This document provides an overview of human psychology and cognition, including:
- The human senses of vision, hearing, touch, and movement and how we process sensory information.
- Memory systems including sensory memory, short-term memory, and long-term memory.
- Thinking processes like reasoning, problem solving, and decision making.
- How emotion influences human capabilities and performance.
- Individual differences in abilities and how contexts like stress or fatigue can impact cognition.
- Applications of psychological principles to the design of interactive systems.
Chapter 1: The human
from
Dix, Finlay, Abowd and Beale (2004).
Human-Computer Interaction, third edition.
Prentice Hall. ISBN 0-13-239864-8.
http://www.hcibook.com/e3/
Cognitive Level of Analysis: Cognitive ProcessesMackenzie
These are my notes for the 3.1 section of my IB HL Psychology textbook. It focuses on the Cognitive Level of Analysis and cognitive processes, particularly memory. Beware: it's quite long, but I doubt I'll post any presentations longer than this one in the future.
Chapter 1: The human
from
Dix, Finlay, Abowd and Beale (2004).
Human-Computer Interaction, third edition.
Prentice Hall. ISBN 0-13-239864-8.
http://www.hcibook.com/e3/
Cognitive Level of Analysis: Cognitive ProcessesMackenzie
These are my notes for the 3.1 section of my IB HL Psychology textbook. It focuses on the Cognitive Level of Analysis and cognitive processes, particularly memory. Beware: it's quite long, but I doubt I'll post any presentations longer than this one in the future.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
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1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
2. the human
• Information i/o …
– visual, auditory, haptic, movement
• Information stored in memory
– sensory, short-term, long-term
• Information processed and applied
– reasoning, problem solving, skill, error
• Emotion influences human capabilities
• Each person is different
3. Vision
Two stages in vision
• physical reception of stimulus
• processing and interpretation of
stimulus
4. The Eye - physical reception
• mechanism for receiving light and
transforming it into electrical energy
• light reflects from objects
• images are focused upside-down on
retina
• retina contains rods for low light vision
and cones for colour vision
• ganglion cells (brain!) detect pattern
and movement
5. Interpreting the signal
• Size and depth
– visual angle indicates how much of view
object occupies
(relates to size and distance from eye)
– visual acuity is ability to perceive detail
(limited)
– familiar objects perceived as constant size
(in spite of changes in visual angle when far away)
– cues like overlapping help perception of
size and depth
6. Interpreting the signal (cont)
• Brightness
– subjective reaction to levels of light
– affected by luminance of object
– measured by just noticeable difference
– visual acuity increases with luminance as does
flicker
• Colour
– made up of hue, intensity, saturation
– cones sensitive to colour wavelengths
– blue acuity is lowest
– 8% males and 1% females colour blind
7. Interpreting the signal (cont)
• The visual system compensates for:
– movement
– changes in luminance.
• Context is used to resolve ambiguity
• Optical illusions sometimes occur due to
over compensation
9. Reading
• Several stages:
– visual pattern perceived
– decoded using internal representation of language
– interpreted using knowledge of syntax, semantics,
pragmatics
• Reading involves saccades and fixations
• Perception occurs during fixations
• Word shape is important to recognition
• Negative contrast improves reading from
computer screen
10. Hearing
• Provides information about environment:
distances, directions, objects etc.
• Physical apparatus:
– outer ear – protects inner and amplifies sound
– middle ear – transmits sound waves as
vibrations to inner ear
– inner ear – chemical transmitters are released
and cause impulses in auditory nerve
• Sound
– pitch – sound frequency
– loudness – amplitude
– timbre – type or quality
11. Hearing (cont)
• Humans can hear frequencies from 20Hz to
15kHz
– less accurate distinguishing high frequencies than
low.
• Auditory system filters sounds
– can attend to sounds over background noise.
– for example, the cocktail party phenomenon.
12. Touch
• Provides important feedback about environment.
• May be key sense for someone who is visually impaired.
• Stimulus received via receptors in the skin:
– thermoreceptors – heat and cold
– nociceptors – pain
– mechanoreceptors – pressure
(some instant, some continuous)
• Some areas more sensitive than others e.g. fingers.
• Kinethesis - awareness of body position
– affects comfort and performance.
13. Movement
• Time taken to respond to stimulus:
reaction time + movement time
• Movement time dependent on age, fitness etc.
• Reaction time - dependent on stimulus type:
– visual ~ 200ms
– auditory ~ 150 ms
– pain ~ 700ms
• Increasing reaction time decreases accuracy in
the unskilled operator but not in the skilled
operator.
14. Movement (cont)
• Fitts' Law describes the time taken to hit a
screen target:
Mt = a + b log2(D/S + 1)
where: a and b are empirically determined constants
Mt is movement time
D is Distance
S is Size of target
targets as large as possible
distances as small as possible
15. Memory
There are three types of memory function:
Sensory memories
Short-term memory or working memory
Long-term memory
Selection of stimuli governed by level of arousal.
19. Long-term memory (LTM)
• Repository for all our knowledge
– slow access ~ 1/10 second
– slow decay, if any
– huge or unlimited capacity
• Two types
– episodic – serial memory of events
– semantic – structured memory of facts,concepts, skills
semantic LTM derived from episodic LTM
20. Long-term memory (cont.)
• Semantic memory structure
– provides access to information
– represents relationships between bits of information
– supports inference
• Model: semantic network
– inheritance – child nodes inherit properties of parent
nodes
– relationships between bits of information explicit
– supports inference through inheritance
22. Models of LTM - Frames
• Information organized in data structures
• Slots in structure instantiated with values for instance
of data
• Type–subtype relationships
DOG
Fixed
legs: 4
Default
diet: carniverous
sound: bark
Variable
size:
colour
COLLIE
Fixed
breed of: DOG
type: sheepdog
Default
size: 65 cm
Variable
colour
23. Models of LTM - Scripts
Model of stereotypical information required to interpret situation
Script has elements that can be instantiated with values for context
Script for a visit to the vet
Entry conditions: dog ill
vet open
owner has money
Result: dog better
owner poorer
vet richer
Props: examination table
medicine
instruments
Roles: vet examines
diagnoses
treats
owner brings dog in
pays
takes dog out
Scenes: arriving at reception
waiting in room
examination
paying
Tracks: dog needs medicine
dog needs operation
24. Models of LTM - Production rules
Representation of procedural knowledge.
Condition/action rules
if condition is matched
then use rule to determine action.
IF dog is wagging tail
THEN pat dog
IF dog is growling
THEN run away
25. LTM - Storage of information
• rehearsal
– information moves from STM to LTM
• total time hypothesis
– amount retained proportional to rehearsal time
• distribution of practice effect
– optimized by spreading learning over time
• structure, meaning and familiarity
– information easier to remember
26. LTM - Forgetting
decay
– information is lost gradually but very slowly
interference
– new information replaces old: retroactive
interference
– old may interfere with new: proactive inhibition
so may not forget at all memory is selective …
… affected by emotion – can subconsciously `choose' to
forget
27. LTM - retrieval
recall
– information reproduced from memory can be
assisted by cues, e.g. categories, imagery
recognition
– information gives knowledge that it has been seen
before
– less complex than recall - information is cue
29. Deductive Reasoning
• Deduction:
– derive logically necessary conclusion from given
premises.
e.g. If it is Friday then she will go to work
It is Friday
Therefore she will go to work.
• Logical conclusion not necessarily true:
e.g. If it is raining then the ground is dry
It is raining
Therefore the ground is dry
30. Deduction (cont.)
• When truth and logical validity clash …
e.g. Some people are babies
Some babies cry
Inference - Some people cry
Correct?
• People bring world knowledge to bear
31. Inductive Reasoning
• Induction:
– generalize from cases seen to cases unseen
e.g. all elephants we have seen have trunks
therefore all elephants have trunks.
• Unreliable:
– can only prove false not true
… but useful!
• Humans not good at using negative evidence
e.g. Wason's cards.
32. Wason's cards
Is this true?
How many cards do you need to turn over to find out?
…. and which cards?
If a card has a vowel on one side it has an even number on the other
7 E 4 K
33. Abductive reasoning
• reasoning from event to cause
e.g. Sam drives fast when drunk.
If I see Sam driving fast, assume drunk.
• Unreliable:
– can lead to false explanations
34. Problem solving
• Process of finding solution to unfamiliar task
using knowledge.
• Several theories.
• Gestalt
– problem solving both productive and reproductive
– productive draws on insight and restructuring of problem
– attractive but not enough evidence to explain `insight'
etc.
– move away from behaviourism and led towards
information processing theories
35. Problem solving (cont.)
Problem space theory
– problem space comprises problem states
– problem solving involves generating states using legal
operators
– heuristics may be employed to select operators
e.g. means-ends analysis
– operates within human information processing system
e.g. STM limits etc.
– largely applied to problem solving in well-defined areas
e.g. puzzles rather than knowledge intensive areas
36. Problem solving (cont.)
• Analogy
– analogical mapping:
• novel problems in new domain?
• use knowledge of similar problem from similar domain
– analogical mapping difficult if domains are semantically
different
• Skill acquisition
– skilled activity characterized by chunking
• lot of information is chunked to optimize STM
– conceptual rather than superficial grouping of problems
– information is structured more effectively
37. Errors and mental models
Types of error
• slips
– right intention, but failed to do it right
– causes: poor physical skill,inattention etc.
– change to aspect of skilled behaviour can cause slip
• mistakes
– wrong intention
– cause: incorrect understanding
humans create mental models to explain behaviour.
if wrong (different from actual system) errors can occur
38. Emotion
• Various theories of how emotion works
– James-Lange: emotion is our interpretation of a
physiological response to a stimuli
– Cannon: emotion is a psychological response to a
stimuli
– Schacter-Singer: emotion is the result of our
evaluation of our physiological responses, in the
light of the whole situation we are in
• Emotion clearly involves both cognitive and
physical responses to stimuli
39. Emotion (cont.)
• The biological response to physical stimuli is
called affect
• Affect influences how we respond to situations
– positive creative problem solving
– negative narrow thinking
“Negative affect can make it harder to do
even easy tasks; positive affect can make
it easier to do difficult tasks”
(Donald Norman)
40. Emotion (cont.)
• Implications for interface design
– stress will increase the difficulty of problem
solving
– relaxed users will be more forgiving of
shortcomings in design
– aesthetically pleasing and rewarding
interfaces will increase positive affect
41. Individual differences
• long term
– sex, physical and intellectual abilities
• short term
– effect of stress or fatigue
• changing
– age
Ask yourself:
will design decision exclude section of user
population?
42. Psychology and the Design of
Interactive System
• Some direct applications
– e.g. blue acuity is poor
blue should not be used for important detail
• However, correct application generally requires
understanding of context in psychology, and an
understanding of particular experimental conditions
• A lot of knowledge has been distilled in
– guidelines (chap 7)
– cognitive models (chap 12)
– experimental and analytic evaluation techniques (chap 9)