LEADER 02336nam 2200613Ia 450 001 9910788539903321 005 20230725045929.0 010 $a1-283-30879-7 010 $a9786613308795 010 $a1-4438-3313-4 035 $a(CKB)3360000000432111 035 $a(EBL)1165705 035 $a(OCoLC)829714465 035 $a(SSID)ssj0000681190 035 $a(PQKBManifestationID)12303398 035 $a(PQKBTitleCode)TC0000681190 035 $a(PQKBWorkID)10673324 035 $a(PQKB)10306341 035 $a(MiAaPQ)EBC1165705 035 $a(Au-PeEL)EBL1165705 035 $a(CaPaEBR)ebr10648346 035 $a(CaONFJC)MIL330879 035 $a(OCoLC)751835416 035 $a(FINmELB)ELB144756 035 $a(EXLCZ)993360000000432111 100 $a20120413d2011 uy 0 101 0 $aeng 135 $aurcn||||||||| 181 $ctxt 182 $cc 183 $acr 200 10$aCompelling form$b[electronic resource] $earchitecture as visual persuasion /$fby J. Donald Ragsdale 210 $aNewcastle upon Tyne $cCambridge Scholars$d2011 215 $a1 online resource (313 p.) 300 $aDescription based upon print version of record. 311 $a1-4438-3286-3 320 $aIncludes bibliographical references (p. [290]-293) and index. 327 $aTABLE OF CONTENTS; LIST OF FIGURES; ACKNOWLEDGEMENTS; PREFACE; CHAPTER ONE; CHAPTER TWO; CHAPTER THREE; CHAPTER FOUR; CHAPTER FIVE; CHAPTER SIX; CHAPTER SEVEN; CHAPTER EIGHT; CHAPTER NINE; CHAPTER TEN; CHAPTER ELEVEN; CHAPTER TWELVE; AFTERWORD; REFERENCES; INDEX 330 $aCompelling Form: Architecture as Visual Persuasion is an assessment of the visual persuasiveness of buildings. It demonstrates that architecture is as capable of social influence as speeches or advertisements are and that an awareness of this influence pr 606 $aArchitecture and society 606 $aCommunication in architecture 606 $aPersuasion (Psychology) 615 0$aArchitecture and society. 615 0$aCommunication in architecture. 615 0$aPersuasion (Psychology) 676 $a720.1 700 $aRagsdale$b J. Donald$01509821 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910788539903321 996 $aCompelling form$93741995 997 $aUNINA LEADER 02771nam0 2200601 i 450 001 VAN0123973 005 20230704090448.309 017 70$2N$a9783319568294 100 $a20191004d2017 |0itac50 ba 101 $aeng 102 $aCH 105 $a|||| ||||| 200 1 $aModels, algorithms and technologies for network analysis$eNET 2016, Nizhny Novgorod, Russia, May 2016$fValery A. Kalyagin ... [et al.] editors 210 $aCham$cSpringer$d2017 215 $axiii, 277 p.$cill.$d24 cm 410 1$1001VAN0102574$12001 $aSpringer proceedings in mathematics & statistics$1210 $aBerlin [etc.]$cSpringer$v197 500 1$3VAN0235734$aModels, algorithms and technologies for network analysis. NET 2016$92598094 606 $a90Bxx$xOperations research and management science [MSC 2020]$3VANC019945$2MF 606 $a90Cxx$xMathematical programming [MSC 2020]$3VANC020086$2MF 606 $a68Rxx$xDiscrete mathematics in relation to computer science [MSC 2020]$3VANC020358$2MF 606 $a90-XX$xOperations research, mathematical programming [MSC 2020]$3VANC025650$2MF 610 $aComplex Networks$9KW:K 610 $aDynamic superclusters$9KW:K 610 $aEfficient algorithms$9KW:K 610 $aLattice-based algorithm$9KW:K 610 $aMachine learning$9KW:K 610 $aMissing node attributes$9KW:K 610 $aModel Applicability$9KW:K 610 $aMulti-layered modeling$9KW:K 610 $aMultivariate distributions$9KW:K 610 $aNetwork analysis$9KW:K 610 $aNetwork methods$9KW:K 610 $aNetwork structures$9KW:K 610 $aPower transmission grids$9KW:K 610 $aScheduling problems$9KW:K 610 $aSimulation modeling$9KW:K 610 $aSocial networks$9KW:K 610 $aSpectral Partitions$9KW:K 610 $aStock market networks$9KW:K 610 $aTelecommunication networks$9KW:K 610 $aTheoretical models$9KW:K 620 $aCH$dCham$3VANL001889 702 1$aKalyagin$bValery A.$3VANV081030 712 12$aInternational Conference on Network Analysis$d6.$f2016$eNizhny Novgorod, Russ$3VANV095439 712 $aSpringer $3VANV108073$4650 801 $aIT$bSOL$c20240614$gRICA 856 4 $uhttp://doi.org/10.1007/978-3-319-56829-4$zE-book ? Accesso al full-text attraverso riconoscimento IP di Ateneo, proxy e/o Shibboleth 899 $aBIBLIOTECA DEL DIPARTIMENTO DI MATEMATICA E FISICA$1IT-CE0120$2VAN08 912 $fN 912 $aVAN0123973 950 $aBIBLIOTECA DEL DIPARTIMENTO DI MATEMATICA E FISICA$d08CONS e-book 0794 $e08eMF794 20191004 996 $aModels, algorithms and technologies for network analysis : NET 2016$92598094 997 $aUNICAMPANIA