How to become an author

This is the complete crash course on the Elliptic Curves Cryptography used in Bitcoin and other blockchains. With code samples and a live demo from scratch.

There is one only too obvious problem with relativity of simultaneity in the way it is normally introduced, and I have never found an answer to it – what’s more, I never read or heard anyone formulate it. I will be grateful for an enlightening discussion.

The framework of the thought experiment introducing relativity of simultaneity is this. Two rays of light travel in opposite directions and reach their destination simultaneously in one frame of reference and at different moments in the other.

For example, in the Wikipedia article on the subject you can read:

‘A flash of light is given off at the center of the traincar just as the two observers pass each other. For the observer on board the train, the front and back of the traincar are at fixed distances from the light source and as such, according to this observer, the light will reach the front and back of the traincar at the same time.

‘For the observer standing on the platform, on the other hand, the rear of the traincar is moving (catching up) toward the point at which the flash was given off, and the front of the traincar is moving away from it. As the speed of light is finite and the same in all directions for all observers, the light headed for the back of the train will have less distance to cover than the light headed for the front. Thus, the flashes of light will strike the ends of the traincar at different times’.

I am always not a little surprised at the modesty displayed by the authors of such illustrations. If we grant the statement ‘the light headed for the back of the train will have less distance to cover than the light headed for the front’ to be true – how then do we evaluate the magnitude of the effect? Or, in other words, how much longer is one distance in comparison to the other?

Recipe for improving your productivity

The present invention relates to an analog signal capturing devices generally and monochrome or color image capture sensors, such as a scanner or a Charge-Coupled-Device (“CCD”) for video and photo camera in particular, which are almost free from moiré and aliasing. The present invention relates to methods for enhancing the resolution of an image capture device and device for digital color/grey image displaying also.

On average, online store users make 64 clicks before adding a product to the cart. Some clicks are useful - so-called discovery clicks that help lead to users finding a product they wish to buy, and some are useless that come as the result of poor UX. With great competition for convenience and increasingly reducing attention spans of users, each useless click reduces the number of visitors that will reach checkout.

17-19 min read

Hi y'all, my name is Labertte and I use Arch btw.
Probably like every other Linux user, I'd like to buy a ThinkPad, put some lightweight distribution like Arch or Gentoo on it, and then go to Starbucks, get a soy latte and tell everyone that I use "linux". But I decided to go a little different route and give a chance to my old laptop that I was using about five or seven years ago.

Problems of multithreaded servers with blocking I/O

Author: Denis Zherdetskiy

I know that my article can help a designer who spends a lot of time working and not feeling his or her growth. This article has some tips on how to start building your soft skills.

In this article, I would like to describe how we’ve tackled the named entity recognition (aka NER) issue at Sber with the help of advanced AI techniques. It is one of many natural language processing (NLP) tasks that allows you to automatically extract data from unstructured text. This includes monetary values, dates, or names, surnames and positions.

Just imagine countless textual documents even a medium-sized organisation deals with on a daily basis, let alone huge corporations. Take Sber, for example: it is the largest financial institution in Russia, Central and Eastern Europe that has about 16,500 offices with over 250,000 employees, 137 million retail and 1.1 million corporate clients in 22 countries. As you can imagine, with such an enormous scale, the company collaborates with hundreds of suppliers, contractors and other counterparties, which implies thousands of contracts. For instance, the estimated number of legal documents to be processed in 2022 has been over 65,000, each of them consisting of 30 pages on average. During the lifecycle of a contract, a contract usually updated with 3 to 5 additional agreements. On top of this, a contract is accompanied by various source documents describing transactions. And in the PDF format, too.

Previously, the processing duty befell our service centre’s employees who checked whether payment details in a bill match those in the contract and then sent the document to the Accounting Department where an accountant double-checked everything. This is quite a long journey to a payment, right?

An example of using Electron + React JS and a native ffmpeg addon to access a webcamera

This guide may be helpful to someone who is trying to find a way
to work with Electron if they need to use a c++ library or code

I was looking for a more realistic example than a simple 'hello world' and i didn't succeed

Here are the links in advance:

- electron - https://github.com/khomin/electron_camera_ffmpeg

- addon - https://github.com/khomin/electron_ffmpeg_addon_camera

So let me share my experience...

In Rust strings can be represented in two ways:

a)       String type

b)      String slice

String type:

String type is defined as a struct of the following structure:

Depending on arch (in my case x86 64bit it is 24byte)

{

   pointer to the address where string characters are stored (8b)

   capacity (8b)

   length (8b)

}

In this article I'd like to describe different traffic mirroring options for HPE Virtual Connect modules. I try to answer two questions: "What options work and why?" and "How different traffic mirroring cases can be implemented?"

This article describes how to develop a real-time weather prediction app in Flutter using the Tomorrow.io Weather API. The app consists of a single screen that displays the current weather and a 4-day daily forecast for a specific location. We’re creating this prediction app on Flutter because it is an open-source UI development kit, which means it can be integrated beautifully into desktop and mobile apps across various platforms, making it scalable. 

Today, we will share some knowledge points related to resource memory leak. A memory leak is the most common issue that we continuously see and also are afraid of. What is the reason behind it? Because we can’t predict the extent of the leak before we locate the leak bottleneck, we had no idea whether it will burst out at a certain moment on the line. We have received feedback from developers that their players had no problem playing for half an hour, but they would get more and more stuck after 3 to 4 hours of playing, which they never expected before. How can it be solved? Today’s sharing will answer such questions.

UWA’s GOT Online-Assets report has a resource occupancy trend chart. If there is a rising trend like the one below, you must pay special attention.

I reinstalled both Windows and Linux (Fedora) recently on a notebook PC, and I decided to write the summary article about my experience with both OS. I'm also going to describe how to configure each OS via command-line and set up a dual-boot system.

Demid Efremov and Ivan Kornienko.

Music box on Verilog HDL for Cyclone IV.

Application Programming Interfaces or API’s are responsible for majority of system integration and functional components of modern computing landscape in both consumer and enterprise environments.

Properly constructed secure API’s provide significant benefits during initial build, integration with other systems and during entire application lifecycle while protecting sensitive information stored in business systems.

Based on author's experience designing and implementing API’s for variety of clients in financial, insurance, telecom and public sectors, security is often overlooked in favor of simplistic, vendor/product specific solutions.

This article addresses best practices for API security design in product neutral manner to help architects to plan and build easy to work with and secure API's.

Recommended approach is to separate API security from its business functionality and allow back-end developers to concentrate only on business functions. Once business logic for an API is ready, it can be published using common security components described in this article.

This article does not provide any product specific recommendations, but any modern API security/governance platform will be able to satisfy majority of suggested requirements using out-of-the-box functionality.

Hi everyone, today I will tell how I restored a defunct LVM thinpool. Unfortunately I could not find any howtos or manuals on the internet, so maybe this one will help someone in a similar situation.

JiraCLI is an interactive command line tool for Atlassian Jira that will help you avoid Jira UI to some extent. This tool is not yet considered complete but has all the essential features required to improve your workflow with Jira.

The tool started with the idea of making issue search and navigation as straightforward as possible. However, the tool now includes all necessary features like issue creation, cloning, linking, ticket transition, and much more.

The tool supports both jira cloud and on-premise jira installation since the latest release.

When we move towards the digital world, we shouldn’t forget that cybersecurity has been playing a major role in our life. Talks about digital security have been stiff. The main challenge we would face is abnormality.

During an online transaction, most of the product-lovers prefer credit cards. The credit limit available in credit cards would allow us to purchase even when our bank balance is insufficient. But this is great news for cyber attackers eyeing your money.

For tackling this problem, we should depend upon a system to make hardpressed transactions effortless.

This is where we need a system to track the transaction patterns. With AI, we can abort any abnormal transaction, precisely for credit card fraud detection AI.

As of now, we will come across a number of machine learning algorithms to classify unusual transactions where Artificial Intelligence detect fraud. We only need past data and the right algorithm to fit the data in the right form in case of credit card fraud detection ai.

How do we make this happen? Let’s look into the process of credit card fraud detection AI:

Import the needed libraries

The best step to detect credit card fraud detection with AI is to import the libraries. The best practice would be to import the necessary libraries in a single section for the purpose of quick modification. To use the credit card data, we can use the PCA’s transformed version or RFECV, RFE, VIF and SelectKBest to get the best model features.

Import Dataset

Machine learning helps with fraud detection. It’s quite simple to import the dataset when you use the pandas module in python. You can run the run command for importing your data.