11,383 research outputs found

    A Design Science Research Approach to Smart and Collaborative Urban Supply Networks

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    Urban supply networks are facing increasing demands and challenges and thus constitute a relevant field for research and practical development. Supply chain management holds enormous potential and relevance for society and everyday life as the flow of goods and information are important economic functions. Being a heterogeneous field, the literature base of supply chain management research is difficult to manage and navigate. Disruptive digital technologies and the implementation of cross-network information analysis and sharing drive the need for new organisational and technological approaches. Practical issues are manifold and include mega trends such as digital transformation, urbanisation, and environmental awareness. A promising approach to solving these problems is the realisation of smart and collaborative supply networks. The growth of artificial intelligence applications in recent years has led to a wide range of applications in a variety of domains. However, the potential of artificial intelligence utilisation in supply chain management has not yet been fully exploited. Similarly, value creation increasingly takes place in networked value creation cycles that have become continuously more collaborative, complex, and dynamic as interactions in business processes involving information technologies have become more intense. Following a design science research approach this cumulative thesis comprises the development and discussion of four artefacts for the analysis and advancement of smart and collaborative urban supply networks. This thesis aims to highlight the potential of artificial intelligence-based supply networks, to advance data-driven inter-organisational collaboration, and to improve last mile supply network sustainability. Based on thorough machine learning and systematic literature reviews, reference and system dynamics modelling, simulation, and qualitative empirical research, the artefacts provide a valuable contribution to research and practice

    Statistical phase estimation and error mitigation on a superconducting quantum processor

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    Quantum phase estimation (QPE) is a key quantum algorithm, which has been widely studied as a method to perform chemistry and solid-state calculations on future fault-tolerant quantum computers. Recently, several authors have proposed statistical alternatives to QPE that have benefits on early fault-tolerant devices, including shorter circuits and better suitability for error mitigation techniques. However, practical implementations of the algorithm on real quantum processors are lacking. In this paper we practically implement statistical phase estimation on Rigetti's superconducting processors. We specifically use the method of Lin and Tong [PRX Quantum 3, 010318 (2022)] using the improved Fourier approximation of Wan et al. [PRL 129, 030503 (2022)], and applying a variational compilation technique to reduce circuit depth. We then incorporate error mitigation strategies including zero-noise extrapolation and readout error mitigation with bit-flip averaging. We propose a simple method to estimate energies from the statistical phase estimation data, which is found to improve the accuracy in final energy estimates by one to two orders of magnitude with respect to prior theoretical bounds, reducing the cost to perform accurate phase estimation calculations. We apply these methods to chemistry problems for active spaces up to 4 electrons in 4 orbitals, including the application of a quantum embedding method, and use them to correctly estimate energies within chemical precision. Our work demonstrates that statistical phase estimation has a natural resilience to noise, particularly after mitigating coherent errors, and can achieve far higher accuracy than suggested by previous analysis, demonstrating its potential as a valuable quantum algorithm for early fault-tolerant devices.Comment: 24 pages, 13 figure

    Augmented classification for electrical coil winding defects

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    A green revolution has accelerated over the recent decades with a look to replace existing transportation power solutions through the adoption of greener electrical alternatives. In parallel the digitisation of manufacturing has enabled progress in the tracking and traceability of processes and improvements in fault detection and classification. This paper explores electrical machine manufacture and the challenges faced in identifying failures modes during this life cycle through the demonstration of state-of-the-art machine vision methods for the classification of electrical coil winding defects. We demonstrate how recent generative adversarial networks can be used to augment training of these models to further improve their accuracy for this challenging task. Our approach utilises pre-processing and dimensionality reduction to boost performance of the model from a standard convolutional neural network (CNN) leading to a significant increase in accuracy

    An investigation of the geothermal potential of the Upper Devonian sandstones beneath eastern Glasgow

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    The urban development of the city of Glasgow is a consequence of its economic development, in part fuelled by local coalfields which exploited rocks in the same sedimentary basin within which geothermal resources in flooded abandoned mine workings, and deeper hot sedimentary aquifers (HSA), are present. This creates an opportunity to provide geothermal heating to areas of dense urban population with high heat demand. The depth of the target HSA geothermal resource, in Upper Devonian aged sandstones of the Stratheden Group, beneath eastern Glasgow was determined by gravity surveying and structural geological modelling. The estimated depth of the geothermal resource ranged from c.1500-2000 m, in the eastward deepening sedimentary basin. To reliably estimate the temperature of the geothermal resource, rigorous corrections to account for the effects of palaeoclimate and topography on heat flow were applied to boreholes in the Greater Glasgow area. The mean regional corrected heat flow was calculated as 75.7 mW m-2, an increase of 13.8 mW m-2 from the uncorrected value of 61.9 mW m-2, emphasising the extent to which heat flow was previously underestimated. Extrapolation of the geothermal gradient, calculated from the mean regional corrected heat flow, results in aquifer temperatures of c. 64-79 °C at depths of c.1500-2000 m beneath eastern Glasgow. The geothermal resource may, therefore, be capable of supporting a wide variety of direct heat use applications if sufficient matrix permeability or fracture networks are present. However, diagenetic effects such as quartz and carbonate cementation were found to restrict the porosity in Upper Devonian sandstones in a borehole and outcrop analogue study. These effects may likewise reduce porosity and intergranular permeability in the target aquifer, although this crucial aspect cannot be fully understood without deep exploratory drilling. To quantify the magnitude of the deep geothermal resource, the indicative thermal power outputs of geothermal doublet wells located in Glasgow’s East End were calculated for the first time, with outputs ranging from 1.3-2.1 MW dependent upon the aquifer depth. This, however, is predicated upon an aquifer permeability of c. 40 mD, which if reduced to 10 mD or less due to the effects of diagenesis, significantly reduces the thermal power outputs to 230-390 kW. The lack of assured project-success, given uncertainties related to the aquifer properties at depth, coupled with high capital costs of drilling, pose barriers to the development of deep geothermal energy in Glasgow. Further investigation of the economic viability of geothermal exploration, and alternative technological solutions is therefore required to mitigate the technical and economic risks. However, if sufficient matrix permeability or fracture networks are present at depth in the Upper Devonian sandstone sequence, then the potential contribution that geothermal energy could make to meeting local heat demand, reducing greenhouse gas emissions, and addressing the ‘energy trilemma’ in Glasgow is significant

    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

    Educating Sub-Saharan Africa:Assessing Mobile Application Use in a Higher Learning Engineering Programme

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    In the institution where I teach, insufficient laboratory equipment for engineering education pushed students to learn via mobile phones or devices. Using mobile technologies to learn and practice is not the issue, but the more important question lies in finding out where and how they use mobile tools for learning. Through the lens of Kearney et al.’s (2012) pedagogical model, using authenticity, personalisation, and collaboration as constructs, this case study adopts a mixed-method approach to investigate the mobile learning activities of students and find out their experiences of what works and what does not work. Four questions are borne out of the over-arching research question, ‘How do students studying at a University in Nigeria perceive mobile learning in electrical and electronic engineering education?’ The first three questions are answered from qualitative, interview data analysed using thematic analysis. The fourth question investigates their collaborations on two mobile social networks using social network and message analysis. The study found how students’ mobile learning relates to the real-world practice of engineering and explained ways of adapting and overcoming the mobile tools’ limitations, and the nature of the collaborations that the students adopted, naturally, when they learn in mobile social networks. It found that mobile engineering learning can be possibly located in an offline mobile zone. It also demonstrates that investigating the effectiveness of mobile learning in the mobile social environment is possible by examining users’ interactions. The study shows how mobile learning personalisation that leads to impactful engineering learning can be achieved. The study shows how to manage most interface and technical challenges associated with mobile engineering learning and provides a new guide for educators on where and how mobile learning can be harnessed. And it revealed how engineering education can be successfully implemented through mobile tools

    Full stack development toward a trapped ion logical qubit

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    Quantum error correction is a key step toward the construction of a large-scale quantum computer, by preventing small infidelities in quantum gates from accumulating over the course of an algorithm. Detecting and correcting errors is achieved by using multiple physical qubits to form a smaller number of robust logical qubits. The physical implementation of a logical qubit requires multiple qubits, on which high fidelity gates can be performed. The project aims to realize a logical qubit based on ions confined on a microfabricated surface trap. Each physical qubit will be a microwave dressed state qubit based on 171Yb+ ions. Gates are intended to be realized through RF and microwave radiation in combination with magnetic field gradients. The project vertically integrates software down to hardware compilation layers in order to deliver, in the near future, a fully functional small device demonstrator. This thesis presents novel results on multiple layers of a full stack quantum computer model. On the hardware level a robust quantum gate is studied and ion displacement over the X-junction geometry is demonstrated. The experimental organization is optimized through automation and compressed waveform data transmission. A new quantum assembly language purely dedicated to trapped ion quantum computers is introduced. The demonstrator is aimed at testing implementation of quantum error correction codes while preparing for larger scale iterations.Open Acces

    How to Be a God

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    When it comes to questions concerning the nature of Reality, Philosophers and Theologians have the answers. Philosophers have the answers that can’t be proven right. Theologians have the answers that can’t be proven wrong. Today’s designers of Massively-Multiplayer Online Role-Playing Games create realities for a living. They can’t spend centuries mulling over the issues: they have to face them head-on. Their practical experiences can indicate which theoretical proposals actually work in practice. That’s today’s designers. Tomorrow’s will have a whole new set of questions to answer. The designers of virtual worlds are the literal gods of those realities. Suppose Artificial Intelligence comes through and allows us to create non-player characters as smart as us. What are our responsibilities as gods? How should we, as gods, conduct ourselves? How should we be gods
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