Pandya, Abhijit S.

A novel personnel authentication and verification system for devices
communicating through Bluetooth protocol has been proposed in this thesis.
Unlike existing verification systems which provide password or a PIN as a key,
the system uses biometrics features as a key. In the implementation of the scheme,
ridges and bifurcation based parameters are derived to generate a 128 bit
Bluetooth pairing PIN. In this thesis a unique translational and rotational invariant
feature set has been developed. These extracted feature data, unlike traditional
systems which include the extracted data into payload, is used for device
connection by generating the 128 bit PIN. The system performance is analyzed
using the pairing PIN for inter-sample and intra-sample recognition. To validate
the stability of the system the performance is analyzed with external samples
which are not a part of the internal database.

This research aims at proposing the use of Electrical Impedance Tomography (EIT), a
non-invasive technique that makes it possible to measure two or three dimensional
impedance of living local tissue in a human body which is applied for medical
diagnosis of diseases. In order to achieve this, electrodes are attached to the part of
human body and an image of the conductivity or permittivity of living tissue is
deduced from surface electrodes. In this thesis we have worked towards alleviating
drawbacks of EIT such as estimating parameters by incorporating it in an electrode
structure and determining a solution to spatial distribution of bio-impedance to a close
proximity. We address the issue of initial parameter estimation and spatial resolution
accuracy of an electrode structure by using an arrangement called "divided electrode"
for measurement of bio-impedance in a cross section of a local tissue. Its capability is
examined by computer simulations, where a distributed equivalent circuit is utilized
as a model for the cross section tissue. Further, a novel hybrid model is derived which
is a combination of artificial intelligence based gradient free optimization technique
and numerical integration in order to estimate parameters. This arne! iorates the
achievement of spatial resolution of equivalent circuit model to the closest accuracy.

The focus of this research is on images extracted from surveillance videos that
have a low resolution and are taken under low illumination. In recent years, great
advances have been made in face recognition and many studies mention results of 80%
and 90% of recognition efficiency, however, most of these studies reported results using
face images under controlled conditions. Current surveillance systems are equipped with
low resolution cameras and are located in places with changing illumination, as opposed
to a controlled environment. To be used in face recognition, images extracted from
videos need to be normalized, enlarged and preprocessed. There is a multitude of
processing algorithms for image enhancement, and each algorithm faces its advantages
and disadvantages. This thesis presents a novel method for image enlargement of human
faces applied to low quality video recordings. Results and comparison to traditional
methods are also presented.

With the increasing number of cellular phone service subscribers, the
telecommunications service providers have placed immense emphasis on improving
audio quality and ensure fewer dropped calls. Handoff behavior of all handsets is an
important factor in quality of service of a mobile phone service. This thesis focuses
on the analysis of large volumes of diagnostic data collected from mobile phones in
the real world and the identification of aberrant behavior of a mobile handset under
test by means of drive test data visualization. Our target was to identify poor mobility
decisions that are made by the handsets in calls. Premature, delayed or exceedingly
sensitive decisions are considered poor mobility decisions. The goal was to compare a
set of behaviors from a baseline unit (one accepted to generally operate well). We
were able to identify a particular call that was exhibiting a different path (talking to a
different cell than expected or taking longer to move to a new cell). We designed a
chi-square statistical test to evaluate the performance of specific mobile handset
models. We also developed a mobility tool that evaluated the handset's performance
by means of mapping the handoffs on the Google Maps. The mapping of the handoffs
by means of the Google Maps were very powerful in identifying the above mentioned
mobility patterns.

The ever increasing demand for capacity in wireless cellular networks is
resolved by decreasing the size of the cells. The smaller cells created inside large
cells are called microcells and they cover smaller and dense areas. As a result of this,
the mobile device ends up changing the base stations or performing handover at a
much higher rate. To maintain the reliability and quality of the call, it is obligatory to
ascertain that the handover is performed at a proper location. If the handover is
delayed or the mobile handset drags its base station, it is more probable that either the
call will drop or the quality of the call will be compromised. The last thing a mobile
handset user would want is to experience any of these two consequences. In this
thesis we study the methods to analyze the performance ofhandover by the mobile
handsets in the drive setup under test. This thesis presents a model for analyzing the
performance ofhandoffbased on the measurements ofthe received signal strength
indicator and the color code recorded by the mobile handset in the drive test field
path. The model from the simulations is seen to yield results that agree with other
research about the performance of mobile handsets.

One of the biggest factors in the quest to better wireless communication is cellular
call handoff, which in tum, is a function of geographic location. In this thesis, our
fundamental goal was to demonstrate the value addition brought forth by spatial data
visualization techniques for the analysis of geo-referenced data from two different
location tracking technologies: GPS and cellular systems. Through our efforts, we
unearthed some valuable and surprising insights from the data being analyzed that led to
interesting observations about the data itself as opposed to the entity, or entities, that the
data is supposed to describe. In doing so, we underscored the value addition brought forth
by spatial data visualization techniques even in the incipient stages of analysis of georeferenced
data from cellular networks. We also demonstrated the value of visualization
techniques as a verification tool to verify the results of analysis done through other
methods, such as statistical analysis.

Even though, the current cellular network provides the user with a wide array of
services, for a typical user voice communication is still the primary usage. It has become
increasingly important for a cellular network provider to provide the customers with the
clearest possible end-to-end speech during a call. However, this perceptually motivated
QoS is hard to measure. While the main goal of this research has been on the modeling of
the perceptual audio quality, this thesis focuses on the discovery of procedures for
collecting audio and diagnostic data, the evaluation of the captured audio, and the
mapping and visualization of the diagnostic and audio related data. The correct
application of these modified procedures should increase the productivity of the drive test
team as well as provides a platform for the accurate assessment of the data collected.

In this thesis, a practical solution for drive test data evaluation and a real
application are studied. We propose a system framework to project high dimensional
Drive Test Data (DTD) to well-organized web pages, such that users can visually review
phone performance with respect to different factors.
The proposed application, iVESTA (interactive Visualization and Evaluation
System for driven Test dAta), employs a web-based architecture which enables users to
upload DTD and immediately visualize the test results and observe phone and network
performances with respect to different factors such as dropped call rate, signal quality,
vehicle speed, handover and network delays. iVESTA provides practical solutions for
mobile phone manufacturers and network service providers to perform comprehensive
study on their products from the real-world DTD.

Tinnitus is a conscious perception of phantom sounds in the absence of external
acoustic stimuli, and masking is one of the popular ways to treat it. Due to the variation
in the perceived tinnitus sound from patient to patient, the usefulness of masking therapy
cannot be generalized. Thus, it is important to first determine the feasibility of masking
therapy on a particular patient, by quantifying the tinnitus sound, and then generate an
appropriate masking signal. This paper aims to achieve this kind of individual profiling
by developing interactive software - Tinnitus Analyzer, based on clinical approach. The
developed software has been proposed to be used in place oftraditional clinical methods
and this software (as a part of the future work) will be implemented in the practical
scenario involving real tinnitus patients.

The emerging Scalable Video Coding (SVC) extends the H.264/AVC video coding standard with new tools designed to efficiently support temporal, spatial and SNR scalability. In real-time multimedia systems, the coding performance of video encoders and decoders is limited by computational complexity. This thesis presents techniques to manage computational complexity of H.264/AVC and SVC video encoders. These techniques aim to provide significant complexity saving as well as a framework for efficient use of SVC.