has	requested	enhancement	of	the	downloaded	file.Improving the accuracy of 2D SNMR surveysusing the multijcentraljloop configurationTG KremerEz HG MichelEz MG MüllerAPetke2z TG Irons3z TG Hermans4z RG Duglosch2z FG NguyenEGAnother possibility that would provide similar benefits and raise similar questionsB is to invertsimultaneously several data sets obtained independently Tat different timeskB using varyintransmitter sizes or excitation pulse lengthsE We investigate these aspects using a QTinversion approach TMRSMatlabB MullerQPetke et alxR AL"5kE We acknowledge that the mainchallenge is to adapt the regularization of the inversion processB so as to handle correctly thenoise originating from different data setsB although it seems less needed for the multijcentraljloop configuration than for independent data setsE FinallyB we introduce a new method for theinterpretation of SNMR data based on statistical analysis of a large number of modelsB calledthe predictionjfocused approach TPFAB Hermans et alxR AL"5kE We observe that the efficiency ofthe method benefits from the use of the multijcentraljloop configurationEThe centraljloop configuration for 2D SNMR surveysB where the receiver loop is smaller thanthe transmitter loop was first presented by Berhoozmand et alx bAL"5TE They compared itscharacteristics with the classical coincidentjloop configurationB and demonstrated that it issuperior on many aspects such as sensitivity distribution behaviorB resolution at large depthand signal to noise ratioE Based on these findingsB we investigate the potential of the multijcentraljloop configurationB where several smaller receivers are placed within the transmittingloopB and all the data sets are processed and inverted togetherE The objective is to takeadvantage of the complementary resolution and sensitivity features of the differentconfigurationsB in order to improve the quality of the inverted modelE We present herepreliminary tests and results obtained with synthetic and field dataEK, CentralHloop conﬁguration features x, Synthetic data=, PredictionHfocused approach k, Conclusion 0 ImplicationsReferencesFigx Aa shows the "D Kernels computed for the three loop configurationsbnormalized to the receiver loop area for comparisonTx Synthetic data sets aregenerated based on the model from Figx Abx These data sets are first invertedindependently then jointly bmerged dataTx Inversions are carried out with thecode MRSMatlab bMullerQPetke et alx AL"5TR using a QT aproach with complexdata and monoQexponential fitx Regularization is chosen as high as possiblewhile keeping a chiA value close to "x Statistical runs are performed to assessthe unecrtainty of the modelxbqbqThe centralQloop bCLT configuration has benefits compared to the cclassicalc coincidentloop configurationR as demonstrated by Berhoozmand et alx bAL"5Tx The complex kernelsshow additional sensitivity features in the shallow part bFigx "aTx AlsoR resolution studiesshow that the CL configuration probes deeper than the coincident one when usingcomplex data bFigx "bR modified after Berhoozmand et alx AL"5TxMultijcentraljloopW, MultiHcentralHloop 0 REAL DATA 0 Independent data setsaqaqbqWhen the signalQtoQnoise ratio is lowR the multijcentraljloop configurationtakes advantage of the varying sensitivity distributions and resolutioncapabilities of the separated configurations to better retrieve watercontent distributionsx Model uncertainties can be affected by thesimultaneous inversionR although we observe little deterioration with realfield dataxThe simultaneous inversion of independent data sets leads to astrong increase of the inverted model uncertaintyx Data weightingstrategies must be applied to correctly handle the different noisedistribution from each data setxThe Predictionjfocused approach is a promising method to interpretSNMR parameters without groing through an inversion processx It seemsto benefit from the increase of information brought by the use of themultijcentraljloop configurationBehroozmandB AE AEB AukenB EEB FiandacaB GEB W RejkjaerB SE T0&2Ckx Increasing the resolution and thesignalQtoQnoise ratio of magnetic resonance sounding data using a central loop configurationx GeophysicalSupplements to the Monthly Notices of the Royal Astronomical SocietyR ALGb"TR ANWQAG5xMüllerjPetkeB MEB BraunB MEB HertrichB MEB CostabelB SEB W WalbreckerB JE T0&2Ckx MRSmatlab—A softwaretool for processingR modelingR and inversion of magnetic resonance sounding dataMRSmatlabx GeophysicsR3"bNTR WB—QWBA"xHermansB TEB OwareB EEB W CaersB JE T0&2Ckx Direct prediction of spatially and temporally varying physicalproperties from time‐lapse electrical resistance datax Water Resources ResearchR GAb—TR 4A5AQ4A3WxaqE : University of Liegez Department of applied geophysicsz Liegez BelgiumG2 : Leibniz Institute for Applied Geophysicsz Hanoverz GermanyG3 : University of Utahz Department of Civil f Environmental EngineeringG4 : Ghent Universityz Department of Geologyz Gentz BelgiumGThe outer loop bd="LLmT is used as atransmitter and a receiverR and the inner loopsbd=GLm and d=ALmT are used as receivers onlyxGaussian noise of "GLL nV amplitude is addedto the data bscaling to the loop areaTR whichcorresponds to high noise conditionsR with asignal to noise ratio of about LxWxIn such high noise level contextsR the best reconstruction of the W aquifer model isobtained when using the multiQcentralQloop bmergedT data bFig AbTx All threestructures are detected and the water content correctly estimatedx However theuncertainty is stronger in some parts of the modelxPredictionHfocused approach is a new statistical method for the interpretation ofgeophysical data that does not require inversion of the data but rather relies on directstatistical relations between forecast variables and observed data wFig, =aq wHermans etal,F x6KGq,Models parameters Models responseForward modellingPrincipleComponentAnalysis wPCAqCanonical Corellation Analysis wCCAqReal dataKerneldensitySampling the cdfComputingRMSRelaxation timeWater contentaqbqTxHRxK 0 d=K66mRxx 0 d=k6mRxW 0 d=K6mWe have successfully applied the method to a synthetic dataset originating from a synthetic model wFig,=bF dashed black lineq, Gaussian noise of k66 nV amplitude is added to the data wscaling the the loopareaq, The results wFig, =bq showed that the multiHcentralHloop conﬁguration was advantageous to reducethe global uncertainty, Whereas the independent interpretations wTxK660RxK66F TxK660Rxk6 and TxK660RxK6q showed large uncertainties won the thickness of the ﬁrst layer for exampleqF the merged caseuncertainty is narrowed, MoreoverF the envelope of possibilities from the merged case is the only one thatcontains the true model, The water content of the second layer is too large in the TxK660RxK66conﬁguration and the water content of the ﬁrst layer is too low in the TxK660Rxk6 one, The TxK660RxK6case clearly shows that the data from this receiver are not suﬃcent on their own,Multijcentraljloop Independent data setsMultiQcentral loop data was acquired at the Schillerslage test site in Germanyx A circular loop bd=GLmTwas used as a receiver and transmitter and a secondary loop bd=WLmT was used as a receiverx FigxWa shows the results of the separated inversions and of the simultaneous inversionR with theiruncertaintyR against the mobile water content measured with borehole NMR borange lineTx Themerged data leads to an improved resolution of the water table without increasing uncertaintiesR anddelinates three different structuresR in accordance with the lithological logxA second data set was acquired on the same day at the same location using a A turn WLm diameter loop fortransmissionx Figx Wb shows the inversion results of this data set aloneR and of the simultaneous inversion ofthe GLm loop data bFig WaQleftT with this WLm loop datax The uncertainties are strongly increasedR making theinterpretation of the model much more difficultx The chiA value is high b"xNATR indicating that the inverse modelfails to fit correctly both data sets simultaneouslyxThe loss in data fitting precision is likely due toa wrong weighting of the data due the differentnoise distribution of the two data setsx Figx Wcshows the intial noise distribution used for dataweightingR after timeQgate integrationcqView publication stats