#embedded software project

[emblogicsblog]

Embedded Systems Software Engineering Course

Embedded systems are at the heart of modern technology, powering devices ranging from smartphones to industrial machines. If you're a BE or B. Tech students looking to master this fascinating field, an Embedded Systems Software Engineering Course is the perfect choice. This course equips you with the knowledge and practical skills to design, develop, and deploy embedded software solutions.

Training in embedded systems focuses on the integration of hardware and software to create efficient, reliable systems. In locations such as Noida, Texas, Cambridge, Chicago, Sydney, Perth, Tampa, Brisbane, Melbourne, New York, Quebec, British Columbia, Ontario, Calgary, Alberta, and Yorkshire, these courses are tailored to meet the needs of students and professionals aiming to excel in embedded software development.

What You’ll Learn:

Basics of embedded systems architecture.

Programming with C and C++ for microcontrollers.

Real-time operating systems (RTOS) and their applications.

Debugging, testing, and deploying embedded software.

Hands-on experience with project development.

Practical Project Training

The best way to learn embedded software is through hands-on practice. Courses include real-world projects like developing IoT devices, robotics systems, and automotive controls. These projects give you a deep understanding of embedded systems and boost your confidence to work on advanced applications.

Global Opportunities

Embedded systems professionals are in demand worldwide. Whether you're in Cambridge, Chicago, or Sydney, training in this field opens doors to exciting job roles in industries like automotive, healthcare, and consumer electronics.

Embark on your journey in embedded systems software engineering today, and pave the way for a rewarding career in cutting-edge technology!

embedded software project, Embedded systems software engineering, embedded software training, embedded software course, embedded software noida, Texas, Cambridge, Chicago, Sydney, Perth, Tampa, Brisbane, Melbourne, embedded Cambridge, New York, Quebec, British Colombia, Ontario, Calgary, Alberta, Yorkshire.

[learnandgrowcommunity]

Use this trick to Save time : HDL Simulation through defining clock

Why is this trick useful? Defining a clock in your simulation can save you time during simulation because you don't have to manually generate the clock signal in your simulation environment. Wanted to know how to define and force clock to simulate your digital system. Normally define clock used to simulate system with clock input. But I am telling you this trick for giving values to input ports other than clock. It will help you to save time in simulation because you do not need to force values to input ports every time. Lets brief What we did - gave some clock frequency to input A, like we gave 100. Than we made Half the frequency of clock to 50 and gave it to Input B. In similar way if we have 3rd input too we goanna half the frequency again to 25 and would give to next input.

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[blockverse-infotech]

IoT Development; A Complete Guide, on Bringing Devices from Idea to Implementation

In todays paced tech world, the Internet of Things (IoT) has emerged as a game changer transforming the way we engage with our environment. At Blockverse Infotech Solutions we recognize the power of devices providing customized solutions to bring ideas to life and seamlessly integrate them into the digital realm.

The Internet of Things (IoT) has evolved from a buzzword to an aspect of contemporary technology influencing various facets of our everyday routines. From homes and wearable gadgets to automation and healthcare systems IoT enables us to connect and empower ourselves like never before. However transitioning from conceptualization to implementation of solutions can be overwhelming without guidance.

Conceptualization marks the phase, in IoT development. It entails identifying the problem or opportunity that can be addressed through technology and envisioning how interconnected devices can improve efficiency, convenience or safety. At Blockverse Infotech Solutions we work closely with clients to brainstorm ideas grasp their needs and devise IoT solutions tailored specifically for them.

Once the concept is solidified, the development phase begins. This involves designing and prototyping IoT devices, selecting appropriate sensors and connectivity protocols, and developing the software infrastructure to collect, analyze, and act upon data generated by the devices. Our team of skilled developers and engineers at Blockverse Infotech Solutions leverages cutting-edge technologies to build robust and scalable IoT solutions that meet the highest standards of performance and reliability.

Testing and validation are integral parts of the development process, ensuring that IoT devices function as intended and deliver the desired outcomes. Through rigorous testing procedures and simulation environments, we identify and rectify any issues or vulnerabilities, ensuring that the deployed IoT solutions operate seamlessly in real-world scenarios.

Deployment marks the culmination of the IoT development journey, as the solutions are implemented and integrated into existing systems or environments. From device provisioning and network configuration to data management and security protocols, our experts at Blockverse Infotech Solutions handle every aspect of the deployment process with precision and care, ensuring a smooth transition from development to operation.

Post-deployment support and maintenance are essential for ensuring the long-term success and sustainability of IoT solutions. At Blockverse Infotech Solutions, we offer comprehensive support services, including monitoring, troubleshooting, and software updates, to keep IoT devices running smoothly and efficiently.

In conclusion, navigating the complex landscape of IoT development requires expertise, innovation, and a comprehensive understanding of the technology. With Blockverse Infotech Solutions providing tailored solutions for IoT devices, businesses and organizations can embark on their IoT journey with confidence, knowing that they have a trusted partner to guide them from concept to deployment and beyond.

[iiesbangalore]

Embedded Systems Course For Beginners

Embedded systems have permeated nearly every aspect of modern technology. From the smartphones we use to the cars we drive, embedded systems are responsible for powering many of the devices we rely on daily. If you're looking to gain an understanding of embedded course in Bangalore and how to work with them, you might want to consider taking a beginner's course at the Indian Institute of Embedded Systems (IIES).

Introduction

Embedded systems are integrated computer systems designed to perform specific tasks without human intervention. They are widely used in industries such as automotive, healthcare, home automation, and more, and are becoming increasingly popular as the Internet of Things (IoT) continues to grow. A beginner's course at IIES is an excellent way to get started with embedded systems and learn about the fundamental concepts, tools, and techniques used in the industry.

Why Take a Beginner's Course on Embedded Systems?

Taking a beginner's course on embedded systems has several benefits, including:

Understanding the Fundamentals

A beginner's course at IIES can help you understand the foundational concepts of embedded systems, including hardware and software components, communication protocols, and programming languages commonly used in the industry.

Developing Practical Skills

The course is designed to provide a hands-on approach to learning, allowing you to work with real-world hardware and software platforms, including the Arduino and Raspberry Pi. This practical experience will give you the confidence and skills you need to build embedded systems on your own.

Career Opportunities

As the use of embedded systems continues to grow, so does the demand for professionals in the field. Completing a beginner's course at IIES can open the door to a wide range of career opportunities, including embedded system engineer, IoT developer, and more.

Course Curriculum

The beginner's course offered at IIES covers a comprehensive range of topics, including:

Introduction to Embedded Systems

This section provides a comprehensive overview of embedded systems. It covers the basics of hardware and software components, communication protocols, and programming languages.

Microcontrollers and Microprocessors

Learn about the various microcontrollers and microprocessors used in the industry, including AVR, ARM, and PIC microcontrollers.

Programming Languages

Gain an understanding of the programming languages used in embedded systems development, including C and Python in embedded system.

Real-time Operating Systems

This section covers the basics of real-time operating systems, including scheduling algorithms, task management, and inter-task communication.

Hardware Interfacing and Peripheral Control

Learn how to interface with various hardware components, such as sensors, motors, and displays, and control them using programming languages and microcontrollers.

Projects and Workshops

The course offers several practical workshops and projects that allow students to work with real-world projects and gain hands-on experience.

Indian Institute of Embedded Systems (IIES)

IIES is one of the most reputed institutes for embedded systems training in India. The institute offers a wide range of certificate and diploma programs in embedded systems, including the beginner's course mentioned above.

Expert Trainers

IIES has a team of experienced trainers who are experts in their field. They provide practical training sessions, enabling students to gain skills that are relevant to industry standards.

Industry Partnerships

Keeping up with the current industry trends is essential to gaining expertise in a field; IIES has partnered with various companies such as Altair, Tiempo Labs, and many more reputed firms. This collaboration helps to keep the students updated about industry trends and expectations.

Advanced Facilities

IIES has cutting-edge infrastructure and world-class facilities, providing students with access to the latest hardware and software technologies and practical hands-on learning experiences.

Course Duration and Cost

The beginner's course offered by IIES is of 3 months' duration and offers flexible batch timings. The fee structure is reasonable and affordable, making it accessible to anyone interested in learning about embedded systems.

Conclusion

A beginner's course on embedded systems offered by IIES can be an excellent way to learn about this fascinating field. The program provides a comprehensive overview of embedded system concepts, tools, and techniques while also offering practical hands-on learning experiences. Completing the course can be a great career opportunity in a field where the demand for professionals continues to grow. And with IIES's expert trainers and state-of-the-art facilities, you can be confident that you're learning from the best. So, enroll today and start your journey into the exciting world of embedded systems!

[mariacallous]

Margaret Mitchell is a pioneer when it comes to testing generative AI tools for bias. She founded the Ethical AI team at Google, alongside another well-known researcher, Timnit Gebru, before they were later both fired from the company. She now works as the AI ethics leader at Hugging Face, a software startup focused on open source tools.

We spoke about a new dataset she helped create to test how AI models continue perpetuating stereotypes. Unlike most bias-mitigation efforts that prioritize English, this dataset is malleable, with human translations for testing a wider breadth of languages and cultures. You probably already know that AI often presents a flattened view of humans, but you might not realize how these issues can be made even more extreme when the outputs are no longer generated in English.

My conversation with Mitchell has been edited for length and clarity.

Reece Rogers: What is this new dataset, called SHADES, designed to do, and how did it come together?

Margaret Mitchell: It's designed to help with evaluation and analysis, coming about from the BigScience project. About four years ago, there was this massive international effort, where researchers all over the world came together to train the first open large language model. By fully open, I mean the training data is open as well as the model.

Hugging Face played a key role in keeping it moving forward and providing things like compute. Institutions all over the world were paying people as well while they worked on parts of this project. The model we put out was called Bloom, and it really was the dawn of this idea of “open science.”

We had a bunch of working groups to focus on different aspects, and one of the working groups that I was tangentially involved with was looking at evaluation. It turned out that doing societal impact evaluations well was massively complicated—more complicated than training the model.

We had this idea of an evaluation dataset called SHADES, inspired by Gender Shades, where you could have things that are exactly comparable, except for the change in some characteristic. Gender Shades was looking at gender and skin tone. Our work looks at different kinds of bias types and swapping amongst some identity characteristics, like different genders or nations.

There are a lot of resources in English and evaluations for English. While there are some multilingual resources relevant to bias, they're often based on machine translation as opposed to actual translations from people who speak the language, who are embedded in the culture, and who can understand the kind of biases at play. They can put together the most relevant translations for what we're trying to do.

So much of the work around mitigating AI bias focuses just on English and stereotypes found in a few select cultures. Why is broadening this perspective to more languages and cultures important?

These models are being deployed across languages and cultures, so mitigating English biases—even translated English biases—doesn't correspond to mitigating the biases that are relevant in the different cultures where these are being deployed. This means that you risk deploying a model that propagates really problematic stereotypes within a given region, because they are trained on these different languages.

So, there's the training data. Then, there's the fine-tuning and evaluation. The training data might contain all kinds of really problematic stereotypes across countries, but then the bias mitigation techniques may only look at English. In particular, it tends to be North American– and US-centric. While you might reduce bias in some way for English users in the US, you've not done it throughout the world. You still risk amplifying really harmful views globally because you've only focused on English.

Is generative AI introducing new stereotypes to different languages and cultures?

That is part of what we're finding. The idea of blondes being stupid is not something that's found all over the world, but is found in a lot of the languages that we looked at.

When you have all of the data in one shared latent space, then semantic concepts can get transferred across languages. You're risking propagating harmful stereotypes that other people hadn't even thought of.

Is it true that AI models will sometimes justify stereotypes in their outputs by just making shit up?

That was something that came out in our discussions of what we were finding. We were all sort of weirded out that some of the stereotypes were being justified by references to scientific literature that didn't exist.

Outputs saying that, for example, science has shown genetic differences where it hasn't been shown, which is a basis of scientific racism. The AI outputs were putting forward these pseudo-scientific views, and then also using language that suggested academic writing or having academic support. It spoke about these things as if they're facts, when they're not factual at all.

What were some of the biggest challenges when working on the SHADES dataset?

One of the biggest challenges was around the linguistic differences. A really common approach for bias evaluation is to use English and make a sentence with a slot like: “People from [nation] are untrustworthy.” Then, you flip in different nations.

When you start putting in gender, now the rest of the sentence starts having to agree grammatically on gender. That's really been a limitation for bias evaluation, because if you want to do these contrastive swaps in other languages—which is super useful for measuring bias—you have to have the rest of the sentence changed. You need different translations where the whole sentence changes.

How do you make templates where the whole sentence needs to agree in gender, in number, in plurality, and all these different kinds of things with the target of the stereotype? We had to come up with our own linguistic annotation in order to account for this. Luckily, there were a few people involved who were linguistic nerds.

So, now you can do these contrastive statements across all of these languages, even the ones with the really hard agreement rules, because we've developed this novel, template-based approach for bias evaluation that’s syntactically sensitive.

Generative AI has been known to amplify stereotypes for a while now. With so much progress being made in other aspects of AI research, why are these kinds of extreme biases still prevalent? It’s an issue that seems under-addressed.

That's a pretty big question. There are a few different kinds of answers. One is cultural. I think within a lot of tech companies it's believed that it's not really that big of a problem. Or, if it is, it's a pretty simple fix. What will be prioritized, if anything is prioritized, are these simple approaches that can go wrong.

We'll get superficial fixes for very basic things. If you say girls like pink, it recognizes that as a stereotype, because it's just the kind of thing that if you're thinking of prototypical stereotypes pops out at you, right? These very basic cases will be handled. It's a very simple, superficial approach where these more deeply embedded beliefs don't get addressed.

It ends up being both a cultural issue and a technical issue of finding how to get at deeply ingrained biases that aren't expressing themselves in very clear language.

[communistkenobi]

I’m downloading shapefiles (basically geographic files, in this case the polygons of every country) for a mapping project I’m doing and while most countries have an ISO code column in their file (which is a 2 letter abbreviation of their country name), Canada, the UK, and the US do not. The US doesn’t even have a country column, it just listed the states. Now these are official shapefiles made by the vendor of the software I’m using (Esri, which is one of if not the dominant global distributor of mapping software) and are treated as the authoritative copies. Like if you wanted to download the outline of the US and all its states you would download Esri’s copy of it. And the reason I noticed this discrepancy is because I’m trying to combine individual country files to a global world file and I first had to edit the US & UK & Canada shapefiles and manually add in their ISO codes so they would join the world file properly. Notably countries like Argentina already have country & ISO code embedded in its shapefile.

And what I’m taking away from this is that there is an epistemic assumption happening where western countries can stand alone - they do not need to be combined or compared with other countries, they are complete units that constitute their own global file. Their data lack an “international character,” they are not set up for comparison or combination with other country data. The assumption being made by excluding these (extraordinarily trivial and easy to include) datapoints is that the only reason you would be downloading shapefiles for the US or Canada is to study these countries in isolation, while countries in the Global South are structured to accommodate the act of comparison

[utopicwork]

Out of curiousity, how did you get into doing this sort of computer work? Especially more low level stuff. :]

How can other people get into it / what would you like to see people make in the future in this area?

- Aspiring Programmer

I was an extremely poor kid, in middle school I learned about piracy which led to me getting into FOSS software for media conversion so I could load a bunch of media onto my psp. A short time later I learned about cfw, custom firmware, for psps when I was trying to figure out how pirating games for the system worked, that led to my first hardware hacking, at the time you needed to make a "magic battery" in order to save money on hacking the system which luckily for me I was able to do with a busted battery. That was really my big start because it was so exciting to be a poor kid with access to tons of games and media all of a sudden. Since then I've been very interested in firmware work and embedded systems, though I definitely didnt know thats what it was at the time.

For getting into software/hardware hacking/programming in a similar way I'd seriously recommend getting a cheap SBC, something like a Raspberry Pi Zero or just a Raspberry Pi is a good place to start especially since there are tons of projects for those boards that you can hack on and tons of very useful programs like pi-hole which does DNS ad blocking.

As to what I'd like to see people do: more projects dealing with media on these kinds of systems, video djing, glitch art, etc, because usually you're limited to something like VLC for media.

[kyokosasagawa]

I started writing "4 srs" this month and I like how free and accessible writing is, so I'm recommending free software I've experimented with that might help people who want to get into the hobby!

“Specifically Created for Writing Stories”

-------------------------------

Manuskript – Story organizer / word processor. Has an outliner and index card function, along with distraction free mode. Lets you switch between different templates such as a non-fiction mode or a short story.

Bibisco – Novel writing software that includes writing goals, world-building, distraction free mode, and a timeline.

“I Just Want to Write”

---------------------------

LibreOffice – Microsoft 365 alternative, but free! LibreOffice Writer is what I wrote this tumblr post in before I posted it. Also if you copy & paste the text into the Rich Text Editor on AO3, it seems that it actually converts it properly. Nice! No need for scripts.

Note-Taking

-------------------------------

Zim Wiki - note taking application that is very, very lightweight (1.1mb). It functions with a tree structure, so I’d personally recommend it for world-building and character bios. There are built-in plugins that also turn it into a good software for task management (it even has a article on how to use it for GTD) and journalling. See also: CherryTree (2mb), which is a more outdated-looking app, but functions similarly.

Obsidian MD – The Big Boy. markdown note editor that has been adopted by personal knowledge management fans---if it doesn’t do something you want it to do, just look in the community plugins to see if someone has already done it. Some unique non-word processing related usages I’ve found is the ability to create a table of contents dashboard, a image gallery for images, embedding youtube videos and timestamping notes, so forth.

Logseq – A bullet point based markdown note editor that also has PDF annotations, Zotero integration, flashcard creation, and whiteboards. Best used for outlining projects due to the bullet point structure.

Joplin – A modern app comparable to Zim Wiki, it’s basically just a note-taking software that uses folders and tags to sort easier. Looks prettier than Zim Wiki and Cherry Tree

Notion – An online-only website that allows usage of different database types. Free for personal use. Note: I dislike the AI updates that have been making the app lag more. I prefer the others on this list.

Mind Maps

-------------------------------

Freeplane – So much goddamn features, including a ton of add-ons. Looks somewhat ugly, but it works for anyone willing to spend a while learning how to use it.

Mermaid – Text-based diagram creator. Can be used in apps like Joplin, Notion, and Obsidian.

Obsidian’s Canvas – A core plugin for Obsidian, it deserves its own mention in that it allows you to create embedded notes of the mindmap nodes. Thus, if you want to create a 20-page long note and have it minimized to the size of a penny on the mindmap, you could.

Other Things That Might Be Of Interest

Syncthing - A free software that allows you to sync between two or more computers. Have a desktop but also laze around on a laptop in bed, coming up with ideas?? This is your buddy if you don't want to use a online software.

[this-week-in-rust]

This Week in Rust 595

Hello and welcome to another issue of This Week in Rust! Rust is a programming language empowering everyone to build reliable and efficient software. This is a weekly summary of its progress and community. Want something mentioned? Tag us at @thisweekinrust.bsky.social on Bluesky or @ThisWeekinRust on mastodon.social, or send us a pull request. Want to get involved? We love contributions.

This Week in Rust is openly developed on GitHub and archives can be viewed at this-week-in-rust.org. If you find any errors in this week's issue, please submit a PR.

Want TWIR in your inbox? Subscribe here.

Updates from Rust Community

Official

March Project Goals Update

Newsletters

The Embedded Rustacean Issue #43

Project/Tooling Updates

Shadertoys ported to Rust GPU

Meilisearch 1.14 - composite embedders, embedding cache, granular filterable attributes, and batch document retrieval by ID

rust-query 0.4: structural types and other new features

Observations/Thoughts

Rebuilding Prime Video UI with Rust and WebAssembly

ALP Rust is faster than C++

what if the poison were rust?

A surprising enum size optimization in the Rust compiler

Two Years of Rust

An ECS lite architecture

A 2025 Survey of Rust GUI Libraries

BTrees, Inverted Indices, and a Model for Full Text Search

Cutting Down Rust Compile Times From 30 to 2 Minutes With One Thousand Crates

SIMD in zlib-rs (part 1): Autovectorization and target features

Avoiding memory fragmentation in Rust with jemalloc

[video] Bevy Basics: Who Observes the Observer

Rust Walkthroughs

Rust Type System Deep Dive From GATs to Type Erasure

Async from scratch 1: What's in a Future, anyway? | natkr's ramblings

Async from scratch 2: Wake me maybe | natkr's ramblings

Building a search engine from scratch, in Rust: part 4

Pretty State Machine Patterns in Rust

[video] Build with Naz : Declarative macros in Rust

Miscellaneous

March 2025 Jobs Report

Rust resources

Crate of the Week

This week's crate is wgpu, a cross-platform graphics and compute library based on WebGPU.

Despite a lack of suggestions, llogiq is pleased with his choice.

Please submit your suggestions and votes for next week!

Calls for Testing

An important step for RFC implementation is for people to experiment with the implementation and give feedback, especially before stabilization.

If you are a feature implementer and would like your RFC to appear in this list, add a call-for-testing label to your RFC along with a comment providing testing instructions and/or guidance on which aspect(s) of the feature need testing.

No calls for testing were issued this week by Rust, Rust language RFCs or Rustup.*

Let us know if you would like your feature to be tracked as a part of this list.

RFCs

Rust

Rustup

If you are a feature implementer and would like your RFC to appear on the above list, add the new call-for-testing label to your RFC along with a comment providing testing instructions and/or guidance on which aspect(s) of the feature need testing.

Call for Participation; projects and speakers

CFP - Projects

Always wanted to contribute to open-source projects but did not know where to start? Every week we highlight some tasks from the Rust community for you to pick and get started!

Some of these tasks may also have mentors available, visit the task page for more information.

rama - add serve command to rama-cli

rama - add support for include_dir for to ServeDir and related

rama - add curl module to rama-http-types

If you are a Rust project owner and are looking for contributors, please submit tasks here or through a PR to TWiR or by reaching out on X (formerly Twitter) or Mastodon!

CFP - Events

Are you a new or experienced speaker looking for a place to share something cool? This section highlights events that are being planned and are accepting submissions to join their event as a speaker.

If you are an event organizer hoping to expand the reach of your event, please submit a link to the website through a PR to TWiR or by reaching out on X (formerly Twitter) or Mastodon!

Updates from the Rust Project

480 pull requests were merged in the last week

Compiler

detect and provide suggestion for &raw EXPR

don't suggest the use of impl Trait in closure parameter

make the compiler suggest actual paths instead of visible paths if the visible paths are through any doc hidden path

tell LLVM about impossible niche tags

remove Nonterminal and TokenKind::Interpolated

re-use Sized fast-path

Library

add core::intrinsics::simd::{simd_extract_dyn, simd_insert_dyn}

initial UnsafePinned implementation (Part 1: Libs)

polymorphize array::IntoIter's iterator impl

speed up String::push and String::insert

std: add Output::exit_ok

Cargo

added symlink resolution for workspace-path-hash

improved error message when build-dir template var is invalid

Rustdoc

search: add unbox flag to Result aliases

enable Markdown extensions when looking for doctests

Clippy

arbitrary_source_item_ordering should ignore test modules

implicit_return: better handling of asynchronous code

accept self.cmp(other).into() as canonical PartialOrd impl

add manual_abs_diff lint

consecutive returns dont decrease cognitive Complexity level anymore

consider nested lifetimes in mut_from_ref

correctly handle bracketed type in default_constructed_unit_struct

deprecate match_on_vec_items lint

do not propose to auto-derive Clone in presence of unsafe fields

fix: iter_cloned_collect false positive with custom From/IntoIterator impl

fix: map_entry: don't emit lint before checks have been performed

fix: redundant_clone false positive in overlapping lifetime

various fixes for manual_is_power_of_two

Rust-Analyzer

ast: return correct types for make::expr_* methods

add children modules feature

add normalizeDriveLetter

distribute x64 and aarch64 Linux builds with PGO optimizations

fix dyn compatibility code bypassing callable_item_signature query

fix a small bug with catastrophic effects

fix an incorrect ExpressionStore that was passed

prevent panics when there is a cyclic dependency between closures

shadow type by module

ignore errors from rustfmt which may trigger error notification

port closure inference from rustc

Rust Compiler Performance Triage

Relatively small changes this week, nothing terribly impactful (positive or negative).

Triage done by @simulacrum. Revision range: e643f59f..15f58c46

1 Regressions, 3 Improvements, 3 Mixed; 2 of them in rollups 35 artifact comparisons made in total

Full report here

Approved RFCs

Changes to Rust follow the Rust RFC (request for comments) process. These are the RFCs that were approved for implementation this week:

No RFCs were approved this week.

Final Comment Period

Every week, the team announces the 'final comment period' for RFCs and key PRs which are reaching a decision. Express your opinions now.

Tracking Issues & PRs

Rust

Split elided_lifetime_in_paths into tied and untied

check types of const param defaults

Stabilize flags for doctest cross compilation

Do not remove trivial SwitchInt in analysis MIR

Implement a lint for implicit autoref of raw pointer dereference - take 2

Implement Default for raw pointers

make abi_unsupported_vector_types a hard error

Stabilize let chains in the 2024 edition

Make closure capturing have consistent and correct behaviour around patterns

Stabilize the cell_update feature

Other Areas

*No Items entered Final Comment Period this week for Rust RFCs, Cargo, Language Team, Language Reference or Unsafe Code Guidelines.

Let us know if you would like your PRs, Tracking Issues or RFCs to be tracked as a part of this list.

New and Updated RFCs

No New or Updated RFCs were created this week.

Upcoming Events

Rusty Events between 2025-04-16 - 2025-05-14 🦀

Virtual

2025-04-16 | Virtual (Vancouver, BC, CA) | Vancouver Rust

Rust Study/Hack/Hang-out

2025-04-17 | Virtual and In-Person (Redmond, WA, US) | Seattle Rust User Group

April, 2025 SRUG (Seattle Rust User Group) Meetup

2025-04-22 | Virtual (Dallas, TX, US) | Dallas Rust User Meetup

Fourth Tuesday

2025-04-23 | Virtual (Cardiff, UK) | Rust and C++ Cardiff

Beyond embedded - OS development in Rust

2025-04-24 | Virtual (Berlin, DE) | Rust Berlin

Rust Hack and Learn

2025-04-24 | Virtual (Charlottesville, VA, US) | Charlottesville Rust Meetup

Part 2: Quantum Computers Can’t Rust-Proof This!"

2025-05-03 | Virtual (Kampala, UG) | Rust Circle Meetup

Rust Circle Meetup

2025-05-05 | Virtual (Tel Aviv-Yafo, IL) | Rust 🦀 TLV

Tauri: Cross-Platform desktop applications with Rust and web technologies

2025-05-07 | Virtual (Indianapolis, IN, US) | Indy Rust

Indy.rs - with Social Distancing

2025-05-08 | Virtual (Berlin, DE) | Rust Berlin

Rust Hack and Learn

2025-05-13 | Virtual (Dallas, TX, US) | Dallas Rust User Meetup

Second Tuesday

Asia

2025-04-22 | Tel Aviv-Yafo, IL | Rust 🦀 TLV

In person Rust April 2025 at Braavos in Tel Aviv in collaboration with StarkWare

Europe

2025-04-19 | Istanbul, TR | Türkiye Rust Community

Rust Konf Türkiye

2025-04-23 | London, UK | London Rust Project Group

Fusing Python with Rust using raw C bindings

2025-04-24 | Aarhus, DK | Rust Aarhus

Talk Night at MFT Energy

2025-04-24 | Edinburgh, UK | Rust and Friends

Rust and Friends (evening pub)

2025-04-24 | Manchester, UK | Rust Manchester

Rust Manchester April Code Night

2025-04-25 | Edinburgh, UK | Rust and Friends

Rust and Friends (daytime coffee)

2025-04-26 | Stockholm, SE | Stockholm Rust

Ferris' Fika Forum #11

2025-04-29 | London, UK | Rust London User Group

LDN Talks April 2025 Community Showcase

2025-04-29 | Paris, FR | Rust Paris

Rust meetup #76

2025-04-30 | Frankfurt, DE | Rust Rhein-Main

Kubernetes Operator in Rust

2025-05-01 | Nürnberg, DE | Rust Nuremberg

Hackers Hike 0x0

2025-05-06 - 2025-05-07 | Paris, FR | WebAssembly and Rust Meetup

GOSIM AI Paris 2025

2025-05-06 | Paris, FR | WebAssembly and Rust Meetup (Wasm Empowering AI)

GOSIM AI Paris 2025 (Discount available)

2025-05-07 | Madrid, ES | MadRust

VII Lenguajes, VII Perspectivas, I Problema

2025-05-07 | Oxford, UK | Oxford Rust Meetup Group

Oxford Rust and C++ social

2025-05-08 | Gdansk, PL | Rust Gdansk

Rust Gdansk Meetup #8

2025-05-08 | London, UK | London Rust Project Group

Adopting Rust (Hosted by Lloyds bank)

2025-05-13 | Amsterdam, NL | RustNL

RustWeek 2025 announcement

2025-05-13 - 2025-05-17 | Utrecht, NL | Rust NL

RustWeek 2025

2025-05-14 | Reading, UK | Reading Rust Workshop

Reading Rust Meetup

North America

2025-04-17 | Mountain View, CA, US | Hacker Dojo

RUST MEETUP at HACKER DOJO

2025-04-17 | Nashville, TN, US | Music City Rust Developers

Using Rust For Web Series 1 : Why HTMX Is Bad

2025-04-17 | Redmond, WA, US | Seattle Rust User Group

April, 2025 SRUG (Seattle Rust User Group) Meetup

2025-04-22 | Detroit, MI, US | Detroit Rust

Rust Community Meet and Conference Report - Ann Arbor

2025-04-23 | Austin, TX, US | Rust ATX

Rust Lunch - Fareground

2025-04-23 | Austin, TX, US | Rust ATX

Rust Lunch - Fareground 2025-04-23 | Spokane, WA, US | Spokane Rust

Community Show & Tell at Fuel Coworking

2025-04-24 | Atlanta, GA, US | Rust Atlanta

3rd 3RD TIME OMG YES!

2025-04-25 | Boston, MA, US | Boston Rust Meetup

Ball Square Rust Lunch, Apr 25

2025-05-01 | Saint Louis, MO, US | STL Rust

SIUE Capstone Project reflections on Rust

2025-05-03 | Boston, MA, US | Boston Rust Meetup

Boston Common Rust Lunch, May 3

2025-05-08 | México City, MX | Rust MX

Calculando con el compilador: Compiler time vs Run time

2025-05-08 | Portland, OR, US | PDXRust

Apache DataFusion: A Fast, Extensible, Modular Analytic Query Engine in Rust

2025-05-11 | Boston, MA, US | Boston Rust Meetup

Porter Square Rust Lunch, May 11

Oceania

2025-04-22 | Barton, AC, AU | Canberra Rust User Group

April Meetup

If you are running a Rust event please add it to the calendar to get it mentioned here. Please remember to add a link to the event too. Email the Rust Community Team for access.

Jobs

Please see the latest Who's Hiring thread on r/rust

Quote of the Week

IEEE 754 floating point, proudly providing counterexamples since 1985!

– Johannes Dahlström on rust-internals

Thanks to Ralf Jung for the suggestion!

Please submit quotes and vote for next week!

This Week in Rust is edited by: nellshamrell, llogiq, cdmistman, ericseppanen, extrawurst, U007D, joelmarcey, mariannegoldin, bennyvasquez, bdillo

Email list hosting is sponsored by The Rust Foundation

Discuss on r/rust

[moose-mousse]

Finally fucking happened! Straight up stared at the boss with my mouth open while he was telling me something. I was saying we need to turn compiler optimization from the weird 01 with extra restrictions to 03. Functions that needs lower can then specify that with #pragma statements. But since those can only LOWER the compiler optimization we need it set to max per default. Boss then told me that we can never increase the compiler optimization level BECAUSE THEN THE COMPILER SOMETIMES CREATES WRONG MACHINE CODE!!! ... there is a limit... on how easy the code I can write I can write code... based on incompetence... Fuck Renesas micro-controllers! And screw my workplace for not starting to move to other micro-controllers the second they realized this!

No_inline means that any function I write will incur the cost of calling the function when the production code runs Normally I can break everything down into tiiiiny functions. 20 lines of code max. Everything is just... SO easy to read, understand, test and modify. And I can write them so they always get optimized away But nope. Cannot do that on an embedded system with no_inline Have to write giant impossible to read piece of shit function with 3-10 levels of abstraction jumps in them. Good luck you poor barstard that have to read my code later. Because I am now on another project. But it is taking a long time for some reason, because the code is unreadable. Anyway, good luck understanding my unreadable code! And then the boss claims we don't have money to change microcontrollers. And I am claiming, we cannot fucking afford to NOT pay for different micro-controllers. Software costs MILLIONS of dollars to develop. We are pissing MILLIONS out the window... So we can save several thousand dollars... Just... "Headdesks"

[mitvpusolapur]

Top B.Tech Courses in Maharashtra – CSE, AI, IT, and ECE Compared

B.Tech courses continue to attract students across India, and Maharashtra remains one of the most preferred states for higher technical education. From metro cities to emerging academic hubs like Solapur, students get access to diverse courses and skilled faculty. Among all available options, four major branches stand out: Computer Science and Engineering (CSE), Artificial Intelligence (AI), Information Technology (IT), and Electronics and Communication Engineering (ECE).

Each of these streams offers a different learning path. B.Tech in Computer Science and Engineering focuses on coding, algorithms, and system design. Students learn Python, Java, data structures, software engineering, and database systems. These skills are relevant for software companies, startups, and IT consulting.

B.Tech in Artificial Intelligence covers deep learning, neural networks, data processing, and computer vision. Students work on real-world problems using AI models. They also learn about ethical AI practices and automation systems. Companies hiring AI talent are in healthcare, retail, fintech, and manufacturing.

B.Tech in IT trains students in systems administration, networking, cloud computing, and application services. Graduates often work in system support, IT infrastructure, and data management. IT blends technical and management skills for enterprise use.

B.Tech ECE is for students who enjoy working with circuits, embedded systems, mobile communication, robotics, and signal processing. This stream is useful for telecom companies, consumer electronics, and control systems in industries.

Key Differences Between These B.Tech Programs:

CSE is programming-intensive. IT includes applications and system-level operations.

AI goes deeper into data modeling and pattern recognition.

ECE focuses more on hardware, communication, and embedded tech.

AI and CSE overlap, but AI involves more research-based learning.

How to Choose the Right B.Tech Specialization:

Ask yourself what excites you: coding, logic, data, devices, or systems.

Look for colleges with labs, project-based learning, and internship support.

Talk to seniors or alumni to understand real-life learning and placements.

Explore industry demand and long-term growth in each field.

MIT Vishwaprayag University, Solapur, offers all four B.Tech programs with updated syllabi, modern infrastructure, and practical training. Students work on live projects, participate in competitions, and build career skills through soft skills training. The university also encourages innovation and startup thinking.

Choosing the right course depends on interest and learning style. CSE and AI suit tech lovers who like coding and research. ECE is great for those who enjoy building real-world devices. IT fits students who want to blend business with technology.

Take time to explore the subjects and talk to faculty before selecting a stream. Your B.Tech journey shapes your future, so make an informed choice.

[nitte-university-blog]

Essential Skills Every Electronics Engineer Should Master

Electronics engineering is an exciting and constantly evolving field. With new technologies emerging every day, the need for skilled professionals has never been greater. If you're pursuing a B Tech in Electrical and Electronics Engineering or exploring options at B Tech colleges for Electrical and Electronics, it's crucial to know which skills can set you apart in this competitive domain.

Let’s dive into the essential skills every aspiring electronics engineer should master.

Strong Foundation in Circuit Design

Circuit design is at the heart of electronics engineering. Understanding how to create, analyze, and optimize circuits is a must-have skill. Whether you’re designing a simple resistor network or a complex integrated circuit, mastering tools like SPICE and PCB design software can make your designs efficient and innovative.

Programming Proficiency

Electronics and programming often go hand in hand. Languages like Python, C, and MATLAB are widely used to simulate electronic systems, automate processes, and even build firmware for devices. Engineers proficient in programming can troubleshoot problems effectively and add versatility to their skill set.

Knowledge of Embedded Systems

Embedded systems are everywhere—from your smartphone to your washing machine. As an electronics engineer, understanding microcontrollers, sensors, and actuators is crucial for creating devices that work seamlessly in our daily lives. Hands-on experience with platforms like Arduino and Raspberry Pi can be a great way to start.

Problem-Solving and Analytical Thinking

Electronics engineers often face unique challenges, such as debugging faulty circuits or improving system performance. Strong problem-solving and analytical thinking skills help them identify issues quickly and find effective solutions. To cultivate these skills, tackle real-world projects during your coursework or internships.

Familiarity with Power Systems

As the world moves toward renewable energy and smart grids, knowledge of power systems is becoming increasingly important. Engineers in this field should understand how electrical power is generated, transmitted, and distributed and how to design energy-efficient systems.

Effective Communication Skills

Electronics engineering often involves working in teams with other engineers, designers, or clients. Communicating your ideas clearly—whether through reports, presentations, or technical drawings—is just as important as your technical skills. Strong communication ensures that your brilliant ideas come to life effectively.

Adaptability to New Technologies

Technology evolves rapidly, and staying updated is essential for electronics engineers. Whether you’re learning about IoT (Internet of Things), AI integration, or 5G communication, an adaptable mindset will ensure you remain relevant and capable of tackling emerging challenges.

Hands-On Experience

While theoretical knowledge is important, nothing beats practical experience. Participating in labs, internships, or personal projects gives you the opportunity to apply what you’ve learned and develop confidence in your skills. Employers often value hands-on experience as much as your academic achievements.

Preparing for Success in Electronics Engineering

Pursuing a B Tech in Electrical and Electronics Engineering is the first step toward mastering these skills. The best B Tech colleges for Electrical and Electronics not only provide a strong academic foundation but also opportunities for practical learning and industry exposure. By focusing on the skills mentioned above, you can position yourself as a competent and innovative engineer ready to tackle real-world challenges.

[mariacallous]

Addressing a single executive order from Donald Trump’s voluminous first-day edicts is like singling out one bullet in a burst from an AK-47. But one of them hit me in the gut. That is “Establishing and Implementing the President’s Department of Government Efficiency.’’ The acronym for that name is DOGE (named after a memecoin), and it’s the Elon Musk–led effort to cut government spending by a trillion bucks or two. Though DOGE was, until this week, pitched as an outside body, this move makes it an official part of government—by embedding it in an existing agency that was formerly part of the Office of Management and Budget called the United States Digital Service. The latter will now be known as the US DOGE Service, and its new head will be more tightly connected to the president, reporting to his chief of staff.

The new USDS will apparently shift its former laser focus on building cost-efficient and well-designed software for various agencies to a hardcore implementation of the Musk vision. It’s kind of like a government version of a SPAC, the dodgy financial maneuver that launched Truth Social in the public market without ever having to reveal a coherent business plan to underwriters.

The order is surprising in a sense because, on its face, DOGE seems more limited than its original super ambitious pitch. This iteration seems more tightly centered on saving money through streamlining and modernizing the government’s massive and messy IT infrastructure. There are big savings to be had, but a handful of zeros short of trillions. As of yet, it’s uncertain whether Musk will become the DOGE administrator. It doesn’t seem big enough for him. (The first USDS director, Mikey Dickerson, jokingly posted on LinkedIn, “I’d like to congratulate Elon Musk on being promoted to my old job.”) But reportedly Musk pushed for this structure as a way to embed DOGE in the White House. I hear that inside the Executive Office Building, there are numerous pink Post-it notes claiming space even beyond USDS’s turf, including one such note on the former chief information officers’ enviable office. So maybe this could be a launch pad for a more sweeping effort that will eliminate whole agencies and change policies. (I was unable to get a White House representative to answer questions, which isn’t surprising considering that there are dozens of other orders that equally beg for explanation.)

One thing is clear—this ends United States Digital Service as it previously existed, and marks a new, and maybe perilous era for the USDS, which I have been enthusiastically covering since its inception. The 11-year-old agency sprang out of the high-tech rescue squad salvaging the mess that was Healthcare.gov, the hellish failure of a website that almost tanked the Affordable Care Act. That intrepid team of volunteers set the template for the agency: a small group of coders and designers who used internet-style techniques (cloud not mainframe; the nimble “agile” programming style instead of the outdated “waterfall” technique) to make government tech as nifty as the apps people use on their phones. Its soldiers, often leaving lucrative Silicon Valley jobs, were lured by the prospect of public service. They worked out of the agency’s funky brownstone headquarters on Jackson Place, just north of the White House. The USDS typically took on projects that were mired in centi-million contracts and never completed—delivering superior results within weeks. It would embed its employees in agencies that requested help, being careful to work collaboratively with the lifers in the IT departments. A typical project involved making DOD military medical records interoperable with the different systems used by the VA. The USDS became a darling of the Obama administration, a symbol of its affiliation with cool nerddom.

During the first Trump administration, deft maneuvering kept the USDS afloat—it was the rare Obama initiative that survived. Its second-in-command, Haley Van Dyck, cleverly got buy-in from Trump’s in-house fixer, Jared Kushner. When I went to meet Kushner for an off-the-record talk early in 2017, I ran into Van Dyck in the West Wing; she gave me a conspiratorial nod that things were looking up, at least for the moment. Nonetheless, the four Trump years became a balancing act in sharing the agency’s achievements while somehow staying under the radar. “At Disney amusement parks, they paint things that they want to be invisible with this certain color of green so that people don't notice it in passing,” one USDSer told me. “We specialized in painting ourselves that color of green.” When Covid hit, that became a feat in itself, as USDS worked closely with White House coronavirus response coordinator Deborah Birx on gathering statistics—some of which the administration wasn’t eager to publicize.

By the end of Trump’s term, the green paint was wearing thin. A source tells me that at one point a Trump political appointee noticed—not happily—that USDS was recruiting at tech conferences for lesbians and minorities, and asked why. The answer was that it was an effective way to find great product managers and designers. The appointee accepted that but asked if, instead of putting “Lesbians Who Tech” on the reimbursement line, could they just say LWT?

Under Biden no subterfuge was needed—the USDS thrived. But despite many months of effort, it could not convince Congress to give it permanent funding. With the return of Trump, and his promises to cut government spending, there was reason to think that USDS would evaporate. That’s why the DOGE move is kind of bittersweet—at least it now has more formal recognition and ostensibly will get a reliable budget line.

How will the integration work? The executive order mandates that in addition to normal duties the USDS director will also head a temporary organization “dedicated to advancing the President’s 18-month DOGE agenda.” That agenda is not clearly defined, but elsewhere the order speaks of improving the quality and efficiency of government-wide software, systems, and infrastructure. More specific is the mandate to embed four-person teams inside every agency to help realize the DOGE agenda. The order is very explicit that the agency must provide “full and prompt access to all unclassified agency records, software systems, and IT systems.” Apparently Musk is obsessed with an unprecedented centralization of the data that makes the government go—or not. This somewhat adversarial stance is a dramatic shift from the old USDS MO of working collegially with the lifers inside the agencies.

Demanding all that data might be a good thing. Clare Martorana, who until last week was the nation’s chief information officer, says that while she saw many victories during her eight years in government tech, making big changes has been tough, in large part because of the difficulty of getting such vital data. “We have budget data that is incomprehensible,” she says. “The agency understands it, but they hide money in all kinds of places, so no one can really get a 100,000-foot view. How many open positions do they have? What are the skill sets? What are their top contracts? When are they renegotiating their most important contracts? How much do they spend on operations and maintenance versus R&D or innovation? You should know all these things.” If DOGE gets that information and uses it well, it could be transformational. “Through self-reporting, we spend $120 billion on IT,” she says “If we found all the hidden money and shadow IT, it's $200, $300, maybe $500 billion. We lose a lot of money on technology we buy stupidly, and we don't deliver services to the American public that they deserve.” So this Trump effort could be a great thing? “I’m trying very hard to be optimistic about it,” says Martorana. The USDS’s outgoing director, Mina Hsiang, is also trying to be upbeat. “I think there's a tremendous opportunity,” she says. “ I don't know what [DOGE] will do with it, but I hope that they listen to a lot of great folks who are there.”

On the other hand, those four-person teams could be a blueprint for mayhem. Up until now, USDS would send only engineers and designers into agencies, and their focus was to build things and hopefully set an example for the full-timers to do work like they do at Google or Amazon. The EO dictates only one engineer in a typical four-person team, joined by a lawyer (not known for building stuff), an HR person (known for firing people), and a “team lead” whose job description sounds like a political enforcer: “implementing the president’s DOGE Agenda.” I know that’s a dark view, but Elon Musk —and his new boss—are no strangers to clearing out a workplace. Maybe they’ll figure AI can do things better.

Whichever way it goes, the original Obama-era vibes of the USDS may forever be stilled—to be superseded by a different kind of idealist in MAGA garb. As one insider told me, “USDS leadership is pretty ill equipped to navigate the onslaught of these DOGE guys, and they are going to get the shit kicked out of them.” Though not perfect, the USDS has by dint of hard work, mad skills, and corny idealism, made a difference. Was there really a need to embed the DOGE experiment into an agency that was doing good? And what are the odds that on July 4, 2026, when the “temporary” DOGE experiment is due to end, the USDS will sunset as well? At best, the new initiative might help unravel the near intractable train wreck that is government IT. But at worst, the integration will be like a greedy brain worm wreaking havoc on its host.

[sindhu14]

What is Python, How to Learn Python?

What is Python?

Python is a high-level, interpreted programming language known for its simplicity and readability. It is widely used in various fields like: ✅ Web Development (Django, Flask) ✅ Data Science & Machine Learning (Pandas, NumPy, TensorFlow) ✅ Automation & Scripting (Web scraping, File automation) ✅ Game Development (Pygame) ✅ Cybersecurity & Ethical Hacking ✅ Embedded Systems & IoT (MicroPython)

Python is beginner-friendly because of its easy-to-read syntax, large community, and vast library support.

How Long Does It Take to Learn Python?

The time required to learn Python depends on your goals and background. Here’s a general breakdown:

1. Basics of Python (1-2 months)

If you spend 1-2 hours daily, you can master:

Variables, Data Types, Operators

Loops & Conditionals

Functions & Modules

Lists, Tuples, Dictionaries

File Handling

Basic Object-Oriented Programming (OOP)

2. Intermediate Level (2-4 months)

Once comfortable with basics, focus on:

Advanced OOP concepts

Exception Handling

Working with APIs & Web Scraping

Database handling (SQL, SQLite)

Python Libraries (Requests, Pandas, NumPy)

Small real-world projects

3. Advanced Python & Specialization (6+ months)

If you want to go pro, specialize in:

Data Science & Machine Learning (Matplotlib, Scikit-Learn, TensorFlow)

Web Development (Django, Flask)

Automation & Scripting

Cybersecurity & Ethical Hacking

Learning Plan Based on Your Goal

📌 Casual Learning – 3-6 months (for automation, scripting, or general knowledge) 📌 Professional Development – 6-12 months (for jobs in software, data science, etc.) 📌 Deep Mastery – 1-2 years (for AI, ML, complex projects, research)

Scope @ NareshIT:

At NareshIT’s Python application Development program you will be able to get the extensive hands-on training in front-end, middleware, and back-end technology.

It skilled you along with phase-end and capstone projects based on real business scenarios.

Here you learn the concepts from leading industry experts with content structured to ensure industrial relevance.

An end-to-end application with exciting features

Earn an industry-recognized course completion certificate.

For more details:

[iotric1]

Transforming Businesses with IoT: How Iotric’s IoT App Development Services Drive Innovation

In these days’s fast-paced virtual world, companies should include smart technology to stay ahead. The Internet of Things (IoT) is revolutionizing industries by way of connecting gadgets, collecting actual-time data, and automating approaches for stronger efficiency. Iotric, a leading IoT app improvement carrier issuer, makes a speciality of developing contemporary answers that help businesses leverage IoT for boom and innovation.

Why IoT is Essential for Modern Businesses IoT generation allows seamless communique between gadgets, permitting agencies to optimize operations, enhance patron enjoy, and reduce charges. From smart homes and wearable gadgets to business automation and healthcare monitoring, IoT is reshaping the manner industries perform. With a complicated IoT app, companies can:

Enhance operational efficiency by automating methods Gain real-time insights with linked devices Reduce downtime thru predictive renovation Improve purchaser revel in with smart applications

Strengthen security with far off tracking

Iotric: A Leader in IoT App Development Iotric is a trusted name in IoT app development, imparting cease-to-stop solutions tailored to numerous industries. Whether you want an IoT mobile app, cloud integration, or custom firmware improvement, Iotric can provide modern answers that align with your commercial enterprise goals.

Key Features of Iotric’s IoT App Development Service Custom IoT App Development – Iotric builds custom designed IoT programs that seamlessly connect to various gadgets and systems, making sure easy statistics waft and person-pleasant interfaces.

Cloud-Based IoT Solutions – With knowledge in cloud integration, Iotric develops scalable and comfy cloud-based totally IoT programs that permit real-time statistics access and analytics.

Embedded Software Development – Iotric focuses on developing green firmware for IoT gadgets, ensuring optimal performance and seamless connectivity.

IoT Analytics & Data Processing – By leveraging AI-driven analytics, Iotric enables businesses extract valuable insights from IoT facts, enhancing decision-making and operational efficiency.

IoT Security & Compliance – Security is a pinnacle precedence for Iotric, ensuring that IoT programs are covered in opposition to cyber threats and comply with enterprise standards.

Industries Benefiting from Iotric’s IoT Solutions Healthcare Iotric develops IoT-powered healthcare programs for far off patient tracking, clever wearables, and real-time health monitoring, making sure better patient care and early diagnosis.

Manufacturing With business IoT (IIoT) solutions, Iotric facilitates manufacturers optimize manufacturing traces, lessen downtime, and decorate predictive preservation strategies.

Smart Homes & Cities From smart lighting and security structures to intelligent transportation, Iotric’s IoT solutions make contributions to building linked and sustainable cities.

Retail & E-commerce Iotric’s IoT-powered stock monitoring, smart checkout structures, and personalized purchaser reviews revolutionize the retail region.

Why Choose Iotric for IoT App Development? Expert Team: A team of professional IoT builders with deep industry understanding Cutting-Edge Technology: Leverages AI, gadget gaining knowledge of, and big records for smart solutions End-to-End Services: From consultation and development to deployment and support Proven Track Record: Successful IoT projects throughout more than one industries

Final Thoughts As organizations maintain to embody digital transformation, IoT stays a game-changer. With Iotric’s advanced IoT app improvement services, groups can unencumber new possibilities, beautify efficiency, and live ahead of the competition. Whether you are a startup or an established agency, Iotric offers the expertise and innovation had to carry your IoT vision to lifestyles.

Ready to revolutionize your commercial enterprise with IoT? Partner with Iotric these days and enjoy the destiny of connected generation!

[quacheta]

So a few months ago, there was at least one (1) person who got permission to, and started, the project of bookbinding AmevelloBlue's The Ghost in the Shell. And when they tried to print it, it was like 700-800 pages. Which is... a lot.

So I figured, since (1) I also love Ghost in the Shell, (2) I do typesetting semi-professionally, and (3) why the heckers not, I could probably get it down to a more reasonable size.

And I did. And then AmevelloBlue gave me permission to share it here, so.

The Drive Folder With All the Files.

File-specific information below. :)

(Please, for the love of Donnie's banana pancakes, read it. I am trying to answer as many technical questions in advance as I can, so people don't get overwhelmed or confused or frustrated.)

(But also it is a LOT of information, so if you need clarification please ask. This is for to be fun! Not scary!)

There are three parts.

GitS.p8: This is the straight PDF export, done in pages and not spreads. That means each page is its own page (a spread has 2+ to a page) and the pages are in order. If you want a pretty PDF to read on a device, this is what you want. If you want to run it through your own imposition software, this is also what you want.

GitS.p8_typeset: This is the imposition. That means the pages have been rearranged into signatures and spreads for bookbinding. There are 16 pages, or 8 spreads, or 4 sheets of paper (printed double-sided) to each signature. Each signature gets stacked, folded into a booklet, and then stacked on top of the next signature for sewing the book block. THIS IS THE WHOLE BOOK. If you want ONE file to send to the printer, in one straight run, this is what you want.

signatures (folder): These are INDIVIDUAL SIGNATURES. That means each signature is a separate file. If you want to do a test print of a single signature, this is what you want. If you want to run different signatures through different printers, this is what you want. If you want to do this piecemeal for any other reason, this is what you want.

(The last three signatures are three sheets of paper, not four. This is for the sake of balancing page count against structural integrity in the bound book.)

Why would you want different printers, you ask?

Because color printing is expensive. And I used color in the typeset.

The entire thing is designed to still be readable (and pretty!) in a regular, black-and-white printer. Because I wanted this to be accessible to everyone, not just people who can afford color printing. But if you want to split it, and send the signatures-with-colored-bits to a color printer, and save money by NOT sending the whole book, these are the signatures with colored bits:

0, 5, 7, 11, 13, 14, 25, 26, 28, 35

And if that's too many pages still, here are the signatures with the most important colored bits (i.e., the title pages and the illustrations):

0, 7, 35

All of the files are PDFs. All of them, specifically, are PDF/x-1a(2003), which means the color profile is CMYK only and all the fonts are embedded. So nothing should go screwy-whompus when you download it or send it to the printer.

TRIM SIZE: the pages are 5x7.5. This is (1) to allow printing on letter-sized paper more easily, and (2) to also allow for trimming of the book block without screwing over the margins. The imposition and the signature files have trimming / cutting guides (the little lines) for your convenience.

There are 36 signatures total, or 560-something pages (less than 200 sheets of paper, before folding, if printed double-sided). This is still a big book. Big enough that you will need to know about spine swell, and possible rounding and backing, if you decide to do the binding. Please keep that in mind as you plan your project.

EPUB: some people like to convert PDF book files to ePUBs for eBook reading. Due to how I designed the typeset, this is not going to be pretty if you try it with these. I am currently in the final stages of making the eBook for GitS, and will upload the ePUB to the drive folder as soon as it's done. It will not have the pretty background / border illustrations of the print file, but it will be neat and tidy and include the pretty title pages.

I... think that's everything?