Searched for: subject%3A%22network%22
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Schweidtmann, A.M. (author), Zhang, Dongda (author), von Stosch, Moritz (author)
The term hybrid modeling refers to the combination of parametric models (typically derived from knowledge about the system) and nonparametric models (typically deduced from data). Despite more than 20 years of research, over 150 scientific publications (Agharafeie et al., 2023), and some recent industrial applications on this topic, the...
review 2024
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Murti, Fahri Wisnu (author), Ali, Samad (author), Iosifidis, G. (author), Latva-aho, Matti (author)
Virtualized Radio Access Networks (vRANs) are fully configurable and can be implemented at a low cost over commodity platforms to enable network management flexibility. In this paper, a novel vRAN reconfiguration problem is formulated to jointly reconfigure the functional splits of the base stations (BSs), locations of the virtualized central...
journal article 2024
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Aarnoudse, Leontine (author), Kon, Johan (author), Ohnishi, Wataru (author), Poot, Maurice (author), Tacx, Paul (author), Strijbosch, Nard (author), Oomen, T.A.E. (author)
The performance of feedforward control depends strongly on its ability to compensate for reproducible disturbances. The aim of this paper is to develop a systematic framework for artificial neural networks (ANN) for feedforward control. The method involves three aspects: a new criterion that emphasizes the closed-loop control objective,...
journal article 2024
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Trunz, Elena (author), Klein, Jonathan (author), Müller, Jan (author), Bode, Lukas (author), Sarlette, Ralf (author), Weinmann, M. (author), Klein, Reinhard (author)
We investigate the capabilities of neural inverse procedural modeling to infer high-quality procedural yarn models with fiber-level details from single images of depicted yarn samples. While directly inferring all parameters of the underlying yarn model based on a single neural network may seem an intuitive choice, we show that the complexity...
journal article 2024
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He, K. (author), Shi, S. (author), van den Boom, A.J.J. (author), De Schutter, B.H.K. (author)
Approximate dynamic programming (ADP) faces challenges in dealing with constraints in control problems. Model predictive control (MPC) is, in comparison, well-known for its accommodation of constraints and stability guarantees, although its computation is sometimes prohibitive. This paper introduces an approach combining the two methodologies...
journal article 2024
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Diware, S.S. (author), Chilakala, Koteswararao (author), Joshi, Rajiv V. (author), Hamdioui, S. (author), Bishnoi, R.K. (author)
Diabetic retinopathy (DR) is a leading cause of permanent vision loss worldwide. It refers to irreversible retinal damage caused due to elevated glucose levels and blood pressure. Regular screening for DR can facilitate its early detection and timely treatment. Neural network-based DR classifiers can be leveraged to achieve such screening in...
journal article 2024
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Krishnakumar, Nila (author)
To keep pace with increasing renewable energy penetration and consequent increase in inverter-based resources in the power grid, it is pertinent for present-day research to address the resulting drop in system inertia levels and its impact on frequency stability. With decreasing levels of inherent rotational inertia present in the system, any...
master thesis 2023
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Burgers, Nienke (author)
The real-life Vehicle Routing Problem (VRP) is the problem in which a set of vehicles needs to perform a set of tasks such that we have a shortest total driving distance. Such problems can be solved using construction algorithms. Finding the best-performing construction algorithm is time-consuming because these algorithms consist of many...
master thesis 2023
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Lv, Maolong (author), De Schutter, B.H.K. (author), Cao, Jinde (author), Baldi, S. (author)
Practical tracking results have been reported in the literature for high-order odd-rational-power nonlinear dynamics (a chain of integrators whose power is the ratio of odd integers). Asymptotic tracking remains an open problem for such dynamics. This note gives a positive answer to this problem in the framework of prescribed performance...
journal article 2023
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Franci, B. (author), Grammatico, S. (author)
Generative adversarial networks (GANs) are a class of generative models with two antagonistic neural networks: a generator and a discriminator. These two neural networks compete against each other through an adversarial process that can be modeled as a stochastic Nash equilibrium problem. Since the associated training process is challenging,...
journal article 2023
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Li, Wanda (author), Xu, Zhiwei (author), Sun, Yi (author), Gong, Qingyuan (author), Chen, Y. (author), Ding, Aaron Yi (author), Wang, Xin (author), Hui, Pan (author)
Outstanding users (OUs) denote the influential, 'core' or 'bridge' users in online social networks. How to accurately detect and rank them is an important problem for third-party online service providers and researchers. Conventional efforts, ranging from early graph-based algorithms to recent machine learning-based approaches, typically rely on...
journal article 2023
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Liu, Chengen (author), Leus, G.J.T. (author), Isufi, E. (author)
The edge flow reconstruction task consists of retreiving edge flow signals from corrupted or incomplete measurements. This is typically solved by a regularized optimization problem on higher-order networks such as simplicial complexes and the corresponding regularizers are chosen based on prior knowledge. Tailoring this prior to the setting...
journal article 2023
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Magnini, Matteo (author), Ciatto, Giovanni (author), Cantürk, Furkan (author), Aydoğan, Reyhan (author), Omicini, Andrea (author)
Background and objective:This paper focuses on nutritional recommendation systems (RS), i.e. AI-powered automatic systems providing users with suggestions about what to eat to pursue their weight/body shape goals. A trade-off among (potentially) conflictual requirements must be taken into account when designing these kinds of systems, there...
journal article 2023
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Anikiev, Denis (author), Birnie, Claire (author), Waheed, Umair bin (author), Alkhalifah, Tariq (author), Gu, Chen (author), Verschuur, D.J. (author), Eisner, Leo (author)
The confluence of our ability to handle big data, significant increases in instrumentation density and quality, and rapid advances in machine learning (ML) algorithms have placed Earth Sciences at the threshold of dramatic progress. ML techniques have been attracting increased attention within the seismic community, and, in particular, in...
review 2023
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Rizki, Z. (author), Ottens, M. (author)
Membrane technology is commonly used within food, bio- and pharmaceutical processes. Beside single-stage membranes, multi-stage membrane systems are become more popular to improve separation performance. In this review, we present a unified four-phase model-based optimization framework to optimize these systems, using mechanistic models,...
review 2023
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Mercier, Arthur (author), Smolin, Nikita (author), Sihlovec, Oliver (author), Koffas, S. (author), Picek, S. (author)
Outsourced training and crowdsourced datasets lead to a new threat for deep learning models: the backdoor attack. In this attack, the adversary inserts a secret functionality in a model, activated through malicious inputs. Backdoor attacks represent an active research area due to diverse settings where they represent a real threat. Still,...
journal article 2023
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Kueffner, Konstantin (author), Lukina, A. (author), Schilling, Christian (author), Henzinger, Thomas A. (author)
Neural-network classifiers achieve high accuracy when predicting the class of an input that they were trained to identify. Maintaining this accuracy in dynamic environments, where inputs frequently fall outside the fixed set of initially known classes, remains a challenge. We consider the problem of monitoring the classification decisions of...
journal article 2023
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Mauro, F. (author), Conti, Fabien (author), Vassalos, Dracos (author)
Real-time assessment of flooding risk associated with the collision between two ships, requires a fast estimation of damage dimensions and associated survivability. The state-of-the-art frameworks for risk assessment on passenger ships do not consider a direct evaluation of damages through crash simulations but refer to probabilistic...
journal article 2023
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Borst, N.G. (author), Verhagen, W.J.C. (author)
Prognostics and Health Management (PHM) models aim to estimate remaining useful life (RUL) of complex systems, enabling lower maintenance costs and increased availability. A substantial body of work considers the development and testing of new models using the NASA C-MAPSS dataset as a benchmark. In recent work, the use of ensemble methods...
journal article 2023
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Li, Ruohan (author), Dong, Y. (author)
Lane detection is crucial for vehicle localization which makes it the foundation for automated driving and many intelligent and advanced driving assistant systems. Available vision-based lane detection methods do not make full use of the valuable features and aggregate contextual information, especially the interrelationships between lane...
journal article 2023
Searched for: subject%3A%22network%22
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