LEADER 01134nam a2200289 i 4500 001 991001833019707536 005 20020507152400.0 008 000713s1987 it ||| | ita 020 $a8814011613 035 $ab1157057x-39ule_inst 035 $aLE02725951$9ExL 040 $aDip.to Studi Giuridici$bita 084 $aCM-XIII/A 100 1 $aCoda, Vittorio$0437302 245 10$aCrisi di impresa e strategie di superamento /$c[relazioni di] V. Coda ... [et al.] 260 $aMilano :$bA. Giuffrè,$cstampa1987 300 $ax, 160 p. ;$c23 cm. 490 0 $aCollana di studi economico-aziendali. Centro universitario studi aziendali ;$v9 500 $aPresentate al Seminario tenuto a Palermo nel 1985. 500 $aIndicazione di A. sul dorso: AA. VV 650 4$aDirezione aziendale 907 $a.b1157057x$b01-03-17$c02-07-02 912 $a991001833019707536 945 $aLE027 CM-XIII/A 1$g1$i2027000208302$lle027$o-$pE0.00$q-$rl$s- $t0$u4$v2$w4$x0$y.i11775051$z02-07-02 996 $aCrisi di impresa e strategie di superamento$9895663 997 $aUNISALENTO 998 $ale027$b01-01-00$cm$da $e-$fita$git $h0$i1 LEADER 01540nam 2200409 450 001 9910711912103321 005 20190718130605.0 035 $a(CKB)5470000002488975 035 $a(OCoLC)1090062983 035 $a(EXLCZ)995470000002488975 100 $a20190318d2013 ua 0 101 0 $aeng 135 $aurcn||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 12$aA sand budget for Marble Canyon, Arizona $eimplications for long-term monitoring of sand storage change 210 1$a[Reston, Va.] :$cU.S. Department of the Interior, U.S. Geological Survey,$d2013. 215 $a1 online resource (4 unnumbered pages) $ccolor illustrations, color maps 225 1 $aFact sheet ;$v2013-3074 300 $aAuthor: Paul Grams; edited by James W. Hendley II; graphics and layout by Jeanne S. DiLeo. 300 $a"August 2013." 320 $aIncludes bibliographical references (pages [4]). 517 $aSand budget for Marble Canyon, Arizona 606 $aSedimentation and deposition$zArizona$zMarble Canyon (Coconino County : Canyon) 606 $aSand bars$zArizona$zMarble Canyon (Coconino County : Canyon) 615 0$aSedimentation and deposition 615 0$aSand bars 700 $aGrams$b Paul E.$01388550 702 $aHendley$b James W. 712 02$aGeological Survey (U.S.), 801 0$bGPO 801 1$bGPO 906 $aBOOK 912 $a9910711912103321 996 $aA sand budget for Marble Canyon, Arizona$93509741 997 $aUNINA LEADER 07609nam 22008775 450 001 9910483641003321 005 20251113194753.0 010 $a3-540-77343-6 024 7 $a10.1007/978-3-540-77343-6 035 $a(CKB)1000000000490348 035 $a(SSID)ssj0000316387 035 $a(PQKBManifestationID)11246741 035 $a(PQKBTitleCode)TC0000316387 035 $a(PQKBWorkID)10281777 035 $a(PQKB)10069465 035 $a(DE-He213)978-3-540-77343-6 035 $a(MiAaPQ)EBC337267 035 $a(MiAaPQ)EBC4976517 035 $a(MiAaPQ)EBC6413290 035 $a(Au-PeEL)EBL337267 035 $a(OCoLC)808680724 035 $a(PPN)123731763 035 $a(MiAaPQ)EBC5585884 035 $a(EXLCZ)991000000000490348 100 $a20100301d2007 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt 182 $cc 183 $acr 200 10$aAttention in Cognitive Systems. Theories and Systems from an Interdisciplinary Viewpoint $e4th International Workshop on Attention in Cognitive Systems, WAPCV 2007 Hyderabad, India, January 8, 2007 Revised Selected Papers /$fedited by Lucas Paletta, Erich Rome 205 $a1st ed. 2007. 210 1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d2007. 215 $a1 online resource (XI, 500 p.) 225 1 $aLecture Notes in Artificial Intelligence,$x2945-9141 ;$v4840 300 $aEarlier conferences titled: Attention and performance in computational vision. 300 $a"euCognition"--Cover. 311 08$a3-540-77342-8 320 $aIncludes bibliographical references and index. 327 $aEmbodiment of Attention -- The Embodied Dynamics of Emotion, Appraisal and Attention -- The Role of Attention in Creating a Cognitive System -- The Influence of the Body and Action on Spatial Attention -- Abstraction Level Regulation of Cognitive Processing Through Emotion-Based Attention Mechanisms -- Embodied Active Vision in Language Learning and Grounding -- Language Label Learning for Visual Concepts Discovered from Video Sequences -- Cognitive Control of Attention -- Learning to Attend ? From Bottom-Up to Top-Down -- An Attentional System Combining Top-Down and Bottom-Up Influences -- The Selective Attention for Identification Model (SAIM): Simulating Visual Search in Natural Colour Images -- A Bayesian Approach to Attention Control and Concept Abstraction -- Modeling of Saliency and Visual Search -- An Information Theoretic Model of Saliency and Visual Search -- An Experimental Comparison of Three Guiding Principles for the Detection of Salient Image Locations: Stability, Complexity, and Discrimination -- A Proto-object Based Visual Attention Model -- Context Driven Focus of Attention for Object Detection -- Color Saliency and Inhibition Using Static and Dynamic Scenes in Region Based Visual Attention -- I See What You See: Eye Movements in Real-World Scenes Are Affected by Perceived Direction of Gaze -- Sequential Attention -- Selective Attention in the Learning of Viewpoint and Position Invariance -- Generating Sequence of Eye Fixations Using Decision-Theoretic Attention Model -- Reinforcement Learning for Decision Making in Sequential Visual Attention -- Biologically Inspired Framework for Learning and Abstract Representation of Attention Control -- Biological Aspects of Attention -- Modeling the Dynamics of Feature Binding During Object-Selective Attention -- The Spiking Search overTime and Space Model (sSoTS): Simulating Dual Task Experiments and the Temporal Dynamics of Preview Search -- On the Role of Dopamine in Cognitive Vision -- Differences and Interactions Between Cerebral Hemispheres When Processing Ambiguous Words -- Attention in Early Vision: Some Psychophysical Insights -- Auditory Gist Perception: An Alternative to Attentional Selection of Auditory Streams? -- Applications of Attentive Vision -- Simultaneous Robot Localization and Mapping Based on a Visual Attention System -- Autonomous Attentive Exploration in Search and Rescue Scenarios -- Attention-Based Landmark Selection in Autonomous Robotics -- Simulation and Formal Analysis of Visual Attention in Cognitive Systems -- Region-Oriented Visual Attention Framework for Activity Detection -- Autonomous Attentive Exploration in Search and Rescue Scenarios. 330 $aAttentionhasbeenrepresentingacorescienti?ctopicinthedesignofAI-enabled systems within the last decades. Today, in the ongoing debate, design, and c- putationalmodelingofarti?cialcognitivesystems,attentionhasgainedacentral position as a focus of research. For instance, attentional methods are considered in investigating the interfacing of sensory and cognitive information processing, for the organization of behaviors, and for the understanding of individual and social cognition in re?ection of infant development. Whilevisualcognitionplaysacentralroleinhumanperception,?ndingsfrom neuroscience and experimental psychology have provided strong evidence about theperception-actionnatureofcognition.Theembodiednatureofsensory-motor intelligence requires a continuous and focused interplay between the control of motor activities and the interpretation of feedback from perceptual modalities. Decision making about the selection of information from the incoming sensory stream ? in tune with contextual processing on a current task and an agent?s global objectives ? becomes a further challenging issue in attentional control. Attention must operate at interfaces between bottom-up driven world int- pretation and top-down driven information selection, thus acting at the core of arti?cial cognitive systems. These insights have already induced changes in AI-related disciplines, such as the design of behavior-based robot control and the computational modeling of animats. Today, the development of enabling technologiessuch as autonomous robotic systems,miniaturizedmobile?evenwearable?sensors,andambientintelligence systems involves the real-time analysis of enormous quantities of data. These data have to be processed in an intelligent way to provide ?on time delivery?of the required relevant information. Knowledge has to be applied about what needs to be attended to, and when, and what to do in a meaningful sequence, in correspondence with visual feedback. 410 0$aLecture Notes in Artificial Intelligence,$x2945-9141 ;$v4840 606 $aComputer science 606 $aArtificial intelligence 606 $aComputer vision 606 $aPattern recognition systems 606 $aComputer graphics 606 $aNeurosciences 606 $aTheory of Computation 606 $aArtificial Intelligence 606 $aComputer Vision 606 $aAutomated Pattern Recognition 606 $aComputer Graphics 606 $aNeuroscience 615 0$aComputer science. 615 0$aArtificial intelligence. 615 0$aComputer vision. 615 0$aPattern recognition systems. 615 0$aComputer graphics. 615 0$aNeurosciences. 615 14$aTheory of Computation. 615 24$aArtificial Intelligence. 615 24$aComputer Vision. 615 24$aAutomated Pattern Recognition. 615 24$aComputer Graphics. 615 24$aNeuroscience. 676 $a006.3/7 702 $aRome$b Erich 702 $aPaletta$b Lucas 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910483641003321 996 $aAttention in Cognitive Systems. Theories and Systems from an Interdisciplinary Viewpoint$9772086 997 $aUNINA