2,388 research outputs found

    Computational and experimental studies on the reaction mechanism of bio-oil components with additives for increased stability and fuel quality

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    As one of the world’s largest palm oil producers, Malaysia encountered a major disposal problem as vast amount of oil palm biomass wastes are produced. To overcome this problem, these biomass wastes can be liquefied into biofuel with fast pyrolysis technology. However, further upgradation of fast pyrolysis bio-oil via direct solvent addition was required to overcome it’s undesirable attributes. In addition, the high production cost of biofuels often hinders its commercialisation. Thus, the designed solvent-oil blend needs to achieve both fuel functionality and economic targets to be competitive with the conventional diesel fuel. In this thesis, a multi-stage computer-aided molecular design (CAMD) framework was employed for bio-oil solvent design. In the design problem, molecular signature descriptors were applied to accommodate different classes of property prediction models. However, the complexity of the CAMD problem increases as the height of signature increases due to the combinatorial nature of higher order signature. Thus, a consistency rule was developed reduce the size of the CAMD problem. The CAMD problem was then further extended to address the economic aspects via fuzzy multi-objective optimisation approach. Next, a rough-set based machine learning (RSML) model has been proposed to correlate the feedstock characterisation and pyrolysis condition with the pyrolysis bio-oil properties by generating decision rules. The generated decision rules were analysed from a scientific standpoint to identify the underlying patterns, while ensuring the rules were logical. The decision rules generated can be used to select optimal feedstock composition and pyrolysis condition to produce pyrolysis bio-oil of targeted fuel properties. Next, the results obtained from the computational approaches were verified through experimental study. The generated pyrolysis bio-oils were blended with the identified solvents at various mixing ratio. In addition, emulsification of the solvent-oil blend in diesel was also conducted with the help of surfactants. Lastly, potential extensions and prospective work for this study have been discuss in the later part of this thesis. To conclude, this thesis presented the combination of computational and experimental approaches in upgrading the fuel properties of pyrolysis bio-oil. As a result, high quality biofuel can be generated as a cleaner burning replacement for conventional diesel fuel

    LIPIcs, Volume 251, ITCS 2023, Complete Volume

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    LIPIcs, Volume 251, ITCS 2023, Complete Volum

    The 2023 wearable photoplethysmography roadmap

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    Photoplethysmography is a key sensing technology which is used in wearable devices such as smartwatches and fitness trackers. Currently, photoplethysmography sensors are used to monitor physiological parameters including heart rate and heart rhythm, and to track activities like sleep and exercise. Yet, wearable photoplethysmography has potential to provide much more information on health and wellbeing, which could inform clinical decision making. This Roadmap outlines directions for research and development to realise the full potential of wearable photoplethysmography. Experts discuss key topics within the areas of sensor design, signal processing, clinical applications, and research directions. Their perspectives provide valuable guidance to researchers developing wearable photoplethysmography technology

    Towards A Practical High-Assurance Systems Programming Language

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    Writing correct and performant low-level systems code is a notoriously demanding job, even for experienced developers. To make the matter worse, formally reasoning about their correctness properties introduces yet another level of complexity to the task. It requires considerable expertise in both systems programming and formal verification. The development can be extremely costly due to the sheer complexity of the systems and the nuances in them, if not assisted with appropriate tools that provide abstraction and automation. Cogent is designed to alleviate the burden on developers when writing and verifying systems code. It is a high-level functional language with a certifying compiler, which automatically proves the correctness of the compiled code and also provides a purely functional abstraction of the low-level program to the developer. Equational reasoning techniques can then be used to prove functional correctness properties of the program on top of this abstract semantics, which is notably less laborious than directly verifying the C code. To make Cogent a more approachable and effective tool for developing real-world systems, we further strengthen the framework by extending the core language and its ecosystem. Specifically, we enrich the language to allow users to control the memory representation of algebraic data types, while retaining the automatic proof with a data layout refinement calculus. We repurpose existing tools in a novel way and develop an intuitive foreign function interface, which provides users a seamless experience when using Cogent in conjunction with native C. We augment the Cogent ecosystem with a property-based testing framework, which helps developers better understand the impact formal verification has on their programs and enables a progressive approach to producing high-assurance systems. Finally we explore refinement type systems, which we plan to incorporate into Cogent for more expressiveness and better integration of systems programmers with the verification process

    Contributions to improve the technologies supporting unmanned aircraft operations

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    Mención Internacional en el título de doctorUnmanned Aerial Vehicles (UAVs), in their smaller versions known as drones, are becoming increasingly important in today's societies. The systems that make them up present a multitude of challenges, of which error can be considered the common denominator. The perception of the environment is measured by sensors that have errors, the models that interpret the information and/or define behaviors are approximations of the world and therefore also have errors. Explaining error allows extending the limits of deterministic models to address real-world problems. The performance of the technologies embedded in drones depends on our ability to understand, model, and control the error of the systems that integrate them, as well as new technologies that may emerge. Flight controllers integrate various subsystems that are generally dependent on other systems. One example is the guidance systems. These systems provide the engine's propulsion controller with the necessary information to accomplish a desired mission. For this purpose, the flight controller is made up of a control law for the guidance system that reacts to the information perceived by the perception and navigation systems. The error of any of the subsystems propagates through the ecosystem of the controller, so the study of each of them is essential. On the other hand, among the strategies for error control are state-space estimators, where the Kalman filter has been a great ally of engineers since its appearance in the 1960s. Kalman filters are at the heart of information fusion systems, minimizing the error covariance of the system and allowing the measured states to be filtered and estimated in the absence of observations. State Space Models (SSM) are developed based on a set of hypotheses for modeling the world. Among the assumptions are that the models of the world must be linear, Markovian, and that the error of their models must be Gaussian. In general, systems are not linear, so linearization are performed on models that are already approximations of the world. In other cases, the noise to be controlled is not Gaussian, but it is approximated to that distribution in order to be able to deal with it. On the other hand, many systems are not Markovian, i.e., their states do not depend only on the previous state, but there are other dependencies that state space models cannot handle. This thesis deals a collection of studies in which error is formulated and reduced. First, the error in a computer vision-based precision landing system is studied, then estimation and filtering problems from the deep learning approach are addressed. Finally, classification concepts with deep learning over trajectories are studied. The first case of the collection xviiistudies the consequences of error propagation in a machine vision-based precision landing system. This paper proposes a set of strategies to reduce the impact on the guidance system, and ultimately reduce the error. The next two studies approach the estimation and filtering problem from the deep learning approach, where error is a function to be minimized by learning. The last case of the collection deals with a trajectory classification problem with real data. This work completes the two main fields in deep learning, regression and classification, where the error is considered as a probability function of class membership.Los vehículos aéreos no tripulados (UAV) en sus versiones de pequeño tamaño conocidos como drones, van tomando protagonismo en las sociedades actuales. Los sistemas que los componen presentan multitud de retos entre los cuales el error se puede considerar como el denominador común. La percepción del entorno se mide mediante sensores que tienen error, los modelos que interpretan la información y/o definen comportamientos son aproximaciones del mundo y por consiguiente también presentan error. Explicar el error permite extender los límites de los modelos deterministas para abordar problemas del mundo real. El rendimiento de las tecnologías embarcadas en los drones, dependen de nuestra capacidad de comprender, modelar y controlar el error de los sistemas que los integran, así como de las nuevas tecnologías que puedan surgir. Los controladores de vuelo integran diferentes subsistemas los cuales generalmente son dependientes de otros sistemas. Un caso de esta situación son los sistemas de guiado. Estos sistemas son los encargados de proporcionar al controlador de los motores información necesaria para cumplir con una misión deseada. Para ello se componen de una ley de control de guiado que reacciona a la información percibida por los sistemas de percepción y navegación. El error de cualquiera de estos sistemas se propaga por el ecosistema del controlador siendo vital su estudio. Por otro lado, entre las estrategias para abordar el control del error se encuentran los estimadores en espacios de estados, donde el filtro de Kalman desde su aparición en los años 60, ha sido y continúa siendo un gran aliado para los ingenieros. Los filtros de Kalman son el corazón de los sistemas de fusión de información, los cuales minimizan la covarianza del error del sistema, permitiendo filtrar los estados medidos y estimarlos cuando no se tienen observaciones. Los modelos de espacios de estados se desarrollan en base a un conjunto de hipótesis para modelar el mundo. Entre las hipótesis se encuentra que los modelos del mundo han de ser lineales, markovianos y que el error de sus modelos ha de ser gaussiano. Generalmente los sistemas no son lineales por lo que se realizan linealizaciones sobre modelos que a su vez ya son aproximaciones del mundo. En otros casos el ruido que se desea controlar no es gaussiano, pero se aproxima a esta distribución para poder abordarlo. Por otro lado, multitud de sistemas no son markovianos, es decir, sus estados no solo dependen del estado anterior, sino que existen otras dependencias que los modelos de espacio de estados no son capaces de abordar. Esta tesis aborda un compendio de estudios sobre los que se formula y reduce el error. En primer lugar, se estudia el error en un sistema de aterrizaje de precisión basado en visión por computador. Después se plantean problemas de estimación y filtrado desde la aproximación del aprendizaje profundo. Por último, se estudian los conceptos de clasificación con aprendizaje profundo sobre trayectorias. El primer caso del compendio estudia las consecuencias de la propagación del error de un sistema de aterrizaje de precisión basado en visión artificial. En este trabajo se propone un conjunto de estrategias para reducir el impacto sobre el sistema de guiado, y en última instancia reducir el error. Los siguientes dos estudios abordan el problema de estimación y filtrado desde la perspectiva del aprendizaje profundo, donde el error es una función que minimizar mediante aprendizaje. El último caso del compendio aborda un problema de clasificación de trayectorias con datos reales. Con este trabajo se completan los dos campos principales en aprendizaje profundo, regresión y clasificación, donde se plantea el error como una función de probabilidad de pertenencia a una clase.I would like to thank the Ministry of Science and Innovation for granting me the funding with reference PRE2018-086793, associated to the project TEC2017-88048-C2-2-R, which provide me the opportunity to carry out all my PhD. activities, including completing an international research internship.Programa de Doctorado en Ciencia y Tecnología Informática por la Universidad Carlos III de MadridPresidente: Antonio Berlanga de Jesús.- Secretario: Daniel Arias Medina.- Vocal: Alejandro Martínez Cav

    Integrating ecosystem–based management and marine spatial planning for sustainable ocean governance in the Bay of Bengal

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    In the contemporary world, oceans are increasingly realized as ‘threatened places’ in need of environmental protection, at risk from pollution, habitat loss, and overfishing. On the other hand, nations around the world are turning their attention to oceans as a new source of economic development and growth, seeing them as ‘industrialized spaces’. The concept of integrating Ecosystem-Based Management (EBM) and Marine Spatial Planning (MSP) is a new approach for sustainable Ocean Governance (SOG). As an effective strategic tool for planning and managing conflicting ocean uses and their interactions with marine ecosystems, the EBM-MSP approach creates an opportunity for long-term development in relation to ocean and its resources. This thesis scrutinizes the contemporary concepts, definitions, and approaches pertinent to the establishment of a comprehensive Ecosystem-based Management and Marine Spatial Planning (EBM-MSP) framework for Sustainable Ocean Governance that reflects global and regional standards. The study also analyses various scientific data – especially the pollutants’ concentration at spatial and temporal scales – with special reference to EBM-MSP. The research analyses international laws, declarations, conventions, and agreements that are relevant to the proposition of a new dynamic approach to SOG based on EBM-MSP. This new approach could be useful to support necessary reforms, filling gaps in legal regimes and achieving integrated and effective ocean governance mechanisms to prevent, reduce, and control pollution in the marine environment, as well as promoting sustainable exploration of marine resources. Specifically, the research critically analyses the existing legal frameworks in relation to SOG in the Bay of Bengal (BOB). Based on an analysis of sectoral legislation and institutional arrangements in the BOB, the thesis recommends the modification and adoption of legislation, as well as integration among the relevant departments of Bangladesh Government, to match transboundary SOG, particularly along with EBM-MSP development processes. The study focuses on national policies and strategies along with sectoral legislation and institutional arrangements to contribute towards EBM-MSP at national level for SOG, by considering socioeconomic balance and jurisdictional overlays. Based on experiences in the Baltic Sea, Mediterranean Sea, and Great Barrier Reef Marine Park (GBRMP), the research determines numerous key features to assist with the generation and application of EBM-MSP in the BOB region, specifically in Bangladesh, by integrating EBM-MSP with particular reference to a Comprehensive Ocean Zoning (COZ). The substantial outcome of the study is to suggest a COZ Framework for Bangladesh to protect priority seascapes and sites, species of special concern, and their critical habitats, by designing Marine Protected Area networks throughout the transboundary coast

    Computer Vision and Architectural History at Eye Level:Mixed Methods for Linking Research in the Humanities and in Information Technology

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    Information on the history of architecture is embedded in our daily surroundings, in vernacular and heritage buildings and in physical objects, photographs and plans. Historians study these tangible and intangible artefacts and the communities that built and used them. Thus valuableinsights are gained into the past and the present as they also provide a foundation for designing the future. Given that our understanding of the past is limited by the inadequate availability of data, the article demonstrates that advanced computer tools can help gain more and well-linked data from the past. Computer vision can make a decisive contribution to the identification of image content in historical photographs. This application is particularly interesting for architectural history, where visual sources play an essential role in understanding the built environment of the past, yet lack of reliable metadata often hinders the use of materials. The automated recognition contributes to making a variety of image sources usable forresearch.<br/

    Flexible Long-Term Secure Archiving

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    Privacy and data protection have always been basic human needs in any society that makes use of written language. From simple personal correspondence over military communication to trade secrets or medical information, confidentiality has been of utmost importance. The implications of a leak of such sensitive information may prove devastating, as the previous examples illustrate perfectly. Furthermore reliability, that is, integrity and authenticitiy of information, is critical with risks reaching from annoying to lethal as can again be seen in the previous examples. This need for data protection has carried over from the analogue to the digital age seamlessly with the amount of data being generated, transmitted and stored increasing steadily and containing more and more personal details. And in regard of the developments in computational technology that recent years have seen, such as the ongoing improvements with respect to quantum computing as well as cryptoanalytical advances, the capabilities of attackers on the security of private information have never been more distinct. Thus the need for privacy and data protection has rarely been more dire

    Design and optimisation of solar sail orbits in proximity of asteroids

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    A solar sail is a large reflective membrane which is capable of producing thrust for a spacecraft by the reflection of sunlight. Such a propellant-less propulsion system can offer solutions to high-energy missions which would be impossible for conventional propulsion systems. As a result, this technology has been proposed by many authors as the ideal candidate for a multiple asteroid rendezvous mission. At the time of writing, there are more than 30,000 known near-Earth asteroids (NEAs) alone. Adding to this those contained in the main belt and elsewhere in the solar system, the abundance of these small rocky worlds becomes apparent. Focusing only on the NEAs, there are many reasons for interest in missions to these bodies. In the first instance, they represent the earliest building blocks of the rocky worlds of the solar system, and are often still in pristine condition, similar to how they would have been since these earliest moments. As such, there is massive scientific interest in visiting and extracting samples of their constituent materials. There is another community which is also interested in the extraction of these materials: the future asteroid miners. This mining could provide propellant for deep space missions, materials for in-space infrastructure and potentially also in the return of minerals which are rare on Earth, and so of great value. However, although these bodies provide many opportunities, they are not without threat. Although the frequency of impacts of large bodies capable of causing considerable damage to Earth-based infrastructure is relatively low, there are still recent examples of just such events. With the potential for large scale loss of life due to an asteroid impacting populated areas, the science of planetary defence requires greater knowledge of the make-up of these bodies. Yet another reason for mission designers to examine further options in achieving efficient missions to these bodies. It would be beneficial, in terms of cost, for a single spacecraft to be able to carry out a mission to multiple asteroids. Such a high-energy mission is ideally suited to the solar sail. Although the literature has provided many works on orbital transfers to multiple bodies, the operation of the sail when in proximity of the asteroid has not received quite as much attention. It is in this phase of the mission, where the science objectives would be carried out, that this thesis focuses. There are numerous challenges which the sail faces in the near-asteroid environment. These include the irregular gravity field, the strength of the acceleration provided by the sail in a relatively weak gravitational field, the often fast rotational velocities of the asteroid and higher demands on slew rates for the sail due to the shorter period of low-altitude orbits. The work will consider three main proximity phases. The first operation is in the control of an orbit using the solar sail in an irregular gravity field. In this operation, the sail must counter the perturbative effects of a non-spherical body. This manifests in the rotation of the orbit node line, referred to as nodal regression. A new tool, referred to as the Control Transition Matrix (CTM), which aids in forcing a periodic orbit solution over multiple orbits is then presented. The second operation deals with the control of a sail at the point of and subsequent to the deployment of a lander and during the deployment of a series of small ChipSat probes. The landing conditions for deployments from various locations around the asteroid are analysed before the deployment is presented from a low-asteroid orbit. The control of the sail along a nominal orbit while the lander is still on-board is presented before the sail control subsequent to the lander deployment is considered. Given the high velocity impacts for a ballistic lander deployed at large distances from the surface, an alternative mission scenario of the deployment of small ChipSat probes is presented. These probes are envisaged to carry out their science goals during the descent and so the landing conditions are less important. The final operation is in the gravitational capture of the sail around the asteroid. This work provides a preliminary analysis of the capability of the sail in achieving this by using a simple on/off control law. Following this, a more detailed two-phase approach is presented. In the first “initial capture” phase, the sail uses the value of Jacobi constant in the 3 body system as a guide to reduce the orbit radius to within a defined region. After this, the “orbit shaping” phase aims to circularise the orbit at this radius. Subsequently, preliminary investigations into an optimal approach are presented. In controlling the effects due to the non-spherical asteroid shape, an optimally controlled solution, where a minimum effort control law is sought, is presented. Following this, a novel method of updating a control law was successfully applied to force a periodic orbit. In the work carried out on lander deployment, it was found that the sail was capable of maintaining a periodic orbit after the point of lander separation by application of time-delay feedback control. For the deployment of a series of small probes, it was found that maintaining a fixed attitude for the sail during the deployment was not considerably different in station-keeping performance compared with LQR control, and performed this with no effort required of the sail. Finally, in the work on capture, the two-phase approach provided successful capture trajectories down to the desired orbit radius. The work showed that, for reducing size of asteroid, there was a reduction in the time to capture. This is due to the fact that the same size of sail is used in the weakening gravity field of each asteroid. This makes the sail relatively more powerful and so able to affect quicker capture. It was also seen that long period capture trajectories are compounded by the need for the sail to spend periods of time waiting for the position of the Sun relative to the orbit to be in such a way as to permit the capture operations to proceed. There was also the successful demonstration of an optimally controlled capture which minimised the orbit semi-parameter over one orbit revolution. The work contained in this thesis provides preliminary analysis for the consideration of future solar sail mission designers in the proximity operations of a sail near an asteroid. The findings presented here have shown that the sail can be of considerable utility in these proximity operations. They also present challenges to the mission designer given the continuous thrust that they may provide. Where a powerful sail may benefit the interplanetary phase of a mission in reaching many more asteroids further from the Earth, this can also present a challenge in the relatively weak asteroid gravitational field. However, these challenges are not insurmountable and so the sail remains a promising option for these high-energy missions
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