Ray Marching Explained
•Download as PPTX, PDF•
1 like•570 views
This document provides an overview of ray marching techniques for rendering 3D scenes using shaders. It explains basic linear algebra concepts used in ray marching like position, distance to surface, and normals. It also covers lighting models including diffuse and specular lighting. Advanced techniques like boolean operations allow for creating complex geometries. Additional effects covered include soft shadows, ambient occlusion, and examples of shadertoy implementations. Links to further resources on raymarching and distance fields are also provided.
Report
Share
Report
Share
Recommended
ECE469 Project1
This document summarizes the results of a class project on analyzing the fault detection capabilities of test vectors for integrated circuits. It includes plots and conclusions about how the number of detected faults varies with increasing test vector size and detection capability (K) for several benchmark circuits. It finds that larger test sets and higher K detection capability detect more faults. The document also lists the group members and their contributions to the project.
GAN in_kakao
The document discusses generative adversarial networks (GANs) and their applications to image-to-image translation tasks. It introduces DiscoGAN and CycleGAN, two models that use GANs to translate between image domains without paired training data. The key differences between DiscoGAN and CycleGAN are discussed, including architectural choices like the number of layers, normalization methods, and losses used. CycleGAN adds reconstruction losses and uses residual blocks, while DiscoGAN has a simpler architecture with fewer layers.
20180831 riemannian representation learning
This document provides an overview of hierarchical representation with hyperbolic geometry. It introduces hyperbolic space as an alternative to Euclidean space for embedding symbolic and hierarchical data. Key points covered include: (1) the limitations of Euclidean embedding for graph structures, (2) definitions of hyperbolic space and the Poincare disk model, (3) optimization techniques for gradient descent in hyperbolic space including calculating gradients and using retractions, and (4) simple toy experiments demonstrating optimization in hyperbolic space.
Introduction to Artificial Neural Networks (ANNs) - Step-by-Step Training & T...
This is an introduction to artificial neural networks (ANNs) including the idea of classification and how ANNs can classify data into number of distinct classes based on some features.
A basic neural network example is given that uses a single layer perceptron with three inputs and one output to classify data linearly using the Signum activation function.
The presented example is about classifying data about colors into two categories (Red and Blue).
Artificial neural networks (ANNs) or connectionist systems are a computational model used in machine learning, computer science and other research disciplines, which is based on a large collection of connected simple units called artificial neurons, loosely analogous to axons in a biological brain. Connections between neurons carry an activation signal of varying strength. If the combined incoming signals are strong enough, the neuron becomes activated and the signal travels to other neurons connected to it. Such systems can be trained from examples, rather than explicitly programmed, and excel in areas where the solution or feature detection is difficult to express in a traditional computer program. Like other machine learning methods, neural networks have been used to solve a wide variety of tasks, like computer vision and speech recognition, that are difficult to solve using ordinary rule-based programming.
Find me on:
AFCIT
http://www.afcit.xyz
YouTube
https://www.youtube.com/channel/UCuewOYbBXH5gwhfOrQOZOdw
Google Plus
https://plus.google.com/u/0/+AhmedGadIT
SlideShare
https://www.slideshare.net/AhmedGadFCIT
LinkedIn
https://www.linkedin.com/in/ahmedfgad/
ResearchGate
https://www.researchgate.net/profile/Ahmed_Gad13
Academia
https://www.academia.edu/
Google Scholar
https://scholar.google.com.eg/citations?user=r07tjocAAAAJ&hl=en
Mendelay
https://www.mendeley.com/profiles/ahmed-gad12/
ORCID
https://orcid.org/0000-0003-1978-8574
StackOverFlow
http://stackoverflow.com/users/5426539/ahmed-gad
Twitter
https://twitter.com/ahmedfgad
Facebook
https://www.facebook.com/ahmed.f.gadd
Pinterest
https://www.pinterest.com/ahmedfgad/
CVRP solver with Multi-Head Attention
This document discusses using a multi-head attention mechanism to solve vehicle routing problems. It proposes an encoder-decoder model where customer locations are embedded in vectors and passed through an encoder with multi-head attention layers. A decoder then selects the next node in a route using a context vector containing embedding and capacity information, with the goal of minimizing total route distance. The model is trained using a policy gradient method to approximate the gradient and update the encoder and decoder.
Code_Saturne流体解析入門講習会 講習会資料
This document is the distribution material on "Code-Saturne beginner seminar". (November 1 2014 "OpenCAE Study Meeting @ Kansai")
http://ofbkansai.sakura.ne.jp/
"Incremental Lossless Graph Summarization", KDD 2020
A presentation slides of Jihoon Ko*, Yunbum Kook* and Kijung Shin, "Incremental Lossless Graph Summarization", KDD 2020.
Given a fully dynamic graph, represented as a stream of edge insertions and deletions, how can we obtain and incrementally update a lossless summary of its current snapshot?
As large-scale graphs are prevalent, concisely representing them is inevitable for efficient storage and analysis. Lossless graph summarization is an effective graph-compression technique with many desirable properties. It aims to compactly represent the input graph as (a) a summary graph consisting of supernodes (i.e., sets of nodes) and superedges (i.e., edges between supernodes), which provide a rough description, and (b) edge corrections which fix errors induced by the rough description. While a number of batch algorithms, suited for static graphs, have been developed for rapid and compact graph summarization, they are highly inefficient in terms of time and space for dynamic graphs, which are common in practice.
In this work, we propose MoSSo, the first incremental algorithm for lossless summarization of fully dynamic graphs. In response to each change in the input graph, MoSSo updates the output representation by repeatedly moving nodes among supernodes. MoSSo decides nodes to be moved and their destinations carefully but rapidly based on several novel ideas. Through extensive experiments on 10 real graphs, we show MoSSo is (a) Fast and 'any time': processing each change in near-constant time (less than 0.1 millisecond), up to 7 orders of magnitude faster than running state-of-the-art batch methods, (b) Scalable: summarizing graphs with hundreds of millions of edges, requiring sub-linear memory during the process, and (c) Effective: achieving comparable compression ratios even to state-of-the-art batch methods.
Scala as a Declarative Language
The document discusses the benefits of declarative programming using Scala. It provides examples of implementing algorithms and data structures declaratively in Scala. It also discusses the history and future of Scala, as well as how Scala encourages thinking about programs as transformations rather than changes to memory.
Recommended
ECE469 Project1
This document summarizes the results of a class project on analyzing the fault detection capabilities of test vectors for integrated circuits. It includes plots and conclusions about how the number of detected faults varies with increasing test vector size and detection capability (K) for several benchmark circuits. It finds that larger test sets and higher K detection capability detect more faults. The document also lists the group members and their contributions to the project.
GAN in_kakao
The document discusses generative adversarial networks (GANs) and their applications to image-to-image translation tasks. It introduces DiscoGAN and CycleGAN, two models that use GANs to translate between image domains without paired training data. The key differences between DiscoGAN and CycleGAN are discussed, including architectural choices like the number of layers, normalization methods, and losses used. CycleGAN adds reconstruction losses and uses residual blocks, while DiscoGAN has a simpler architecture with fewer layers.
20180831 riemannian representation learning
This document provides an overview of hierarchical representation with hyperbolic geometry. It introduces hyperbolic space as an alternative to Euclidean space for embedding symbolic and hierarchical data. Key points covered include: (1) the limitations of Euclidean embedding for graph structures, (2) definitions of hyperbolic space and the Poincare disk model, (3) optimization techniques for gradient descent in hyperbolic space including calculating gradients and using retractions, and (4) simple toy experiments demonstrating optimization in hyperbolic space.
Introduction to Artificial Neural Networks (ANNs) - Step-by-Step Training & T...
This is an introduction to artificial neural networks (ANNs) including the idea of classification and how ANNs can classify data into number of distinct classes based on some features.
A basic neural network example is given that uses a single layer perceptron with three inputs and one output to classify data linearly using the Signum activation function.
The presented example is about classifying data about colors into two categories (Red and Blue).
Artificial neural networks (ANNs) or connectionist systems are a computational model used in machine learning, computer science and other research disciplines, which is based on a large collection of connected simple units called artificial neurons, loosely analogous to axons in a biological brain. Connections between neurons carry an activation signal of varying strength. If the combined incoming signals are strong enough, the neuron becomes activated and the signal travels to other neurons connected to it. Such systems can be trained from examples, rather than explicitly programmed, and excel in areas where the solution or feature detection is difficult to express in a traditional computer program. Like other machine learning methods, neural networks have been used to solve a wide variety of tasks, like computer vision and speech recognition, that are difficult to solve using ordinary rule-based programming.
Find me on:
AFCIT
http://www.afcit.xyz
YouTube
https://www.youtube.com/channel/UCuewOYbBXH5gwhfOrQOZOdw
Google Plus
https://plus.google.com/u/0/+AhmedGadIT
SlideShare
https://www.slideshare.net/AhmedGadFCIT
LinkedIn
https://www.linkedin.com/in/ahmedfgad/
ResearchGate
https://www.researchgate.net/profile/Ahmed_Gad13
Academia
https://www.academia.edu/
Google Scholar
https://scholar.google.com.eg/citations?user=r07tjocAAAAJ&hl=en
Mendelay
https://www.mendeley.com/profiles/ahmed-gad12/
ORCID
https://orcid.org/0000-0003-1978-8574
StackOverFlow
http://stackoverflow.com/users/5426539/ahmed-gad
Twitter
https://twitter.com/ahmedfgad
Facebook
https://www.facebook.com/ahmed.f.gadd
Pinterest
https://www.pinterest.com/ahmedfgad/
CVRP solver with Multi-Head Attention
This document discusses using a multi-head attention mechanism to solve vehicle routing problems. It proposes an encoder-decoder model where customer locations are embedded in vectors and passed through an encoder with multi-head attention layers. A decoder then selects the next node in a route using a context vector containing embedding and capacity information, with the goal of minimizing total route distance. The model is trained using a policy gradient method to approximate the gradient and update the encoder and decoder.
Code_Saturne流体解析入門講習会 講習会資料
This document is the distribution material on "Code-Saturne beginner seminar". (November 1 2014 "OpenCAE Study Meeting @ Kansai")
http://ofbkansai.sakura.ne.jp/
"Incremental Lossless Graph Summarization", KDD 2020
A presentation slides of Jihoon Ko*, Yunbum Kook* and Kijung Shin, "Incremental Lossless Graph Summarization", KDD 2020.
Given a fully dynamic graph, represented as a stream of edge insertions and deletions, how can we obtain and incrementally update a lossless summary of its current snapshot?
As large-scale graphs are prevalent, concisely representing them is inevitable for efficient storage and analysis. Lossless graph summarization is an effective graph-compression technique with many desirable properties. It aims to compactly represent the input graph as (a) a summary graph consisting of supernodes (i.e., sets of nodes) and superedges (i.e., edges between supernodes), which provide a rough description, and (b) edge corrections which fix errors induced by the rough description. While a number of batch algorithms, suited for static graphs, have been developed for rapid and compact graph summarization, they are highly inefficient in terms of time and space for dynamic graphs, which are common in practice.
In this work, we propose MoSSo, the first incremental algorithm for lossless summarization of fully dynamic graphs. In response to each change in the input graph, MoSSo updates the output representation by repeatedly moving nodes among supernodes. MoSSo decides nodes to be moved and their destinations carefully but rapidly based on several novel ideas. Through extensive experiments on 10 real graphs, we show MoSSo is (a) Fast and 'any time': processing each change in near-constant time (less than 0.1 millisecond), up to 7 orders of magnitude faster than running state-of-the-art batch methods, (b) Scalable: summarizing graphs with hundreds of millions of edges, requiring sub-linear memory during the process, and (c) Effective: achieving comparable compression ratios even to state-of-the-art batch methods.
Scala as a Declarative Language
The document discusses the benefits of declarative programming using Scala. It provides examples of implementing algorithms and data structures declaratively in Scala. It also discusses the history and future of Scala, as well as how Scala encourages thinking about programs as transformations rather than changes to memory.
Reed solomon Encoder and Decoder
The document outlines Reed-Solomon error correction codes. It discusses how Reed-Solomon codes encode data using a generator polynomial to produce parity check symbols. The document then describes how Reed-Solomon codes can decode errors using syndrome calculation, error location polynomials, and finding the error positions and values through algorithms like Forney's method and Chien search. Reed-Solomon codes are widely used in applications like CDs, DVDs, wireless communications and digital television for their ability to efficiently correct both random and burst errors.
Overlap Layout Consensus assembly
OLC assembly involves three main steps:
1. Overlap - Compute all overlaps between reads to construct an overlap graph
2. Layout - Bundle stretches of the overlap graph into contigs
3. Consensus - Pick the most likely nucleotide sequence for each contig by determining consensus from the underlying reads
Linkedin_PowerPoint
This document presents an outer approximation solution algorithm for solving reliable shortest path problems on transportation networks. The algorithm formulates the problem as a mixed integer conic quadratic program to minimize the mean plus standard deviation of path costs. It then uses an outer approximation approach to decompose the problem and solve it efficiently through alternating steps of solving a master problem and subproblem. Computational results on several test networks show the algorithm converges quickly and outperforms directly solving the large-scale mixed integer conic quadratic program. The approach can also be applied to other reliability metrics and joint inventory location problems.
No more dumb hex!
Troopers, Heidelberg, Germany
21 March 2019
co-presented and designed with Rafał Hirsz
https://github.com/corkami/sbud
https://github.com/evoL/albert
Sbe final exam jan17 - solved-converted
This document contains a multi-part exam question regarding dynamic control systems. It asks the student to perform block diagram reductions to solve for various transfer functions T(s). It also asks the student to analyze the system poles, find damping ratio and natural frequency, and determine the unit impulse and step responses. Additional questions involve analyzing the characteristics of a flow system and determining sensitivity functions.
DISCRETE LOGARITHM PROBLEM
The document discusses public key cryptography based on the discrete logarithm problem (DLP). It defines the DLP and describes some common algorithms for solving it, including the ElGamal cryptosystem, Diffie-Hellman key exchange, baby-step giant-step algorithm, Pohlig-Hellman algorithm, and Pollard's rho algorithm. It also explains how the difficulty of solving the DLP can provide the basis for secure cryptographic systems.
Introduction to PyTorch
Basic concept of Deep Learning with explaining its structure and backpropagation method and understanding autograd in PyTorch. (+ Data parallism in PyTorch)
Elliptic Curve Cryptography
Elliptic curve cryptography (ECC) uses elliptic curves over finite fields for encryption, digital signatures, and key exchange. The key sizes are smaller than RSA for the same security level. Its security relies on the assumed hardness of solving the discrete logarithm problem over elliptic curves. ECC defines elliptic curves with parameters over Galois fields GF(p) for prime p or binary fields GF(2m). Points on the curves along with addition and doubling formulas are used to perform scalar multiplications for cryptographic operations.
Solucion de ejercicios de Analisis estructural I
This document contains solutions to structural analysis exercises involving determining forces in reinforcement bars. Exercise 41 involves a frame with nodes A, B, G and calculates the forces in the bars. The forces are: FAB = 25 kN (compression), FAG = 4 kN (compression), FCG = 5 kN (compression), FBG = 3 kN (tension). Exercise 42 involves a similar frame with nodes A, B, D, E, F, G, H and calculates forces such as: FAH = 18.92 kN (compression), FAB = 15.13 kN (tension), FCF = 2 kN (compression). Exercise 43 calculates forces in a frame with nodes A, B,
Reinforcement learning
This document provides an overview of reinforcement learning. It discusses how reinforcement learning differs from supervised and unsupervised learning by focusing on choosing actions to maximize long-term reward. It also formalizes reinforcement learning problems using Markov decision processes and describes algorithms like value iteration and policy iteration that can be used to find optimal policies.
Semana 11 numeros complejos ii álgebra-uni ccesa007
This document provides information about complex numbers including:
- Properties of complex numbers such as conjugates, opposites, and theorems regarding addition, multiplication, and powers of complex numbers.
- Calculating the modulus (absolute value) of a complex number.
- Representing a complex number in trigonometric form using modulus, argument, and cis notation.
- Examples of calculating modulus, finding conjugates and opposites, and converting complex numbers to trigonometric form.
Know your FOSS obligations
Free doesn't always means free of obligations. Knowing your FOSS obligations is good software practice.
Better performance through Superscalarity
How to employ "hidden" parallelism in CPU:s of today to improve the performance of CPU intensive algorithms
Property Based Tesing
Property-based testing involves generating random test data and checking that code satisfies specific properties for all possible inputs. This improves productivity and test quality by finding more bugs during development. The document discusses property-based testing of common data structures like maps and trees by specifying properties like nodes following certain ordering rules. It also mentions testing actions, models, and using property-based testing frameworks to generate random but reproducible tests based on a seed value. Property-based testing frameworks like QuickCheck, FsCheck, and ScalaCheck are mentioned.
Monad - a functional design pattern
This document discusses refactoring code to use functional design patterns, specifically monads. It begins by showing an example of defining attribute queries in a functional style using monads. It then explores monads in more depth, explaining their essence as separating computation composition from execution while allowing computations to carry extra implicit data. Common uses of monads are listed and additional resources provided for further understanding monads and their usefulness.
Formlets
Formlets are a way to build composable HTML forms that are type-safe, handle errors, are abstract, and easy to combine into larger forms. The key feature of formlets is that they are composable, like integers that can be added together or enumerables that can be selected, filtered and ordered. This allows text boxes, text areas, dropdowns and other form elements to be combined to create complex nested composite forms through binding operations. Demo code shows how common form validation and error handling tasks can be abstracted using formlets.
Pragmatic metaprogramming
Do not repeat yourself, we teach every fledgling software developer. It makes sense as with growing code redundancy the maintenance cost increase. Simple tools such as functions or loops are a great ways to reduce code redundancy but in our quest to avoid code redundancy we sometimes indulge into complexity. Complex code is also costly to maintain. I will demonstrate, using real-world examples, how one can adopt metaprogramming to minimize code redundancy as well keeping the code simple enough for my mom to understand it.
Concurrency - responsiveness in .NET
The document discusses concurrency and asynchronous programming in .NET. It covers three pillars of concurrency: scalability using Parallel.For, responsiveness using tasks and async/await, and consistency using locks, mutexes, etc. It demonstrates how async/await allows programs to be responsive by freeing threads for other work while waiting for I/O. A key point is that the SynchronizationContext impacts asynchronous code behavior and can cause unintended threading issues if not properly understood.
Meta Programming
The document discusses using T4 templates to reduce code repetition through metaprogramming. It provides examples of how T4 can generate exception classes, dependency properties, and other code automatically. The benefits of T4 include simplifying complex patterns, making debugging easier, and saving developer time by avoiding repetitive manual coding tasks. T4 templates act as code generators that can produce any text-based output like C#, VB, or C++.
Concurrency scalability
Herb Sutter (GotW.ca) says that the concept of Concurrency is easier understood if split into three sub concepts; scalability, responsiveness and consistency. This presentation is the first of three covering these concepts, starting off with everyone’s favorite: Scalability – i.e. splitting a CPU-bound problem onto several cores in order to solve the problem faster. I will show what tools what .NET offer but also performance pitfalls that arise from an escalating problem that plagued computer architecture for the last 20 years.
Concurrency
This document discusses concurrency and parallelism in .NET. It covers three pillars of concurrency: scalability using Parallel.For, responsiveness using tasks and async/await, and consistency using locks, interlocked operations, and mutexes/events/semaphores. It also discusses challenges with shared state and race conditions when naively using Parallel.For on shared data. Several solutions are presented such as not sharing data, using smaller work chunks to reduce overhead, and running completely independent tasks in parallel. The document emphasizes the importance of measuring performance before and after optimizations.
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-und-domino-lizenzkostenreduzierung-in-der-welt-von-dlau/
DLAU und die Lizenzen nach dem CCB- und CCX-Modell sind für viele in der HCL-Community seit letztem Jahr ein heißes Thema. Als Notes- oder Domino-Kunde haben Sie vielleicht mit unerwartet hohen Benutzerzahlen und Lizenzgebühren zu kämpfen. Sie fragen sich vielleicht, wie diese neue Art der Lizenzierung funktioniert und welchen Nutzen sie Ihnen bringt. Vor allem wollen Sie sicherlich Ihr Budget einhalten und Kosten sparen, wo immer möglich. Das verstehen wir und wir möchten Ihnen dabei helfen!
Wir erklären Ihnen, wie Sie häufige Konfigurationsprobleme lösen können, die dazu führen können, dass mehr Benutzer gezählt werden als nötig, und wie Sie überflüssige oder ungenutzte Konten identifizieren und entfernen können, um Geld zu sparen. Es gibt auch einige Ansätze, die zu unnötigen Ausgaben führen können, z. B. wenn ein Personendokument anstelle eines Mail-Ins für geteilte Mailboxen verwendet wird. Wir zeigen Ihnen solche Fälle und deren Lösungen. Und natürlich erklären wir Ihnen das neue Lizenzmodell.
Nehmen Sie an diesem Webinar teil, bei dem HCL-Ambassador Marc Thomas und Gastredner Franz Walder Ihnen diese neue Welt näherbringen. Es vermittelt Ihnen die Tools und das Know-how, um den Überblick zu bewahren. Sie werden in der Lage sein, Ihre Kosten durch eine optimierte Domino-Konfiguration zu reduzieren und auch in Zukunft gering zu halten.
Diese Themen werden behandelt
- Reduzierung der Lizenzkosten durch Auffinden und Beheben von Fehlkonfigurationen und überflüssigen Konten
- Wie funktionieren CCB- und CCX-Lizenzen wirklich?
- Verstehen des DLAU-Tools und wie man es am besten nutzt
- Tipps für häufige Problembereiche, wie z. B. Team-Postfächer, Funktions-/Testbenutzer usw.
- Praxisbeispiele und Best Practices zum sofortigen Umsetzen
More Related Content
Similar to Ray Marching Explained
Reed solomon Encoder and Decoder
The document outlines Reed-Solomon error correction codes. It discusses how Reed-Solomon codes encode data using a generator polynomial to produce parity check symbols. The document then describes how Reed-Solomon codes can decode errors using syndrome calculation, error location polynomials, and finding the error positions and values through algorithms like Forney's method and Chien search. Reed-Solomon codes are widely used in applications like CDs, DVDs, wireless communications and digital television for their ability to efficiently correct both random and burst errors.
Overlap Layout Consensus assembly
OLC assembly involves three main steps:
1. Overlap - Compute all overlaps between reads to construct an overlap graph
2. Layout - Bundle stretches of the overlap graph into contigs
3. Consensus - Pick the most likely nucleotide sequence for each contig by determining consensus from the underlying reads
Linkedin_PowerPoint
This document presents an outer approximation solution algorithm for solving reliable shortest path problems on transportation networks. The algorithm formulates the problem as a mixed integer conic quadratic program to minimize the mean plus standard deviation of path costs. It then uses an outer approximation approach to decompose the problem and solve it efficiently through alternating steps of solving a master problem and subproblem. Computational results on several test networks show the algorithm converges quickly and outperforms directly solving the large-scale mixed integer conic quadratic program. The approach can also be applied to other reliability metrics and joint inventory location problems.
No more dumb hex!
Troopers, Heidelberg, Germany
21 March 2019
co-presented and designed with Rafał Hirsz
https://github.com/corkami/sbud
https://github.com/evoL/albert
Sbe final exam jan17 - solved-converted
This document contains a multi-part exam question regarding dynamic control systems. It asks the student to perform block diagram reductions to solve for various transfer functions T(s). It also asks the student to analyze the system poles, find damping ratio and natural frequency, and determine the unit impulse and step responses. Additional questions involve analyzing the characteristics of a flow system and determining sensitivity functions.
DISCRETE LOGARITHM PROBLEM
The document discusses public key cryptography based on the discrete logarithm problem (DLP). It defines the DLP and describes some common algorithms for solving it, including the ElGamal cryptosystem, Diffie-Hellman key exchange, baby-step giant-step algorithm, Pohlig-Hellman algorithm, and Pollard's rho algorithm. It also explains how the difficulty of solving the DLP can provide the basis for secure cryptographic systems.
Introduction to PyTorch
Basic concept of Deep Learning with explaining its structure and backpropagation method and understanding autograd in PyTorch. (+ Data parallism in PyTorch)
Elliptic Curve Cryptography
Elliptic curve cryptography (ECC) uses elliptic curves over finite fields for encryption, digital signatures, and key exchange. The key sizes are smaller than RSA for the same security level. Its security relies on the assumed hardness of solving the discrete logarithm problem over elliptic curves. ECC defines elliptic curves with parameters over Galois fields GF(p) for prime p or binary fields GF(2m). Points on the curves along with addition and doubling formulas are used to perform scalar multiplications for cryptographic operations.
Solucion de ejercicios de Analisis estructural I
This document contains solutions to structural analysis exercises involving determining forces in reinforcement bars. Exercise 41 involves a frame with nodes A, B, G and calculates the forces in the bars. The forces are: FAB = 25 kN (compression), FAG = 4 kN (compression), FCG = 5 kN (compression), FBG = 3 kN (tension). Exercise 42 involves a similar frame with nodes A, B, D, E, F, G, H and calculates forces such as: FAH = 18.92 kN (compression), FAB = 15.13 kN (tension), FCF = 2 kN (compression). Exercise 43 calculates forces in a frame with nodes A, B,
Reinforcement learning
This document provides an overview of reinforcement learning. It discusses how reinforcement learning differs from supervised and unsupervised learning by focusing on choosing actions to maximize long-term reward. It also formalizes reinforcement learning problems using Markov decision processes and describes algorithms like value iteration and policy iteration that can be used to find optimal policies.
Semana 11 numeros complejos ii álgebra-uni ccesa007
This document provides information about complex numbers including:
- Properties of complex numbers such as conjugates, opposites, and theorems regarding addition, multiplication, and powers of complex numbers.
- Calculating the modulus (absolute value) of a complex number.
- Representing a complex number in trigonometric form using modulus, argument, and cis notation.
- Examples of calculating modulus, finding conjugates and opposites, and converting complex numbers to trigonometric form.
Similar to Ray Marching Explained (11)
Semana 11 numeros complejos ii álgebra-uni ccesa007
Semana 11 numeros complejos ii álgebra-uni ccesa007
More from Mårten Rånge
Know your FOSS obligations
Free doesn't always means free of obligations. Knowing your FOSS obligations is good software practice.
Better performance through Superscalarity
How to employ "hidden" parallelism in CPU:s of today to improve the performance of CPU intensive algorithms
Property Based Tesing
Property-based testing involves generating random test data and checking that code satisfies specific properties for all possible inputs. This improves productivity and test quality by finding more bugs during development. The document discusses property-based testing of common data structures like maps and trees by specifying properties like nodes following certain ordering rules. It also mentions testing actions, models, and using property-based testing frameworks to generate random but reproducible tests based on a seed value. Property-based testing frameworks like QuickCheck, FsCheck, and ScalaCheck are mentioned.
Monad - a functional design pattern
This document discusses refactoring code to use functional design patterns, specifically monads. It begins by showing an example of defining attribute queries in a functional style using monads. It then explores monads in more depth, explaining their essence as separating computation composition from execution while allowing computations to carry extra implicit data. Common uses of monads are listed and additional resources provided for further understanding monads and their usefulness.
Formlets
Formlets are a way to build composable HTML forms that are type-safe, handle errors, are abstract, and easy to combine into larger forms. The key feature of formlets is that they are composable, like integers that can be added together or enumerables that can be selected, filtered and ordered. This allows text boxes, text areas, dropdowns and other form elements to be combined to create complex nested composite forms through binding operations. Demo code shows how common form validation and error handling tasks can be abstracted using formlets.
Pragmatic metaprogramming
Do not repeat yourself, we teach every fledgling software developer. It makes sense as with growing code redundancy the maintenance cost increase. Simple tools such as functions or loops are a great ways to reduce code redundancy but in our quest to avoid code redundancy we sometimes indulge into complexity. Complex code is also costly to maintain. I will demonstrate, using real-world examples, how one can adopt metaprogramming to minimize code redundancy as well keeping the code simple enough for my mom to understand it.
Concurrency - responsiveness in .NET
The document discusses concurrency and asynchronous programming in .NET. It covers three pillars of concurrency: scalability using Parallel.For, responsiveness using tasks and async/await, and consistency using locks, mutexes, etc. It demonstrates how async/await allows programs to be responsive by freeing threads for other work while waiting for I/O. A key point is that the SynchronizationContext impacts asynchronous code behavior and can cause unintended threading issues if not properly understood.
Meta Programming
The document discusses using T4 templates to reduce code repetition through metaprogramming. It provides examples of how T4 can generate exception classes, dependency properties, and other code automatically. The benefits of T4 include simplifying complex patterns, making debugging easier, and saving developer time by avoiding repetitive manual coding tasks. T4 templates act as code generators that can produce any text-based output like C#, VB, or C++.
Concurrency scalability
Herb Sutter (GotW.ca) says that the concept of Concurrency is easier understood if split into three sub concepts; scalability, responsiveness and consistency. This presentation is the first of three covering these concepts, starting off with everyone’s favorite: Scalability – i.e. splitting a CPU-bound problem onto several cores in order to solve the problem faster. I will show what tools what .NET offer but also performance pitfalls that arise from an escalating problem that plagued computer architecture for the last 20 years.
Concurrency
This document discusses concurrency and parallelism in .NET. It covers three pillars of concurrency: scalability using Parallel.For, responsiveness using tasks and async/await, and consistency using locks, interlocked operations, and mutexes/events/semaphores. It also discusses challenges with shared state and race conditions when naively using Parallel.For on shared data. Several solutions are presented such as not sharing data, using smaller work chunks to reduce overhead, and running completely independent tasks in parallel. The document emphasizes the importance of measuring performance before and after optimizations.
More from Mårten Rånge (10)
Recently uploaded
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-und-domino-lizenzkostenreduzierung-in-der-welt-von-dlau/
DLAU und die Lizenzen nach dem CCB- und CCX-Modell sind für viele in der HCL-Community seit letztem Jahr ein heißes Thema. Als Notes- oder Domino-Kunde haben Sie vielleicht mit unerwartet hohen Benutzerzahlen und Lizenzgebühren zu kämpfen. Sie fragen sich vielleicht, wie diese neue Art der Lizenzierung funktioniert und welchen Nutzen sie Ihnen bringt. Vor allem wollen Sie sicherlich Ihr Budget einhalten und Kosten sparen, wo immer möglich. Das verstehen wir und wir möchten Ihnen dabei helfen!
Wir erklären Ihnen, wie Sie häufige Konfigurationsprobleme lösen können, die dazu führen können, dass mehr Benutzer gezählt werden als nötig, und wie Sie überflüssige oder ungenutzte Konten identifizieren und entfernen können, um Geld zu sparen. Es gibt auch einige Ansätze, die zu unnötigen Ausgaben führen können, z. B. wenn ein Personendokument anstelle eines Mail-Ins für geteilte Mailboxen verwendet wird. Wir zeigen Ihnen solche Fälle und deren Lösungen. Und natürlich erklären wir Ihnen das neue Lizenzmodell.
Nehmen Sie an diesem Webinar teil, bei dem HCL-Ambassador Marc Thomas und Gastredner Franz Walder Ihnen diese neue Welt näherbringen. Es vermittelt Ihnen die Tools und das Know-how, um den Überblick zu bewahren. Sie werden in der Lage sein, Ihre Kosten durch eine optimierte Domino-Konfiguration zu reduzieren und auch in Zukunft gering zu halten.
Diese Themen werden behandelt
- Reduzierung der Lizenzkosten durch Auffinden und Beheben von Fehlkonfigurationen und überflüssigen Konten
- Wie funktionieren CCB- und CCX-Lizenzen wirklich?
- Verstehen des DLAU-Tools und wie man es am besten nutzt
- Tipps für häufige Problembereiche, wie z. B. Team-Postfächer, Funktions-/Testbenutzer usw.
- Praxisbeispiele und Best Practices zum sofortigen Umsetzen
Generating privacy-protected synthetic data using Secludy and Milvus
During this demo, the founders of Secludy will demonstrate how their system utilizes Milvus to store and manipulate embeddings for generating privacy-protected synthetic data. Their approach not only maintains the confidentiality of the original data but also enhances the utility and scalability of LLMs under privacy constraints. Attendees, including machine learning engineers, data scientists, and data managers, will witness first-hand how Secludy's integration with Milvus empowers organizations to harness the power of LLMs securely and efficiently.
5th LF Energy Power Grid Model Meet-up Slides
5th Power Grid Model Meet-up
It is with great pleasure that we extend to you an invitation to the 5th Power Grid Model Meet-up, scheduled for 6th June 2024. This event will adopt a hybrid format, allowing participants to join us either through an online Mircosoft Teams session or in person at TU/e located at Den Dolech 2, Eindhoven, Netherlands. The meet-up will be hosted by Eindhoven University of Technology (TU/e), a research university specializing in engineering science & technology.
Power Grid Model
The global energy transition is placing new and unprecedented demands on Distribution System Operators (DSOs). Alongside upgrades to grid capacity, processes such as digitization, capacity optimization, and congestion management are becoming vital for delivering reliable services.
Power Grid Model is an open source project from Linux Foundation Energy and provides a calculation engine that is increasingly essential for DSOs. It offers a standards-based foundation enabling real-time power systems analysis, simulations of electrical power grids, and sophisticated what-if analysis. In addition, it enables in-depth studies and analysis of the electrical power grid’s behavior and performance. This comprehensive model incorporates essential factors such as power generation capacity, electrical losses, voltage levels, power flows, and system stability.
Power Grid Model is currently being applied in a wide variety of use cases, including grid planning, expansion, reliability, and congestion studies. It can also help in analyzing the impact of renewable energy integration, assessing the effects of disturbances or faults, and developing strategies for grid control and optimization.
What to expect
For the upcoming meetup we are organizing, we have an exciting lineup of activities planned:
-Insightful presentations covering two practical applications of the Power Grid Model.
-An update on the latest advancements in Power Grid -Model technology during the first and second quarters of 2024.
-An interactive brainstorming session to discuss and propose new feature requests.
-An opportunity to connect with fellow Power Grid Model enthusiasts and users.
leewayhertz.com-AI in predictive maintenance Use cases technologies benefits ...
Predictive maintenance is a proactive approach that anticipates equipment failures before they happen. At the forefront of this innovative strategy is Artificial Intelligence (AI), which brings unprecedented precision and efficiency. AI in predictive maintenance is transforming industries by reducing downtime, minimizing costs, and enhancing productivity.
Programming Foundation Models with DSPy - Meetup Slides
Prompting language models is hard, while programming language models is easy. In this talk, I will discuss the state-of-the-art framework DSPy for programming foundation models with its powerful optimizers and runtime constraint system.
Operating System Used by Users in day-to-day life.pptx
Dive into the realm of operating systems (OS) with Pravash Chandra Das, a seasoned Digital Forensic Analyst, as your guide. 🚀 This comprehensive presentation illuminates the core concepts, types, and evolution of OS, essential for understanding modern computing landscapes.
Beginning with the foundational definition, Das clarifies the pivotal role of OS as system software orchestrating hardware resources, software applications, and user interactions. Through succinct descriptions, he delineates the diverse types of OS, from single-user, single-task environments like early MS-DOS iterations, to multi-user, multi-tasking systems exemplified by modern Linux distributions.
Crucial components like the kernel and shell are dissected, highlighting their indispensable functions in resource management and user interface interaction. Das elucidates how the kernel acts as the central nervous system, orchestrating process scheduling, memory allocation, and device management. Meanwhile, the shell serves as the gateway for user commands, bridging the gap between human input and machine execution. 💻
The narrative then shifts to a captivating exploration of prominent desktop OSs, Windows, macOS, and Linux. Windows, with its globally ubiquitous presence and user-friendly interface, emerges as a cornerstone in personal computing history. macOS, lauded for its sleek design and seamless integration with Apple's ecosystem, stands as a beacon of stability and creativity. Linux, an open-source marvel, offers unparalleled flexibility and security, revolutionizing the computing landscape. 🖥️
Moving to the realm of mobile devices, Das unravels the dominance of Android and iOS. Android's open-source ethos fosters a vibrant ecosystem of customization and innovation, while iOS boasts a seamless user experience and robust security infrastructure. Meanwhile, discontinued platforms like Symbian and Palm OS evoke nostalgia for their pioneering roles in the smartphone revolution.
The journey concludes with a reflection on the ever-evolving landscape of OS, underscored by the emergence of real-time operating systems (RTOS) and the persistent quest for innovation and efficiency. As technology continues to shape our world, understanding the foundations and evolution of operating systems remains paramount. Join Pravash Chandra Das on this illuminating journey through the heart of computing. 🌟
Artificial Intelligence for XMLDevelopment
In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.
Azure API Management to expose backend services securely
How to use Azure API Management to expose backend service securely
Introduction of Cybersecurity with OSS at Code Europe 2024
I develop the Ruby programming language, RubyGems, and Bundler, which are package managers for Ruby. Today, I will introduce how to enhance the security of your application using open-source software (OSS) examples from Ruby and RubyGems.
The first topic is CVE (Common Vulnerabilities and Exposures). I have published CVEs many times. But what exactly is a CVE? I'll provide a basic understanding of CVEs and explain how to detect and handle vulnerabilities in OSS.
Next, let's discuss package managers. Package managers play a critical role in the OSS ecosystem. I'll explain how to manage library dependencies in your application.
I'll share insights into how the Ruby and RubyGems core team works to keep our ecosystem safe. By the end of this talk, you'll have a better understanding of how to safeguard your code.
Digital Marketing Trends in 2024 | Guide for Staying Ahead
https://www.wask.co/ebooks/digital-marketing-trends-in-2024
Feeling lost in the digital marketing whirlwind of 2024? Technology is changing, consumer habits are evolving, and staying ahead of the curve feels like a never-ending pursuit. This e-book is your compass. Dive into actionable insights to handle the complexities of modern marketing. From hyper-personalization to the power of user-generated content, learn how to build long-term relationships with your audience and unlock the secrets to success in the ever-shifting digital landscape.
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
Building Production Ready Search Pipelines with Spark and Milvus
Spark is the widely used ETL tool for processing, indexing and ingesting data to serving stack for search. Milvus is the production-ready open-source vector database. In this talk we will show how to use Spark to process unstructured data to extract vector representations, and push the vectors to Milvus vector database for search serving.
Taking AI to the Next Level in Manufacturing.pdf
Read Taking AI to the Next Level in Manufacturing to gain insights on AI adoption in the manufacturing industry, such as:
1. How quickly AI is being implemented in manufacturing.
2. Which barriers stand in the way of AI adoption.
3. How data quality and governance form the backbone of AI.
4. Organizational processes and structures that may inhibit effective AI adoption.
6. Ideas and approaches to help build your organization's AI strategy.
Monitoring and Managing Anomaly Detection on OpenShift.pdf
Monitoring and Managing Anomaly Detection on OpenShift
Overview
Dive into the world of anomaly detection on edge devices with our comprehensive hands-on tutorial. This SlideShare presentation will guide you through the entire process, from data collection and model training to edge deployment and real-time monitoring. Perfect for those looking to implement robust anomaly detection systems on resource-constrained IoT/edge devices.
Key Topics Covered
1. Introduction to Anomaly Detection
- Understand the fundamentals of anomaly detection and its importance in identifying unusual behavior or failures in systems.
2. Understanding Edge (IoT)
- Learn about edge computing and IoT, and how they enable real-time data processing and decision-making at the source.
3. What is ArgoCD?
- Discover ArgoCD, a declarative, GitOps continuous delivery tool for Kubernetes, and its role in deploying applications on edge devices.
4. Deployment Using ArgoCD for Edge Devices
- Step-by-step guide on deploying anomaly detection models on edge devices using ArgoCD.
5. Introduction to Apache Kafka and S3
- Explore Apache Kafka for real-time data streaming and Amazon S3 for scalable storage solutions.
6. Viewing Kafka Messages in the Data Lake
- Learn how to view and analyze Kafka messages stored in a data lake for better insights.
7. What is Prometheus?
- Get to know Prometheus, an open-source monitoring and alerting toolkit, and its application in monitoring edge devices.
8. Monitoring Application Metrics with Prometheus
- Detailed instructions on setting up Prometheus to monitor the performance and health of your anomaly detection system.
9. What is Camel K?
- Introduction to Camel K, a lightweight integration framework built on Apache Camel, designed for Kubernetes.
10. Configuring Camel K Integrations for Data Pipelines
- Learn how to configure Camel K for seamless data pipeline integrations in your anomaly detection workflow.
11. What is a Jupyter Notebook?
- Overview of Jupyter Notebooks, an open-source web application for creating and sharing documents with live code, equations, visualizations, and narrative text.
12. Jupyter Notebooks with Code Examples
- Hands-on examples and code snippets in Jupyter Notebooks to help you implement and test anomaly detection models.
Main news related to the CCS TSI 2023 (2023/1695)
An English 🇬🇧 translation of a presentation to the speech I gave about the main changes brought by CCS TSI 2023 at the biggest Czech conference on Communications and signalling systems on Railways, which was held in Clarion Hotel Olomouc from 7th to 9th November 2023 (konferenceszt.cz). Attended by around 500 participants and 200 on-line followers.
The original Czech 🇨🇿 version of the presentation can be found here: https://www.slideshare.net/slideshow/hlavni-novinky-souvisejici-s-ccs-tsi-2023-2023-1695/269688092 .
The videorecording (in Czech) from the presentation is available here: https://youtu.be/WzjJWm4IyPk?si=SImb06tuXGb30BEH .
Recently uploaded (20)
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
Deep Dive: Getting Funded with Jason Jason Lemkin Founder & CEO @ SaaStr
Deep Dive: Getting Funded with Jason Jason Lemkin Founder & CEO @ SaaStr
Generating privacy-protected synthetic data using Secludy and Milvus
Generating privacy-protected synthetic data using Secludy and Milvus
leewayhertz.com-AI in predictive maintenance Use cases technologies benefits ...
leewayhertz.com-AI in predictive maintenance Use cases technologies benefits ...
Overcoming the PLG Trap: Lessons from Canva's Head of Sales & Head of EMEA Da...
Overcoming the PLG Trap: Lessons from Canva's Head of Sales & Head of EMEA Da...
Programming Foundation Models with DSPy - Meetup Slides
Programming Foundation Models with DSPy - Meetup Slides
Operating System Used by Users in day-to-day life.pptx
Operating System Used by Users in day-to-day life.pptx
WeTestAthens: Postman's AI & Automation Techniques
WeTestAthens: Postman's AI & Automation Techniques
Azure API Management to expose backend services securely
Azure API Management to expose backend services securely
Introduction of Cybersecurity with OSS at Code Europe 2024
Introduction of Cybersecurity with OSS at Code Europe 2024
Digital Marketing Trends in 2024 | Guide for Staying Ahead
Digital Marketing Trends in 2024 | Guide for Staying Ahead
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
Building Production Ready Search Pipelines with Spark and Milvus
Building Production Ready Search Pipelines with Spark and Milvus
Deep Dive: AI-Powered Marketing to Get More Leads and Customers with HyperGro...
Deep Dive: AI-Powered Marketing to Get More Leads and Customers with HyperGro...
Monitoring and Managing Anomaly Detection on OpenShift.pdf
Monitoring and Managing Anomaly Detection on OpenShift.pdf
Ray Marching Explained
- 1. Ray Marching Explained Mårten Rånge
- 13. r d p 𝑑 = 𝑝 − 𝑟
- 14. Show us the code
- 15. Lighting
- 16. 𝑛𝑜𝑟𝑚𝑎𝑙
- 17. 𝑛𝑜𝑟𝑚𝑎𝑙
- 18. 10 51520
- 19. 𝑛: 𝑛𝑜𝑟𝑚𝑎𝑙𝑖𝑧𝑒(𝑑 𝑝 + 𝑒𝑥 − 𝑑 𝑝 − 𝑒𝑥 , 𝑑 𝑝 + 𝑒𝑦 − 𝑑 𝑝 − 𝑒𝑦 , 𝑑 𝑝 + 𝑒𝑧 − 𝑑 𝑝 − 𝑒𝑧 ) 𝑒𝑧: (0, 0, 𝑒𝑝𝑠𝑖𝑙𝑜𝑛) 𝑒𝑦: (0, 𝑒𝑝𝑠𝑖𝑙𝑜𝑛, 0) 𝑒𝑥: (𝑒𝑝𝑠𝑖𝑙𝑜𝑛, 0, 0) 𝑝: 𝑝𝑜𝑖𝑛𝑡𝑂𝑛𝑆𝑢𝑟𝑓𝑎𝑐𝑒 𝑑: 𝑑𝑖𝑠𝑡𝑎𝑛𝑐𝑒𝑇𝑜𝑆𝑢𝑟𝑓𝑎𝑐𝑒
- 20. 𝑑𝑖𝑓𝑓𝑢𝑠𝑒 a
- 21. 𝑑𝑖𝑓𝑓𝑢𝑠𝑒: 𝑚𝑎𝑥(𝑑𝑜𝑡 𝑛𝑜𝑟𝑚𝑎𝑙, 𝑙𝑖𝑔ℎ𝑡𝐷𝑖𝑟𝑒𝑐𝑡𝑖𝑜𝑛 , 0)
- 22. 𝑠𝑝𝑒𝑐𝑢𝑙𝑎𝑟 a a b
- 23. 𝑠𝑝𝑒𝑐𝑢𝑙𝑎𝑟: 𝑚𝑎𝑥 𝑑𝑜𝑡 𝑟𝑒𝑓𝑙𝑒𝑐𝑡 𝑙𝑖𝑔ℎ𝑡𝐷𝑖𝑟𝑒𝑐𝑡𝑖𝑜𝑛, 𝑛𝑜𝑟𝑚𝑎𝑙 , 𝑒𝑦𝑒𝐷𝑖𝑟𝑒𝑐𝑡𝑖𝑜𝑛 , 0 𝑓𝑜𝑐𝑢𝑠
- 24. Show us the code
- 26. 𝑢𝑛𝑖𝑜𝑛: 𝑚𝑖𝑛(𝑑1, 𝑑2) 𝑖𝑛𝑡𝑒𝑟𝑠𝑒𝑐𝑡𝑖𝑜𝑛: 𝑚𝑎𝑥(𝑑1, 𝑑2) 𝑠𝑢𝑏𝑡𝑟𝑎𝑐𝑡𝑖𝑜𝑛: 𝑚𝑎𝑥(𝑑1, −𝑑2) 𝑏𝑜𝑜𝑙𝑒𝑎𝑛 𝑜𝑝𝑒𝑟𝑎𝑡𝑜𝑟𝑠
- 27. 𝑠𝑐𝑎𝑙𝑒: 𝑑(𝑝 ∗ 𝑠)/𝑠 𝑟𝑒𝑝𝑒𝑡𝑖𝑡𝑖𝑜𝑛: 𝑑(𝑚𝑜𝑑 𝑝, 𝑟 − 0.5𝑟) 𝑡𝑟𝑎𝑛𝑠𝑙𝑎𝑡𝑖𝑜𝑛: 𝑑(𝑝 − 𝑡) 𝑑𝑜𝑚𝑎𝑖𝑛 𝑜𝑝𝑒𝑟𝑎𝑡𝑜𝑟𝑠
- 28. Show us the code
- 29. Shadows
- 30. 𝑠𝑜𝑓𝑡 𝑠ℎ𝑎𝑑𝑜𝑤𝑠
- 32. Show us the code
- 33. All together now
- 34. Cool shadertoy examples • Graphics + Music • https://www.shadertoy.com/view/4tc3zf • 460 lines! • https://www.shadertoy.com/view/4sjSW1 • https://www.shadertoy.com/view/XlBGz3 • Retro! • Mandel bulb • https://www.shadertoy.com/view/ltfSWn • Advanced modeling • https://www.shadertoy.com/view/ld3Gz2 • Terrains • https://www.shadertoy.com/view/MdlGW7 • https://www.shadertoy.com/view/4ttSWf • https://www.shadertoy.com/view/XslGRr
- 35. Links • Raymarching explanined • http://9bitscience.blogspot.com/2013/07/raymarching-distance-fields_14.html • Links other useful resources as well • Advanced operators • http://mercury.sexy/hg_sdf/ • NNUG Demos • https://www.shadertoy.com/view/4t3cDl • https://www.shadertoy.com/view/Xl3cDl • https://www.shadertoy.com/view/Xl3cDs • https://www.shadertoy.com/view/MtcyWl • https://www.shadertoy.com/view/ltccD2
- 37. Questions?