LEADER 03582nam 22006492 450 001 9910463090303321 005 20151005020621.0 010 $a1-107-23389-5 010 $a1-107-30116-5 010 $a1-107-30543-8 010 $a1-107-30624-8 010 $a1-107-30844-5 010 $a1-107-31179-9 010 $a1-299-00891-7 010 $a1-107-31399-6 010 $a0-511-67591-7 035 $a(CKB)2670000000329880 035 $a(EBL)1113038 035 $a(OCoLC)827210368 035 $a(SSID)ssj0000820170 035 $a(PQKBManifestationID)11459503 035 $a(PQKBTitleCode)TC0000820170 035 $a(PQKBWorkID)10874243 035 $a(PQKB)10472202 035 $a(UkCbUP)CR9780511675911 035 $a(MiAaPQ)EBC1113038 035 $a(Au-PeEL)EBL1113038 035 $a(CaPaEBR)ebr10649593 035 $a(CaONFJC)MIL432141 035 $a(EXLCZ)992670000000329880 100 $a20100211d2013|||| uy| 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aObstacles to ethical decision-making $emental models, Milgram and the problem of obedience /$fPatricia H. Werhane, Laura Pincus Hartman, Crina Archer, Elaine E. Englehardt, and Michael S. Pritchard$b[electronic resource] 210 1$aCambridge :$cCambridge University Press,$d2013. 215 $a1 online resource (xii, 246 pages) $cdigital, PDF file(s) 300 $aTitle from publisher's bibliographic system (viewed on 05 Oct 2015). 311 $a1-107-44205-2 311 $a1-107-00003-3 320 $aIncludes bibliographical references and indexes. 327 $aMachine generated contents note: 1. Introduction; 2. The role of mental models in social construction; 3. The Milgram studies: obedience, disobedience, and ethical context; 4. Obstacles to ethical decision-making in the perception of ethical context; 5. Obstacles to ethical decision-making in impact analysis and action; 6. Managing ethical obstacles; 7. Problematic mental models: some applications; 8. Conclusion. 330 $aIn commerce, many moral failures are due to narrow mindsets that preclude taking into account the moral dimensions of a decision or action. In turn, sometimes these mindsets are caused by failing to question managerial decisions from a moral point of view, because of a perceived authority of management. In the 1960s, Stanley Milgram conducted controversial experiments to investigate just how far obedience to an authority figure could subvert his subjects' moral beliefs. In this thought-provoking work, the authors examine the prevalence of narrow mental models and the phenomenon of obedience to an authority to analyse and understand the challenges which business professionals encounter in making ethical decisions. Obstacles to Ethical Decision-Making proposes processes - including collaborative input and critique - by which individuals may reduce or overcome these challenges. It provides decision-makers at all levels in an organisation with the means to place ethical considerations at the heart of managerial decision-making. 606 $aBusiness ethics 606 $aDecision making$xMoral and ethical aspects 615 0$aBusiness ethics. 615 0$aDecision making$xMoral and ethical aspects. 676 $a174/.4 700 $aWerhane$b Patricia Hogue$0118364 801 0$bUkCbUP 801 1$bUkCbUP 906 $aBOOK 912 $a9910463090303321 996 $aObstacles to ethical decision-making$92492457 997 $aUNINA LEADER 04917nam 2200565 450 001 9910479931903321 005 20180322121046.0 010 $a1-4613-9777-4 024 7 $a10.1007/978-1-4613-9777-9 035 $a(CKB)3400000000093667 035 $a(SSID)ssj0000935118 035 $a(PQKBManifestationID)11575536 035 $a(PQKBTitleCode)TC0000935118 035 $a(PQKBWorkID)10949571 035 $a(PQKB)10908766 035 $a(DE-He213)978-1-4613-9777-9 035 $a(MiAaPQ)EBC3079950 035 $a(EXLCZ)993400000000093667 100 $a20170913h19901990 uy 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt 182 $cc 183 $acr 200 12$aA taxonomy for texture description and identification /$fA. Ravishankar Rao 210 1$aNew York :$cSpringer-Verlag,$d1990. 210 4$dİ1990 215 $a1 online resource (XXIII, 198 p.) 225 1 $aSpringer Series in Perception Engineering 300 $a"With 79 Illustrations." 311 $a1-4613-9779-0 320 $aIncludes bibliographical references and index. 327 $a1 Introduction -- 1.1 Scope of the book -- 1.2 Importance of texture -- 1.3 Potential applications of this research -- 1.4 Issues in automated process control involving computer vision -- 1.5 A taxonomy for texture -- 1.6 Outline -- 2 Computing oriented texture fields -- 2.1 Introduction -- 2.2 Background -- 2.3 Oriented Texture Fields -- 2.4 Experimental Methods -- 2.5 Experimental Results -- 2.6 Analyzing texture at different scales -- 2.7 Processing of the intrinsic images -- 2.8 Conclusions -- 3 The analysis of oriented textures through phase portraits -- 3.1 Introduction -- 3.2 Background -- 3.3 Geometric theory of differential equations -- 3.4 Experimental Methods -- 3.5 Experimental Results -- 3.6 Experiments with noise addition -- 3.7 A related model from fluid flow analysis -- 3.8 Discussion -- 3.9 Conclusion -- 4 Analyzing strongly ordered textures -- 4.1 Introduction -- 4.2 Extraction of primitives -- 4.3 Extracting structure from primitives -- 4.4 Models for strongly ordered textures -- 4.5 Symbolic descriptions: models from petrography -- 4.6 Frieze groups and wallpaper groups -- 4.7 Implications for computer vision -- 4.8 Summary -- 5 Disordered textures -- 5.1 Statistical measures for disordered textures -- 5.2 Describing disordered textures by means of the fractal dimension -- 5.3 Computing the fractal dimension -- 5.4 Experimental Results -- 5.5 Conclusion -- 6 Compositional textures -- 6.1 Introduction -- 6.2 Primitive textures -- 6.3 A Parametrized symbol set -- 6.4 Three types of composition -- 6.5 Linear combination (transparent overlap) -- 6.6 Functional composition -- 6.7 Opaque overlap -- 6.8 Definition of texture -- 6.9 A complete taxonomy for texture -- 6.10 Implementing the taxonomy -- 6.11 Conclusion -- 7 Conclusion -- 7.1 Summary of results -- 7.2 Contributions -- 7.3 Future Work -- B Region Refinement -- C Preparation of the manuscript -- Permissions. 330 $aA central issue in computer vision is the problem of signal to symbol transformation. In the case of texture, which is an important visual cue, this problem has hitherto received very little attention. This book presents a solution to the signal to symbol transformation problem for texture. The symbolic de- scription scheme consists of a novel taxonomy for textures, and is based on appropriate mathematical models for different kinds of texture. The taxonomy classifies textures into the broad classes of disordered, strongly ordered, weakly ordered and compositional. Disordered textures are described by statistical mea- sures, strongly ordered textures by the placement of primitives, and weakly ordered textures by an orientation field. Compositional textures are created from these three classes of texture by using certain rules of composition. The unifying theme of this book is to provide standardized symbolic descriptions that serve as a descriptive vocabulary for textures. The algorithms developed in the book have been applied to a wide variety of textured images arising in semiconductor wafer inspection, flow visualization and lumber processing. The taxonomy for texture can serve as a scheme for the identification and description of surface flaws and defects occurring in a wide range of practical applications. 410 0$aSpringer series in perception engineering. 606 $aComputer vision 606 $aVisual texture recognition 608 $aElectronic books. 615 0$aComputer vision. 615 0$aVisual texture recognition. 676 $a006.6 676 $a006.37 700 $aRavishankar Rao$b A.$0961283 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910479931903321 996 $aA taxonomy for texture description and identification$92179247 997 $aUNINA