We consider the problem of finding unknown patterns that are recurring across multiple sets. For example, finding multiple objects that are present in multiple images or a short DNA code that is repeated across multiple DNA sequences. We first consider a simple problem of finding a single unknown pattern in...
In the thesis, an application of a genetic algorithm (GA) is considered to solve the vehicle routing problem (VRP) which involves heterogeneous vehicles to serve known customer demands from multiple depots achieving the minimum delivery cost, where each customer must be satisfied by one or more visit(s), and each vehicle...
The quality of a digital image pipeline relies greatly on its color reproduction which should at a minimum handle the color constancy, and the final judgment of the excellence of the pipeline is made through subjective observations by humans.
This dissertation addresses a few topics surrounding the color processing of...
Multi-instance data, in which each object (e.g., a document) is a collection of instances
(e.g., word), are widespread in machine learning, signal processing, computer vision,
bioinformatic, music, and social sciences. Existing probabilistic models, e.g., latent
Dirichlet allocation (LDA), probabilistic latent semantic indexing (pLSI), and discrete
component analysis (DCA), have been...
A relatively new model of error control is the limited magnitude error over high radix channels. In this error model, the error magnitude does not exceed a certain limit known beforehand. In this dissertation, we study systematic error control codes for common channels under the assumption that the maximum error...
As more wind farms are connected to the grid, the variable nature of wind energy begins to influence grid stability. Energy storage could help smooth the variable nature of wind energy. Laboratory demonstration and exploration of the interaction between different energy storage devices and wind energy could help improve and...
Iterative algorithms are simple yet efficient in solving large-scale optimization problems in practice. With a surge in the amount of data in past decades, these methods have become increasingly important in many application areas including matrix/tensor recovery, deep learning, data mining, and reinforcement learning. To optimize or improve iterative algorithms,...
Low-Density Parity-check (LDPC) codes have attracted considerable attention due to their capacity approaching performance over AWGN channel and highly parallelizable decoding schemes. They have been considered in a variety of industry standards for the next generation communication systems. In general, LDPC codes achieve outstanding performance with large codeword lengths (e.g.,...
We define an inner product on a vector space of adelic measures over a number field $K$. We find that the norm induced by this inner product governs weak convergence at each place of $K$. The canonical adelic measure associated to a rational map is in this vector space, and...
This dissertation is composed of two self-contained essays, which examine two
different factors that could affect human capital accumulation in a developing country.
Both essays utilize cross-sectional data from the second round (2003/04) of national level
household survey from Nepal.
In the first essay, I estimate the impact of remittances...