Working memory span tasks involve maintaining items while performing a concurrent processing task. The document summarizes the time-based resource-sharing model, which proposes that working memory spans depend on the rate of processing and duration of the processing component, rather than the complexity of the task. Experiments varying factors like number of retrievals, retrieval speed, and task type support the model by showing spans correlate with actual processing time but not task nature independently of duration. The model argues working memory spans are limited by the time attention is unavailable to refresh memory traces due to concurrent processing.
1. The document summarizes the Time-Based Resource-Sharing model of working memory which proposes that working memory span tasks depend only on the time during which processing captures attention, not on the complexity of the processing.
2. According to the model, working memory performance depends on the rate of processing (number of retrievals per unit time), the duration of individual processing steps, and whether processing involves retrievals from long-term memory.
3. Several experiments are described that support the model by showing equivalent effects of different tasks when their actual processing durations are equated.
This study examined two hypotheses about what drives performance on working memory span tasks: the resource-sharing hypothesis and the temporal decay hypothesis. The researchers developed a new paradigm to test these hypotheses. In one experiment, they found that equating duration while manipulating cognitive cost did not significantly change span performance across tasks. A second experiment showed that a continuous operation span task requiring sustained attention had a lower span than a reading operation span task. This supports the idea that working memory span depends more on the attentional demands of the processing task than on duration alone.
The document summarizes the time-based resource-sharing model of working memory. The model proposes that (1) processing and memory maintenance both require attention, which is limited, requiring sharing. (2) When attention is switched away from maintenance, activation decays over time. (3) Memory retrievals have the most detrimental effect on concurrent maintenance due to a bottleneck. (4) Sharing attention is time-based, with cognitive load determined by the proportion of time attention is captured by processing versus refreshing memory. Experiments support cognitive load varying with retrieval rate and duration rather than complexity.
The document discusses extending the Chemical Tagger natural language processing tool to be more applicable to climate science texts by incorporating climate science controlled vocabularies. It describes adapting the Chemical Tagger, originally designed for chemistry texts, to process abstracts from climate science journals. This includes modifying the tagger's dictionaries and grammars. Web forms and a CIM document viewer are also discussed which can generate and view outputs in the CIM XML format. The document aims to highlight climate science terms in texts to map them to a controlled vocabulary and better populate the CIM framework.
The study used temporal order judgment (TOJ) tasks to directly measure how motivationally significant stimuli like faces capture attention. In Experiment 1, upright faces showed prior entry over inverted faces. Experiment 2 found emotional faces had greater prior entry than neutral faces. Experiment 3 ruled out low-level feature differences by finding prior entry for inverted emotional faces. Experiment 4 eliminated prior entry for inverted faces, supporting the role of holistic processing. Experiment 5 extended these effects to realistic faces. Experiment 6 addressed response biases. Across experiments, the study provides evidence that faces and emotional expressions capture attention through visual prior entry.
Auditory measures of attention & working memory in children with learning dis...Alexander Decker
This document summarizes a study that compared the auditory attention and working memory abilities of children with learning disabilities to typically developing children. The study assessed 19 children aged 10-14 years using dichotic listening, auditory Stroop, and digit backward recall tasks. The results showed that children with learning disabilities performed significantly worse than typically developing children on all tasks. Specifically, children with learning disabilities had longer reaction times on the auditory Stroop task, lower scores on digit backward recall, and poorer performance on the dichotic listening task. The findings suggest that children with learning disabilities have deficits in selective attention and working memory compared to their typically developing peers.
The port of Sines: contribution for the emergence of a regional clusterCláudio Carneiro
The document discusses the port of Sines in Portugal and its potential role in the emergence of a regional cluster. It provides background on the port's past as an industrial complex focused on oil refining. Currently, the port has diversified its cargo and is managed by a public authority with private terminals. The future potential for Sines includes capturing more transatlantic cargo as the Panama Canal expands, allowing it to serve as a strategic port connecting Europe, North and South America. The port aims to develop regional linkages through rail and other infrastructure to spur economic growth and form a maritime cluster across industries like shipbuilding and renewable energy.
The document discusses the "cocktail party effect", which is our ability to focus attention on a single conversation among other noises. It describes early research by Colin Cherry in the 1950s studying how air traffic controllers distinguish pilot communications. The key challenges are sound separation and directing attention. Later studies showed little semantic information is obtained from unattended messages due to early filtering in the brain. While our understanding of these auditory processes is still limited, factors like expectations and divided attention can contribute to failures in sound separation known as "inattentional blindness."
1. The document summarizes the Time-Based Resource-Sharing model of working memory which proposes that working memory span tasks depend only on the time during which processing captures attention, not on the complexity of the processing.
2. According to the model, working memory performance depends on the rate of processing (number of retrievals per unit time), the duration of individual processing steps, and whether processing involves retrievals from long-term memory.
3. Several experiments are described that support the model by showing equivalent effects of different tasks when their actual processing durations are equated.
This study examined two hypotheses about what drives performance on working memory span tasks: the resource-sharing hypothesis and the temporal decay hypothesis. The researchers developed a new paradigm to test these hypotheses. In one experiment, they found that equating duration while manipulating cognitive cost did not significantly change span performance across tasks. A second experiment showed that a continuous operation span task requiring sustained attention had a lower span than a reading operation span task. This supports the idea that working memory span depends more on the attentional demands of the processing task than on duration alone.
The document summarizes the time-based resource-sharing model of working memory. The model proposes that (1) processing and memory maintenance both require attention, which is limited, requiring sharing. (2) When attention is switched away from maintenance, activation decays over time. (3) Memory retrievals have the most detrimental effect on concurrent maintenance due to a bottleneck. (4) Sharing attention is time-based, with cognitive load determined by the proportion of time attention is captured by processing versus refreshing memory. Experiments support cognitive load varying with retrieval rate and duration rather than complexity.
The document discusses extending the Chemical Tagger natural language processing tool to be more applicable to climate science texts by incorporating climate science controlled vocabularies. It describes adapting the Chemical Tagger, originally designed for chemistry texts, to process abstracts from climate science journals. This includes modifying the tagger's dictionaries and grammars. Web forms and a CIM document viewer are also discussed which can generate and view outputs in the CIM XML format. The document aims to highlight climate science terms in texts to map them to a controlled vocabulary and better populate the CIM framework.
The study used temporal order judgment (TOJ) tasks to directly measure how motivationally significant stimuli like faces capture attention. In Experiment 1, upright faces showed prior entry over inverted faces. Experiment 2 found emotional faces had greater prior entry than neutral faces. Experiment 3 ruled out low-level feature differences by finding prior entry for inverted emotional faces. Experiment 4 eliminated prior entry for inverted faces, supporting the role of holistic processing. Experiment 5 extended these effects to realistic faces. Experiment 6 addressed response biases. Across experiments, the study provides evidence that faces and emotional expressions capture attention through visual prior entry.
Auditory measures of attention & working memory in children with learning dis...Alexander Decker
This document summarizes a study that compared the auditory attention and working memory abilities of children with learning disabilities to typically developing children. The study assessed 19 children aged 10-14 years using dichotic listening, auditory Stroop, and digit backward recall tasks. The results showed that children with learning disabilities performed significantly worse than typically developing children on all tasks. Specifically, children with learning disabilities had longer reaction times on the auditory Stroop task, lower scores on digit backward recall, and poorer performance on the dichotic listening task. The findings suggest that children with learning disabilities have deficits in selective attention and working memory compared to their typically developing peers.
The port of Sines: contribution for the emergence of a regional clusterCláudio Carneiro
The document discusses the port of Sines in Portugal and its potential role in the emergence of a regional cluster. It provides background on the port's past as an industrial complex focused on oil refining. Currently, the port has diversified its cargo and is managed by a public authority with private terminals. The future potential for Sines includes capturing more transatlantic cargo as the Panama Canal expands, allowing it to serve as a strategic port connecting Europe, North and South America. The port aims to develop regional linkages through rail and other infrastructure to spur economic growth and form a maritime cluster across industries like shipbuilding and renewable energy.
The document discusses the "cocktail party effect", which is our ability to focus attention on a single conversation among other noises. It describes early research by Colin Cherry in the 1950s studying how air traffic controllers distinguish pilot communications. The key challenges are sound separation and directing attention. Later studies showed little semantic information is obtained from unattended messages due to early filtering in the brain. While our understanding of these auditory processes is still limited, factors like expectations and divided attention can contribute to failures in sound separation known as "inattentional blindness."
DocValues aka. Column Stride Fields in Lucene 4.0 - By Willnauer Simonlucenerevolution
See conference video - http://www.lucidimagination.com/devzone/events/conferences/revolution/2011
Lucene 4.0 is on its way to deliver a tremendous amount of new features and improvements. Beside
Real-Time Search & Flexible Indexing DocValues aka. Column Stride Fields is one of the “next
generation” features. DocValues enable Lucene to efficiently store and retrieve type-safe Document
& Value pairs in a column stride fashion either entirely memory resident random access or disk
resident iterator based without the need to un-invert fields. Its final goal is to provide a
independently update-able per document storage for scoring, sorting or even filtering. This talk will
introduce the current state of development, implementation details, its features and how DocValues
have been integrated into Lucene’s Codec API for full extendability.
Lucene 4.0 is on its way to deliver a tremendous amount of new features and improvements. Beside Real-Time Search & Flexible Indexing DocValues aka. Column Stride Fields is one of the "next generation" features
Column Stride Fields, also known as DocValues, provide a native way in Lucene to store numeric or arbitrary values per document without requiring conversion or parsing. They allow for constant-time random access to these values. DocValues improve on alternatives like Stored Fields and FieldCache by using a dense column-based storage that is faster to load and uses less memory. The current implementation of DocValues is ready to be landed in Lucene core, providing a customizable and efficient way to store additional per-document values in Lucene.
Consistency Models in New Generation Databasesiammutex
The document discusses transaction and consistency models in databases as the database world changes. It covers the CAP theorem and how it is impossible to guarantee availability, consistency and partition tolerance simultaneously in an asynchronous distributed system. It then discusses various consistency models including eventual, monotonic read, and read your own writes (RYOW). Examples are provided of eventually consistent systems. The document also discusses Amazon Dynamo's consistency model and how MongoDB supports different consistency levels and strategies for handling transactions and writes in distributed systems.
The document discusses transaction and consistency models in databases as the database world changes. It covers the CAP theorem and how it is impossible to guarantee availability, consistency and partition tolerance simultaneously in an asynchronous distributed system. It then discusses various consistency models including eventual, monotonic read, and read your own writes (RYOW). Examples are provided of eventually consistent systems. The document also discusses Amazon Dynamo's consistency model and how MongoDB supports different consistency levels and strategies for handling multiple writers and network partitions.
Thoughts on Transaction and Consistency Modelsiammutex
The document discusses database transaction models and consistency in light of CAP theorem. It explains that RDBMS use ACID transactions while newer databases like NoSQL choose availability over consistency. Eventual consistency guarantees last write wins if no new updates. It discusses strategies for handling multiple writers like last write wins with vector clocks. MongoDB supports atomic operations on single documents and provides options for read and write scaling through replication and sharding.
This document discusses binding and scope in programming languages. It defines binding as the association between a name and the thing it names. Binding can occur at different times, such as language design time, implementation time, program writing time, compile time, link time, load time, and run time. The key concepts of static and dynamic scoping are introduced. Static scoping means bindings are determined by examining the program text, while dynamic scoping means bindings depend on runtime control flow. The document also discusses modules, classes, inheritance, polymorphism, operator overloading, and closures.
Realtime olap architecture in apache kylin 3.0Shi Shao Feng
1) Apache Kylin v3.0 introduces a new real-time OLAP architecture using long-running streaming jobs to provide low latency queries over streaming data.
2) The data flow uses streaming receivers to aggregate streaming events in memory and flush to local disk in real-time segments before uploading to remote storage.
3) The query flow scans local real-time segments for low latency before querying remote historical data, providing millisecond responses over trillions of rows.
The document describes a series of experiments that investigated the effect of memory load on processing performance. Specifically, it examined how increasing the number of items held in memory affected response times and accuracy on various processing tasks. The experiments varied the domain of the items held in memory (verbal vs spatial) and the type of concurrent processing task. The results showed that memory load had a larger detrimental effect on both processing accuracy and response times when items from different domains (verbal and spatial) had to be maintained together in working memory, compared to when items were from the same domain. This suggests maintaining cross-domain items in working memory is more cognitively demanding than single-domain items.
The document describes a series of experiments that investigated the effect of memory load on processing performance. Specifically, it examined how increasing the number of items held in memory affected response times and accuracy on various processing tasks. The experiments varied the domain of the items held in memory (verbal vs spatial) and the type of concurrent processing task. The results showed that memory load had a larger detrimental effect on both processing accuracy and response times when items from different domains (verbal and spatial) had to be maintained together in working memory, compared to when items were from the same domain. This suggests maintaining cross-domain items in working memory is more cognitively demanding than single-domain items.
This study examined working memory and cognitive inhibition in gifted children compared to non-gifted children. [1] The gifted children performed better on reasoning, verbal fluidity, and working memory tasks. [2] However, both groups performed similarly on divergent thinking and cognitive inhibition tasks. [3] The researchers hypothesize that enhanced cognitive inhibition capacities seen in gifted children's development may temporarily reduce creative performance during childhood.
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.
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
Building RAG with self-deployed Milvus vector database and Snowpark Container...Zilliz
This talk will give hands-on advice on building RAG applications with an open-source Milvus database deployed as a docker container. We will also introduce the integration of Milvus with Snowpark Container Services.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/building-and-scaling-ai-applications-with-the-nx-ai-manager-a-presentation-from-network-optix/
Robin van Emden, Senior Director of Data Science at Network Optix, presents the “Building and Scaling AI Applications with the Nx AI Manager,” tutorial at the May 2024 Embedded Vision Summit.
In this presentation, van Emden covers the basics of scaling edge AI solutions using the Nx tool kit. He emphasizes the process of developing AI models and deploying them globally. He also showcases the conversion of AI models and the creation of effective edge AI pipelines, with a focus on pre-processing, model conversion, selecting the appropriate inference engine for the target hardware and post-processing.
van Emden shows how Nx can simplify the developer’s life and facilitate a rapid transition from concept to production-ready applications.He provides valuable insights into developing scalable and efficient edge AI solutions, with a strong focus on practical implementation.
Introducing Milvus Lite: Easy-to-Install, Easy-to-Use vector database for you...Zilliz
Join us to introduce Milvus Lite, a vector database that can run on notebooks and laptops, share the same API with Milvus, and integrate with every popular GenAI framework. This webinar is perfect for developers seeking easy-to-use, well-integrated vector databases for their GenAI apps.
“An Outlook of the Ongoing and Future Relationship between Blockchain Technologies and Process-aware Information Systems.” Invited talk at the joint workshop on Blockchain for Information Systems (BC4IS) and Blockchain for Trusted Data Sharing (B4TDS), co-located with with the 36th International Conference on Advanced Information Systems Engineering (CAiSE), 3 June 2024, Limassol, Cyprus.
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slackshyamraj55
Discover the seamless integration of RPA (Robotic Process Automation), COMPOSER, and APM with AWS IDP enhanced with Slack notifications. Explore how these technologies converge to streamline workflows, optimize performance, and ensure secure access, all while leveraging the power of AWS IDP and real-time communication via Slack notifications.
DocValues aka. Column Stride Fields in Lucene 4.0 - By Willnauer Simonlucenerevolution
See conference video - http://www.lucidimagination.com/devzone/events/conferences/revolution/2011
Lucene 4.0 is on its way to deliver a tremendous amount of new features and improvements. Beside
Real-Time Search & Flexible Indexing DocValues aka. Column Stride Fields is one of the “next
generation” features. DocValues enable Lucene to efficiently store and retrieve type-safe Document
& Value pairs in a column stride fashion either entirely memory resident random access or disk
resident iterator based without the need to un-invert fields. Its final goal is to provide a
independently update-able per document storage for scoring, sorting or even filtering. This talk will
introduce the current state of development, implementation details, its features and how DocValues
have been integrated into Lucene’s Codec API for full extendability.
Lucene 4.0 is on its way to deliver a tremendous amount of new features and improvements. Beside Real-Time Search & Flexible Indexing DocValues aka. Column Stride Fields is one of the "next generation" features
Column Stride Fields, also known as DocValues, provide a native way in Lucene to store numeric or arbitrary values per document without requiring conversion or parsing. They allow for constant-time random access to these values. DocValues improve on alternatives like Stored Fields and FieldCache by using a dense column-based storage that is faster to load and uses less memory. The current implementation of DocValues is ready to be landed in Lucene core, providing a customizable and efficient way to store additional per-document values in Lucene.
Consistency Models in New Generation Databasesiammutex
The document discusses transaction and consistency models in databases as the database world changes. It covers the CAP theorem and how it is impossible to guarantee availability, consistency and partition tolerance simultaneously in an asynchronous distributed system. It then discusses various consistency models including eventual, monotonic read, and read your own writes (RYOW). Examples are provided of eventually consistent systems. The document also discusses Amazon Dynamo's consistency model and how MongoDB supports different consistency levels and strategies for handling transactions and writes in distributed systems.
The document discusses transaction and consistency models in databases as the database world changes. It covers the CAP theorem and how it is impossible to guarantee availability, consistency and partition tolerance simultaneously in an asynchronous distributed system. It then discusses various consistency models including eventual, monotonic read, and read your own writes (RYOW). Examples are provided of eventually consistent systems. The document also discusses Amazon Dynamo's consistency model and how MongoDB supports different consistency levels and strategies for handling multiple writers and network partitions.
Thoughts on Transaction and Consistency Modelsiammutex
The document discusses database transaction models and consistency in light of CAP theorem. It explains that RDBMS use ACID transactions while newer databases like NoSQL choose availability over consistency. Eventual consistency guarantees last write wins if no new updates. It discusses strategies for handling multiple writers like last write wins with vector clocks. MongoDB supports atomic operations on single documents and provides options for read and write scaling through replication and sharding.
This document discusses binding and scope in programming languages. It defines binding as the association between a name and the thing it names. Binding can occur at different times, such as language design time, implementation time, program writing time, compile time, link time, load time, and run time. The key concepts of static and dynamic scoping are introduced. Static scoping means bindings are determined by examining the program text, while dynamic scoping means bindings depend on runtime control flow. The document also discusses modules, classes, inheritance, polymorphism, operator overloading, and closures.
Realtime olap architecture in apache kylin 3.0Shi Shao Feng
1) Apache Kylin v3.0 introduces a new real-time OLAP architecture using long-running streaming jobs to provide low latency queries over streaming data.
2) The data flow uses streaming receivers to aggregate streaming events in memory and flush to local disk in real-time segments before uploading to remote storage.
3) The query flow scans local real-time segments for low latency before querying remote historical data, providing millisecond responses over trillions of rows.
The document describes a series of experiments that investigated the effect of memory load on processing performance. Specifically, it examined how increasing the number of items held in memory affected response times and accuracy on various processing tasks. The experiments varied the domain of the items held in memory (verbal vs spatial) and the type of concurrent processing task. The results showed that memory load had a larger detrimental effect on both processing accuracy and response times when items from different domains (verbal and spatial) had to be maintained together in working memory, compared to when items were from the same domain. This suggests maintaining cross-domain items in working memory is more cognitively demanding than single-domain items.
The document describes a series of experiments that investigated the effect of memory load on processing performance. Specifically, it examined how increasing the number of items held in memory affected response times and accuracy on various processing tasks. The experiments varied the domain of the items held in memory (verbal vs spatial) and the type of concurrent processing task. The results showed that memory load had a larger detrimental effect on both processing accuracy and response times when items from different domains (verbal and spatial) had to be maintained together in working memory, compared to when items were from the same domain. This suggests maintaining cross-domain items in working memory is more cognitively demanding than single-domain items.
This study examined working memory and cognitive inhibition in gifted children compared to non-gifted children. [1] The gifted children performed better on reasoning, verbal fluidity, and working memory tasks. [2] However, both groups performed similarly on divergent thinking and cognitive inhibition tasks. [3] The researchers hypothesize that enhanced cognitive inhibition capacities seen in gifted children's development may temporarily reduce creative performance during childhood.
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.
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
Building RAG with self-deployed Milvus vector database and Snowpark Container...Zilliz
This talk will give hands-on advice on building RAG applications with an open-source Milvus database deployed as a docker container. We will also introduce the integration of Milvus with Snowpark Container Services.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/building-and-scaling-ai-applications-with-the-nx-ai-manager-a-presentation-from-network-optix/
Robin van Emden, Senior Director of Data Science at Network Optix, presents the “Building and Scaling AI Applications with the Nx AI Manager,” tutorial at the May 2024 Embedded Vision Summit.
In this presentation, van Emden covers the basics of scaling edge AI solutions using the Nx tool kit. He emphasizes the process of developing AI models and deploying them globally. He also showcases the conversion of AI models and the creation of effective edge AI pipelines, with a focus on pre-processing, model conversion, selecting the appropriate inference engine for the target hardware and post-processing.
van Emden shows how Nx can simplify the developer’s life and facilitate a rapid transition from concept to production-ready applications.He provides valuable insights into developing scalable and efficient edge AI solutions, with a strong focus on practical implementation.
Introducing Milvus Lite: Easy-to-Install, Easy-to-Use vector database for you...Zilliz
Join us to introduce Milvus Lite, a vector database that can run on notebooks and laptops, share the same API with Milvus, and integrate with every popular GenAI framework. This webinar is perfect for developers seeking easy-to-use, well-integrated vector databases for their GenAI apps.
“An Outlook of the Ongoing and Future Relationship between Blockchain Technologies and Process-aware Information Systems.” Invited talk at the joint workshop on Blockchain for Information Systems (BC4IS) and Blockchain for Trusted Data Sharing (B4TDS), co-located with with the 36th International Conference on Advanced Information Systems Engineering (CAiSE), 3 June 2024, Limassol, Cyprus.
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slackshyamraj55
Discover the seamless integration of RPA (Robotic Process Automation), COMPOSER, and APM with AWS IDP enhanced with Slack notifications. Explore how these technologies converge to streamline workflows, optimize performance, and ensure secure access, all while leveraging the power of AWS IDP and real-time communication via Slack notifications.
Removing Uninteresting Bytes in Software FuzzingAftab Hussain
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
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.
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.
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?Speck&Tech
ABSTRACT: A prima vista, un mattoncino Lego e la backdoor XZ potrebbero avere in comune il fatto di essere entrambi blocchi di costruzione, o dipendenze di progetti creativi e software. La realtà è che un mattoncino Lego e il caso della backdoor XZ hanno molto di più di tutto ciò in comune.
Partecipate alla presentazione per immergervi in una storia di interoperabilità, standard e formati aperti, per poi discutere del ruolo importante che i contributori hanno in una comunità open source sostenibile.
BIO: Sostenitrice del software libero e dei formati standard e aperti. È stata un membro attivo dei progetti Fedora e openSUSE e ha co-fondato l'Associazione LibreItalia dove è stata coinvolta in diversi eventi, migrazioni e formazione relativi a LibreOffice. In precedenza ha lavorato a migrazioni e corsi di formazione su LibreOffice per diverse amministrazioni pubbliche e privati. Da gennaio 2020 lavora in SUSE come Software Release Engineer per Uyuni e SUSE Manager e quando non segue la sua passione per i computer e per Geeko coltiva la sua curiosità per l'astronomia (da cui deriva il suo nickname deneb_alpha).
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
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.
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:
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!
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.
Sudheer Mechineni, Head of Application Frameworks, Standard Chartered Bank
Discover how Standard Chartered Bank harnessed the power of Neo4j to transform complex data access challenges into a dynamic, scalable graph database solution. This keynote will cover their journey from initial adoption to deploying a fully automated, enterprise-grade causal cluster, highlighting key strategies for modelling organisational changes and ensuring robust disaster recovery. Learn how these innovations have not only enhanced Standard Chartered Bank’s data infrastructure but also positioned them as pioneers in the banking sector’s adoption of graph technology.
1. Do Working Memory Spans
Depend only on Time?
Valérie Camos
Pierre Barrouillet
Université de Bourgogne
LEAD - CNRS
2. Working Memory Span Tasks
They involve:
• Maintenance: items to be maintained and recalled
• Processing: some task, usually complex, such as reading
comprehension or problem solving
3. Working Memory Span Tasks
(6/3)+5=7? Operation span
(Turner & Engle, 1989)
Truck
(3+6)/3=2?
Deer
(8-6)x3=6?
Nail
Recall
4. Time-Based Resource-Sharing Model
The main proposals
Barrouillet, Bernardin, & Camos, JEP:G, 2004
1. Processing and maintenance require attention which is a limited resource (some
sharing is needed)
2. As soon as attention is switched away from the memory items, their activation
suffers from a time-related decay
3. Refreshing the decaying memory traces necessitates their retrieval through
attentional focusing (as proposed by Cowan, 1999)
4. When processing component requires retrievals from LTM, it should have the
most detrimental effect on concurrent maintenance
5. In this case, sharing attention is time based because a central bottleneck allows
only one retrieval at a time
6. Switching mechanism and decay
Possible reactivation
of memory traces CL
Truck R R R R Deer
CL
Truck R R R R Deer
CL
Truck R R R R Deer
7. Cognitive Load is
Duration of attentional capture
CL =
Total time allowed
The proportion of time during which a given activity captures attention
in such a way that the refreshment of memory traces is impeded.
8. A metric for Cognitive Load
In tasks involving retrievals from LTM
The number of retrievals n
Their difficulty a
(the time they occupy central processes)
The total time allowed to perform them T
aN
CL =
T
9. Cognitive Load
as defined by the Time-Based Resource-Sharing model
depends on
rate of processing rather than complexity
duration of the atomic steps of processing
nature of the processes involved
10. Cognitive Load
as defined by the Time-Based Resource-Sharing model
depends on
rate of processing rather than complexity
duration of the atomic steps of processing
nature of the processes involved
11. Rate of Processing
Manipulating the Number of Retrievals / Time ratio
The Reading Digit Span Task
R8
31 Read aloud the successive screens
64 and recall the letters
K7
25
49
L3
68
24
12. Rate of Processing
Manipulating the Number of Retrievals / Time ratio
Either 6 or 10 digits to be read
Constant duration of the interletter intervals (6 s)
4,5
4
3,5
3
2,5
2
1,5
1
0,5
0
6 Digits 10 Digits
13. Rate of Processing
Manipulating the Number of Retrievals / Time ratio
Fixed number of digits to be read
Either 600 or 1000 ms per digit
5
4,5
4
3,5
3
2,5
2
1,5
1
0,5
0
Slow Fast
1000 ms 600 ms
14. Rate of Processing
Manipulating the Number of Retrievals / Time ratio
Varying
the number of digits to be read
and the time allowed to read them
• Either 4, 8, or 12 digits during 6, 8, or 10 seconds
• 9 different values of the critical ratio (from 0.4 to 2)
15. Rate of Processing
6
5,5
5
4,5
4
Mean Span
3,5
3
2,5
R2 = .932
2
1,5
1
0 0,5 1 1,5 2 2,5
Number of retrievals / Time ratio
Barrouillet, Bernardin, & Camos, JEP:G, 2004
16. Rate of processing rather than complexity
Lépine, Bernardin, & Barrouillet, EJCP, 2005
In undergraduate students who remembered series of digits:
• Traditional Reading Span (self paced)
• Reading Letter Span (slow: 1200 ms per letter)
• Reading Letter Span (fast: 600 ms per letter)
17. Rate of processing rather than complexity
Lépine, Bernardin, & Barrouillet, EJCP, 2005
4,5
4
3,5
WM span
3
2,5
2
1,5
1
RS self-paced RLS slow RLS fast
Reading letters can have the same detrimental effect on spans as reading complex sentences !
18. Cognitive Load
as defined by the Time-Based Resource-Sharing model
depends on
rate of processing rather than complexity
duration of the atomic steps of processing
nature of the processes involved
19. Duration of the atomic steps of processing
Slower retrievals
Central processes occupied for a longer period
Higher CL
LOWER SPANS
20. Duration of the atomic steps of processing
A reading digit span with digits presented …
4 Four IV
442 ms 446 ms 625 ms
Reading digit spans should be lower when digits are presented in roman
Reading numbers (1 to 9) while maintaining letters
1 digit per second
21. Duration of the atomic steps of processing
4,5
4
*
WM span
3,5
3
2,5
2
4 Four IV
Slower retrievals occupy central processes for longer periods
and involve higher cognitive load.
22. Cognitive Load
as defined by the Time-Based Resource-Sharing model
depends on
rate of processing rather than complexity
duration of the atomic steps of processing
nature of the processes involved
23. Nature of the processes involved
Bernardin, Portrat, & Barrouillet, in press
Two different groups are presented with the same display
G 8 but perform different activities:
5
6
Location
Parity 1 2 “ Up, up, down, down”
“ Even, odd, even, odd …”
Retrievals from LTM required
3
Lower spans predicted
P
24. Nature of the processes involved
Bernardin, Portrat, & Barrouillet, in press
4,5
4
3,5
*
3
WM span
2,5
2
1,5
1
0,5
0
Location Parity
Retrievals from LTM more demanding than location judgments
25. Nature of the processes or time ???
Parity judgments involve lower spans but …
they probably take also longer !
26. Nature or duration of the processes involved?
WM spans as a function of the actual processing time within the interletter interval
4 7 2
T 9 K
Stimulus onset Response
Parity RT
Actual Processing Time = Σ RT
Location
27. Nature or duration of the processes involved?
Series of ascending length of 1 to 7 letters to be remembered (3 series of
each length)
Interletter intervals 6400 ms
Either 4, 6, or 8 stimuli to be processed in each interval
Responses by pressing keys
2 Tasks x 3 Rates = 6 groups of 16 adults
28. Spans as a function of the number of stimuli
and the nature of the task
6
Location
5.5
5
4.5
Mean span
4
3.5
3
2.5
2
4 6 8
Number of stimuli
29. Spans as a function of the number of stimuli
and the nature of the task
6
Location
5.5
Parity
5
4.5
Mean span
4
3.5
3
2.5
2
4 6 8
Number of stimuli
30. Actual duration of processing as a function of
the task and number of stimuli
4
3.5
3
Actual duration of processing
Location
2.5
2
1.5
1
0.5
0
4 6 8
Number of stimuli
31. Actual duration of processing as a function of
the task and number of stimuli
4
Parity
3.5
3
Actual duration of processing
Location
2.5
2
1.5
1
0.5
0
4 6 8
Number of stimuli
32. Nature or duration of the processes involved?
6.5
6
Observed location spans
5.5
Mean Span
5
4.5
4
3.5
3
1.5 2 2.5 3 3.5 4
Actual Interletter Processing Time (sec)
33. Nature or duration of the processes involved?
6.5
6
5.5
Mean Span
5
4.5
4
3.5
3
1.5 2 2.5 3 3.5 4
Actual Interletter Processing Time (sec)
34. Nature or duration of the processes involved?
6.5
6
Predicted span values for a
5.5 location task thatobserved
Parity spans would take
longer
Mean Span
5
4.5
4
3.5
3
1.5 2 2.5 3 3.5 4
Actual Interletter Processing Time (sec)
35. Nature or duration of the processes involved?
6.5
6
Mean location span
5.23
5.5
Mean parity span observed
Mean Span
5
4.48
4.5
Mean span predicted
4.34
4
3.5
3
1.5 2 2.5 3 3.5 4
Actual Interletter Processing Time (sec)
36. Nature or duration of the processes involved?
6.5
6
Mean location span
5.23
5.5
Mean parity span observed
Mean Span
5
4.48
4.5
Mean span predicted
4.34
4
3.5
3
1.5 2 2.5 3 3.5 4
Actual Interletter Processing Time (sec)
37. Tasks have no effect on spans beyond their duration
Do working memory spans depend only on time?
Working memory spans depend on the time
during which the processing component
captures attention
38. Thanks to
Sophie Bernardin
Raphaëlle Lépine
Nathalie Gavens
Sophie Portrat
LEAD - CNRS Université de Bourgogne
Editor's Notes
WM is a system devoted to the maintenance of relevant information during processing Thus WM span tasks usually involve these two activities with some memory items to be maintained while a concurrent processing must be performed
For example, in the well known Operation span, participants are asked to solve arithmetic equations while maintaining words to be recalled at the end of the series.
We recently proposed a model accounting for the cognitive processes involved in WM span tasks, the TBRS model. In its initial version, the TBRS model was based on five main proposals
Within this model, the main point is probably that resource sharing is achieved through a rapid switching between processing and maintenance that occurs during the processing component of the task.
We assume that the constraints on the switching process determines cognitive load. Suppose that your are performing a WM span task, and that you are successively presented with these two words. Unfortunately, you have to perform some intervening task during the interval. This task involves for example successive memory retrievals, during which the memory traces of the words decay, but you can keep free short slots to retrieve and refresh these traces. Let us suppose that this activity involves a moderate cognitive load. Now, if you are given more time to perform the same task, you have longer periods of time to reactivate memory traces. The WM task becomes easier because cognitive load decreases On the other hand, if the time is reduced, it becomes difficult to concurrently refresh memory traces. Cognitive load increases and WM span should decrease.
In this account, CL depends on the number and difficulty of retrievals because retrievals block attention for a portion of time. In other words CL is given by this equation the proportion of time during which attention is captured.
According to this analysis, the CL of the task we presented above depends on three parameters: the number of retrievals it requires, their difficulty, (some retrievals need more time than others), and the time allowed to perform them CL is given by the following equation, CL depends here on the Number of retrievals / Time ratio .
CL, and as a consequence WM spans, would thus depend on three main parameters Rate of processing rather than complexity of the processing component (lire) with long durations resulting in higher CL and lower spans (lire) Because we initially assumed that retrievals are more damaging than other activities
Let us recall what happens when the rate of processing is manipulated
We tested the hypothesis that CL is a matter of rate of processing using a very simple task, the reading digit span task letters to be remembered and digits to be read are successively presented on screen And subjects are asked to read them aloud and to recall the letters.
First we manipulated the number of retrievals while keeping time constant so, we presented either 6 or 10 digits Within constant interletter intervals of 6 s As we predicted, increasing the number of digits to be read had a detrimental effect on span
Then we manipulated the time allowed to perform an unchanged task We presented a constant number of digits That were presented either 600 or thousand ms Once more, there was a clear effect of pace. The faster the pace, the lower the span.
We verified the predictive value of the equation in a study in which we varied both the number of digits to be read and the time allowed to read them. (lire) (lire)
As we predicted, WM spans smoothly decreased as the CL of the reading digit task increased. and the regression line Nicely fitted these points
Our theory predicts that very simple tasks can have a highly detrimental effect on spans because complexity does not matter. What is important is pace. Actually, our experiments support this prediction. We compared three tasks in which undergraduate students had to recall digits: in the traditional RS, adults were asked to read and understand sentences Whereas in the reading letter span task, they were just asked to read successive letters presented at a slow Or fast pace And the reading digit span in which adults have just to read digits, a very simple activity.
The mean reading span was about 3 Not surprisingly, the reading letter span was higher and above 4 But when performed at a fast pace, the task became as difficult as the reading span task (lire)
Now the second point concerning the duration of processing steps
If our analysis is correct, the time a given activity blocks the central processes has a direct impact on the CL. For example slower retrievals occupy the central processes for longer periods of time, Thus involve a higher CL and then lower spans.
We compared three conditions of a reading digit span task in which numbers were presented either in their Arabic Verbal or Roman form. The corresponding Reading times are … wit the roman form that takes longer Thus we predicted lower spans when numbers are presented in their Roman form. Participants had to read numbers while maintaining letters At a rate of 1 digit per s.
As predicted by the reading times there was no big difference between spans when digits were presented in Arabic or Verbal form. but, the roman presentation, which takes longer to read resulted in lower spans. As predicted by the Time-based resource sharing model … (lire)
Our last point concerns the impact of nature of the processes
Remember that we predicted that among attention-demanding activities, the retrievals should have the most detrimental effect because retrievals are also needed to refresh decaying memory traces in STM. We designed a task … in which participants had to maintain letters and process numbers but in two different ways One group had to judge the parity of the number Whereas the other was just asked to judge their location on screen Our prediction was, all other thinks being equal, that the parity task would result in lower spans than the location task.
As we expected, an activity that requires retrievals from LTM is more disruptive than an activity that just requires response selection. Retrievals seem to be more demanding
But, what is the locus of the effect, the nature of the task or its duration
What is needed is a careful control of the actual processing time For example, using the same task We could measure the time taken to evaluate the parity of each number Or its location The actual processing time is the sum of these RTs
Thus we designed an experiment in which adults were asked to Maintain series of letters With interletter intervals of 6400 ms During which were presented either 4, 6, or 8 numbers for a parity or a location task The responses were given by pressing keys And we used 6 independent groups
As we already knew, the spans decreased when the number of stimuli increased
And the parity task resulted in lower spans
Concerning the actual duration of processing, of course it increased with the number of stimuli to process
Concerning the actual duration of processing, of course it increased with the number of stimuli to process
To answer the question, we have to analyse spans as a function of time. These are the actual processing times for the location span task And the resulting spans observed Would these spans differ from the parity spans if the two tasks involved the same durations? Remember that the parity judgments took longer
To answer the question, we have to analyse spans as a function of time. These are the actual processing times for the location span task And the resulting spans observed Would these spans differ from the parity spans if the two tasks involved the same durations? Remember that the parity judgments took longer
To answer the question, we have to analyse spans as a function of time. These are the actual processing times for the location span task And the resulting spans observed Would these spans differ from the parity spans if the two tasks involved the same durations? Remember that the parity judgments took longer
To answer the question, we have to analyse spans as a function of time. These are the actual processing times for the location span task And the resulting spans observed Would these spans differ from the parity spans if the two tasks involved the same durations? Remember that the parity judgments took longer
To answer the question, we have to analyse spans as a function of time. These are the actual processing times for the location span task And the resulting spans observed Would these spans differ from the parity spans if the two tasks involved the same durations? Remember that the parity judgments took longer
Thus there is no difference between tasks when durations were equated. Our question was And the answer is