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In a dynamic global landscape, the role of UK Export Finance (UKEF) and other export credit agencies (ECAs) has never been more important. Access to finance is critical for exporters as it enables them to invest in production, expand operations, manage cash flow and mitigate trade risks. However, businesses face challenges in securing export finance and trade credit insurance as geopolitical and trade megatrends lead to increased political, market and credit risks. Drawing on qualitative data from 35 semi-structured interviews and expert discussions and based on the Futures Triangle analytical framework, this white paper analyses the geopolitical and trade megatrends that UKEF and other ECAs will face in the coming years. It presents novel findings about the implications for ECA mandates, strategies, products and operations: The evolution of mandates towards a “growth promoter”, the need to further scale up operations, the use of big data and artificial intelligence for risk analysis and forecasting, and the need to balance multiple and conflicting priorities, including export growth, support for small and medium-sized exporters, inclusive trade, climate action, and positive impact in developing markets.
The last decades have seen the evolution of industrial production into more sophisticated processes. The development of specialized, high-end machines has increased the importance of predictive maintenance of mechanical systems to produce high-quality goods and avoid machine breakdowns. Predictive maintenance has two main objectives: to classify the current status of a machine component and to predict the maintenance interval by estimating its remaining useful life (RUL). Nowadays, both objectives are covered by machine learning and deep learning approaches and require large training datasets that are often not available. One possible solution may be transfer learning, where the knowledge of a larger dataset is transferred to a smaller one. This thesis is primarily concerned with transfer learning for predictive maintenance for fault classification and RUL estimation. The first part presents the state-of-the-art machine learning techniques with a focus on techniques applicable to predictive maintenance tasks (Chapter 2). This is followed by a presentation of the machine tool background and current research that applies the previously explained machine learning techniques to predictive maintenance tasks (Chapter 3). One novelty of this thesis is that it introduces a new intermediate domain that represents data by focusing on the relevant information to allow the data to be used on different domains without losing relevant information (Chapter 4). The proposed solution is optimized for rotating elements. Therefore, the presented intermediate domain creates different layers by focusing on the fault frequencies of the rotating elements. Another novelty of this thesis is its semi and unsupervised transfer learning-based fault classification approach for different component types under different process conditions (Chapter 5). It is based on the intermediate domain utilized by a convolutional neural network (CNN). In addition, a novel unsupervised transfer learning loss function is presented based on the maximum mean discrepancy (MMD), one of the state-of-the-art algorithms. It extends the MMD by considering the intermediate domain layers; therefore, it is called layered maximum mean discrepancy (LMMD). Another novelty is an RUL estimation transfer learning approach for different component types based on the data of accelerometers with low sampling rates (Chapter 6). It applies the feature extraction concepts of the classification approach: the presented intermediate domain and the convolutional layers. The features are then used as input for a long short-term memory (LSTM) network. The transfer learning is based on fixed feature extraction, where the trained convolutional layers are taken over. Only the LSTM network has to be trained again. The intermediate domain supports this transfer learning type, as it should be similar for different component types. In addition, it enables the practical usage of accelerometers with low sampling rates during transfer learning, which is an absolute novelty. All presented novelties are validated in detailed case studies using the example of bearings (Chapter 7). In doing so, their superiority over state-of-the-art approaches is demonstrated.
This paper presents a streaming-based E-Learning environment where closer integration between learning and work is achieved by integrating multimedia services into manufacturing processes. It contains a comprehensive and detailed explanation of the proposed E-Learning streaming framework, especially the adaption of streaming services to mobile environments. We first analyze several scenarios where E-Learning streaming services can be integrated into manufacturing processes. To allow systematic and tailor-made integration, we develop a model and a specification language for E-Learning streaming services and apply the model using practical scenarios from real manufacturing processes. Adaption of multimedia streaming services to mobile devices is discussed based on Synchronized Multimedia Integration Language (SMIL). Last, we comment on the benefits of using E-Learning streaming services as part of manufacturing processes and analyze the acceptance of the developed system. The key components of our E-Learning environment are 1) an xml based streaming service specification language, 2) adaption of multimedia E-Learning services to mobile environments, and 3) Web Services for searching, registration, and creation of E-Learning streaming services.
The invention concerns a method for spectrum monitoring a given frequency band, in which the spectral power density (S(f)) within the given frequency band is determined for all noise and signal components in the frequency band and, in order to detect the presence of one or more signals within the given frequency band, it is evaluated whether the spectral power density (S(f)) exceeds a threshold value (&lgr;). According to the invention, the threshold value (&lgr;) is calculated in accordance with an estimation of a distribution density (hR(S)) for the noise component of the spectral power density (S(f)) within the given frequency band and in accordance with a predefined value for the false-alarm probability (Pfa).
The invention relates to a container (1) for a liquid medium (3), in particular a blood bag, comprising a flexible outer wall (5) and a device (13) connected to the container (1) for acquiring and/or storing data. According to the invention, the device (13) for acquiring and/or storing data is arranged within the flexible outer wall (5), wherein positioning means (15) are provided which hold the device (13) for acquiring and/or storing data in a floating manner in the liquid medium when the container (1) is filled with said liquid medium (3), and wherein the device (13) or the device (13) and the positioning means (15) are designed such that the mass of liquid medium (3) which is displaced in each case is essentially equal to the mass of the device (13) or to the mass of the device (13) and the positioning means (15).
A wet-chemical treatment system for electrochemically coating flat substrates with coating material, has having a basin for receiving an electrolyte, a transporting means, by means of which the flat substrates can be transported through the electrolyte horizontally, and at least one contact element which comprises a shaft having an axis of rotation and a cylindrical circumferential surface suitable for rolling on the substrate, wherein the circumferential surface comprises at least one electrically insulated segment and at least one electrically conductive segment which can be connected to a current source in such a way that the polarity can be reversed, wherein the axis of rotation of the contact element is positioned above the surface of the electrolyte, and wherein the contact element is designed as a consumable electrode.
The invention relates to a device for metalising substrates. In particular, the invention relates to the field of contact elements used to electroplate solar cells within the context of a wet-chemical continuous treatment system. A wet-chemical treatment system according to the invention, for electrochemically coating flat substrates (1) with coating material, has a tank for accommodating an electrolyte, transporting means, by means of which the flat substrates (1) can be transported through the electrolyte horizontally, and at least one contact element (2), which comprises a shaft (4) having an axis of rotation (5) and a cylindrical circumferential surface suitable for rolling on the substrate (1), wherein the circumferential surface comprises at least one electrically insulating segment (3B) and at least one electrically conductive segment (3A), which can be connected to a current source (6) in such a way that the polarity can be reversed, wherein the axis of rotation (5) of the contact element (2) is positioned above the surface of the electrolyte, and wherein the contact element (2) is designed as a consumable electrode.
The invention relates to a method for determining properties of a pipeline, more particularly the position of a branch in a waste water pipeline, in which: a sound wave transmission signal (S, S') is fed into the pipeline (1) at a predetermined infeed point and propagates in the axial direction of the pipeline (1), wherein the frequency spectrum of the sound wave transmission signal (S, S') has a frequency component or a spectral range, the maximum frequency of which is lower than the lower limit frequency (fc) for the first upper mode; in which method components (Sr1, Sr2, Sr3, S'r1, S'r2, S'r3) of the sound wave transmission signal (S, S') reflected inside the pipeline (1) are detected as a sound wave reception signal (E, E'); and in which method, by evaluating the sound wave reception signal (E, E') in relation to the sound wave transmission signal (S, S'), the pipeline (1) is examined for the presence of reflection sites along the pipeline (1) that cause sound wave reflections (Sr1, Sr2, Sr3, S'r1, S'r2, S'r3), wherein at least the distance (I) of a reflection site from the infeed point is determined by evaluating the respective sound wave reception signal (E, E'). The invention further relates to a device for implementing said method.
The application relates to an electronic pill for dispensing a substance, in particular a drug, in a human or animal body in a controllable manner, said electronic pill having a housing (3) in which the substance (17) to be dispensed is accommodated and in which a dispensing opening (47) for dispensing the substance (17) is provided, wherein the substance (17) can be subjected to a predetermined pressure in order to be dispensed from the housing (3), having an electronic control unit (53, 59, 61, 63), and having a valve unit (33) which is arranged in the course of a dispensing path and can be moved from an open position to a closed position by the control unit (53, 59, 61, 63). In the housing (3), a throttle section (45) is provided in the course of the dispensing path for the substance (17) to be dispensed.