Some researchers have developed relevant and diverse proposals for improving the content quality of the learner model in Intelligent Tutoring Systems, mainly reducing its uncertainty. Following
this aim, this paper proposes an open learner modeling approach using
Bayesian networks, focusing on negotiation mechanism to solve detected
cognitive conflicts that can emerge when the learner inspects information
of his model inferred by the system. Therefore, we addressed some issues
concerning the provision of inspectable model and negotiated updating
of this model. Its contribution lies in the fact that the learners attempt
to change the learner model is met with a challenge, leading to a decision
if the learner claims to know more (or less) than the model represents.
Improving a Recommender System Through Integration of User Profiles: a Semant...Jonathas Magalhães
The users are present in multiple social networks/virtual communities and each one can be considered as a source of information about this user. In face to this question it is important a mechanism to integrate the user profiles. Through the integration of user profiles it is possible identifier more accurately their interests analyzing other data sources that they are present, possible reducing the cold-start problem. In this context, we present a semantic approach to help integrate data from multiple sources, for the construction and maintenance of user profiles that will be used to improve the quality of a recommender system. To integrate data from multiple sources, we defined a heuristic that quantifies the importance of each data source for a given user. To validate our approach, we perform a case study, where the solution was coupled into a recommender system of papers focused in Software Engineering domain. The user profiles were built extracting their information from the Brazilian Curriculum Vitae database named CV-Lattes, an academic platform, and Linkedin, a business network. We compared the quality of the recommendation based on the profiles integrated and non-integrated. The results show the superior quality of the recommendation based on integrated profile.
Using worked example to teach the role of focal question: building conceptual...Paulo Correia
Frequently, students fail to define a proper focal question (FQ) and, sometimes, even ignore it during the Cmap elaboration. In this study, we propose the development and test of a process-oriented worked example (WE) to explain the concept of a focal question (FQ) to new mappers. Twenty-six graduate students were randomly assigned in Control Group (CG, did not study the WE, n = 12) and Experimental Group (EG, did study the WE, n = 14). A pairwise comparison was conducted for the performance in near- (questionnaires) and far-transfer tests (declaring a FQ). The results indicated that no effect existed for the near-transfer test when studying the WE; for the far-transfer test, studying the WE somewhat disturbed the conceptual understanding of FQ. Perhaps, the WE format caused an extraneous cognitive load and left only little working memory resources for germane load related to learn about the role of FQ. This process would be reflected in a poor performance during the tests. Moreover, the prior discussion about Cmap might negatively interfere in the training phase. Final considerations are teaching the role of FQ is not a trivial task and the use of WE might not be so proper for this purpose. Changes in the proposed WE format are under consideration to run future studies.
Improving a Recommender System Through Integration of User Profiles: a Semant...Jonathas Magalhães
The users are present in multiple social networks/virtual communities and each one can be considered as a source of information about this user. In face to this question it is important a mechanism to integrate the user profiles. Through the integration of user profiles it is possible identifier more accurately their interests analyzing other data sources that they are present, possible reducing the cold-start problem. In this context, we present a semantic approach to help integrate data from multiple sources, for the construction and maintenance of user profiles that will be used to improve the quality of a recommender system. To integrate data from multiple sources, we defined a heuristic that quantifies the importance of each data source for a given user. To validate our approach, we perform a case study, where the solution was coupled into a recommender system of papers focused in Software Engineering domain. The user profiles were built extracting their information from the Brazilian Curriculum Vitae database named CV-Lattes, an academic platform, and Linkedin, a business network. We compared the quality of the recommendation based on the profiles integrated and non-integrated. The results show the superior quality of the recommendation based on integrated profile.
Using worked example to teach the role of focal question: building conceptual...Paulo Correia
Frequently, students fail to define a proper focal question (FQ) and, sometimes, even ignore it during the Cmap elaboration. In this study, we propose the development and test of a process-oriented worked example (WE) to explain the concept of a focal question (FQ) to new mappers. Twenty-six graduate students were randomly assigned in Control Group (CG, did not study the WE, n = 12) and Experimental Group (EG, did study the WE, n = 14). A pairwise comparison was conducted for the performance in near- (questionnaires) and far-transfer tests (declaring a FQ). The results indicated that no effect existed for the near-transfer test when studying the WE; for the far-transfer test, studying the WE somewhat disturbed the conceptual understanding of FQ. Perhaps, the WE format caused an extraneous cognitive load and left only little working memory resources for germane load related to learn about the role of FQ. This process would be reflected in a poor performance during the tests. Moreover, the prior discussion about Cmap might negatively interfere in the training phase. Final considerations are teaching the role of FQ is not a trivial task and the use of WE might not be so proper for this purpose. Changes in the proposed WE format are under consideration to run future studies.
Enhancing the Status Message Question Asking Process on FacebookJonathas Magalhães
People have been using Social Networks to search for help by broadcasting messages that reflect their information needs. However, several factors, usually not considered by the user, influence the outcome of receiving or not an answer. In this work, we aim to increase the users’ chances of finding someone who could help them. For this purpose, we propose a mobile app called Social Query, which guides the users through some steps before they share the problem with their friends. As far as we know, this is the first work to merge these three aspects of the social search: Question Rephrasing, Expert Search Filtering and Expertise Finding. To evaluate our proposal, we ran a questionnaire in which users considered Useful most functions of the app.
Recommending Scientific Papers: Investigating the User CurriculumJonathas Magalhães
In this paper, we propose a Personalized Paper Recommender System, a new user-paper based approach that takes into consideration the user academic curriculum vitae. To build the user profiles, we use a Brazilian academic platform called CV-Lattes. Furthermore, we examine some issues related to user profiling, such as (i) we define and compare different strategies to build and represent the user profiles, using terms and using concepts; (ii) we verify how much past information of a user is required to provide good recommendations; (iii) we compare our approaches with the state-of-art in paper recommendation using the CV-Lattes. To validate our strategies, we conduct a user study experiment involving 30 users in the Computer Science domain. Our results show that (i) our approaches outperform the state-of-art in CV-Lattes; (ii) concepts profiles are comparable with the terms profiles; (iii) analyzing the content of the past four years for terms profiles and five years for concepts profiles achieved the best results; and (iv) terms profiles provide better results but they are slower than concepts profiles, thus, if the system needs real time recommendations, concepts profiles are better.
An Ontology Based Approach for Sharing Distributed EducationalJonathas Magalhães
Over the last decade, research in the area of e-learning employed efforts in solutions for sharing and reuse of educational resources. However, these solutions were not built for communication with each other. That is, in general, the development of these solutions has not provided mechanisms to facilitate the exchange of resources among them. Thus, this effort led to a fragmented landscape of concurrent metadata schemas or interface mechanisms. To address this problem, this work aims to design an ontology based semantic model for sharing educational resources from different sources. This model serves as a hub of enriched metadata for educational resources, aiming to classify, organize and align these resources. At the
current step of this research, we developed the ontology for the integration model, and initial evaluations were performed, showing its efficiency in the formal description of educational resources.
A Recommender System for Predicting User Engagement in TwitterJonathas Magalhães
The RecSys Challenge is a traditional competition among
Recommender Systems’ (RS) researchers. The 2014 edition is focused on predicting the amount of interaction achieved by tweets related to movies. In this paper, we present an approach to participate in the 2014 RecSys Challenge. Our approach consists of three steps: (i) using binary classification methods in order to split the tweets into two lists, those having user engagement equal to zero, and those having user engagement different from zero; (ii) each list is sorted through the use of regression methods; and (iii) is performed a concatenation of the two lists and a sort of tweets. To validate our approach we tested 126 configurations and verify that the settings using MovieTweetings dataset, Naïve Bayes classifier and Linear Regression, obtained the best results: nDCG@10 = 0.9037242.
Social Query is a new and efficient way to get
answers on the social networks. However, the popular method of sharing public questions could be optimized by directing the question to an expert, a process called query routing. In this work, we propose a Social Query System for query routing on Twitter, currently, one of the most popular social networks. The Social Query Systems analyzes the information about the questioner’s followers and recommends the most suitable users to answer the questions. The use of the system changes the usual process, working apart of Twitter and allowing questioner and responder exceed the limit of 140 characters. Through a qualitative evaluation, we showed promising results and ideas for improving the system and the recommendation algorithm.
A Query Routing Model to Rank Expertcandidates on TwitterJonathas Magalhães
Online Social Networks (OSNs) have become very popular and new ways of use their virtual environment have emerged. One of these new ways is a method to obtain information online called Social Query that consists of sharing a question on an OSN and waiting for answers come from contacts. The usual strategy is sharing a question that will be visible to everyone (public). However, this way there is no guarantee that an answer will be received neither about the quality of the answer. Directing the question to an expert about its subject (Query Routing) is a better strategy, but decides to whom direct the question is not always an easy task. In this work, we propose and evaluate a model to decide who user is the most able to receive a question and answer it correctly and quickly. The differential of our research is that we focused in OSNs context and leaded with the recommendation as multi-criteria decision making problem. Our evaluation shows promising results and confirms the great performance of our proposal.
Predicting Potential Responders in Twitter: A Query Routing AlgorithmJonathas Magalhães
A phenomenon not so recent is the substantial increase in popularity and use of online social networks. With that has emerged a new way to find information online: the social query, which consists of posting a question in a social network and wait for responses from close friends. Usually, a question is posted to be visible to everyone, but we believe that this is not the best way: there will be the possibility of receiving several responses (including wrong), keep receiving answers where there is no need, do not receive answers, etc. The query router problem consists of finding the most able individual in the personal social network
of the questioner. This work presents an algorithm to Routing Questions in Twitter. The model was validated through its predict capacity and the results shows that its recommendations match in half cases only when combined with a technique to enrich the information present in the question.
In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.
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.
Threats to mobile devices are more prevalent and increasing in scope and complexity. Users of mobile devices desire to take full advantage of the features
available on those devices, but many of the features provide convenience and capability but sacrifice security. This best practices guide outlines steps the users can take to better protect personal devices and information.
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.
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.
Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!SOFTTECHHUB
As the digital landscape continually evolves, operating systems play a critical role in shaping user experiences and productivity. The launch of Nitrux Linux 3.5.0 marks a significant milestone, offering a robust alternative to traditional systems such as Windows 11. This article delves into the essence of Nitrux Linux 3.5.0, exploring its unique features, advantages, and how it stands as a compelling choice for both casual users and tech enthusiasts.
A tale of scale & speed: How the US Navy is enabling software delivery from l...sonjaschweigert1
Rapid and secure feature delivery is a goal across every application team and every branch of the DoD. The Navy’s DevSecOps platform, Party Barge, has achieved:
- Reduction in onboarding time from 5 weeks to 1 day
- Improved developer experience and productivity through actionable findings and reduction of false positives
- Maintenance of superior security standards and inherent policy enforcement with Authorization to Operate (ATO)
Development teams can ship efficiently and ensure applications are cyber ready for Navy Authorizing Officials (AOs). In this webinar, Sigma Defense and Anchore will give attendees a look behind the scenes and demo secure pipeline automation and security artifacts that speed up application ATO and time to production.
We will cover:
- How to remove silos in DevSecOps
- How to build efficient development pipeline roles and component templates
- How to deliver security artifacts that matter for ATO’s (SBOMs, vulnerability reports, and policy evidence)
- How to streamline operations with automated policy checks on container images
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.
Enhancing the Status Message Question Asking Process on FacebookJonathas Magalhães
People have been using Social Networks to search for help by broadcasting messages that reflect their information needs. However, several factors, usually not considered by the user, influence the outcome of receiving or not an answer. In this work, we aim to increase the users’ chances of finding someone who could help them. For this purpose, we propose a mobile app called Social Query, which guides the users through some steps before they share the problem with their friends. As far as we know, this is the first work to merge these three aspects of the social search: Question Rephrasing, Expert Search Filtering and Expertise Finding. To evaluate our proposal, we ran a questionnaire in which users considered Useful most functions of the app.
Recommending Scientific Papers: Investigating the User CurriculumJonathas Magalhães
In this paper, we propose a Personalized Paper Recommender System, a new user-paper based approach that takes into consideration the user academic curriculum vitae. To build the user profiles, we use a Brazilian academic platform called CV-Lattes. Furthermore, we examine some issues related to user profiling, such as (i) we define and compare different strategies to build and represent the user profiles, using terms and using concepts; (ii) we verify how much past information of a user is required to provide good recommendations; (iii) we compare our approaches with the state-of-art in paper recommendation using the CV-Lattes. To validate our strategies, we conduct a user study experiment involving 30 users in the Computer Science domain. Our results show that (i) our approaches outperform the state-of-art in CV-Lattes; (ii) concepts profiles are comparable with the terms profiles; (iii) analyzing the content of the past four years for terms profiles and five years for concepts profiles achieved the best results; and (iv) terms profiles provide better results but they are slower than concepts profiles, thus, if the system needs real time recommendations, concepts profiles are better.
An Ontology Based Approach for Sharing Distributed EducationalJonathas Magalhães
Over the last decade, research in the area of e-learning employed efforts in solutions for sharing and reuse of educational resources. However, these solutions were not built for communication with each other. That is, in general, the development of these solutions has not provided mechanisms to facilitate the exchange of resources among them. Thus, this effort led to a fragmented landscape of concurrent metadata schemas or interface mechanisms. To address this problem, this work aims to design an ontology based semantic model for sharing educational resources from different sources. This model serves as a hub of enriched metadata for educational resources, aiming to classify, organize and align these resources. At the
current step of this research, we developed the ontology for the integration model, and initial evaluations were performed, showing its efficiency in the formal description of educational resources.
A Recommender System for Predicting User Engagement in TwitterJonathas Magalhães
The RecSys Challenge is a traditional competition among
Recommender Systems’ (RS) researchers. The 2014 edition is focused on predicting the amount of interaction achieved by tweets related to movies. In this paper, we present an approach to participate in the 2014 RecSys Challenge. Our approach consists of three steps: (i) using binary classification methods in order to split the tweets into two lists, those having user engagement equal to zero, and those having user engagement different from zero; (ii) each list is sorted through the use of regression methods; and (iii) is performed a concatenation of the two lists and a sort of tweets. To validate our approach we tested 126 configurations and verify that the settings using MovieTweetings dataset, Naïve Bayes classifier and Linear Regression, obtained the best results: nDCG@10 = 0.9037242.
Social Query is a new and efficient way to get
answers on the social networks. However, the popular method of sharing public questions could be optimized by directing the question to an expert, a process called query routing. In this work, we propose a Social Query System for query routing on Twitter, currently, one of the most popular social networks. The Social Query Systems analyzes the information about the questioner’s followers and recommends the most suitable users to answer the questions. The use of the system changes the usual process, working apart of Twitter and allowing questioner and responder exceed the limit of 140 characters. Through a qualitative evaluation, we showed promising results and ideas for improving the system and the recommendation algorithm.
A Query Routing Model to Rank Expertcandidates on TwitterJonathas Magalhães
Online Social Networks (OSNs) have become very popular and new ways of use their virtual environment have emerged. One of these new ways is a method to obtain information online called Social Query that consists of sharing a question on an OSN and waiting for answers come from contacts. The usual strategy is sharing a question that will be visible to everyone (public). However, this way there is no guarantee that an answer will be received neither about the quality of the answer. Directing the question to an expert about its subject (Query Routing) is a better strategy, but decides to whom direct the question is not always an easy task. In this work, we propose and evaluate a model to decide who user is the most able to receive a question and answer it correctly and quickly. The differential of our research is that we focused in OSNs context and leaded with the recommendation as multi-criteria decision making problem. Our evaluation shows promising results and confirms the great performance of our proposal.
Predicting Potential Responders in Twitter: A Query Routing AlgorithmJonathas Magalhães
A phenomenon not so recent is the substantial increase in popularity and use of online social networks. With that has emerged a new way to find information online: the social query, which consists of posting a question in a social network and wait for responses from close friends. Usually, a question is posted to be visible to everyone, but we believe that this is not the best way: there will be the possibility of receiving several responses (including wrong), keep receiving answers where there is no need, do not receive answers, etc. The query router problem consists of finding the most able individual in the personal social network
of the questioner. This work presents an algorithm to Routing Questions in Twitter. The model was validated through its predict capacity and the results shows that its recommendations match in half cases only when combined with a technique to enrich the information present in the question.
In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.
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.
Threats to mobile devices are more prevalent and increasing in scope and complexity. Users of mobile devices desire to take full advantage of the features
available on those devices, but many of the features provide convenience and capability but sacrifice security. This best practices guide outlines steps the users can take to better protect personal devices and information.
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.
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.
Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!SOFTTECHHUB
As the digital landscape continually evolves, operating systems play a critical role in shaping user experiences and productivity. The launch of Nitrux Linux 3.5.0 marks a significant milestone, offering a robust alternative to traditional systems such as Windows 11. This article delves into the essence of Nitrux Linux 3.5.0, exploring its unique features, advantages, and how it stands as a compelling choice for both casual users and tech enthusiasts.
A tale of scale & speed: How the US Navy is enabling software delivery from l...sonjaschweigert1
Rapid and secure feature delivery is a goal across every application team and every branch of the DoD. The Navy’s DevSecOps platform, Party Barge, has achieved:
- Reduction in onboarding time from 5 weeks to 1 day
- Improved developer experience and productivity through actionable findings and reduction of false positives
- Maintenance of superior security standards and inherent policy enforcement with Authorization to Operate (ATO)
Development teams can ship efficiently and ensure applications are cyber ready for Navy Authorizing Officials (AOs). In this webinar, Sigma Defense and Anchore will give attendees a look behind the scenes and demo secure pipeline automation and security artifacts that speed up application ATO and time to production.
We will cover:
- How to remove silos in DevSecOps
- How to build efficient development pipeline roles and component templates
- How to deliver security artifacts that matter for ATO’s (SBOMs, vulnerability reports, and policy evidence)
- How to streamline operations with automated policy checks on container images
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.
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.
GridMate - End to end testing is a critical piece to ensure quality and avoid...ThomasParaiso2
End to end testing is a critical piece to ensure quality and avoid regressions. In this session, we share our journey building an E2E testing pipeline for GridMate components (LWC and Aura) using Cypress, JSForce, FakerJS…
In his public lecture, Christian Timmerer provides insights into the fascinating history of video streaming, starting from its humble beginnings before YouTube to the groundbreaking technologies that now dominate platforms like Netflix and ORF ON. Timmerer also presents provocative contributions of his own that have significantly influenced the industry. He concludes by looking at future challenges and invites the audience to join in a discussion.
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
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.
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
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...SOFTTECHHUB
The choice of an operating system plays a pivotal role in shaping our computing experience. For decades, Microsoft's Windows has dominated the market, offering a familiar and widely adopted platform for personal and professional use. However, as technological advancements continue to push the boundaries of innovation, alternative operating systems have emerged, challenging the status quo and offering users a fresh perspective on computing.
One such alternative that has garnered significant attention and acclaim is Nitrux Linux 3.5.0, a sleek, powerful, and user-friendly Linux distribution that promises to redefine the way we interact with our devices. With its focus on performance, security, and customization, Nitrux Linux presents a compelling case for those seeking to break free from the constraints of proprietary software and embrace the freedom and flexibility of open-source computing.
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfPaige Cruz
Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
I, a former op, would like to extend an invitation to all application developers to join the observability party will share these foundational concepts to build on:
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdf
An Open and Inspectable Learner Modeling with a Negotiation Mechanism to Solve Cognitive Conflicts in an Intelligent Tutoring System
1. Introduction
Related Work
Our Proposal
Demonstration Scenario
Final Considerations
References
An Open and Inspectable Learner Modeling with a
Negotiation Mechanism to Solve Cognitive Conflicts
in an Intelligent Tutoring System
Evandro Costa, Priscylla Silva,
Jonathas Magalh˜es and Marlos Silva
a
TIPS Group
Computing Institute
Federal University of Alagoas, Brazil
Federal University of Campina Grande, Brazil
E. Costa, P. Silva, J. Magalh˜es and M. Silva
a PALE UMAP 2012 1
2. Introduction
Related Work
Our Proposal
Demonstration Scenario
Final Considerations
References
Research Context
Learner modeling tasks in ITS;
High level of uncertainty;
Probabilistic Learner Modeling in ITS;
Opening and Viewing Learner Model;
Presence of Cognitive Conflicts;
Mechanisms for dealing with conflicts;
Negotiating the open learner model.
E. Costa, P. Silva, J. Magalh˜es and M. Silva
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3. Introduction
Related Work
Our Proposal
Demonstration Scenario
Final Considerations
References
Research Questions
Q1 : What approach should we adopt to deal with uncertainty
found in a learner model for ITS?
Q2 : What is an appropriate way to define and viewing OLM?
Q3 : How can we detect cognitive conflicts between the student
and the system concerning problem solving activities?
Q4 : How can we effectively address these conflicts?
E. Costa, P. Silva, J. Magalh˜es and M. Silva
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4. Introduction
Related Work
Our Proposal
Demonstration Scenario
Final Considerations
References
How those Questions have been addressed?
With respect to Q1 – Representation and Maintenance:
Conati et al. [2];
E. Costa, P. Silva, J. Magalh˜es and M. Silva
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5. Introduction
Related Work
Our Proposal
Demonstration Scenario
Final Considerations
References
How those Questions have been addressed?
With respect to Q2 – OLM and Visualization:
Zapata and Greer [5];
E. Costa, P. Silva, J. Magalh˜es and M. Silva
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6. Introduction
Related Work
Our Proposal
Demonstration Scenario
Final Considerations
References
How those Questions have been addressed?
With respect to Q3 and Q4 – Conflicts detection and Negotiation:
Bull et al. [1];
Dimitrova [3];
Thomson and Mitrovic [4].
E. Costa, P. Silva, J. Magalh˜es and M. Silva
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7. Introduction
Related Work
Our Proposal
Demonstration Scenario
Final Considerations
References
Our General Approach
E. Costa, P. Silva, J. Magalh˜es and M. Silva
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8. Introduction
Related Work
Our Proposal
Demonstration Scenario
Final Considerations
References
The Open Learner Model
E. Costa, P. Silva, J. Magalh˜es and M. Silva
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9. Introduction
Related Work
Our Proposal
Demonstration Scenario
Final Considerations
References
The Open Learner Model
1 4
The system put a problem to the learner: 3 + 3;
He declares his belief:
Very unsure = 0.05;
Unsure = 0.25;
Almost sure = 0.5;
Sure = 0.75;
Very sure = 0.95.
Then, he submits a solution and the system evaluate it and
returns a grade [0,1].
E. Costa, P. Silva, J. Magalh˜es and M. Silva
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10. Introduction
Related Work
Our Proposal
Demonstration Scenario
Final Considerations
References
The Open Learner Model
(a) The Ms . (b) The Mt .
Figure: Task-specific part of the Learner Model.
E. Costa, P. Silva, J. Magalh˜es and M. Silva
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11. Introduction
Related Work
Our Proposal
Demonstration Scenario
Final Considerations
References
The Open Learner Model
(a) The Ms . (b) The Mt .
Figure: Domain-general part of the Learner Model.
E. Costa, P. Silva, J. Magalh˜es and M. Silva
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12. Introduction
Related Work
Our Proposal
Demonstration Scenario
Final Considerations
References
The Open Learner Model
Figure: The Visualization of the Learner Model.
E. Costa, P. Silva, J. Magalh˜es and M. Silva
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13. Introduction
Related Work
Our Proposal
Demonstration Scenario
Final Considerations
References
Negotiation Process
The negotiation mechanism depends on the learner’s credibility:
Figure: The DBN of the learner’s credibility.
E. Costa, P. Silva, J. Magalh˜es and M. Silva
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14. Introduction
Related Work
Our Proposal
Demonstration Scenario
Final Considerations
References
Negotiation Process
When the learner wants to change the tutor’s belief
Credibility L’s belief < T’s belief L’s Belief > T’s belief
Low Persuasion Persuasion
Medium Persuasion Cooperation
High Persuasion Cooperation
When the tutor wants to change the student’s belief
Credibility L’s belief < T’s belief L’s belief > T’s belief
Low Support Contestation
Medium Support Contestation
High Support Contestation
E. Costa, P. Silva, J. Magalh˜es and M. Silva
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15. Introduction
Related Work
Our Proposal
Demonstration Scenario
Final Considerations
References
Prove Process
During the negotiation:
The system can request that the learner proves his knowledge, or;
The learner can request the opportunity of prove.
The proof process consists of:
Two problems and the learner has two chances to solve each
problem;
Then, his model is updated.
E. Costa, P. Silva, J. Magalh˜es and M. Silva
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16. Introduction
Related Work
Our Proposal
Demonstration Scenario
Final Considerations
References
Demonstration Scenario
Figure: Example of Negotiation Dialogue Started by the Learner.
E. Costa, P. Silva, J. Magalh˜es and M. Silva
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17. Introduction
Related Work
Our Proposal
Demonstration Scenario
Final Considerations
References
We are we going next?
Improve the visualization, allowing the visualization of the two
parts of the model;
Put other evidences in the learner model: social characteristics,
CV-curriculum of the student, collaborative information;
Perform an experiment in a basic math classroom.
E. Costa, P. Silva, J. Magalh˜es and M. Silva
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18. Introduction
Related Work
Our Proposal
Demonstration Scenario
Final Considerations
References
References
Susan Bull, Paul Brna, and Helen Pain.
Extending the scope of the student model.
User Modeling and User-Adapted Interaction, 5(1):45–65, 1995.
Cristina Conati, Abigail Gertner, and Kurt Vanlehn.
Using bayesian networks to manage uncertainty in student
modeling.
User Modeling and User-Adapted Interaction, 12(4):371–417,
2002.
Vania Dimitrova.
Style-olm: Interactive open learner modelling.
International Journal of Artificial Intelligence in Education,
13(1):35–78, January 2003.
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19. Introduction
Related Work
Our Proposal
Demonstration Scenario
Final Considerations
References
Referˆncias
e
David Thomson and Antonija Mitrovic.
Preliminary evaluation of a negotiable student model in a
constraint-based its.
Research and Practice in Technology Enhanced Learning,
5(1):19–33, 2010.
Juan-Diego Zapata-Rivera and Jim E. Greer.
Interacting with inspectable bayesian student models.
International Journal of Artificial Intelligence in Education,
14(2):127–163, 2004.
E. Costa, P. Silva, J. Magalh˜es and M. Silva
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20. Introduction
Related Work
Our Proposal
Demonstration Scenario
Final Considerations
References
Thanks!!
E. Costa, P. Silva, J. Magalh˜es and M. Silva
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21. Introduction
Related Work
Our Proposal
Demonstration Scenario
Final Considerations
References
For more information: http://tip.ic.ufal.br/site/
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