Partial programming is a field of study where users specify an outline or skeleton of a program, but leave various parts undefined. The undefined parts are then completed by an external mechanism to form a complete program. Adaptation-Based Programming (ABP) is a method of partial programming that utilizes techniques from...
This thesis presents a low power DC-DC converter suitable for harvesting energy from high impedance thermoelectric generators (TEGs) for the use in body powered electronics. The chip has been fabricated in a 130nm CMOS technology. To meet the power demands of body powered networks, a novel dual-path architecture capable of...
Phase Locked Loops(PLLs) are an integral part of almost every electronic system. Systems involving low frequency clocks often require PLLs with low bandwidth. The area occupied by the large loop filter capacitor and resistor in a low bandwidth PLL design makes the realization of traditional charge-pump PLL architecture impractical on...
Wireless sensor networks are becoming important in several monitoring and sensing applications. Ultra low power consumption in the sensor nodes is important for extending the battery life of the nodes. In this dissertation, two low power BFSK receiver architectures are proposed and verified with prototype implementations in silicion.
A 2.4...
The proliferation of body worn autometric devices has been enabled by advances in low-power electronics and fueled by the quantified-self movement. These devices range in complexity from pedometers to clinical vital sign measurement. They all share the same drawback, typically the most expensive and heaviest component, the battery. The future...
The work detailed here is the development of simulations and fabrication techniques used for the construction of thin-film acoustic transducers for use in the parametric pumping of spin waves. The Mason Model, a 1-D equivalent circuit simulating the responses of multilayer acoustic transducers, is implemented using ABCD-parameters in MATLAB to...
We develop efficient coordination techniques that support inelastic traffic in large-scale distributed dynamic spectrum access DSA networks. By means of any learning algorithm, the proposed techniques enable DSA users to locate and exploit spectrum opportunities effectively, thereby increasing their achieved throughput (or "rewards" to be more general). Basically, learning algorithms...
Object categorization is one of the fundamental topics in computer vision research. Most current work in object categorization aims to discriminate among generic object classes with gross differences. However, many applications require much finer distinctions. This thesis focuses on the design, evaluation and analysis of learning algorithms for fine- grained...
Semi-supervised clustering aims to improve clustering performance by considering user supervision in the form of pairwise constraints. In this paper, we study the active learning problem of selecting pairwise must-link and cannot-link constraints for semisupervised clustering. We consider active learning in an iterative manner where in each iteration queries are...
End-user programmers face many barriers in programming. Research has seen many programming environments that attempted to lower or remove the barriers but despite these efforts, empirical studies continue to report barriers users face. To investigate this issue, we took a theory-informed approach. Using theories from design, creativity, and problem solving...