Adaptive Image Diffusion in Wavelet Domain

Removing noise without sacrificing important structures Nonlinear strategies: Wavelet shrinkage and Nonlinear diffusion filtering based on features Clustering based wavelet diffusio

A Comparative Study of Cognitive Systems for Learning

Learning is the modification of a behavioral tendency by experience. Memory and reasoning are the most important aspects for learning in humans; information is temporarily stored in the short-term memory and processed, compared with existing memories and stored in long-term memory, and can be re-used when needed. One way to describe an organized pattern of thought or behavior and the categories of information along with their relationships is by using schemas. A cognitive script is one form of a schema that evolves over multiple exposures to the same set of stimuli and/or repeated enactment of a particular behavior. This research aims to provide a comparative study between three cognitive systems/tools designed to allow learning, by using cognitive scripts representation. Since retrieving and re-using past experiences is the core of any learning process, the focus of this thesis is to examine the current existing cognitive systems and tools to evaluate their ability to retrieve past experiences. SOAR, myCBR and Pharaoh are three systems considered for this thesis. Linear and multi-branched cognitive scripts were considered in order to measure the capacity of those systems to allow learning using cognitive scripts representation. The results of this work show that SOAR, myCBR and Pharaoh took almost the same time to retrieve a set of similar cognitive scripts to a query script. However, SOAR was able to retrieve one similar script only, while myCBR and Pharaoh were able to retrieve multiple scripts. Pharaoh tops the other two system in its ability to handle multibranched scripts of different sizes and the way it considers context

Histone Modifications in Trypanosoma Brucei

Trypanosoma brucei maintains an infection in its mammalian host by switching its surface antigen, thus evading host antibodies, in a process known as antigenic variation. Variant surface glycoproteins (VSG), the surface antigen, are expressed from genes located at as many as 20 Expression Sites (ES), which are present in subtelomeric regions of several chromosomes. How trypanosomes maintain monoallelic expression of VSG is a major question in trypanosome biology. Several theories have been proposed, including the presence of an Expression Site Body (a dedicated ‘transcription factory’), regulation of RNA elongation, and some kind of transcriptionally restrictive chromatin structure at inactive ES. In other organisms, the role of histone posttranslational modifications (PTMs) in influencing transcriptional states has been well-documented. To begin to understand the role of chromatin structure in the regulation of gene expression in trypanosomes, I developed a protocol for the purification of histones from mammalian-infective trypanosomes and identified PTMs using Edman degradation and mass spectrometry. I found that the N-termini of H4 and, possibly, H3 have a number of posttranslational modifications (PTMs), while H2A and H2B, in contrast, have relatively few. I also found a series of acetylated lysines at the C-terminus of H2A. Interestingly, I observed that alanine 1 of H2A, H2B, and H4 is monomethylated, a novel modification found in trypanosomatids. Next, I attempted to identify the targets of the putative histone deacetylase TbSIR2RP-1, a SIR2-related protein. Yeast SIR2 plays a key role in establishing heterochromatin at subtelomeric loci. TbSIR2RP-1 was chosen as a possible mediator of ES silencing, although this was later shown not to be the case. I showed that, unlike its yeast counterpart, TbSIR2RP-1 may not be an H4 deacetylase. Finally, I began to characterize H3 K4 methylation, which, in other organisms, is traditionally associated with transcriptionally active chromatin. I showed that nucleosomes containing the histone variant H2BV are enriched for H3 K4 methylation. I initially hypothesized that this is due to ubiquitination at a conserved lysine at the H2BV C-terminus, but find that this is not the case. Instead, I propose that replacement of major histones H2A/H2B with H2AZ/H2BV acts as a trigger to stimulate H3 K4 methylation, which represents an alternative pathway leading to H3 methylation, compared to what is observed in yeast

COLOR MULTIPLEXED SINGLE PATTERN SLI

Structured light pattern projection techniques are well known methods of accurately capturing 3-Dimensional information of the target surface. Traditional structured light methods require several different patterns to recover the depth, without ambiguity or albedo sensitivity, and are corrupted by object movement during the projection/capture process. This thesis work presents and discusses a color multiplexed structured light technique for recovering object shape from a single image thus being insensitive to object motion. This method uses single pattern whose RGB channels are each encoded with a unique subpattern. The pattern is projected on to the target and the reflected image is captured using high resolution color digital camera. The image is then separated into individual color channels and analyzed for 3-D depth reconstruction through use of phase decoding and unwrapping algorithms thereby establishing the viability of the color multiplexed single pattern technique. Compared to traditional methods (like PMP, Laser Scan etc) only one image/one-shot measurement is required to obtain the 3-D depth information of the object, requires less expensive hardware and normalizes albedo sensitivity and surface color reflectance variations. A cosine manifold and a flat surface are measured with sufficient accuracy demonstrating the feasibility of a real-time system

Data science for health-care: Patient condition recognition

>Magister Scientiae - MScThe emergence of the Internet of Things (IoT) and Artificial Intelligence (AI) have elicited increased interest in many areas of our daily lives. These include health, agriculture, aviation, manufacturing, cities management and many others. In the health sector, portable vital sign monitoring devices are being developed using the IoT technology to collect patients’ vital signs in real-time. The vital sign data acquired by wearable devices is quantitative and machine learning techniques can be applied to find hidden patterns in the dataset and help the medical practitioner with decision making. There are about 30000 diseases known to man and no human being can possibly remember all of them, their relations to other diseases, their symptoms and whether the symptoms exhibited by the patients are early warnings of a fatal disease. In light of this, Medical Decision Support Systems (MDSS) can provide assistance in making these crucial assessments. In most decision support systems factors a ect each other; they can be contradictory, competitive, and complementary. All these factors contribute to the overall decision and have di erent degrees of influence [85]. However, while there is more need for automated processes to improve the health-care sector, most of MDSS and the associated devices are still under clinical trials. This thesis revisits cyber physical health systems (CPHS) with the objective of designing and implementing a data analytics platform that provides patient condition monitoring services in terms of patient prioritisation and disease identification [1]. Di erent machine learning algorithms are investigated by the platform as potential candidate for achieving patient prioritisation. These include multiple linear regression, multiple logistic regression, classification and regression decision trees, single hidden layer neural networks and deep neural networks. Graph theory concepts are used to design and implement disease identification. The data analytics platform analyses data from biomedical sensors and other descriptive data provided by the patients (this can be recent data or historical data) stored in a cloud which can be private local health Information organisation (LHIO) or belonging to a regional health information organisation (RHIO). Users of the data analytics platform consisting of medical practitioners and patients are assumed to interact with the platform through cities’ pharmacies , rural E-Health kiosks end user applications

Race, Poverty, and Basic Needs

Black Americans experience poverty at disproportionately high rates that are concerning both because of the perils of poverty as well as the belief that one’s race should not affect one’s opportunities in life. This paper extends the Capability Approach and argues that basic needs play an important economic role in providing people with a minimum level of opportunity that allows them to avoid poverty. Using MSA-level data on basic needs access and poverty rates, this paper finds that increasing rates of homeownership, high school graduation, and car access as well as decreasing rates of disability are all significantly associated with lower poverty rates for Black Americans. However, the empirical results also show that higher rates of high school graduation and car access for White populations are associated with higher rates of Black poverty, likely due to spillover effects in the labor market that crowd out Black workers

VLSI design of stability routing protocol for sensors in wireless mobile ad-hoc networks

This thesis gives a detailed description of the Application specific integrated circuit (ASIC) design of Stability routing protocol for sensors in mobile ad-hoc networks. The Stability routing protocol is based on the signal strength and position components during data transmission while considering sensors in an ad-hoc network. A general ad-hoc network has unpredictable and variable mobility patterns therefore the signal strength criteria is adopted for routing. Signal strength criteria has been proved to be efficient for communication between the mobile nodes without any data loss. In this thesis an architecture for a processor implementing stability routing protocol for effective communication has been designed. The processor detects the alert signal from the sensor network and sends an emergency signal to all the other nodes in the network. Apart form sending the emergency signal the processor also sends the position and velocity components of its own node to all the other nodes in the network. The other functionality of the processor is whenever the processor receives data from another node it updates the information and sends that information to the destination node. A VHDL model for this architecture was developed, a selected set of specific conditions are evaluated through simulation. VHDL simulation validates the functionality of the architecture. This model was synthesized and the place and route was done using cadence tools

Location-Aware Traffic Management on Mobile Phones

The growing number of mobile phone users is a primary cause of congestion in cellular networks. Therefore, cellular network providers have turned to expensive and differentiated data plans. Unfortunately, as the number of smartphone users keeps increasing, changing data plans only provides a temporary solution. A more permanent solution is offloading 3G traffic to networks in orthogonal frequency bands. One such plausible network is open Wi-Fi, which is free by definition. As Wi-Fi networks become ubiquitous, there are several areas where there is simultaneous Wi-Fi and 3G coverage. In this thesis, we study the feasibility of offloading 3G traffic to Wi-Fi networks. First, we design a custom tool for the Android phone, which helps us collect data on CPU usage, GPS coordinates, applications running on the platform, and traffic generated by the smartphone. With the help of initial data collected from the tool, we quantify the amount and characteristics of traffic that users generate from smartphones. Next, using the data we show that at several locations offloading a considerable amount of data is possible from 3G to Wi-Fi. Our study can lead to the design of multiradio systems that prevent traffic overload on 3G networks