iMotions White Paper: Validation of Emotion Evaluation System embedded in Att...iMotionsEyeTracking
Abstract: This paper describes how Attention Tool® can be used to measure human emotions and which statistical outputs are provided in the tool for each tested visual stimulus. The method in Attention Tool for measuring the emotional strength, also known as physiological arousal, is based on pupil size variation, eye blink pattern and gaze behavior. Furthermore, the method is evaluated together with galvanic skin response (GSR) recordings that is a well-known and widely used method for measuring arousal. The comparison of these two methods shows that Attention Tool is just as good an evaluator of physiological arousal as the currently used GSR.
The research discussed in this paper is part of a pilot study in the use of wearable devices incorporating electroencephalogram (EEG) and heartrate sensors to sense for the emotional responses closely correlated to frustration when performing certain tasks. For this study the methodology used a combination of puzzle, arcade style game and a meditation apps to emulate a task based environment and detect frustration and satisfaction emotions. Preliminary results indicate that degree of task completion has an effect on emotions and can be detected by EEG and heartrate changes.
iMotions White Paper: Validation of Emotion Evaluation System embedded in Att...iMotionsEyeTracking
Abstract: This paper describes how Attention Tool® can be used to measure human emotions and which statistical outputs are provided in the tool for each tested visual stimulus. The method in Attention Tool for measuring the emotional strength, also known as physiological arousal, is based on pupil size variation, eye blink pattern and gaze behavior. Furthermore, the method is evaluated together with galvanic skin response (GSR) recordings that is a well-known and widely used method for measuring arousal. The comparison of these two methods shows that Attention Tool is just as good an evaluator of physiological arousal as the currently used GSR.
The research discussed in this paper is part of a pilot study in the use of wearable devices incorporating electroencephalogram (EEG) and heartrate sensors to sense for the emotional responses closely correlated to frustration when performing certain tasks. For this study the methodology used a combination of puzzle, arcade style game and a meditation apps to emulate a task based environment and detect frustration and satisfaction emotions. Preliminary results indicate that degree of task completion has an effect on emotions and can be detected by EEG and heartrate changes.
Thelxinoë: Recognizing Human Emotions Using Pupillometry and Machine Learningmlaij
In this study, we present a method for emotion recognition in Virtual Reality (VR) using pupillometry. We analyze pupil diameter responses to both visual and auditory stimuli via a VR headset and focus on extracting key features in the time-domain, frequency-domain, and time-frequency domain from VR-generated data. Our approach utilizes feature selection to identify the most impactful features using Maximum Relevance Minimum Redundancy (mRMR). By applying a Gradient Boosting model, an ensemble learning technique using stacked decision trees, we achieve an accuracy of 98.8% with feature engineering, compared to 84.9% without it. This research contributes significantly to the Thelxinoë framework, aiming to enhance VR experiences by integrating multiple sensor data for realistic and emotionally resonant touch interactions. Our findings open new avenues for developing more immersive and interactive VR environments, paving the way for future advancements in virtual touch technology.
Thelxinoë: Recognizing Human Emotions Using Pupillometry and Machine Learningmlaij
In this study, we present a method for emotion recognition in Virtual Reality (VR) using pupillometry. We analyze pupil diameter responses to both visual and auditory stimuli via a VR headset and focus on extracting key features in the time-domain, frequency-domain, and time-frequency domain from VR-generated data. Our approach utilizes feature selection to identify the most impactful features using Maximum Relevance Minimum Redundancy (mRMR). By applying a Gradient Boosting model, an ensemble learning technique using stacked decision trees, we achieve an accuracy of 98.8% with feature engineering, compared to 84.9% without it. This research contributes significantly to the Thelxinoë framework, aiming to enhance VR experiences by integrating multiple sensor data for realistic and emotionally resonant touch interactions. Our findings open new avenues for developing more immersive and interactive VR environments, paving the way for future advancements in virtual touch technology.
Do you know your EEG from your fMRI? Don't panic; we've got you covered! Learn about the best methods from psychology, behavioural economics and market research to gain insights from your customers and employees
Galvanic Skin Response Data Classification for Emotion Detection IJECEIAES
Emotion detection is a very exhausting job and needs a complicated process; moreover, these processes also require the proper data training and appropriate algorithm. The process involves the experimental research in psychological experiment and classification methods. This paper describes a method on detection emotion using Galvanic Skin Response (GSR) data. We used the Positive and Negative Affect Schedule (PANAS) method to get a good data training. Furthermore, Support Vector Machine and a correct preprocessing are performed to classify the GSR data. To validate the proposed approach, Receiver Operating Characteristic (ROC) curve, and accuracy measurement are used. Our method shows that the accuracy is about 75.65% while ROC is about 0.8019. It means that the emotion detection can be done satisfactorily and well performed.
The world of science cannot be measured in terms of development and progress. It has now reached to the technology known as “Blue eyes technology” that can sense and control human emotions and feelings through gadgets. The eyes, fingers, speech are the elements which help to sense the emotion level of human body.
The basic idea behind this technology is to give the computer the human power. We all have some perceptual abilities. That is we can understand each other’s feelings. For example we can understand ones emotional state by analyzing his facial expression. If we add these perceptual abilities of human to computers would enable computers to work together with human beings as intimate partners.
The “BLUE EYES” technology aims at creating computational machines that have perceptual and sensory ability like those of human beings. This paper implements a new technique known as Emotion Sensory World of Blue eyes technology which identifies human emotions (sad. happy. exalted or surprised) using image processing techniques by extracting eye portion from the captured image which is then compared with stored images of data base.
Knowledge and tools aimed at characterizing sleep in physiological and
pathological conditions. Develops and tests approaches and tools aimed at intervening on sleep to modify its efficiency and functions.
Emotion Detection Using Noninvasive Low-cost SensorsNicole Novielli
Emotion recognition from biometrics is relevant to a wide range of application domains, including healthcare and software development. Existing approaches usually adopt multi-electrodes sensors that could be expensive or uncomfortable to be used in real-life situations. We investigate whether we can reliably recognize high vs. low emotional valence and arousal by relying on noninvasive low-cost EEG, EMG, and GSR sensors. We report the results of an empirical study involving 19 subjects in a laboratory setting for emotion elicitation. We achieve state-of-the-art classification performance for both valence and arousal even in a cross-subject classification setting, which eliminates the need for individual training and tuning of classification models. Furthermore, we will discuss our ongoing work on the recognition of affective and cognitive states of software engineer during their daily programming tasks.
Analysis on techniques used to recognize and identifying the Human emotions IJECEIAES
Facial expression is a major area for non-verbal language in day to day life communication. As the statistical analysis shows only 7 percent of the message in communication was covered in verbal communication while 55 percent transmitted by facial expression. Emotional expression has been a research subject of physiology since Darwin’s work on emotional expression in the 19th century. According to Psychological theory the classification of human emotion is classified majorly into six emotions: happiness, fear, anger, surprise, disgust, and sadness. Facial expressions which involve the emotions and the nature of speech play a foremost role in expressing these emotions. Thereafter, researchers developed a system based on Anatomic of face named Facial Action Coding System (FACS) in 1970. Ever since the development of FACS there is a rapid progress in the domain of emotion recognition. This work is intended to give a thorough comparative analysis of the various techniques and methods that were applied to recognize and identify human emotions. This analysis results will help to identify proper and suitable techniques, algorithms and the methodologies for future research directions. In this paper extensive analysis on various recognition techniques used to identify the complexity in recognizing the facial expression is presented.
NYAI #23: Using Cognitive Neuroscience to Create AI (w/ Dr. Peter Olausson)Maryam Farooq
Dr. Peter Olausson started his career as a cognitive neuroscientist and spent over a decade at Yale University researching how our memories, motivation and cognitive control together affect decision-making. Before starting COGNITUUM, Peter was focusing on new breakthroughs in the information solutions that shape the human experience, including cognitive computing, data analytics, neuromanagement, and knowledge networks. Peter received his PhD in neuropharmacology at the University of Gothenburg in Sweden and his postdoctoral training at Yale University.
COGNITUUM has developed a general intelligence framework that provides a viable pathway towards human-level machine intelligence. The platform features continuous and real-time learning from any data source.
Psychology is a branch of science that studies the behavior, emotion, and thought structure of a living thing. Artificial intelligence, on the other hand, is a system that tries to imitate human behavior, reasoning ability, and problem-solving skills.
Now, with the partnership of these two structures, a new era begins in psychology. Artificial intelligence is ushering in a new era in psychology.
Thelxinoë: Recognizing Human Emotions Using Pupillometry and Machine Learningmlaij
In this study, we present a method for emotion recognition in Virtual Reality (VR) using pupillometry. We analyze pupil diameter responses to both visual and auditory stimuli via a VR headset and focus on extracting key features in the time-domain, frequency-domain, and time-frequency domain from VR-generated data. Our approach utilizes feature selection to identify the most impactful features using Maximum Relevance Minimum Redundancy (mRMR). By applying a Gradient Boosting model, an ensemble learning technique using stacked decision trees, we achieve an accuracy of 98.8% with feature engineering, compared to 84.9% without it. This research contributes significantly to the Thelxinoë framework, aiming to enhance VR experiences by integrating multiple sensor data for realistic and emotionally resonant touch interactions. Our findings open new avenues for developing more immersive and interactive VR environments, paving the way for future advancements in virtual touch technology.
Thelxinoë: Recognizing Human Emotions Using Pupillometry and Machine Learningmlaij
In this study, we present a method for emotion recognition in Virtual Reality (VR) using pupillometry. We analyze pupil diameter responses to both visual and auditory stimuli via a VR headset and focus on extracting key features in the time-domain, frequency-domain, and time-frequency domain from VR-generated data. Our approach utilizes feature selection to identify the most impactful features using Maximum Relevance Minimum Redundancy (mRMR). By applying a Gradient Boosting model, an ensemble learning technique using stacked decision trees, we achieve an accuracy of 98.8% with feature engineering, compared to 84.9% without it. This research contributes significantly to the Thelxinoë framework, aiming to enhance VR experiences by integrating multiple sensor data for realistic and emotionally resonant touch interactions. Our findings open new avenues for developing more immersive and interactive VR environments, paving the way for future advancements in virtual touch technology.
Do you know your EEG from your fMRI? Don't panic; we've got you covered! Learn about the best methods from psychology, behavioural economics and market research to gain insights from your customers and employees
Galvanic Skin Response Data Classification for Emotion Detection IJECEIAES
Emotion detection is a very exhausting job and needs a complicated process; moreover, these processes also require the proper data training and appropriate algorithm. The process involves the experimental research in psychological experiment and classification methods. This paper describes a method on detection emotion using Galvanic Skin Response (GSR) data. We used the Positive and Negative Affect Schedule (PANAS) method to get a good data training. Furthermore, Support Vector Machine and a correct preprocessing are performed to classify the GSR data. To validate the proposed approach, Receiver Operating Characteristic (ROC) curve, and accuracy measurement are used. Our method shows that the accuracy is about 75.65% while ROC is about 0.8019. It means that the emotion detection can be done satisfactorily and well performed.
The world of science cannot be measured in terms of development and progress. It has now reached to the technology known as “Blue eyes technology” that can sense and control human emotions and feelings through gadgets. The eyes, fingers, speech are the elements which help to sense the emotion level of human body.
The basic idea behind this technology is to give the computer the human power. We all have some perceptual abilities. That is we can understand each other’s feelings. For example we can understand ones emotional state by analyzing his facial expression. If we add these perceptual abilities of human to computers would enable computers to work together with human beings as intimate partners.
The “BLUE EYES” technology aims at creating computational machines that have perceptual and sensory ability like those of human beings. This paper implements a new technique known as Emotion Sensory World of Blue eyes technology which identifies human emotions (sad. happy. exalted or surprised) using image processing techniques by extracting eye portion from the captured image which is then compared with stored images of data base.
Knowledge and tools aimed at characterizing sleep in physiological and
pathological conditions. Develops and tests approaches and tools aimed at intervening on sleep to modify its efficiency and functions.
Emotion Detection Using Noninvasive Low-cost SensorsNicole Novielli
Emotion recognition from biometrics is relevant to a wide range of application domains, including healthcare and software development. Existing approaches usually adopt multi-electrodes sensors that could be expensive or uncomfortable to be used in real-life situations. We investigate whether we can reliably recognize high vs. low emotional valence and arousal by relying on noninvasive low-cost EEG, EMG, and GSR sensors. We report the results of an empirical study involving 19 subjects in a laboratory setting for emotion elicitation. We achieve state-of-the-art classification performance for both valence and arousal even in a cross-subject classification setting, which eliminates the need for individual training and tuning of classification models. Furthermore, we will discuss our ongoing work on the recognition of affective and cognitive states of software engineer during their daily programming tasks.
Analysis on techniques used to recognize and identifying the Human emotions IJECEIAES
Facial expression is a major area for non-verbal language in day to day life communication. As the statistical analysis shows only 7 percent of the message in communication was covered in verbal communication while 55 percent transmitted by facial expression. Emotional expression has been a research subject of physiology since Darwin’s work on emotional expression in the 19th century. According to Psychological theory the classification of human emotion is classified majorly into six emotions: happiness, fear, anger, surprise, disgust, and sadness. Facial expressions which involve the emotions and the nature of speech play a foremost role in expressing these emotions. Thereafter, researchers developed a system based on Anatomic of face named Facial Action Coding System (FACS) in 1970. Ever since the development of FACS there is a rapid progress in the domain of emotion recognition. This work is intended to give a thorough comparative analysis of the various techniques and methods that were applied to recognize and identify human emotions. This analysis results will help to identify proper and suitable techniques, algorithms and the methodologies for future research directions. In this paper extensive analysis on various recognition techniques used to identify the complexity in recognizing the facial expression is presented.
NYAI #23: Using Cognitive Neuroscience to Create AI (w/ Dr. Peter Olausson)Maryam Farooq
Dr. Peter Olausson started his career as a cognitive neuroscientist and spent over a decade at Yale University researching how our memories, motivation and cognitive control together affect decision-making. Before starting COGNITUUM, Peter was focusing on new breakthroughs in the information solutions that shape the human experience, including cognitive computing, data analytics, neuromanagement, and knowledge networks. Peter received his PhD in neuropharmacology at the University of Gothenburg in Sweden and his postdoctoral training at Yale University.
COGNITUUM has developed a general intelligence framework that provides a viable pathway towards human-level machine intelligence. The platform features continuous and real-time learning from any data source.
Psychology is a branch of science that studies the behavior, emotion, and thought structure of a living thing. Artificial intelligence, on the other hand, is a system that tries to imitate human behavior, reasoning ability, and problem-solving skills.
Now, with the partnership of these two structures, a new era begins in psychology. Artificial intelligence is ushering in a new era in psychology.
The most current release of Tobii Studio is version 2.0 which contains significant increases in stability, speed and functionality. Read about the updates here.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
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.
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.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
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.