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- Delgado Blasco, José Manuel (author) doctoral thesis 2023
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Wang, C. (author)The scale of the power system has been significantly expanded in recent decades. To gain real-time insights into the power system, an increasing number of sensors have been deployed tomonitor grid states, resulting in a rapidly growing number of measurement points. Simultaneously, there has also been a rise in the penetration of renewable energy...doctoral thesis 2023
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Mourragui, S.M.C. (author)Extensive efforts in cancer research over the past decades have markedly improved diagnosis and treatments, leading to better outcomes for cancer patients. Paradoxically, however, these discoveries have begun to shed light on a level of complexity that rules out the emergence of a universal cancer treatment. As any tumor is now known to be...doctoral thesis 2023
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Vargas Quiros, J.D. (author), Kapcak, Oyku (author), Hung, H.S. (author), Cabrera Quiros, L.C. (author)Interpersonal attraction is known to motivate behavioral responses in the person experiencing this subjective phenomenon. Such responses may involve the imitation of behavior, as in mirroring or mimicry of postures or gestures, which have been found to be associated with the desire to be liked by an interlocutor. Speed dating provides a...journal article 2023
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Kartal, S. (author)Spatiotemporal time series prediction plays a crucial role in a wide range of applications. However, in most of the studies, spatial information was ignored and predictions were carried out either on a few points or on average values. In this study, 37 different configurations of 4 traditional ML models and 3 Neural Network (NN) based models...journal article 2023
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Sabzehee, F. (author), Amiri Simkooei, A. (author), Iran Pour, S. (author), Vishwakarma, B.D. (author), Kerachian, R. (author)The Urmia lake in north-west Iran has dried up to perilously low levels in the past two decades. In this study, we investigate the drivers behind the decline in lake water level with the help of in-situ and remote sensing data. We use total water storage (TWS) changes from the gravity recovery and climate experiment (GRACE) satellite mission....journal article 2023
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Freites, Alfredo (author), Corbett, P. W.M. (author), Rongier, G. (author), Geiger, S. (author)Understanding the impact of fractures on fluid flow is fundamental for developing geoenergy reservoirs. Pressure transient analysis could play a key role for fracture characterization purposes if better links can be established between the pressure derivative responses (p′) and the fracture properties. However, pressure transient analysis is...journal article 2023
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Thanh, Hung Vo (author), Ebrahimnia Taremsari, Sajad (author), Ranjbar, Benyamin (author), Mashhadimoslem, Hossein (author), Rahimi, E. (author), Rahimi, Mohammad (author), Elkamel, Ali (author)Porous carbons as solid adsorbent materials possess effective porosity characteristics that are the most important factors for gas storage. The chemical activating routes facilitate hydrogen storage by adsorbing on the high surface area and microporous features of porous carbon-based adsorbents. The present research proposed to predict H<sub...journal article 2023
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Applis, L.H. (author), Panichella, A. (author), Marang, R.J. (author)More machine learning (ML) models are introduced to the field of Software Engineering (SE) and reached a stage of maturity to be considered for real-world use; But the real world is complex, and testing these models lacks often in explainability, feasibility and computational capacities. Existing research introduced meta-morphic testing to...conference paper 2023
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Nowroozi, Ehsan (author), Mohammadi, Mohammadreza (author), Savas, Erkay (author), Mekdad, Yassine (author), Conti, M. (author)In the past few years, Convolutional Neural Networks (CNN) have demonstrated promising performance in various real-world cybersecurity applications, such as network and multimedia security. However, the underlying fragility of CNN structures poses major security problems, making them inappropriate for use in security-oriented applications,...journal article 2023
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Panichella, A. (author), Di Domenico, Giuseppe (author)Spatial mode division de-multiplexing of optical signals has many real-world applications, such as quantum computing and both classical and quantum optical communication. In this context, it is crucial to develop devices able to efficiently sort optical signals according to the optical mode they belong to and route them on different paths....conference paper 2023
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Sharifi Noorian, S. (author), Qiu, S. (author), Sayin, Burcu (author), Balayn, A.M.A. (author), Gadiraju, Ujwal (author), Yang, J. (author), Bozzon, A. (author)High-quality data plays a vital role in developing reliable image classification models. Despite that, what makes an image difficult to classify remains an unstudied topic. This paper provides a first-of-its-kind, model-agnostic characterization of image atypicality based on human understanding. We consider the setting of image classification...conference paper 2023
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Shengren, H. (author), Vergara Barrios, P.P. (author), Salazar Duque, Edgar Mauricio (author), Palensky, P. (author)The massive integration of renewable-based distributed energy resources (DERs) inherently increases the energy system’s complexity, especially when it comes to defining its operational schedule. Deep reinforcement learning (DRL) algorithms arise as a promising solution due to their data-driven and model-free features. However, current DRL...journal article 2023
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van 't Sant, S. (author), Thakolkaran, P. (author), Martínez, Jonàs (author), Kumar, Siddhant (author)Advancements in machine learning have sparked significant interest in designing mechanical metamaterials, i.e., materials that derive their properties from their inherent microstructure rather than just their constituent material. We propose a data-driven exploration of the design space of growth-based cellular metamaterials based on star-shaped...journal article 2023
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Reed, Robert (author), Laurenti, L. (author), Lahijanian, Morteza (author)Deep Kernel Learning (DKL) combines the representational power of neural networks with the uncertainty quantification of Gaussian Processes. Hence, it is potentially a promising tool to learn and control complex dynamical systems. In this letter, we develop a scalable abstraction-based framework that enables the use of DKL for control...journal article 2023
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Difrancesco, S. (author), van Baardewijk, J.U. (author), Cornelissen, A.S. (author), Varon, Carolina (author), Hendriks, R.C. (author), Bouwer, A.M. (author)Wearable sensors offer new opportunities for the early detection and identification of toxic chemicals in situations where medical evaluation is not immediately possible. We previously found that continuously recorded physiology in guinea pigs can be used for early detection of exposure to an opioid (fentanyl) or a nerve agent (VX), as well as...journal article 2023
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- de Croon, G.C.H.E. (author) journal article 2023
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Li, Z. (author), Kant, Henk (author), Hai, R. (author), Katsifodimos, A (author), Brambilla, Marco (author), Bozzon, A. (author)Machine learning (ML) practitioners and organizations are building model repositories of pre-trained models, referred to as model zoos. These model zoos contain metadata describing the properties of the ML models and datasets. The metadata serves crucial roles for reporting, auditing, ensuring reproducibility, and enhancing interpretability....journal article 2023
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Buijsman, S.N.R. (author)Machine learning is used more and more in scientific contexts, from the recent breakthroughs with AlphaFold2 in protein fold prediction to the use of ML in parametrization for large climate/astronomy models. Yet it is unclear whether we can obtain scientific explanations from such models. I argue that when machine learning is used to conduct...journal article 2023
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Lavrinenko, A.K. (author), Chernyshov, I. (author), Pidko, E.A. (author)Deep eutectic solvents (DESs) represent an environmentally friendly alternative to conventional organic solvents. Their liquid range determines the areas of application, and therefore, the prediction of solid-liquid equilibrium (SLE) diagrams is essential for developing new DESs. Such predictions are not yet possible by using the current...journal article 2023