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Yes / An effective method is presented for suppressing mutual coupling between adjacent radiating elements which is based on metasurface isolation for MIMO and synthetic aperture radar (SAR) systems. This is achieved by choking surface current waves induced over the patch antenna by inserting a cross-shaped metasurface structure between the radiating elements. Each arm of the cross-shaped structure constituting the metasurface is etched with meander-line slot (MLS). Effectiveness of the metasurface is demonstrated for a2×2antenna array that operates over six frequency sub-bands in X, Ku and K-bands. With the proposed technique, the maximum improvement achieved in attenuating mutual coupling between neighbouring antennas is: 8.5 dB (8-8.4 GHz), 28 dB (9.6-10.8 GHz), 27 dB (11.7-12.6 GHz), 7.5 dB (13.4-14.2 GHz), 13 dB (16.5-16.8 GHz) and 22.5 dB (18.5-20.3 GHz). Furthermore, with the proposed technique (i) minimum center-to-center separation between the radiating elements can be reduced to 0.26λ0, where λ0 is 8.0 GHz; (ii) use of ground-plane or defected ground structures are unnecessary; (iii) use of short-circuited via-holes are avoided; (iv) it eliminates the issue with poor front-to-back ratio; and (v) it can be applied to existing arrays retrospectively. / H2020-MSCA-ITN-2016 SECRET-722424 and the financial support from the UK Engineering and Physical Sciences Research Council (EPSRC) under grant EP/E0/22936/1

Most acoustic measurements and parameters provided by a manufacturer of acoustic elements, which are offering additional solutions to room acoustics as well as acoustic construction works, are mainly limited to the parameters associated with absorption of individual elements. Until now, these diffusional elements have been neglected. Diffusi- onal panels are used to e.g. eliminate direct reflection of sound waves to the listener or reflection of sound waves concentrated at one point. Combination of absorptive acoustic panels and diffusion elements results in a space that is customised to the submitter’s needs.

This thesis is concerned with the problem of designing Mobile Location Services (MLS) - also commonly termed Location-Based Services - that meet user needs. MLS are applications that users access via a portable device such as a mobile phone. They provide services (i.e. information or other functionality) to end-users based on knowledge of the location of individuals and other entities within the environment. The market failure of many mobile services, including MLS, has been attributed in part to failing to provide `value' to the end user. This thesis reviews different theoretical approaches to help understand the notion of `value', and how value may be used to inform design (Chapter 2). Research methods are also discussed, including the particular challenges with doing `mobile' research (Chapter 3). A survey of UK consumers( Chapter4 ) demonstratesa current lack of use, and lack of awarenesso f most forms of MLS in the UK. llowever, overall positive attitudes,a nd a range of behavioural and demographic data, suggest that MLS have the potential to be successful if they can be designed to meet user needs. A qualitative study of users' travelling behaviour (Chapter 5) then demonstrates how effective mobile information delivery can provide considerable value within a dynamic, uncertain and location-varying environment. This added value is highly dependent on contextual and situated factors, including existing information sources, variances in possible outcomes and the intrinsic qualities of information provision. The thesis then focuses on a particular application domain for MLS - drivers navigating in an unfamiliar environment. A literature review (Chapter 6) investigates how drivers navigate, and what their information needs are. Three experimental studies (Chapters 7 to 9) then investigate what information adds value within a navigation context, the impact of contextual influences on driving and navigation performance, and the impact of the quality of the navigation cue on task performance. Good landmarks (such as traffic lights) are shown to add value for drivers navigating an unfamiliar route, depending on the context at particular manoeuvres. This thesis discusses( Chapter 10) how a multi-disciplinary perspectivec an help maximise the acceptance and effectiveness of MLS. 'Value' can be used to design specific services for users, based on offering new freedoms to the individual within a mobile context, employing time and location sensitivity to maximise relevance, taking into account user knowledge, existing information sources and contextual factors, and ensuring impact on real-world outcomes. In conclusion (Chapter 11), specific contributions and avenues for future work are highlighted.

Approved for public release, distribution is unlimited / Internet Protocol version six (IPv6), the next generation Internet Protocol, exists sparsely in today's world. However, as it gains popularity, it will grow into a vital part of the Internet and communications technology in general. Many large organizations, including the Department of Defense, are working toward deploying IPv6 in many varied applications. This thesis focuses on the design and implementation issues that accompany a migration from Internet Protocol version four (IPv4) to IPv6 in the Monterey Security Enhanced Architecture (MYSEA). The research for this thesis consists of two major parts: a functional comparison between the IPv6 and IPv4 designs, and a prototype implementation of MYSEA with IPv6. The current MYSEA prototype relies on a subset of Network Address Translation (NAT) functionality to support the network's operation; and, due to the fact that IPv6 has no native support for NAT, this work also requires the creation of a similar mechanism for IPv6. This thesis provides a preliminary examination of IPv6 in MYSEA, which is a necessary step in determining whether the new protocol will assist with or detract from the enforcement of MYSEA policies. / Ensign, United States Navy

Three-dimensional laser scanning has revolutionized spatial data acquisition and can be completed from a variety of platforms including airborne (ALS), mobile (MLS), and static terrestrial (TLS) laser scanning. MLS is a rapidly evolving technology that provides increases in efficiency and safety over static TLS, while still providing similar levels of accuracy and resolution. The componentry that make up a MLS system are more parallel to Airborne Laser Scanning (ALS) than to that of TLS. However, achievable accuracies, precisions, and resolution results are not clearly defined for MLS systems. As such, industry professionals need guidelines to standardize the process of data collection, processing, and reporting. This thesis lays the foundation for MLS guidelines with a thorough review of currently available literature that has been completed in order to demonstrate the capabilities and limitations of a generic MLS system. A key difference between MLS and TLS is that a mobile platform is able to collect a continuous path of geo-referenced points along the navigation path, while a TLS collects points from many separate reference frames as the scanner is moved from location to location. Each individual TLS setup must be registered (linked with a common coordinate system) to adjoining scan setups. A study was completed comparing common methods of TLS registration and geo-referencing (e.g., target, cloud-cloud, and hybrid methods) to assist a TLS surveyor in deciding the most appropriate method for their projects. Results provide insight into the level of accuracy (mm to cm level) that can be achieved using the various methods as well as the field collection and office processing time required to obtain a fully geo-referenced point cloud. Lastly, a quality assurance methodology has been developed for any form of LiDAR data to verify both the absolute and relative accuracy of a point cloud without the use of retro-reflective targets. This methodology incorporates total station validation of a scanners point cloud to compare slopes of common features. The comparison of 2D slope features across a complex geometry of cross-sections provides 3D positional error in both horizontal and vertical component. This methodology lowers the uncertainty of single point accuracy statistics for point clouds by utilizing a larger portion of a point cloud for statistical accuracy verification. This use of physical features for accuracy validation is particularly important for MLS systems because MLS systems cannot produce sufficient resolution on targets for accuracy validation unless they are placed close to the vehicle. / Graduation date: 2012

Polystyrene (PS) nanocomposite foams were prepared using supercritical fluid (SCF) CO2 as a solvent and blowing agent. PS was first in-situ polymerized with a range of concentrations of montmorillonite layered silicate (MLS). The polymerized samples were then compression molded into 1 to 2mm thick laminates. The laminates were foamed in a batch supercritical CO2 process at various temperatures and pressures from 60°-85°C and 7.6-12MPa. The resulting foams were analyzed by scanning electron microscopy to determine effect of MLS on cellular morphology. Differential scanning calorimetry was used to determine the impact of nanocomposite microstructure on glass transition of the foamed polymer. X-ray diffraction spectra suggested that the PS/MLS composite had an intercalated structure at both the 1% and 3% mixtures, and that the intercalation may be enhanced by the foaming process.

Monitoring and predicting machine breakdowns are of vital importance in the manufacturing industry. Machine Learning models could be used to improve these breakdown predictions. However, the operators responsible for the machines need to trust and understand the predictions in order to base their decisions on the information. For this reason, Explainable Artificial Intelligence, XAIs, was introduced. It is defined as the set of Artificial Intelligence systems that can provide predictions in an intelligible and trustful form. Hence, the purpose of this research is to study different techniques of Explainable Artificial Intelligence XAIs in order to discover the most suitable methodology for allowing people without a machine learning background, employed in a manufacturing environment, to understand and trust predictions. Four XAI interfaces have been tested: three integrated XAI techniques were identified through a literature review, and one was presenting an experimental XAIs facility based on a machine learning model for outliers identification. In order to predict future machines’ states, classifiers based on Random Forest were built, while for identifying anomalies a model based on Isolation Forest was built. In addition, a user study was carried out in order to discern end-users perspectives about the four XAI interfaces. Final results showed that the XAI interface based on anomalous production values gained high approval among users with no or basic machine learning knowledge. / Övervakning och förutsägelse av maskinhaverier är av avgörande betydelse inom tillverkningsindustrin. Machine Learning-modeller kan användas för att förbättra dessa förutsägelser om sammanbrott. De operatörer som ansvarar för maskinerna måste dock lita på och förstå förutsägelserna för att kunna basera sina beslut på informationen. Av denna anledning introducerades Explainable Artificial Intelligence, XAIs. Det definieras som en uppsättning artificiell intelligenssystem som kan ge förutsägelser i en begriplig och pålitlig form. Därför är syftet med denna forskning att studera olika tekniker för Explainable Artificiell Intelligens XAIs för att upptäcka den mest lämpliga metoden för att låta människor utan maskininlärningsbakgrund, anställda i en tillverkningsmiljö, förstå och lita på förutsägelser. Fyra XAIgränssnitt har testats: tre integrerade XAI-tekniker identifierade genom en litteraturgenomgång, och en presenterade en experimentell XAI-anläggning baserad på en maskininlärningsmodell för identifiering av extremvärden. För att förutsäga framtida maskiners tillstånd byggdes klassificerare baserade på Random Forest, medan för att identifiera anomalier byggdes en modell baserad på Isolation Forest. Dessutom genomfördes en användarstudie för att urskilja slutanvändarnas perspektiv på de fyra XAI-gränssnitten. Slutresultaten visade att XAI-gränssnittet baserat på onormala produktionsvärden fick högt godkännande bland användare utan någon eller grundläggande kunskap om maskininlärning.

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