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Copy file name to clipboardExpand all lines: posts/3DRoute/3DRoute.nd
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:: import "./macros.js"; ::
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title: 3D Route
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creationDate: 22/12/2021
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After discovering that phone sensor data can be accessed from the browser[^hardware], I decided to do a project with that. This project is a way to visualize this sensor data. In this demo, you will see a wireframe abstraction of a phone, moving in space, with its movement tracing a path.
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After discovering that phone sensor data can be accessed from the browser[^hardware], I decided to build a project around it. This project is a way to visualize that sensor data. In this demo, you can see a wireframe abstraction of a phone moving in space, with its movement tracing a path.
Copy file name to clipboardExpand all lines: posts/ArcSummary/ArcSummary.nd
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This blog entry redirects you to my masters thesis about _"Arc Summaries of TV Series"_. Although I _couldn't test it properly_, in the paper there are a good description of the algorithms that were developed/used for *segmentation*, *clustering* and *summarization* of text signals. In the paper we used [Spectral Graph Theory](https://en.wikipedia.org/wiki/Spectral_graph_theory) framework to solve most of the problems, relating this area with glimpses of other fields such as [Discrete Exterior Calculus](https://en.wikipedia.org/wiki/Discrete_exterior_calculus), [Functional Data Analysis](https://en.wikipedia.org/wiki/Functional_data_analysis).
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This blog entry redirects you to my master's thesis, _"Arc Summaries of TV Series"_. Although I _couldn't test it properly_, the paper contains a good description of the algorithms developed and used for *segmentation*, *clustering*, and *summarization* of text signals. In the paper, we used the [Spectral Graph Theory](https://en.wikipedia.org/wiki/Spectral_graph_theory) framework to solve most of the problems, connecting this area with ideas from other fields such as [Discrete Exterior Calculus](https://en.wikipedia.org/wiki/Discrete_exterior_calculus) and [Functional Data Analysis](https://en.wikipedia.org/wiki/Functional_data_analysis).
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## Abstract
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In this dissertation, we aim to create a system capable of generating summaries of arcs of TV series. With thousands of hours of video being uploaded and stored in video-sharing websites and online streaming services, a need for video summarization appears as a necessary tool to save time and catch up with our beloved series. We propose a way to solve this problem using just subtitles information. The presented solution uses the framework of spectral graph theory to segment, find story arcs and summarize those arcs.
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In this dissertation, we aim to create a system capable of generating summaries of TV series story arcs. With thousands of hours of video being uploaded and stored on video-sharing websites and online streaming services, video summarization becomes a necessary tool to save time and catch up with our beloved series. We propose a way to solve this problem using only subtitle information. The presented solution uses the spectral graph theory framework to segment episodes, identify story arcs, and summarize those arcs.
- [Presentation (watch it in presentation mode)](https://docs.google.com/presentation/d/1iQXAZszNOVqrjnANjOsVPEUHrQNjqlOWJqWMKAidRgc/edit?usp=sharing)
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- [Presentation (watch it in presentation mode)](https://docs.google.com/presentation/d/1iQXAZszNOVqrjnANjOsVPEUHrQNjqlOWJqWMKAidRgc/edit?usp=sharing)
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## Video Tutorial
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In this video tutorial, you will understand how to use the software made for implementation of the thesis.
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In this video tutorial, you will learn how to use the software built to implement the thesis.
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## Running with docker
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## Running with Docker
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Just run:
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```
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It will run a page at `localhost:31415/ArcSummary`. There you must insert the full path to folder where the series is in the container.
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It will run a page at `localhost:31415/ArcSummary`. There, you must enter the full path to the folder where the series is located inside the container.
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### Example
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A simple example would be:
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A simple example would be:
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```sh
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sudo docker run -it -v ~/Downloads/OverTheGardenWall:/app/OverTheGardenWall -p 31415:31415 pedroth/arc-summary
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```
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Then in `localhost:31415/ArcSummary`, in the `base folder` input you should put `/app/OverTheGardenWall`. For more details check the video tutorial above.
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Then, at `localhost:31415/ArcSummary`, in the `base folder` input, you should enter `/app/OverTheGardenWall`. For more details, check the video tutorial above.
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## Artifacts
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As said above, you can test the software by using docker, or use the alternative, which is to download the artifacts below:
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As mentioned above, you can test the software by using Docker, or use the alternative option, which is to download the artifacts below:
Copy file name to clipboardExpand all lines: posts/BitCalculator/BitCalculator.nd
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_Bit Calculator_ is a simple _parser_ and _evaluator_ for mathematical expressions in binary. My main motivation for creating this, was to study [formal grammars](https://en.wikipedia.org/wiki/Formal_grammar), [parsers](https://en.wikipedia.org/wiki/Recursive_descent_parser) and [compilers](https://en.wikipedia.org/wiki/Compiler). To achieve this, I tried to build the simplest parser I could, using no dependencies. The parser that was implemented is similar to a [parser combinator](https://en.wikipedia.org/wiki/Parser_combinator). With the practice I have got from this I started to write the [Nabladown language](https://github.com/pedroth/nabladown.js).
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_Bit Calculator_ is a simple _parser_ and _evaluator_ for mathematical expressions in binary. My main motivation for creating this was to study [formal grammars](https://en.wikipedia.org/wiki/Formal_grammar), [parsers](https://en.wikipedia.org/wiki/Recursive_descent_parser), and [compilers](https://en.wikipedia.org/wiki/Compiler). To achieve this, I tried to build the simplest parser I could, with no dependencies. The implemented parser is similar to a [parser combinator](https://en.wikipedia.org/wiki/Parser_combinator). With the practice I got from this project, I started writing the [Nabladown language](https://github.com/pedroth/nabladown.js).
Copy file name to clipboardExpand all lines: posts/BrownianMotion/BrownianMotion.nd
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_Brownian Motion_ is `java` application where particles collide with each other. In this program you are able to control the direction of a constant length force field. I created it because I enjoy observing the dynamics of the system. Enjoy!
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_Brownian Motion_ is a `Java` application where particles collide with each other. In this program, you can control the direction of a constant-magnitude force field. I created it because I enjoy observing the dynamics of the system. Enjoy!
All balls have the same size and start in a random position and velocity. They can be accelerated by a constant force field $X$, controlled by the user. When a ball is moving in free space it moves as an accelerated object:
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All balls have the same size and start with random positions and velocities. They can be accelerated by a constant force field $X$, controlled by the user. When a ball is moving in free space, it behaves like an accelerated object:
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$$ \ddot p_i = X $$
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@quote(){
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$p_i$ is the position of the ball.
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}
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The interesting behavior is when there is a *collision* between two balls. In this regime the ball velocity will be updated as follows:
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The interesting behavior appears when there is a *collision* between two balls. In this regime, the ball velocity is updated as follows:
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$$
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\dot p_i = v_i - (2 - \beta) \left < v_i, n \right> n
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$$
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Where $v$ is the velocity of the ball before collision and $n$ is the normalized normal to the plane of contact between the balls in collision. That is:
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Here, $v$ is the velocity of the ball before collision, and $n$ is the normalized normal to the contact plane between the colliding balls. That is:
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$$n = \frac{p_i - p_j}{|p_i - p_j|}$$
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While $\beta$ is the damping factor, which is a value between $0< \beta < 1$. Where $\beta = 0$.
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Here, $\beta$ is the damping factor, with values in the range $0< \beta < 1$.
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This simulation doesn't try to follow the rules of physics, instead it tries to be a cool dynamical system.
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This simulation is not trying to be physically exact. It just aims to be a cool dynamical system.
Copy file name to clipboardExpand all lines: posts/CellularAutomaton/CellularAutomaton.nd
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I made a simple [*Cellular Automaton*][automaton] application long time ago. Here each pixel represents a [cellular automaton][automaton] which is *alive* if is green or *dead* if is dark. The rules for the cellular automaton to be born and to survive are defined by the $S/B$ rules:
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- $S$ defines counts of alive neighbors necessary for a cell to survive.
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- $B$ defines counts of alive neighbors necessary for a cell to be born.
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I made a simple [*Cellular Automaton*][automaton] application a long time ago. Here, each pixel represents a [cellular automaton][automaton], which is *alive* if it is green and *dead* if it is dark. The rules for a cellular automaton to be born and to survive are defined by the $S/B$ notation:
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- $S$ defines the numbers of live neighbors required for a cell to survive.
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- $B$ defines the numbers of live neighbors required for a cell to be born.
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If cell is not born or does not survive, then it dies or remains dead.
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If a cell is not born or does not survive, then it dies or remains dead.
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In this _app_ you can try several [cellular automata rules][rules]:
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In this _app_, you can try several [cellular automata rules][rules]:
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