ROI for testing
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This document discusses return on investment (ROI) and provides three examples of ROI calculations: 1) A software testing example that shows how finding and fixing bugs early can save significant costs later and provide a ROI of 350%. 2) An example of how investing $70,000 in testing upfront resulted in $315,000 of savings, providing a ROI of 350%. 3) A brief example comparing investing $40 upfront versus $50 later, highlighting the potential cost savings from earlier investment.
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FIDO Seminar: Perspectives on Passkeys & Consumer AdoptionImproving Data Integrity: Synchronization between EAM and ArcGIS Utility Netw...
Improving Data Integrity: Synchronization between EAM and ArcGIS Utility Netw...Safe Software
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Utilities and water companies play a key role in the creation of clean drinking water. The creation and maintenance of clean drinking water is becoming a critical problem due to pollution and pressure on the environment. A lot of data is necessary to create clean drinking water. For fieldworkers, two types of data are key: Asset data in an asset management system (EAM for example) and Geographic data in a GIS (ArcGIS Utility Network ). Keeping this type of data up to date and in sync is a challenge for many organizations, leading to duplicating data and creating a bulk of extra attributes and data to keep everything in sync. Using FME, it is possible to synchronize Enterprise Asset Management (EAM) data with the ArcGIS Utility Network in real time. Changes (creation, modification, deletion) in ArcGIS Pro are relayed to EAM via FME, and vice versa. This ensures continuous synchronization of both systems without daily bulk updates, minimizes risks, and seamlessly integrates with ArcGIS Utility Network services. This presentation focuses on the use of FME at a Dutch water company, to create a sync between the asset management and GIS.Smarter Aviation Data Management: Lessons from Swedavia Airports and Sweco
Smarter Aviation Data Management: Lessons from Swedavia Airports and SwecoSafe Software
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Managing airport and airspace data is no small task, especially when youre expected to deliver it in AIXM format without spending a fortune on specialized tools. But what if there was a smarter, more affordable way?
Join us for a behind-the-scenes look at how Sweco partnered with Swedavia, the Swedish airport operator, to solve this challenge using FME and Esri.
Learn how they built automated workflows to manage periodic updates, merge airspace data, and support data extracts all while meeting strict government reporting requirements to the Civil Aviation Administration of Sweden.
Even better? Swedavia built custom services and applications that use the FME Flow REST API to trigger jobs and retrieve results streamlining tasks like securing the quality of new surveyor data, creating permdelta and baseline representations in the AIS schema, and generating AIXM extracts from their AIS data.
To conclude, FME expert Dean Hintz will walk through a GeoBorders reading workflow and highlight recent enhancements to FMEs AIXM (Aeronautical Information Exchange Model) processing and interpretation capabilities.
Discover how airports like Swedavia are harnessing the power of FME to simplify aviation data management, and how you can too.Key Requirements to Successfully Implement Generative AI in Edge DevicesOpt...
Key Requirements to Successfully Implement Generative AI in Edge DevicesOpt...Edge AI and Vision Alliance
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For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2025/06/key-requirements-to-successfully-implement-generative-ai-in-edge-devices-optimized-mapping-to-the-enhanced-npx6-neural-processing-unit-ip-a-presentation-from-synopsys/
Gordon Cooper, Principal Product Manager at Synopsys, presents the Key Requirements to Successfully Implement Generative AI in Edge DevicesOptimized Mapping to the Enhanced NPX6 Neural Processing Unit IP tutorial at the May 2025 Embedded Vision Summit.
In this talk, Cooper discusses emerging trends in generative AI for edge devices and the key role of transformer-based neural networks. He reviews the distinct attributes of transformers, their advantages over conventional convolutional neural networks and how they enable generative AI.
Cooper then covers key requirements that must be met for neural processing units (NPU) to support transformers and generative AI in edge device applications. He uses transformer-based generative AI examples to illustrate the efficient mapping of these workloads onto the enhanced Synopsys ARC NPX NPU IP family.FIDO Seminar: Authentication for a Billion Consumers - Amazon.pptx
FIDO Seminar: Authentication for a Billion Consumers - Amazon.pptxFIDO Alliance
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FIDO Seminar: Authentication for a Billion Consumers - AmazonEnhance GitHub Copilot using MCP - Enterprise version.pdf
Enhance GitHub Copilot using MCP - Enterprise version.pdfNilesh Gule
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際際滷 deck related to the GitHub Copilot Bootcamp in Melbourne on 17 June 2025Wenn alles versagt - IBM Tape sch端tzt, was z辰hlt! Und besonders mit dem neust...
Wenn alles versagt - IBM Tape sch端tzt, was z辰hlt! Und besonders mit dem neust...Josef Weingand
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IBM LTO10June Patch Tuesday
June Patch TuesdayIvanti
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Ivantis Patch Tuesday breakdown goes beyond patching your applications and brings you the intelligence and guidance needed to prioritize where to focus your attention first. Catch early analysis on our Ivanti blog, then join industry expert Chris Goettl for the Patch Tuesday Webinar Event. There well do a deep dive into each of the bulletins and give guidance on the risks associated with the newly-identified vulnerabilities. OpenPOWER Foundation & Open-Source Core Innovations
OpenPOWER Foundation & Open-Source Core InnovationsIBM
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penPOWER offers a fully open, royalty-free CPU architecture for custom chip design.
It enables both lightweight FPGA cores (like Microwatt) and high-performance processors (like POWER10).
Developers have full access to source code, specs, and tools for end-to-end chip creation.
It supports AI, HPC, cloud, and embedded workloads with proven performance.
Backed by a global community, it fosters innovation, education, and collaboration.cnc-processing-centers-centateq-p-110-en.pdf
cnc-processing-centers-centateq-p-110-en.pdfAmirStern2
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廨 廣 廬廣廩廬 廣 3/4/5 廢廨, 廣 22 廚廬 廣 廚廩廨廬 廣 廨廩廬.油廣 廩 廣 廩 廡 廚廣 廩廚 廣廨廬/廨廖廬/廬/廖廚廨廬/廣廨廬 廣..
廖 廢廣 廚廣廬 廣 廩廬 廬廬 廣廚 廩: 廡 , 廚廡, 廖廨, 廨廖 .Key Requirements to Successfully Implement Generative AI in Edge DevicesOpt...
Key Requirements to Successfully Implement Generative AI in Edge DevicesOpt...Edge AI and Vision Alliance
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