Mueller matrix polarimetry using full Poincaré beams

Astronomical Polarimetry: Polarization algebra and graphical methods

Spirally polarized beams for polarimetry measurements of deterministic and homogeneous samples

Polarimetry with azimuthally polarized light

Compensation of non-ideal beam splitter polarization distortion effect in Michelson interferometer

We propose a new method for determining the Mueller matrix of an arbitrary optical element and verify it with three known optical elements. This method makes use of two universal SU(2) polarization gadgets to obtain the projection matrix directly from the experiment. It allows us to determine the Mueller matrix without precalibration of the setup, since the generated polarization states are fully determined by the azimuths of the wave plates. We calculate errors in determining the Mueller matrix and compare with other techniques.

Measuring the Mueller matrix of an arbitrary optical element with a universal SU(2) polarization gadget

In today’s culture, many people suffer from a range of ailments and illnesses. It’s not always simple to recommend a diet right away. The majority of individuals are frantically trying to reduce weight, gain weight, or keep their health in check. Time has also become a potential stumbling block. The study relies on a database that has the exact amounts of a variety of nutrients. As a result of the circumstance, a program that would encourage individuals to eat healthier has been created. Only three sorts of goods are recommended: weight loss, weight gain, and staying healthy. The Diet Recommendation System leverages user inputs such as medical data and the option of vegetarian or non-vegetarian meals from the two categories above to predict food items. We’ll discuss about food classification, parameters, and machine learning in this post. This study also includes a comparative review of the advantages and disadvantages of machine learning methods. Finally, we’ll discuss future research directions for the diet guidance system.

Diet Recommendation System based on Different Machine Learners: A Review

http://www.theglobaljournals.com/ijar/file.php?val=May_2014_1398966424_e9548_133.pdf

Structural Classification of Pax7 Using Homology Modeling: A Functional Approach

We are describing a novel way to find the Mueller matrix of an arbitrary optical element, by taking advantage of projection of resulting polarization states on four known input polarization states by using Simon-Mukunda gadget.

http://ieeexplore.ieee.org/iel7/6524692/6545200/06545212.pdf

Megh Shah

Papers

Measuring the Mueller matrix of an arbitrary optical element with a universal SU(2) polarization gadget

Diet Recommendation System based on Different Machine Learners: A Review

Structural Classification of Pax7 Using Homology Modeling: A Functional Approach

Determination of Mueller matrix of an optical element with Simon-Mukunda gadget

Determination of Mueller matrix of an optical element with Simon-Mukunda gadget