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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
Welcome to my page!
About me
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Posts
Blog Post number 4
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 3
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 2
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 1
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
portfolio
Portfolio item number 1
Short description of portfolio item number 1
Portfolio item number 2
Short description of portfolio item number 2
publications
Paper Title Number 1
Published in Journal 1, 2009
This paper is about the number 1. The number 2 is left for future work.
Recommended citation: Your Name, You. (2009). "Paper Title Number 1." Journal 1. 1(1). http://academicpages.github.io/files/paper1.pdf
Paper Title Number 2
Published in Journal 1, 2010
This paper is about the number 2. The number 3 is left for future work.
Recommended citation: Your Name, You. (2010). "Paper Title Number 2." Journal 1. 1(2). http://academicpages.github.io/files/paper2.pdf
Paper Title Number 3
Published in Journal 1, 2015
This paper is about the number 3. The number 4 is left for future work.
Recommended citation: Your Name, You. (2015). "Paper Title Number 3." Journal 1. 1(3). http://academicpages.github.io/files/paper3.pdf
talks
A STUDY ON THE ROBOT SWARM ANIMATION IN A SINGLE OBSTACLE WORKSPACE
Published:
The Project is based on multi-robot based coordination and a study on their behavior as they come across an obstacle or any object in their path while moving towards a particular goal. The robots are programmed and are controlled by the intelligence programmed to them i.e. called the Swarm Intelligence. The simulations are first carried out in MATLAB considering a robot as a point. The points (the robots) are positioned at their respective positions and they have to reach the goal by bypassing an obstacle (a large sphere in this case). The trajectory obtained from the particles is saved for animation using Python-Ogre. The animation of the problem statement is done in Python-Ogre for proper visualization of the robots, their behavior and coordination. The robotic entities have to follow the trajectory obtained from the MATLAB simulation. The particles were intelligently controlled using Swarm Intelligence algorithms and were successfully simulated in MATLAB and animated in Python-Ogre.
MAXIMUM POWER POINT TRACKING BY FRACTIONAL OPEN CIRCUIT VOLTAGE ALGORITHM USING A LOW COST MICROCONTROLLER
Published:
Solar energy extracted from a Photovoltaic cell offers an eco-friendly, free and renewable source of electricity which is still relatively costly and inefficient today which includes the difficulties related to complete harnessing of solar power. The maximum power point tracking (MPPT) of the PV panel for all sunshine conditions is the vital strategy to get the maximum power output thus increasing the efficiency of solar power extraction mechanism. The Fractional Open Circuit (FOC) Voltage Algorithm is implemented on a PV panel for MPPT by using a low cost microcontroller. In this paper the implementation of the FOC voltage method is shown. This method is simple and is used to approximate the linear relationship between the open circuit voltage and the MPP voltage for a PV panel. So, in this method, the current sensor is not required and the PV panel voltage is sensed using a voltage divider circuit. The effectiveness of the algorithm is verified with experimental results.
LOCATION PREDICTION USING COLLABORATED NETWORK IN SMARTPHONES
Published:
The algorithm that can perform prediction is based on a stochastic model on the HMM theory. This model is based on the concept of collaborative filtering where the algorithm predicts the context of the user based on the context observation of the users related to the primary user. This model can also use homomorphic encryption to preserve privacy of the users involved. In order to evaluate this model, we developed and used a context feature collection application to obtain data. Due to issues with one of the devices, only one device’s features were successfully collected. In order to evaluate the collaborative aspect of HCFContext, we synthetically create collaborators from this real dataset. Using this, we then evaluate the algorithm’s predictions against the sample data.
FACE RECOGNITION
Published:
In this project, I Implementated the face recognition algorithm using AlexNet and VGG16 deep networks by training them from the LFW dataset. In the second part of the project, I implemented the face recognition algorithm using PCA, LDA, SVM SRC on YaleB dataset.
THORACIC DISEASE PREDICTION USING CHEST X RAY IMAGES
Published:
In this project, a Convolutional Neural Network (CNN) is developed and trained to classify the thoracic diseases from the chest X-ray images that are available from the NIH database. The images available in the NIH database are labelled by Wang et al and are updated in a csv file. The objective of this project is to use the data and train a CNN from scratch or use a pre-trained CNN like AlexNet or VGG and classify the thoracic diseases from the chest radiographs.
PARALLEL COMPUTING
Published:
The objective of the project was to develop a parallel computing scenario using the server client architecture by implementing the socket programming algorithm.
CROWD IMAGES ANNOTATION AND ANALYSIS USING CASCADED CNNS
Published:
In this project, I collaborated with Prof. Vishal M. Patel and Mr. Vishwanath Sindagi to annotate approximately 4000 crowd images using the Amazon Mechanical Turk. Using the annotated images, we trained the cascaded CNN for Crowd Counting and Density Estimation.
RADICAL PILOT
Published:
In this project, I am researching and analyzing the efficiency of various scheduling algorithms for the Radical proprietary software namely Radical-Pilot. RADICAL-Pilot (RP) is a Pilot Job system written in Python. It allows a user to run large numbers of computational tasks (called ComputeUnits) concurrently on one or more remote ComputePilots that RADICAL-Pilot can start transparently on a multitude of different distributed resources, like HPC clusters and Clouds. Ater the analysis, I will be implementating the scheduling algorithms on Radical-Pilot.
teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
This is a description of a teaching experience. You can use markdown like any other post.
Teaching experience 2
Workshop, University 1, Department, 2015
This is a description of a teaching experience. You can use markdown like any other post.