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Schweidtmann, A.M. (author), Weber, Jana M. (author), Wende, Christian (author), Netze, Linus (author), Mitsos, Alexander (author)Data-driven models are becoming increasingly popular in engineering, on their own or in combination with mechanistic models. Commonly, the trained models are subsequently used in model-based optimization of design and/or operation of processes. Thus, it is critical to ensure that data-driven models are not evaluated outside their validity...journal article 2021
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Zhou, Jia Bin (author), Bai, Yan Qin (author), Guo, Y. (author), Lin, H.X. (author)In general, data contain noises which come from faulty instruments, flawed measurements or faulty communication. Learning with data in the context of classification or regression is inevitably affected by noises in the data. In order to remove or greatly reduce the impact of noises, we introduce the ideas of fuzzy membership functions and the...journal article 2021
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Muñoz Muñoz, F.A. (author), Mor, A. R. (author)This paper presents a wavelet analysis technique together with support vector machines (SVM) to discriminate partial discharges (PD) from external disturbances (electromagnetic noise) in a GIS PD measuring system based on magnetic antennas. The technique uses the Cross Wavelet Transform (XWT) to process the PD signals and the external...journal article 2020
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Uitterdijk, Niels (author)This thesis presents a novel data-driven Fault Detection and Isolation algorithm for the public network of Electric Vehicle chargers of Tritium Ltd. Pty. The proposed solution is robust against marginal differences in data distribution as well as marginal changes over time due the state-of-the-art optimization techniques used. This is required...master thesis 2020
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Kharagjitsing, Manish (author)The TU-Wien developed a soil moisture retrieval algorithm that uses the incidence angle dependence of backscatter to obtain soil moisture estimates (Wagner et al., 1999). The core of this algorithm is a second order Taylor expansion with which the backscatter is normalized at a reference angle. Studies have shown that the first and second order...master thesis 2020
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Liu, Xinyu (author)One interesting part of the application of human activity recognition is sports motion recognition and classification. In recent years, many commercial wearable devices have been used for recording and supervising motion data information during sports. However, their claimed high-accuracy results but motion recognition and classification method...master thesis 2020
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Nasiri, Jalal A. (author), Mir, S.A.M. (author)Among the extensions of twin support vector machine (TSVM), some scholars have utilized K-nearest neighbor (KNN) graph to enhance TSVM’s classification accuracy. However, these KNN-based TSVM classifiers have two major issues such as high computational cost and overfitting. In order to address these issues, this paper presents an enhanced...journal article 2020
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Jin, J. (author), Duan, Yunling (author)Automatic and efficient ground penetrating radar (GPR) data analysis remains a bottleneck, especially restricting applications in real-time monitoring systems. Deep learning approaches have good practice in automatic object identification, but their intensive data requirement has reduced their applicability. This paper developed a machine...journal article 2020
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Tideman, Leonoor (author)Imaging mass spectrometry (IMS) is a multiplexed chemical imaging technique that enables the spatially targeted molecular mapping of biological samples at cellular resolutions. Within a single experiment, IMS can measure the spatial distribution and relative concentration of thousands of distinct molecular species across the surface of a tissue...master thesis 2019
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Ritsma, Folkert (author)Performance of set based fault detection is highly dependent on the complexity of the set bounding methods used to bound the healthy residual set. Existing methods achieve robust performance with complex set bounding that narrowly define healthy system behavior, yet at the cost of higher computation times. In this thesis a major improvement is...master thesis 2019
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de Bruijn, Janno (author)In the Netherlands there are many bridges that crosses waterways, which are key nodes in the transportation system. The safety and integrity of these bridges is nowadays assessed by (visual) inspections at regular intervals. This approach cannot provide information about damage development in between inspections, leading to potential failure or...master thesis 2019
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Leunge, Laurens (author)In the Netherlands, robust dike and dam design is a major concern in the context of flood defence. Due to heterogeneity of the subsoil on which these structures are founded, the validity range of in situ tests decreases drastically. Consequently, large uncertainties regarding spatial variation of soil stratification and soil layer parameters are...master thesis 2019
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Chen, Cong (author), Batselier, K. (author), Ko, Ching Yun (author), Wong, Ngai (author)There has been growing interest in extending traditional vector-based machine learning techniques to their tensor forms. Support tensor machine (STM) and support Tucker machine (STuM) are two typical tensor generalization of the conventional support vector machine (SVM). However, the expressive power of STM is restrictive due to its rank-one...conference paper 2019
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Liu, Chenguang (author), Zheng, Huarong (author), Negenborn, R.R. (author), Chu, Xiumin (author), Xie, Shuo (author)Since vessel dynamics could vary during maneuvering because of load changes, speed changing, environmental disturbances, aging of mechanism, etc., the performance of model-based path following control may be degraded if the controller uses the same motion model all the time. This article proposes an adaptive path following control method...journal article 2019
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Vigueras Guillén, J.P. (author), Andrinopoulou, Eleni Rosalina (author), Engel, Angela (author), Lemij, Hans G. (author), van Rooij, J. (author), Vermeer, K.A. (author), van Vliet, L.J. (author)Corneal endothelium images obtained by in vivo specular microscopy provide important information to assess the health status of the cornea. Estimation of clinical parameters, such as cell density, polymegethism, and pleomorphism, requires accurate cell segmentation. State-of-the-art techniques to automatically segment the endothelium are...journal article 2018
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Sun, Zhuo (author), Qiao, Yuchuan (author), Lelieveldt, B.P.F. (author), Staring, M. (author)In recent years, machine learning approaches have been successfully applied to the field of neuroimaging for classification and regression tasks. However, many approaches do not give an intuitive relation between the raw features and the diagnosis. Therefore, they are difficult for clinicians to interpret. Moreover, most approaches treat the...journal article 2018
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Yan, Gaowei (author), Jia, Songda (author), Ding, Jie (author), Xu, Xinying (author), Pang, Y. (author)In this paper, a local cloud model similarity measurement (CMSM) is proposed as a novel method to measure the similarity of time series. Time series similarity measurement is an indispensable part for improving the efficiency and accuracy of prediction. The randomness and uncertainty of series data are critical problems in the processing of...journal article 2018
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Toward complete oral cavity cancer resection using a handheld diffuse reflectance spectroscopy probeBrouwer de Koning, Susan G. (author), Baltussen, Elisabeth J.M. (author), Karakullukcu, M. Baris (author), Dashtbozorg, Behdad (author), Smit, Laura A. (author), Dirven, Richard (author), Hendriks, B.H.W. (author), Sterenborg, Henricus J.C.M. (author), Ruers, Theo J.M. (author)This ex-vivo study evaluates the feasibility of diffuse reflectance spectroscopy (DRS) for discriminating tumor from healthy tissue, with the aim to develop a technology that can assess resection margins for the presence of tumor cells during oral cavity cancer surgery. Diffuse reflectance spectra were acquired on fresh surgical specimens...journal article 2018
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van Gent, P. (author), Melman, T. (author), Farah, H. (author), Nes, Nicole Van (author), van Arem, B. (author)The present study aims to add to the literature on driver workload prediction using machine learning methods. The main aim is to develop workload prediction on a multi-class basis, rather than a binary high/low distinction as often found in litearature. The presented approach relies on measures that can be obtained unobtrusively in the driving...conference paper 2018
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Liscio, Enrico (author)Autonomous grasping is a key requisite for the autonomy of robots.<br/>However, grasping of unknown objects in domestic environments is difficult due to the presence of unpredictability and clutter.<br/>In this paper, a novel algorithm capable of finding an unobstructed grasping pose on unknown regular object shapes in cluttered environments is...master thesis 2017