The major challenges facing resource constraint wireless devices are error resilience, security and speed. Three joint schemes are presented in this research which could be broadly divided into error correction based and cipher based. The error correction based ciphers take advantage of the properties of LDPC codes and Nordstrom Robinson code. A cipher-based cryptosystem is also presented in this research. The complexity of this scheme is reduced compared to conventional schemes. The securities of the ciphers are analyzed against known-plaintext and chosen-plaintext attacks and are found to be secure. Randomization test was also conducted on these schemes and the results are presented. For the proof of concept, the schemes were implemented in software and hardware and these shows a reduction in hardware usage compared to conventional schemes. As a result, joint schemes for error correction and security provide security to the physical layer of wireless communication systems, a layer in the protocol stack where currently little or no security is implemented. In this physical layer security approach, the properties of powerful error correcting codes are exploited to deliver reliability to the intended parties, high security against eavesdroppers and efficiency in communication system. The notion of a highly secure and reliable …

While pragmatics, through its integration of situational awareness and real world relevant knowledge, offers a high level of analysis that is suitable for real interpretation of natural dialogue, semantics, on the other end, represents a lower yet more tractable and affordable linguistic level of analysis using current technologies. Generally, the understanding of semantic meaning in literature has revolved around the famous quote ``You shall know a word by the company it keeps''. In this thesis we investigate the role of context constituents in decoding the semantic meaning of the engulfing context; specifically we probe the role of salient concepts, defined as content-bearing expressions which afford encyclopedic definitions, as a suitable source of semantic clues to an unambiguous interpretation of context. Furthermore, we integrate this world knowledge in building a new and robust unsupervised semantic model and apply it to entail semantic relatedness between textual pairs, whether they are words, sentences or paragraphs. Moreover, we explore the abstraction of semantics across languages and utilize our findings into building a novel multi-lingual semantic relatedness model exploiting information acquired from various languages. We demonstrate the effectiveness and the superiority of our mono-lingual and multi-lingual models through a comprehensive set of evaluations on specialized …

Conventional pattern recognition systems have two components: feature analysis and pattern classification. For any object in an image, features could be considered as the major characteristic of the object either for object recognition or object tracking purpose. Features extracted from a training image, can be used to identify the object when attempting to locate the object in a test image containing many other objects. To perform reliable scene analysis, it is important that the features extracted from the training image are detectable even under changes in image scale, noise and illumination. Scale invariant feature has wide applications such as image classification, object recognition and object tracking in the image processing area. In this thesis, color feature and SIFT (scale invariant feature transform) are considered to be scale invariant feature. The classification, recognition and tracking result were evaluated with novel evaluation criterion and compared with some existing methods. I also studied different types of scale invariant feature for the purpose of solving scene analysis problems. I propose probabilistic models as the foundation of analysis scene scenario of images. In order to differential the content of image, I develop novel algorithms for the adaptive combination for multiple features extracted from images. I …

Indoor localization consists of locating oneself inside new buildings. GPS does not work indoors due to multipath reflection and signal blockage. WiFi based systems assume ubiquitous availability and infrastructure based systems require expensive installations, hence making indoor localization an open problem. This dissertation consists of solving the problem of indoor localization by thoroughly exploiting the indoor ambient magnetic fields comprising mainly of disturbances termed as anomalies in the Earth’s magnetic field caused by pillars, doors and elevators in hallways which are ferromagnetic in nature. By observing uniqueness in magnetic signatures collected from different campus buildings, the work presents the identification of landmarks and guideposts from these signatures and further develops magnetic maps of buildings - all of which can be used to locate and navigate people indoors. To understand the reason behind these anomalies, first a comparison between the measured and model generated Earth’s magnetic field is made, verifying the presence of a constant field without any disturbances. Then by modeling the magnetic field behavior of different pillars such as steel reinforced concrete, solid steel, and other structures like doors and elevators, the interaction of the Earth’s field with the ferromagnetic fields is described thereby explaining the causes of the …

The recent growth in sensor technology allows easier information gathering in real-time as sensors have grown smaller, more accurate, and less expensive. The resulting data is often in a geo-stream format continuously changing input with a spatial extent. Researchers developing geo-streaming management systems (GSMS) require a benchmark system for evaluation, which is currently lacking. This thesis presents GSMark, a benchmark for evaluating GSMSs. GSMark provides a data generator that creates a combination of synthetic and real geo-streaming data, a workload simulator to present the data to the GSMS as a data stream, and a set of benchmark queries that evaluate typical GSMS functionality and query performance. In particular, GSMark generates both moving points and evolving spatial regions, two fundamental data types for a broad range of geo-stream applications, and the geo-streaming queries on this data.

Abstract Due to the vast amount of information we are faced with, summarization has become a critical necessity of everyday human life. Given that a large fraction of the electronic documents available online and elsewhere consist of short texts such as Web pages, news articles, scientific reports, and others, the focus of natural language processing techniques to date has been on the automation of methods targeting short documents. We are witnessing however a change: an increasingly larger number of books become available in electronic format. This means that the need for language processing techniques able to handle very large documents such as books is becoming increasingly important. This thesis addresses the problem of summarization of novels, which are long and complex literary narratives. While there is a significant body of research that has been carried out on the task of automatic text summarization, most of this work has been concerned with the summarization of short documents, with a particular focus on news stories. However, novels are different in both length and genre, and consequently different summarization techniques are required. This thesis attempts to close this gap by analyzing a new domain for summarization, and by building unsupervised and supervised systems …

Video surveillance systems have been commonly used in transportation systems to support traffic monitoring, speed estimation, and incident detection. However, there are several challenges in developing and deploying such systems, including high development and maintenance costs, bandwidth bottleneck for long range link, and lack of advanced analytics. In this thesis, I leverage current wireless, video camera, and analytics technologies, and present a wireless traffic monitoring system. I first present an overview of the system. Then I describe the site investigation and several test links with different hardware/software configurations to demonstrate the effectiveness of the system. The system development process was documented to provide guidelines for future development. Furthermore, I propose a novel speed-estimation analytics algorithm that takes into consideration roads with slope angles. I prove the correctness of the algorithm theoretically, and validate the effectiveness of the algorithm experimentally. The experimental results on both synthetic and real dataset show that the algorithm is more accurate than the baseline algorithm 80% of the time. On average the accuracy improvement of speed estimation is over 3.7% even for very small slope angles.

Directly mapped caches are an attractive option for processor designers as they combine fast lookup times with reduced complexity and area. However, directly-mapped caches are prone to higher miss-rates as there are no candidates for replacement on a cache miss, hence data residing in a cache set would have to be evicted to the next level cache. Another issue that inhibits cache performance is the non-uniformity of accesses exhibited by most applications: some sets are under-utilized while others receive the majority of accesses. This implies that increasing the size of caches may not lead to proportionally improved cache hit rates. Several solutions that address cache non-uniformity have been proposed in the literature. These techniques have been proposed over the past decade and each proposal independently claims the benefit of reduced conflict misses. However, because the published results use different benchmarks and different experimental setups, (there is no established frame of reference for comparing these results) it is not easy to compare them. In this work we report a side-by-side comparison of these techniques. Finally, we propose and Adaptive-Partitioned cache for multi-threaded applications. This design limits inter-thread thrashing while dynamically reducing traffic to heavily accessed sets.

The advent of sensory and communication technologies enables the generation and consumption of large volumes of streaming data. Many of these data streams are geo-referenced. Existing spatio-temporal databases and data stream management systems are not capable of handling real time queries on spatial extents. In this thesis, we investigated several fundamental research issues toward building a data-type-based real time geospatial data stream management system. The thesis makes contributions in the following areas: geo-stream data models, aggregation, window-based nearest neighbor operators, and query optimization strategies. The proposed geo-stream data model is based on second-order logic and multi-typed algebra. Both abstract and discrete data models are proposed and exemplified. I further propose two useful geo-stream operators, namely Region By and WNN, which abstract common aggregation and nearest neighbor queries as generalized data model constructs. Finally, I propose three query optimization algorithms based on spatial, temporal, and spatio-temporal constraints of geo-streams. I show the effectiveness of the data model through many query examples. The effectiveness and the efficiency of the algorithms are validated through extensive experiments on both synthetic and real data sets. This work established the fundamental building blocks toward a full-fledged geo-stream database management system and has potential impact in many …

The future wireless communication systems are required to meet the growing demands of reliability, bandwidth capacity, and mobility. However, as corruptions such as fading effects, thermal noise, are present in the channel, the occurrence of errors is unavoidable. Motivated by this, the work in this dissertation attempts to improve the system performance by way of exploiting schemes which statistically reduce the error rate, and in turn boost the system throughput. The network can be studied using a simplified model, the two-way relay channel, where two parties exchange messages via the assistance of a relay in between. In such scenarios, this dissertation performs theoretical analysis of the system, and derives closed-form and upper bound expressions of the error probability. These theoretical measurements are potentially helpful references for the practical system design. Additionally, several novel transmission methods including block relaying, permutation modulations for the physical-layer network coding, are proposed and discussed. Numerical simulation results are presented to support the validity of the conclusions.

Location-based services (LBS) are available on a variety of mobile platforms like cell phones, PDA's, etc. and an increasing number of users subscribe to and use these services. Two of the popular models of information flow in LBS are the client-server model and the peer-to-peer model, in both of which, existing approaches do not always provide privacy for all parties concerned. In this work, I study the feasibility of applying cryptographic protocols to design privacy-preserving solutions for LBS from an experimental and theoretical standpoint. In the client-server model, I construct a two-phase framework for processing nearest neighbor queries using combinations of cryptographic protocols such as oblivious transfer and private information retrieval. In the peer-to-peer model, I present privacy preserving solutions for processing group nearest neighbor queries in the semi-honest and dishonest adversarial models. I apply concepts from secure multi-party computation to realize our constructions and also leverage the capabilities of trusted computing technology, specifically TPM chips. My solution for the dishonest adversarial model is also of independent cryptographic interest. I prove my constructions secure under standard cryptographic assumptions and design experiments for testing the feasibility or practicability of our constructions and benchmark key operations. My experiments show that the proposed …