published_or_final_version / Pathology / Doctoral / Doctor of Philosophy

No description available.

In recent years, advances in signal processing have led to small, low power, inexpensive Wireless Sensor Network (WSN). The signal processing in WSN is different from the traditional wireless networks in two critical aspects: firstly, the signal processing in WSN is performed in a fully distributed manner, unlike in traditional wireless networks; secondly, due to the limited computation capabilities of sensor networks, it is essential to develop an energy and bandwidth efficient signal processing algorithms. Target localisation and tracking problems in WSNs have received considerable attention recently, driven by the necessity to achieve higher localisation accuracy, lower cost, and the smallest form factor. Received Signal Strength (RSS) based localisation techniques are at the forefront of tracking research applications. Since tracking algorithms have been attracting research and development attention recently, prolific literature and a wide range of proposed approaches regarding the topic have emerged. This thesis is devoted to discussing the existing WSN-based localisation and tracking approaches. This thesis includes five studies. The first study leads to the design and implementation of a triangulation-based localisation approach using RSS technique for indoor tracking applications. The presented work achieves low localisation error in complex environments by predicting the environmental characteristics among beacon nodes. The second study concentrates on investigating a fingerprinting localisation method for indoor tracking applications. The proposed approach offers reasonable localisation accuracy while requiring a short period of offline computation time. The third study focuses on designing and implementing a decentralised tracking approach for tracking multiple mobile targets with low resource requirements. Despite the interest in target tracking and localisation issues, there are few systems deployed using ZigBee network standard, and no tracking system has used the full features of the ZigBee network standard. Tracking through the ZigBee is a challenging task when the density of router and end-device nodes is low, due to the limited communication capabilities of end-device nodes. The fourth study focuses on developing and designing a practical ZigBee-based tracking approach. To save energy, different strategies were adopted. The fifth study outlines designing and implementing an energy-efficient approach for tracking applications. This study consists of two main approaches: a data aggregation approach, proposed and implemented in order to reduce the total number of messages transmitted over the network; and a prediction approach, deployed to increase the lifetime of the WSN. For evaluation purposes, two environmental models were used in this thesis: firstly, real experiments, in which the proposed approaches were implemented on real sensor nodes, to test the validity for the proposed approaches; secondly, simulation experiments, in which NS-2 was used to evaluate the power-consumption issues of the two approaches proposed in this thesis.

The thesis examines two related combinatorial objects, namely fingerprinting codes and separating hash families. Fingerprinting codes are combinatorial objects that have been studied for more than 15 years due to their applications in digital data copyright protection and their combinatorial interest. Four well-known types of fingerprinting codes are studied in this thesis; traceability, identifiable parent property, secure frameproof and frameproof. Each type of code is named after the security properties it guarantees. However, the power of these four types of fingerprinting codes is limited by a certain condition. The first known attempt to go beyond that came out in the concept of two-level traceability codes, introduced by Anthapadmanabhan and Barg (2009). This thesis extends their work to the other three types of fingerprinting codes, so in this thesis four types of two-level fingerprinting codes are defined. In addition, the relationships between the different types of codes are studied. We propose some first explicit non-trivial con- structions for two-level fingerprinting codes and provide some bounds on the size of these codes. Separating hash families were introduced by Stinson, van Trung, and Wei as a tool for creating an explicit construction for frameproof codes in 1998. In this thesis, we state a new definition of separating hash families, and mainly focus on improving previously known bounds for separating hash families in some special cases that related to fingerprinting codes. We improve upper bounds on the size of frameproof and secure frameproof codes under the language of separating hash families.

The rapid increase in mobile malware and deployment of over-privileged applications over the years has been of great concern to the security community. Encroaching on user’s privacy, mobile applications (apps) increasingly exploit various sensitive data on mobile devices. The information gathered by these applications is sufficient to uniquely and accurately profile users and can cause tremendous personal and financial damage. On Android specifically, the security and privacy holes in the operating system and framework code has created a whole new dynamic for malware and privacy exploitation. This research work seeks to develop novel analysis techniques that monitor Android applications for possible unwanted behaviors and then suggest various ways to deal with the privacy leaks associated with them. Current state-of-the-art static malware analysis techniques on Android-focused mainly on detecting known variants without factoring any kind of software obfuscation. The dynamic analysis systems, on the other hand, are heavily dependent on extending the Android OS and/or runtime virtual machine. These methodologies often tied the system to a single Android version and/or kernel making it very difficult to port to a new device. In privacy, accesses to the database system’s objects are not controlled by any security check beyond overly-broad read/write permissions. This flawed model exposes the database contents to abuse by privacy-agnostic apps and malware. This research addresses the problems above in three ways. First, we developed a novel static analysis technique that fingerprints known malware based on three-level similarity matching. It scores similarity as a function of normalized opcode sequences found in sensitive functional modules and application permission requests. Our system has an improved detection ratio over current research tools and top COTS anti-virus products while maintaining a high level of resiliency to both simple and complex obfuscation. Next, we augment the signature-related weaknesses of our static classifier with a hybrid analysis system which incorporates bytecode instrumentation and dynamic runtime monitoring to examine unknown malware samples. Using the concept of Aspect-oriented programming, this technique involves recompiling security checking code into an unknown binary for data flow analysis, resource abuse tracing, and analytics of other suspicious behaviors. Our system logs all the intercepted activities dynamically at runtime without the need for building custom kernels. Finally, we designed a user-level privacy policy enforcement system that gives users more control over their personal data saved in the SQLite database. Using bytecode weaving for query re-writing and enforcing access control, our system forces new policies at the schema, column, and entity levels of databases without rooting or voiding device warranty.

In accordance with the 2010 Dodd-Frank Act, conflict minerals refer to gold, tantalum, tin, and tungsten bearing minerals sourced from the Democratic Republic of Congo (DRC) that have been mined illegally and used to funnel funds to rebel forces. In response to an increasing demand for these metals used in cellphones, computers, and other popular technologies, Dodd-Frank mandates that industrial consumers demonstrate due diligence and assure that the materials they use have been extracted legally. Because current chain-of-custody methods have not been effective in sourcing ores, a study was undertaken whereby the range of mineralogical characteristics of 15 samples along the wolframite solid solution series were determined in order to ascertain if differences in these characteristics would permit fingerprinting of the source deposit of wolframite, of which the DRC is the world's fifth largest producer. For these 15 samples, single-crystal X-ray structure and powder X-ray diffraction studies have been conducted; major, minor and trace element chemistry has been determined using ICP-MS and ICP-OES; and Raman spectroscopy has been carried out. Finally, statistical methods were used to determine relationships between samples, and the results of that mathematical work show that there is no firm method at the present time of determining the provenance of a sample based on the information of the crystal structure, diffraction patterns, vibrational frequencies/scattering, or major and trace elemental chemistry. This study elucidates the range of mineralogical properties along the hübnerite-ferberite solid solution series while working towards to development of an analytical technique that is affordable, practical, accessible and effective for industrial consumers seeking product certification and compliance with the 2010 Dodd-Frank Act.

M.Sc. (Botany) / Global efforts to protect the world’s forests from unsustainable and inequitable exploitation have been undermined in recent years by rampant illegal logging in many timber-producing countries. A prerequisite for efficient control and seizure of illegally harvested forest product is a rapid, accurate and tamper proof method of species identification. DNA barcoding is one such a tool, relatively simple to apply. It is acknowledged to bring about accuracy and efficiency in species identification. In this study a DNA barcode reference library for traded and protected tree species of southern Africa was developed comprising of 81 species and 48 genera. Four primary analyses were conducted to assess the suitability of the core barcodes as a species identification tool using the R package Spider 1.2-0. Lastly, to evaluate this identification tool, query specimens independently sampled at a Mozambican logging concession were identified using DNA barcoding techniques. The nearest neighbour (k-NN) and best close match (BCM) distance based parameter yielded 90% and 85% identification success rate using the core plant barcodes respectively. DNA barcoding identification of query specimens maintained a constant 83% accuracy over the single marker dataset and the combined dataset. This database can serve as a backbone to a control mechanism based on DNA techniques for species identification and also advance the ability of relevant authorities to rapidly identify species of timber at entry and exit points between countries with simple, fast, and accurate DNA techniques.

A technique is proposed to improve the accuracy of indoor positioning systems based on WIFI radio-frequency signals by using dynamic access points and fingerprints (DAFs). Moreover, an indoor position system that relies solely in DAFs is proposed. The walking pattern of indoor users is classified as dynamic or static for indoor positioning purposes. I demonstrate that the performance of a conventional indoor positioning system that uses static fingerprints can be enhanced by considering dynamic fingerprints and access points. The accuracy of the system is evaluated using four positioning algorithms and two random access point selection strategies. The system facilitates the location of people where there is no wireless local area network (WLAN) infrastructure deployed or where the WLAN infrastructure has been drastically affected, for example by natural disasters. The system can be used for search and rescue operations and for expanding the coverage of an indoor positioning system.

Heparin is a complex mixture of sulfated polysaccharides derived from animals and one of the oldest drugs in use. While an efficacious anticoagulant, heparin is beset by side effects and pharmacokinetic difficulties. Low molecular weight heparins (LMWH) are made by depolymerizing unfractionated heparin (UFH) and present improvements in these areas. However, they still retain a phenomenally high level of complexity due to their polydispersity and the introduction of non-native structural features. This makes the structural characterization LMWHs a daunting task. This work details the development of a novel capillary electrophoretic (CE) method for fingerprinting LMWHs. Since their complexity normally results in a nearly featureless electropherogram, polyalkylamines were used as a resolving agents to yield highly resolved and reproducible fingerprints characteristic of the LMWH being investigated. Linear polyamines of resolved LMWH in a manner dependent on chain length and charge density, while cyclic polyamines were incapable of resolution. Longer length glycosaminoglycans such as UFH and chondroitin sulfate were not successfully fingerprinted as they lacked run to run consistency. Further investigation into the mode of polyamine binding showed that they bound to LMWH via a two site binding model, indicating the presence of specific sites on LMWH that tightly bind polyamines. Upon the saturation of these sites, the polyamines continue to interact via general electrostatic binding. Pentaethylenehexamine was also able to separate the known contaminant oversulfated chondroitin sulfate from UFH. In July of 2010, the US food and drug administration approved a generic for the widely used LMWH enoxaparin, a questionable move due to the difficulties of proving the equivalence of such a complex mixture. A comparison of the brand and generic batches of enoxaparin using the fingerprinting method revealed striking similarities, bolstering the generic’s claim of equivalency and providing a protocol for the evaluation of other biosimilar LMWHs. This is the first work utilizing CE in developing high resolution fingerprints of LMWH. It presents a noteworthy method for quality assessment of LMWH and provides the basis for designing other small molecule probes for the analysis of complex glycosaminoglycans.

Neofabraea is a genus of an important plant pathogenic fungi having worldwide appearance. Four Neofabraea species are responsible for bull's eye rot of pome fruits. The aim of this thesis was to investigate which of these species occur in the Czech Republic. 81 isolates were collected during a two- year period and they were identified using PCR fingerprinting (primers ERIC 1R and M13-core) and DNA sequencing (ITS, mtSSU and tub2). The results showed that species N. alba, N. perennans and Cryptosporiopsis kienholzii occur in the Czech Republic. According to available information, this is the second record of C. kienholzii in Europe. One isolate (KP4) failed to be identified as any of the species. KP4 is very close to C. kienholzii, but it can be distinguished both biologically and genetically. Furthermore, the aggressiveness of individual species was compared.N. perennans and strain KP4 proved to be most aggressive, the least aggressive is C. kienholzii. Two N. alba strains (KP36 and KP37) isolated from healthy apple fruit and leaf are pathogenic for apple fruits. Keywords: aggressiveness, Cryptosporiopsis kienholzii, Dermateaceae, Helotiales, apple tree, Malus, PCR fingerprinting, postharvest diseases Powered by TCPDF (www.tcpdf.org)