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Facebook angelarosa
Facebook is a paper presented by Blanca Nieves Torres Rincón, a student at the Technical Educational Institution Lisandro Cely. The paper was presented on October 21, 2010 and focuses on the authorship of Facebook.
Initial Ideas PowerPoint
The document outlines plans for a student film project inspired by movies like Se7en and Sin City. It will follow three main characters: a killer dressed in a hooded jacket, and two detectives in suits. The killer will commit a murder caught on camera by Detective 2, calling Detective 1 to the crime scene at Burn Valley. Meanwhile, scenes will show the killer's strange actions at home before and after the murder, similar to Se7en. Props like guns, hats, suits, and a fake dead body are assigned to the three students to film their scenes at the killer's home and the crime scene.
Question7
Our preliminary task lacked planning and had poor quality, so for this task we conducted extensive research and planning in 10 areas. This included researching genre conventions and history to understand what makes a good film noir. We analyzed title sequences and screened films to inform our ideas and understand institutions. Audience research found fans of art and filmmaking would enjoy the genre. Finally, we created a pitch, call sheet, and storyboard with animatic to plan our improved film noir media product.
Faceboo1
Facebook is a paper presented by Blanca Nieves Torres Rincón, a student at the Technical Educational Institution Lisandro Cely. The paper was presented on October 21, 2010 and focuses on the authorship of Facebook.
Question 6
We learned a lot about using various technologies for our film project. Through filming our preliminary task, we learned how to properly use cameras and tripods. During editing, we used effects in iMovie to improve sound quality and resolve weaknesses from our camera equipment. We also changed to a different camera for the main task because the first camera had poor sound quality. While filming, we noticed unwanted noise from the tripod and worked to reduce it during editing. Overall, iMovie, GarageBand, a flash mic, blogger, and Photoshop were useful tools that we learned to use through experimenting with help from others. We are now more confident using these technologies.
Facebook angelarosa
Facebook is a paper presented by Blanca Nieves Torres Rincón, a student at the Technical Educational Institution Lisandro Cely. The paper was presented on October 21, 2010 and focuses on the authorship of Facebook.
Recommended
Facebook angelarosa
Facebook is a paper presented by Blanca Nieves Torres Rincón, a student at the Technical Educational Institution Lisandro Cely. The paper was presented on October 21, 2010 and focuses on the authorship of Facebook.
Initial Ideas PowerPoint
The document outlines plans for a student film project inspired by movies like Se7en and Sin City. It will follow three main characters: a killer dressed in a hooded jacket, and two detectives in suits. The killer will commit a murder caught on camera by Detective 2, calling Detective 1 to the crime scene at Burn Valley. Meanwhile, scenes will show the killer's strange actions at home before and after the murder, similar to Se7en. Props like guns, hats, suits, and a fake dead body are assigned to the three students to film their scenes at the killer's home and the crime scene.
Question7
Our preliminary task lacked planning and had poor quality, so for this task we conducted extensive research and planning in 10 areas. This included researching genre conventions and history to understand what makes a good film noir. We analyzed title sequences and screened films to inform our ideas and understand institutions. Audience research found fans of art and filmmaking would enjoy the genre. Finally, we created a pitch, call sheet, and storyboard with animatic to plan our improved film noir media product.
Faceboo1
Facebook is a paper presented by Blanca Nieves Torres Rincón, a student at the Technical Educational Institution Lisandro Cely. The paper was presented on October 21, 2010 and focuses on the authorship of Facebook.
Question 6
We learned a lot about using various technologies for our film project. Through filming our preliminary task, we learned how to properly use cameras and tripods. During editing, we used effects in iMovie to improve sound quality and resolve weaknesses from our camera equipment. We also changed to a different camera for the main task because the first camera had poor sound quality. While filming, we noticed unwanted noise from the tripod and worked to reduce it during editing. Overall, iMovie, GarageBand, a flash mic, blogger, and Photoshop were useful tools that we learned to use through experimenting with help from others. We are now more confident using these technologies.
Facebook angelarosa
Facebook is a paper presented by Blanca Nieves Torres Rincón, a student at the Technical Educational Institution Lisandro Cely. The paper was presented on October 21, 2010 and focuses on the authorship of Facebook.
Facebook angelarosa
Facebook is a paper presented by Blanca Nieves Torres Rincón, a student at the Technical Educational Institution Lisandro Cely. The paper was presented on October 21, 2010 and focuses on the authorship of Facebook.
Boa design lolly popbrazil
This document contains the repeated URL www.lollypopbrazil.com listed multiple times without any other text or context. The URL www.lollypopbrazil.com is mentioned 8 times throughout the document.
Node.js a-deep-dive 2-final
The document discusses the benefits of exercise for mental health. Regular physical activity can help reduce anxiety and depression and improve mood and cognitive functioning. Exercise has also been shown to boost self-esteem and can serve as a healthy way to manage stress.
Cognitive load theory
1. Cognitive load theory examines how instruction can affect the cognitive processes of learning and memory. It recognizes that working memory has limited capacity and looks to reduce extraneous cognitive load and manage intrinsic load.
2. Key aspects of cognitive load theory include the structure of working memory and long-term memory. Working memory can only hold a limited number of elements at once, around 7 plus or minus 2. Instruction should avoid splitting a learner's attention across multiple sources.
3. Cognitive load has three components - intrinsic, extraneous, and germane. Well-designed instruction reduces extraneous load and manages intrinsic load to promote germane cognitive load that supports learning and schema acquisition.
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Node is fundamentally different from the other technologies frequently used in big teams.
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AppSec PNW: Android and iOS Application Security with MobSF
Mobile Security Framework - MobSF is a free and open source automated mobile application security testing environment designed to help security engineers, researchers, developers, and penetration testers to identify security vulnerabilities, malicious behaviours and privacy concerns in mobile applications using static and dynamic analysis. It supports all the popular mobile application binaries and source code formats built for Android and iOS devices. In addition to automated security assessment, it also offers an interactive testing environment to build and execute scenario based test/fuzz cases against the application.
This talk covers:
Using MobSF for static analysis of mobile applications.
Interactive dynamic security assessment of Android and iOS applications.
Solving Mobile app CTF challenges.
Reverse engineering and runtime analysis of Mobile malware.
How to shift left and integrate MobSF/mobsfscan SAST and DAST in your build pipeline.
"$10 thousand per minute of downtime: architecture, queues, streaming and fin...
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As part of the talk, we will consider the architectural strategies necessary for the development of highly loaded fintech solutions. We will focus on using queues and streaming to efficiently work and manage large amounts of data in real-time and to minimize latency.
We will focus special attention on the architectural patterns used in the design of the fintech system, microservices and event-driven architecture, which ensure scalability, fault tolerance, and consistency of the entire system.
A Deep Dive into ScyllaDB's Architecture
This talk will cover ScyllaDB Architecture from the cluster-level view and zoom in on data distribution and internal node architecture. In the process, we will learn the secret sauce used to get ScyllaDB's high availability and superior performance. We will also touch on the upcoming changes to ScyllaDB architecture, moving to strongly consistent metadata and tablets.
“Temporal Event Neural Networks: A More Efficient Alternative to the Transfor...
“Temporal Event Neural Networks: A More Efficient Alternative to the Transfor...Edge AI and Vision Alliance
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Chris Jones, Director of Product Management at BrainChip , presents the “Temporal Event Neural Networks: A More Efficient Alternative to the Transformer” tutorial at the May 2024 Embedded Vision Summit.
The expansion of AI services necessitates enhanced computational capabilities on edge devices. Temporal Event Neural Networks (TENNs), developed by BrainChip, represent a novel and highly efficient state-space network. TENNs demonstrate exceptional proficiency in handling multi-dimensional streaming data, facilitating advancements in object detection, action recognition, speech enhancement and language model/sequence generation. Through the utilization of polynomial-based continuous convolutions, TENNs streamline models, expedite training processes and significantly diminish memory requirements, achieving notable reductions of up to 50x in parameters and 5,000x in energy consumption compared to prevailing methodologies like transformers.
Integration with BrainChip’s Akida neuromorphic hardware IP further enhances TENNs’ capabilities, enabling the realization of highly capable, portable and passively cooled edge devices. This presentation delves into the technical innovations underlying TENNs, presents real-world benchmarks, and elucidates how this cutting-edge approach is positioned to revolutionize edge AI across diverse applications.Mutation Testing for Task-Oriented Chatbots
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To fill this gap, we propose adapting mutation testing (MuT) for task-oriented chatbots. To this end, we introduce a set of mutation operators that emulate faults in chatbot designs, an architecture that enables MuT on chatbots built using heterogeneous technologies, and a practical realisation as an Eclipse plugin. Moreover, we evaluate the applicability, effectiveness and efficiency of our approach on open-source chatbots, with promising results.
"NATO Hackathon Winner: AI-Powered Drug Search", Taras Kloba
This is a session that details how PostgreSQL's features and Azure AI Services can be effectively used to significantly enhance the search functionality in any application.
In this session, we'll share insights on how we used PostgreSQL to facilitate precise searches across multiple fields in our mobile application. The techniques include using LIKE and ILIKE operators and integrating a trigram-based search to handle potential misspellings, thereby increasing the search accuracy.
We'll also discuss how the azure_ai extension on PostgreSQL databases in Azure and Azure AI Services were utilized to create vectors from user input, a feature beneficial when users wish to find specific items based on text prompts. While our application's case study involves a drug search, the techniques and principles shared in this session can be adapted to improve search functionality in a wide range of applications. Join us to learn how PostgreSQL and Azure AI can be harnessed to enhance your application's search capability.
Dandelion Hashtable: beyond billion requests per second on a commodity server
This slide deck presents DLHT, a concurrent in-memory hashtable. Despite efforts to optimize hashtables, that go as far as sacrificing core functionality, state-of-the-art designs still incur multiple memory accesses per request and block request processing in three cases. First, most hashtables block while waiting for data to be retrieved from memory. Second, open-addressing designs, which represent the current state-of-the-art, either cannot free index slots on deletes or must block all requests to do so. Third, index resizes block every request until all objects are copied to the new index. Defying folklore wisdom, DLHT forgoes open-addressing and adopts a fully-featured and memory-aware closed-addressing design based on bounded cache-line-chaining. This design offers lock-free index operations and deletes that free slots instantly, (2) completes most requests with a single memory access, (3) utilizes software prefetching to hide memory latencies, and (4) employs a novel non-blocking and parallel resizing. In a commodity server and a memory-resident workload, DLHT surpasses 1.6B requests per second and provides 3.5x (12x) the throughput of the state-of-the-art closed-addressing (open-addressing) resizable hashtable on Gets (Deletes).
From Natural Language to Structured Solr Queries using LLMs
This talk draws on experimentation to enable AI applications with Solr. One important use case is to use AI for better accessibility and discoverability of the data: while User eXperience techniques, lexical search improvements, and data harmonization can take organizations to a good level of accessibility, a structural (or “cognitive” gap) remains between the data user needs and the data producer constraints.
That is where AI – and most importantly, Natural Language Processing and Large Language Model techniques – could make a difference. This natural language, conversational engine could facilitate access and usage of the data leveraging the semantics of any data source.
The objective of the presentation is to propose a technical approach and a way forward to achieve this goal.
The key concept is to enable users to express their search queries in natural language, which the LLM then enriches, interprets, and translates into structured queries based on the Solr index’s metadata.
This approach leverages the LLM’s ability to understand the nuances of natural language and the structure of documents within Apache Solr.
The LLM acts as an intermediary agent, offering a transparent experience to users automatically and potentially uncovering relevant documents that conventional search methods might overlook. The presentation will include the results of this experimental work, lessons learned, best practices, and the scope of future work that should improve the approach and make it production-ready.
Demystifying Knowledge Management through Storytelling
The Department of Veteran Affairs (VA) invited Taylor Paschal, Knowledge & Information Management Consultant at Enterprise Knowledge, to speak at a Knowledge Management Lunch and Learn hosted on June 12, 2024. All Office of Administration staff were invited to attend and received professional development credit for participating in the voluntary event.
The objectives of the Lunch and Learn presentation were to:
- Review what KM ‘is’ and ‘isn’t’
- Understand the value of KM and the benefits of engaging
- Define and reflect on your “what’s in it for me?”
- Share actionable ways you can participate in Knowledge - - Capture & Transfer
How to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdf
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1. Cognitive load theory examines how instruction can affect the cognitive processes of learning and memory. It recognizes that working memory has limited capacity and looks to reduce extraneous cognitive load and manage intrinsic load.
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This slide deck presents DLHT, a concurrent in-memory hashtable. Despite efforts to optimize hashtables, that go as far as sacrificing core functionality, state-of-the-art designs still incur multiple memory accesses per request and block request processing in three cases. First, most hashtables block while waiting for data to be retrieved from memory. Second, open-addressing designs, which represent the current state-of-the-art, either cannot free index slots on deletes or must block all requests to do so. Third, index resizes block every request until all objects are copied to the new index. Defying folklore wisdom, DLHT forgoes open-addressing and adopts a fully-featured and memory-aware closed-addressing design based on bounded cache-line-chaining. This design offers lock-free index operations and deletes that free slots instantly, (2) completes most requests with a single memory access, (3) utilizes software prefetching to hide memory latencies, and (4) employs a novel non-blocking and parallel resizing. In a commodity server and a memory-resident workload, DLHT surpasses 1.6B requests per second and provides 3.5x (12x) the throughput of the state-of-the-art closed-addressing (open-addressing) resizable hashtable on Gets (Deletes).
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This approach leverages the LLM’s ability to understand the nuances of natural language and the structure of documents within Apache Solr.
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- Understand the value of KM and the benefits of engaging
- Define and reflect on your “what’s in it for me?”
- Share actionable ways you can participate in Knowledge - - Capture & Transfer
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