PSYCHOLOGY-Thinking and Problem SolvingBlixs Phire
Thinking
-is type of behavior that uses as “inner representations” of objects and events.-the symbolic reference deals with remembered,absent or imagined things and events,including those and elaborates on what is present in perception and movement
Thinking Process Involves:
Problem Solving
Problem Solving*whenever goal-oriented activity is blocked,or whenever a need remained unfulfilled,or perplexity unresolved,there is a problem.
* Solving a problems usually involves discovering a correct response to a new situation*It involves the appropriate combination of concepts ,ideas and skills.
A presentation regarding the Human-Computer Interaction (2015): Affective Factors.
For details, visit the HCI discipline Website available at http://profs.info.uaic.ro/~busaco/teach/courses/hci/
Talk given at the International Conference on Cognitive Modelling, University of Groningen on 10 April 2015.#
CC0 - Public Domain
To the extent possible under law, Caspar Addyman has waived all copyright and related or neighboring rights to Open science in cognitive modeling. This work is published from: United Kingdom.
PSYCHOLOGY-Thinking and Problem SolvingBlixs Phire
Thinking
-is type of behavior that uses as “inner representations” of objects and events.-the symbolic reference deals with remembered,absent or imagined things and events,including those and elaborates on what is present in perception and movement
Thinking Process Involves:
Problem Solving
Problem Solving*whenever goal-oriented activity is blocked,or whenever a need remained unfulfilled,or perplexity unresolved,there is a problem.
* Solving a problems usually involves discovering a correct response to a new situation*It involves the appropriate combination of concepts ,ideas and skills.
A presentation regarding the Human-Computer Interaction (2015): Affective Factors.
For details, visit the HCI discipline Website available at http://profs.info.uaic.ro/~busaco/teach/courses/hci/
Talk given at the International Conference on Cognitive Modelling, University of Groningen on 10 April 2015.#
CC0 - Public Domain
To the extent possible under law, Caspar Addyman has waived all copyright and related or neighboring rights to Open science in cognitive modeling. This work is published from: United Kingdom.
A review of cognitive modeling and intelligent tutors. Presentation based on three papers, summarized below.
The base paper reports on an experiment of intelligent tutoring in three urban high schools in Pittsburgh. An intelligent tutor has been made a part of 9th grade algebra, accompanying a new algebra curriculum focused on mathematical analysis of real world situations and the use of computations tools. The 470 students in experimental classes outperformed students in comparison classes by 15% on standardized tests and 100% on tests targeting the PUMP objectives. The first auxiliary paper by Anderson describes the cognitive basis for intelligent tutors, from theory to model-tracing methodology, to issues that arise in implementation. The second auxiliary paper by VanLehn describes the lessons learned in developing and testing a cognitive tutor for physics at the U.S. Naval Academy. In particular, this system was designed to run as part of a course with minimal invasion of curricular design. Interestingly, the intelligent tutors for both algebra and physics, based on different models and designed for different educational contexts, had almost identical results.
It was amazing to see the long history of work on intelligent tutors, the scientific progress and implementation in schools across the country. The cognitive basis for such models is fascinating, tracing students' cognitive states in real time and modeling their knowledge as they learn new material. Yet, interaction with the tutor is simple: the tutor silently observes the students strategy, until the student asks for help or makes a mistake, and provides immediate feedback. This helps increase the quality and speed of learning as well as positively reinforce the joy (rather than the struggle) involved, keeping students motivated and moving in the right direction as they develop their problem-solving skills. However, its clear that there is a lot of work still remaining. Despite having a long history, the number of researchers in this area remains relatively small and the challenges ahead of them are large (including technical and political/social challenges).
International Conference on Cognitive Modeling 2010 Brahms tutorialMaarten Sierhuis
This presentation is the course work for the Brahms tutorial given at the 2010 International Conference on Cognitive Modeling. Brahms is a Multi-Agent Modeling and Simulation Environment for Human Behavior and Work Practice.
Modeling and Adapting to Cognitive LoadLucas Rizoli
A summary of three papers on assessing users' cognitive load and adapting interfaces to it, used as a starting point for class discussion.
Presented on Nov. 20, 2007 for CPSC 532B (http://www.cs.ubc.ca/~conati/532b-2007/532-description.html)
This slideshow was created with images from the web. I claim no copyright or ownership of any images. If a copyright owner of any image objects to the use in this slideshow, contact me to remove it. This is for a course in Introductory Psychology using Wayne Weiten's "Psychology: Themes and Variations" 8th ed. Published by Cengage. Images from the text are copyrighted by Cengage.
Presentation for the Cognitive Control course (DGCN25) of the Research Master Cognitive Neuroscience at Radboud University on the topic of Cognitive Modeling
Effects Of Moods And Emotions | Myth Of Rationality | Emotional Labor | Sourc...FaHaD .H. NooR
Emotional Dissonance - Felt emotions - Displayed Emotions
Surface acting - Deep Level Acting
Work event trigger positive and negative emotional reactions.employees respond to them with greater or lesser intensity according to their personalities and moods. Emotions influence performance and satisfaction variables.
Emotional episode-series of emotional experience
Current emotions influence job satisfaction
Moods and emotions fluctuate sodoes their effect on performance.
Emotion-driven behaviors are short in duration and of high variability.
Emotions typically have negative influence on job performance
Emotions are critical factor in employee behavior.
The “myth of rationality”
Emotions of any kind are disruptive to organizations.
Original OB focus was solely on the effects of strong negative emotions that interfered with individual and organizational efficiency.
Myth of rationality: emotions were the antithesis of rationality and should not be seen in the workplace
How to Get CNIC Information System with Paksim Ga.pptxdanishmna97
Pakdata Cf is a groundbreaking system designed to streamline and facilitate access to CNIC information. This innovative platform leverages advanced technology to provide users with efficient and secure access to their CNIC details.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Unlocking Productivity: Leveraging the Potential of Copilot in Microsoft 365, a presentation by Christoforos Vlachos, Senior Solutions Manager – Modern Workplace, Uni Systems
zkStudyClub - Reef: Fast Succinct Non-Interactive Zero-Knowledge Regex ProofsAlex Pruden
This paper presents Reef, a system for generating publicly verifiable succinct non-interactive zero-knowledge proofs that a committed document matches or does not match a regular expression. We describe applications such as proving the strength of passwords, the provenance of email despite redactions, the validity of oblivious DNS queries, and the existence of mutations in DNA. Reef supports the Perl Compatible Regular Expression syntax, including wildcards, alternation, ranges, capture groups, Kleene star, negations, and lookarounds. Reef introduces a new type of automata, Skipping Alternating Finite Automata (SAFA), that skips irrelevant parts of a document when producing proofs without undermining soundness, and instantiates SAFA with a lookup argument. Our experimental evaluation confirms that Reef can generate proofs for documents with 32M characters; the proofs are small and cheap to verify (under a second).
Paper: https://eprint.iacr.org/2023/1886
UiPath Test Automation using UiPath Test Suite series, part 6DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Full-RAG: A modern architecture for hyper-personalizationZilliz
Mike Del Balso, CEO & Co-Founder at Tecton, presents "Full RAG," a novel approach to AI recommendation systems, aiming to push beyond the limitations of traditional models through a deep integration of contextual insights and real-time data, leveraging the Retrieval-Augmented Generation architecture. This talk will outline Full RAG's potential to significantly enhance personalization, address engineering challenges such as data management and model training, and introduce data enrichment with reranking as a key solution. Attendees will gain crucial insights into the importance of hyperpersonalization in AI, the capabilities of Full RAG for advanced personalization, and strategies for managing complex data integrations for deploying cutting-edge AI solutions.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Communications Mining Series - Zero to Hero - Session 1DianaGray10
This session provides introduction to UiPath Communication Mining, importance and platform overview. You will acquire a good understand of the phases in Communication Mining as we go over the platform with you. Topics covered:
• Communication Mining Overview
• Why is it important?
• How can it help today’s business and the benefits
• Phases in Communication Mining
• Demo on Platform overview
• Q/A
20 Comprehensive Checklist of Designing and Developing a WebsitePixlogix Infotech
Dive into the world of Website Designing and Developing with Pixlogix! Looking to create a stunning online presence? Look no further! Our comprehensive checklist covers everything you need to know to craft a website that stands out. From user-friendly design to seamless functionality, we've got you covered. Don't miss out on this invaluable resource! Check out our checklist now at Pixlogix and start your journey towards a captivating online presence today.
UiPath Test Automation using UiPath Test Suite series, part 5DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 5. In this session, we will cover CI/CD with devops.
Topics covered:
CI/CD with in UiPath
End-to-end overview of CI/CD pipeline with Azure devops
Speaker:
Lyndsey Byblow, Test Suite Sales Engineer @ UiPath, Inc.
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.
Pushing the limits of ePRTC: 100ns holdover for 100 daysAdtran
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
Maruthi Prithivirajan, Head of ASEAN & IN Solution Architecture, Neo4j
Get an inside look at the latest Neo4j innovations that enable relationship-driven intelligence at scale. Learn more about the newest cloud integrations and product enhancements that make Neo4j an essential choice for developers building apps with interconnected data and generative AI.
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024Neo4j
Neha Bajwa, Vice President of Product Marketing, Neo4j
Join us as we explore breakthrough innovations enabled by interconnected data and AI. Discover firsthand how organizations use relationships in data to uncover contextual insights and solve our most pressing challenges – from optimizing supply chains, detecting fraud, and improving customer experiences to accelerating drug discoveries.
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024
Depth of Feelings: Modeling Emotions in User Models and Agent Architectures
1. Depth of Feelings: Alternatives for Modeling Affect in User Models & Cognitive Architectures Eva Hudlicka Psychometrix Associates Blacksburg, US [email_address] psychometrixassociates.com TSD 2006 Masarykova Universita, Brno, Czech Republic September 15, 2006
2. “ Diseases of the Mind”* Are emotions….. *Immanuel Kant
8. Emotions in HCI: State-of-the-art KISMET - Cynthia Breazeal, MIT Media Lab
9. Emotions in HCI: State-of-the-art Agent Max - Becker-Asano et al.
10. Requirements for Affective HCI Affective User Model / Cognitive-Affective Architecture Emotion Sensing & Recognition “ Emotion” Expression OR? GRETA, Fiorella de Rosis, U. Bari
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16. Simple Fear “Signature”: Large, Approaching Object Increased heart-rate; Attacked? Crushed? Flee? Freeze? Feeling of fear Cognitive Subjective
17. A Taxonomy of Affective Factors Traits Affective Factors NOT ALL TRAITS are affective! Attitudes, Preferences… Affective States Emotions Moods Negative Positive Traits States “ Big 5” … Basic Anger Joy Fear … Complex Shame Guilt Pride …
18. Core Processes of Emotions Effects of Emotions (on cognition & behavior) Generation of Emotions (via cognitive appraisal) Cognitive-Affective Architecture Stimuli Situations Expectations Goals Cognitive Appraisal Emotions
23. “ Thank God! Those blasted crickets have finally stopped!”
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29. A Taxonomy of Affective Factors States Affective States Emotions Moods Basic Complex Negative Positive Anger Joy Fear Shame Guilt Pride Traits Traits Affective Factors “ Big 5” …
35. Valenced Reactions Event-based emotions Attribution emotions Attraction emotions Event Related Appraised wrt goals “ Does this promote world peace?” Acts-by-Agents Related Appraised wrt standards “ Was it appropriate for John to rob the bank?” Object Related Appraised wrt attitudes “ Is this appealing to me?”
41. STIMULI Novelty Valence Goal relevance Outcome probability Urgency Goal congruence Agency Coping potential Norms high high v. high low other low low high FEAR
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43. Results of the Appraisal Process: Emotion ‘Specification’ fear .90 probability, importance of affected goals 2 minutes (exp. decay) { aggressive dog | owner} “ aggressive dog approaching” negative { dog | negligent owner | self } low { safety of self | safety of dog | delay } Other appraisal variables….: Type: Descriptive detail: Intensity: Variables affecting intensity: Cause: Direction: Coping potential: Duration: Valence: Goals affected:
51. Emotions As Parameters (MAMID, Hudlicka) Traits Extraversion Stability Conscientiousness Aggressiveness STATES / TRAITS Processing Structural Module Parameters Construct parameters Architecture topology Long-term memory speed, capacity Cue selection & delay …. Data flow among modules Content & structure Affective States Anxiety Anger Sadness Joy ARCHITECTURE PARAMETERS COGNITIVE ARCHITECTURE Attention Action Selection Situation Assessment Goal Manager Expectation Generator Affect Appraiser
52. Modeling Threat Bias Processing Parameters Construct parms. - Cue selection - Interpretive biases ... Process Threat cues Process Threatening interpretations Traits Low Stability TRAITS / STATES COGNITIVE ARCHITECTURE PARAMETERS COGNITIVE ARCHITECTURE Attention Action Selection Situation Assessment Goal Manager Expectation Generator Affect Appraiser Emotions Higher Anxiety / Fear Predisposes towards Preferential processing of Threatening stimuli Threat constructs Rated more highly
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54. Distinct Individual Profiles & Behavior “ Normal” “Anxious” Attention Perception / Situation Assessment Expectation Generation Affect Appraisal Goal Selection Action Selection Hostile large crowd Hostile large crowd Objective near Unit capability high Limited # of high-threat & self cues Movement blocked Danger to unit low Danger to unit and self high Perceptual threat & self bias Anxiety: Normal Anxiety: High Rapid-onset of high anxiety Danger from crowd unlikely Danger to unit and self high Career success threatened Threat and self oriented expectations Non-lethal crowd control Reduce anxiety Defend unit Threat and self focus goals Stop Stop; Lethal crowd control Non-lethal crowd control Report info Request help Request info Anxiety regulating behavior
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62. MAMID Cognitive-Affective Architecture Action Selection Cues: State of the world ( “growling dog”, “approaching”) Situations: Perceived state ( “aggressive dog” ) Expectations: Expected state (“dog will attack”, “bite wound”) Goals: Desired state (“protect self”) Actions: to accomplish goals (“climb tree”) Affective state & emotions: Negative valence High anxiety Low happiness Cues Actions Attention Situation Assessment Expectation Generator Affect Appraiser Goal Manager
72. Depth of Feelings: Alternatives for Modeling Affect in User Models & Cognitive Architectures Eva Hudlicka Psychometrix Associates Blacksburg, US [email_address] psychometrixassociates.com TSD 2006 Masarykova Universita, Brno, Czech Republic September 15, 2006