hpcwiki - User contributions [en]

Cluster Ucentral Hpclab

2016-10-27T18:46:20Z

Jmolinar: /* Software & Libraries */

'''Manuelas de configuración cluster Hplab'''

== Configuration ==

* [[Installing and Testing TFTP Server in Ubuntu]]
*

== Testing ==
*...

== Software & Libraries ==
* GCC compiler: [[gcc]]
* Fast Fourier Transform: [[fftw3]]
* OpenMPI parallelization libraries: [[MPI]]
* NetCDF big file library: [[netcdf]]
* ScalaPack: [[scalapack]]
* LibTool: [[libtool]]
* Tensorflow: [https://www.tensorflow.org/versions/r0.11/get_started/index.html tensorflow]

=== TO-DO ===

* Matlab 64 bits
* Python,
** NumPy
** ScyPy
** Jupyter
** Anaconda
** iPython
* Apache Spark
* Hadoop
* GNU R
* COMSOL Multiphysics

Cluster Ucentral Hpclab

2016-10-27T18:45:47Z

Jmolinar: /* Software & Libraries */

'''Manuelas de configuración cluster Hplab'''

== Configuration ==

* [[Installing and Testing TFTP Server in Ubuntu]]
*

== Testing ==
*...

== Software & Libraries ==
* GCC compiler: [[gcc]]
* Fast Fourier Transform: [[fftw3]]
* OpenMPI parallelization libraries: [[MPI]]
* NetCDF big file library: [[netcdf]]
* ScalaPack: [[scalapack]]
* LibTool: [[libtool]]
* Tensorflow: [https://www.tensorflow.org/versions/r0.11/get_started/index.html:Link]

=== TO-DO ===

* Matlab 64 bits
* Python,
** NumPy
** ScyPy
** Jupyter
** Anaconda
** iPython
* Apache Spark
* Hadoop
* GNU R
* COMSOL Multiphysics

Cluster Ucentral Hpclab

2016-10-27T18:43:46Z

Jmolinar: /* Software & Libraries */

'''Manuelas de configuración cluster Hplab'''

== Configuration ==

* [[Installing and Testing TFTP Server in Ubuntu]]
*

== Testing ==
*...

== Software & Libraries ==
* GCC compiler: [[gcc]]
* Fast Fourier Transform: [[fftw3]]
* OpenMPI parallelization libraries: [[MPI]]
* NetCDF big file library: [[netcdf]]
* ScalaPack: [[scalapack]]
* LibTool: [[libtool]]
* Tensorflow: [https://www.tensorflow.org/versions/r0.11/get_started/index.htm:Link]

=== TO-DO ===

* Matlab 64 bits
* Python,
** NumPy
** ScyPy
** Jupyter
** Anaconda
** iPython
* Apache Spark
* Hadoop
* GNU R
* COMSOL Multiphysics

Cluster Ucentral Hpclab

2016-10-27T18:41:55Z

Jmolinar: /* Software & Libraries */

'''Manuelas de configuración cluster Hplab'''

== Configuration ==

* [[Installing and Testing TFTP Server in Ubuntu]]
*

== Testing ==
*...

== Software & Libraries ==
* GCC compiler: [[gcc]]
* Fast Fourier Transform: [[fftw3]]
* OpenMPI parallelization libraries: [[MPI]]
* NetCDF big file library: [[netcdf]]
* ScalaPack: [[scalapack]]
* LibTool: [[libtool]]
* Tensorflow: [https://www.tensorflow.org/versions/r0.11/get_started/index.htm | tensorflow]

=== TO-DO ===

* Matlab 64 bits
* Python,
** NumPy
** ScyPy
** Jupyter
** Anaconda
** iPython
* Apache Spark
* Hadoop
* GNU R
* COMSOL Multiphysics

Cluster Ucentral Hpclab

2016-10-27T18:41:29Z

Jmolinar: /* Software & Libraries */

'''Manuelas de configuración cluster Hplab'''

== Configuration ==

* [[Installing and Testing TFTP Server in Ubuntu]]
*

== Testing ==
*...

== Software & Libraries ==
* GCC compiler: [[gcc]]
* Fast Fourier Transform: [[fftw3]]
* OpenMPI parallelization libraries: [[MPI]]
* NetCDF big file library: [[netcdf]]
* ScalaPack: [[scalapack]]
* LibTool: [[libtool]]
* Tensorflow: [[https://www.tensorflow.org/versions/r0.11/get_started/index.htm| tensorflow]]

=== TO-DO ===

* Matlab 64 bits
* Python,
** NumPy
** ScyPy
** Jupyter
** Anaconda
** iPython
* Apache Spark
* Hadoop
* GNU R
* COMSOL Multiphysics

ROIs Relevants JFMR

2015-09-30T20:50:51Z

Jmolinar:

== Confluence ==

[[File:ConfluenceGradient.png|800px]]
[[File:ConfluenceGradientwithVectorField.png|800px]]

== Diffluence ==
[[File:DivergenceGradient.png|800px]]
[[File:DivergenceGradientwithVectorField.png|800px]]

== Saddle ==
[[File:SaddleGradient.png|800px]]
[[File:SaddleGradientWithVectorField.png|800px]]
== Vortex ==
[[File:VortexGradient.png|800px]]
[[File:VortexGradientwithVectorField.png|800px]]
== Vector Field ==

[[File:VectorField.png|800px]]

File:VectorField.png

2015-09-30T20:48:51Z

Jmolinar:

ROIs Relevants JFMR

2015-09-30T20:29:21Z

Jmolinar: /* Vortex */

File:VortexGradientwithVectorField.png

2015-09-30T20:29:04Z

Jmolinar:

File:VortexGradient.png

2015-09-30T20:28:30Z

Jmolinar:

ROIs Relevants JFMR

2015-09-30T20:27:30Z

Jmolinar:

== Confluence ==

[[File:ConfluenceGradient.png|800px]]
[[File:ConfluenceGradientwithVectorField.png|800px]]

== Diffluence ==
[[File:DivergenceGradient.png|800px]]
[[File:DivergenceGradientwithVectorField.png|800px]]

== Saddle ==
[[File:SaddleGradient.png|800px]]
[[File:SaddleGradientWithVectorField.png|800px]]
== Vortex ==
[[File:ConfluenceGradient.png|800px]]
[[File:ConfluenceGradientwithVectorField.png|800px]]

File:SaddleGradientWithVectorField.png

2015-09-30T20:27:16Z

Jmolinar:

File:SaddleGradient.png

2015-09-30T20:26:51Z

Jmolinar:

ROIs Relevants JFMR

2015-09-30T20:26:26Z

Jmolinar:

== Confluence ==

[[File:ConfluenceGradient.png|800px]]
[[File:ConfluenceGradientwithVectorField.png|800px]]

== Diffluence ==
[[File:DivergenceGradient.png|800px]]
[[File:DivergenceGradientwithVectorField.png|800px]]

== Saddle ==
[[File:ConfluenceGradient.png|800px]]
[[File:ConfluenceGradientwithVectorField.png|800px]]
== Vortex ==
[[File:ConfluenceGradient.png|800px]]
[[File:ConfluenceGradientwithVectorField.png|800px]]

File:DivergenceGradientwithVectorField.png

2015-09-30T20:26:00Z

Jmolinar:

File:DivergenceGradient.png

2015-09-30T20:25:02Z

Jmolinar:

ROIs Relevants JFMR

2015-09-30T20:24:03Z

Jmolinar: /* Confluence */

== Confluence ==

[[File:ConfluenceGradient.png|800px]]
[[File:ConfluenceGradientwithVectorField.png|800px]]

== Diffluence ==

== Saddle ==

== Vortex ==

File:ConfluenceGradientwithVectorField.png

2015-09-30T20:23:33Z

Jmolinar:

ROIs Relevants JFMR

2015-09-30T20:22:18Z

Jmolinar:

== Confluence ==

[[File:ConfluenceGradient.png|800px]]

== Diffluence ==

== Saddle ==

== Vortex ==

ROIs Relevants JFMR

2015-09-30T20:15:00Z

Jmolinar:

[[File:ConfluenceGradient.png|800px]]

File:ConfluenceGradient.png

2015-09-30T20:14:25Z

Jmolinar:

ROIs Relevants JFMR

2015-09-30T20:14:04Z

Jmolinar: Created page with "Edit ..."

Edit ...

Actividades Realizadas

2015-09-30T19:55:54Z

Jmolinar: /* Juan Molina */

== Reporte de avances ==

=== Douglas Baquero ===
* Bitácora de trabajo
** [[Bitácora Douglas Baquero]]

=== Juan Molina ===
* Bitácora de trabajo
** [[Bitácora Juan Molina]]
* Actividades de Desarrollo
** Herramienta de anotaciones para estructuras atmosféricas: [[Bitácora Juan Molina Herramienta de Anotaciones]]
** Protocolo de anotaciones para estructuras atmosféricas: [[Protocolo_de_anotaciones_ASAR| Protocolo de anotaciones]]
** Proceso de anotaciones: [[Avances_Anotaciones| Anotaciones Realizadas]]
* Tesis de Maestría
** [[Esquema_Tesis_JFMR | Esquema de tesis de maestría]]
** [[Experiments_JFMR| Experimentaciones realizadas]]
** [[DescriptorPropuesto_JFMR| Descriptor Definido]]
** [[Descriptor_Proposed_JFMR| Descriptor propuesto Juan Felipe Molina Rojas]]
** [[ROIs_Relevants_JFMR| Regiones de interes relevantes]]

=== Germán Sosa ===
# ...

=== Wilson Sierra ===
# ---

=== Marcela Duarte ===
# ...

=== Oscar Parada ===
* Thesis
** [[MSc Thesis OParada]]
** [[3D Surface Reconstruction Review]]
* TO-DO
** [[3D surface reconstruction algorithms - implementation]]
** [[3D Mesh validation, refinement and reduction]]

== Actas de Reuniones ==
# ACOLMET: [[Acta_Reunion | Reunión del día 10 de Junio]]

Descriptor Proposed JFMR

2015-09-26T23:39:58Z

Jmolinar: /* Implementation */

= Definition =

Given a vector field <math>\vec{V}=(u,v)</math>, where <math>u</math> and <math>v</math> represent the components of the winds of each of the annotations.

The vector field representation allow to observe the behavior of the winds in a determined region, these behavior are represented as:

* Vortex
* Confluence
* Difluence
* Saddle Point

The meteorologists annotated the different configurations that it can present in a period of time and a level determined, this process was done with an annotations tool that allow to select this configurations.

= Model Mathematic =

Given a vector field <math>\vec{V}</math>, a way to classify this configurations is through the use of phase portrait, this method is used in the dynamic system to understand the behavior of functions of 2 or more variables. In computer vision is used in the detection corner, mammography and others.

This method allows to construct a equation system in which these can calculate the determinant and the trace.

: <math> A =
\begin{bmatrix}
\frac{\partial U}{\partial x} & \frac{\partial U}{\partial y} \\
\frac{\partial V}{\partial x} & \frac{\partial V}{\partial y} \\
\end{bmatrix}
</math>

The trace and the determinant indicate as is the behavior of the system. To calculate the trace and determinant with their:

<math> Trace(A) = \frac{\partial U}{\partial x} + \frac{\partial V}{\partial y} </math>

<math> det(A) = \left(\frac{\partial U}{\partial x} \frac{\partial V}{\partial y}\right) - \left(\frac{\partial U}{\partial y} \frac{\partial V}{\partial x} \right) </math>

= Implementation =
The implementation of a descriptor that use the phase portrait depends of the components <math>u</math> and <math>v</math> obtained of the ROI that allow to construct the equation system, although needed the gradient of <math>u</math> and <math>v</math> to construct the system.

: <math> A =
\begin{bmatrix}
\frac{\partial U}{\partial x} & \frac{\partial U}{\partial y} \\
\frac{\partial V}{\partial x} & \frac{\partial V}{\partial y} \\
\end{bmatrix}
</math>

With the system, we can calculate the solution of the system through the equation characteristic <math>det(A-I\lambda) = 0</math> where I is the identify matrix of the size of A, at expand the equation obtains:
<math>\lambda^2-Trace(A)\lambda+det(A) = 0</math>, when we solve this equation obatin the next:

<math> \lambda_1,\lambda_2 = 0.5 (Trace(A) \pm \sqrt{Trace(A)^2 - 4det(A)})</math>

The descriptor is calculated using moments statistics in the trace and the determinant because is necessary to have a only value of these components, we use the mean, standard desviation and the variance, we use these 3 statistics

We obtain 2 values of a <math>\lambda</math> because it has a square root and it mean that we must with space real and complex. In the descriptor we use both and obtain 6 values and we aggregate the 3 statistics of the trace and the determinant

== Rules ==
* When <math>det(A) < 0</math> is saddle point.
* When <math>det(A) > 0</math> is possible a node or a spiral
* It is a spiral if <math>Trace(A)^2 - 4 det(A) < 0</math>
* It is a node if <math>Trace(A)^2 - 4 det(A) > 0</math>
* It is a stable if <math>Trace(A) < 0</math>
* It is a unstable if <math>Trace(A) > 0</math>

[[File:PhasePortraitRules.png|800px]]

In our case this rules can be used as features to describe the ROI

Descriptor Proposed JFMR

2015-09-26T20:27:14Z

Jmolinar:

= Definition =

Given a vector field <math>\vec{V}=(u,v)</math>, where <math>u</math> and <math>v</math> represent the components of the winds of each of the annotations.

The vector field representation allow to observe the behavior of the winds in a determined region, these behavior are represented as:

* Vortex
* Confluence
* Difluence
* Saddle Point

The meteorologists annotated the different configurations that it can present in a period of time and a level determined, this process was done with an annotations tool that allow to select this configurations.

= Model Mathematic =

Given a vector field <math>\vec{V}</math>, a way to classify this configurations is through the use of phase portrait, this method is used in the dynamic system to understand the behavior of functions of 2 or more variables. In computer vision is used in the detection corner, mammography and others.

This method allows to construct a equation system in which these can calculate the determinant and the trace.

: <math> A =
\begin{bmatrix}
\frac{\partial U}{\partial x} & \frac{\partial U}{\partial y} \\
\frac{\partial V}{\partial x} & \frac{\partial V}{\partial y} \\
\end{bmatrix}
</math>

The trace and the determinant indicate as is the behavior of the system. To calculate the trace and determinant with their:

<math> Trace(A) = \frac{\partial U}{\partial x} + \frac{\partial V}{\partial y} </math>

<math> det(A) = \left(\frac{\partial U}{\partial x} \frac{\partial V}{\partial y}\right) - \left(\frac{\partial U}{\partial y} \frac{\partial V}{\partial x} \right) </math>

= Implementation =
The implementation of a descriptor that use the phase portrait depends of the components <math>u</math> and <math>v</math> obtained of the simulation that allow to construct the equation system, although needed the gradient of <math>u</math> and <math>v</math> to construct the system.

: <math> A =
\begin{bmatrix}
\frac{\partial U}{\partial x} & \frac{\partial U}{\partial y} \\
\frac{\partial V}{\partial x} & \frac{\partial V}{\partial y} \\
\end{bmatrix}
</math>

With the system, we can calculate the solution of the system through the equation characteristic <math>det(A-I\lambda) = 0</math> where I is the identify matrix of the size of A, at expand the equation obtains:
<math>\lambda^2-Trace(A)\lambda+det(A) = 0</math>, when we solve this equation obatin the next:

<math> \lambda_1,\lambda_2 = 0.5 (Trace(A) \pm \sqrt{Trace(A)^2 - 4det(A)})</math>

The descriptor is calculated using moments statistics in the trace and the determinant because is necessary to have a only value of these components, we use the mean, standard desviation and the variance, we use these 3 statistics

We obtain 2 values of a <math>\lambda</math> because it has a square root and it mean that we must with space real and complex. In the descriptor we use both and obtain 6 values and we aggregate the 3 statistics of the trace and the determinant

== Rules ==
* When <math>det(A) < 0</math> is saddle point.
* When <math>det(A) > 0</math> is possible a node or a spiral
* It is a spiral if <math>Trace(A)^2 - 4 det(A) < 0</math>
* It is a node if <math>Trace(A)^2 - 4 det(A) > 0</math>
* It is a stable if <math>Trace(A) < 0</math>
* It is a unstable if <math>Trace(A) > 0</math>

[[File:PhasePortraitRules.png|800px]]

In our case this rules can be used as features to describe the ROI

Descriptor Proposed JFMR

2015-09-20T18:01:33Z

Jmolinar: /* Rules */

= Definition =

Given a vector field <math>\vec{V}=(u,v)</math>, where <math>u</math> and <math>v</math> represent the components of the winds of each of the annotations.

The vector field representation allow to observe the behavior of the winds in a determined region, these behavior are represented as:

* Vortex
* Confluence
* Difluence
* Saddle Point

The meteorologists annotated the different configurations that it can present in a period of time and a level determined, this process was done with an annotations tool that allow to select this configurations.

= Model Mathematic =

Given a vector field <math>\vec{V}</math>, a way to classify this configurations is through the use of phase portrait, this method is used in the dynamic system to understand the behavior of functions of 2 or more variables. In computer vision is used in the detection corner, mammography and others.

This method allows to construct a equation system in which these can calculate the determinant and the trace.

: <math> A =
\begin{bmatrix}
\frac{\partial U}{\partial x} & \frac{\partial U}{\partial y} \\
\frac{\partial V}{\partial x} & \frac{\partial V}{\partial y} \\
\end{bmatrix}
</math>

The trace and the determinant indicate as is the behavior of the system. To calculate the trace and determinant with their:

<math> Trace(A) = \frac{\partial U}{\partial x} + \frac{\partial V}{\partial y} </math>

<math> det(A) = \left(\frac{\partial U}{\partial x} \frac{\partial V}{\partial y}\right) - \left(\frac{\partial U}{\partial y} \frac{\partial V}{\partial x} \right) </math>

= Implementation =
The implementation of a descriptor that use the phase portrait depends of the components <math>u</math> and <math>v</math> obtained of the simulation that allow to construct the equation system, although needed the gradient of <math>u</math> and <math>v</math> to construct the system. With the system, we can calculate the solution of the system through the equation characteristic <math>det(A-I\lambda) = 0</math> where I is the identify matrix of the size of A, at expand the equation obtains:
<math>\lambda^2-Trace(A)\lambda+det(A) = 0</math>, when we solve this equation obatin the next:

<math> \lambda_1,\lambda_2 = 0.5 (Trace(A) \pm \sqrt{Trace(A)^2 - 4det(A)})</math>

The descriptor is calculated using moments statistics in the trace and the determinant because is necessary to have a only value of these components, we use the mean, standard desviation and the variance, we use these 3 statistics

We obtain 2 values of a <math>\lambda</math> because it has a square root and it mean that we must with space real and complex. In the descriptor we use both and obtain 6 values and we aggregate the 3 statistics of the trace and the determinant

== Rules ==
* When <math>det(A) < 0</math> is saddle point.
* When <math>det(A) > 0</math> is possible a node or a spiral
* It is a spiral if <math>Trace(A)^2 - 4 det(A) < 0</math>
* It is a node if <math>Trace(A)^2 - 4 det(A) > 0</math>
* It is a stable if <math>Trace(A) < 0</math>
* It is a unstable if <math>Trace(A) > 0</math>

[[File:PhasePortraitRules.png|800px]]

In our case this rules can be used as features to describe the ROI

Descriptor Proposed JFMR

2015-09-20T17:59:31Z

Jmolinar: /* Implementation */

= Definition =

Given a vector field <math>\vec{V}=(u,v)</math>, where <math>u</math> and <math>v</math> represent the components of the winds of each of the annotations.

The vector field representation allow to observe the behavior of the winds in a determined region, these behavior are represented as:

* Vortex
* Confluence
* Difluence
* Saddle Point

The meteorologists annotated the different configurations that it can present in a period of time and a level determined, this process was done with an annotations tool that allow to select this configurations.

= Model Mathematic =

Given a vector field <math>\vec{V}</math>, a way to classify this configurations is through the use of phase portrait, this method is used in the dynamic system to understand the behavior of functions of 2 or more variables. In computer vision is used in the detection corner, mammography and others.

This method allows to construct a equation system in which these can calculate the determinant and the trace.

: <math> A =
\begin{bmatrix}
\frac{\partial U}{\partial x} & \frac{\partial U}{\partial y} \\
\frac{\partial V}{\partial x} & \frac{\partial V}{\partial y} \\
\end{bmatrix}
</math>

The trace and the determinant indicate as is the behavior of the system. To calculate the trace and determinant with their:

<math> Trace(A) = \frac{\partial U}{\partial x} + \frac{\partial V}{\partial y} </math>

<math> det(A) = \left(\frac{\partial U}{\partial x} \frac{\partial V}{\partial y}\right) - \left(\frac{\partial U}{\partial y} \frac{\partial V}{\partial x} \right) </math>

= Implementation =
The implementation of a descriptor that use the phase portrait depends of the components <math>u</math> and <math>v</math> obtained of the simulation that allow to construct the equation system, although needed the gradient of <math>u</math> and <math>v</math> to construct the system. With the system, we can calculate the solution of the system through the equation characteristic <math>det(A-I\lambda) = 0</math> where I is the identify matrix of the size of A, at expand the equation obtains:
<math>\lambda^2-Trace(A)\lambda+det(A) = 0</math>, when we solve this equation obatin the next:

<math> \lambda_1,\lambda_2 = 0.5 (Trace(A) \pm \sqrt{Trace(A)^2 - 4det(A)})</math>

The descriptor is calculated using moments statistics in the trace and the determinant because is necessary to have a only value of these components, we use the mean, standard desviation and the variance, we use these 3 statistics

We obtain 2 values of a <math>\lambda</math> because it has a square root and it mean that we must with space real and complex. In the descriptor we use both and obtain 6 values and we aggregate the 3 statistics of the trace and the determinant

== Rules ==
* When <math>det(A) < 0</math> is saddle point.
* When <math>det(A) > 0</math> is possible a node or a spiral
* It is a spiral if <math>Trace(A)^2 - 4 det(A) < 0</math>
* It is a node if <math>Trace(A)^2 - 4 det(A) > 0</math>
* It is a stable if <math>Trace(A) < 0</math>
* It is a unstable if <math>Trace(A) > 0</math>

[[File:PhasePortraitRules.png|800px]]

Descriptor Proposed JFMR

2015-09-20T17:21:03Z

Jmolinar: /* Implementation */

= Definition =

Given a vector field <math>\vec{V}=(u,v)</math>, where <math>u</math> and <math>v</math> represent the components of the winds of each of the annotations.

The vector field representation allow to observe the behavior of the winds in a determined region, these behavior are represented as:

* Vortex
* Confluence
* Difluence
* Saddle Point

The meteorologists annotated the different configurations that it can present in a period of time and a level determined, this process was done with an annotations tool that allow to select this configurations.

= Model Mathematic =

Given a vector field <math>\vec{V}</math>, a way to classify this configurations is through the use of phase portrait, this method is used in the dynamic system to understand the behavior of functions of 2 or more variables. In computer vision is used in the detection corner, mammography and others.

This method allows to construct a equation system in which these can calculate the determinant and the trace.

: <math> A =
\begin{bmatrix}
\frac{\partial U}{\partial x} & \frac{\partial U}{\partial y} \\
\frac{\partial V}{\partial x} & \frac{\partial V}{\partial y} \\
\end{bmatrix}
</math>

The trace and the determinant indicate as is the behavior of the system. To calculate the trace and determinant with their:

<math> Trace(A) = \frac{\partial U}{\partial x} + \frac{\partial V}{\partial y} </math>

<math> det(A) = \left(\frac{\partial U}{\partial x} \frac{\partial V}{\partial y}\right) - \left(\frac{\partial U}{\partial y} \frac{\partial V}{\partial x} \right) </math>

= Implementation =
The implementation of a descriptor that use the phase portrait depends of the components <math>u</math> and <math>v</math> obtained of the simulation that allow to construct the equation system, although needed the gradient of <math>u</math> and <math>v</math> to construct the system. With the system, we can calculate the solution of the system through the equation characteristic <math>det(A-I\lambda) = 0</math> where I is the identify matrix of the size of A, at expand the equation obtains:
<math>\lambda^2-Trace(A)\lambda+det(A) = 0</math>, when we solve this equation obatin the next:

<math> \lambda_1,\lambda_2 = 0.5 (Trace(A) \pm \sqrt{Trace(A)^2 - 4det(A)})</math>

The descriptor is calculated using moments statistics in the trace and the determinant because is necessary to have a only value of these components, we use the mean, standard desviation and the variance, we use these 3 statistics

We obtain 2 values of a <math>\lambda</math> because it has a square root and it mean that we must with space real and complex. In the descriptor we use both and obtain 6 values and we aggregate the 3 statistics of the trace and the determinant

Descriptor Proposed JFMR

2015-09-20T01:02:31Z

Jmolinar: /* Implementation */

= Definition =

Given a vector field <math>\vec{V}=(u,v)</math>, where <math>u</math> and <math>v</math> represent the components of the winds of each of the annotations.

The vector field representation allow to observe the behavior of the winds in a determined region, these behavior are represented as:

* Vortex
* Confluence
* Difluence
* Saddle Point

The meteorologists annotated the different configurations that it can present in a period of time and a level determined, this process was done with an annotations tool that allow to select this configurations.

= Model Mathematic =

Given a vector field <math>\vec{V}</math>, a way to classify this configurations is through the use of phase portrait, this method is used in the dynamic system to understand the behavior of functions of 2 or more variables. In computer vision is used in the detection corner, mammography and others.

This method allows to construct a equation system in which these can calculate the determinant and the trace.

: <math> A =
\begin{bmatrix}
\frac{\partial U}{\partial x} & \frac{\partial U}{\partial y} \\
\frac{\partial V}{\partial x} & \frac{\partial V}{\partial y} \\
\end{bmatrix}
</math>

The trace and the determinant indicate as is the behavior of the system. To calculate the trace and determinant with their:

<math> Trace(A) = \frac{\partial U}{\partial x} + \frac{\partial V}{\partial y} </math>

<math> det(A) = \left(\frac{\partial U}{\partial x} \frac{\partial V}{\partial y}\right) - \left(\frac{\partial U}{\partial y} \frac{\partial V}{\partial x} \right) </math>

= Implementation =
The implementation of a descriptor that use the phase portrait depends of the components <math>u</math> and <math>v</math> obtained of the simulation that allow to construct the equation system, although needed the gradient of <math>u</math> and <math>v</math> to construct the system. With the system, we can calculate the solution of the system through the equation characteristic <math>det(A-I\lambda) = 0</math> where I is the identify matrix of the size of A, at expand the equation obtains:
<math>\lambda^2-Trace(A)\lambda+det(A) = 0</math> when we solve this equation have the next:

<math> \lambda_1,\lambda_2 = 0.5 (Trace(A) \pm \sqrt{Trace(A)^2 - 4det(A)})</math>

The descriptor is calculated using moments statistics in the trace and the determinant because is necessary to have a only value of these components, we use the mean, standard desviation and the variance, we use these 3 statistics

We obtain 2 values of a <math>\lambda</math> because it has a square root and it mean that we must with space real and complex. In the descriptor we use both and obtain 6 values and we aggregate the 3 statistics of the trace and the determinant

Descriptor Proposed JFMR

2015-09-20T00:56:06Z

Jmolinar: /* Implementation */

= Definition =

Given a vector field <math>\vec{V}=(u,v)</math>, where <math>u</math> and <math>v</math> represent the components of the winds of each of the annotations.

The vector field representation allow to observe the behavior of the winds in a determined region, these behavior are represented as:

* Vortex
* Confluence
* Difluence
* Saddle Point

The meteorologists annotated the different configurations that it can present in a period of time and a level determined, this process was done with an annotations tool that allow to select this configurations.

= Model Mathematic =

Given a vector field <math>\vec{V}</math>, a way to classify this configurations is through the use of phase portrait, this method is used in the dynamic system to understand the behavior of functions of 2 or more variables. In computer vision is used in the detection corner, mammography and others.

This method allows to construct a equation system in which these can calculate the determinant and the trace.

: <math> A =
\begin{bmatrix}
\frac{\partial U}{\partial x} & \frac{\partial U}{\partial y} \\
\frac{\partial V}{\partial x} & \frac{\partial V}{\partial y} \\
\end{bmatrix}
</math>

The trace and the determinant indicate as is the behavior of the system. To calculate the trace and determinant with their:

<math> Trace(A) = \frac{\partial U}{\partial x} + \frac{\partial V}{\partial y} </math>

<math> det(A) = \left(\frac{\partial U}{\partial x} \frac{\partial V}{\partial y}\right) - \left(\frac{\partial U}{\partial y} \frac{\partial V}{\partial x} \right) </math>

= Implementation =
The implementation of a descriptor that use the phase portrait depends of the components <math>u</math> and <math>v</math> obtained of the simulation that allow to construct the equation system, although needed the gradient of <math>u</math> and <math>v</math> to construct the system. With the system, we can calculate the solution of the system through the equation characteristic <math>det(A-I\lambda) = 0</math> where I is the identify matrix of the size of A, at expand the equation obtains:
<math>\lambda^2-Trace(A)\lambda+det(A) = 0</math> when we solve this equation have the next:

<math> \lambda_1,\lambda_2 = 0.5 (Trace(A) \pm \sqrt{Trace(A)^2 - 4det(A)})</math>

The descriptor is calculated using moments statistics in the trace and the determinant because is necessary to have a only value of these components, we use the mean, standard desviation and the variance, we use these 3 statistics

Descriptor Proposed JFMR

2015-09-20T00:47:56Z

Jmolinar: /* Implementation */

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Jmolinar:

Given a vector field <math>\vec{V}=(u,v)</math>, where <math>u</math> and <math>v</math> represent the components of the winds of each of the annotations.

Descriptor Proposed JFMR

2015-09-19T19:57:32Z

Jmolinar:

Given a vector field <math>\vec{V}=(u,v)</math>, where <math>u</math> and <math>v</math> represent the components of the winds

Descriptor Proposed JFMR

2015-09-19T19:47:54Z

Jmolinar: Created page with "Given a vector field <math>\vec{V}=(u,v)</math>"

Given a vector field <math>\vec{V}=(u,v)</math>

Actividades Realizadas

2015-09-19T19:47:16Z

Jmolinar:

== Reporte de avances ==

=== Douglas Baquero ===
* Bitácora de trabajo
** [[Bitácora Douglas Baquero]]

=== Juan Molina ===
* Bitácora de trabajo
** [[Bitácora Juan Molina]]
* Actividades de Desarrollo
** Herramienta de anotaciones para estructuras atmosféricas: [[Bitácora Juan Molina Herramienta de Anotaciones]]
** Protocolo de anotaciones para estructuras atmosféricas: [[Protocolo_de_anotaciones_ASAR| Protocolo de anotaciones]]
** Proceso de anotaciones: [[Avances_Anotaciones| Anotaciones Realizadas]]
* Tesis de Maestría
** [[Esquema_Tesis_JFMR | Esquema de tesis de maestría]]
** [[Experiments_JFMR| Experimentaciones realizadas]]
** [[DescriptorPropuesto_JFMR| Descriptor Definido]]
** [[Descriptor_Proposed_JFMR| Descriptor propuesto Juan Felipe Molina Rojas]]

=== Germán Sosa ===
# ...

=== Wilson Sierra ===
# ---

=== Marcela Duarte ===
# ...

=== Oscar Parada ===
* Thesis
** [[MSc Thesis OParada]]
** [[3D Surface Reconstruction Review]]
* TO-DO
** [[3D surface reconstruction algorithms - implementation]]
** [[3D Mesh validation, refinement and reduction]]

== Actas de Reuniones ==
# ACOLMET: [[Acta_Reunion | Reunión del día 10 de Junio]]