01357nam 2200397 n 450 99639031500331620221108074507.0(CKB)1000000000651868(EEBO)2240933823(UnM)99853597(EXLCZ)99100000000065186819920624d1585 uy |itaurbn||||a|bb|Cabala del cavallo pegaseo[electronic resource] Con l'aggiunta dell'Asino cillenico. Deseritta dal Nolano: dedicata al Vescouo di CasamarcianoParigi [i.e. London] Appresso Antonio Baio [i.e. J. Charlewood]Anno 1585[96] pBy Giordano Bruno.Imprint false; actual place of publication and printer's name from STC."L'Asino cillenico del Nolano" has caption title.Signatures: A * ² A-D.Reproduction of the original in the British Library.eebo-0018Christian ethicsEarly works to 1800SoulEarly works to 1800Christian ethicsSoulBruno Giordano1548-1600.45390Cu-RivESCu-RivESCStRLINWaOLNBOOK996390315003316Cabala del Cavallo Pegaseo530263UNISA06126nam 22006495 450 991029956430332120200630222149.0981-10-6692-210.1007/978-981-10-6692-4(CKB)4100000000881599(DE-He213)978-981-10-6692-4(MiAaPQ)EBC6299350(MiAaPQ)EBC5591606(Au-PeEL)EBL5591606(OCoLC)1066188494(PPN)220125066(EXLCZ)99410000000088159920171026d2018 u| 0engurnn|008mamaatxtrdacontentcrdamediacrrdacarrierKinesthetic Perception A Machine Learning Approach /by Subhasis Chaudhuri, Amit Bhardwaj1st ed. 2018.Singapore :Springer Singapore :Imprint: Springer,2018.1 online resource (XV, 138 p. 50 illus., 44 illus. in color.) Studies in Computational Intelligence,1860-949X ;748981-10-6691-4 Intro -- Preface -- Acknowledgements -- Contents -- About the Authors -- 1 Introduction -- 1.1 Basics of Haptics -- 1.1.1 Various Research Areas in Haptics -- 1.1.2 Possible Applications -- 1.2 Kinesthetic Perception -- 1.3 Perception: Aware Engineering Design -- 1.4 Organization of the Book -- References -- 2 Perceptual Deadzone -- 2.1 Haptic Data Compression -- 2.2 Perceptual Deadzone for Multidimensional Signals -- 2.3 Effect of Rate of Change of Kinesthetic Stimuli -- References -- 3 Predictive Sampler Design for Haptic Signals -- 3.1 Introduction -- 3.2 Experimental Setup -- 3.2.1 Device Setup -- 3.2.2 Signal Characteristics -- 3.2.3 Lag in User Response -- 3.2.4 Collected Data -- 3.3 Classification of Haptic Response -- 3.3.1 Performance Metric -- 3.3.2 Weber Classifier -- 3.3.3 Level Crossing Classifier -- 3.3.4 Classifiers Based on Decision Tree and Random Forests -- 3.3.5 Effect of Temporal Spacing -- 3.3.6 Significance Test for Classifiers -- 3.4 Applications in Adaptive Sampling -- References -- 4 Deadzone Analysis of 2-D Kinesthetic Perception -- 4.1 Introduction -- 4.2 Experimental Setup -- 4.2.1 Signal Characteristics and User Response -- 4.2.2 Data Statistics -- 4.3 Determination of Perceptual Deadzone -- 4.3.1 The Weber Classifier -- 4.3.2 Level Crossing Classifier -- 4.3.3 Elliptical Deadzone -- 4.3.4 Oriented Elliptical Deadzone -- References -- 5 Effect of Rate of Change of Stimulus -- 5.1 Introduction -- 5.2 Design of Experiment -- 5.2.1 Kinesthetic Force Stimulus -- 5.2.2 Data Collection -- 5.3 System Correction -- 5.4 Estimation of Decision Boundary -- 5.4.1 Parametric Decision Boundary -- 5.4.2 Nonparametric Decision Boundary -- 5.5 Analysis of Results -- References -- 6 Temporal Resolvability of Stimulus -- 6.1 Introduction -- 6.1.1 Motivation for the Study -- 6.1.2 Related Work -- 6.1.3 Our Approach.6.2 Experimental Setup -- 6.2.1 Signal Characteristics -- 6.2.2 Data Collection -- 6.3 Estimation of Temporal Resolution -- 6.4 Effect of Fatigue -- 6.5 Application in Data Communication -- References -- 7 Task Dependence of Perceptual Deadzone -- 7.1 Introduction -- 7.1.1 Objective of the Study -- 7.1.2 Prior Work -- 7.1.3 Our Approach -- 7.2 Design of Experiment -- 7.2.1 Kinesthetic Force Stimulus -- 7.2.2 Data Statistics -- 7.3 Estimation of Perceptual Deadzones -- References -- 8 Sequential Effect on Kinesthetic Perception -- 8.1 Introduction -- 8.2 Sequential Effect -- 8.3 Quantification of Sequential Effect -- 8.3.1 Logistic Regression -- 8.3.2 Description of the Regression Model -- 8.4 Analysis of Effect on Comparative Task -- 8.5 Analysis of Effect on Discriminative Task -- References -- 9 Conclusions -- Index.This book focuses on the study of possible adaptive sampling mechanisms for haptic data compression aimed at applications like tele-operations and tele-surgery. Demonstrating that the selection of the perceptual dead zones is a non-trivial problem, it presents an exposition of various issues that researchers must consider while designing compression algorithms based on just noticeable difference (JND). The book begins by identifying perceptually adaptive sampling strategies for 1-D haptic signals, and goes on to extend the findings on multidimensional signals to study directional sensitivity, if any. The book also discusses the effect of the rate of change of kinesthetic stimuli on the JND, temporal resolution for the perceivability of kinesthetic force stimuli, dependence of kinesthetic perception on the task being performed, the sequential effect on kinesthetic perception, and, correspondingly, on the perceptual dead zone. Offering a valuable resource for researchers, professionals, and graduate students working on haptics and machine perception studies, the book can also support interdisciplinary work focused on automation in surgery.Studies in Computational Intelligence,1860-949X ;748RoboticsAutomationArtificial intelligenceAutomatic controlRobotics and Automationhttps://scigraph.springernature.com/ontologies/product-market-codes/T19020Artificial Intelligencehttps://scigraph.springernature.com/ontologies/product-market-codes/I21000Control and Systems Theoryhttps://scigraph.springernature.com/ontologies/product-market-codes/T19010Robotics.Automation.Artificial intelligence.Automatic control.Robotics and Automation.Artificial Intelligence.Control and Systems Theory.004.77Chaudhuri Subhasisauthttp://id.loc.gov/vocabulary/relators/aut846530Bhardwaj Amitauthttp://id.loc.gov/vocabulary/relators/autMiAaPQMiAaPQMiAaPQBOOK9910299564303321Kinesthetic Perception2504035UNINA