FROM VISION SCIENCE TO DATA SCIENCE: APPLYING PERCEPTION TO PROBLEMS IN BIG DATA
|
|
|
- Dylan Boyd
- 5 years ago
- Views:
Transcription
1 1/37 National Academy of Science, 2018 FROM VISION SCIENCE TO DATA SCIENCE: APPLYING PERCEPTION TO PROBLEMS IN BIG DATA Remco Chang Associate Professor, Computer Science Tufts University
2 2/37 National Academy of Science, 2018 ROLE OFVISUALIZATION IN BIG DATA Big Data Machine Learning Databases Visualization Visualization allows the user to interactively and visually explore large amounts of data
3 3/37 National Academy of Science, 2018 ROLE OFVISUALIZATION IN BIG DATA Big Data Machine Learning Databases Visualization Tableau Visualization allows the user to interactively and visually explore large amounts of data
4 4/37 National Academy of Science, 2018 ROLE OFVISUALIZATION IN BIG DATA Big Data Machine Learning Databases Visualization Visualization allows the user to interactively and visually explore large amounts of data Spotfire
5 5/37 National Academy of Science, 2018 ROLE OFVISUALIZATION IN BIG DATA Big Data Machine Learning Databases Visualization Visualization allows the user to interactively and visually explore large amounts of data SAS Visual Analytics
6 6/37 National Academy of Science, 2018 DOMAIN-SPECIFIC VISUALANALYTICS SYSTEMS Financial Fraud Detection Bank of America Political Simulation DARPA Global Terrorism Database DHS Bridge Maintenance US DOT Biomechanical Motion Brown University
7 7/37 National Academy of Science, 2018 APPLICATIONS OF VISUAL ANALYTICS Financial Fraud Detection Bank of America Political Simulation DARPA Global Terrorism Database DHS Bridge Maintenance US DOT Biomechanical Motion Brown University R. Chang et al., Two Visualization Tools for Analysis of Agent-Based Simulations in Political Science. IEEE CG&A, 2012
8 8/37 National Academy of Science, 2018 APPLICATIONS OF VISUAL ANALYTICS Financial Fraud Detection Bank of America Political Simulation DARPA Global Terrorism Database DHS Bridge Maintenance US DOT Biomechanical Motion Brown University What Who Evidence Box Original Data Where When R. Chang et al., Investigative Visual Analysis of Global Terrorism, Journal of Computer Graphics Forum, 2008.
9 9/37 National Academy of Science, 2018 APPLICATIONS OF VISUAL ANALYTICS Financial Fraud Detection Bank of America Political Simulation DARPA Global Terrorism Database DHS Bridge Maintenance US DOT Biomechanical Motion Brown University R. Chang et al., An Interactive Visual Analytics System for Bridge Management, Journal of Computer Graphics Forum, To Appear.
10 10/37 National Academy of Science, 2018 APPLICATIONS OF VISUAL ANALYTICS Financial Fraud Detection Bank of America Political Simulation DARPA Global Terrorism Database DHS Bridge Maintenance US DOT Biomechanical Motion Brown University R. Chang et al., Interactive Coordinated Multiple-View Visualization of Biomechanical Motion Data, IEEE Vis (TVCG) 2009.
11 11/37 National Academy of Science, 2018 INSUFFICIENT FOR BIG DATA? Scalability Data growing faster than compute power With Big Data, every user s interaction can take seconds, minutes, hours, or days to complete. For Library-of-Congress-scale of IC data, existing tools do not scale to meet the needs (Dr. Fingar).
12 12/37 National Academy of Science, 2018 DATA VISUALIZATION PIPELINE
13 13/37 National Academy of Science, 2018 INTERACTIVE SYSTEMS FOR BIG DATA Effects of Latency Interrupts analysis flow Cannot meet time sensitive needs (Dr. Wilson) Affects short-term memory 500ms affects exploration 10 minutes affects recall Conversely, highly interactive systems allow: Higher throughput for analysts Better communication between human and computer Increase efficiency and accuracy of decision
14 14/37 National Academy of Science, 2018 TAKING A STEP BACK: BIG DATA VISUALIZATION Visualize 10 million data points Information theoretic upperbound 10 million data -> 1 million pixels 10:1 reduction in information Problem is in fact worse, because There is a perceptual and cognitive limit Adding more pixels doesn t solve the problem 1000 pixels 1000 pixels 1000x1000 = 1 million
15 15/37 National Academy of Science, 2018 TURNING OBSTACLES INTO OPPORTUNITIES! Fitting billions of data points into million of pixels can be an obstacle Or it can be an opportunity!!
16 16/37 National Academy of Science, 2018 OPPORTUNITIES IN BIG DATA VISUALIZATION 1. We should never fetch more than 1 million rows of data from the database How to pick the 1 million points? 2. Since the user can t see the details anyway, we can simplify the visualization a little for as long as the user can t perceive the difference How to model the perceptual limits in data visualization?
17 17/37 National Academy of Science, 2018 A SIMPLE EXAMPLE OF PERCEPTION-DRIVEN COMPUTATION Simple Box-and-Whisker plots (or Box Plots) Spot the difference?
18 18/37 National Academy of Science, 2018 A SIMPLE EXAMPLE OF PERCEPTION-DRIVEN COMPUTATION This difference, although perceptually small, can mean the difference of scanning all data points or using a smaller sampled data set. If the user cannot perceive the difference, we can save computation time by not rendering the perfect visualization!
19 19/37 National Academy of Science, 2018 WHY VISION SCIENCE MATTERS Spot the difference? Although the difference between the two bars is the same as the previous example, we know from vision science that the difference here is easier to spot. But these are rules, not models Does not indicate how many pixels for how much sampling
20 20/37 National Academy of Science, 2018 PERCEPTION-DRIVEN COMPUTATION Perception & Cognitive Model Visualization Approximate Data & Computation
21 21/37 National Academy of Science, 2018 PERCEPTUAL MODELING IN DATA VISUALIZATION? Requires collaboration between the Perceptual Psychologists with Computer Scientists. One promising direction is to consider modeling the JND (just noticeable differences) in different visualization designs. Example of JND: Imagine yourself in a dark room
22 22/37 National Academy of Science, 2018 PERCEPTUAL MODELING Weber s Law (mid 1800s) Low-level perceptual discrimination (sound, touch, taste, brightness, etc.) Perceived Difference Weber Fraction (via experiments) dddd = kk dddd SS Change in Intensity Intensity of the Stimulus
23 23/37 National Academy of Science, 2018 PERCEPTUAL MODELING Weber s Law (mid 1800s) Low-level perceptual discrimination (sound, touch, taste, brightness, etc.) dddd = kk dddd Given a fixed stimulus SS, the smallest of dddd that can be perceived by humans is known as the Just Noticeable Difference, or JND SS
24 24/37 National Academy of Science, 2018 BALDRIDGE & RENSINK, 2010: PERCEPTION OF CORRELATION Δr = 0.05
25 25/37 National Academy of Science, 2018 BALDRIDGE & RENSINK, 2010: PERCEPTION OF CORRELATION Δr = 0.05
26 26/37 National Academy of Science, 2018 PERCEPTION OF CORRELATION In 2010, Ron Rensink and colleague found that the perception of correlation in a scatterplot follows Weber s Law worse In 2014, our team extended this work to determine if perception of correlation in all bivariate visualizations follows Weber s Law better
27 27/37 National Academy of Science, 2018
28 28/37 National Academy of Science, 2018
29 29/37 National Academy of Science, 2018
30 30/37 National Academy of Science, 2018
31 31/37 National Academy of Science, 2018
32 32/37 National Academy of Science, 2018 less precise more precise
33 33/37 National Academy of Science, 2018 The perception of correlation in every tested chart can be modeled using Weber s law.
34 34/37 National Academy of Science, 2018 WHY IS THIS SO COOL? Positives: 1. These models have both descriptive and prescriptive powers It describes what people see (and don t see) from the data It predicts what people will see given a new data 2. They can be used to quantitatively compare the effectiveness of visualizations 3. They can be used to drive computation (sampling) Useful, but limited to correlation
35 35/37 National Academy of Science, 2018 BEYOND CORRELATION: VISUALIZATION METAMERS Metamers: Stimuli that are different but appear the same (under some condition) Visualization Metamers Visualizations that appear the same (under some condition) Uses much less data Are much faster to render Collaboration with Steve Franconeri (Northwestern) and Eugene Wu (Columbia)
36 36/37 National Academy of Science, 2018 VISUALIZATION METAMERS Focus: 1D visualizations Bar charts, line graphs, heatmaps, etc. Properties of the model for visualization metamers Recursive Peaks and valleys Slope Concavity Texture Progressive Refinement
37 37/37 National Academy of Science, 2018 IN 10 YEARS Science of Perception (and Cognition) What do people see (and not see) when perceiving data? Can we model these properties and anticipate what mistakes will be made? Engineering of Data Systems based on Perception and Cognitive Principles Compute only what you can see Conversely, Make more clear what an analyst cannot see Two sides of the same coin. Collaboration between the fields (Psych, CogSci, CS, IC) is essential
38 38/37 National Academy of Science, 2018 QUESTIONS?
39 39/37 National Academy of Science, 2018 Backup Slides
40 40/37 National Academy of Science, 2018 SUMMARY & CONCLUSION Need more cross-disciplinary research between Vision Science and Computer Science In 10 Years: need more systems to help analyst combat the data deluge More CPUs is not the answer! Perception- and Cognitive- based approaches enable building machines that make analysts smarter (Dr. Klein) Data analysis for the Masses (DARPA) Support Bayesian Reasoning Interaction Inferencing for Predictive Analysis
41 41/37 National Academy of Science, 2018 HYPOTHESIS Perception of Correlation follows Weber s Law because the Visual Features used to discriminate Correlation follows Weber s Law. Regression (Logistic) Analysis of Visual Features vs. Judgment Mathematical Confirmation
42 42/37 National Academy of Science, 2018 VISUAL FEATURES
43 43/37 National Academy of Science, 2018 HYPOTHESIS Perception of Correlation follows Weber s Law because the Visual Features used to discriminate Correlation follows Weber s Law. Regression (Logistic) Analysis of Visual Features vs. Judgment
44 44/37 National Academy of Science, 2018 HYPOTHESIS Perception of Correlation follows Weber s Law because the Visual Features used to discriminate Correlation follows Weber s Law. Mathematical Confirmation Model for the Perception of Correlation (from our experiment): JJJJDD rr = kk rr II rr + bb rr Model for the Perception of the Visual Feature (from Psych): JJJJDD vvvv = kk vvvv II vvvv + bb vvvv
45 45/37 National Academy of Science, 2018 HYPOTHESIS Perception of Correlation follows Weber s Law because the Visual Features used to discriminate Correlation follows Weber s Law. Mathematical Confirmation If a Visual Feature (VF) is used to judge correlation, then the two equations should equate: JJJJDD rr = kk rr II rr + bb rr JJJJDD vvvv = kk vvvv II vvvv + bb vvvv
46 46/37 National Academy of Science, 2018 VISUALIZATION METAMERS: BEYOND CORRELATION
Visualization Research and the Human Mind
Visualization Research and the Human Mind Ronald A. Rensink Departments of Psychology and Computer Science University of British Columbia Vancouver, Canada IEEE VIS 2016, Baltimore, MD How can empirical
Visualization & Vision Science
Visualization & Vision Science Ronald A. Rensink Departments of Psychology and Computer Science University of British Columbia Vancouver, Canada IEEE VIS 2017, Phoenix, AZ Visualization and vision science
Fundamentals of Psychophysics
Fundamentals of Psychophysics John Greenwood Department of Experimental Psychology!! NEUR3045! Contact: john.greenwood@ucl.ac.uk 1 Visual neuroscience physiology stimulus How do we see the world? neuroimaging
Method of Limits Worksheet
1 Method of Limits Worksheet Name: Date: Trial # Upper Threshold Lower Threshold 1 2 3 4 5 6 7 8 9 10 Sum Mean Question 1: What is the upper threshold of Trial #1? Question 2: Compute the mean upper threshold.
TERRORIST WATCHER: AN INTERACTIVE WEB- BASED VISUAL ANALYTICAL TOOL OF TERRORIST S PERSONAL CHARACTERISTICS
TERRORIST WATCHER: AN INTERACTIVE WEB- BASED VISUAL ANALYTICAL TOOL OF TERRORIST S PERSONAL CHARACTERISTICS Samah Mansoour School of Computing and Information Systems, Grand Valley State University, Michigan,
IAT 355 Visual Analytics. Encoding Information: Design. Lyn Bartram
IAT 355 Visual Analytics Encoding Information: Design Lyn Bartram 4 stages of visualization design 2 Recall: Data Abstraction Tables Data item (row) with attributes (columns) : row=key, cells = values
Perception Lecture 1
Page 1 Perception Lecture 1 Sensation vs Perception Sensation is detection Perception is interpretation The distal and proximal stimulus Distal stimulus: the object out there in the world (distal=distant).
Sensation is the conscious experience associated with an environmental stimulus. It is the acquisition of raw information by the body s sense organs
Sensation is the conscious experience associated with an environmental stimulus. It is the acquisition of raw information by the body s sense organs Perception is the conscious experience of things and
Modeling Human Perception
Modeling Human Perception Could Stevens Power Law be an Emergent Feature? Matthew L. Bolton Systems and Information Engineering University of Virginia Charlottesville, United States of America Mlb4b@Virginia.edu
PSYC 441 Cognitive Psychology II
PSYC 441 Cognitive Psychology II Session 6 Psychophysics Lecturer: Dr. Benjamin Amponsah, Dept., of Psychology, UG, Legon Contact Information: bamponsah@ug.edu.gh College of Education School of Continuing
Name Psychophysical Methods Laboratory
Name Psychophysical Methods Laboratory 1. Classical Methods of Psychophysics These exercises make use of a HyperCard stack developed by Hiroshi Ono. Open the PS 325 folder and then the Precision and Accuracy
Schwartz and Krantz, Sensation and Perception
Test Bank Chapter 2 1. The Scoville scale measures: a. Any psychophysical measure of sensitivity *b. The amount of capsaicin in food c. The strength of auditory amplitude d. The number of caffeine molecules
Announcements. Perceptual Grouping. Quiz: Fourier Transform. What you should know for quiz. What you should know for quiz
Announcements Quiz on Tuesday, March 10. Material covered (Union not Intersection) All lectures before today (March 3). Forsyth and Ponce Readings: Chapters 1.1, 4, 5.1, 5.2, 5.3, 7,8, 9.1, 9.2, 9.3, 6.5.2,
Research methods in sensation and perception. (and the princess and the pea)
Research methods in sensation and perception (and the princess and the pea) Sensory Thresholds We can measure stuff in the world like pressure, sound, light, etc. We can't easily measure your psychological
Perceptual Studies. Perceptual Studies. Conclusions. Perceptual Studies. Strengths? Weakness? Follow-on Studies?
Perceptual Studies Jason Harrison, Ron Rensink, and Michiel van de Panne, Obscuring Length Changes During Animated Motion. ACM Transactions on Graphics, 23(3), Proceedings of SIGGRAPH 2004. Perceptual
IAT 355 Perception 1. Or What You See is Maybe Not What You Were Supposed to Get
IAT 355 Perception 1 Or What You See is Maybe Not What You Were Supposed to Get Why we need to understand perception The ability of viewers to interpret visual (graphical) encodings of information and
Dikran J. Martin. Psychology 110. Name: Date: Making Contact with the World around Us. Principal Features
Dikran J. Martin Psychology 110 Name: Date: Lecture Series: Chapter 3 Sensation and Perception: Pages: 31 Making Contact with the World around Us TEXT: Baron, Robert A. (2001). Psychology (Fifth Edition).
Slide 2.1. Perception and interpretation
Slide 2.1 Perception and interpretation Slide 2.2 Perception defined Perception is the process by which physical sensations such as sights, sounds, and smells are selected, organised, and interpreted.
Divide your paper sections
How to take: Divide your paper sections Now: Heading Notes Later: Study?s Summary Title of Notes Study?s Level 1,2 & 3 Summary 3-5 sentences Date Take Notes during presentation Underline key words Skip
Psychology Unit 3 Test
1 Choose the best answer. (2 pts each). Psychology Unit 3 Test 1. In bright light, the iris and the pupil to control the amount of light entering the eye. a. expands; constricts b. constricts; expands
Probability-Based Protein Identification for Post-Translational Modifications and Amino Acid Variants Using Peptide Mass Fingerprint Data
Probability-Based Protein Identification for Post-Translational Modifications and Amino Acid Variants Using Peptide Mass Fingerprint Data Tong WW, McComb ME, Perlman DH, Huang H, O Connor PB, Costello
Describe what is meant by a placebo Contrast the double-blind procedure with the single-blind procedure Review the structure for organizing a memo
Business Statistics The following was provided by Dr. Suzanne Delaney, and is a comprehensive review of Business Statistics. The workshop instructor will provide relevant examples during the Skills Assessment
UNLOCKING VALUE WITH DATA SCIENCE BAYES APPROACH: MAKING DATA WORK HARDER
UNLOCKING VALUE WITH DATA SCIENCE BAYES APPROACH: MAKING DATA WORK HARDER 2016 DELIVERING VALUE WITH DATA SCIENCE BAYES APPROACH - MAKING DATA WORK HARDER The Ipsos MORI Data Science team increasingly
Competing Frameworks in Perception
Competing Frameworks in Perception Lesson II: Perception module 08 Perception.08. 1 Views on perception Perception as a cascade of information processing stages From sensation to percept Template vs. feature
Competing Frameworks in Perception
Competing Frameworks in Perception Lesson II: Perception module 08 Perception.08. 1 Views on perception Perception as a cascade of information processing stages From sensation to percept Template vs. feature
Office of Human Resources. Forensic Scientist II CE0412
Office of Human Resources Forensic Scientist II CE0412 General Statement of Duties Performs full performance level forensic work including applying the physical sciences to the investigation of crimes,
Still important ideas
Readings: OpenStax - Chapters 1 13 & Appendix D & E (online) Plous Chapters 17 & 18 - Chapter 17: Social Influences - Chapter 18: Group Judgments and Decisions Still important ideas Contrast the measurement
Errol Davis Director of Research and Development Sound Linked Data Inc. Erik Arisholm Lead Engineer Sound Linked Data Inc.
An Advanced Pseudo-Random Data Generator that improves data representations and reduces errors in pattern recognition in a Numeric Knowledge Modeling System Errol Davis Director of Research and Development
Framework for Comparative Research on Relational Information Displays
Framework for Comparative Research on Relational Information Displays Sung Park and Richard Catrambone 2 School of Psychology & Graphics, Visualization, and Usability Center (GVU) Georgia Institute of
Shaw - PSYC& 100 Lilienfeld et al (2014) - Chapter 4 Sensation and Perception: How we sense and conceptualize the world
Name: 1 Shaw - PSYC& 100 Lilienfeld et al (2014) - Chapter 4 Sensation and Perception: How we sense and conceptualize the world 1 Distinguish between sensation and perception. Include as part of your answer
Readings: Textbook readings: OpenStax - Chapters 1 13 (emphasis on Chapter 12) Online readings: Appendix D, E & F
Readings: Textbook readings: OpenStax - Chapters 1 13 (emphasis on Chapter 12) Online readings: Appendix D, E & F Plous Chapters 17 & 18 Chapter 17: Social Influences Chapter 18: Group Judgments and Decisions
Introduction to Sensation
Introduction to Sensation Learning Targets 1. Contrast sensation & perception. 2. Distinguish between absolute and difference thresholds. ---- Explain Weber s Law Sensation vs. Perception Sensation: our
PSYC& Lilienfeld et al. - Chapter 4 Sensation and Perception: How We Sense and Conceptualize the World Study Guide
Many first time college students struggle adjusting to expectations of college-level courses. One reason for this is that college-level courses require students to learn new content and apply that content
Chapter 3 CORRELATION AND REGRESSION
CORRELATION AND REGRESSION TOPIC SLIDE Linear Regression Defined 2 Regression Equation 3 The Slope or b 4 The Y-Intercept or a 5 What Value of the Y-Variable Should be Predicted When r = 0? 7 The Regression
Sensation and Perception: How the World Enters the Mind
Sensation and Perception: How the World Enters the Mind Copyright Allyn & Bacon 2007 Sensation and Perception Sensation The awareness of properties of an object or event when a sensory receptor is stimulated
2012 Course: The Statistician Brain: the Bayesian Revolution in Cognitive Sciences
2012 Course: The Statistician Brain: the Bayesian Revolution in Cognitive Sciences Stanislas Dehaene Chair of Experimental Cognitive Psychology Lecture n 5 Bayesian Decision-Making Lecture material translated
June 16, The retina has two types of light-sensitive receptor cells (or photoreceptors) called rods and cones.
K K The retina has two types of light-sensitive receptor cells (or photoreceptors) called rods and cones. rods: 75 to 150 million cells which are very sensitive to all levels of light. cones: 6 to 7 million
Introduction. Chapter The Perceptual Process
Chapter 1 Introduction Most of us take for granted our ability to perceive the external world. However, this is no simple deed at all. Imagine being given a task of designing a machine that can perceive,
Psychology of Perception Psychology 4165, Spring 2003 Laboratory 1 Weight Discrimination
Psychology 4165, Laboratory 1 Weight Discrimination Weight Discrimination Performance Probability of "Heavier" Response 1.0 0.8 0.6 0.4 0.2 0.0 50.0 100.0 150.0 200.0 250.0 Weight of Test Stimulus (grams)
Lecture 12: Psychophysics and User Studies
ME 327: Design and Control of Haptic Systems Autumn 2018 Lecture 12: Psychophysics and User Studies Allison M. Okamura Stanford University Reminders The last ~20 minutes of today s lecture will be in 520-145
ANALYSIS AND DETECTION OF BRAIN TUMOUR USING IMAGE PROCESSING TECHNIQUES
ANALYSIS AND DETECTION OF BRAIN TUMOUR USING IMAGE PROCESSING TECHNIQUES P.V.Rohini 1, Dr.M.Pushparani 2 1 M.Phil Scholar, Department of Computer Science, Mother Teresa women s university, (India) 2 Professor
Sensory Thresholds and Signal Detection. Lecture 13
Sensory Thresholds and Signal Detection Lecture 13 1 Qualities of Sensation Boring (1953) Modality-Specific Vision: Hue, Saturation Audition: Pitch, Timbre Olfaction: Odor Gustation: Flavor Touch: Roughness,
Psychology of Perception Psychology 4165, Fall 2001 Laboratory 1 Weight Discrimination
Psychology 4165, Laboratory 1 Weight Discrimination Weight Discrimination Performance Probability of "Heavier" Response 1.0 0.8 0.6 0.4 0.2 0.0 50.0 100.0 150.0 200.0 250.0 Weight of Test Stimulus (grams)
CONTRIBUTION OF DIRECTIONAL ENERGY COMPONENTS OF LATE SOUND TO LISTENER ENVELOPMENT
CONTRIBUTION OF DIRECTIONAL ENERGY COMPONENTS OF LATE SOUND TO LISTENER ENVELOPMENT PACS:..Hy Furuya, Hiroshi ; Wakuda, Akiko ; Anai, Ken ; Fujimoto, Kazutoshi Faculty of Engineering, Kyushu Kyoritsu University
d). Draw the following neural circuits (using the notation taught in class) and then say what would happen if they were stimulated as specified.
1. The neuropsychology of perception. a). Describe the process in which a neural impulse travel down one axon, making sure to specify chemical substances involved and how that affects the charge within
Mr. Silimperi Council Rock High School South Chapter 5 Sensation Sensation II
Mr. Silimperi Council Rock High School South AP Psychology Name: Date: Chapter 5 Sensation Sensation II Psychophysics study of the relationship between physical characteristics of stimuli and our psychological
Sensory Cue Integration
Sensory Cue Integration Summary by Byoung-Hee Kim Computer Science and Engineering (CSE) http://bi.snu.ac.kr/ Presentation Guideline Quiz on the gist of the chapter (5 min) Presenters: prepare one main
1. What is the difference between positive and negative correlations?
1. What is the difference between positive and negative correlations? 2. Can correlations make predictions? 3. Can correlations prove causation? 4. What are illusory correlations? We can take data from
Supporting Information
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 Supporting Information Variances and biases of absolute distributions were larger in the 2-line
CS160: Sensori-motor Models. Prof Canny
CS160: Sensori-motor Models Prof Canny 1 Why Model Human Performance? To test understanding of behavior To predict impact of new technology we can build a simulator to evaluate user interface designs 2
Biological Psychology. Unit Two AD Mr. Cline Marshall High School Psychology
Biological Psychology Unit Two AD Mr. Cline Marshall High School Psychology Sensory and Perception Though each sense works a little differently to do this, psychologists have developed principles to describe
A Novel Software Solution to Diagnose the Hearing Disabilities In Human Beings
A Novel Software Solution to Diagnose the Hearing Disabilities In Human Beings Prithvi B S Dept of Computer Science & Engineering SVIT, Bangalore bsprithvi1992@gmail.com Sanjay H S Research Scholar, Jain
Risk Classification Modeling to Combat Opioid Abuse
Risk Classification Modeling to Combat Opioid Abuse Improve Data Sharing to Identify High-Risk Prescribers of Opioids Christopher Sterling Chief Statistician NCI, Inc. www.nciinc.com 11730 Plaza America
SENSES: VISION. Chapter 5: Sensation AP Psychology Fall 2014
SENSES: VISION Chapter 5: Sensation AP Psychology Fall 2014 Sensation versus Perception Top-Down Processing (Perception) Cerebral cortex/ Association Areas Expectations Experiences Memories Schemas Anticipation
PSY 402. Theories of Learning Chapter 8 Stimulus Control How Stimuli Guide Instrumental Action
PSY 402 Theories of Learning Chapter 8 Stimulus Control How Stimuli Guide Instrumental Action Categorization and Discrimination Animals respond to stimuli in ways that suggest they form categories. Pigeons
Application of ecological interface design to driver support systems
Application of ecological interface design to driver support systems J.D. Lee, J.D. Hoffman, H.A. Stoner, B.D. Seppelt, and M.D. Brown Department of Mechanical and Industrial Engineering, University of
Definition Slides. Sensation. Perception. Bottom-up processing. Selective attention. Top-down processing 11/3/2013
Definition Slides Sensation = the process by which our sensory receptors and nervous system receive and represent stimulus energies from our environment. Perception = the process of organizing and interpreting
= add definition here. Definition Slide
= add definition here Definition Slide Definition Slides Sensation = the process by which our sensory receptors and nervous system receive and represent stimulus energies from our environment. Perception
What is Data? Part 2: Patterns & Associations. INFO-1301, Quantitative Reasoning 1 University of Colorado Boulder
What is Data? Part 2: Patterns & Associations INFO-1301, Quantitative Reasoning 1 University of Colorado Boulder August 29, 2016 Prof. Michael Paul Prof. William Aspray Overview This lecture will look
fmri: What Does It Measure?
fmri: What Does It Measure? Psychology 355: Cognitive Psychology Instructor: John Miyamoto 04/02/2018: Lecture 02-1 Note: This Powerpoint presentation may contain macros that I wrote to help me create
Business Statistics Probability
Business Statistics The following was provided by Dr. Suzanne Delaney, and is a comprehensive review of Business Statistics. The workshop instructor will provide relevant examples during the Skills Assessment
Augmented Cognition: Allocation of Attention
Augmented Cognition: Allocation of Attention Misha Pavel 1, Guoping Wang, Kehai Li Oregon Health and Science University OGI School of Science and Engineering 20000 NW Walker Road Beaverton, OR 97006, USA
SMARTfit Multisensory Learning Develops the Brain and the Body. A 30 minute PE class on SMARTfit helps the brain to learn better
1 SMARTfit Multisensory Learning Develops the Brain and the Body A 30 minute PE class on SMARTfit helps the brain to learn better SMARTfit and BDNF Essential for Every Developing Child Early studies indicate
(Visual) Attention. October 3, PSY Visual Attention 1
(Visual) Attention Perception and awareness of a visual object seems to involve attending to the object. Do we have to attend to an object to perceive it? Some tasks seem to proceed with little or no attention
Computational Neuroscience. Instructor: Odelia Schwartz
Computational Neuroscience 2017 1 Instructor: Odelia Schwartz From the NIH web site: Committee report: Brain 2025: A Scientific Vision (from 2014) #1. Discovering diversity: Identify and provide experimental
Human Information Processing. CS160: User Interfaces John Canny
Human Information Processing CS160: User Interfaces John Canny Review Paper prototyping Key part of early design cycle Fast and cheap, allows more improvements early Formative user study Experimenters
HAPTIC EVALUATION OF MALAY FEMALES' TRADITIONAL CLOTHES IN Kansei PERSPECTIVE
Kansei Engineering International Vol.3 No.2 pp.23-30 (2002) ORIGINAL ARTICLES HAPTIC EVALUATION OF MALAY FEMALES' TRADITIONAL CLOTHES IN Kansei PERSPECTIVE Nazlina SHAARI*, Terauchi FUMIO**, Kubo MITSUNORI
Introduction. Visual Perception Aditi Majumder, UCI. Perception is taken for granted!
Introduction Visual Perception Perception is taken for granted! Slide 2 1 Perception is very complex Perceive Locate Identify/Recognize Different objects Their relationship with each other Qualitative
Key Ideas. Explain how science is different from other forms of human endeavor. Identify the steps that make up scientific methods.
Key Ideas Explain how science is different from other forms of human endeavor. Identify the steps that make up scientific methods. Analyze how scientific thought changes as new information is collected.
! Can hear whistle? ! Where are we on course map? ! What we did in lab last week. ! Psychoacoustics
2/14/18 Can hear whistle? Lecture 5 Psychoacoustics Based on slides 2009--2018 DeHon, Koditschek Additional Material 2014 Farmer 1 2 There are sounds we cannot hear Depends on frequency Where are we on
SCIENCE GRADE 8 Navrachana International School, Vadodara ( ) GRADE 8 (SCIENCE) ASSESSMENT OBJECTIVE (based on Assessment Criteria)
ATL / 12 TOPIC- Plant Nutrition AOI- Environments CONCEPTS 1. Structure of leaves and their adaptations for photosynthesis. 2. How plants make and use glucose they produce in photosynthesis. 3. Factors
Mammogram Analysis: Tumor Classification
Mammogram Analysis: Tumor Classification Term Project Report Geethapriya Raghavan geeragh@mail.utexas.edu EE 381K - Multidimensional Digital Signal Processing Spring 2005 Abstract Breast cancer is the
Myers PSYCHOLOGY. (6th Ed) Chapter 5. Sensation
Myers PSYCHOLOGY (6th Ed) Chapter 5 Sensation Sensation Sensation a process by which our sensory receptors and nervous system receive and represent stimulus energy Perception a process of organizing and
OBSERVATIONAL MEDICAL OUTCOMES PARTNERSHIP
OBSERVATIONAL Patient-centered observational analytics: New directions toward studying the effects of medical products Patrick Ryan on behalf of OMOP Research Team May 22, 2012 Observational Medical Outcomes
A Process Tracing Approach to the Investigation of Situated Cognition
PROCEEDINGS of the HUMAN FACTORS AND ERGONOMICS SOCIETY 48th ANNUAL MEETING 2004 658 A Process Tracing Approach to the Investigation of Situated Cognition Lawrence G. Shattuck United States Military Academy
Sensation, Part 1 Gleitman et al. (2011), Chapter 4
Sensation, Part 1 Gleitman et al. (2011), Chapter 4 Mike D Zmura Department of Cognitive Sciences, UCI Psych 9A / Psy Beh 11A February 11, 2014 T. M. D'Zmura 1 Origins of Knowledge Empiricism knowledge
Comment on W.S. Cleveland, A Model for Studying Display Methods of Statistical Graphics. Leland Wilkinson SYSTAT, Inc. and Northwestern University
Comment on W.S. Cleveland, A Model for Studying Display Methods of Statistical Graphics Leland Wilkinson SYSTAT, Inc. and Northwestern University Revised version published in Journal of Computational and
Psychology Chapter 4. Sensation and Perception. Most amazing introduction ever!! Turn to page 77 and prepare to be amazed!
Psychology Chapter 4 Sensation and Perception Most amazing introduction ever!! Turn to page 77 and prepare to be amazed! Chapter 4 Section 1 EQ: Distinguish between sensation and perception, and explain
Congruency Effects with Dynamic Auditory Stimuli: Design Implications
Congruency Effects with Dynamic Auditory Stimuli: Design Implications Bruce N. Walker and Addie Ehrenstein Psychology Department Rice University 6100 Main Street Houston, TX 77005-1892 USA +1 (713) 527-8101
1 Version SP.A Investigate patterns of association in bivariate data
Claim 1: Concepts and Procedures Students can explain and apply mathematical concepts and carry out mathematical procedures with precision and fluency. Content Domain: Statistics and Probability Target
Choose an approach for your research problem
Choose an approach for your research problem This course is about doing empirical research with experiments, so your general approach to research has already been chosen by your professor. It s important
Lecture 6. Human Factors in Engineering Design
GE105 Introduction to Engineering Design College of Engineering King Saud University Lecture 6. Human Factors in Engineering Design SPRING 2016 What is Human Factors in Design? Considering information
Readings: Textbook readings: OpenStax - Chapters 1 11 Online readings: Appendix D, E & F Plous Chapters 10, 11, 12 and 14
Readings: Textbook readings: OpenStax - Chapters 1 11 Online readings: Appendix D, E & F Plous Chapters 10, 11, 12 and 14 Still important ideas Contrast the measurement of observable actions (and/or characteristics)
VISUAL MEMORY. Visual Perception
VISUAL MEMORY Visual Perception Memory is unqiue Other aspects of visual perception Bombard us with stimuli at every instance Memory Helps us to make sense from chain of such instances Slide 2 Two Theories
Introduction to Sensation and Perception
PSYCHOLOGY (8th Edition, in Modules) David Myers PowerPoint Slides Worth Publishers, 2007 1 Introduction to Sensation and Perception Module 12 2 Sensation Sensing the World: Some Basic Principles Threshold
1 Introduction. 1 Early Philosophy of Perception. 1 Early Philosophy of Perception (cont d)
Introduction Sensation and perception The processes by which physical energy impinging on the senses is converted into electrochemical energy by the senses, transmitted to the brain for adaptive interaction
Three methods for measuring perception. Magnitude estimation. Steven s power law. P = k S n
Three methods for measuring perception 1. Magnitude estimation 2. Matching 3. Detection/discrimination Magnitude estimation Have subject rate (e.g., 1-10) some aspect of a stimulus (e.g., how bright it
perception and visualization WOLFGANG AiGNER perception and visualization 1
Wolfgang Aigner aigner@ifs.tuwien.ac.at http://ieg.ifs.tuwien.ac.at/~aigner/ Version 1.1 26.10.2010 perception and visualization WOLFGANG AiGNER perception and visualization 1 [http://xkcd.com/688/] WOLFGANG
John E. Laird University of Michigan 1101 Beal Ave. Ann Arbor, MI
From: AAAI Technical Report SS-01-02. Compilation copyright 2001, AAAI (www.aaai.org). All rights reserved. Creating Human-like Synthetic Characters with Multiple Skill Levels: A Case Study using the Soar
Experimental Psychology PSY 433. Appendix A Experimental Psychology: A Historical Sketch
Experimental Psychology PSY 433 Appendix A Experimental Psychology: A Historical Sketch Origins in Philosophy Mind-body problem are the mind and body the same or different? If they are different substances,
SCATTER PLOTS AND TREND LINES
1 SCATTER PLOTS AND TREND LINES LEARNING MAP INFORMATION STANDARDS 8.SP.1 Construct and interpret scatter s for measurement to investigate patterns of between two quantities. Describe patterns such as
MULTIPLE LINEAR REGRESSION 24.1 INTRODUCTION AND OBJECTIVES OBJECTIVES
24 MULTIPLE LINEAR REGRESSION 24.1 INTRODUCTION AND OBJECTIVES In the previous chapter, simple linear regression was used when you have one independent variable and one dependent variable. This chapter
Understandable Statistics
Understandable Statistics correlated to the Advanced Placement Program Course Description for Statistics Prepared for Alabama CC2 6/2003 2003 Understandable Statistics 2003 correlated to the Advanced Placement
Results & Statistics: Description and Correlation. I. Scales of Measurement A Review
Results & Statistics: Description and Correlation The description and presentation of results involves a number of topics. These include scales of measurement, descriptive statistics used to summarize
Fleishman s Taxonomy of Human Abilities
Fleishman s Taxonomy of Human Abilities Ability Taxonomy: Introduction At I/O Solutions, we utilize research to build selection tools that are effective and valid. Part of this effort is to use an ability
Supplemental Information: Task-specific transfer of perceptual learning across sensory modalities
Supplemental Information: Task-specific transfer of perceptual learning across sensory modalities David P. McGovern, Andrew T. Astle, Sarah L. Clavin and Fiona N. Newell Figure S1: Group-averaged learning
Birds' Judgments of Number and Quantity
Entire Set of Printable Figures For Birds' Judgments of Number and Quantity Emmerton Figure 1. Figure 2. Examples of novel transfer stimuli in an experiment reported in Emmerton & Delius (1993). Paired
Current State of Visualization of EHR data: What's needed? What's next? (Session No: S50)
Current State of Visualization of EHR data: What's needed? What's next? (Session No: S50) Panel: Danny Wu, University of Michigan Vivian West, Duke University Dawn Dowding, Columbia University Hadi Kharrazi,
Information-theoretic stimulus design for neurophysiology & psychophysics
Information-theoretic stimulus design for neurophysiology & psychophysics Christopher DiMattina, PhD Assistant Professor of Psychology Florida Gulf Coast University 2 Optimal experimental design Part 1
A Neural Model of Context Dependent Decision Making in the Prefrontal Cortex
A Neural Model of Context Dependent Decision Making in the Prefrontal Cortex Sugandha Sharma (s72sharm@uwaterloo.ca) Brent J. Komer (bjkomer@uwaterloo.ca) Terrence C. Stewart (tcstewar@uwaterloo.ca) Chris