#Interpolation Techniques Online Help | Explore Tumblr posts and blogs

nancy-resma · 5 months ago

Text

Unlocking the Power of AI Image Expansion: Revolutionizing Image Quality and Resizing

Introduction: AI Expand Image

In recent years, AI-driven technologies have revolutionized image processing, allowing for faster and more efficient techniques to expand and enhance images. "AI expand image" refers to using artificial intelligence algorithms to increase the resolution and detail of an image without sacrificing quality. This has become a game-changer in industries like digital marketing, e-commerce, and photography.

AI image expansion leverages deep learning models to predict and generate missing details when enlarging images, which traditionally lose sharpness and clarity when scaled. With AI, users can upscale images while maintaining resolution, leading to enhanced visual appeal and improved user engagement.

What is AI Image Expansion?

AI image expansion is a method used to increase the resolution of images through artificial intelligence. This process involves utilizing algorithms, primarily based on deep learning, to predict and create additional pixels in an image when it is resized or expanded. Unlike traditional image resizing techniques that often result in pixelation, AI-powered expansion works to enhance image clarity by intelligently adding new details and enhancing existing ones.

This AI technology relies on neural networks that have been trained on vast amounts of data to understand patterns and textures. As a result, AI can successfully enlarge an image without the typical blurriness or pixelation that occurs with conventional methods. Whether used for personal projects or professional purposes, AI image expansion is becoming a crucial tool for many industries that rely heavily on visual content.

How AI Image Expansion Works

Ai expand image works by utilizing advanced neural networks trained on large datasets. These networks analyze the structure, color, and patterns within an image to determine how to best add new pixels when the image is scaled up. The AI processes this information and generates new data to fill in the gaps, ensuring that the image remains sharp and visually appealing.

When you use AI for image expansion, the algorithm essentially predicts the missing pixels based on learned data, making intelligent adjustments to preserve natural textures, lines, and details. This is why AI-generated upscaling often looks more accurate and realistic compared to conventional resizing techniques, which rely purely on interpolation methods.

Benefits of Using AI for Image Expansion

The benefits of using AI for image expansion are numerous. First and foremost, AI enables high-quality enlargements, making it possible to upscale images without losing clarity or introducing pixelation. Traditional resizing methods often degrade image quality, especially when scaling images to large sizes, but AI expansion ensures the images remain sharp and clear.

Moreover, AI image expansion can significantly save time. For professionals in fields like e-commerce or digital marketing, manually enhancing images is a time-consuming process. AI automates much of the work, allowing users to focus on more important tasks. It also provides a cost-effective solution, especially for businesses that regularly require high-quality images for product listings, advertisements, or marketing materials.

Common Applications of AI Image Expansion

AI image expansion is widely used in various industries. In product photography, for example, e-commerce retailers often need high-resolution product images for online stores. AI image expansion allows them to quickly upscale photos to meet specific resolution requirements while maintaining high visual quality.

In marketing and advertising, companies can use AI to enhance promotional images for print or digital campaigns. By expanding the images to meet the necessary size requirements, brands can ensure their visuals are crisp and appealing to customers.

In online retail, AI-powered expansion helps ensure that product images look appealing across all platforms, including mobile and desktop. High-quality images are crucial for online shopping, where the customer’s experience is often centered around the visual aspect of the products.

AI Image Expansion in Professional Photography

Professional photographers also benefit from AI image expansion. Many photographers work with high-quality images that need to be printed in large formats or used in various media. AI-driven image upscaling allows photographers to maintain the integrity of the image while resizing it for different use cases, whether it’s for a print advertisement or a large exhibition display.

Case studies show that photographers can rely on AI image expansion to save time during post-processing and deliver high-quality results to clients. By using AI algorithms to enlarge images, photographers can achieve the desired results without the need for labor-intensive techniques, making their workflow more efficient.

Challenges and Limitations of AI Image Expansion

While AI image expansion offers remarkable advantages, there are certain challenges and limitations. One limitation is the quality of the original image. If the original image is of very low quality, AI expansion may struggle to generate accurate details, resulting in less satisfactory results.

Another issue is resolution limitations. AI image expansion may not always be able to restore intricate details or produce true-to-life results in very low-resolution images. Some distortion or blurring may still occur, especially when enlarging images by a significant factor.

Moreover, there are also ethical concerns regarding the manipulation of images. AI can be used to artificially enhance images, which raises questions about the authenticity and integrity of visual content.

AI Image Expansion vs. Traditional Image Resizing

AI image expansion offers several advantages over traditional image resizing techniques. Traditional methods, such as bicubic or bilinear interpolation, involve calculating intermediate pixel values when resizing an image. These methods can lead to blurry or pixelated images, especially when enlarging an image significantly.

AI image expansion, on the other hand, uses deep learning to predict missing pixels and enhance existing ones. This approach results in much sharper, more accurate upscaled images. Additionally, AI can handle complex patterns and textures in ways that traditional resizing methods cannot, producing more natural-looking images.

Future Trends in AI Image Expansion

The future of AI image expansion is promising. As AI technology continues to advance, we can expect more precise and efficient image enhancement. The integration of generative adversarial networks (GANs) and other advanced machine learning models is expected to improve the accuracy of image upscaling further, with better handling of fine details and textures.

AI expansion tools will also become more accessible to individuals and businesses alike, with easier-to-use interfaces and more automated processes. The use of AI in the design and photography industry will likely continue to grow as the demand for high-quality visual content increases.

Conclusion

AI image expansion is revolutionizing the way businesses and photographers handle image resizing and enhancement. Its ability to upscale images without losing quality offers significant benefits for industries like e-commerce, marketing, and photography. As AI technology continues to evolve, its potential to improve image quality and streamline workflows will be crucial for businesses looking to stay competitive in the digital landscape.

For businesses that rely on high-quality visual content, incorporating AI image expansion tools can drastically improve productivity and visual appeal. Additionally, integrating AI with a product photography app can further streamline the process, enabling businesses to create crisp, high-resolution product images with ease.

#b2b

0 notes

iit-jam · 7 months ago

Text

IIT JAM Syllabus 2025: A Comprehensive Guide

The IIT JAM (Joint Admission Test for Masters) is one of the most competitive exams for students aspiring to pursue postgraduate studies in esteemed institutions like IITs and IISc. Mathematics, being a core subject, attracts candidates with strong analytical and problem-solving skills. To excel in this exam, a thorough understanding of the IIT JAM Mathematics Syllabus 2025 is essential. This blog outlines the syllabus in detail and provides tips to help candidates prepare effectively.

Overview of IIT JAM Mathematics Syllabus 2025

The IIT JAM Mathematics Syllabus 2025 is crafted to test the candidates' knowledge of fundamental mathematical concepts covered at the undergraduate level. The syllabus is broad, covering topics such as calculus, linear algebra, differential equations, and numerical analysis. Each section focuses on key areas that are crucial for advanced studies and professional applications.

Key Topics in the Syllabus

1. Sequences and Series

This section includes the convergence of sequences and series, tests for convergence (such as comparison, ratio, and root tests), and the study of power series and their radius of convergence.

2. Differential Calculus

Candidates must understand single-variable calculus concepts like limits, continuity, and differentiability. Topics also include Taylor series, mean value theorem, and indeterminate forms. For multivariable calculus, partial derivatives, maxima, minima, saddle points, and the method of Lagrange multipliers are essential.

3. Integral Calculus

This section covers definite and indefinite integrals, improper integrals, and special functions like beta and gamma functions. The application of double and triple integrals is also emphasized.

4. Linear Algebra

A critical area of the syllabus, it focuses on vector spaces, subspaces, linear transformations, rank, nullity, eigenvalues, eigenvectors, and matrix diagonalization. Understanding the solution of systems of linear equations is vital.

5. Real Analysis

This section involves the properties of real numbers, limits, continuity, differentiability, and Riemann integration. Candidates must also be familiar with sequences, Cauchy sequences, and uniform continuity.

6. Ordinary Differential Equations (ODEs)

This includes first-order ODEs, linear differential equations with constant coefficients, systems of linear ODEs, and Laplace transform techniques for solutions.

7. Vector Calculus

Important topics include gradient, divergence, curl, line integrals, surface integrals, and volume integrals, along with Green’s, Stokes’, and Gauss divergence theorems.

8. Group Theory

The basics of groups, subgroups, cyclic groups, Lagrange’s theorem, permutation groups, and homomorphisms are covered.

9. Numerical Analysis

This section focuses on numerical solutions for non-linear equations, numerical integration and differentiation, interpolation methods, and error analysis.

Tips for Preparing the Syllabus

Understand the Weightage: Review past papers to prioritize high-scoring topics like Linear Algebra, Real Analysis, and Differential Calculus.

Strategize Your Study Plan: Divide the syllabus into manageable sections, set achievable goals, and stick to a consistent schedule.

Practice Regularly: Solve previous years’ papers and mock tests to familiarize yourself with the question patterns and improve speed.

Strengthen Fundamentals: Focus on core concepts by revisiting undergraduate textbooks and seeking clarity on challenging topics.

Leverage Online Resources: Utilize tutorials, study materials, and practice tests available online to supplement your preparation.

Conclusion

The IIT JAM Mathematics Syllabus 2025 is extensive yet well-structured, providing a clear framework for aspirants to plan their preparation. By mastering the syllabus and practicing diligently, candidates can confidently tackle the exam and achieve their dream of joining top postgraduate programs. Dedicate time, stay consistent, and focus on strengthening your mathematical foundations to excel in IIT JAM Mathematics 2025.

0 notes

ryunochie · 4 years ago

Text

MME Laughing Man FX READING: a translation by ryuu

The following tutorial is an English translation of the original one in Japanese by Dance Intervention P.

Disclaimer: coding isn’t my area, not even close to my actual career and job (writing/health). I have little idea of what’s going on here and I’m relying on my IT friends to help me with this one.

Content index:

Introduction

Overall Flow

Parameter Declaration

Billboard Drawing

Final Notes

1. INTRODUCTION

This documentation shows how to edit the Laughing Man effect and read its HLSL coding. Everything in this tutorial will try to stay as faithful as possible to the original one in Japanese

It was translated from Japanese to English by ryuu. As I don’t know how to contact Dance Intervention P for permission to translate and publish it here, the original author is free to request me to take it down. The translation was done with the aid of the online translator DeepL and my friends’ help. This documentation has no intention in replacing the original author’s.

Any coding line starting with “// [Japanese text]” is the author’s comments. If the coding isn’t properly formatted on Tumblr, you can visit the original document to check it. The original titles of each section were added for ease of use.

2. OVERALL FLOW (全体の流れ)

Prepare a flat polygon that faces the screen (-Z axis) direction.

Perform world rotation and view rotation inversion on objects.

Convert coordinates as usual.

World rotation and view rotation components cancel each other out and always face the screen.

3. PARAMETER DECLARATION (パラメータ宣言)

4 // site-specific transformation matrix

5 float4x4 WorldViewProjMatrix : WORLDVIEWPROJECTION;

6 float4x4 WorldViewMatrixInverse : WORLDVIEWINVERSE;

• WorldViewProjMatrix: a matrix that can transform vertices in local coordinates to projective coordinates with the camera as the viewpoint in a single step.

• WorldViewMatrixInverse: the inverse of a matrix that can transform vertices in local coordinates to view coordinates with the camera as the viewpoint in a single step.

• Inverse matrix: when E is the unit matrix for a matrix A whose determinant is non-zero, the matrix B that satisfies AB=BA=E is called the inverse of A and is denoted by A-1 . Because of this property, it’s used to cancel the transformation matrix.

• Unit matrix: asquare matrix whose diagonal component is 1 and the others are 0. When used as a transformation matrix, it means that the coordinates of the vertices are multiplied by 1. In other words:

8 texture MaskTex : ANIMATEDTEXTURE <

9 string ResourceName = "laughing_man.png";

10 >;

• ANIMATEDTEXTURE: textures that animate in response to frame time. Animated GIF and animated PNG (APNG) are supported.

• APNG: Mozilla Corporation's own specified animation format that is backward compatible with PNG. I hacked libpng to support it, but it was rejected by the PNG group because the specification isn’t aesthetically pleasing.

11 sampler Mask = sampler_state {

12 texture = <MaskTex>;

13 MinFilter = LINEAR;

14 MagFilter = LINEAR;

15 MipFilter = NONE;

16 AddressU = CLAMP;

17 AddressV = CLAMP;

18 };

• MinFilter: methods used for the reduction filter.

• MagFilter: methods used for the expansion filter.

• MipFilter: methods used for MIPMAP.

• AdressU: method used to resolve u-texture coordinates that are outside the 0-1 range.

• AdressV: method used to resolve v-texture coordinates that are outside the 0-1 range.

• LINEAR: bilinear interpolation filtering. Uses a weighted average region of 2×2 texels inscribed in the pixel of interest.

• NONE: disable MIPMAP and use the expansion filter.

• CLAMP: texture coordinates outside the range [0.0, 1.0] will have a texture color of 0.0 or 1.0, respectively.

• MIPMAP: a set of images that have been precomputed and optimized to complement the main texture image. Switch between images depending on the level of detail.

21 static float3x3 BillboardMatrix = {

22 normalize(WorldViewMatrixInverse[0].xyz),

23 normalize(WorldViewMatrixInverse[1].xyz),

24 normalize(WorldViewMatrixInverse[2].xyz),

25 };

Obtain the rotation scaling component xyz of the inverse matrix, normalize it by using normalize, and extract the rotation component. Do this for each row. The 4x4 inverse matrix contains a translation component in the fourth row, so it’s cut off and made into a 3x3 matrix.

The logical meaning of the matrix hasn’t been investigated yet. Without normalization, the size of the display accessory is 1/10, which suggests that the world expansion matrix component is used as the unit matrix. Also, each row corresponds to an x,y,z scale.

29 struct VS_OUTPUT

30 {

31 float4 Pos : POSITION; // projective transformation coordinates

32 float2 Tex : TEXCOORD0; // texture coordinates

33 };

A structure for passing multiple return values between shader stages.

4. BILLBOARD DRAWING (ビルボード描画)

35 // vertex shader

36 VS_OUTPUT Mask_VS(float4 Pos : POSITION, float2 Tex : TEXCOORD0)

37 {

38 VS_OUTPUT Out;

40 // billboard

41 Pos.xyz = mul( Pos.xyz, BillboardMatrix );

BillboardMatrix is a 3x3 rotation matrix, so multiply it by the xyz3 component of Pos.

If the object is fixed in the world and doesn’t rotate, then Pos.xyz = mul(Pos.xyz, (float3x3)ViewInverseMatrix); or Pos.xyz = mul(Pos.xyz, (float3x3)ViewTransposeMatrix); cancels the screen rotation. Since the rotation matrix is an orthogonal matrix, the transpose and inverse matrices are equal.

42 // world-view projection transformation of camera viewpoint.

43 Out.Pos = mul( Pos, WorldViewProjMatrix );

45 // texture coordinates

46 Out.Tex = Tex;

48 return Out;

49 }

Perform world-view projection transformation and return the structure as usual.

51 // pixel shader

52 float4 Mask_PS( float2 Tex :TEXCOORD0 ) : COLOR0

53 {

54 return tex2D( Mask, Tex );

55 }

Return the color of the texture retrieved from the sampler.

57 technique MainTec < string MMDPass = "object"; > {

58 pass DrawObject {

59 ZENABLE = false;

60 VertexShader = compile vs_1_1 Mask_VS();

61 PixelShader = compile ps_2_0 Mask_PS();

62 }

63 }

Self-shadow disabled? (technique is ignored by object_ss when enabled), run without depth information.

• ZENABLE: enable seismic intensity information (Z buffer) when drawing pixels and make drawing decisions.

5. FINAL NOTES

For further reading on HLSL coding, please visit Microsoft’s official English reference documentation.

#mmd tutorial #mmd #mmdc #translation #coding #tutorial #mikumikueffect #mikuMikuDance

3 notes · View notes

matlabhwexperts-blog · 7 years ago

Text

Interpolation Techniques Homework Help

https://www.matlabhomeworkexperts.com/interpolation-techniques-assignment-help.php

Students can even avail our online tutoring sessions at reasonable cost. Our Matlab Interpolation Techniques tutors are capable of teaching all kind of techniques in the simplest way so that you can understand it easily. Interpolation Techniques Projects and assignment solved by our experts have helped many students across the world to achieve higher grades. Our main motto is to provide constant guidelines to the students in the subject area and make them learn the concepts in simplistic yet succinct manner. We frequently receive requests from students for help with the below mentioned topics and types of Interpolation Techniques. Hence, we have a team with expertise in these topics to help you out. Linear Interpolation and Geometric Ratios Multivariate interpolation Newton–Cotes formulas NIST Digital Library of Mathematical Functions Piecewise Linear Interpolation Polynomial evaluation & interpolation Repeated Linear Interpolation Simple rational approximation Two-dimensional Interpolation

#Interpolation Techniques Homework Help #Interpolation Techniques Assignment Help #Interpolation Techniques Homework Help Experts #Interpolation Techniques Project Help #Interpolation Techniques Online Help #Online Interpolation Techniques Homework Help #Interpolation Techniques Help

0 notes

newscvv · 5 years ago

Text

E-skimming cyberattack is growing along with online shopping

During the busy vacation procuring season late final yr, firearms maker American Outdoor Brands observed an issue with one in every of its web sites, which sells principally hats, shirts and equipment.

The website, it turned out, was topic to an e-skimming assault over Thanksgiving, the place a sort of malware contaminated its checkout pages to steal fee and private data of buyers. The firm, previously referred to as Smith & Wesson, says the incident affected about 780 folks.

“Our first action upon learning of the attack was to disable the checkout function on the site to reduce the amount of individuals impacted,” Elizabeth Sharp, vice chairman of investor relations, mentioned in a press release to CNBC. “During the investigation we found the malware and identified when the malicious code was placed on the site.”

Skimmers, or hidden units designed to steal bank card data, have lengthy been a menace for customers on the fuel pump or ATM. Now, skimming has gone high-tech and hackers can steal your data in a extra insidious and profitable method. This kind assault is often known as Magecart.

Just this week, the primary arrests had been introduced for the crime. Interpol, which helps coordinate police companies in 194 nations, said Monday it arrested three people from Indonesia who allegedly compromised lots of of on-line procuring web sites. It mentioned the suspects stole fee card particulars and private information corresponding to names, addresses and cellphone numbers.

Companies giant and small have been hit by e-skimming assaults prior to now two years, including Macy’s in October, Puma’s Australian website in April and Ticketmaster’s United Kingdom website in June 2018. Macy’s, Puma and Ticketmaster didn’t reply to CNBC’s request for remark.

“Any retailer that has a significant online presence that accepts online orders is definitely concerned about e-skimming. This has been in the news recently, and even big-name stores have been hit,” mentioned Randy Pargman, senior director for menace looking and counterintelligence at Binary Defense, an Ohio-based cybersecurity firm that screens firms’ computer systems for indicators of assaults. The firm will not disclose its shoppers however says many are within the retail sector.

Cybercriminals can compromise web sites in some ways, together with breaking into the net server straight or breaking into a standard server that helps many on-line procuring web sites, to compromise all of them. One instance of an online shopping service is Magento, which was acquired by Adobe in 2018 for greater than $1.6 billion. The Magecart identify for this kind of assault comes from Magento however can seek advice from assaults on different software program as properly.

“Magento is committed to delivering security to our customers, as well as helping to maintain that security,” mentioned Gaby Yim, a spokeswoman for Adobe. “As the majority of exploits tend to target software installations that are not up to date with the latest security updates, we always strongly recommend that users install security updates as soon as they are available.”

The FBI says e-skimming has been on its radar for almost seven years however the crime is rising as a result of cybercriminals are sharing the malware on-line and changing into extra refined.

“If you are a company that has a heavy volume of credit card numbers being inputted into your website, at that point, you’re probably at a higher risk,” mentioned Herb Stapleton, part chief for the FBI’s cyber division. “Now one thing about those types of companies is often they have more resources to invest in cybersecurity measures. So as a result of that, even some lower-traffic companies, some smaller and medium-sized businesses, are still at risk because some of them may not have the resources to invest as heavily in their cybersecurity.”

The precise variety of web sites compromised is unknown, however Stapleton mentioned thousands and thousands of bank cards have been stolen, and that’s simply what’s reported to the FBI. The true quantity is probably going larger.

Unlike conventional skimming, the criminals behind the assault don’t want bodily entry to allow them to be positioned wherever on the earth.

“Cybercriminals have a harder time now stealing the credit card information from cash registers or point-of-sale terminals. That’s where you physically swipe your card or you dip the chip cards. The reason is because the technology for those point-of-sale systems has become better,” mentioned Binary Defense’s Pargman.

E-skimming, or Magecart, is a cybersecurity hacking approach that steals data as the buyer places it right into a on-line procuring web site. This is a demo of what the attacker can see.

Source: CNBC

Retailers who’re compromised face reputational threat.

“That’s why companies put a lot of effort into making sure that their security is good, so they don’t have to notify consumers that they had lost their data because of a lapse in security,” Pargman mentioned.

In addition, firms can face stiff fines for not having the techniques in place to guard their shopper’s data. British Airways is dealing with an almost $230 million high-quality for an information breach involving about half one million clients. British Airways didn’t reply to CNBC’s request for remark.

In order to guard themselves, Pargman says firms want to remain on prime of system updates and monitor their servers.

“There’s records of what’s happening on the web server. You need to monitor those to make sure that there’s no signs of an attacker who’s logging on and taking control of the web server,” he mentioned.

For customers, it may be troublesome to forestall having their data taken. Consumers ought to use bank cards as an alternative of debit playing cards when procuring on-line to reduce any inconvenience if their card is compromised, Pargman mentioned. Users of bank cards normally have decrease legal responsibility for fraud. In addition, getting cash returned to your debit card can take a while.

Another tip is to think about using a digital bank card, Pargman mentioned. Some banks and bank card firms supply the choice to create a singular bank card quantity for use for particular transactions. If this quantity is compromised, different costs can be declined.

Consumers must also monitor their playing cards for any uncommon exercise and report it immediately, he mentioned.

“It’s nearly impossible for a consumer to detect that this has happened to them before the actual occurrence. The site that they would look at, which is already infected, would look no different to a consumer,” the FBI’s Stapleton mentioned.

The post E-skimming cyberattack is growing along with online shopping appeared first on CVV NEWS.

from WordPress https://cvvnews.com/e-skimming-cyberattack-is-growing-along-with-online-shopping/

1 note · View note

thecoroutfitters · 6 years ago

Link

Get the Scoop on Discreetly Definition Before You’re Too Late

The underboob tattoo is really a perfect tattoo if you should appear tattoo-free at work. All cells contain the specific DNA. Proteins occupy quite some of roles in the body.

In the end, it’s not simply because pleasure comes from seeing or hearing that it’s beautiful. A person is never guilty of another person’s sin. A good explanation will surely offer you best suit.

college essay

How parents and caregivers react to their kid’s temperament can impact the kid and their general well-being. The choice to sleep with somebody who’s not her husband will be entirely her choice. Inside this regard, if you may not or don’t want to grow in your own house, and choose to do so elsewhere, do your best not to arouse suspicions.

Understand what you’ve got to stomach. Luckily, it’s quite simple to temporarily disable it. In case it occurs, believe on your very own fortunate.

The very first floor positioning of powder rooms allows guests to use the facilities without feeling as if they’ve intruded in your house. It’s kind of like attempting to grab a candy bar from a vending machine during the most important door. It is normally a very small room that is conveniently located and rarely contains a window.

Discreetly Definition and Discreetly Definition – The Perfect Combination

This spelling is not difficult to remember because the 2 es in the second syllable are discrete from one another. http://www.bu.edu/zhanglab/ The top-level internet sites demand a good price tag of rate for those solutions provided. The frequency column isn’t about the question so it can be ignored.

The absolute most important rule is that you want to get connected to TFVC server to perform the the vast majority of these actions. Numerical analysis offers an important example. No approximation or interpolation is essential.

One of the absolute most important aims of the technology acquisition procedure is to objectify a subjective decision about which vendor and solution is most effective for your circumstance. Evaluation In order to decide on the best model, it’s critical to measure and assess forecast accuracy. Our costs incorporate the most competitive sold on the market and what’s more, you may constantly get affordability.

As soon as you have finished the research, it’s the right time to rate the outcome and decide on a vendor. In other words, the central dogma states that it results in RNA which, then, leads to protein. After that there are lots of kinds of RNA.

The whole process doesn’t require energy in order to take place. The biggest and most excited development characteristics that are going to be added to Digital Twin will be linked to its accuracy and simplicity of usage. essay writer online Because of this gain in the acquisition of technology, there’s a demand for a project life cycle that project managers can utilize to manage an acquisition undertaking.

The collection of the site has to be very carefully done while buying sex toys online so as to avoid receiving the incorrect product at a larger price. Our company can’t condemn it on them all. All orders are shipped from the United States, so expect extra shipping time for international delivery.

Here’s What I Know About Discreetly Definition

If you wish to grind with a guy and look good when doing it, you will need to understand a few things to do it the correct way. How to remember things is only a technique that you must utilize, for example to attempt to keep in mind a face you just need to examine somebody’s face discretely whenever you’re introduced. Ahead of making a choice to time anybody, it is truly constantly excellent to comprehend what she anticipates from you.

If your qualities captivate her, she’s going to manage for the approaching time and get in contact with you. When there’s no true reason aside from attraction, escalate that touch. Additionally, it serves to reinforce the dual nature of the principal characters.

There are a lot of reasons for this. Since everyone can create learning resources efficiently, more content can be developed by people who best understand the requirements of the learners. TV ads are a sort of outbound marketing, also called interruption marketing, which relies on interrupting viewers in a bid to obtain their attention.

You’re no different from anyone you merely have certain preferences when it has to do with the people that you love, no-one should have the right to ask you that. To make things simpler, we don’t provide a wholly rigorous definition inside this lecture. Pansexual folks are attracted to all types of people, irrespective of their gender, sex or presentation.

With such a wide variety of opportunities to select from, being an expert guard is among the few careers that truly has a place to fit any personality type or preference. Again, it will help to spend some time considering your motives, because they’ll be questioned by the majority of people. There are many genders, and while some trans people don’t fit into the conventional gender binary, some do.

from Patriot Prepper Don't forget to visit the store and pick up some gear at The COR Outfitters. Are you ready for any situation? #SurvivalFirestarter #SurvivalBugOutBackpack #PrepperSurvivalPack #SHTFGear #SHTFBag

#SHTF #TEOTWAWKI #MARTIALLAW #BUGOUT #PREPPERBAG #USAF #USSOCOM #ARMY #NAVY #SurvivalFirestarter #Sur

2 notes · View notes

twixtor-crack-tk · 3 years ago

Text

Download Twixtor crack (license key) latest version BEN!

💾 ►►► DOWNLOAD FILE 🔥🔥🔥 Conclusion: Twixtor Crack 7. Users can switch between and also insert among the fixed point frameworks. The benefit of this WordPress plugin over similar extensions is the increased reliability for this plugin Twixtor 7 Crack Cagion, which allows it to control the product better than other resources, and at one-third the number of components. The highest framework rates make it possible to create picture slow-downs, which can make something that is legendary. It is likely to in conjunction with an enunciation of these needs. It works effectively to boost the cost of your framework reduction by interpolation and bending of the terme advice from the initial series. The quality of your films will improved by using Twixtor 7 Activation Key. The application offers basic course motion suggestions. Silicon tape can also employ different speeds of movement within a space, such as certain unique results for movies. Twixtor 7 Pro Crack can help you to include slow-motion for your movies, following the progress you may creating for your films. The speed parameters suffer from the fact that they are causing us to shift our pace limitations. The framework-by-framework option allows us to make the development of key plans that can framed. We can get an extensive understanding of frames. It helps you create plenty of amazing outcomes. The free version of it Download on Mac provides additional data on capabilities available. It gives you the ability to manage media content and the ability to give the system precision levels. It will allow you to go one step ahead of the standard form interpolation, which often ends up with fuzzy buildings that fall in between or out of form online videos. Give examples of how to work using the present platform. Twixtor 7 Premiere Pro Crack is a commonly used tool to make continuous motion recordings, focusing on little thought to create high-quality recordings. This type of solution allows to, among other things the creation of excellent pieces by utilizing select clip parts without the need to record photographs using costly and expert equipment. The video will more precise structurally when you add interpolation. Upgrade your video quality. If your video is a part of frames that are already present, fewer artifacts will visible. Producing high-quality products using specific elements, this method is a way to do business that lets you do other things. You can enhance and reduce the speeds of sequences of images. By twisting the housing, you could make your clasp adaptable. The applications make it easy to modify sizes. The drawback is the lack of options. A film that is incorrectly deformed or constantly blurred film. Additionally, the Twixtor 7 Key kind of technique allows only one among the people to create high-quality films from specific regions. The advantage of this program over other similar alternatives is the greater reliability that comes with Twixtor 7. This function is known as a sufficient period wrap. This software has many wonderful features to use. Speed up and slow down the movie to improve the quality of your situation. It can remap the sound and movie using its extensive remapping tools. Twixtor 7. A music group with rubberized edges is usually made in a photograph which allows you to achieve astonishing outcomes. It will make your work and business more attractive and appealing. In addition, it allows you to create top-quality products using the best elements of the cut, without having to take pictures with specialists and expensive equipment. It enhances the pleasure with a similar effect, but at smaller frames per second, but with the same quality. It will affect their videos. Mac or Windows users can benefit from this feature. Making your videos more appealing is as simple as creating powerful effects. Twixtor Premiere Pro Crack 7. There are silicone bands that do similar results. This software can use to speed up and slow down your video clips very quickly. Making a video with an extremely high rate of structuring is achievable through interpolating and warping the sequences. Contrary to Consequences regular shape interpolation, Twitter can go higher than it. Videos with blurred edges can include in your photos. This can significantly increase the security that your equipment has. It also permits products to manufactured using specific materials, in addition to enhancing the quality of products. The benefit of using this plugin in conjunction with other plugins is the greater quality of Twixtor 7. The program allows you to create using many popular editors. Twitter helps you to activate all the top elements free of cost to make use of the program. It is possible to download Twixtor 7. The program is designed to be able to perform and manage the scope of stunning, moderately improved impacts beyond the norm that is expected of shopping mall editors. To direct the impact estimates, this program creates unique designs that are not found in the others who rely on only a small percentage of pixels that are a part of the constantly evolving structure. Twixtor Mac Crack 7. The most up-to-date version that is available of the Twixtor 7. This is accomplished by an elastic band that allows for incredible effects within one scene. This program is amazing in the way it presents new designs using the bending technique. There is also an incredible following technique that determines the evolution of each pixel. This means that it can create singular edges that are created by cutting and interjecting edges that were present in the previous series. The program burns down less time and allows you to rebuild with constantly easily accessible speed settings. Additionally, the twister crack is simple and free software. It makes a top-quality system and then selects the components to make the records of photos. Motion vectors are then able to be utilized in other parts of the pipeline. The points could be manually placed in any framework. There is also a spline-based advice feature that can be used. Substitute for automatically enhancing dark images or photos with undefined edges. Key framable retiming that allows for total control of a body-by-body basis. The slow impact development formula can develop a new framework. Why do we need a Twixtor 7. World-class motion estimation Twixtor 7. This is a result of less tearing as well as stretching objects when they move across or beyond the frame. You can easily and without a stretch proselytize the edge rate using this program. The option to regulate the retiming process on a frame-by-frame basis is always in place! This program allows you to stamp the material using cuts. Furthermore, the application allows you to effectively deal with interwoven material. Incredible visual effects To create the best image quality To achieve the highest quality image , we created a unique system for tracking that computes the motion for each pixel, which allows us to create unique frames by interpolating and warping frames from that original sequence. This is especially helpful for CG masking, masked, or keyed materials. We can say that the film is free of images or high-quality equipment. You can add a professional look to your recordings by incorporating stunning effects. With the tracking points, you can specify to this the location of a pixel between one frame, guiding the calculation of motion vectors by it. Application designed to slow down or more films. Display examples that are compatible with the framework that is already in use. When making video the frame rate does not require compensation. A lower frame rate will yield the same effect. It is also possible to edit software INFO Twitter allows you to accelerate the speed, decrease the speed or frame rate transforms your image sequences to produce stunning visual results. To create stunning images, Twixtor 7. In many instances footage that was hard to follow becomes efficient after changing the timing. There is an option to add or remove motion blur as needed. Intelligent processing of interlaced material. Twixtor Crack is then able to track each layer independently for better results. Provide it motion vectors from other sources like from a 3D device to time-remap footage, and even add motion-interpolated fields onto otherwise motion-related material. This feature is extremely powerful and is accompanied by visual debugging modes to allow you to better evaluate and improve the accuracy of the estimation process. A few of the features of this are as follows. There was a service to create the separation of background from foreground using certain mattes. To improve the quality of the result it tracks each layer separately. It includes Track Point Guidance. It has about 12 user-defined parameters that can specified to aid it specialists in motion estimation. Key Features Of Twixtor 7 Key: Twixtor Premiere Pro Crack can make the choices and also improves the dark pictures on the form of a contact form that is described. We find this as the creator of bending and interpolation costs to a time-bending type of video. Expanding your series using the person dimension variables is easy and easy. Eliminate or block motions that are not known. The system gives you the complete instruction video. Create different effects for video Additionally, professional instruments allow you to slow or speed up recordings. Restarting multiple times slower than the current one. Supports all video editors. Stunning visual results. Furthermore, easy edge rate adjustment for degree video Resizes the video by setting the speed. This gives better management control. Useful for dull photos Makes movement clearer or less obvious. Additionally, allows users to import vectors of movement. Include different effects to recordings. A powerful tool to slow or speed up recordings. Recordings can restart up to a few times faster than running Most video editors are supported. Twitter macintosh free produces shocking visual effects, as well as easy edge rate change. Continue degree video Resizes the film using a one-speed setting. Additionally, adding or removing movement obscure allows you to import motion vectors. The software incorporates. The application can monitor degree images and synchronize them precisely, taking into account each angle. This program allows you to reset the timing of your sequences using a one-speed setting. It is possible to enhance dull images or images with poorly defined edges. Tools Of Twixtor 7 Crack: Speed changes: Create an array that permits the use of a single-speed parameter. Frames by frames: Twixtor Key programming keyframes in a way that allows full structure with the control of frames. Frame rate conversion — simple frame rate conversions are simplified. Motion Blur: This is a way to remove or add motion blurs, based on the need. Enhance dark images: A method to enhance dark images or photos with weak edges. Additionally, in many instances, concepts that were hard to identify work much better when they are reprogrammed. Not offered for DaVinciResolve. Interlaced Processing: Innovative processing and manipulation of interlaced materials. Benefits Of Twixtor 7. The program includes plugins that are already in use. A plugin could a competitor to Media composer , smooth image, etc. The program will provide you with an entire instructional video guideline. The software works with every film studio. Resets shots with one-speed parameter. Improved tire control. Motion blur can removed or added. Broadcast transmissions are permitted. Twixtor Pro Crack is the most recently released version that will available in The latest version can run effectively on bit operating systems. It also allows surveillance of the most powerful traffic. The program creates un-petalled images and quality videos. It provides alternatives and improves the dark images in a specified format. This version also addresses GPU acceleration issues that can cause crashes. Also, it extends its sequences and increases the size of the parameters. This program is used to create smooth as well as video clips direct.

1 note · View note

twixtor-crack-1q · 3 years ago

Text

Download Twixtor crack (serial key) latest version 9HJV?

1 note · View note

twixtor-crack-cc · 3 years ago

Text

Download Twixtor crack (serial key) latest version HDD;

1 note · View note

thedatasciencehyderabad · 4 years ago

Text

Courses You will learn picture processing techniques, noise discount using moving average strategies, various kinds of filters - smoothing the image by averaging, Gaussian filter and the disadvantages of correlation filters. You will study several types of filters, boundary effects, template matching, price of change within the intensity detection, several types of noise, image sampling and interpolation strategies. Learn about single-layered Perceptrons, Rosenblatt’s perceptron for weights and bias updation. Weights updating strategies - Windrow-Hoff Learning Rule & Rosenblatt’s Perceptron. You may have a excessive degree understanding of the human mind, significance of a number of layers in the Neural Network, extraction of features layers clever, composition of the data in Deep Learning utilizing an image, speech and text. Under Linear Algebra, you'll be taught sets, operate, scalar, vector, matrix, tensor, primary operations and totally different matrix operations. Under Probability one will study Uniform Distribution, Normal Distribution, Binomial Distribution, Discrete Random Variable, Cumulative Distribution Function and Continuous Random Variables. It is mostly geared toward choice makers and individuals who want to decide on what knowledge is price collecting and what is value analyzing. For example, an analyst can arrange an algorithm which can reach a conclusion routinely primarily based on extensive knowledge source. This course has been designed for people excited about extracting that means from written English textual content, although the knowledge may be applied to different human languages as nicely. Exercises after each matter have been actually helpful, regardless of there were too complicated at the finish. In common, the introduced materials was very attention-grabbing and involving! The coaching provided the best basis that permits us to further to broaden on, by exhibiting how concept and follow go hand in hand. Logistic regression Logistic Regression is likely one of the hottest ML algorithms, like Linear Regression. It is a straightforward classification algorithm to predict the categorical dependent variables with the assistance of impartial variables. This module will drive you through all the concepts of Logistic Regression utilized in Machine Learning. Multiple Variable Linear regression Linear Regression is among the most popular ML algorithms used for predictive analysis in Machine Learning, resulting in producing the best outcomes. It is a method assuming a linear relationship between the unbiased variable and dependent variable. Hypothesis Testing This module will teach you about Hypothesis Testing in Machine Learning utilizing Python. Hypothesis Testing is a needed process in Applied Statistics for doing experiments primarily based on the noticed/surveyed data. In this Machine Learning online course, we talk about supervised standalone fashions’ shortcomings and be taught a number of strategies, similar to Ensemble methods to overcome these shortcomings. Dimension Reduction-PCA Principal Component Analysis for Dimensional Reduction is a technique to scale back the complexity of a model like eliminating the variety of input variables for a predictive mannequin to avoid overfitting. I am very grateful to them for successfully and sincerely serving to me to seize first ever opportunity that came into my life. The Bureau of Labour Statistics predicts a development rate of 21 percent—a lot faster than common—by 2028 for software builders, together with the addition of 284,a hundred jobs. Software engineers additionally make a median wage of $eighty four,336 per yr, with potential increases for these with a specialty in AI. As these people are on the crux of development in AI, their job outlook could be very positive. The Department of AI @ IIT Hyderabad's mission is to produce college students with a sound understanding of the fundamentals of the idea and practise of Artificial Intelligence and Machine Learning. The mission can also be to enable students to turn out to be leaders in

the trade and academia nationally and internationally. Finally, the mission is to fulfill the pressing calls for of the nation in the areas of Artificial Intelligence and Machine Learning. They also interact area experts who are working in great MNC firms to coach the scholars on initiatives on weekends and likewise to mentor all the school members on the latest tendencies and main applied sciences. Also, the web training is to develop the worker requirements on a really professional efficiency level that in flip aggravates the important proficiency of all the corporates. They are broadly utilized in text mining and pure language processing tasks. Preprocessing text data Text preprocessing is the tactic to clean and put together text data. This module will teach you all the steps involved in preprocessing a text like Text Cleansing, Tokenization, Stemming, etc. Semantic segmentation The goal of semantic segmentation in computer vision is to label every pixel of the enter image with the respective class representing a specific object/physique. Collaborative filtering (User similarity & Item similarity) Collaborative Filtering is a joint utilization of algorithms where there are a number of methods to determine similar customers or objects to counsel the best suggestions. Popularity based mostly model Popularity based mostly model is a kind of advice system that works based on recognition or something that's presently trending. We lined lots of matters in the time and the trainer was all the time receptive to speaking more intimately or extra generally concerning the subjects and how they were related. I really feel the training has given me the tools to continue learning versus it being a one off session where studying stops as soon as you've finished which is essential given the dimensions and complexity of the subject. Inferential Statistics This module will let you explore elementary concepts of using information for estimation and assessing theories using Python. Pandas, NumPy, Matplotlib, Seaborn This module will give you a deep understanding of exploring data units utilizing Pandas, NumPy, Matplotlib, and Seaborn. Python capabilities, packages and routines Functions and Packages are used for code reusability and program modularity, respectively. Understanding the architecture of RBM and the method concerned in it. Understand and implement Long Short-Term Memory, which is used to maintain the data intact, unless the input makes them overlook. You may also be taught the components of LSTM - cell state, forget gate, input gate and the output gate together with the steps to course of the data. Learn the distinction between RNN and LSTM, Deep RNN and Deep LSTM and completely different terminologies. You will be taught to build an object detection model utilizing Fast R-CNN by utilizing bounding packing containers, understand why fast RCNN is a more sensible choice while dealing with object detection. You may even learn by occasion segmentation issues which could be prevented using Mask RCNN. It permits us to uncover patterns and insights, often with visual methods, inside knowledge. In this module, you will discover ways to collect information and predict the future worth of data specializing in its distinctive trends. Neural Machine Translation Neural Machine Translation is a task for machine translation that uses a synthetic neural network, which automatically converts supply textual content in a single language to the textual content in another language. Introduction to Sequential models A sequence, because the name suggests, is an ordered assortment of several objects. This module will train you how to use the TensorBoard library using Python for Machine Learning. This block will train you how TensorBoard offers the visualization and tooling required for machine studying experimentation. In this module, you'll learn how to improve the productivity of deploying your Machine Learning fashions. In this module, you will discover ways to improve your Machine Learning mannequin’s productiveness Using Flask.

Exploratory Data Analysis, or EDA, is essentially a kind of storytelling for statisticians.@ IIT Hyderabad's mission is to produce college students with a sound understanding of the fundamentals of the idea and practise of Artificial Intelligence and Machine Learning. The mission can also be to enable students to turn out to be leaders in the trade and academia nationally and internationally. Finally, the mission is to fulfill the pressing calls for of the nation in the areas of Artificial Intelligence and Machine Learning. They also interact area experts who are working in great MNC firms to coach the scholars on initiatives on weekends and likewise to mentor all the school members on the latest tendencies and main applied sciences. Also, the web training is to develop the worker requirements on a really professional efficiency level that in flip aggravates the important proficiency of all the corporates. They are broadly utilized in text mining and pure language processing tasks. Preprocessing text data Text preprocessing is the tactic to clean and put together text data. This module will teach you all the steps involved in preprocessing a text like Text Cleansing, Tokenization, Stemming, etc. Semantic segmentation The goal of semantic segmentation in computer vision is to label every pixel of the enter image with the respective class representing a specific object/physique. Collaborative filtering (User similarity & Item similarity) Collaborative Filtering is a joint utilization of algorithms where there are a number of methods to determine similar customers or objects to counsel the best suggestions. Popularity based mostly model Popularity based mostly model is a kind of advice system that works based on recognition or something that's presently trending. We lined lots of matters in the time and the trainer was all the time receptive to speaking more intimately or extra generally concerning the subjects and how they were related. I really feel the training has given me the tools to continue learning versus it being a one off session where studying stops as soon as you've finished which is essential given the dimensions and complexity of the subject. Inferential Statistics This module will let you explore elementary concepts of using information for estimation and assessing theories using Python. Pandas, NumPy, Matplotlib, Seaborn This module will give you a deep understanding of exploring data units utilizing Pandas, NumPy, Matplotlib, and Seaborn. Python capabilities, packages and routines Functions and Packages are used for code reusability and program modularity, respectively. Understanding the architecture of RBM and the method concerned in it. Understand and implement Long Short-Term Memory, which is used to maintain the data intact, unless the input makes them overlook. You may also be taught the components of LSTM - cell state, forget gate, input gate and the output gate together with the steps to course of the data. Learn the distinction between RNN and LSTM, Deep RNN and Deep LSTM and completely different terminologies. You will be taught to build an object detection model utilizing Fast R-CNN by utilizing bounding packing containers, understand why fast RCNN is a more sensible choice while dealing with object detection. You may even learn by occasion segmentation issues which could be prevented using Mask RCNN. It permits us to uncover patterns and insights, often with visual methods, inside knowledge. In this module, you will discover ways to collect information and predict the future worth of data specializing in its distinctive trends. Neural Machine Translation Neural Machine Translation is a task for machine translation that uses a synthetic neural network, which automatically converts supply textual content in a single language to the textual content in another language. Introduction to Sequential models A sequence, because the name suggests, is an ordered assortment of several objects. This module will train you how to use the TensorBoard library using Python for Machine

Learning. This block will train you how TensorBoard offers the visualization and tooling required for machine studying experimentation. In this module, you'll learn how to improve the productivity of deploying your Machine Learning fashions. In this module, you will discover ways to improve your Machine Learning mannequin’s productiveness Using Flask. Exploratory Da seeta Analysis, or EDA, is essentially a kind of storytelling for statisticians.

Navigate to Address: 360DigiTMG - Data Analytics, Data Science Course Training Hyderabad 2-56/2/19, 3rd floor,, Vijaya towers, near Meridian school,, Ayyappa Society Rd, Madhapur,, Hyderabad, Telangana 500081 099899 94319

0 notes

ryunochie · 4 years ago

Text

MMD FX file reading for shaders: a translation by ryuu

The following tutorial is an English translation of the original one in Japanese by Dance Intervention P.

This English documentation was requested by Chestnutscoop on DeviantArt, as it’ll be useful to the MME modding community and help MMD become open-source for updates. It’s going to be an extensive one, so take it easy.

Content Index:

Introduction

Overall Flow

Parameter Declaration

Outline Drawing

Non-Self-shadow Rendering

Drawing Objects When Self-shadow is Disabled

Z-value Plot For Self-shadow Determination

Drawing Objects in Self-shadowing

Final Notes

1. INTRODUCTION

This documentation contains the roots of .fx file reading for MME as well as information on DirectX and programmable shaders while reading full.fx version 1.3. In other words, how to use HLSL for MMD shaders. Everything in this tutorial will try to stay as faithful as possible to the original text in Japanese.

2. OVERALL FLOW (全体の流れ)

Applicable technique → pass → VertexShader → PixelShader

• Technique: processing of annotations that fall under <>.

• Pass: processing unit.

• VertexShader: convert vertices in local coordinates to projective coordinates.

• PixelShader: sets the color of a vertex.

3. PARAMETER DECLARATION (パラメータ宣言)

9 // site-specific transformation matrix

10 float4x4 WorldViewProjMatrix : WORLDVIEWPROJECTION;

11 float4x4 WorldMatrix : WORLD;

12 float4x4 ViewMatrix : VIEW;

13 float4x4 LightWorldViewProjMatrix : WORLDVIEWPROJECTION < string Object = “Light”; >;

• Float4x4: 32-bit floating point with 4 rows and 4 columns.

• WorldViewProjMatrix: a matrix that can transform vertices in local coordinates to projective coordinates with the camera as the viewpoint in a single step.

• WorldMatrix: a matrix that can transform vertices in local coordinates into world coordinates with the camera as the viewpoint.

• ViewMatrix: a matrix that can convert world coordinate vertices to view coordinates with the camera as the viewpoint.

• LightWorldViewProjMatrix: a matrix that can transform vertices in local coordinates to projective coordinates with the light as a viewpoint in a single step.

• Local coordinate system: coordinates to represent the positional relationship of vertices in the model.

• World coordinate: coordinates to show the positional relationship between models.

• View coordinate: coordinates to represent the positional relationship with the camera.

• Projection Coordinates: coordinates used to represent the depth in the camera. There are two types: perspective projection and orthographic projection.

• Perspective projection: distant objects are shown smaller and nearby objects are shown larger.

• Orthographic projection: the size of the image does not change with depth.

15 float3 LightDirection : DIRECTION < string Object = “Light”; >;

16 float3 CameraPosition : POSITION < string Object = “Camera”; >;

• LightDirection: light direction vector.

• CameraPosition: world coordinates of the camera.

18 // material color

19 float4 MaterialDiffuse : DIFFUSE < string Object = “Geometry”; >;

20 float3 MaterialAmbient : AMBIENT < string Object = “Geometry”; >;

21 float3 MaterialEmmisive : EMISSIVE < string Object = “Geometry”; >;

22 float3 MaterialSpecular : SPECULAR < string Object = “Geometry”; >;

23 float SpecularPower : SPECULARPOWER < string Object = “Geometry”; >;

24 float3 MaterialToon : TOONCOLOR;

25 float4 EdgeColor : EDGECOLOR;

• float3: no alpha value.

• MaterialDiffuse: diffuse light color of material, Diffuse+A (alpha value) in PMD.

• MaterialAmbient: ambient light color of the material; Diffuse of PMD?

• MaterialEmmisive: light emitting color of the material, Ambient in PMD.

• MaterialSpecular: specular light color of the material; PMD’s Specular.

• SpecularPower: specular strength. PMD Shininess.

• MaterialToon: shade toon color of the material, lower left corner of the one specified by the PMD toon texture.

• EdgeColor: putline color, as specified by MMD’s edge color.

26 // light color

27 float3 LightDiffuse : DIFFUSE < string Object = “Light”; >;

28 float3 LightAmbient : AMBIENT < string Object = “Light”; >;

29 float3 LightSpecular : SPECULAR < string Object = “Light”; >;

30 static float4 DiffuseColor = MaterialDiffuse * float4(LightDiffuse, 1.0f);

31 static float3 AmbientColor = saturate(MaterialAmbient * LightAmbient + MaterialEmmisive);

32 static float3 SpecularColor = MaterialSpecular * LightSpecular;

• LightDiffuse: black (floa3(0,0,0))？

• LightAmbient: MMD lighting operation values.

• LightSpecular: MMD lighting operation values.

• DiffuseColor: black by multiplication in LightDiffuse?

• AmbientColor: does the common color of Diffuse in PMD become a little stronger in the value of lighting manipulation in MMD?

• SpecularColor: does it feel like PMD’s Specular is a little stronger than MMD’s Lighting Manipulation value?

34 bool parthf; // perspective flags

35 bool transp; // semi-transparent flag

36 bool spadd; // sphere map additive synthesis flag

37 #define SKII1 1500

38 #define SKII2 8000

39 #define Toon 3

• parthf: true for self-shadow distance setting mode2.

• transp: true for self-shadow distance setting mode2.

• spadd: true in sphere file .spa.

• SKII1:self-shadow A constant used in mode1. The larger the value, the weirder the shadow will be, and the smaller the value, the weaker the shadow will be.

• SKII2: self-shadow A constant used in mode2. If it is too large, the self-shadow will have a strange shadow, and if it is too small, it will be too thin.

• Toon: weaken the shade in the direction of the light with a close range shade toon.

41 // object textures

42 texture ObjectTexture: MATERIALTEXTURE;

43 sampler ObjTexSampler = sampler_state {

44 texture = <ObjectTexture>;

45 MINFILTER = LINEAR;

46 MAGFILTER = LINEAR;

47 };

• ObjectTexture: texture set in the material.

• ObjTexSampler: setting the conditions for acquiring material textures.

• MINIFILTER: conditions for shrinking textures.

• MAGFILTER: conditions for enlarging a texture.

• LINEAR: interpolate to linear.

49 // sphere map textures

50 texture ObjectSphereMap: MATERIALSPHEREMAP;

51 sampler ObjSphareSampler = sampler_state {

52 texture = <ObjectSphereMap>;

53 MINFILTER = LINEAR;

54 MAGFILTER = LINEAR;

55 };

• ObjectSphereMap: sphere map texture set in the material.

• ObjSphareSampler: setting the conditions for obtaining a sphere map texture.

57 // this is a description to avoid overwriting the original MMD sampler. Cannot be deleted.

58 sampler MMDSamp0 : register(s0);

59 sampler MMDSamp1 : register(s1);

60 sampler MMDSamp2 : register(s2);

• register: assign shader variables to specific registers.

• s0: sampler type register 0.

4. OUTLINE DRAWING (輪郭描画)

Model contours used for drawing, no accessories.

65 // vertex shader

66 float4 ColorRender_VS(float4 Pos : POSITION) : POSITION

67 {

68 // world-view projection transformation of camera viewpoint.

69 return mul( Pos, WorldViewProjMatrix );

70 }

Return the vertex coordinates of the camera viewpoint after the world view projection transformation.

Parameters

• Pos: local coordinates of the vertex.

• POSITION (input): semantic indicating the vertex position in the object space.

• POSITION (output): semantic indicating the position of a vertex in a homogeneous space.

• mul (x,y): perform matrix multiplication of x and y.

Return value

Vertex coordinates in projective space; compute screen coordinate position by dividing by w.

• Semantics: communicating information about the intended use of parameters.

72 // pixel shader

73 float4 ColorRender_PS() : COLOR

74 {

75 // fill with outline color

76 return EdgeColor;

77 }

Returns the contour color of the corresponding input vertex.

Return value

Output color

• COLOR: output color semantic.

79 // contouring techniques

80 technique EdgeTec < string MMDPass = "edge"; > {

81 pass DrawEdge {

82 AlphaBlendEnable = FALSE;

83 AlphaTestEnable = FALSE;

85 VertexShader = compile vs_2_0 ColorRender_VS();

86 PixelShader = compile ps_2_0 ColorRender_PS();

87 }

88 }

Processing for contour drawing.

• MMDPASS: specify the drawing target to apply.

• “edge”: contours of the PMD model.

• AlphaBlendEnable: set the value to enable alpha blending transparency. Blend surface colors, materials, and textures with transparency information to overlay on another surface.

• AlphaTestEnable: per-pixel alpha test setting. If passed, the pixel will be processed by the framebuffer. Otherwise, all framebuffer processing of pixels will be skipped.

• VertexShader: shader variable representing the compiled vertex shader.

• PixelShader: shader variable representing the compiled pixel shader.

• vs_2_0: vertex shader profile for shader model 2.

• ps_2_0: pixel shader profile for shader model 2.

• Frame buffer: memory that holds the data for one frame until it is displayed on the screen.

5. NON-SELF-SHADOW SHADOW RENDERING (非セルフシャドウ影描画)

Drawing shadows falling on the ground in MMD, switching between showing and hiding them in MMD's ground shadow display.

94 // vertex shader

95 float4 Shadow_VS(float4 Pos : POSITION) : POSITION

96 {

97 // world-view projection transformation of camera viewpoint.

98 return mul( Pos, WorldViewProjMatrix );

99 }

Returns the vertex coordinates of the source vertex of the shadow display after the world-view projection transformation of the camera viewpoint.

Parameters

• Pos: local coordinates of the vertex from which the shadow will be displayed.

Return value

Vertex coordinates in projective space.

101 // pixel shader

102 float4 Shadow_PS() : COLOR

103 {

104 // fill with ambient color

105 return float4(AmbientColor.rgb, 0.65f);

106 }

Returns the shadow color to be drawn. The alpha value will be reflected when MMD's display shadow color transparency is enabled.

Return value

Output color

108 // techniques for shadow drawing

109 technique ShadowTec < string MMDPass = "shadow"; > {

110 pass DrawShadow {

111 VertexShader = compile vs_2_0 Shadow_VS();

112 PixelShader = compile ps_2_0 Shadow_PS();

113 }

114 }

Processing for non-self-shadow shadow drawing.

• “shadow”: simple ground shadow.

6. DRAWING OBJECTS WHEN SELF-SHADOW IS DISABLED (セルフシャドウ無効時オブジェクト描画)

Drawing objects when self-shadowing is disabled. Also used when editing model values.

120 struct VS_OUTPUT {

121 float4 Pos : POSITION; // projective transformation coordinates

122 float2 Tex : TEXCOORD1; // texture

123 float3 Normal : TEXCOORD2; // normal vector

124 float3 Eye : TEXCOORD3; // position relative to camera

125 float2 SpTex : TEXCOORD4; // sphere map texture coordinates

126 float4 Color : COLOR0; // diffuse color

127 };

A structure for passing multiple return values between shader stages. The final data to be passed must specify semantics.

Parameters

• Pos:stores the position of a vertex in projective coordinates as a homogeneous spatial coordinate vertex shader output semantic.

• Tex: stores the UV coordinates of the vertex as the first texture coordinate vertex shader output semantic.

• Normal: stores the vertex normal vector as the second texture coordinate vertex shader output semantic.

• Eye: (opposite?) stores the eye vector as a #3 texture coordinate vertex shader output semantic.

• SpTex: stores the UV coordinates of the vertex as the number 4 texture coordinate vertex shader output semantic.

• Color: stores the diffuse light color of a vertex as the 0th color vertex shader output semantic.

129 // vertex shader

130 VS_OUTPUT Basic_VS(float4 Pos : POSITION, float3 Normal : NORMAL, float2 Tex : TEXCOORD0, uniform bool useTexture, uniform bool useSphereMap, uniform bool useToon)

131 {

Converts local coordinates of vertices to projective coordinates. Sets the value to pass to the pixel shader, which returns the VS_OUTPUT structure.

Parameters

• Pos: local coordinates of the vertex.

• Normal: normals in local coordinates of vertices.

• Tex: UV coordinates of the vertices.

• useTexture: determination of texture usage, given by pass.

• useSphereMap: determination of sphere map usage, given by pass.

• useToon: determination of toon usage. Given by pass in the case of model data.

• uniform: marks variables with data that are always constant during shader execution.

Return value

VS_OUTPUT, a structure passed to the pixel shader.

132 VS_OUTPUT Out = (VS_OUTPUT)0;

133

Initialize structure members with 0. Error if return member is undefined.

134 // world-view projection transformation of camera viewpoint.

135 Out.Pos = mul( Pos, WorldViewProjMatrix );

136

Convert local coordinates of vertices to projective coordinates.

137 // position relative to camera

138 Out.Eye = CameraPosition - mul( Pos, WorldMatrix );

The opposite vector of eye? Calculate.

139 // vertex normal

140 Out.Normal = normalize( mul( Normal, (float3x3)WorldMatrix ) );

141

Compute normalized normal vectors in the vertex world space.

• normalize (x): normalize a floating-point vector based on x/length(x).

• length (x): returns the length of a floating-point number vector.

142 // Diffuse color + Ambient color calculation

143 Out.Color.rgb = AmbientColor;

144 if ( !useToon ) {

145 Out.Color.rgb += max(0,dot( Out.Normal, -LightDirection )) * DiffuseColor.rgb;

By the inner product of the vertex normal and the backward vector of the light, the influence of the light (0-1) is calculated, and the diffuse light color calculated from the influence is added to the ambient light color. DiffuseColor is black because LightDifuse is black, and AmbientColor is the diffuse light of the material. Confirmation required.

• dot (x,y): return the inner value of the x and y vectors.

• max (x,y): choose the value of x or y, whichever is greater.

146 }

147 Out.Color.a = DiffuseColor.a;

148 Out.Color = saturate( Out.Color );

149

• saturate (x): clamp x to the range 0-1. 0>x, 1>x truncated?

150 // texture coordinates

151 Out.Tex = Tex;

152

153 if ( useSphereMap ) {

154 // sphere map texture coordinates

155 float2 NormalWV = mul( Out.Normal, (float3x3)ViewMatrix );

X and Y coordinates of vertex normals in view space.

156 Out.SpTex.x = NormalWV.x * 0.5f + 0.5f;

157 Out.SpTex.y = NormalWV.y * -0.5f + 0.5f;

158 }

159

Converts view coordinate values of vertex normals to texture coordinate values. Idiomatic.

160 return Out;

161 }

Return the structure you set.

163 // pixel shader

164 float4 Basic_PS(VS_OUTPUT IN, uniform bool useTexture, uniform bool useSphereMap, uniform bool useToon) : COLOR0

165 {

Specify the color of pixels to be displayed on the screen.

Parameters

• IN: VS_OUTPUT structure received from the vertex shader.

• useTexture: determination of texture usage, given by pass.

• useSphereMap: determination of using sphere map, given by pass.

• useToon: determination of toon usage. Given by pass in the case of model data.

Output value

Output color

166 // specular color calculation

167 float3 HalfVector = normalize( normalize(IN.Eye) + -LightDirection );

Find the half vector from the inverse vector of the line of sight and the inverse vector of the light.

• Half vector: a vector that is the middle (addition) of two vectors. Used instead of calculating the reflection vector.

168 float3 Specular = pow( max(0,dot( HalfVector, normalize(IN.Normal) )), SpecularPower ) * SpecularColor;

169

From the half-vector and vertex normals, find the influence of reflection. Multiply the influence by the specular intensity, and multiply by the specular light color to get the specular.

• pow (x,y): multiply x by the exponent y.

170 float4 Color = IN.Color;

171 if ( useTexture ) {

172 // apply texture

173 Color *= tex2D( ObjTexSampler, IN.Tex );

174 }

If a texture is set, extract the color of the texture coordinates and multiply it by the base color.

• tex2D (sampler, tex): extract the color of the tex coordinates from the 2D texture in the sampler settings.

175 if ( useSphereMap ) {

176 // apply sphere map

177 if(spadd) Color += tex2D(ObjSphareSampler,IN.SpTex);

178 else Color *= tex2D(ObjSphareSampler,IN.SpTex);

179 }

180

If a sphere map is set, extract the color of the sphere map texture coordinates and add it to the base color if it is an additive sphere map file, otherwise multiply it.

181 if ( useToon ) {

182 // toon application

183 float LightNormal = dot( IN.Normal, -LightDirection );

184 Color.rgb *= lerp(MaterialToon, float3(1,1,1), saturate(LightNormal * 16 + 0.5));

185 }

In the case of the PMD model, determine the influence of the light from the normal vector of the vertex and the inverse vector of the light. Correct the influence level to 0.5-1, and darken the base color for lower influence levels.

• lerp (x,y,s): linear interpolation based on x + s(y - x). 0=x, 1=y.

186

187 // specular application

188 Color.rgb += Specular;

189

190 return Color;

191 }

Add the obtained specular to the base color and return the output color.

195 technique MainTec0 < string MMDPass = "object"; bool UseTexture = false; bool UseSphereMap = false; bool UseToon = false; > {

196 pass DrawObject {

197 VertexShader = compile vs_2_0 Basic_VS(false, false, false);

198 PixelShader = compile ps_2_0 Basic_PS(false, false, false);

199 }

200 }

Technique performed on a subset of accessories (materials) that don’t use texture or sphere maps when self-shadow is disabled.

• “object”: object when self-shadow is disabled.

• UseTexture: true for texture usage subset.

• UseSphereMap: true for sphere map usage subset.

• UseToon: true for PMD model.

7. Z-VALUE PLOT FOR SELF-SHADOW DETERMINATION (セルフシャドウ判定用Z値プロット)

Create a boundary value to be used for determining the self-shadow.

256 struct VS_ZValuePlot_OUTPUT {

257 float4 Pos : POSITION; // projective transformation coordinates

258 float4 ShadowMapTex : TEXCOORD0; // z-buffer texture

259 };

A structure for passing multiple return values between shader stages.

Parameters

• Pos: stores the position of a vertex in projective coordinates as a homogeneous spatial coordinate vertex shader output semantic.

• ShadowMapTex: stores texture coordinates for hardware calculation of z and w interpolation values as 0 texture coordinate vertex shader output semantics.

• w: scaling factor of the visual cone (which expands as you go deeper) in projective space.

261 // vertex shader

262 VS_ZValuePlot_OUTPUT ZValuePlot_VS( float4 Pos : POSITION )

263 {

264 VS_ZValuePlot_OUTPUT Out = (VS_ZValuePlot_OUTPUT)0;

265

266 // do a world-view projection transformation with the eyes of the light.

267 Out.Pos = mul( Pos, LightWorldViewProjMatrix );

268

Conversion of local coordinates of a vertex to projective coordinates with respect to a light.

269 // align texture coordinates to vertices.

270 Out.ShadowMapTex = Out.Pos;

271

272 return Out;

273 }

Assign to texture coordinates to let the hardware calculate z, w interpolation values for vertex coordinates, and return the structure.

275 // pixel shader

276 float4 ZValuePlot_PS( float4 ShadowMapTex : TEXCOORD0 ) : COLOR

277 {

278 // record z-values for R color components

279 return float4(ShadowMapTex.z/ShadowMapTex.w,0,0,1);

280 }

Divide the z-value in projective space by the magnification factor w, calculate the z-value in screen coordinates, assign to r-value and return (internal MMD processing?).

282 // techniques for Z-value mapping

283 technique ZplotTec < string MMDPass = "zplot"; > {

284 pass ZValuePlot {

285 AlphaBlendEnable = FALSE;

286 VertexShader = compile vs_2_0 ZValuePlot_VS();

287 PixelShader = compile ps_2_0 ZValuePlot_PS();

288 }

289 }

Technique to be performed when calculating the z-value for self-shadow determination.

• “zplot”: Z-value plot for self-shadow.

8. DRAWING OBJECTS IN SELF-SHADOWING (セルフシャドウ時オブジェクト描画)

Drawing an object with self-shadow.

295 // sampler for the shadow buffer. “register(s0)" because MMD uses s0

296 sampler DefSampler : register(s0);

297

Assign sampler register 0 to DefSampler. Not sure when it’s swapped with MMDSamp0 earlier. Not replaceable.

298 struct BufferShadow_OUTPUT {

299 float4 Pos : POSITION; // projective transformation coordinates

300 float4 ZCalcTex : TEXCOORD0; // z value

301 float2 Tex : TEXCOORD1; // texture

302 float3 Normal : TEXCOORD2; // normal vector

303 float3 Eye : TEXCOORD3; // position relative to camera

304 float2 SpTex : TEXCOORD4; // sphere map texture coordinates

305 float4 Color : COLOR0; // diffuse color

306 };

VS_OUTPUT with ZCalcTex added.

• ZCalcTex: stores the texture coordinates for calculating the interpolation values of Z and w for vertices in screen coordinates as the 0 texture coordinate vertex shader output semantic.

308 // vertex shader

309 BufferShadow_OUTPUT BufferShadow_VS(float4 Pos : POSITION, float3 Normal : NORMAL, float2 Tex : TEXCOORD0, uniform bool useTexture, uniform bool useSphereMap, uniform bool useToon)

310 {

Converts local coordinates of vertices to projective coordinates. Set the value to pass to the pixel shader, returning the BufferShadow_OUTPUT structure.

Parameters

• Pos: local coordinates of the vertex.

• Normal: normals in local coordinates of vertices.

• Tex: UV coordinates of the vertices.

• useTexture: determination of texture usage, given by pass.

• useSphereMap: determination of sphere map usage, given by pass.

• useToon: determination of toon usage. Given by pass in the case of model data.

Return value

BufferShadow_OUTPUT.

311 BufferShadow_OUTPUT Out = (BufferShadow_OUTPUT)0;

312

Initializing the structure.

313 // world-view projection transformation of camera viewpoint.

314 Out.Pos = mul( Pos, WorldViewProjMatrix );

315

Convert local coordinates of vertices to projective coordinates.

316 // position relative to camera 317 Out.Eye = CameraPosition - mul( Pos, WorldMatrix );

Calculate the inverse vector of the line of sight.

318 // vertex normal

319 Out.Normal = normalize( mul( Normal, (float3x3)WorldMatrix ) );

Compute normalized normal vectors in the vertex world space.

320 // world View Projection Transformation with Light Perspective

321 Out.ZCalcTex = mul( Pos, LightWorldViewProjMatrix );

Convert local coordinates of vertices to projective coordinates with respect to the light, and let the hardware calculate z and w interpolation values.

323 // Diffuse color + Ambient color Calculation

324 Out.Color.rgb = AmbientColor;

325 if ( !useToon ) {

326 Out.Color.rgb += max(0,dot( Out.Normal, -LightDirection )) * DiffuseColor.rgb;

327 }

328 Out.Color.a = DiffuseColor.a;

329 Out.Color = saturate( Out.Color );

Set the base color. For accessories, add a diffuse color to the base color based on the light influence, and set each component to 0-1.

331 // texture coordinates

332 Out.Tex = Tex;

Assign the UV coordinates of the vertex as they are.

334 if ( useSphereMap ) {

335 // sphere map texture coordinates

336 float2 NormalWV = mul( Out.Normal, (float3x3)ViewMatrix );

Convert vertex normal vectors to x and y components in view space coordinates when using sphere maps.

337 Out.SpTex.x = NormalWV.x * 0.5f + 0.5f;

338 Out.SpTex.y = NormalWV.y * -0.5f + 0.5f;

339 }

340

341 return Out;

342 }

Convert view space coordinates to texture coordinates and put the structure back.

344 // pixel shader

345 float4 BufferShadow_PS(BufferShadow_OUTPUT IN, uniform bool useTexture, uniform bool useSphereMap, uniform bool useToon) : COLOR

346 {

Specify the color of pixels to be displayed on the screen.

Parameters

• IN: BufferShadow_OUTPUT structure received from vertex shader.

• useTexture: determination of texture usage, given by pass.

• useSphereMap: determination of sphere map usage, given by pass.

• useToon: determination of toon usage. Given by pass in the case of model data.

Output value

Output color

347 // specular color calculation

348 float3 HalfVector = normalize( normalize(IN.Eye) + -LightDirection );

349 float3 Specular = pow( max(0,dot( HalfVector, normalize(IN.Normal) )), SpecularPower ) * SpecularColor;

350

Same specular calculation as Basic_PS.

351 float4 Color = IN.Color;

352 float4 ShadowColor = float4(AmbientColor, Color.a); // shadow’s color

Base color and self-shadow base color.

353 if ( useTexture ) {

354 // apply texture

355 float4 TexColor = tex2D( ObjTexSampler, IN.Tex );

356 Color *= TexColor;

357 ShadowColor *= TexColor;

358 }

When using a texture, extract the color of the texture coordinates from the set texture and multiply it by the base color and self-shadow color respectively.

359 if ( useSphereMap ) {

360 // apply sphere map

361 float4 TexColor = tex2D(ObjSphareSampler,IN.SpTex);

362 if(spadd) {

363 Color += TexColor;

364 ShadowColor += TexColor;

365 } else {

366 Color *= TexColor;

367 ShadowColor *= TexColor;

368 }

369 }

As with Basic_PS, when using a sphere map, add or multiply the corresponding colors.

370 // specular application

371 Color.rgb += Specular;

372

Apply specular to the base color.

373 // convert to texture coordinates 374 IN.ZCalcTex /= IN.ZCalcTex.w;

Divide the z-value in projective space by the scaling factor w and convert to screen coordinates.

375 float2 TransTexCoord;

376 TransTexCoord.x = (1.0f + IN.ZCalcTex.x)*0.5f;

377 TransTexCoord.y = (1.0f - IN.ZCalcTex.y)*0.5f;

378

Convert screen coordinates to texture coordinates.

379 if( any( saturate(TransTexCoord) != TransTexCoord ) ) {

380 // external shadow buffer

381 return Color;

Return the base color if the vertex coordinates aren’t in the 0-1 range of the texture coordinates.

382 } else {

383 float comp;

384 if(parthf) {

385 // self-shadow mode2

386 comp=1-saturate(max(IN.ZCalcTex.z-tex2D(DefSampler,TransTexCoord).r , 0.0f)*SKII2*TransTexCoord.y-0.3f);

In self-shadow mode2, take the Z value from the shadow buffer sampler and compare it with the Z value of the vertex, if the Z of the vertex is small, it isn't a shadow. If the difference is small (close to the beginning of the shadow), the shadow is heavily corrected. (Weak correction in the upward direction of the screen?) Weakly corrects the base color.

387 } else {

388 // self-shadow mode1

389 comp=1-saturate(max(IN.ZCalcTex.z-tex2D(DefSampler,TransTexCoord).r , 0.0f)*SKII1-0.3f);

390 }

Do the same for self-shadow mode1.

391 if ( useToon ) {

392 // toon application

393 comp = min(saturate(dot(IN.Normal,-LightDirection)*Toon),comp);

In the case of MMD models, compare the degree of influence of the shade caused by the light with the degree of influence caused by the self-shadow, and choose the smaller one as the degree of influence of the shadow.

• min (x,y): select the smaller value of x and y.

394 ShadowColor.rgb *= MaterialToon;

395 }

396

Multiply the self-shadow color by the toon shadow color.

397 float4 ans = lerp(ShadowColor, Color, comp);

Linearly interpolate between the self-shadow color and the base color depending on the influence of the shadow.

398 if( transp ) ans.a = 0.5f;

399 return ans;

400 }

401 }

If translucency is enabled, set the transparency of the display color to 50% and restore the composite color.

403 // techniques for drawing objects (for accessories)

404 technique MainTecBS0 < string MMDPass = "object_ss"; bool UseTexture = false; bool UseSphereMap = false; bool UseToon = false; > {

405 pass DrawObject {

406 VertexShader = compile vs_3_0 BufferShadow_VS(false, false, false);

407 PixelShader = compile ps_3_0 BufferShadow_PS(false, false, false);

408 }

409 }

Technique performed on a subset of accessories (materials) that don’t use a texture or sphere map during self-shadowing.

• “object-ss”: object when self-shadow is disabled.

• UseTexture: true for texture usage subset.

• UseSphereMap: true for sphere map usage subset.

• UseToon: true for PMD model.

9. FINAL NOTES

For further reading on HLSL coding, please visit Microsoft’s official English reference documentation.

#MMD Tutorial #MMD #MMDC #translation #mikumikueffect #mikumikudance #coding

5 notes · View notes

zhannabelle-eng · 5 years ago

Text

How group activities change your life for the better

6 reasons to join the group

Successful in her career, with her predestination revealed, happy in her personal life. This is what the perfect picture of your life looks like. In the morning, when you open your eyes, you realize that you are still lonely just like before. It is frustrating and you want to feel sorry for yourself, but you have to act to change your life. To make it perfect, like in dreams. How? Start attending Zhannabelle's group classes!

Reason one: to find your perfect partner

So, your perfect partner. You have a good idea of him, don't you? What kind of soul mate do you think he dreams of? I'm sure he dreams of having a stunning, confident, sexy beauty with shining eyes, a charming smile and a kind heart.

He can perform any feat, to do any incredible thing for such a woman.

"It's very interesting," you'll agree, "but there is a small obstacle: this whole story is not about me. No man would perform a feat for me."

You are very wrong about it! This story is about you! You just don't know about it yet. You just have not yet been taught how to reveal the most important superpower of any woman - her femininity. Of course, it's not taught at school or college.

There is good news for you: this is what you will learn at Zhannabelle's group classes. She will teach you the most ancient sacred techniques and practices. Thousands of years ago, the greatest women in the world used them all the time and were happy. With the help of these exercises you can increase your self-confidence. They will save you from problems and activate your sexuality.

These practices turn an ordinary woman into a woman of Power, to whom no worthy person can resist.

What is so special about Zhannabelle's group activities, because they bring great results very quickly? It all happens because people strengthen the energy. The more students participate in a ritual or practice, the greater the effect they give. Thousands of Zhannabelle's students can prove that. Take your chance and see for yourself!

Reason two: to solve all financial issues

You think you'll never have expensive things? You don’t even dare dreaming of a new spacious house in a prestigious area?

It’s not like that! You deserve so much more! Money is energy. You can learn to manage this energy. It's really possible. Zhannabelle speaks about the issue of financial well-being in great detail at her group classes.

How are the group classes unique? Imagine, the universe can see us. A lot of people attend group classes. And when they come together, they practice, for example, to open up a well-being channel. Everyone standing next to you increases the power of this request.

The Universe sees this group not a small particle, but a rather noticeable spot. If you put maximum forces into your emotions, the group will be a luminous sphere, which will be visible from anywhere in the galaxy.

And as a pattern, someone from this group gets a new car as a gift, someone receives a large sum of money unexpectedly, and someone gets a new position and a high income.

If the universe pays attention to you, it will have an immediate and most positive impact on your financial well-being.

Will a boundless substance like the universe be able to see one person? Of course, one universe may not even notice one person alone.

If you stay at home all alone and ask for something, the universe must be able to see and hear you with difficulty, or perhaps not at all.

That means that your wish is unlikely to come true. Or you will have to wait so long for your request to be fulfilled that you will be able to forget what you asked for. That's why group lessons are so effective.

Reason three: to be healthy

We used to get sick from time to time even before the coronavirus outbreak. Women's diseases in general seriously violate the hormonal background, cause infertility, decorate the female face with wrinkles and leave a feeling as if you were run over by a truck. Back and forth.

Doctors prescribe a whole list of drugs and procedures, but they treat not the cause of the disease, but its consequence. Vaccine for exhaustion has not been invented yet.

However, such a vaccine exists and has been known for a long time. It's an amazingly powerful female energy. The higher its level, the stronger, more active and healthier you become. You can not increase this level with the help of sports. But Zhannabelle can. She's not an ordinary person. She's a guide of the Power. Zhannabelle has the highest level of energy and shares it generously with her students.

That's why group lessons have such an incredible effect - many students forget about all their diseases right in the class.

For example, one of Zhannabelle's students, Julia, returned home after another group session. It was only in the evening she noticed there was missing a thing she couldn't do without for the last fifteen years. She left her glasses at the class and didn't even notice that she could do without them until the evening! But Julia had very bad eyesight, which she had lost as a result of her injury many years ago.

Blindness had progressed with each passing year. So the woman couldn't do without her glasses. And besides that, she was constantly suffering from the worst headaches that she had right during the practice. Although post-traumatic migraine tormented her for years, and no drugs or doctors could help her. And, after only one session, the pains disappeared. Forever.

Another Zhannabelle’s student, Nancy, Assistant District Attorney, has been taking pills for over eight years. Her collection included medication for all sorts of diseases. She didn't have time for treatment. She wasn't into a healthy lifestyle either. And the constant stress at work didn't make her healthier.

That's why Nancy lived by the principle: if you get sick - take a pill – and keep going.

After six months of group classes, Nancy found a bunch of drugs in her locker accidentally that she hadn’t taken for months. After all, lately she's only been drinking freshly squeezed juice to keep her alive.

And such stories happen all the time!

Reason four: to find true friends

It was such a fun to have noisy parties with girlfriends when you were a student. Every day, some adventure, an explosion of emotion. Your whole group went to the movies, to a cafe together too. Then everyone did yoga together (and dumped together, but that's not the point). And now all the girlfriends have families or make business. Nobody has time. Finding time for fun together is a whole problem.

You dream of finding your soul mate to be with a person on the same page. You want lively human support, sympathy. Don’t you? So no need to wait in vain for it. Zhannabelle's group activities will be the best option for you to make friends and meet like-minded people. You'll be accepted here for who you are.

Here you will always get help and support, and your success will be enjoyed as if it were their own.

Reason five: to become happy

Everyone understands happiness in their own way. As a rule, we call happiness what we lack. When a child is sick, happiness is their health. When your efforts at work are not appreciated, happiness will be your career advancement. When you suffer from loneliness, happiness is the person you love next to you.

It doesn't matter what is happiness for you. What matters is that it is possible! Zhannabelle's group activities change the lives of all her students. Any problem they come to the class will be definitely solved.

For example, one of Zhannabelle's students, Maria, was convinced that happiness is having her own home. For many years she lived renting a room because she could not afford to buy even a small apartment.

And it would have taken Maria nine lives to pay off the mortgage. Like Felix's cat.

When she came to group classes, Zhannabelle did a diagnostic and gave her special recommendations. Maria did her best, she wouldn't miss them. She bought amulets, watched all of Zhannabelle's videos on YouTube channel, attended seminars and a few months later received a job offer ... in Paris!

She now lives in the heart of this beautiful city in her own cozy apartment and gets a huge salary!

Small one but in a nice area near a big park. Can you believe it? You can meet Maria at Zhannabelle's classes, and ask her yourself))).

Reason six: to avoid fatal mistakes

Why learn from your own mistakes, if someone has already done it before you)))) And you shouldn't believe anyone who says that someone else's experience is useless. Of course it's useful! If we hadn't relied on the experience of our ancestors or other people, we'd clearly be extinct like mammoths.

Zhannabelle's group classes are a great way to learn the priceless experience of other students.

For example, Hannah was able to save ten thousand Euros thanks to the group! During one of classes, she told her friends that she had met a wonderful person online. Maximilian was a famous Spanish football player. They began to have passionate correspondence on the Internet.

The Spaniard was pushy, sang of his love and promised the moon.

A few weeks later he proposed to Hannah, and offered an apartment in the suburbs of Barcelona and a villa in Marbella. To match the wedding dress he sent his bride a diamond tiara, which was once worn by Catherine Medici.

But the precious thing had to be cleared. And that's not cheap, ten thousand Euros. Well, the tiara wasn't ordered from the Chinese website. Of course, Maximilian said he'd pay Hannah back that amount as soon as he came to visit her.

The woman didn't have that sum of money, so she decided to take a loan. Before that, she shared the situation with other students in a group class. They helped her see the story at a different angle. Maximilian turned out to be a classic internet gigolo.

Unfortunately, many of Zhannabelle's students had encountered such scammers in their lives. But now they are better than Interpol to track down any scammer and not become his victim.

Zhannabelle's students told Hannah who Maximilian really is and practically saved her.

So do not hesitate to use someone else's experience, because another bump on your forehead is unlikely to make you more beautiful!)).

Now you know that Zhannabelle's group lessons can solve any of your problems. All of them are effective, but it is communication with the coach always gives a faster effect. If for some reason you don't have the opportunity to participate in the seminars alive now, you shouldn't stand idle. Start changing lives today - register for Zhannabelle online school.

The school consists of several workshops aimed at solving different problems: with relationships, health, career, and predestination. Let this be your first step towards a successful and prosperous life. Zhannabelle will do everything to make it happen.

#group activities #seminar #coaching #zhannabelle #spirituality

0 notes

udemy-gift-coupon-blog · 6 years ago

Link

After Effects CC: Learn Lower Thirds Title & Motion Graphics ##UdemyFreeDiscountCoupons ##UdemyOnlineCourse #CC #Effects #Graphics #Learn #Motion #Thirds #Title After Effects CC: Learn Lower Thirds Title & Motion Graphics Learn Lower Thirds From Scratch! Go from Zero to Build 6 Great Lower Thirds in After Effects CC. All Lower Thirds Project files Included! Master Graphic Design, Lower Thirds, Titles, Text Animation & Motion Graphics in Adobe After Effects CC 2018 (from Novice to Expert) in Less Than 3 Hours! Join the 8,600+ happy students in one of the bestselling After Effects CC course on Udemy! With almost 3 hours of training and practical steps you can follow - this is the most comprehensive Adobe After Effects CC course available. We'll cover After Effects Fundamentals, After Effects Interface, Keyframe Animations, Time Remapping, Text Animators, Keyframe Interpolations, Text Layers, Solids, Shapes, Text Animators and much much more! Just Take a Look at These Top Rated Reviews... ★★★★★ "Before I looked at this course, I thought I had learned something about After Effects, now I realize I know nothing. Brilliant course, I recommend " - Tiriplic Catalin ★★★★★ "This is real helpful. This teaching is not only helpful for creating and animating lower thirds but also creating animation in general. " - Balu Grafix ★★★★★ "good course it takes you to learn new techniques, speed answer and reaction it's need to be more details in it, but its a good start to begin with AfterEffects " - Marwa Al-Soudi ★★★★★ "It's really great! It's the most complete course I've ever seen on udemy for lower thirds in after effects. I recommend it to all new after effects users. Thank you! " - Jacob Wilson ★★★★★ "The course is really helpful so far. Instructor is knowledgeable and I think this is a great course. I highly recommend it if you want to learn how to create professional lower thirds fast and easy. LOVE IT ;) " - Mary Malcom ★★★★★ "Awesome course! Very detailed information. Thank you. " - Bobbie Smith ★★★★★ "Thank you very much for making this course, I have been looking for something like this for a long time :) " - Siyad VP Go from Beginner to Advanced You'll go from beginner to extremely high-level and your instructor will take you through each step on screen. Here is What You Will Gain By Enrolling in Our Course: Create eye-catching and professional lower thirds, titles, text animations & motion graphics in Adobe After Effects CC Create organized and fully qualified After Effects Templates for online Adobe After Effects Marketplaces like VideoHive, MotionElements, MotionArray, Pond5, … Create 4K & FullHD compositions in Adobe After Effects Create smooth animations by using keyframe interpolation techniques Export final lower thirds and titles with an alpha channel to use over your videos Create Color Control System for your lower thirds & titles packages that are an essential part for After Effects Templates if you want to sell your projects in After Effects marketplaces Use animators for your texts and shape layers to create dynamic video titles Create dynamic motion graphics utilizing all techniques you have learned in this course Use Track Matte techniques to create different types of lower thirds & titles Create video titles for your videos in social media networks and TV news in After Effects If you’re a Novice After Effects User, don’t worry, we have described all necessary parts of this software and you will learn how to create all lower thirds, titles and motion graphics in this course step-by-step. In this case please watch this course from the beginning so you will get a complete overview of After Effects. What will you gain from this course? 30-Day 100% Money-Back Guarantee 3 Hours of High Quality Training Course 24/7 Online Support to Answer Students Questions Downloadable Adobe After Effects CC Project Files Analyze And Feedback on Your After Effects Project Files or Exported Videos Thanks for enrolling in this course and we hope to see you inside this amazing complete guide to lower thirds and titles animation in Adobe After Effects CC video course! Enroll & Enjoy! Video Course Center Who this course is for: Anyone who wants to learn how to Earn Money Online by creating professional Lower Thirds and Titles Templates in Adobe After Effects Anyone who wants to learn how to make amateur videos look professional with Adobe After Effects Anyone who wants to learn how to create and sell professional Lower Thirds & Titles packages to sell in VideoHive , MotionElements, MotionArray, Pond5, ... marketplaces. 👉 Activate Udemy Coupon 👈 Free Tutorials Udemy Review Real Discount Udemy Free Courses Udemy Coupon Udemy Francais Coupon Udemy gratuit Coursera and Edx ELearningFree Course Free Online Training Udemy Udemy Free Coupons Udemy Free Discount Coupons Udemy Online Course Udemy Online Training 100% FREE Udemy Discount Coupons https://www.couponudemy.com/blog/after-effects-cc-learn-lower-thirds-title-motion-graphics/

0 notes

matlabhwexperts-blog · 8 years ago

Text

Interpolation Techniques online Assignment Help

http://matlabhomeworkexperts.com/interpolation-techniques.php

Interpolation is a method of constructing new data points within the range of a discrete set of known data points. We are capable of solving and delivering help with Matlab Interpolation Techniques homework in best possible manner. There are different Interpolation Techniques which are taught in schools and colleges. Various interpolation techniques are often used in the atmospheric sciences. One of the simplest methods, linear interpolation, requires knowledge of two points and the constant rate of change between them. It is important to understand each technique to fetch good grades in the academic. Any student or working professional facing any problem on their Matlab Interpolation Techniques project can contact us to get the perfect solution.

#Interpolation Techniques Assignment Help | Interpolation Techniques Online Help | Interpolation Techniques Homework Help | Interpolation Tec

0 notes

asfeedin · 5 years ago

Text

Cybercriminals adapt to coronavirus faster than the A.I. cops hunting them

Businesses have been trying to adapt to coronavirus pandemic’s “new normal.” It turns out, criminal enterprises have been making the same transition—often in ways more nimble than legitimate companies.

Last month, the international law enforcement agencies Interpol and Europol both warned of a spike in fraud related to the pandemic, with tactics involving everything from COVID-19-themed phishing emails to sales of phony coronavirus test kits and fake PPE. Hackers have seen an opportunity too, attacking hospitals with ransomware just when they can least afford to have their computer systems fail.

“There has been a very high increase in attacks and, in fact, healthcare institutions have been attacked the most,” Ajay Bhalla, president, cyber and intelligence, at payments giant Mastercard, says.

Earlier this month, Mastercard began offering health organizations free cybersecurity risk assessments, through its RiskRecon subsidiary and a partnership with the Health Information Sharing and Analysis Center (H-ISAC), a consortium of key players in global health.

Max Heinemeyer, director of threat hunting at Darktrace, a cybersecurity company based in Cambridge, England, that uses artificial intelligence to guard against cyberattacks, says there has been an increase in “fearware”—phishing emails made to appear official and purporting to contain vital information about the COVID-19 pandemic that are sent to hospitals, but containing attachments or links that launch ransomware. Darktrace has also been offering its software for free to British hospitals during the pandemic to help protect them from these attacks.

But the pandemic poses a particular challenge for security software designed to detect fraud, money laundering and cybercrime, experts say.

That’s because many of these systems rely on machine-learning algorithms to spot deviations from normal patterns—but when everyone’s normal changes, the software struggles to cope. The result can be too many false positives, blocking legitimate commerce and overwhelming human analysts tasked with investigating the alerts such software generates.

Too many false positives and companies will just turn the security systems off, Michal Pechoucek, chief technology officer at cybersecurity company Avast. Or, he says, they will raise the thresholds for the software to trigger an alert, potentially allowing more fraudulent transactions or cyber attacks to slip through.

In fact, Pechoucek says, sophisticated hackers may even incorporate this into their tactics and deliberately try to trigger false alarms in advance of an actual attack in order to condition their targets’ cybersecurity analysts to ignore the alerts or relax their defenses. Avast recently helped a hospital in the Czech city of Brno mitigate a ransomware attack that temporarily shut down its IT systems.

One way to guard against this is to have multiple security systems working in concert, Martin Rehak, the co-founder and chief executive of Resistant AI, a Prague startup specializing in protecting the automated systems that many financial firms are now using to register new customers and conduct required background checks from being gamed by criminals.

“We don’t trust any one classifier,” Rehak says, referring to a single A.I. algorithm that has to predict whether some activity is fraudulent. Instead, Resistant AI uses four or five different machine-learning modules together to make a decision. “Defense in depth is the only security solution that survives,” he says.

Pechoucek says, however, that coordination among different security layers is vital because simply using more A.I. modules independently will result in more false alarms. “You have to statistically merge the results of the systems,” he says.

Pechoucek, who founded a previous company with Rehak called Cognitive Security, which Cisco purchased for an undisclosed amount in 2013, is an investor in Resistant AI. Today the startup announced it has received $2.75 million in seed funding from two venture capital firms, Index Ventures and Credo Ventures, with participation from technology incubator Seedcamp. Daniel Dines, the CEO of UiPath, the robotic process automation company, is also an angel investor in the startup.

Rehak says the company’s software is designed to work in conjunction with human fraud analysts. “Our view of A.I. is that it is a great way to scale human teams,” he says. Human review is essential, especially when the cost of a false alarm‚ such as blocking an important transaction from a valued customer, is high.

Another solution to the challenge shifting consumer behaviors are posing for A.I.-based fraud detection systems is to simply retrain them on new data. That’s the approach that Feedzai—a San Mateo, Calif. company that uses machine learning to help protect businesses, including Citigroup and Lloyds Bank, against financial fraud—has taken, according to Pedro Bizarro, the company’s co-founder and chief scientist.

Bizarro says just a few years ago, it would have required at least 12 months’ worth of data to train a good machine learning-based fraud detection system. Now, thanks to advances in A.I. techniques, he says, Feedzai can achieve the same results with just a few months of data. And, he says, that for a large national bank, “even just five days of data is tens of millions of transactions and it is easy to train a good model from that.”

Having a comprehensive view of the person attempting a transaction, as Mastercard’s Bhalla says his company’s card network often does, is a big advantage too. He says that while the pandemic may have forced people to shop online instead of in-store, the kinds of things they are buying, the brands they are buying from, and the amounts they are spending, have not changed too dramatically. As a result, automated systems that examine multiple forms of identification such as card number, registered card address, delivery address, IP address, and device type, and then compare these against normal purchasing patterns, can easily cope.

There are exceptions, of course, Bhalla says. For instance, a business manager who is working from home on their personal laptop and making a one-off business purchase with a company card registered to a work address, but asking for the item to be delivered to a co-worker’s home address, may find that a legitimate transaction is flagged as suspicious.

Of course, the pandemic has also forced criminals to change their normal behaviors too. “Often fraudsters were trying to buy things with very high retail value,” Bizarro says. Now, some of those items—such as expensive airline tickets—aren’t available. Instead, he says, Feedzai is seeing more of what he calls “sugar and rice” fraud, in which stolen credit card numbers are used to shop for groceries or other everyday items that are less likely to stand out and be flagged by fraud detection software.

Rehak says that the increasing use of automated systems to register customers for financial services and conduct required know-your-customer and anti-money laundering checks has created new avenues for fraudsters. Sophisticated criminals, he says, are discovering how to use machine learning themselves to produce fake documents, I.D. photos and even biometric data, such as fingerprints, that can fool these automated on-boarding tools. But, he says, these methods tend to leave traces of manipulation that other A.I. systems, such as the ones developed by Resistant AI, can be trained to identify.

Bizarro says that cybercriminals have also discovered ways to use A.I. systems that can identify objects in photographs to defeat the image-based captcha challenges that many businesses use to ensure those trying to complete transactions are “not a robot.”

He says such A.I.-based methods have lowered the barriers to entry to online financial crime. More sophisticated hackers and criminal groups now package and sell stolen credit card numbers and software that allows anyone to easily perpetrate cyber attacks or fraud attempts.

And he worries that with the crushing economic impact of the coronavirus – with millions of people out of work worldwide—a massive surge in fraud is likely coming, as some people are tempted, out of desperation, to become at least part-time criminals. “There are 25 million people out of work in the U.S.,” he says. “Even if just 0.1% of them consider it, that’s 25,000 new fraudsters.”

More must-read tech coverage from Fortune:

—Who is new AT&T CEO John Stankey? —Work from home tips from the executive team that brought you Zoom —Is A.I. better at diagnosing illnesses than doctors? Don’t believe all the hype —Facebook debuts Zoom-like video chat feature called Messenger Rooms —Listen to Leadership Next, a Fortune podcast examining the evolving role of CEO —WATCH: Zoom’s ups and downs since the coronavirus crisis Catch up with Data Sheet, Fortune’s daily digest on the business of tech.

Source link

Tags: A.I., Adapt, adversarial AI, AI, Ajay Bhalla, AML, anti-fraud software, anti-money laundering, Artificial Intelligence, Avast, cops, coronavirus, coronavirus pandemic, covid-19, credit card fraud, Cybercriminals, cybersecurity, Darktrace, Faster, Feedzai, fraud detection, Hackers, hunting, KYC, machine learning, malware, Martin Rehak, Mastercard, Max Heinemeyer, Michal Pechoucek, Pedro Bizarro, ransomware, Resistant AI

from WordPress https://ift.tt/2xky58G via IFTTT

#IFTTT #WordPress #Asfeed.in #asfeed #asfeedin #asfeed blog

0 notes