gssti-omnibus/workshop

workshop

workshop's Issues

SARG: STOCHASTIC MODELLING OF WEATHER DATA

MARKOV CHAIN MODEL

1. ANNUAL RAINFALL

** summarize data into categories (say, low, medium, high) for each station
** generate Transition Probability Matrix (TPM) using Maximum Likelihood Estimator (MLE) for each.

2. MONTHLY RAINFALL

** summarize data into WET & DRY

*** Schwarz criterion to choose the best optimum order
*** Use Chapman-Kolmogorov equation to determine the ergodic distribution matrix of the system.

Weather Sites

1. http://tahmo.org/__african-climate-data/

2. https://climexp.knmi.nl/allstations.cgi?id=someone@somewhere&climate=sealevel_pressure&n=12

3. https://modis.gsfc.nasa.gov/

4. https://www.researchgate.net/post/Where_can_I_freely_download_global_climate_data_sets

Notes

** Testing Kerasregressor
https://nbviewer.jupyter.org/urls/dl.dropbox.com/s/3imkmd9gtrfg7xv/martin_results.ipynb

Journals

https://www.semanticscholar.org/author/T.-Ansah-Narh/3515997

1. Astrophysics and Space Science

http://www.springer.com/astronomy/astrophysics+and+astroparticles/journal/10509
-- http://www.e-publications.org/springer/support/astr.html

2. New Astronomy

https://www.journals.elsevier.com/new-astronomy/

3. Astronomy and Computing

https://www.journals.elsevier.com/astronomy-and-computing/

4. Computational Astrophysics and Cosmology

https://comp-astrophys-cosmol.springeropen.com/about

5. Journal of Astronomical Telescopes, Instruments, and Systems

https://www.spiedigitallibrary.org/journals/journal-of-astronomical-telescopes-instruments-and-systems/author-guidelines
OR
https://www.overleaf.com/15312580qcvwhbxgtxvp#/57976857/

JOURNAL OF ASTRONOMICAL TELESCOPES, INSTRUMENTS, AND SYSTEMS
https://www.spiedigitallibrary.org/journals/Journal-of-Astronomical-Telescopes-Instruments-and-Systems/volume-5/issue-3
https://www.spiedigitallibrary.org/https://www.elsevier.com/journals/new-astronomy/1384-1076/guide-for-authors

International Journal of Data Science and Analytics
https://www.springer.com/journal/41060

Journal of Engineering, Design and Technology
https://www.emeraldgrouppublishing.com/products/journals/journals.htm?id=JEDT

South African Journal of Science
https://www.sajs.co.za/issue/view/584

Birth Prediction

https://machinelearningmastery.com/time-series-prediction-lstm-recurrent-neural-networks-python-keras/
https://www.kaggle.com/karlentsatinyan/lstm-for-us-birth-rate-prediction
https://towardsdatascience.com/pollution-forecasting-using-time-series-and-lstm-with-mxnet-16fe9180ee1

SARG: Primary beam effects of radio antenna: Effects of Kutunse beam on CO Intensity Mapping

• Use true modelled beams to simulate the foreground
• Use distorted beams to simulate the foreground also.
• Produce residual plots
• A mathematical model of CO
• Estimate the power spectrum wrt moments to determine the polarisation leakage

transforming a Healpix all-sky map to a flat one

The following script converts a spherical map into a flat sky::

http://nbviewer.jupyter.org/urls/dl.dropbox.com/s/b00y8jmsbbx498o/spherical_2_flat_sky.ipynb

SARG: Modelling Kutunse Primary Beams from Simulations III

Using Cassbeam::

1. _Produce IXR, FWHM vrs frequences, CO & Cross polarised plots _
2. Reconstruct beams Using Zernike, SVD, SH
3. Introduce phase error

NB: conclude that future work will be done using holography

SARG: Modelling Kutunse Primary Beams from Simulations I

Sim 1: Using OSKAR

1. Geometrical model of Kutunse dish

• Consider the dish as a collection of dipoles;
• Assume the radial distribution of the dipoles to be a Super-Gaussian; (Note: This will mimic an aperture illumination of the dish)
• Introduce errors in the dipole orientations to distort the main reflector
• Introduce phase error to also distort the beam (this will introduce feed displacement)
• remove the supporting structures (i.e. the struts and secondary reflector)
• vary the size of the secondary reflector

2. Produce Complex beams

• Refer to Jones matrix

3. Produce Complete beams

• Refer to Mueller matrix

4. Measure the Intrinsic Polarisation Leakage (IXR)

5. Estimate the FWHM across all frequencies (5 - 6.7 GHz)

6. Reconstruct the simulated beam models

• Apply Zernike Moments Using the strongest Coefficients
• Apply SVD using fewer eigenvalues for reconstruction.

SARG: Modelling Kutunse Primary Beams from Simulations II

sim 2: Using GRASP

1. Geometrical model of the instrument

• compare different spherical cuts

2. Distort the beam by using feed displacement
3. change the size of the reflector to distort the beam
4. _Produce IXR, FWHM vrs frequences, CO & Cross polarised plots _
5. Reconstruct beams Using Zernike, SVD, SH

NB: conclude that future work will be done using holography