Innovative Wireless Localization Techniques and Applications

Innovative methodologies for the wireless localization of users and related applications are addressed in this thesis. In last years, the widespread diffusion of pervasive wireless communication (e.g., Wi-Fi) and global localization services (e.g., GPS) has boosted the interest and the research on location information and services. Location-aware applications are becoming fundamental to a growing number of consumers (e.g., navigation, advertising, seamless user interaction with smart places), private and public institutions in the fields of energy efficiency, security, safety, fleet management, emergency response. In this context, the position of the user - where is often more valuable for deploying services of interest than the identity of the user itself - who. In detail, opportunistic approaches based on the analysis of electromagnetic field indicators (i.e., received signal strength and channel state information) for the presence detection, the localization, the tracking and the posture recognition of cooperative and non-cooperative (device-free) users in indoor environments are proposed and validated in real world test sites. The methodologies are designed to exploit existing wireless infrastructures and commodity devices without any hardware modification. In outdoor environments, global positioning technologies are already available in commodity devices and vehicles, the research and knowledge transfer activities are actually focused on the design and validation of algorithms and systems devoted to support decision makers and operators for increasing efficiency, operations security, and management of large fleets as well as localized sensed information in order to gain situation awareness. In this field, a decision support system for emergency response and Civil Defense assets management (i.e., personnel and vehicles equipped with TETRA mobile radio) is described in terms of architecture and results of two-years of experimental validation

COMPETITIVE DYNAMICS IN ELECTRONIC NETWORKS - ACHIEVING COMPETITIVENESS THROUGH INTERORGANIZATIONAL SYSTEMS

Many dramatic and potentially powerful uses of information technology involveinterorganizational systems (IOS). These systems, defined as distributed computing systems thatsupport shared processes between firms, have become fundamental to business operations,spanning multiple activities in value/supply chains. They have opened avenues to unprecedentedcollaborative linkages between firms. As IOS-mediated relational networks are rapidly evolving,roles of IOS have progressively changed beyond those of efficiency and power functions.To fully appreciate modern roles of IOS in e-business, this dissertation addresses two keyresearch questions: (1) How do firms achieve competitiveness through IOS? (2) How do IOSinfluence competitive behaviors of the competing firms in intertwined electronic networks? Itdoes so by integrating three research streams – social network analysis, interorganizationalsystems, and competitive dynamics – into a model of competitive dynamics in electronicnetworks. This study focuses on the paired relationships between the three constructs of networkstructure, IOS use, and competitive action, and empirically investigates nine general hypotheses.Data collection focuses on second-hand data in the automotive industry. A total of 805collaborative relationships, 106 IOS technologies and applications, and 305 competitive actionsinvolving nine major automakers are collected. Data sources include databases, major tradepublications, Web sites, and industry indices. Data analysis includes network analysis, ANOVAtest, and correlation.Empirical results support the general contention that network structure and IOS use coevolveand influence competitive action. Building on these results, a framework characterizingIOS\u27s roles in achieving firm competitiveness is concluded and advanced. This dissertation broadens our view of IOS\u27s roles in e-business. It contributes to IS/IOS theory, methodology, and practice. First, this study examines IOS-mediated networks inmultiple levels, including firm-level, pair-level, and network-level. It provides new theoreticalconceptualizations of IOS\u27s roles. Second, this study advances a new IT value measureaddressing limitations of the traditional measures. Third, it introduces a novel, usefulmethodology for data collection. Fourth, results from this study can guide a firm\u27s e-businessinitiatives for using IOS as powerful tools for achieving firm competitiveness

Analog-Digital Beamforming in the MU-MISO Downlink by use of Tunable Antenna Loads

We investigate the performance of multi-user multiple-input-single-output (MU-MISO) downlink in the presence of the mutual coupling effect at the transmitter. Contrary to traditional approaches that aim at eliminating this effect, in this paper we propose a joint analog-digital (AD) beamforming scheme that exploits this effect to further improve the system performance. A jointly optimal AD beamformer is firstly obtained by iteratively maximizing the minimum received signal-to-interference-plus-noise ratio (SINR) in the digital domain, followed by an optimization on the load impedance of each antenna element in the analog domain. We further introduce a decoupled low-complexity approach, with which existing closed-form beamforming schemes can also be efficiently applied. For the consideration of hardware imperfections in practice, we study the case where the analog load values are quantized, and propose a sequential search scheme based on greedy algorithm to efficiently obtain the desired quantized load values. Moreover, we also investigate the imperfect channel state information (CSI) scenarios, where we prove the optimality for closed-form beamformers, and further propose the robust schemes for two typical CSI error models. Simulation results show that with the proposed schemes the mutual coupling effect can be exploited to further improve the performance for both perfect CSI and imperfect CSI

Air Force Institute of Technology Research Report 2009

This report summarizes the research activities of the Air Force Institute of Technology’s Graduate School of Engineering and Management. It describes research interests and faculty expertise; lists student theses/dissertations; identifies research sponsors and contributions; and outlines the procedures for contacting the school. Included in the report are: faculty publications, conference presentations, consultations, and funded research projects. Research was conducted in the areas of Aeronautical and Astronautical Engineering, Electrical Engineering and Electro-Optics, Computer Engineering and Computer Science, Systems and Engineering Management, Operational Sciences, Mathematics, Statistics and Engineering Physics

Air Force Institute of Technology Research Report 2010

This report summarizes the research activities of the Air Force Institute of Technology’s Graduate School of Engineering and Management. It describes research interests and faculty expertise; lists student theses/dissertations; identifies research sponsors and contributions; and outlines the procedures for contacting the school. Included in the report are: faculty publications, conference presentations, consultations, and funded research projects. Research was conducted in the areas of Aeronautical and Astronautical Engineering, Electrical Engineering and Electro-Optics, Computer Engineering and Computer Science, Systems and Engineering Management, Operational Sciences, Mathematics, Statistics and Engineering Physic

University of Malaya Research Bulletin, Volume 1, 2015

Previously known as IPPP UM Research Bulleti

The University Defence Research Collaboration In Signal Processing

This chapter describes the development of algorithms for automatic detection of anomalies from multi-dimensional, undersampled and incomplete datasets. The challenge in this work is to identify and classify behaviours as normal or abnormal, safe or threatening, from an irregular and often heterogeneous sensor network. Many defence and civilian applications can be modelled as complex networks of interconnected nodes with unknown or uncertain spatio-temporal relations. The behavior of such heterogeneous networks can exhibit dynamic properties, reflecting evolution in both network structure (new nodes appearing and existing nodes disappearing), as well as inter-node relations. The UDRC work has addressed not only the detection of anomalies, but also the identification of their nature and their statistical characteristics. Normal patterns and changes in behavior have been incorporated to provide an acceptable balance between true positive rate, false positive rate, performance and computational cost. Data quality measures have been used to ensure the models of normality are not corrupted by unreliable and ambiguous data. The context for the activity of each node in complex networks offers an even more efficient anomaly detection mechanism. This has allowed the development of efficient approaches which not only detect anomalies but which also go on to classify their behaviour