7,446 research outputs found

    Towards Autonomous Selective Harvesting: A Review of Robot Perception, Robot Design, Motion Planning and Control

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    This paper provides an overview of the current state-of-the-art in selective harvesting robots (SHRs) and their potential for addressing the challenges of global food production. SHRs have the potential to increase productivity, reduce labour costs, and minimise food waste by selectively harvesting only ripe fruits and vegetables. The paper discusses the main components of SHRs, including perception, grasping, cutting, motion planning, and control. It also highlights the challenges in developing SHR technologies, particularly in the areas of robot design, motion planning and control. The paper also discusses the potential benefits of integrating AI and soft robots and data-driven methods to enhance the performance and robustness of SHR systems. Finally, the paper identifies several open research questions in the field and highlights the need for further research and development efforts to advance SHR technologies to meet the challenges of global food production. Overall, this paper provides a starting point for researchers and practitioners interested in developing SHRs and highlights the need for more research in this field.Comment: Preprint: to be appeared in Journal of Field Robotic

    In-situ crack and keyhole pore detection in laser directed energy deposition through acoustic signal and deep learning

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    Cracks and keyhole pores are detrimental defects in alloys produced by laser directed energy deposition (LDED). Laser-material interaction sound may hold information about underlying complex physical events such as crack propagation and pores formation. However, due to the noisy environment and intricate signal content, acoustic-based monitoring in LDED has received little attention. This paper proposes a novel acoustic-based in-situ defect detection strategy in LDED. The key contribution of this study is to develop an in-situ acoustic signal denoising, feature extraction, and sound classification pipeline that incorporates convolutional neural networks (CNN) for online defect prediction. Microscope images are used to identify locations of the cracks and keyhole pores within a part. The defect locations are spatiotemporally registered with acoustic signal. Various acoustic features corresponding to defect-free regions, cracks, and keyhole pores are extracted and analysed in time-domain, frequency-domain, and time-frequency representations. The CNN model is trained to predict defect occurrences using the Mel-Frequency Cepstral Coefficients (MFCCs) of the lasermaterial interaction sound. The CNN model is compared to various classic machine learning models trained on the denoised acoustic dataset and raw acoustic dataset. The validation results shows that the CNN model trained on the denoised dataset outperforms others with the highest overall accuracy (89%), keyhole pore prediction accuracy (93%), and AUC-ROC score (98%). Furthermore, the trained CNN model can be deployed into an in-house developed software platform for online quality monitoring. The proposed strategy is the first study to use acoustic signals with deep learning for insitu defect detection in LDED process.Comment: 36 Pages, 16 Figures, accepted at journal Additive Manufacturin

    Predictive Maintenance of Critical Equipment for Floating Liquefied Natural Gas Liquefaction Process

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    Predictive Maintenance of Critical Equipment for Liquefied Natural Gas Liquefaction Process Meeting global energy demand is a massive challenge, especially with the quest of more affinity towards sustainable and cleaner energy. Natural gas is viewed as a bridge fuel to a renewable energy. LNG as a processed form of natural gas is the fastest growing and cleanest form of fossil fuel. Recently, the unprecedented increased in LNG demand, pushes its exploration and processing into offshore as Floating LNG (FLNG). The offshore topsides gas processes and liquefaction has been identified as one of the great challenges of FLNG. Maintaining topside liquefaction process asset such as gas turbine is critical to profitability and reliability, availability of the process facilities. With the setbacks of widely used reactive and preventive time-based maintenances approaches, to meet the optimal reliability and availability requirements of oil and gas operators, this thesis presents a framework driven by AI-based learning approaches for predictive maintenance. The framework is aimed at leveraging the value of condition-based maintenance to minimises the failures and downtimes of critical FLNG equipment (Aeroderivative gas turbine). In this study, gas turbine thermodynamics were introduced, as well as some factors affecting gas turbine modelling. Some important considerations whilst modelling gas turbine system such as modelling objectives, modelling methods, as well as approaches in modelling gas turbines were investigated. These give basis and mathematical background to develop a gas turbine simulated model. The behaviour of simple cycle HDGT was simulated using thermodynamic laws and operational data based on Rowen model. Simulink model is created using experimental data based on Rowen’s model, which is aimed at exploring transient behaviour of an industrial gas turbine. The results show the capability of Simulink model in capture nonlinear dynamics of the gas turbine system, although constraint to be applied for further condition monitoring studies, due to lack of some suitable relevant correlated features required by the model. AI-based models were found to perform well in predicting gas turbines failures. These capabilities were investigated by this thesis and validated using an experimental data obtained from gas turbine engine facility. The dynamic behaviours gas turbines changes when exposed to different varieties of fuel. A diagnostics-based AI models were developed to diagnose different gas turbine engine’s failures associated with exposure to various types of fuels. The capabilities of Principal Component Analysis (PCA) technique have been harnessed to reduce the dimensionality of the dataset and extract good features for the diagnostics model development. Signal processing-based (time-domain, frequency domain, time-frequency domain) techniques have also been used as feature extraction tools, and significantly added more correlations to the dataset and influences the prediction results obtained. Signal processing played a vital role in extracting good features for the diagnostic models when compared PCA. The overall results obtained from both PCA, and signal processing-based models demonstrated the capabilities of neural network-based models in predicting gas turbine’s failures. Further, deep learning-based LSTM model have been developed, which extract features from the time series dataset directly, and hence does not require any feature extraction tool. The LSTM model achieved the highest performance and prediction accuracy, compared to both PCA-based and signal processing-based the models. In summary, it is concluded from this thesis that despite some challenges related to gas turbines Simulink Model for not being integrated fully for gas turbine condition monitoring studies, yet data-driven models have proven strong potentials and excellent performances on gas turbine’s CBM diagnostics. The models developed in this thesis can be used for design and manufacturing purposes on gas turbines applied to FLNG, especially on condition monitoring and fault detection of gas turbines. The result obtained would provide valuable understanding and helpful guidance for researchers and practitioners to implement robust predictive maintenance models that will enhance the reliability and availability of FLNG critical equipment.Petroleum Technology Development Funds (PTDF) Nigeri

    Cost-effective non-destructive testing of biomedical components fabricated using additive manufacturing

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    Biocompatible titanium-alloys can be used to fabricate patient-specific medical components using additive manufacturing (AM). These novel components have the potential to improve clinical outcomes in various medical scenarios. However, AM introduces stability and repeatability concerns, which are potential roadblocks for its widespread use in the medical sector. Micro-CT imaging for non-destructive testing (NDT) is an effective solution for post-manufacturing quality control of these components. Unfortunately, current micro-CT NDT scanners require expensive infrastructure and hardware, which translates into prohibitively expensive routine NDT. Furthermore, the limited dynamic-range of these scanners can cause severe image artifacts that may compromise the diagnostic value of the non-destructive test. Finally, the cone-beam geometry of these scanners makes them susceptible to the adverse effects of scattered radiation, which is another source of artifacts in micro-CT imaging. In this work, we describe the design, fabrication, and implementation of a dedicated, cost-effective micro-CT scanner for NDT of AM-fabricated biomedical components. Our scanner reduces the limitations of costly image-based NDT by optimizing the scanner\u27s geometry and the image acquisition hardware (i.e., X-ray source and detector). Additionally, we describe two novel techniques to reduce image artifacts caused by photon-starvation and scatter radiation in cone-beam micro-CT imaging. Our cost-effective scanner was designed to match the image requirements of medium-size titanium-alloy medical components. We optimized the image acquisition hardware by using an 80 kVp low-cost portable X-ray unit and developing a low-cost lens-coupled X-ray detector. Image artifacts caused by photon-starvation were reduced by implementing dual-exposure high-dynamic-range radiography. For scatter mitigation, we describe the design, manufacturing, and testing of a large-area, highly-focused, two-dimensional, anti-scatter grid. Our results demonstrate that cost-effective NDT using low-cost equipment is feasible for medium-sized, titanium-alloy, AM-fabricated medical components. Our proposed high-dynamic-range strategy improved by 37% the penetration capabilities of an 80 kVp micro-CT imaging system for a total x-ray path length of 19.8 mm. Finally, our novel anti-scatter grid provided a 65% improvement in CT number accuracy and a 48% improvement in low-contrast visualization. Our proposed cost-effective scanner and artifact reduction strategies have the potential to improve patient care by accelerating the widespread use of patient-specific, bio-compatible, AM-manufactured, medical components

    The Adirondack Chronology

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    The Adirondack Chronology is intended to be a useful resource for researchers and others interested in the Adirondacks and Adirondack history.https://digitalworks.union.edu/arlpublications/1000/thumbnail.jp

    A productive response to legacy system petrification

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    Requirements change. The requirements of a legacy information system change, often in unanticipated ways, and at a more rapid pace than the rate at which the information system itself can be evolved to support them. The capabilities of a legacy system progressively fall further and further behind their evolving requirements, in a degrading process termed petrification. As systems petrify, they deliver diminishing business value, hamper business effectiveness, and drain organisational resources. To address legacy systems, the first challenge is to understand how to shed their resistance to tracking requirements change. The second challenge is to ensure that a newly adaptable system never again petrifies into a change resistant legacy system. This thesis addresses both challenges. The approach outlined herein is underpinned by an agile migration process - termed Productive Migration - that homes in upon the specific causes of petrification within each particular legacy system and provides guidance upon how to address them. That guidance comes in part from a personalised catalogue of petrifying patterns, which capture recurring themes underlying petrification. These steer us to the problems actually present in a given legacy system, and lead us to suitable antidote productive patterns via which we can deal with those problems one by one. To prevent newly adaptable systems from again degrading into legacy systems, we appeal to a follow-on process, termed Productive Evolution, which embraces and keeps pace with change rather than resisting and falling behind it. Productive Evolution teaches us to be vigilant against signs of system petrification and helps us to nip them in the bud. The aim is to nurture systems that remain supportive of the business, that are adaptable in step with ongoing requirements change, and that continue to retain their value as significant business assets

    Nonunion of the clavicle: novel use of clinical recovery and ultrasound to improve our ability to predict fracture healing

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    The aim of this thesis was to progress our understanding of clavicle nonunion and the ability to accurately predict fracture healing in order to improve the current management of these injuries. Although only one in seven fractures go onto nonunion, these are challenging to predict. It is unclear if the recent widespread increase in the use of acute plate fixation for displaced fractures is justified on current evidence. It is unknown whether the early accurate prediction of fractures at high risk of nonunion is advantageous. Currently the perceived risk of nonunion is largely based on factors available at time of injury alone. The evaluation of clinical recovery following non-operative management and the novel use of ultrasound may advance our ability to accurately predict fracture healing for these injuries. The cost-effectiveness of acute clavicle plate fixation versus non-operative treatment was estimated from randomized controlled trial data that had been previously published. This was completed prior to the start of this thesis and the author was not involved in the original trial. A large retrospective review of clavicle fracture fixations was undertaken to determine whether delayed clavicle fixation has an increased risk of complications compared to acute operative management. A prospective study of displaced midshaft fractures was carried out over a two-year period to determine the influence of functional recovery on the ability to predict fracture healing. The influence of clavicle fracture management on the early functional recovery was evaluated with data from a randomized controlled trial and second prospective cohort. Finally, the novel use of ultrasound to detect early callus formation and determine whether this allows accurate prediction of fracture healing was evaluated for a cohort of clavicle and tibia fractures. The estimated cost per quality-of-life adjusted year of acute plate fixation over non-operative treatment is £480,309.41/QALY. For a threshold of £20,000/QALY the benefit of acute fixation would need to be present for 24 years to be cost-effective over conservative treatment. Linear regression analysis identified nonunion as the only factor to negatively influence the SF-6D at 12-months (p<0.001). A ten-year cohort of 259 clavicle plate fixations found failed primary surgery requiring revision fixation occurred in 7.7% of all patients. Smoking (p<0.001), presence of a post-operative infection (<0.001), increasing age (p=0.018), and greater time delay from injury to surgery (p=0.015) was identified as significant independent predictors on regression analysis. Receiver operating curve analysis (ROC) revealed that surgery beyond 96 days from injury has an increased rate of major complications and revision surgery. Using a matched case cohort of cases before (n=67) and after the ‘safe window’ (n=77), the risk of post-operative infection increased (Odds ratio (OR) 7.7, p=0.028), fixation failure (OR 3.8, p=0.017) and revision surgery (OR 4.8 p=0.004). A delay to operative fixation beyond 3 months following injury would appear to be associated with an increased risk of major operative complications and revision surgery. A large prospective cohort of 200 patients managed non-operatively with a displaced midshaft clavicle fracture were recruited. Regression modelling found a QuickDASH ≥40 (p=0.001), no callus on radiograph (p=0.004) and fracture movement on examination (p=0.001) were significant predictors of nonunion. If none were present the predicted nonunion risk was 3%, found in 40% of the cohort. Conversely if two or more of the predictors were present, found in 23.5% of the cohort, the predicted nonunion risk was 60%. The delayed assessment nonunion model appeared to have superior accuracy when compared to the estimation of nonunion at time of injury alone healing on ROC curve analysis (Area Under Curve analysis; 87.3% vs 64.8% respectively). Data from a randomized controlled trial was used to compare 86 patients who underwent operative fixation against 76 patients that united with non-operative treatment. The recovery of normal shoulder function, as defined by a DASH score within the predicted 95% confidence interval for each respective patient was similar between each group at six-weeks (operative 26.7% vs non-operative 25.0%, p=0.80), three-months (52.3% vs 44.2%, p=0.77) and six-months post-injury (86.0% vs 90.8%, p=0.35). The mean DASH score and return to work was also comparable at each time point. Regression analysis found no specific patient, injury or fracture predictor was associated with an early return of function following non-operative management at six or twelve weeks. From a pilot study of twenty clavicle fractures, six-week sonographic bridging callus appeared to be the most accurate, and repeatable, predictor of fracture healing with a strong agreement on intra class correlation (ICC) between four reviewers (ICC 0.82, 95% confidence interval 0.68-0.91). In a large prospective study of 112 patients, sonographic bridging callus was detected in 62.5% (n=70/112) of the cohort at six weeks post-injury. If present, union occurred in 98.6% of the fractures (n=69/70). If absent, nonunion developed in 40.5% of cases (n=17/42). The sensitivity to predict union with sonographic bridging callus at six weeks was 73.4% and the specificity was 94.4%. Three-dimensional fracture reconstruction can be created using multiple ultrasound images in order to evaluate the presence of bridging callus. This imaging modality has the potential to enhance the usability and accuracy of identification of fracture healing at an early stage following injury. Nonunion following a displaced midshaft clavicle fractures accounts for the majority of poor functional recovery and impaired quality of life over the first-year post-injury. Prediction of clavicle fracture healing at six weeks following injury maybe a safe and effective strategy to identify patients at greatest risk of nonunion. The use of functional recovery enables a more accurate estimation of nonunion risk compared to conventional prediction at time of injury alone. The use of ultrasound may further refine our ability to predict fracture healing

    Digital tools for floating offshore wind turbines (FOWT): A state of the art

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    ABSTRACT: Operations and installation on offshore wind and especially floating are complex and difficult actions due to site accessibility and equipment availability. In this regard, digitalization is disrupting the wind section thanks to the development of advanced sensors, automated equipment, computational power, among other. All these allow to optimize and simplify different parts of the offshore wind power plant development (i.e. design, planning, installation, O&M, etc.). This fact is of special interest on maintenance, since the early detection of failures or malfunctions lead to reduced costly corrective maintenance. This paper presents a literature review of current state-of-the-art on the application of digitalization activities which can be applied for floating wind, including typical component failures, monitoring techniques and advanced digital tools as Digital Twin concept and Building Information Models (BIM). Finally, the review paper provides an analysis of existing gaps, needs and challenges of the sector to provide guides on research and innovation to foster offshore wind sector.The research leading to these results has received funding from the European Union’s H2020 Programme under Grant Agreement n◦ 815083 – Corewin

    Structural basis of translational recycling and bacterial ribosome rescue

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    In the last step of gene expression, a messenger RNA (mRNA) sequence is translated into a polypeptide. This highly regulated and dynamic process is carried out by the ribosome, a ribonucleoprotein complex composed of two unequal subunits. The translation cycle is initiated when the small ribosomal subunit (SSU) binds to an mRNA and recognizes the start codon of the open reading frame (ORF). Then the large ribosomal subunit (LSU) joins and the ribosome starts moving along the mRNA. A protein is synthesized until the ribosome reaches a stop codon. A cell needs thousands (prokaryotes) or millions (eukaryotes) of ribosomes for protein production and spends enormous amounts of energy on the assembly of this macromolecular machinery. Therefore, it is crucial to recycle the machinery after each successful round of translation. The recycling step allows release of mRNA, transfer RNA (tRNA) and the synthesized polypeptide from ribosomal subunits and subsequent binding of the next mRNA for protein synthesis. The first part of this dissertation includes studies of the highly conserved and essential ribosome recycling factor ATP binding cassette (ABC) Subfamily E Member 1 (ABCE1). In eukaryotes and archaea, ABCE1 binds the ribosome and in concert with an A-site factor and splits the ribosome into large and small subunits. ABCE1 harbors two nucleotide binding sites (NBSs), which are formed at the interface of two nucleotide binding domains (NBDs). Prior to this work, the ABCE1-bound pre-splitting complex, as well as the ABCE1-bound post-splitting complex, had been visualized by cryo-electron microscopy (cryo-EM) at medium resolution. This structural analysis combined with functional studies led to a model for the mechanism of the splitting event. ATP-binding and the closure of the NBSs lead to repositioning of the iron-sulfur cluster domain, which results in collision with the A-site factor and ribosome splitting. Yet, how conformational changes during the splitting event are triggered and communicated to the NBSs of ABCE1, was not understood. To gain molecular insights into this process, a structure of a fully nucleotide-occluded (closed) state of ABCE1 bound to the archaeal 30S post-splitting complex was solved by cryo-EM. At a resolution of 2.8 Å a detailed molecular analysis of ABCE1 was performed and confirmed by a combination of mutational and functional studies. This allowed to propose a refined model of how the ATPase cycle is linked to ribosome splitting and which role the different domains of ABCE1 play. In eukaryotes, the recycling phase is directly linked to translation initiation via the SSU. After being released from the mRNA 3’ end, the SSU can engage with another or even the same mRNA at the 5’ end. The recycling factor ABCE1 was found to be associated with initiation complexes, but whether it plays a role in initiation was not clear. Using cryo-EM, structures of native ABCE1-containing initiation complexes were solved and intensive 3D classification allowed to distinguish different stages of initiation, during which ABCE1 may play a role. Surprisingly, ABCE1 adopted a previously unknown state for ABC-type ATPases that was termed “hybrid state”. Here, the NBSI is in a half open state with ADP bound and the NBSII is in a closed state with ATP bound. Further, eukaryotic initiation factor 3j (eIF3j) was found to stabilize this hybrid conformation via its N-terminus. Since eIF3j had already been described to assist ABCE1 in ribosome dissociation, in vitro splitting assays were performed demonstrating that eiF3j indeed actively enhances the splitting reaction. On top of this, the high-resolution structure allowed to describe the interaction network of eIF3j with the ribosome, initiation factors (IFs), and ABCE1. Independent of ABCE1, the structures presented here allowed to provide an improved molecular model of the human 43S pre-initiation complex (PIC) and to analyze its sophisticated interaction network. In particular, new molecular insights into the large eIF3 complex encircling the 43S PIC, and the eIF2 ternary complex delivering the initiator tRNA are provided. Equally important as canonical recycling is the recognition and recycling of ribosomes that result from translational failure. Aberrant translation elongation and ribosome stalling can be caused by a plethora of different stresses. In bacterial cells, multiple rescue systems are known such as trans-translation or alternative ribosome rescue factor-mediated termination, which act on ribosome nascent chain complexes with an empty A-site (non-stop complexes). It has been a long standing question how ribosomes that are stalled in the middle of an ORF (no-go complexes) are recognized and recycled. The second part of this dissertation reports a new bacterial rescue system that acts on no-go complexes. In eukaryotes, the concept of ribosome collisions as a trigger for ribosome rescue has been studied extensively. Here, it was found that a similar mechanism exists in bacteria and thus a structural analysis of collided disomes in E. coli and B. subtilis was conducted. In a genetic screen, the endonuclease SmrB was identified as one candidate for a collision sensor. Structural analysis of SmrB-bound disomes elucidated how this rescue factor is recruited to collided ribosomes. Its SMR domain binds to the disome interface between the stalled and the collided ribosome in close proximity to the mRNA and in a position ideal to perform endonucleolytic cleavage. Such cleavage then results in non-stop complexes that can be recycled by the pathways mentioned above. In conclusion, this work provides mechanistic insights into how a cell distinguishes stalled ribosomes from actively translating ribosomes and characterizes a novel ribosome rescue pathway

    Fast forward: technography of the social integration of connected and automated vehicles into UK society

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    The emerging connected and automated vehicles (CAV) have caught much research attention in the past few years. However, a techno-centric bias in the CAV research domain implies the lack of in-depth qualitative studies. To fill the gap, this Ph.D. project bridges the fields of Social Anthropology with STS by adopting technography, an ethnography of technology, to enable a thick description of the CAV technology’s social integration into UK society. By critically drawing a holistic view of the ongoing process of the CAV social deployment, it aims to (1) unfold CAV’s potential problems and dynamic contributions to everyday life through the lens of sociotechnical imaginaries, and (2) reveal and analyse the institutional practice on its social rollout. Based on pilot research and one-year-long fieldwork in London and Edinburgh, the thesis investigated a wide range of important socio-political aspects where fundamental topics such as trust, human-and-machine relationship, social safety, political transparency, and equity in transport systems were explicated. Different from the planners’ top-down CAV imaginaries that focused on its contribution to functional safety, environment, and the economy, the public’s bottom-up imaginaries highlighted issues that were related to their travelling experiences, such as inequity of transport service distribution and sexual harassment during commutes. These findings inspired thinking and rethinking on what constitutes the success of technology’s social deployment from multiple perspectives. In particular, it critically pointed out that safety means not only technological feasibility but also social safety that refers to a safe commuting environments. Such finding in my thesis thus suggests that CAV technology is not a one-size-fits-all solution to problems in our transport system and calls for research effort to the broader socio-political and ethical areas of this technology. through an investigation of the institutional practice, it identified four major institutional forces, including technicians, industry stakeholders, researchers, and policymakers who have been working on these aspects with different approaches and priorities. Apart from acknowledging their efforts in building safety cases, pushing forward the CAV legislation, and engaging the public in trials, it critically explained challenges such as technical uncertainty and political tension in developing and implementing a legal framework. Hence, the project contributes to an understanding of a close encounter between the CAV technology and its imaginaries, in which, technical and socio-political problems and potentials fabricate the richness in its social deployment. It also explicates the importance of embracing multiple perspectives and calls for continuous research in this field
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