Meta Programming with JavaScript

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The document discusses meta-programming with JavaScript and jQuery. It shows how jQuery simplifies DOM manipulation by providing methods that make it easier to select and modify elements. The document demonstrates using jQuery to change the color and display of a div element in fewer lines of code than vanilla JavaScript. It then shows an example of extending jQuery to create a domain-specific language for additional meta-programming capabilities.

Technology

Meta-Programming
with JavaScript
John Resig
Mozilla / jQuery

DOM + HTML
<html>
<head>
<script>
window.onload = function(){
var test = document.getElementById(“test”);
test.style.color = ‘green’;
test.style.display = ‘block’;
};
</script>
</head>
<body>
<div id=”test” style=”display:none;”>
You have JavaScript enabled!
</div>
</body>
</html>

A JS Library
HTML

jQuery DOM

JavaScript

jQuery
<html>
<head>
<script src=”jquery.js”></script>
<script>
$(function(){
$(“#test”).css(“color”,”green”).show();
});
</script>
</head>
<body>
<div id=”test” style=”display:none;”>
You have JavaScript enabled!
</div>
</body>
</html>

Meta Programming
HTML

Meta
jQuery DOM
Library

JavaScript

jQuery “2”
<html>
<head>
<script src=”jquery.js”></script>
<script src=”jquery2.js”></script>
<script type=”text/jquery”>
#test:
css “color” ”green”
show
</script>
</head>
<body>
<div id=”test” style=”display:none;”>
You have JavaScript enabled!
</div>
</body>
</html>

Demo
http://ejohn.org/apps/jquery2/

More Details

• http://jquery.com/
• http://ejohn.org/apps/jquery2/
• http://ejohn.org/blog/advancing-javascript-with-libraries/

• http://yuiblog.com/blog/2007/04/16/video-resig/

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Hi, I’m Aly Owens, I have a special pleasure to stand here as over a decade ago I graduated from CityU as an international student with an MBA program. I enjoyed the diversity of the school, ability to work and study, the network that came with being here, and of course the price tag for students here has always been more affordable than most around. Since then I have worked for major corporations like T-Mobile and Microsoft and many more, and I have founded a startup. I've also been teaching product management to ensure my students save time and money to get to the same level as me faster avoiding popular mistakes. Today as I’ve transitioned to teaching and focusing on the startup, I hear everybody being concerned about Ai stealing their jobs… We’ll talk about it shortly. But before that, I want to take you back to 1997. One of my favorite movies is “Fifth Element”. It wowed me with futuristic predictions when I was a kid and I’m impressed by the number of these predictions that have already come true. Self-driving cars, video calls and smart TV, personalized ads and identity scanning. Sci-fi movies and books gave us many ideas and some are being implemented as we speak. But we often get ahead of ourselves: Flying cars,Colonized planets, Human-like AI: not yet, Time travel, Mind-machine neural interfaces for everyone: Only in experimental stages (e.g. Neuralink). Cyberpunk dystopias: Some vibes (neon signs + inequality + surveillance), but not total dystopia (thankfully). On the bright side, we predict that the working hours should drop as Ai becomes our helper and there shouldn’t be a need to work 8 hours/day. Nobody knows for sure but we can require that from legislation. Instead of waiting to see what the government and billionaires come up with, I say we should design our own future. So, we as humans, when we don’t know something - fear takes over. The same thing happened during the industrial revolution. In the Industrial Era, machines didn’t steal jobs—they transformed them but people were scared about their jobs. The AI era is making similar changes except it feels like robots will take the center stage instead of a human. First off, even when it comes to the hottest space in the military - drones, Ai does a fraction of work. AI algorithms enable real-time decision-making, obstacle avoidance, and mission optimization making drones far more autonomous and capable than traditional remote-controlled aircraft. Key technologies include computer vision for object detection, GPS-enhanced navigation, and neural networks for learning and adaptation. But guess what? There are only 2 companies right now that utilize Ai in drones to make autonomous decisions - Skydio and DJI.

PyCon SG 25 - Firecracker Made Easy with Python.pdfMuhammad Yuga Nugraha

Explore the ease of managing Firecracker microVM with the firecracker-python. In this session, I will introduce the basics of Firecracker microVM and demonstrate how this custom SDK facilitates microVM operations easily. We will delve into the design and development process behind the SDK, providing a behind-the-scenes look at its creation and features. While traditional Firecracker SDKs were primarily available in Go, this module brings a simplicity of Python to the table.

Agentic AI for Developers and Data Scientists Build an AI Agent in 10 Lines o...All Things Open

Presented at All Things Open RTP Meetup Presented by William Hill - Developer Advocate, NVIDIA Title: Agentic AI for Developers and Data Scientists Build an AI Agent in 10 Lines of Code and the Concepts Behind the Code Abstract: In this talk we will demonstrate building a working data science AI agent in 10 lines of basic Python code in a Colab notebook. Our AI Agent will perform LLM prompt-driven visual analysis using open-source libraries. In this session we will show how to develop an AI Agent using GPUs through NVIDIA’s developer program and Google Colab notebooks. After coding our AI Agent, we will break down the 10 lines of code. We will show the key components and open source library integrations that enable the agent's functionality, focusing on practical implementation details and then the theoretical concepts. The presentation concludes with a survey of current LLM technologies and the latest trends in developing AI applications for enthusiasts and enterprises

Using the SQLExecutor for Data Quality Management: aka One man's love for the...Safe Software

The SQLExecutor is one of FME’s most powerful and flexible transformers. Pivvot maintains a robust internal metadata hierarchy used to support ingestion and curation of thousands of external data sources that must be managed for quality before entering our platform. By using the SQLExecutor, Pivvot can efficiently detect problems and perform analysis before data is extracted from our staging environment, removing the need for rollbacks or cycles waisted on a failed job. This presentation will walk through three distinct examples of how Pivvot uses the SQLExecutor to engage its metadata hierarchy and integrate with its Data Quality Management workflows efficiently and within the source postgres database. Spatial Validation –Validating spatial prerequisites before entering a production environment. Reference Data Validation - Dynamically validate domain-ed columns across any table and multiple columns per table. Practical De-duplication - Removing identical or near-identical well point locations from two distinct source datasets in the same table.

From Manual to Auto Searching- FME in the Driver's SeatSafe Software

Finding a specific car online can be a time-consuming task, especially when checking multiple dealer websites. A few years ago, I faced this exact problem while searching for a particular vehicle in New Zealand. The local classified platform, Trade Me (similar to eBay), wasn’t yielding any results, so I expanded my search to second-hand dealer sites—only to realise that periodically checking each one was going to be tedious. That’s when I noticed something interesting: many of these websites used the same platform to manage their inventories. Recognising this, I reverse-engineered the platform’s structure and built an FME workspace that automated the search process for me. By integrating API calls and setting up periodic checks, I received real-time email alerts when matching cars were listed. In this presentation, I’ll walk through how I used FME to save hours of manual searching by creating a custom car-finding automation system. While FME can’t buy a car for you—yet—it can certainly help you find the one you’re after!

The Growing Value and Application of FME & GenAISafe Software

With the cost of using Generative AI services dropping exponentially and the array of available models continually expanding, integrating AI into FME workflows has become inexpensive, accessible and effective. This presentation explores how GenAI within FME can cost-effectively transform data workflows by automating data extraction, validation, classification and augmentation tasks. We’ll discuss how FME’s no-code flexibility enables users to combine Generative AI and Computer Vision tools that create efficient workflows tailored to specific challenges. Using recent practical examples, we’ll demonstrate how these integrations can simplify complex tasks, save time and enhance data quality.

GenAI Opportunities and Challenges - Where 370 Enterprises Are Focusing Now.pdfPriyanka Aash

9-1-1 Addressing: End-to-End Automation Using FMESafe Software

This session will cover a common use case for local and state/provincial governments who create and/or maintain their 9-1-1 addressing data, particularly address points and road centerlines. In this session, you'll learn how FME has helped Shelby County 9-1-1 (TN) automate the 9-1-1 addressing process; including automatically assigning attributes from disparate sources, on-the-fly QAQC of said data, and reporting. The FME logic that this presentation will cover includes: Table joins using attributes and geometry, Looping in custom transformers, Working with lists and Change detection.

"Scaling in space and time with Temporal", Andriy Lupa.pdfFwdays

Design patterns like Event Sourcing and Event Streaming have long become standards for building real-time analytics systems. However, when the system load becomes nonlinear with fast and often unpredictable spikes, it's crucial to respond quickly in order not to lose real-time operating itself. In this talk, I’ll share my experience implementing and using a tool like Temporal.io. We'll explore the evolution of our system for maintaining real-time report generation and discuss how we use Temporal both for short-lived pipelines and long-running background tasks.

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Securing Account Lifecycles in the Age of Deepfakes.pptxFIDO Alliance

Techniques for Automatic Device Identification and Network Assignment.pdfPriyanka Aash

10 Key Challenges for AI within the EU Data Protection Framework.pdfPriyanka Aash

Cyber Defense Matrix Workshop - RSA ConferencePriyanka Aash