laveena-sachdeva

Activity-Recognition-System

In this project, we use Myo armbands to capture Accelerometer, Gyroscope, Orientation and EMG data for daily activities. We then extract features from that raw data, apply dimensionality reduction techniques and then train classification models on that data in reduced dimensions to distinguish between eating and non-eating activities.

Multimedia-Similarity-Measures

This project uses different similarity techniques for a given set of objects (Images, Users, Locations) depending on the models used for their representation (textual descriptors - TF, DF, TF-IDF; and visual descriptors - CM, CM3x3, CN, CN3x3, CSD, GLRLM, GLRLM3x3, HOG, LBP, LBP3x3) and finds objects most similar to the given object.

researchmatch

Tableau-Tennis-Viz

Analyzing and Visualizing Australian Open Tennis Dataset, 2009-2014

Databse-Partitioning-Range-RoundRobin

Range and Round-Robin partitioning implementation

Equijoin-Map-Reduce

The required task is to write a map-reduce program that will perform equijoin.

Generic-Parallel-Sort-Join

The code builds a generic parallel sort and parallel join algorithm.

MongoDB-Textual-Spatial-Searching

The required task is to write two functions, which will perform some textual and spatial searching on MongoDB. Details are explained below.

Simplified-Query-Processor

This is a code for a simplified query processor that accesses data from the partitioned ratings table.

ActivityLog-Android

Android version of ActivityLog

laveena-sachdeva/researchmatch

laveena-sachdeva/Activity-Recognition-System

In this project, we use Myo armbands to capture Accelerometer, Gyroscope, Orientation and EMG data for daily activities. We then extract features from that raw data, apply dimensionality reduction techniques and then train classification models on that data in reduced dimensions to distinguish between eating and non-eating activities.

laveena-sachdeva/Multimedia-Similarity-Measures

This project uses different similarity techniques for a given set of objects (Images, Users, Locations) depending on the models used for their representation (textual descriptors - TF, DF, TF-IDF; and visual descriptors - CM, CM3x3, CN, CN3x3, CSD, GLRLM, GLRLM3x3, HOG, LBP, LBP3x3) and finds objects most similar to the given object.

laveena-sachdeva/Tableau-Tennis-Viz

Analyzing and Visualizing Australian Open Tennis Dataset, 2009-2014

laveena-sachdeva/MongoDB-Textual-Spatial-Searching

The required task is to write two functions, which will perform some textual and spatial searching on MongoDB. Details are explained below.

laveena-sachdeva/Simplified-Query-Processor

This is a code for a simplified query processor that accesses data from the partitioned ratings table.

laveena-sachdeva/Databse-Partitioning-Range-RoundRobin

Range and Round-Robin partitioning implementation

laveena-sachdeva/Equijoin-Map-Reduce

The required task is to write a map-reduce program that will perform equijoin.

laveena-sachdeva/Generic-Parallel-Sort-Join

The code builds a generic parallel sort and parallel join algorithm.