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Item Open Access 3D Panoptic Segmentation with Unsupervised Clustering for Visual Perception in Autonomous Driving(2021-09) Grenier, Amelie; Chermak, LFor the past decade, substantial progress has been achieved in the field of visual per ception for autonomous driving application thanks notably to the capabilities of deep learning techniques. This work aims to leverage stereovision and explore different methods, in particular unsupervised clustering approaches, to perform 3D panoptic segmentation for navigation purposes. The main contribution of this work consists in the development, test and validation of a novel framework in which geometric and semantic understanding of the scene are obtained separately at the pixel level. The combination of both for the extracted visual 2D information of the desired class provides a 3D sparse classified point cloud, which is used afterward for instance clustering. Preliminary tests of the baseline version of the framework for Vehicle objects were conducted on urban driving datasets. Results demonstrate for the first time the via bility for processing of this type of point cloud from visual data, and reveal improve ments areas. Specially, the importance of the boundary F-score in semantic seg mentation is highlighted for the first time in this application, with an increase up to 32 percentage point in this study. Additional contribution was made by applying distribution clustering as well as density based clustering for instance segmentation in a visual based 3D space representa tion. Results showed that DBSCAN was well suited for this application. As a result, it was proven that the presented framework can successfully provide genuine 3D profile map representation and localisation of vehicles in a urban environment from 2D visual information only. Furthermore, the mathematical formalisation of the link between DBSCAN’s param eter selection and camera projective geometry was presented as future work and a mean to demystify parameter selection.Item Open Access The Application of Deep Learning Algorithms to Longwave Infrared Missile Seekers(2021-12) Westlake, Samuel T; James, D BConvolutional neural networks (CNNs) have already surpassed human-level performance in complex computer vision applications, and can potentially significantly advance the performance of infrared anti-ship guided missile seeker algorithms. But the performance of CNN-based algorithms is very dependent on the data used to optimise them, typically requiring large sets of fully-annotated real-world training examples. Across four technical chapters, this thesis addresses the challenges involved with applying CNNs to longwave infrared ship detection, recognition, and identification. Across four technical chapters, this thesis addresses the challenges involved with applying CNNs to longwave infrared ship detection, recognition, and identification. The absence of suitable longwave infrared training data was addressed through the synthetic generation of a large, thermally-realistic dataset of 972,000 fully labelled images of military ships with varying seascapes and background clutter. This dataset—IRShips—is the largest openly available repository of such images worldwide. Configurable automated workflow pipelines significantly enhance the development of CNN-based algorithms. No such tool was available when this body of work began, so an integrated modular deep learning development environment—Deeplodocus—was created. Publicly-available, it now features among the top 50% of packages on the Python Package Index repository. Using Deeplodocus, the fully-convolutional one-stage YOLOv3 object detection algorithm was trained to detect ships in a highly-cluttered sequence of real world longwave infrared imagery. Further enhancement of YOLOv3 resulted in an F-score of 0.945 being achieved, representing the first time synthetic data has been used to train a CNN algorithm to successfully detect military ships in longwave infrared imagery.Benchmarking YOLOv3’s detection accuracy against two alternative CNNs— Faster R-CNN and Mask R-CNN—using visual-spectrum and near-infrared data from the Singapore Maritime dataset, showed that YOLOv3 was three times faster, but 3% less accurate than Mask R-CNN. Modifying YOLOv3 through the use of spectral domain-dependent encoding delivered state-of-the-art accuracy with respect to the near-infrared test data, while maintaining YOLOv3’s considerable speed advantage.Item Open Access The Boundaries of Flow: when the balance between a person’s challenges and capabilities becomes imbalanced, an empirical investigation of the relationship between subjective experience, capabilities and challenge.(2022-08) Forsyth, Tim; Hilton, Jeremy; Dodd, LorraineThe problematic situation this doctoral research project investigates concerns how the quality of a person’s lived subjective experience is affected by differing degrees of challenge: a product of pressures and demands that overwhelm a person’s knowledge, skills and experience (capability). The cost of stress and the ways stress make people vulnerable to illness is well documented. Therefore, the purpose of this doctoral research project is – to identify the thresholds (points) where the balance between challenges and capability moves to imbalance. This study uses Flow Theory and Complex Systems Theory as the foundation for this research. A literature review of flow theory pertaining to the research problem identified deficiencies in the models, methods and practices. As a result, the project is divided into two sections. The first section developed a new synthesised model of experience using an innovative suite of methods. The insights gained from this model were used to inform the second phase of the research project. The second phase utilises a novel multi-paradigmatic design strategy grounded in a realist philosophy of science. This approach facilitated the development of a quasi-experimental protocol and construct elicitation method to investigate the individual participant's subjective experience of varying degrees of challenge in the sensory and affective domains, respectively. This project contributes to the knowledge gap in two distinct yet complementary ways. Firstly, the research identified a relational link between challenge and subjective experience. Secondly, as experienced by the individual, challenge is incremental and cumulative. Moreover, this doctoral research project realises the overarching research objective by developing a codebook and a new synthesised model of experience. When the model and codebook are combined, they can identify when a person’s challenges and capabilities are aligned and misaligned through the various instances and absences of experiential states. This contribution represents a proof of concept. Future work is required to develop the method's applicability in organisational environments to support and enhance people’s lived experience of work.Item Open Access Conceptualizing, defining, and modelling supply chain management : an objective oriented approach.(2022-08) Alkebaisi, Hussain K; Allen, Robert; Hameed, AmerAlthough it has been more than three decades since the term Supply Chain Management (SCM) was first introduced, there are still divergent views and different interpretations amongst scholars and practitioners about its meaning. The literature lacks consensus on a precise definition of SCM and presents a plethora of different perspectives. A unified conceptual or theoretical model has not yet been acknowledged, and the existing frameworks lack the call for a holistic model that encompasses the essence of the concept. With this disagreement on what SCM is, there are repeated calls to achieve consensus on a unified definition, a unified understanding, a unified conceptual model, and a unified framework of SCM. The argument in the literature is that achieving consensus among scholars and practitioners will improve research and practice and the SCM discipline. The literature revealed that the prevalent and the most recommended approach of conceptualising SCM is the process orientation. However, there is no evidence in the literature that an objective-oriented approach was investigated in resolving those theoretical issues, and neither has a Grounded Theory research method been applied to that end.Through an objective-orientated approach and applying the grounded theory method, it is found that the majority of the theory behind SCM is about managing business activities and achieving business goals through the communication, cooperation, collaboration, and integration within and across firms in a supply chain or network. The proposed name of the identified theory is ‘Business Relations Management Theory.’ The theory states that individuals, organisations, societies and nations achieve better performance and outcomes through communication, cooperation, collaboration, and integration. A literature-based thematic analysis showed that SCM is being used as a synonym for Supply Management, Business Relations Management (BRM), or a combination of both. Also, an assessment survey that included more than 200 managers and employees from different countries showed unclear or limited understanding of the identified theory and perspective of BRM. Accordingly, this research presents the theory and perspective of BRM and asserts that the term Supply Chain Management (SCM) should be replaced with Business Relations Management (BRM). SCM, as a term, limits the benefits of communication, cooperation, collaboration, and integration to a chain or network of firms and enterprises within the production sector. In contrast, the Business Relations Management (BRM) concept generalises the benefits to all sectors and all stakeholders, including the final customers, consumers, and services recipients. In addition, universities or business schools are advised to replace SCM with ‘Supply Management’ or another name that combines supply and demand management fields. A Feedback survey included a group of managers and employees from different sectors in Bahrain showed a high level of satisfaction and acceptance of the outcomes of this research, the researcher’s argument, and recommendations. The feedback survey outcomes led to the conclusion that the objective orientation was an effective approach to conceptualise SCM, and there is a probability of higher acceptance of the outcomes of this research and, consequently, achieving consensus among academics and practitioners.Item Open Access The detection and prevention of Malware attacks on android mobile through the application of artificial intelligence techniques(2021-09) Ashawa, Moses Aprofin; Morris, S; Sastry, V V S SOur everyday lives are integrated with the use of mobile devices which store sensitive data. Sensitive data stored on smartphones attract different threats including malware. Among mobile platforms, Android is the most popular OS with malware targeting sensitive information and other mobile services. If malware infects a digital device, then it has control over the device's functionality and data. This can impact your finances, your privacy, and your access to your data. Malware is a threat not only to individuals but also to corporate organisations and financial institutions as well. This could lead to communication traffic of an infected network, hardware failure of the physical device, data theft, and loss of critical business data, among others. There are existing detection techniques for identifying Android malware. However, these techniques are limited in detecting evolving and sophisticated malware which use permission features as attack vectors in a smart fashion to infect Android mobile devices. To improve malware detection accuracy based on the related problem, we developed techniques for identifying Android-based malicious applications. To achieve this, the author presents a thorough review of the mobile malware evolution and infection strategies. The second part of the survey covers Android mobile malware detection, classification, and analysis techniques where the author identifies their efficacy in detecting evolving malware and their limitations. The author identifies through the review research gaps which open unto the development of different and novel solutions for Android malware classification and analysis. We leveraged the existing strengths of the previous methods to develop a robust novel automated framework to classify and analyse Android malware based on permission features. Classification accuracy of 97% was achieved with our framework with a False Positive Rate of 3%. Our techniques identified privileges that malware exploits as attack vectors to infect Android-based devices. The results demonstrate that our framework has high feature diversity capabilities for Android malware classification. We identified that there are permissions with similar attributes that are correlated and can trigger the installation of similar permissions with the same threat level especially. However, these prevention techniques are not tested on other mobile platforms' data and do not focus on mitigating pileup susceptibilities. Finally, we believe that as the results of this research are being made public and cited by organizations and individuals, the outcome of this will influence the security and social policies that mobile companies will implement based on some of the recommendations by our findings.Item Open Access Evaluation of off-road uninhabited ground vehicle mobility using discrete element method and scalability investigation(2022-09) Nuwal, A; Economou, John T.; Kumar, AFull-scale military vehicles are teaming up with uninhabited ground vehicles (UGVs) to improve the success rate of tactical operations on off-road terrains. UGV can perform initial mobility testing on soft soils during missions to evaluate the performance (e.g., go/ no-go) of full-scale military vehicles. Therefore, the concept of scale model testing is proposed. The scale model testing can be divided into two parts, i.e. the scalability of soil and the scalability of the tyre-soil interaction. The scalability of soil is defined as a relationship between the mechanical properties of an in-situ terrain (heterogeneous) system and a laboratory (homogeneous) soil system while accounting for the differences in sand, silt and clay particle shapes and size distributions. Physical properties such as moisture content, bulk density, compaction, and interparticle forces are kept the same for laboratory and in-situ terrain conditions. The 2NS and fine-grained sands were modelled using the discrete element method with Edinburgh elastic-plastic adhesion contact model. It was found that the scalability depends on the testing conditions and the soil’s nature. The heterogeneity of soil affects the cohesive and adhesive forces present in the soil system. The pressure-sinkage and shear stress vs shear displacement relationships are found scalable. The cone index vs depth relation is not scalable. The scale model testing can be divided into two parts, i.e. the scalability of soil and the scalability of the tyre-soil interaction. The scalability of soil is defined as a relationship between the mechanical properties of an in-situ terrain (heterogeneous) system and a laboratory (homogeneous) soil system while accounting for the differences in sand, silt and clay particle shapes and size distributions. Physical properties such as moisture content, bulk density, compaction, and interparticle forces are kept the same for laboratory and in-situ terrain conditions. The 2NS and fine-grained sands were modelled using the discrete element method with Edinburgh elastic-plastic adhesion contact model. It was found that the scalability depends on the testing conditions and the soil’s nature. The heterogeneity of soil affects the cohesive and adhesive forces present in the soil system. The pressure-sinkage and shear stress vs shear displacement relationships are found scalable. The cone index vs depth relation is not scalable.Further, the scalability of tyre-soil interaction is established using the dimensional analysis method to establish similarity in the full-scale and scaled systems. The developed non dimensional parameters are kept the same in both systems. In this research, the lightweight Armoured Personnel Carriers such as the FED Alpha and Land Rover are considered as the full-scale systems (upper boundary) and UGVs for example, the Husky or Warthog as a scaled system (lower boundary). Consequently, the tyre-soil interaction behaviour is similar in this specific tyre size and loading range. The full-scale tyre modelled is FED Alpha tyre 335/65R22.5 and is scaled down by size to scales 0.7, 0.5 and 0.25. Six different terrain simulation models of both sands were prepared with cone indexes ranging from 14.79 kPa to 149 kPa. It was found that the drawbar pull and tractive efficiency vs slip relations are scalable. The mean error in drawbar pull prediction w.r.t. NATO experiments is 12% and 9% for 2NS and fine-grained sand, respectively. The drawbar pull varies from square to cubic power w.r.t. the scale of the system. The gross traction varies with square power w.r.t. the scale of the system. The tractive efficiency is constant w.r.t. the scale of the system. It is concluded that a 0.5 scale system can predict the full-scale system’s mobility performance on sands. This key finding can be used to design and develop cost-effective and lighter UGVs to support full-scale military vehicles on the battlefield. The limitation of the DEM technique is that it is computationally expensive as the number of particles increases.Item Open Access First World War Grave Concentration on the Western Front: Hooge Crater Cemetery, Belgium(2021-04) Martin, V; Shortland, A; Harrison, K; Braekmans, DThe First World War took place between 1914 and 1918, with conflict occurring in Europe and across the globe. By the end of the War, the bodies of the British and Commonwealth dead were scattered across France and Belgium. It was decided to move single graves or small cemeteries into bigger cemeteries that were being built by the Imperial War Graves Commission. This process was called “concentration”, and involved searching the battlefields for graves, then excavating and attempting to identify the bodies present, prior to their reburial in a concentration cemetery. This thesis focuses on the concentration process and specifically examines a sample of graves from Hooge Crater Cemetery, Belgium. The main research aim is to understand the range of errors that occurred during concentration and identification, and how prolific they were. A historical and literature review was completed, followed by the analysis of data from 109 graves from Hooge Crater Cemetery that were re-exhumed in 1920. This proved that within the sample, a high number of errors occurred in the original concentration work. Following this, 163 burial returns containing the details of 1013 graves from Hooge Crater Cemetery were selected for detailed analysis. The information from these burial returns was gathered and reviewed, and where possible was plotted onto First World War trench maps. This data provides new insights into where and when bodies were concentrated, the type of methods used for identification and how these methods changed over time. The research presented here demonstrates that identification rates varied, and were influenced by several factors including burial location, quantity of body present, time of concentration and primary identification method used. Overall, this thesis expands our knowledge of First World War grave concentration, including how the battlefields were searched and how bodes were identified.Item Open Access A framework for optical features selection and management for camera-only autonomous navigation in the proximity to small celestial objects(2021-08) Di Fraia, Marco Z; Chemak, L; Sanchez Cuartielles, Joan PauSmall celestial bodies such as asteroids and comets are abundantly present in the Solar System, yet their surfaces remain largely unexplored. Achieving regular access to these surfaces would have a major impact on capabilities such as planetary defence and in situ resource utilisation and lead to significant scientific insights. However, missions close to small celestial objects remain challenging in at least two aspects: technically, due to weak gravity fields, complex operational environments and latency from long communication times, and commercially, with the applications still being few and cost-ineffective. A potential solution to reducing development and operational costs and obtaining robust, scalable operations, could be using small, camera-only spacecraft with an elevated degree of autonomy. Enabling a camera-based autonomy requires building appropriate computer vision pipelines. All computer vision pipelines start with the detection of features - salient patterns within the scene. This thesis presents multiple methods and tools enabling the appropriate selection and management of different features for autonomous navigation in proximity to asteroids. To that end, relevant contributions developed during this work consist of: The development of a software toolbox for prototyping and testing optical navigation technologies through a parametrisable synthetic 3D visual environment; An analysis of the response of feature detectors to internal factors (e.g., feature model) and external factors (e.g., illumination). This response, once known, can be used for designing the system or to obtain situational awareness An assessment of the response of template matching methods when the template (model) does not perfectly match the observed target (asteroid, with illumination). Through the above contributions, it was shown that considering environmental cues and the perception model helps in achieving robust camera-only navigation processes. This capability could lead to small satellites autonomously exploring hundreds or thousands of small celestial objects or be employed on more powerful spacecraft for redundancy.Item Open Access Investigation of early medieval pottery production in Lower Austria: an archaeological science approach(2021-06) Polyak, T; Shortland, A; Braekmans, D; Herold, HThis thesis aims to contribute to a better understanding of early medieval pottery production in Lower Austria by the scientific analysis of ceramics. The investigation is based on 135 potsherds, including graphite-containing ceramics, which originate from the Erlauf Valley and other sites of Lower Austria and Vienna. The ceramics are dated to the 1st–12th centuries AD, with a majority of samples (n=123) from the 6th–11th centuries AD. The potsherds are studied, in addition to macroscopic analysis, by four scientific methods: petrographic thin section analysis, scanning electron microscopy (SEM), inductively coupled plasma optical emission spectrometry (ICP-OES) and X-ray diffraction (XRD). These methods are used to identify and characterise the origin and manufacturing technology of the ceramics in order to gain insight into wider aspects of pottery production such as the organisation of production, technological choices, traditions and innovation. The compositions of the studied ceramics are consistent with different parts of one geological unit, the Bohemian Massif. This information, together with the distribution of the pots, provides details about connectivity and suggests the presence of local, regional and supra-regional trade/exchange networks within the study area. Traces of the applied production techniques indicate a relatively low level of standardisation for most of the ceramics; observations in this regard along with scale, degree of control and specialisation are used to discuss organisation of production. Through the reconstruction of the ceramic making process, technological choices are examined, such as the use of a new raw material, graphite, from the 8th/9th centuries. The analysis of the manufacturing steps also sheds light on practices of different periods and reveals, for example, differences in raw material preparation between the 1st–7 th and 8th–9 th centuries, which suggest a more sophisticated technology of pottery production in the former than in the latter period in the Erlauf Valley.Item Open Access Material Chemistry Control for the Additive Manufacture of Composite Propellants(2022-06) Brash, J P A; Vrcelj, Ranko; Moniruzzaman, MThis thesis has sought to aid the additive manufacture of propellants using a novel dry powder printing system developed at Cranfield. The energetic performance and hazard safety of crystalline energetic materials is intrinsically linked to crystal properties such as size, morphology, and crystalline phase. By optimisation of cooling, antisolvent, sonocrystallisation, spray drying and microencapsulation, the properties of cyclotrimethylenetrinitramine (RDX) and ammonium perchlorate (AP) have been engineered towards better performance within our printing system. Crystallisation of AP from solution in water has been assessed as a means of producing particles with a controllable particle size and morphology. Slow cooling processes (−7.5 °C hr-1 ) failed to produce material suited for use in propellant formulations. However, by significantly increasing the nucleation rate using rapid cooling crystallisation processes (~ −5 °C min-1 ) the size of generated crystals was greatly reduced, with a d50 range of 79.1 - 152.3 µm, compared to ~ 500 – 2000 µm. The application of ultrasonic radiation via a horn to the rapid cooling crystallisation gave promising results – leading to particle size reduction (d50 range: 33.5 – 43.4 µm) and a reduced frequency of secondary nucleation. Moreover, the average particle size distribution width was reduced from 245 µm to 75 µm by the application of sonication. Flow character, as assessed by angle of repose measurements, was good for these sonicated materials (31.0° to 34.1°). Spray drying and micro encapsulation was assessed as a means of RDX particle size reduction. Initial studies using paracetamol as an inert simulant demonstrated that modifications to spray drying process parameters (flow, atomisation pressure, nozzle diameter and feed concentration) produced measurable changes in particle size and size distribution. However, attempts to rationalise these effects using a multifactorial design of experiment were inhibited with the significant errors retrieved from the model. Attempts to understand how particle properties impact the flow character of a powder led to the observation that increased particle size gave decreased angle of repose. However, the magnitude of change was negligible when compared to the effect of reformulation in the presence of known glidant nanomaterials. Microencapsulation of RDX with cellulose acetate butyrate (CAB) was conducted at a range of operating temperatures between 55 and 100 °C. Both particle morphology and impact Figure of insensitiveness were demonstrably affected by drying temperature, and both were minimised by the use of lower drying temperatures (d50 = 2.60 µm, FoI = 102.0). FoI values for RDX/CAB microparticles correlated negatively with drying temperature, suggesting that the strain imparted by this rapid crystallisation process may be retained in the material thereby acting to influence its hazardous nature. Crystallisation of RDX by antisolvent precipitation and spray drying was assessed with the inclusion of five different tailor-made additives (TMAs). Of the assessed TMAs, 2,4-dimethyl-1nitrobenzene and 1,2-diemthyl-3- nitrobenzene were noteworthy for causing significant particle size reduction of antisolvent precipitated RDX. Crystal size enlargement and aspect ratio elongation was most pronounced when 1,3,5-triazine-2,4-diamine impurity was present. A novel application of the Scherrer equation was employed, to study the effect of TMA inclusion on the constituent crystallites within spray dried microparticles. The investigation revealed reduced coherence length of the (002) plane and extension of the (210) plane when RDX was spray dried in the presence of TMAs.Item Open Access Multimodal Navigation for Accurate Space Rendezvous Missions(2021-05) Rondao, Duarte O De M A; Aouf, Nabil; Richardson, Mark ARelative navigation is paramount in space missions that involve rendezvousing between two spacecraft. It demands accurate and continuous estimation of the six degree-of-freedom relative pose, as this stage involves close-proximity-fast-reaction operations that can last up to five orbits. This has been routinely achieved thanks to active sensors such as lidar, but their large size, cost, power and limited operational range remain a stumbling block for en masse on-board integration. With the onset of faster processing units, lighter and cheaper passive optical sensors are emerging as the suitable alternative for autonomous rendezvous in combination with computer vision algorithms. Current vision-based solutions, however, are limited by adverse illumination conditions such as solar glare, shadowing, and eclipse. These effects are exacerbated when the target does not hold cooperative markers to accommodate the estimation process and is incapable of controlling its rotational state. This thesis explores novel model-based methods that exploit sequences of monoc ular images acquired by an on-board camera to accurately carry out spacecraft relative pose estimation for non-cooperative close-range rendezvous with a known artificial target. The proposed solutions tackle the current challenges of imaging in the visible spectrum and investigate the contribution of the long wavelength infrared (or “thermal”) band towards a combined multimodal approach. As part of the research, a visible-thermal synthetic dataset of a rendezvous approach with the defunct satellite Envisat is generated from the ground up using a realistic orbital camera simulator. From the rendered trajectories, the performance of several state-of-the-art feature detectors and descriptors is first evaluated for both modalities in a tailored scenario for short and wide baseline image processing transforms. Multiple combinations, including the pairing of algorithms with their non-native counterparts, are tested. Computational runtimes are assessed in an embedded hardware board. From the insight gained, a method to estimate the pose on the visible band is derived from minimising geometric constraints between online local point and edge contour features matched to keyframes generated offline from a 3D model of the target. The combination of both feature types is demonstrated to achieve a pose solution for a tumbling target using a sparse set of training images, bypassing the need for hardware-accelerated real-time renderings of the model. The proposed algorithm is then augmented with an extended Kalman filter which processes each feature-induced minimisation output as individual pseudo measurements, fusing them to estimate the relative pose and velocity states at each time-step. Both the minimisation and filtering are established using Lie group formalisms, allowing for the covariance of the solution computed by the former to be automatically incorporated as measurement noise in the latter, providing an automatic weighing of each feature type directly related to the quality of the matches. The predicted states are then used to search for new feature matches in the subsequent time-step. Furthermore, a method to derive a coarse viewpoint estimate to initialise the nominal algorithm is developed based on probabilistic modelling of the target’s shape. The robustness of the complete approach is demonstrated for several synthetic and laboratory test cases involving two types of target undergoing extreme illumination conditions. Lastly, an innovative deep learning-based framework is developed by processing the features extracted by a convolutional front-end with long short-term memory cells, thus proposing the first deep recurrent convolutional neural network for spacecraft pose estimation. The framework is used to compare the performance achieved by visible-only and multimodal input sequences, where the addition of the thermal band is shown to greatly improve the performance during sunlit sequences. Potential limitations of this modality are also identified, such as when the target’s thermal signature is comparable to Earth’s during eclipse.Item Open Access Non-Parametric Spatial Spectral Band Selection methods(2021-05) Torres, Ruben M; Yuen, Peter W. T.; James, DavidThis project is about the development of band selection (BS) techniques for better target detection and classification in remote sensing and hyperspectral imaging (HSI). Conventionally, this is achieved just by using the spectral features for guiding the band compression. However, this project develops a BS method which uses both spatial and spectral features to allow a handful of crucial spectral bands to be selected for enhancing the target detection and classification performances. This thesis firstly outlines the fundamental concepts and background of remote sensing and HSI, followed by the theories of different atmospheric correction algorithms — in order to assess the reflectance conversion for band selection — and BS techniques, with a detailed explanation of the Hughes principle, which postulates the fundamental drawback for having high-dimensional data in HSI. Subsequently, the thesis highlights the performances of some advanced BS techniques and to point out their deficiencies. Most of the existing BS work in the field have exhibited maximal classification accuracy when more spectral bands have been utilized for classification; this apparently disagrees with the theoretical model of the Hughes phenomenon. The thesis then presents a spatial spectral mutual information (SSMI) BS scheme which utilizes a spatial feature extraction technique as a pre-processing step, followed by the clustering of the mutual information (MI) of spectral bands for enhancing the BS efficiency. Through this BS scheme, a sharp ’bell’-shaped accuracy-dimensionality characteristic has been observed, peaking at about 20 bands. The performance of the proposed SSMI BS scheme has been validated through 6 HSI datasets, and its classification accuracy is shown to be ~10% better than 7 state-of-the-art BS algorithms. These results confirm that the high efficiency of the BS scheme is essentially important to observe, and to validate, the Hughes phenomenon at band selection through experiments for the first time.Item Open Access A novel dual-spin actuation mechanism for small calibre, spin stabilised, guided projectiles(2021) Norris, James J.; Hameed, Amer; Economou, John T.Small calibre projectiles are spin-stabilised to increase ballistic stability, often at high frequencies. Due to hardware limitations, conventional actuators and meth ods are unable to provide satisfactory control at such high frequencies. With the reduced volume for control hardware and increased financial cost, incorporating traditional guid ance methods into small-calibre projectiles is inherently difficult. This work presents a novel method of projectile control which addresses these issues and conducts a systems level analysis of the underlying actuation mechanism. The design is shown to be a viable alternative to traditional control methods, Firstly, a 7 Degree-of-Freedom (DoF) dynamic model is created for dual-spin pro jectiles, including aerodynamic coefficients. The stability of dual-spin projectiles, gov erned by the gyroscopic and dynamic stability factors is given, discussed and unified across available literature. The model is implemented in a Matlab/Simulink simulation environ ment, which is in turn validated against a range of academic literature and experimental test data. The novel design and fundamental operating principle are presented. The actuation mechanism (AM) is then mathematically formulated from both a velocity change (∆V ) and a lateral acceleration (a˜) perspective. A set of axioms are declared and verified using the 7-DoF model, showing that the inherently discrete system behaviour can be controlled continuously via these control variables, ∆V or a˜. Control state switching is simplified to be instantaneous, then expanded to be generically characterised by an arbitrarily complex mathematical function. A detailed investigation, parametric analysis and sensitivity study is undertaken to understand the system behaviour. A Monte Carlo procedure is described, which is used to compare the correction cap abilities of different guidance laws (GLs). A bespoke Zero-Effort-Miss (ZEM) based GLis synthesised from the mathematical formulation of the AM, with innately more know ledge of the system behaviour, which allows superior error correction. This bespoke GL is discussed in detail, a parametric study is undertaken, and both the GL parameters and PID controller gains are optimised using a genetic algorithm. Artificial Intelligence (AI) Reinforcement learning methods are used to emulate a GL, as well as controlling the AM and operating as a GL, simultaneously. The novel GLs are compared against a traditional proportional navigation GL in a nominal system and all GLs were able to control the AMs, reducing the miss distance to a satisfactory margin. The ZEM-based GL provided superior correction to the AI GL, which in turn provided superior correction over proportional navigation. Example CAD models are shown, and the stability analysis is conducted on the geometry. The CAD model is then used in CFD simulations to determine aerodynamic coefficients for use in the 7-DoF dynamic model. The novel control method was able to reduce the 95% dispersion diameter of a traditional ballistic 7.62mm projectile from 70mm to 33mm. Statistical data analysis showed there was no significant correlation or bias present in either the nominal or 7-DoF dispersion patterns. This project is co-sponsored by BAE Systems and ESPRC (ref. 1700064). The con tents of this thesis are covered by patent applications GB2011850.1, GB 2106035.5 and EP 20275128.5. Two papers are currently published (DOI: 10.1016/j.dt.2019.06.003, the second DOI is pending) and one is undergoing peer review..Item Open Access Supporting operational decision making concerning aircraft structural integrity damage identified during maintenance.(2021-06) Green, Richard N.; McNaught, Ken R.; Saddington, Alistair J.Military aircraft operations balance delivery pressures and engineering risks. Aircraft structural damage incurred in-service creates complex risk decision problems for managers deliberating maintenance activity such as delaying rectification to continue operations, or grounding an aircraft or entire fleet. In many operational settings, aircraft availability demands restrict the time, information, or resources to analyse structural risks, making formal risk or decision analysis intractable. Exact solutions are information intensive and require specialist knowledge or machinery beyond the capabilities of generalist engineering managers, often compelling decision-makers to use their subjective judgement in an unsupported way. For actors deliberating aircraft maintenance structural risks in such circumstances, a novel approach based upon heuristics, argument and bounded rationality is proposed, which was informed by the results from a survey of engineering practitioners and case study analyses. Testing of the approach was carried-out with 21 aircraft engineering decision-makers with experience of structural integrity risks, split into three groups, using realistic but fictional textual simulations of aircraft maintenance. One group used existing decision justification approaches and were compared with a second group who provided decision justifications using the novel approach. Users of the novel approach felt supported and were very confident in their justifications. The third group of raters comparing the two sets of decision justifications indicated preferences using Likert scales against the criteria: which is easier to understand, which is more transparent, and which gives the better justification. Analysis of the comparative results iii ABSTRACT iv using ANOVA provided evidence that the novel approach enabled better decision justification and transparency compared to existing approaches. The novel approach aids decision-makers compelled to use their unsupported subjective judgement, improving organisational resilience by improving robustness and stretching system process to handle surprises, and providing a clear record of the decision basis for post hoc reviewItem Open Access Supporting operational decision making concerning aircraft structural integrity damage identified during maintenance.(2021-06-10) Green, Richard; McNaught, Ken R.; Saddington, Alistair J.Military aircraft operations balance delivery pressures and engineering risks. Aircraft structural damage incurred in-service creates complex risk decision problems for managers deliberating maintenance activity such as delaying rectification to continue operations, or grounding an aircraft or entire fleet. In many operational settings, aircraft availability demands restrict the time, information, or resources to analyse structural risks, making formal risk or decision analysis intractable. Exact solutions are information intensive and require specialist knowledge or machinery beyond the capabilities of generalist engineering managers, often compelling decision-makers to use their subjective judgement in an unsupported way. For actors deliberating aircraft maintenance structural risks in such circumstances, a novel approach based upon heuristics, argument and bounded rationality is proposed, which was informed by the results from a survey of engineering practitioners and case study analyses. Testing of the approach was carried-out with 21 aircraft engineering decision-makers with experience of structural integrity risks, split into three groups, using realistic but fictional textual simulations of aircraft maintenance. One group used existing decision justification approaches and were compared with a second group who provided decision justifications using the novel approach. Users of the novel approach felt supported and were very confident in their justifications. The third group of raters comparing the two sets of decision justifications indicated preferences using Likert scales against the criteria: which is easier to understand, which is more transparent, and which gives the better justification. Analysis of the comparative results using ANOVA provided evidence that the novel approach enabled better decision justification and transparency compared to existing approaches. The novel approach aids decision-makers compelled to use their unsupported subjective judgement, improving organisational resilience by improving robustness and stretching system process to handle surprises, and providing a clear record of the decision basis for post hoc review.Item Metadata only Technology and conservation of Chinese painted enamels(2021-07) Norris, Dana; Shortland, A.; Braekmans, DChinese painted enamels are studied in this thesis with the goal of improving their conservation. To do this the material was studied through elemental analysis using two X-ray Fluorescence techniques and Environmental Scanning Electron Microscopy coupled with Energy Dispersive X-ray spectrometry. All three techniques used in this study are non-destructive. The analytical sample set includes 131 examples dating from the inception of the technique in the early 18th century to modern production in the 21st century. Characterisation is used in this thesis to compare the compositions of each Chinese painted enamel colour to related artistic traditions including Chinese glass, cloisonné, overglaze enamels on porcelain, Limoges painted enamels and a late 17th century German painted enamel. Research on related materials was done with the aim of identifying the technological predecessors and exchanges for each colour in the palette. The results illuminate complexity in the development of the technique, which draws heavily on both Chinese and European technology. Manufacturing techniques, construction and degradation are documented through examination of artworks in museum collections, providing insight on the technical art history of the medium and its inherent vulnerabilities. Observations on condition have been used to recognise trends in degradation and link them to specific agents of decay and innate weaknesses from manufacturing. The results show that Chinese painted enamels are particularly vulnerable to physical force which occurs during handling and inappropriate support while on display or in storage. To mitigate future damage, recommendations on environmental conditions are made regarding temperature, humidity, and light levels.Item Open Access Towards a robust slam framework for resilient AUV navigation(Cranfield University, 2021-03) Issartel, Mathieu; Chermak, Lounis P; Le Caillec, Jean-Marc; Richardson, MarrkAutonomous Underwater Vehicles (AUVs) are playing an increasing part in modern navies, to the point that the control of oceans will soon be decided by their strategic use. In face of more complex missions occurring in potentially hostile environments, the resilience of such systems becomes critical. In this study, we investigate the following scenario: how does a lone AUV could recover from a temporary breakdown that has created a gap in its measurements, while remaining beneath the surface to avoid detection? It is assumed that the AUV is equipped with an active sonar and is operating in an uncharted area. The vehicle has to rely on itself by recovering its location using a Simultaneous Localization and Mapping (SLAM) algorithm. While SLAM is widely investigated and developed in the case of aerial and terrestrial robotics, the nature of the poorly structured underwater environment dramatically challenges its effectiveness. To address such a complex problem, the usual side scan sonar data association techniques are investigated under a global registration problem while applying robust graph SLAM modelling. In particular, ways to improve the global detection of features from sonar mosaic region patches that react well to the MICR similarity measure are discussed. The main contribution of this study is centered on a novel data processing framework that is able to generate different graph topologies using robust SLAM techniques. One of its advantages is to facilitate the testing of different modelling hypotheses to tackle the data gap following the temporary breakdown and make the most of the limited available information. Several research perspectives related to this framework are discussed. Notably, the possibility to further extend the proposed framework to heterogeneous datasets and the opportunity to accelerate the recovery process by inferring information about the breakdown using machine learning.Item Open Access Transforming the Kafala in Saudi Arabia: Turning weaknesses into opportunities(2023-01) Al-Saud, Madawi A; Matthews, RonThe research sought to find out what is really going on in the modern Kafala and to create solutions for reform based on what is right for Saudi instead of being led by outside voices. The research focuses on migrant domestic workers as one of the most marginalized and vulnerable groups in Saudi, with Kafala practices that amount to modern slavery. The value of this lies in, firstly, promoting the interests of Saudi and the GCC; secondly, upholding human rights and associated principles; thirdly, contributing to an international understanding of Islam and the GCC; and fourthly, providing a culturally specific solution to reforming the Kafala. The selected research methodology consists of mainly qualitative interviews of government officials and other professionals. The research has identified cross-cutting issues that must be addressed by reforms of the Kafala, and that are borne out of the intersecting issues of slavery, Islam, and gender. These cross-cutting issues include: culture (in particular the fact that the status of women and foreigners means that their exploitation may be culturally accepted); migration (which includes the global context of migration and Saudi’s own aims in relation to the system); and access to justice (such as the problem of ensuring that legal reforms are implemented and people are able to exercise their rights).