Healthcare in the United States is a system that, organizationally speaking, is fragmented. Each hospital facility is independently operated and is responsible for the hiring of its own employees. However, corrupt individuals can take advantage of this fragmentation and move from hospital to hospital, gaining employment while hiding previous employment history. Traditionally, hospitals have been reluctant to share information on their previous employees, even with other hospitals, for fear of issues surrounding defamation, negligent hiring, and violation of the employee's privacy. However, growth in healthcare services is expected to rise exponentially in the near future, increasing the demand for employees. The need, therefore, to exchange pertinent information regarding employees will become necessary as hospitals seek qualified employees to fill positions throughout their organizations. One way to promote this information exchange is to develop trusted information sharing networks among hospital units. This study examined the problems surrounding organizational information sharing as well as the current level of employee information sharing being conducted by hospitals nationwide. Utilizing a survey of hospital administrators, this study drew upon the theoretical foundations of the Diffusion of Innovation Theory, the Knowledge Management Theory, the Social Exchange Theory and the earlier organizational information sharing frameworks established by Dawes (1996) and Landsbergen and Wolken (1998; 2001) in order to examine the variables that contribute to propensity of hospital administrators to engage in the sharing of employee information with other organizations.

D. Tech. (Department of Information Technology, Faculty of Applied and Computer Sciences), Vaal University of Technology. / Simultaneous Localization and Mapping (SLAM) is a significant problem that has been extensively researched in robotics. Its contribution to autonomous robot navigation has attracted researchers towards focusing on this area. In the past, various techniques have been proposed to address SLAM problem with remarkable achievements but there are several factors having the capability to degrade the effectiveness of SLAM technique. These factors include environmental noises (light intensity and shadow), dynamic environment, kidnap robot and computational cost. These problems create inconsistency that can lead to erroneous results in implementation. In the attempt of addressing these problems, a novel SLAM technique Known as DIK-SLAM was proposed. The DIK-SLAM is a SLAM technique upgraded with filtering algorithms and several re-modifications of Monte-Carlo algorithm to increase its robustness while taking into consideration the computational complexity. The morphological technique and Normalized Differences Index (NDI) are filters introduced to the novel technique to overcome shadow. The dark channel model and specular-to-diffuse are filters introduced to overcome light intensity. These filters are operating in parallel since the computational cost is a concern. The re-modified Monte-Carlo algorithm based on initial localization and grid map technique was introduced to overcome the issue of kidnap problem and dynamic environment respectively. In this study, publicly available dataset (TUM-RGBD) and a privately generated dataset from of a university in South Africa were employed for evaluation of the filtering algorithms. Experiments were carried out using Matlab simulation and were evaluated using quantitative and qualitative methods. Experimental results obtained showed an improved performance of DIK-SLAM when compared with the original Monte Carlo algorithm and another available SLAM technique in literature. The DIK-SLAM algorithm discussed in this study has the potential of improving autonomous robot navigation, path planning, and exploration while it reduces robot accident rates and human injuries.

The Quality of Service (QoS) routing approach is gaining an increasing interest in the Internet community due to the new emerging Internet applications such as real-time multimedia applications. These applications require better levels of quality of services than those supported by best effort networks. Therefore providing such services is crucial to many real time and multimedia applications which have strict quality of service requirements regarding bandwidth and timeliness of delivery. QoS routing is a major component in any QoS architecture and thus has been studied extensively in the literature. Scalability is considered one of the major issues in designing efficient QoS routing algorithms due to the high cost of QoS routing both in terms of computational effort and communication overhead. Localized quality of service routing is a promising approach to overcome the scalability problem of the conventional quality of service routing approach. The localized quality of service approach eliminates the communication overhead because it does not need the global network state information. The main aim of this thesis is to contribute towards the localised routing area by proposing and developing some new models and algorithms. Toward this goal we make the following major contributions. First, a scalable and efficient QoS routing algorithm based on a localised approach to QoS routing has been developed and evaluated. Second, we have developed a path selection technique that can be used with existing localized QoS routing algorithms to enhance their scalability and performance. Third, a scalable and efficient hierarchical QoS routing algorithm based on a localised approach to QoS routing has been developed and evaluated.

The tremendous increase in usage and complexity of modern communication and network systems connected to the Internet, places demands upon security management to protect organisations¿ sensitive data and resources from malicious intrusion. Malicious attacks by intruders and hackers exploit flaws and weakness points in deployed systems through several sophisticated techniques that cannot be prevented by traditional measures, such as user authentication, access controls and firewalls. Consequently, automated detection and timely response systems are urgently needed to detect abnormal activities by monitoring network traffic and system events. Network Intrusion Detection Systems (NIDS) and Network Intrusion Prevention Systems (NIPS) are technologies that inspect traffic and diagnose system behaviour to provide improved attack protection. The current implementation of intrusion detection systems (commercial and open-source) lacks the scalability to support the massive increase in network speed, the emergence of new protocols and services. Multi-giga networks have become a standard installation posing the NIDS to be susceptible to resource exhaustion attacks. The research focuses on two distinct problems for the NIDS: missing alerts due to packet loss as a result of NIDS performance limitations; and the huge volumes of generated alerts by the NIDS overwhelming the security analyst which makes event observation tedious. A methodology for analysing alerts using a proposed framework for alert correlation has been presented to provide the security operator with a global view of the security perspective. Missed alerts are recovered implicitly using a contextual technique to detect multi-stage attack scenarios. This is based on the assumption that the most serious intrusions consist of relevant steps that temporally ordered. The pre- and post- condition approach is used to identify the logical relations among low level alerts. The alerts are aggregated, verified using vulnerability modelling, and correlated to construct multi-stage attacks. A number of algorithms have been proposed in this research to support the functionality of our framework including: alert correlation, alert aggregation and graph reduction. These algorithms have been implemented in a tool called Multi-stage Attack Recognition System (MARS) consisting of a collection of integrated components. The system has been evaluated using a series of experiments and using different data sets i.e. publicly available datasets and data sets collected using real-life experiments. The results show that our approach can effectively detect multi-stage attacks. The false positive rates are reduced due to implementation of the vulnerability and target host information.

Active Queue Management (AQM) schemes are used for ensuring the Quality of Service (QoS) in telecommunication networks. However, they are sensitive to parameter settings and have weaknesses in detecting and controlling congestion under dynamically changing network situations. Another drawback for the AQM algorithms is that they have been applied only on the Markovian models which are considered as Short Range Dependent (SRD) traffic models. However, traffic measurements from communication networks have shown that network traffic can exhibit self-similar as well as Long Range Dependent (LRD) properties. Therefore, it is important to design new algorithms not only to control congestion but also to have the ability to predict the onset of congestion within a network. An aim of this research is to devise some new congestion control methods for communication networks that make use of various traffic characteristics, such as LRD, which has not previously been employed in congestion control methods currently used in the Internet. A queueing model with a number of ON/OFF sources has been used and this incorporates a novel congestion prediction algorithm for AQM. The simulation results have shown that applying the algorithm can provide better performance than an equivalent system without the prediction. Modifying the algorithm by the inclusion of a sliding window mechanism has been shown to further improve the performance in terms of controlling the total number of packets within the system and improving the throughput. Also considered is the important problem of maintaining QoS constraints, such as mean delay, which is crucially important in providing satisfactory transmission of real-time services over multi-service networks like the Internet and which were not originally designed for this purpose. An algorithm has been developed to provide a control strategy that operates on a buffer which incorporates a moveable threshold. The algorithm has been developed to control the mean delay by dynamically adjusting the threshold, which, in turn, controls the effective arrival rate by randomly dropping packets. This work has been carried out using a mixture of computer simulation and analytical modelling. The performance of the new methods that have / Ministry of Higher Education in Egypt and the Egyptian Cultural Centre and Educational Bureau in London

This thesis considers the modulation division based on the concept of uniquely factorable constellation pair (UFCP) and uniquely decodable constellation group (UDCG) in multiuser wireless communication networks. We first consider a two-hop relay network consisting of two single-antenna users and a two-antenna relay node, for which a novel distributed concatenated Alamouti code is devised. This new design allows the source and relay nodes to transmit their own information to the destination node concurrently at the symbol level with the aid of the UFCP generated from both PSK and square QAM constellations as well as by jointly processing the noisy signals received at the relay node. Moreover, an asymptotic symbol error probability (SEP) formula is derived for the ML receiver, showing that the maximum diversity gain function is achieved, which is proportional to $\ln \mathtt{SNR}/\mathtt{SNR}^2$. Then, we concentrate on the point-to-point correlated multiple-input and multiple-output (MIMO) communication systems where full knowledge of channel state information (CSI) is available at the receiver and only the first- and second-order statistics of the channels are available at the transmitter. When the number of antenna elements of both ends goes to infinity while keeping their ratio constant, the asymptotic SEP analysis is carried out for either optimally precoded or uniformly precoded correlated large MIMO fading channels using the zero-forcing (ZF) detector with equally likely PAM, PSK or square QAM constellations. For such systems, we reveal some very nice structures which inspire us to explore two very useful mathematical tools (i.e., the Szego's theorem on large Hermitian Toeplitz matrices and the well-known limit: $\lim_{x\to\infty}(1+1/x)^x=e$), for the systematic study of asymptotic behaviors on their error performance. This new approach enables us to attain a very simple expression for the SEP limit as the number of the available antenna elements goes to infinity. In what follows, the problem of precoder design using a zero-forcing decision-feedback (ZF-DF) detector is also addressed. For such a MIMO system, our principal goal is to efficiently design an optimal precoder that minimizes the asymptotic SEP of the ZF-DF detector under a perfect decision feedback. By fully taking advantage of the product majorization relationship among eigenvalues, singular-values and Cholesky values of the precoded channel matrix parameters, a necessary condition for the optimal solution to satisfy is first developed and then the structure of the optimal solution is characterized. With these results, the original non-convex problem is reformulated into a convex one that can be efficiently solved by using an interior-point method. In addition, by scaling up the antenna array size of both terminals without bound for such a network, we propose a novel method as we did for the ZF receiver scenario to analyze the asymptotic SEP performance of an equal-diagonal QRS precoded large MIMO system when employing an abstract Toeplitz correlation model for the transmitter antenna array. This new approach has a simple expression with a fast convergence rate and thus, is efficient and effective for error performance evaluation. For multiuser communication networks, we first consider a discrete-time multiple-input single-output (MISO) Gaussian broadcast channel (BC) where perfect CSI is available at both the transmitter and all the receivers. We propose a flexible and explicit design of a uniquely decomposable constellation group (UDCG) based on PAM and rectangular QAM constellations. With this new concept, a modulation division (MD) transmission scheme is developed for the considered MISO BC. The proposed MD scheme enables each receiver to uniquely and efficiently recover their desired signals from the superposition of mutually interfering cochannel signals in the absence of noise. Using max-min fairness as a design criterion, the optimal transmitter beamforming problem is solved in a closed-form for two-user MISO BC. Then, for a general case with more than two receivers, a user-grouping based beamforming scheme is developed, where the grouping method, beamforming vector design and power allocation problems are addressed by employing weighted max-min fairness. Then, we consider an uplink massive single-input and multiple-output (SIMO) network consisting of a base station (BS) and several single-antenna users. To recover the transmitted signal matrix of all the users when the antenna array size is large, a novel multi-user space-time modulation (MUSTM) scheme is proposed for the considered network based on the explicit construction of QAM uniquely-decomposable constellation groups (QAM-UDCGs). In addition, we also develop a sub-constellation allocation method at the transmitter side to ensure the signal matrix is always invertible. In the meanwhile, an efficient training correlation receiver (TCR) is proposed which calculates the correlation between the received sum training signal vector and the sum information carrying vector. Moreover, the optimal power allocation problems are addressed by maximizing the coding gain or minimizing the average SEP of the received sum signal under both average and peak power constraints on each user. The proposed transmission scheme not only allows the transmitted signals with strong mutual interference to be decoded by a simple TCR but it also enables the CSI of all the users to be estimated within a minimum number of time slots equal to that of the users. Comprehensive computer simulations are carried out to verify the effectiveness of the proposed uniquely decomposable space-time modulation method in various network topologies and configurations. Our modulation division method will be one of the promising technologies for the fifth generation (5G) communication systems. / Dissertation / Doctor of Philosophy (PhD)

Against the theoretical background of evolutionary behavioral economics, this project analyzes bounded rationality and adaptive behaviour in organizational settings characterized by complexity and persistent uncertainty. In particular, drawing upon the standard NK model, two laboratory experiments investigate individual and collective decision-making in combinatorial problems of resource allocation featuring multiple dimensions and various levels of complexity. In the first study, investment horizons of different length are employed to induce a near or distant future temporal orientation, in order to assess the effects of complexity and time horizon on performance and search behaviour, examine the presence of a temporal midpoint heuristic, and inspect the moderating effects of deadline proximity on the performance-risk relationship. This is relevant for organizational science because the passage of time is essential to articulate many strategic practices, such as assessing progress, scheduling and coordinating task-related activities, discerning the processual dynamics of how these activities emerge, develop, and terminate, or interpreting retrospected, current, and anticipated events. A greater or lesser amount of time reflects then a greater or lesser provision of resources, thereby representing a constraint that can greatly affect the ability to maintain a competitive advantage or ensure organizational survival. In the second study, the accuracy of the imitative process is varied to induce a flawless or flawed information diffusion system and, congruently, an efficient or inefficient communication network, in order to assess the effects of complexity and parallel problem-solving on autonomous search behaviour, clarify the core drivers of imitative behaviour, control for the degree of strategic diversity under different communication networks, and evaluate individual as well as collective performance conditional to the interaction between the levels of complexity and the modalities of parallel problem-solving. This is relevant for organizational science because imitating the practices of high-performing actors is one of the key strategies employed by organizations to solve complex problems and improve their performance, thereby representing a major part of the competitive process. The project is intended to contribute grounding individual and collective behaviour in a more psychologically and socially informed decision-making, with a view to further the research agenda of behavioral strategy and sustain the paradigm shift towards an evolutionary-complexity approach to real economic structures.

<p>Smart downlink scheduling can be used to reduce infrastructure-to-vehicle energy costs in delay tolerant roadside networks. In this thesis this type of scheduling is incorporated into ON/OFF roadside unit sleep activity, to further reduce infrastructure power consumption. To achieve significant power savings however, the OFF-to-ON sleep transitions may be very lengthy, and this overhead must be taken into account when performing the scheduling. The OFF/ON sleep transitions are incorporated into a lower bound on energy use for the constant bit rate air interface case. An online scheduling algorithm referred to as the Flow Graph Sleep Scheduler (FGS) is then introduced which makes locally optimum ON/OFF cycle decisions. This is done by computing energy estimates needed both with and without a new OFF/ON cycle. The energy calculation can be efficiently done using a novel minimum ow graph formulation. We also consider the fixed transmit power, variable bit rate, air interface case. As before, a lower bound on RSU energy use is computed by formulating and solving an integer program. Results from a variety of experiments show that the proposed scheduling algorithms perform well when compared to the energy lower bounds. The algorithms are especially attractive in situations where vehicle demands and arrival rates are such that the energy costs permit frequent ON/OFF cycling.</p> / Master of Science (MSc)

Increasingly, wireless subscribers are demanding reliable data capabilities from wireless networks. The ability of wireless network engineers and Information Technology (IT) professionals to rapidly design, deploy, and maintain wireless communication systems that can provide strong, reliable data service is severely hampered by a lack of adequate systems and methods for simulating the performance of such networks a priori. Unlike older generation wireless systems that could be readily deployed on the basis of strong received signal strength and simple circuit-switched channel allocation protocols, modern and emerging wireless data networks are more noise and interference limited and rely on packet-based protocols. A heavier emphasis is needed on predicting and simulating throughput, bit error rate, frame error rate, user priority classes, and overall network capacity. This research provides wireless network engineers and IT professionals with a comprehensive system and method for the simulation and design of wireless communication systems that combines site-specific databases, equipment-specific distribution system modeling, and advanced ray tracing propagation analysis to directly predict throughput, frame error rate (FER), and other critical performance parameters for emerging wireless data networks. / Ph. D.

The mobility attribute of a mobile agent implies deployment thereof in untrustworthy environments, which introduces malicious host threats. The research question deals with how a security framework could be constructed to address the mentioned threats without introducing high costs or restraining the mobile agent's autonomy or performance. Available literature have been studied, analysed and discussed. The salient characteristics as well as the drawbacks of current solutions were isolated. Through this knowledge a dynamic mobile agent security framework was defined. The framework is based on the definition of multiple security levels, depending on type of deployment environment and type of application. A prototype was constructed and tested and it was found to be lightweight and efficient, giving developers insight into possible security threats as well as tools for maximum protection against malicious hosts. The framework outperformed other frameworks / models as it provides dynamic solutions without burdening a system with unnecessary security gadgets and hence paying for it in system cost and performance / Computing / D.Phil.