Oracle fusion financial p2p cycle
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Adobe After Effects is a software application used for creating motion graphics, special effects, and video compositing. It's widely used in TV and film post-production, as well as for creating visuals for online content, presentations, and more. While it can be used to create basic animations and designs, its primary strength lies in adding visual effects and motion to videos and graphics after they have been edited.
Here's a more detailed breakdown:
Motion Graphics:
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After Effects is powerful for creating animated titles, transitions, and other visual elements to enhance the look of videos and presentations.
Visual Effects:
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It's used extensively in film and television for creating special effects like green screen compositing, object manipulation, and other visual enhancements.
Video Compositing:
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After Effects allows users to combine multiple video clips, images, and graphics to create a final, cohesive visual.
Animation:
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It uses keyframes to create smooth, animated sequences, allowing for precise control over the movement and appearance of objects.
Integration with Adobe Creative Cloud:
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After Effects is part of the Adobe Creative Cloud, a suite of software that includes other popular applications like Photoshop and Premiere Pro.
Post-Production Tool:
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After Effects is primarily used in the post-production phase, meaning it's used to enhance the visuals after the initial editing of footage has been completed.
Adobe Marketo Engage Champion Deep Dive - SFDC CRM Synch V2 & Usage Dashboards
Adobe Marketo Engage Champion Deep Dive - SFDC CRM Synch V2 & Usage DashboardsBradBedford3 Join Ajay Sarpal and Miray Vu to learn about key Marketo Engage enhancements. Discover improved in-app Salesforce CRM connector statistics for easy monitoring of sync health and throughput. Explore new Salesforce CRM Synch Dashboards providing up-to-date insights into weekly activity usage, thresholds, and limits with drill-down capabilities. Learn about proactive notifications for both Salesforce CRM sync and product usage overages. Get an update on improved Salesforce CRM synch scale and reliability coming in Q2 2025.
Key Takeaways:
Improved Salesforce CRM User Experience: Learn how self-service visibility enhances satisfaction.
Utilize Salesforce CRM Synch Dashboards: Explore real-time weekly activity data.
Monitor Performance Against Limits: See threshold limits for each product level.
Get Usage Over-Limit Alerts: Receive notifications for exceeding thresholds.
Learn About Improved Salesforce CRM Scale: Understand upcoming cloud-based incremental sync.
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Revolutionizing Residential Wi-Fi PPT.pptx
Revolutionizing Residential Wi-Fi PPT.pptxnidhisingh691197 Discover why Wi-Fi 7 is set to transform wireless networking and how Router Architects is leading the way with next-gen router designs built for speed, reliability, and innovation.
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How Valletta helped healthcare SaaS to transform QA and compliance to grow wi...Egor Kaleynik This case study explores how we partnered with a mid-sized U.S. healthcare SaaS provider to help them scale from a successful pilot phase to supporting over 10,000 users—while meeting strict HIPAA compliance requirements.
Faced with slow, manual testing cycles, frequent regression bugs, and looming audit risks, their growth was at risk. Their existing QA processes couldn’t keep up with the complexity of real-time biometric data handling, and earlier automation attempts had failed due to unreliable tools and fragmented workflows.
We stepped in to deliver a full QA and DevOps transformation. Our team replaced their fragile legacy tests with Testim’s self-healing automation, integrated Postman and OWASP ZAP into Jenkins pipelines for continuous API and security validation, and leveraged AWS Device Farm for real-device, region-specific compliance testing. Custom deployment scripts gave them control over rollouts without relying on heavy CI/CD infrastructure.
The result? Test cycle times were reduced from 3 days to just 8 hours, regression bugs dropped by 40%, and they passed their first HIPAA audit without issue—unlocking faster contract signings and enabling them to expand confidently. More than just a technical upgrade, this project embedded compliance into every phase of development, proving that SaaS providers in regulated industries can scale fast and stay secure.
Requirements in Engineering AI- Enabled Systems: Open Problems and Safe AI Sy...
Requirements in Engineering AI- Enabled Systems: Open Problems and Safe AI Sy...Lionel Briand Keynote at RAISE workshop, ICSE 2025
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How to Batch Export Lotus Notes NSF Emails to Outlook PST Easily?
How to Batch Export Lotus Notes NSF Emails to Outlook PST Easily?steaveroggers Migrating from Lotus Notes to Outlook can be a complex and time-consuming task, especially when dealing with large volumes of NSF emails. This presentation provides a complete guide on how to batch export Lotus Notes NSF emails to Outlook PST format quickly and securely. It highlights the challenges of manual methods, the benefits of using an automated tool, and introduces eSoftTools NSF to PST Converter Software — a reliable solution designed to handle bulk email migrations efficiently. Learn about the software’s key features, step-by-step export process, system requirements, and how it ensures 100% data accuracy and folder structure preservation during migration. Make your email transition smoother, safer, and faster with the right approach.
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What Do Contribution Guidelines Say About Software Testing? (MSR 2025)
What Do Contribution Guidelines Say About Software Testing? (MSR 2025)Andre Hora Software testing plays a crucial role in the contribution process of open-source projects. For example, contributions introducing new features are expected to include tests, and contributions with tests are more likely to be accepted. Although most real-world projects require contributors to write tests, the specific testing practices communicated to contributors remain unclear. In this paper, we present an empirical study to understand better how software testing is approached in contribution guidelines. We analyze the guidelines of 200 Python and JavaScript open-source software projects. We find that 78% of the projects include some form of test documentation for contributors. Test documentation is located in multiple sources, including CONTRIBUTING files (58%), external documentation (24%), and README files (8%). Furthermore, test documentation commonly explains how to run tests (83.5%), but less often provides guidance on how to write tests (37%). It frequently covers unit tests (71%), but rarely addresses integration (20.5%) and end-to-end tests (15.5%). Other key testing aspects are also less frequently discussed: test coverage (25.5%) and mocking (9.5%). We conclude by discussing implications and future research.
Landscape of Requirements Engineering for/by AI through Literature Review
Landscape of Requirements Engineering for/by AI through Literature ReviewHironori Washizaki Hironori Washizaki, "Landscape of Requirements Engineering for/by AI through Literature Review," RAISE 2025: Workshop on Requirements engineering for AI-powered SoftwarE, 2025.
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Top 10 Client Portal Software Solutions for 2025.docxPortli Discover the top 10 client portal software solutions for 2025. Streamline communication, ensure security, and enhance client experience.
Not So Common Memory Leaks in Java Webinar
Not So Common Memory Leaks in Java WebinarTier1 app This SlideShare presentation is from our May webinar, “Not So Common Memory Leaks & How to Fix Them?”, where we explored lesser-known memory leak patterns in Java applications. Unlike typical leaks, subtle issues such as thread local misuse, inner class references, uncached collections, and misbehaving frameworks often go undetected and gradually degrade performance. This deck provides in-depth insights into identifying these hidden leaks using advanced heap analysis and profiling techniques, along with real-world case studies and practical solutions. Ideal for developers and performance engineers aiming to deepen their understanding of Java memory management and improve application stability.
Explaining GitHub Actions Failures with Large Language Models Challenges, In...
Explaining GitHub Actions Failures with Large Language Models Challenges, In...ssuserb14185 GitHub Actions (GA) has become the de facto tool that developers use to automate software workflows, seamlessly building, testing, and deploying code. Yet when GA fails, it disrupts development, causing delays and driving up costs. Diagnosing failures becomes especially challenging because error logs are often long, complex and unstructured. Given these difficulties, this study explores the potential of large language models (LLMs) to generate correct, clear, concise, and actionable contextual descriptions (or summaries) for GA failures, focusing on developers’ perceptions of their feasibility and usefulness. Our results show that over 80% of developers rated LLM explanations positively in terms of correctness for simpler/small logs. Overall, our findings suggest that LLMs can feasibly assist developers in understanding common GA errors, thus, potentially reducing manual analysis. However, we also found that improved reasoning abilities are needed to support more complex CI/CD scenarios. For instance, less experienced developers tend to be more positive on the described context, while seasoned developers prefer concise summaries. Overall, our work offers key insights for researchers enhancing LLM reasoning, particularly in adapting explanations to user expertise.
https://arxiv.org/abs/2501.16495
Designing AI-Powered APIs on Azure: Best Practices& Considerations
Designing AI-Powered APIs on Azure: Best Practices& ConsiderationsDinusha Kumarasiri AI is transforming APIs, enabling smarter automation, enhanced decision-making, and seamless integrations. This presentation explores key design principles for AI-infused APIs on Azure, covering performance optimization, security best practices, scalability strategies, and responsible AI governance. Learn how to leverage Azure API Management, machine learning models, and cloud-native architectures to build robust, efficient, and intelligent API solutions
Exceptional Behaviors: How Frequently Are They Tested? (AST 2025)
Exceptional Behaviors: How Frequently Are They Tested? (AST 2025)Andre Hora Exceptions allow developers to handle error cases expected to occur infrequently. Ideally, good test suites should test both normal and exceptional behaviors to catch more bugs and avoid regressions. While current research analyzes exceptions that propagate to tests, it does not explore other exceptions that do not reach the tests. In this paper, we provide an empirical study to explore how frequently exceptional behaviors are tested in real-world systems. We consider both exceptions that propagate to tests and the ones that do not reach the tests. For this purpose, we run an instrumented version of test suites, monitor their execution, and collect information about the exceptions raised at runtime. We analyze the test suites of 25 Python systems, covering 5,372 executed methods, 17.9M calls, and 1.4M raised exceptions. We find that 21.4% of the executed methods do raise exceptions at runtime. In methods that raise exceptions, on the median, 1 in 10 calls exercise exceptional behaviors. Close to 80% of the methods that raise exceptions do so infrequently, but about 20% raise exceptions more frequently. Finally, we provide implications for researchers and practitioners. We suggest developing novel tools to support exercising exceptional behaviors and refactoring expensive try/except blocks. We also call attention to the fact that exception-raising behaviors are not necessarily “abnormal” or rare.
Secure Test Infrastructure: The Backbone of Trustworthy Software Development
Secure Test Infrastructure: The Backbone of Trustworthy Software DevelopmentShubham Joshi A secure test infrastructure ensures that the testing process doesn’t become a gateway for vulnerabilities. By protecting test environments, data, and access points, organizations can confidently develop and deploy software without compromising user privacy or system integrity.
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