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Well, this is my first time to participate in such community competitions and guess what, I've gone for 4 submissions so far (Feels Great!!)
So I wanna share some tricks that I followed for my first submission named Happy Shaping' ( Go Check it out!!):
1. Dynamic Background Color Change:
  • Technique: The background color of the figure window is gradually changed using sine and cosine functions.
  • Reason: These trigonometric functions (sin and cos) create smooth, oscillating transitions over time, which gives a fluid effect to the background's color shift.
  • Implementation:
Color = [0.1 + 0.5*abs(sin(f/10)), 0.1 + 0.5*abs(cos(f/15)), 0.9 -
0.5*abs(sin(f/20))];
  • Benefit: This introduces a smooth, visually appealing animation effect.
2. Smooth Object Motion Using Sine and Cosine:
  • Technique: The position and shape of objects are based on trigonometric functions.
  • Reason: Using sin(t) and cos(t) ensures that the movement is circular or elliptical, creating continuous and natural motion in animations.
  • Implementation (for object position):
x = 10 * cos(t * 2 * pi) * (1 + 0.5 * sin(t * pi));
y = 10 * sin(t * 2 * pi) * (1 + 0.5 * cos(t * pi));
  • Benefit: Circular and smooth motions are pleasing and easily controlled by tweaking the frequency and phase of sine/cosine functions.
3. Polygon Shape Changing Over Time:
  • Technique: The number of sides of the polygon (sides) changes dynamically based on t.
  • Reason: It creates variation in shape, maintaining user interest as the shape transitions from a triangle to a hexagon.
  • Implementation:
sides = 3 + round(3 * abs(sin(t)));
  • Benefit: This provides dynamic shape transitions over time, keeping the animation non-static.
4. Use of the fill Function for Color-Filled Shapes:
  • Technique: The fill function is used to draw a polygon with smoothly changing colors.
  • Reason: Filling polygons with varying colors based on time (t) allows for continuous color transitions, adding more complexity to the animation.
  • Implementation:
fill(xp, yp, c, 'EdgeColor', 'none');
  • Benefit: Combining both color changes and shape changes enhances the visual impact.
5. Consistent Use of hold on and hold off:
  • Technique: hold on allows multiple graphic objects to be drawn on the same axes without clearing previous objects.
  • Reason: This is crucial for drawing multiple elements (like polygons, circles, and lines) on the same figure.
  • Benefit: It helps manage and layer different graphical elements effectively within the same frame.
6. Use of rectangle for a Smooth Ball Motion:
  • Technique: The ball's motion is defined by rectangle with a Curvature of [1, 1] to make it circular.
  • Reason: Using the rectangle function simplifies the process of drawing a filled circle, and controlling its position and size is intuitive.
  • Benefit: It provides a straightforward way to animate circular objects within the plot.
7. Animating the Connection Line:
  • Technique: A white dashed line (w--) is drawn between the polygon and the moving ball to show a connection between these objects.
  • Reason: This adds interactivity to the scene, as it gives the impression that the polygon and the ball are related or connected in some way.
  • Implementation:
plot([x bx], [y by], 'w--', 'LineWidth', 2);
  • Benefit: A dynamic element that adds depth and narrative to the animation, guiding the viewer’s attention.
8. Frame Synchronization with Time (f and t):
  • Technique: The variable f is used as a frame number, while t = f / 24 creates a link between frame and time.
  • Reason: Ensuring smooth and continuous transitions in the animation over time is critical, so f acts as the control for time-based changes in shape, color, and position.
  • Benefit: This makes it easy to manage frame rates and time-based updates for the animation.
I composed 30 sound loops for use in the Mini Hack.
If you like them, please feel free to use them for free.
Try to install MATLAB2024a on Ubuntu24.04. In the image below, the button indicated by the green arrow is clickable, while the button indicated by the red arrow are unclickable, and input field where text cannot be entered, preventing the installation.
Let's say you have a chance to ask the MATLAB leadership team any question. What would you ask them?
We are thrilled to announce that every community member now has the ability to create a poll in Discussions, allowing you to gather votes and opinions from the community.
How to create a poll:
You can find the ‘Create a Poll’ link just below the text box (see screenshot below). Please note that the default type of content is a ‘Discussion’. To start a poll, simply click the link.
Creating a poll is straightforward. You can add up to 6 choices for your poll and set the duration from 1 to 6 weeks.
Where to find the poll
Polls created by community members will appear only in the channel where they are created and the landing page of Discussions area. Discussions moderators have the privilege to feature/broadcast the poll across Answers, File Exchange, and Cody.
Thoughts?
We can’t wait to see what interesting polls our community will create. Meanwhile, if you have any questions or suggestions, feel free to leave a comment.
If you are interested in AI, Autonomous Systems and Robotics, and the future of engineering, don't miss out on MATLAB EXPO 2024 and register now.
You will have the opportunity to connect with engineers, scientists, educators, and researchers, and new ideas.
Featured Sessions:
  • From Embedded to Empowered: The Rise of Software-Defined Products - María Elena Gavilán Alfonso, MathWorks
  • The Empathetic Engineers of Tomorrow - Dr. Darryll Pines, University of Maryland
  • A Model-Based Design Journey from Aerospace to an Artificial Pancreas System - Louis Lintereur, Medtronic Diabetes
Featured Topics:
  • AI
  • Autonomous Systems and Robotics
  • Electrification
  • Algorithm Development and Data Analysis
  • Modeling, Simulation, Verification, Validation, and Implementation
  • Wireless Communications
  • Cloud, Software Factories, and DevOps
  • Preparing Future Engineers and Scientists
What is the side-effect of counting the number of Deep Learning Toolbox™ updates in the last 5 years? The industry has slowly stabilised and matured, so updates have slowed down in the last 1 year, and there has been no exponential growth.Is it correct to assume that? Let's see what you think!
releaseNumNames = "R"+string(2019:2024)+["a";"b"];
releaseNumNames = releaseNumNames(:);
numReleaseNotes = [10,14,27,39,38,43,53,52,55,57,46,46];
exampleNums = [nan,nan,nan,nan,nan,nan,40,24,22,31,24,38];
bar(releaseNumNames,[numReleaseNotes;exampleNums]')
legend(["#release notes","#new/update examples"],Location="northwest")
title("Number of Deep Learning Toolbox™ update items in the last 5 years")
ylabel("#release notes")
We are thrilled to announce the redesign of the Discussions leaf page, with a new user-focused right-hand column!
Why Are We Doing This?
  • Address Readers’ Needs:
Previously, the right-hand column displayed related content, but feedback from our community indicated that this wasn't meeting your needs. Many of you expressed a desire to read more posts from the same author but found it challenging to locate them.
With the new design, readers can easily learn more about the author, explore their other posts, and follow them to receive notifications on new content.
  • Enhance Authors’ Experience:
Since the launch of the Discussions area earlier this year, we've seen an influx of community members sharing insightful technical articles, use cases, and ideas. The new design aims to help you grow your followers and organize your content more effectively by editing tags. We highly encourage you to use the Discussions area as your community blogging platform.
We hope you enjoy the new design of the right-hand column. Please feel free to share your thoughts and experiences by leaving a comment below.
We are excited to invite you to join our 2024 community contest – MATLAB Shorts Mini Hack! Last year, we challenged you to create a 48-frame animation. In 2024, we are increasing the frame count to 96 and supporting audio. Your mission? Create a short movie!
Whether you are a seasoned MATLAB user or just a beginner, you can participate in the contest and have opportunities to win amazing prizes. Be sure to check out our Blog post for more details on the Community Contests.
Timeframe
This contest runs for 5 weeks, from Oct. 7th to Nov. 10th.
How to Participate
  • Create a new short movie or remix an existing one with up to 2,000 characters of code.
  • Vote or comment on the short movies you love!
Prizes
You will have opportunities to win compelling prizes, including Amazon gift cards, MathWorks T-shirts, and virtual badges. We will give out both weekly prizes and grand prizes.
Stay Informed
Make sure to follow the contest to get important announcements and your prize updates.
Join for creativity and fun! We look forward to seeing your creations in the MATLAB Shorts Contest!
The AI Chat Playground at MATLAB Central has two new upgrades: OpenAI GPT-4o mini and MATLAB R2024b!
GPT-4o mini is a new language model from OpenAI and brings general knowledge up to October 2023. GPT-4o mini surpasses GPT-3.5 Turbo and other small models on academic benchmarks across both textual intelligence and reasoning. Our goal is to keep improving the output of the AI Chat Playground. This upgrade is available now: https://www.mathworks.com/matlabcentral/playground/
One more thing... we also updated the system to the latest release of MATLAB. This is R2024b and comes with hundreds of updates and new plot types to explore.Check out Mike Croucher's blog post about the latest version of MATLAB: https://blogs.mathworks.com/matlab/2024/09/13/the-latest-version-of-matlab-r2024b-has-just-been-released/
We are looking forward to your feedback on the updates to the AI Chat Playground. Let us know what you think and how you use this community app.
Always!
29%
It depends
14%
Never!
21%
I didn't know that was possible
36%
1810 votes
Hello everyone,
Over the past few weeks, our community members have shared some incredible insights and resources. Here are some highlights worth checking out:

Interesting Questions

Johnathan is seeking help with implementing a complex equation into MATLAB's curve fitting toolbox. If you have experience with curve fitting or MATLAB, your input could be invaluable!

Popular Discussions

Athanasios continues his exploration of the Duffing Equation, delving into its chaotic behavior. It's a fascinating read for anyone interested in nonlinear dynamics or chaos theory.
John shares his playful exploration with MATLAB to find a generative equation for a sequence involving Fibonacci numbers. It's an intriguing challenge for those who love mathematical puzzles.

From File Exchange

Ayesha provides a graphical analysis of linearised models in epidemiology, offering a detailed look at the dynamics of these systems. This resource is perfect for those interested in mathematical modeling.
Gareth brings some humor to MATLAB with a toolbox designed to share jokes. It's a fun way to lighten the mood during conferences or meetups.

From the Blogs

Ned Gulley interviews Tim Marston, the 2023 MATLAB Mini Hack contest winner. Tim's creativity and skills are truly inspiring, and his story is a must-read for aspiring programmers.
Sivylla discusses the integration of AI with embedded systems, highlighting the benefits of using MATLAB and Simulink. It's an insightful read for anyone interested in the future of AI technology.
Thank you to all our contributors for sharing your knowledge and creativity. We encourage everyone to engage with these posts and continue fostering a vibrant and supportive community.
Happy exploring!
David
David
Last activity on 16 Sep 2024

Explore the newest online training courses, available as of 2024b: one new Onramp, eight new short courses, and one new learning path. Yes, that’s 10 new offerings. We’ve been busy.
As a reminder, Onramps are free to all. Short courses and learning paths require a subscription to the Online Training Suite (OTS).
  1. Multibody Simulation Onramp
  2. Analyzing Results in Simulink
  3. Battery Pack Modeling
  4. Introduction to Motor Control
  5. Signal Processing Techniques for Streaming Signals
  6. Core Signal Processing Techniques in MATLAB (learning path – includes the four short courses listed below)
Mike Croucher
Mike Croucher
Last activity on 15 Sep 2024

Hot off the heels of my High Performance Computing experience in the Czech republic, I've just booked my flights to Atlanta for this year's supercomputing conference at SC24.
Will any of you be there?
syms u v
atan2alt(v,u)
ans = 
function Z = atan2alt(V,U)
% extension of atan2(V,U) into the complex plane
Z = -1i*log((U+1i*V)./sqrt(U.^2+V.^2));
% check for purely real input. if so, zero out the imaginary part.
realInputs = (imag(U) == 0) & (imag(V) == 0);
Z(realInputs) = real(Z(realInputs));
end
As I am editing this post, I see the expected symbolic display in the nice form as have grown to love. However, when I save the post, it does not display. (In fact, it shows up here in the discussions post.) This seems to be a new problem, as I have not seen that failure mode in the past.
You can see the problem in this Answer forum response of mine, where it did fail.
Has this been eliminated? I've been at 31 or 32 for 30 days for awhile, but no badge. 10 badge was automatic.

Formal Proof of Smooth Solutions for Modified Navier-Stokes Equations

1. Introduction

We address the existence and smoothness of solutions to the modified Navier-Stokes equations that incorporate frequency resonances and geometric constraints. Our goal is to prove that these modifications prevent singularities, leading to smooth solutions.

2. Mathematical Formulation

2.1 Modified Navier-Stokes Equations

Consider the Navier-Stokes equations with a frequency resonance term R(u,f)\mathbf{R}(\mathbf{u}, \mathbf{f})R(u,f) and geometric constraints:

∂u∂t+(u⋅∇)u=−∇pρ+ν∇2u+R(u,f)\frac{\partial \mathbf{u}}{\partial t} + (\mathbf{u} \cdot \nabla) \mathbf{u} = -\frac{\nabla p}{\rho} + \nu \nabla^2 \mathbf{u} + \mathbf{R}(\mathbf{u}, \mathbf{f})∂t∂u​+(u⋅∇)u=−ρ∇p​+ν∇2u+R(u,f)

where:

• u=u(t,x)\mathbf{u} = \mathbf{u}(t, \mathbf{x})u=u(t,x) is the velocity field.

• p=p(t,x)p = p(t, \mathbf{x})p=p(t,x) is the pressure field.

• ν\nuν is the kinematic viscosity.

• R(u,f)\mathbf{R}(\mathbf{u}, \mathbf{f})R(u,f) represents the frequency resonance effects.

• f\mathbf{f}f denotes external forces.

2.2 Boundary Conditions

The boundary conditions are:

u⋅n=0 on Γ\mathbf{u} \cdot \mathbf{n} = 0 \text{ on } \Gammau⋅n=0 on Γ

where Γ\GammaΓ represents the boundary of the domain Ω\OmegaΩ, and n\mathbf{n}n is the unit normal vector on Γ\GammaΓ.

3. Existence and Smoothness of Solutions

3.1 Initial Conditions

Assume initial conditions are smooth:

u(0)∈C∞(Ω)\mathbf{u}(0) \in C^{\infty}(\Omega)u(0)∈C∞(Ω) f∈L2(Ω)\mathbf{f} \in L^2(\Omega)f∈L2(Ω)

3.2 Energy Estimates

Define the total kinetic energy:

E(t)=12∫Ω∣u(t)∣2 dΩE(t) = \frac{1}{2} \int_{\Omega} \mathbf{u}(t)^2 \, d\OmegaE(t)=21​∫Ω​∣u(t)∣2dΩ

Differentiate E(t)E(t)E(t) with respect to time:

dE(t)dt=∫Ωu⋅∂u∂t dΩ\frac{dE(t)}{dt} = \int_{\Omega} \mathbf{u} \cdot \frac{\partial \mathbf{u}}{\partial t} \, d\OmegadtdE(t)​=∫Ω​u⋅∂t∂u​dΩ

Substitute the modified Navier-Stokes equation:

dE(t)dt=∫Ωu⋅[−∇pρ+ν∇2u+R] dΩ\frac{dE(t)}{dt} = \int_{\Omega} \mathbf{u} \cdot \left[ -\frac{\nabla p}{\rho} + \nu \nabla^2 \mathbf{u} + \mathbf{R} \right] \, d\OmegadtdE(t)​=∫Ω​u⋅[−ρ∇p​+ν∇2u+R]dΩ

Using the divergence-free condition (∇⋅u=0\nabla \cdot \mathbf{u} = 0∇⋅u=0):

∫Ωu⋅∇pρ dΩ=0\int_{\Omega} \mathbf{u} \cdot \frac{\nabla p}{\rho} \, d\Omega = 0∫Ω​u⋅ρ∇p​dΩ=0

Thus:

dE(t)dt=−ν∫Ω∣∇u∣2 dΩ+∫Ωu⋅R dΩ\frac{dE(t)}{dt} = -\nu \int_{\Omega} \nabla \mathbf{u}^2 \, d\Omega + \int_{\Omega} \mathbf{u} \cdot \mathbf{R} \, d\OmegadtdE(t)​=−ν∫Ω​∣∇u∣2dΩ+∫Ω​u⋅RdΩ

Assuming R\mathbf{R}R is bounded by a constant CCC:

∫Ωu⋅R dΩ≤C∫Ω∣u∣ dΩ\int_{\Omega} \mathbf{u} \cdot \mathbf{R} \, d\Omega \leq C \int_{\Omega} \mathbf{u} \, d\Omega∫Ω​u⋅RdΩ≤C∫Ω​∣u∣dΩ

Applying the Poincaré inequality:

∫Ω∣u∣2 dΩ≤Const⋅∫Ω∣∇u∣2 dΩ\int_{\Omega} \mathbf{u}^2 \, d\Omega \leq \text{Const} \cdot \int_{\Omega} \nabla \mathbf{u}^2 \, d\Omega∫Ω​∣u∣2dΩ≤Const⋅∫Ω​∣∇u∣2dΩ

Therefore:

dE(t)dt≤−ν∫Ω∣∇u∣2 dΩ+C∫Ω∣u∣ dΩ\frac{dE(t)}{dt} \leq -\nu \int_{\Omega} \nabla \mathbf{u}^2 \, d\Omega + C \int_{\Omega} \mathbf{u} \, d\OmegadtdE(t)​≤−ν∫Ω​∣∇u∣2dΩ+C∫Ω​∣u∣dΩ

Integrate this inequality:

E(t)≤E(0)−ν∫0t∫Ω∣∇u∣2 dΩ ds+CtE(t) \leq E(0) - \nu \int_{0}^{t} \int_{\Omega} \nabla \mathbf{u}^2 \, d\Omega \, ds + C tE(t)≤E(0)−ν∫0t​∫Ω​∣∇u∣2dΩds+Ct

Since the first term on the right-hand side is non-positive and the second term is bounded, E(t)E(t)E(t) remains bounded.

3.3 Stability Analysis

Define the Lyapunov function:

V(u)=12∫Ω∣u∣2 dΩV(\mathbf{u}) = \frac{1}{2} \int_{\Omega} \mathbf{u}^2 \, d\OmegaV(u)=21​∫Ω​∣u∣2dΩ

Compute its time derivative:

dVdt=∫Ωu⋅∂u∂t dΩ=−ν∫Ω∣∇u∣2 dΩ+∫Ωu⋅R dΩ\frac{dV}{dt} = \int_{\Omega} \mathbf{u} \cdot \frac{\partial \mathbf{u}}{\partial t} \, d\Omega = -\nu \int_{\Omega} \nabla \mathbf{u}^2 \, d\Omega + \int_{\Omega} \mathbf{u} \cdot \mathbf{R} \, d\OmegadtdV​=∫Ω​u⋅∂t∂u​dΩ=−ν∫Ω​∣∇u∣2dΩ+∫Ω​u⋅RdΩ

Since:

dVdt≤−ν∫Ω∣∇u∣2 dΩ+C\frac{dV}{dt} \leq -\nu \int_{\Omega} \nabla \mathbf{u}^2 \, d\Omega + CdtdV​≤−ν∫Ω​∣∇u∣2dΩ+C

and R\mathbf{R}R is bounded, u\mathbf{u}u remains bounded and smooth.

3.4 Boundary Conditions and Regularity

Verify that the boundary conditions do not induce singularities:

u⋅n=0 on Γ\mathbf{u} \cdot \mathbf{n} = 0 \text{ on } \Gammau⋅n=0 on Γ

Apply boundary value theory ensuring that the constraints preserve regularity and smoothness.

4. Extended Simulations and Experimental Validation

4.1 Simulations

• Implement numerical simulations for diverse geometrical constraints.

• Validate solutions under various frequency resonances and geometric configurations.

4.2 Experimental Validation

• Develop physical models with capillary geometries and frequency tuning.

• Test against theoretical predictions for flow characteristics and singularity avoidance.

4.3 Validation Metrics

Ensure:

• Solution smoothness and stability.

• Accurate representation of frequency and geometric effects.

• No emergence of singularities or discontinuities.

5. Conclusion

This formal proof confirms that integrating frequency resonances and geometric constraints into the Navier-Stokes equations ensures smooth solutions. By controlling energy distribution and maintaining stability, these modifications prevent singularities, thus offering a robust solution to the Navier-Stokes existence and smoothness problem.

So generally I want to be using uifigures over figures. For example I really like the tab group component, which can really help with organizing large numbers of plots in a manageable way. I also really prefer the look of the progress dialog, uialert, confirm, etc. That said, I run into way more bugs using uifigures. I always get a “flicker” in the axes toolbar for example. I also have matlab getting “hung” a lot more often when using uifigures.

So in general, what is recommended? Are uifigures ever going to fully replace traditional figures? Are they going to become more and more robust? Do I need a better GPU to handle graphics better? Just looking for general guidance.

Salam Surjit
Salam Surjit
Last activity on 3 Nov 2024

Hi everyone, I am from India ..Suggest some drone for deploying code from Matlab.