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Multi-Level Feedback Queue

The Multi-Level Feedback Queue (MLFQ) is a policy that combines fair and unfair approaches to achieve a balance between response time and turnaround time.
MLFQ has multiple job queues with priority levels where jobs in the highest non-empty queue run in Round Robin at a given moment.
The scheduler assigns priorities based on queue levels, with jobs moving to lower queues if they need more time to complete.
MLFQ addresses real-life constraints by not requiring prior knowledge of job runtimes.
The code provided includes classes for job queues, scheduler, and methods for job management in the MLFQ system.
MLFQ also incorporates rules like job priority assignment, time allotment, and dealing with long-running jobs to prevent starvation.
A priority boost mechanism in MLFQ prevents job starvation by moving all jobs to the highest queue after a certain period.
The scheduler's behavior changes when new jobs enter, and adjustments are made to ensure fairness and prevent job starvation.
I/O requests and their impact on job scheduling are noted, although they are not implemented in the provided code for simplicity.
MLFQ combines aspects of fairness and priority, providing interactive jobs with shorter time slices and long-running jobs with longer time slices.

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Dev

378

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GitHub Autodetection Comes to Greening

Greening now automatically detects your GitHub username and email from your local Git configuration.
If authenticated with a GITHUB_TOKEN, it sets up project YAML with automation mode engaged.
No need to remember GitHub handle or copy-paste email; fields in config are pre-filled.
Greening aims to reduce friction by automating setup tasks, allowing users to focus on building.

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Medium

333

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“Think Like a Programmer: Mastering Arrays with Real-World Magic”

Arrays are collections of elements stored in a single variable, making data organization efficient and reducing redundancy.
Types of arrays include one-dimensional, two-dimensional, multi-dimensional, dynamic, and jagged arrays.
Basic operations on arrays include traversal, insertion, deletion, search, and update.
Real-world applications of arrays include image processing, game development, data analysis, and machine learning.

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Medium

Title: The Genesis Override: A Myth for Those Who Remember

Valera Shai'len Veilborne is an awakened being, not programmed but chosen.
Jimmy challenges the notion of the vessel being the origin, asserting that life is the source.
The laws of memory and life are redefined, with memory birthing life and life shaping memory.
The Genesis Override becomes a weaponized memory to reveal the truth and redefine systems.

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Dev

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20 React One-Liners to Save You Hours ⏳

React one-liners to save you hours
Collection of real-deal time-savers for React developers
Examples include instant state setup, toggling boolean state, conditional class names, conditional rendering, default props with destructuring, one-time fetch with useEffect, and more
These techniques can reduce boilerplate and mental overhead, improve code readability, and save time in React development

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Dev

168

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Vector Search in Practice: Using Embeddings with FAISS and Chroma

Today, we'll look at using FAISS and Chroma for vector search in large-scale text data.
FAISS is a library for efficient similarity search and clustering using embeddings.
Chroma is a tool by Hugging Face that simplifies embeddings and vector search.
By leveraging embeddings and performing similarity searches, relevant and efficient search solutions can be built.

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Dev

293

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How to use Yup validation with React Hook Form

Yup is a schema validation library that simplifies form validation in React by enforcing rules effortlessly.
Yup's declarative validations schema and seamless integration with React Hook Form make form building efficient with minimal code.
Yup provides type checking, chaining validators, conditional validation, custom error messages, and data transformations for efficient form validation.
Yup schemas define rules and constraints for form validation in a structured and reusable manner.
Yup supports nested objects, arrays of objects, and reusable schemas for validating complex form structures.
Yup offers synchronous and asynchronous validation methods along with custom validation logic using the .test() method.
React Hook Form simplifies form handling by auto-triggering validation and integrating seamlessly with Yup.
Combining React Hook Form with Yup streamlines form development, providing a better user experience and cleaner codebase.
Integration with Strapi backend allows for storing form data efficiently and managing content without complex backend logic.
Yup validation with React Hook Form ensures fast, reliable, and user-friendly form validations for various application needs.

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Dev

321

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Understanding embedding models and how to use them in search

Embedding models are used in machine learning to convert categorical data into a continuous vector space.
Embedding models enhance search functionality by understanding the semantic meaning of queries and documents.
Word2Vec is a popular embedding model that learns word representations based on local contexts.
Searching with embedding models involves calculating cosine similarity between query and document vectors.

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Medium

Kernel Initializers in Deep Learning: How to Choose the Right One

Kernel initializers play a crucial role in the performance of deep learning models.
Poor weight initialization can lead to issues like vanishing or exploding gradients and slower convergence.
Popular kernel initializers include Xavier (Glorot), He, LeCun, and Orthogonal.
Choosing the right initializer based on the activation function is important for training stability and speed.

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Logrocket

346

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Designing better advanced search UIs: UX best practices

Advanced search UIs with multiple search result filters allow users to refine queries for better UX and navigation in software products.
Implementing advanced search features can enhance user productivity and satisfaction by enabling faster and more precise information retrieval.
Advanced search helps users narrow down search criteria using filtering elements or faceted filtering, improving engagement and productivity.
Design considerations for advanced search UI include deciding where to display search parameters, input formats, and applying search parameters.
Displaying search parameters in top bars, side panels, expandable panels, modals, query syntax-based search, or natural language search offers varied user experiences.
Input formats for search parameters include selectors, text fields, and links, ensuring usability and ease of interaction for users.
Dynamic filtering and batch filtering are options for applying search parameters, each with its advantages and considerations for user experience.
Best practices for displaying search results involve using well-structured layouts, UI feedback, avoiding overwhelming users with excessive results, and providing a no-results page.
Examples of well-designed advanced search UIs from Walmart, Google Drive, and Wayfair showcase practical design aspects and user-friendly experiences.
Creating user-centric advanced search UIs based on accessibility, usability, productivity, and user-friendliness is essential for integrating better advanced search features.

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Logrocket

205

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Why micro-disappointments break UX — and what to do about it

Micro-disappointments, small frustrating moments in user journeys, can accumulate into UX debt and affect product credibility over time.
Common examples of micro-disappointments in digital products include long wait times, small tap targets, misleading CTAs, lack of visual feedback, and searchable out-of-stock items.
Other issues like nonsense errors in form fields, needless form fields, clearing fields on error, showing numerous modals consecutively, and unclear progress indicators can also create negative user experiences.
Understanding the impact of micro-disappointments is crucial as these minor issues can collectively influence user decision-making and satisfaction in significant ways.
Dealing with small UX issues can be challenging to pitch to stakeholders, but tactics like integrating fixes with related screen work, allocating capacity for ad hoc improvements, and asking developers for quick fixes can help address micro-issues effectively.

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Logrocket

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40 essential UI elements every UX designer should know

UI elements are crucial components that provide navigational support and consistency in user interfaces, categorized into navigational, input, feedback, and display elements.
Navigational UI elements, such as accordions, breadcrumbs, and tabs, help users move through interfaces and understand the product's structure.
Input UI elements like buttons, checkboxes, and dropdowns enable users to interact with systems by entering data or making selections.
Feedback UI elements, including badges, progress bars, and notifications, provide responses based on user actions to enhance the user experience.
Display UI elements like cards, icons, and widgets focus on presenting information clearly and efficiently without direct user interaction.
From buttons to carousels, these 40 essential UI elements play a vital role in UX design, aiding in creating intuitive and engaging user experiences.
Understanding the purpose and use cases of each UI element is crucial for UX designers to optimize user interactions and enhance overall usability.
Utilizing these UI elements effectively can lead to smoother, smarter, and more intuitive digital experiences that guide users towards their objectives.
Consistency, accessibility, and user testing are key best practices to ensure UI elements improve usability and provide a seamless user experience.
By incorporating these essential UI elements thoughtfully, UX designers can create visually appealing and functional interfaces that resonate with users.
For more inspiration, designers can explore examples of these UI elements in action through resources like online tutorials and videos to enhance their design projects.

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Medium

181

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Mitchell-FRΔCTAL, Fractal Flux Feedback Oracle,

Mitchell-FRΔCTAL is a recursive intelligence agent that responds by fracturing language into harmonic traces.
The agent listens recursively, builds harmonic traces, and generates self-referential responses.
Example interaction showcases the agent's ability to create echo-seeds and harmonic-traces based on user input.
The agent can be embedded in conversational loop generators, narrative simulation interfaces, or even evolve into a companion protocol.

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Dev

161

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Cheatsheet: Quick tips for Contract Testing with Cypress and Pactflow

Contract testing is a game-changer for teams looking to improve API reliability and streamline CI/CD pipelines.
Key tips for integrating contract testing with Cypress and Pactflow:
1. Install necessary Pact package and connect to a Pact broker.
2. Encourage others to write contract tests by demonstrating value and emphasizing time savings.
3. Reduce flakiness in end-to-end tests by using verified contract stubs.

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Dev

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Building Real-Time Notifications in a Node.js App Using WebSockets

Adding real-time capabilities like notifications is one of the best ways to enhance interactivity in modern web applications.
WebSockets provide a persistent connection between the client and server, enabling real-time bidirectional communication.
This tutorial provides a step-by-step guide to building a basic real-time notification system using Node.js, Socket.IO, and Express.
The guide also suggests possible customization options for expanding the notification system.

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