Viser treff 1-20 av 227

    • Learning Parameterized ODEs From Data 

      Li, Qing; Evje, Steinar; Geng, Jiahui (Peer reviewed; Journal article, 2023)
      In contemporary research, neural networks are being used to derive Ordinary Differential Equations (ODEs) from observations. However, parameterized ODEs pose a more significant challenge than non-parameterized ODEs since ...
    • ARTICONF decentralized social media platform for democratic crowd journalism 

      Rito Lima, Inês; Filipe, Vasco; Marinho, Claudia; Ulisses, Alexandre; Chakravorty, Antorweep; Hristov, Atanas; Saurabh, Nishant; Zhao, Zhiming; Xin, Ruyue; Prodan, Radu (Peer reviewed; Journal article, 2023)
      Media production and consumption behaviors are changing in response to new technologies and demands, giving birth to a new generation of social applications. Among them, crowd journalism represents a novel way of constructing ...
    • Vision transformers for small histological datasets learned through knowledge distillation 

      Kanwal, Neel; Eftestøl, Trygve Christian; Khoraminia, Farbod; Zuiverloon, Tahlita C M; Engan, Kjersti (Chapter, 2023)
      Computational Pathology (CPATH) systems have the potential to automate diagnostic tasks. However, the artifacts on the digitized histological glass slides, known as Whole Slide Images (WSIs), may hamper the overall performance ...
    • Availability model of a 5G-MEC system 

      Pathirana, Thilina Dhanushka Kalahe; Nencioni, Gianfranco (Chapter, 2023)
      Multi-access Edge Computing (MEC) is one of the enabling technologies of the fifth generation (5G) of mobile networks. MEC enables services with strict latency requirements by bringing computing capabilities close to the ...
    • Analysis of Machine Learning Based Imputation of Missing Data 

      Rizvi, Syed Tahir Hussain; Latif, Muhammad Yasir; Amin, Muhammad Saad; Telmoudi, Achraf Jabeur; Shah, Nasir Ali (Peer reviewed; Journal article, 2023)
      Data analysis and classification can be affected by the availability of missing data in datasets. To deal with missing data, either deletion- or imputation-based methods are used that result in the reduction of data records ...
    • MigraMEC: Hybrid Testbed for MEC App Migration 

      Wadatkar, Prachi Vinod; Garroppo, Rosario G.; Nencioni, Gianfranco (Chapter, 2023)
      Multi-access Edge Computing (MEC) enhances the capabilities of 5G by enabling the computation closer to the end-user for real-time and context-aware services. One of the main challenges of MEC is the migration of the MEC ...
    • Joint multi-objective MEH selection and traffic path computation in 5G-MEC systems 

      Wadatkar, Prachi Vinod; Garroppo, Rosario G.; Nencioni, Gianfranco; Volpi, Marco (Peer reviewed; Journal article, 2024)
      Multi-access Edge Computing (MEC) is an emerging technology that allows to reduce the service latency and traffic congestion and to enable cloud offloading and context awareness. MEC consists in deploying computing devices, ...
    • Evaluation Study of Inertial Positioning in Road Tunnels for Cooperative ITS Applications 

      Martin Rodriguez, Aitor; Khademi, Naeem (Peer reviewed; Journal article, 2023)
      Global Navigation Satellite Systems (GNSS) are unreliable positioning sources in road tunnels, as the satellite signals are unable to reach deep inside the tunnels. As innovative technologies emerge within the transportation ...
    • Revenue-Model Learning for a Slice Broker in the Presence of Adversaries 

      Khan, Md Muhidul Islam; Nencioni, Gianfranco (Chapter, 2023)
      Multi-Access Edge Computing (MEC) and network slicing two of the key enabling technologies of the Fifth Generation (5G) of cellular network. MEC helps to reduce latency, offload the cloud, and allow context-awareness. ...
    • Revenue Maximization of a Slice Broker in the Presence of Byzantine Faults 

      Khan, Md Muhidul Islam; Nencioni, Gianfranco (Chapter, 2023)
      Multi-Access Edge Computing (MEC) and network slicing are vital for advancing the Fifth Generation (5G) of cellular systems. MEC provides context awareness and reduces the latency for communication. Network slicing allows ...
    • CT Perfusion is All We Need: 4D CNN Segmentation of Penumbra and Core in Patients With Suspected Acute Ischemic Stroke 

      Tomasetti, Luca; Engan, Kjersti; Høllesli, Liv Jorunn; Kurz, Kathinka Dæhli; Khanmohammadi, Mahdieh (Peer reviewed; Journal article, 2023)
      Stroke is the second leading cause of death worldwide, and around 87 % of strokes are ischemic strokes. Accurate and rapid prediction techniques for identifying ischemic regions, including dead tissue (core) and potentially ...
    • Modelling and Design of Pre-Equalizers for a Fully Operational Visible Light Communication System 

      Bostanoglu, Murat; Dalveren, Yaser; Catak, Ferhat Özgur; Kara, Ali (Peer reviewed; Journal article, 2023-06)
      Nowadays, Visible Light Communication (VLC) has gained much attention due to the significant advancements in Light Emitting Diode (LED) technology. However, the bandwidth of LEDs is one of the important concerns that limits ...
    • Quantification of perineural satellitosis in pretreatment glioblastoma with structural MRI and a diffusion tensor imaging template 

      van den Elshout, Rik; Ariëns, Benthe; Blaauboer, Joost; Meijer, Frederick J A; van der Kolk, Anja G; Esmaeili, Morteza; Scheenen, Tom W J; Henssen, Dylan J H A (Peer reviewed; Journal article, 2023)
      Background Survival outcomes for glioblastoma (GBM) patients remain unfavorable, and tumor recurrence is often observed. Understanding the radiological growth patterns of GBM could aid in improving outcomes. This study ...
    • Resource allocation for cost minimization of a slice broker in a 5G-MEC scenario 

      Sarah, Annisa; Nencioni, Gianfranco (Peer reviewed; Journal article, 2023-11)
      The fifth generation (5G) of mobile networks may offer a custom logical and virtualized network called network slicing. This virtualization opens a new opportunity to share infrastructure resources and encourage cooperation ...
    • Deployment and Implementation Aspects of Radio Frequency Fingerprinting in Cybersecurity of Smart Grids 

      Awan, Maaz Ali; Dalveren, Yaser; Catak, Ferhat Özgur; Kara, Ali (Peer reviewed; Journal article, 2023)
      Smart grids incorporate diverse power equipment used for energy optimization in intelligent cities. This equipment may use Internet of Things (IoT) devices and services in the future. To ensure stable operation of smart ...
    • MRI data-driven clustering reveals different subtypes of Dementia with Lewy bodies 

      Inguanzo, Anna; Poulakis, Konstantinos; Mohanty, Rosaleena; Schwarz, Christopher G.; Przybelski, Scott A.; Diaz-Galvan, Patricia; Lowe, Val J.; Boeve, Bradley F.; Lemstra, Afina W.; van de Beek, Marleen; van der Flier, Wiesje; Barkhof, Frederik; Blanc, Frederic; Loureiro de Sousa, Paulo; Philippi, Nathalie; Cretin, Benjamin; Demuynck, Catherine; Nedelska, Zuzana; Hort, Jakub; Segura, Barbara; Junque, Carme; Oppedal, Ketil; Aarsland, Dag; Westman, Eric; Kantarci, Kejal; Ferreira, Daniel (Peer reviewed; Journal article, 2023)
      Dementia with Lewy bodies (DLB) is a neurodegenerative disorder with a wide heterogeneity of symptoms, which suggests the existence of different subtypes. We used data-driven analysis of magnetic resonance imaging (MRI) ...
    • Kernel recursive least squares dictionary learning algorithm 

      Alipoor, Ghasem; Skretting, Karl (Peer reviewed; Journal article, 2023)
      An online dictionary learning algorithm for kernel sparse representation is developed in the current paper. In this framework, the input signal nonlinearly mapped into the feature space is sparsely represented based on a ...
    • Recurrent Neural Networks for Artifact Correction in HRV Data During Physical Exercise 

      Svane, Jakob; Wiktorski, Tomasz; Ørn, Stein; Eftestøl, Trygve Christian (Peer reviewed; Journal article, 2023)
      In this paper, we propose the use of recurrent neural networks (RNNs) for artifact correction and analysis of heart rate variability (HRV) data. HRV can be a valuable metric for determining the function of the heart and ...
    • A Low-Cost Wireless Body Area Network for Human Activity Recognition in Healthy Life and Medical Applications 

      Demrozi, Florenc (Peer reviewed; Journal article, 2023)
      Moved by the necessity, also related to the ongoing COVID-19 pandemic, of the design of innovative solutions in the context of digital health, and digital medicine, Wireless Body Area Networks (WBANs) are more and more ...
    • Resource Allocation in Networking and Computing Systems: A Security and Dependability Perspective 

      Khan, Md Muhidul Islam; Nencioni, Gianfranco (Peer reviewed; Journal article, 2023)
      In recent years, there has been a trend to integrate networking and computing systems, whose management is getting increasingly complex. Resource allocation is one of the crucial aspects of managing such systems and is ...