6,301 research outputs found

    Sensors and Methods for Railway Signalling Equipment Monitoring

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    Signalling upgrade projects that have been installed in equipment rooms in the recent past have limited capability to monitor performance of certain types of external circuits. To modify the equipment rooms on the commissioned railway would prove very expensive to implement and would be unacceptable in terms of delays caused to passenger services due to re-commissioning circuits after modification, to comply with rail signalling standards. The use of magnetoresistive sensors to provide performance data on point circuit operation and point operation is investigated. The sensors are bench tested on their ability to measure current in a circuit in a non-intrusive manner. The effect of shielding on the sensor performance is tested and found to be significant. The response of the sensors with various levels of amplification produces linear responses across a range of circuit gain. The output of the sensor circuit is demonstrated for various periods of interruption of conductor current. A three-axis accelerometer is mounted on a linear actuator to demonstrate the type of output expected from similar sensors mounted on a set of points. Measurements of current in point detection circuits and acceleration forces resulting from vibration of out of tolerance mechanical assemblies can provide valuable information on performance and possible threats to safe operation of equipment. The sensors seem capable of measuring the current in a conductor with a comparatively high degree of sensitivity. There is development work required on shielding the sensor from magnetic fields other than those being measured. The accelerometer work is at a demonstration level and requires development. The future testing work with accelerometers should be at a facility where multiple point moves can be made; with the capability to introduce faults to the point mechanisms. Methods can then be developed for analysis of the vibration signatures produced by the various faults

    Industry 4.0: product digital twins for remanufacturing decision-making

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    Currently there is a desire to reduce natural resource consumption and expand circular business principles whilst Industry 4.0 (I4.0) is regarded as the evolutionary and potentially disruptive movement of technology, automation, digitalisation, and data manipulation into the industrial sector. The remanufacturing industry is recognised as being vital to the circular economy (CE) as it extends the in-use life of products, but its synergy with I4.0 has had little attention thus far. This thesis documents the first investigating into I4.0 in remanufacturing for a CE contributing a design and demonstration of a model that optimises remanufacturing planning using data from different instances in a product’s life cycle. The initial aim of this work was to identify the I4.0 technology that would enhance the stability in remanufacturing with a view to reducing resource consumption. As the project progressed it narrowed to focus on the development of a product digital twin (DT) model to support data-driven decision making for operations planning. The model’s architecture was derived using a bottom-up approach where requirements were extracted from the identified complications in production planning and control that differentiate remanufacturing from manufacturing. Simultaneously, the benefits of enabling visibility of an asset’s through-life health were obtained using a DT as the modus operandi. A product simulator and DT prototype was designed to use Internet of Things (IoT) components, a neural network for remaining life estimations and a search algorithm for operational planning optimisation. The DT was iteratively developed using case studies to validate and examine the real opportunities that exist in deploying a business model that harnesses, and commodifies, early life product data for end-of-life processing optimisation. Findings suggest that using intelligent programming networks and algorithms, a DT can enhance decision-making if it has visibility of the product and access to reliable remanufacturing process information, whilst existing IoT components provide rudimentary “smart” capabilities, but their integration is complex, and the durability of the systems over extended product life cycles needs to be further explored

    Study of myocardial pathological fibrosis using protein-protein-directed nanomaterials as theracnostic tool and targeted gene expressin system

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    RESUMEN La tesis aquí escrita pretende abordar el estudio de la fibrosis cardiaca patológica, con el objetivo de esclarecer y contribuir al desarrollo de nuevas aproximaciones a su tratamiento. Los medios para alcanzar estos objetivos se basan en la utilización de nanomateriales dirigidos por proteínas como herramienta teragnóstica, así como la implementación de un sistema de expresión genética dirigido. Como rasgo distintivo de este estudio, se establecerá un sistema de investigación traslacional, mediante la utilización y evolución de los sistemas utilizados en el trabajo, con el claro objetivo final, de que el trabajo aquí presentado pueda ser utilizado para futuras investigaciones.ABSTRACT This thesis aims to address the study of pathological cardiac fibrosis, with the objective of clarifying and contributing to the development of new approaches to its treatment. The means to achieve these objectives are based on the use of protein targeted nanomaterials as a theragnostic tool, as well as the implementation of a targeted gene expression system. As a distinctive feature of this study, a translational research system will be established through the use and evolution of the systems used in the work, with the clear final objective that the work presented here can be used for future research

    FPGA acceleration of DNA sequence alignment: design analysis and optimization

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    Existing FPGA accelerators for short read mapping often fail to utilize the complete biological information in sequencing data for simple hardware design, leading to missed or incorrect alignment. In this work, we propose a runtime reconfigurable alignment pipeline that considers all information in sequencing data for the biologically accurate acceleration of short read mapping. We focus our efforts on accelerating two string matching techniques: FM-index and the Smith-Waterman algorithm with the affine-gap model which are commonly used in short read mapping. We further optimize the FPGA hardware using a design analyzer and merger to improve alignment performance. The contributions of this work are as follows. 1. We accelerate the exact-match and mismatch alignment by leveraging the FM-index technique. We optimize memory access by compressing the data structure and interleaving the access with multiple short reads. The FM-index hardware also considers complete information in the read data to maximize accuracy. 2. We propose a seed-and-extend model to accelerate alignment with indels. The FM-index hardware is extended to support the seeding stage while a Smith-Waterman implementation with the affine-gap model is developed on FPGA for the extension stage. This model can improve the efficiency of indel alignment with comparable accuracy versus state-of-the-art software. 3. We present an approach for merging multiple FPGA designs into a single hardware design, so that multiple place-and-route tasks can be replaced by a single task to speed up functional evaluation of designs. We first experiment with this approach to demonstrate its feasibility for different designs. Then we apply this approach to optimize one of the proposed FPGA aligners for better alignment performance.Open Acces

    3D printed Microneedles for Transdermal Drug Delivery

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    3D printing is a revolutionary manufacturing and prototyping technology that has altered the outlooks of numerous industrial and scientific fields since its introduction. Recently, it has attracted attention for its potential as a manufacturing tool for transdermal microneedles for drug delivery. In the present thesis, the 3D printability of solid and hollow microneedles via photopolymerisation-based 3D printing was investigated, aiming at establishing robust manufacturing strategies for reproducible, mechanically strong and versatile microneedles. The developed microneedles were employed as drug delivery systems for the treatment of diabetes via insulin administration. Solid microneedles featuring different geometries were designed and 3D printed. It was demonstrated that the printing and post-printing parameters affected the printed quality, a finding that was employed to optimise the manufacturing strategy. Microneedle geometry was also found to have an impact on the piercing and fracture behaviour; however all microneedle designs were found to be mechanically safe upon application. The solid microneedles were subsequently coated with insulin-polymer films, using a 2D inkjet printing technology. The coating process achieved spatial control of the drug deposition, with quantitative accuracy. The microneedle geometry was shown to influence the morphology of the coating film, an effect that was pronounced during in the in vitro delivery studies of insulin to porcine skin. Furthermore, hollow microneedles were designed and 3D printed, featuring different heights. Two photopolymerisation-based technologies were studied, and their performance was compared. The key influential parameters of the printing outcome and microneedle quality were identified to be the printing angle and the size of the microneedle opening. The hollow microneedles were found to be effective in piercing porcine skin without structural damaging. The hollow microneedles were incorporated into complex patches with internal microfluidic structures for the provision and distribution of drug-containing solutions. The developed complex hollow microneedle patches were coupled with a microelectromechanical system to create a novel platform device for controlled, personalised transdermal drug delivery. Advanced imaging techniques revealed that the device achieved distribution of the liquid within porcine skin tissue without the creation of depots that would delay absorption. The device was evaluated for its efficacy to transdermally deliver a model dye and insulin in vitro. In vivo trials were also conducted using diabetic rodents, with the device achieving faster onset of insulin action and sustained glycemic control, in comparison to subcutaneous injections. Overall, the findings of the present research are anticipated to elucidate key problematic areas associated with the application of 3D printing for microneedle manufacturing and propose feasible solutions. The outermost goal of this work is to contribute to the advancement of knowledge in the field of 3D printed transdermal drug delivery systems, in order to bring them one step closer to their adoption in the clinical setting

    A Genealogy of Consumer Surveillance: From the First Public Market to Eatons Department Store to Amazon

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    Consumer surveillance has intensified over time and across differing forms of consumption space and spatial arrangement, which in turn raises the question of what explains the historical changes in the modalities of consumer surveillance. Contemporary surveillance literatures focus primarily on the current phenomenon with little consideration of the historical processes upon which the changes in the scope and intensity of the modalities of consumer surveillance were made possible. My study employs Foucauldian genealogical methodology as a system of inquiry to map the historical transformation in the modalities of consumer surveillance, by utilizing archival records, across three different consumption spaces in key stages of retail development: the first regulatory public market in the Town of York during the pre-industrial period, Eatons department store in the industrial economy, and Amazon that coincided with the rise of information economy. Conversely, contemporary theories of surveillance generally approach the intensification question by focusing on the surveillance-space axis or surveillance-consumption axis, and the spatiality of consumer surveillance is reduced to Foucauldian disciplinary panopticon. Utilizing Foucaults theories of power and governmentality and his intriguing account of the role of space in the exercise of power, my genealogical project examines the intersection of surveillance-space-consumption to understand the intensification of consumer surveillance over time across the three spaces under study. In my genealogical project, I identify five key moments pertaining to differing modalities of consumer surveillance: marketization of space, standardization of consuming bodies, statistification of consumers, virtualization of consumption, and AI inhabitation in consumer spaces. My genealogical project demonstrates that spatiality and spatialization are a recurring issue in differing modalities of consumer surveillance over time. Yet, the spatial techniques have changed and become more complex to augment the scope and intensity of monitoring and gaining of new knowledge about consumers and consumption, as part of long-standing efforts to manage the unpredictable dynamics of consumer behaviour by attaining control over all aspects of consumers life

    Secure Smart Wearable Computing through Artificial Intelligence-Enabled Internet of Things and Cyber-Physical Systems for Health Monitoring

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    The functionality of the Internet is continually changing from the Internet of Computers (IoC) to the “Internet of Things (IoT)”. Most connected systems, called Cyber-Physical Systems (CPS), are formed from the integration of numerous features such as humans and the physical environment, smart objects, and embedded devices and infrastructure. There are a few critical problems, such as security risks and ethical issues that could affect the IoT and CPS. When every piece of data and device is connected and obtainable on the network, hackers can obtain it and utilise it for different scams. In medical healthcare IoT-CPS, everyday medical and physical data of a patient may be gathered through wearable sensors. This paper proposes an AI-enabled IoT-CPS which doctors can utilise to discover diseases in patients based on AI. AI was created to find a few disorders such as Diabetes, Heart disease and Gait disturbances. Each disease has various symptoms among patients or elderly. Dataset is retrieved from the Kaggle repository to execute AI-enabled IoT-CPS technology. For the classification, AI-enabled IoT-CPS Algorithm is used to discover diseases. The experimental results demonstrate that compared with existing algorithms, the proposed AI-enabled IoT-CPS algorithm detects patient diseases and fall events in elderly more efficiently in terms of Accuracy, Precision, Recall and F-measure

    The Evolution of Smart Buildings: An Industrial Perspective of the Development of Smart Buildings in the 2010s

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    Over the course of the 2010s, specialist research bodies have failed to provide a holistic view of the changes in the prominent reason (as driven by industry) for creating a smart building. Over the 2010s, research tended to focus on remaining deeply involved in only single issues or value drivers. Through an analysis of the author’s peer reviewed and published works (book chapters, articles, essays and podcasts), supplemented with additional contextual academic literature, a model for how the key drivers for creating a smart building have evolved in industry during the 2010s is presented. The critical research commentary within this thesis, tracks the incremental advances of technology and their application to the built environment via academic movements, industrial shifts, or the author’s personal contributions. This thesis has found that it is demonstrable, through the chronology and publication dates of the included research papers, that as the financial cost and complexity of sensors and cloud computing reduced, smart buildings became increasingly prevalent. Initially, sustainability was the primary focus with the use of HVAC analytics and advanced metering in the early 2010s. The middle of the decade saw an economic transformation of the commercial office sector and the driver for creating a smart building was concerned with delivering flexible yet quantifiably used space. Driven by society’s emphasis on health, wellbeing and productivity, smart buildings pivoted their focus towards the end of the 2010s. Smart building technologies were required to demonstrate the impacts of architecture on the human. This research has evidenced that smart buildings use data to improve performance in sustainability, in space usage or for humancentric outcomes
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