• 5G Multi-Access Edge Computing: A Survey on Security, Dependability, and Performance 

      Nencioni, Gianfranco; Garroppo, Rosario G.; Olimid-Nencioni, Ruxandra-Florentina (Peer reviewed; Journal article, 2023)
      The Fifth Generation (5G) of mobile networks offers new and advanced services with stricter requirements. Multi-access Edge Computing (MEC) is a key technology that enables these new services by deploying multiple devices ...
    • 5G Network Slicing: A Security Overview 

      Olimid, Ruxandra; Nencioni, Gianfranco (Peer reviewed; Journal article, 2020-05)
      The fifth-generation (5G) of cellular networks is currently under deployment by network operators, and new 5G end-user devices are about to be commercialized by many manufacturers. This is just a first step in the 5G's ...
    • Advancing Deep Learning to Improve Upstream Petroleum Monitoring 

      Heghedus, Cristina Viorica; Shchipanov, Anton; Chunming, Rong (Peer reviewed; Journal article, 2019)
      Data analytics is rapidly growing field in both academia and industry dealing with processing and interpreting large and complex data sets. It has got already many successful applications via advancing machine (ML) and ...
    • Automatic Cardiac Rhythm Classification With Concurrent Manual Chest Compressions 

      Isasi, Iraia; Irusta, Unai; Rad, Ali Bahrami; Aramendi, Elisabete; Zabihi, Morteza; Eftestøl, Trygve Christian; Kramer-Johansen, Jo; Wik, Lars (Journal article; Peer reviewed, 2019-08)
      Electrocardiogram (EKG) based classification of out-of-hospital cardiac arrest (OHCA) rhythms is important to guide treatment and to retrospectively elucidate the effects of therapy on patient response. OHCA rhythms are ...
    • Automatic diagnostic tool for predicting cancer grade in bladder cancer patients using deep learning 

      Wetteland, Rune; Engan, Kjersti; Eftestøl, Trygve Christian; Kvikstad, Vebjørn; Janssen, Emiel; Tøssebro, Erlend; Lillesand, Melinda (Peer reviewed; Journal article, 2021-08)
      The most common type of bladder cancer is urothelial carcinoma, which is among the cancer types with the highest recurrence rate and lifetime treatment cost per patient. Diagnosed patients are stratified into risk groups, ...
    • Building Precision: Efficient Encoder-Decoder Networks for Remote Sensing Based on Aerial RGB and LiDAR Data 

      Sulaiman, Muhammad; Finnesand, Erik; Farmanbar, Mina; Belbachir, Ahmed Nabil; Rong, Chunming (Peer reviewed; Journal article, 2024-04)
      Precision in building delineation plays a pivotal role in population data analysis, city management, policy making, and disaster management. Leveraging computer vision technologies, particularly deep learning models for ...
    • CrossTransUnet: A new computationally inexpensive tumor segmentation model for brain MRI 

      Anaya-Isaza, Andres; Mera Jiménez, Leonel; Fernandez Quilez, Alvaro (Peer reviewed; Journal article, 2023)
      Brain tumors are usually fatal diseases with low life expectancies due to the organs they affect, even if the tumors are benign. Diagnosis and treatment of these tumors are challenging tasks, even for experienced physicians ...
    • 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 ...
    • Defensive Distillation-based Adversarial Attack Mitigation Method for Channel Estimation using Deep Learning Models in Next-Generation Wireless Networks 

      Catak, Ferhat Özgur; Kuzlu, Murat; Catak, Evren; Cali, Umit; Guler, Ozgur (Peer reviewed; Journal article, 2022-09)
      Future wireless networks (5G and beyond), also known as Next Generation or NextG, are the vision of forthcoming cellular systems, connecting billions of devices and people together. In the last decades, cellular networks ...
    • The devil is in the details: Whole Slide Image acquisition and processing for artifacts detection, color variation, and data augmentation: A review. 

      Kanwal, Neel; Pérez-Bueno, Fernando; Schmidt, Arne; Engan, Kjersti; Molina, Rafael (Peer reviewed; Journal article, 2022)
      Whole Slide Images (WSI) are widely used in histopathology for research and the diagnosis of different types of cancer. The preparation and digitization of histological tissues leads to the introduction of artifacts and ...
    • Distributed Ledger Technology Based Integrated Healthcare Solution for Bangladesh 

      ISLAM, MD. ARIFUL; ISLAM, MD. ANTONIN; JACKY, MD. AMZAD HOSSAIN; AL-AMIN, MD.; MIAH, MD. SAEF ULLAH; Khan, Md Muhidul Islam; HOSSAIN, MD. IQBAL (Peer reviewed; Journal article, 2023)
      Healthcare data is highly sensitive and must be safeguarded. Personal and sensitive data, such as names and addresses, is stored in Encrypted Electronic Health Records (EHRs). This paper proposes a Blockchain-based distributed ...
    • Enhancing Safety and Privacy in Industry 4.0: The ICE Laboratory Case Study 

      Cunico, Federico; Aldegheri, Stefano; Avogaro, Andrea; Boldo, Michele; Bombieri, Nicola; Capogrosso, Luigi; Caputo, Ariel; Carra, Damiano; Centomo, Stefano; Cheng, Dong Seon; Cinquetti, Ettore; Cristani, Marco; Marchi, Mirco De; Demrozi, Florenc; Emporio, Marco; Fummi, Franco; Geretti, Luca; Germiniani, Samuele; Giachetti, Andrea; Girella, Federico; Martini, Enrico; Menegaz, Gloria; Muijs, Niek; Paci, Federica; Panato, Marco; Pravadelli, Graziano; Quintarelli, Elisa; Siviero, Ilaria; Storti, Silvia Francesca; Tadiello, Carlo; Turetta, Cristian; Villa, Tiziano; Zannone, Nicola; Quaglia, Davide (Peer reviewed; Journal article, 2024)
      he revolutionary technologies behind Industry 4.0 have opened a new era for manufacturing: connected and autonomous machines, collaborative robotics, and monitoring techniques are spreading to increase productivity and ...
    • An Ensemble Approach for Multi-Step Ahead Energy Forecasting of Household Communities 

      Mehdipourpirbazari, Aida; Sharma, Ekanki; Chakravorty, Antorweep; Elmenreich, Wilfreid; Chunming, Rong (Peer reviewed; Journal article, 2021)
      This paper addresses the estimation of household communities' overall energy usage and solar energy production, considering different prediction horizons. Forecasting the electricity demand and energy generation of communities ...
    • Extracting Petri Modules From Large and Legacy Petri Net Models 

      Davidrajuh, Reggie (Peer reviewed; Journal article, 2020)
      Petri nets, even though very useful for modeling of discrete event systems, suffer from some weaknesses such as huge size, huge state space, and slow in simulation. Due to the huge state space, model checking a Petri net ...
    • Flexible and Lightweight Mitigation Framework for Distributed Denial-of-Service Attacks in Container-Based Edge Networks using Kubernetes 

      Koksal, Sarp; Catak, Ferhat Özgur; Dalveren, Yaser (Peer reviewed; Journal article, 2024)
      Mobile Edge Computing (MEC) has a significant potential to become more prevalent in Fifth Generation (5G) networks, requiring resource management that is lightweight, agile, and dynamic. Container-based virtualization ...
    • Functional Failure Criticality Assessment and Control of Power Distribution Systems: Failure Prioritization Using AHP 

      Attanayake, Sakura; Ratnayake Mudiyanselage, Chandima; Markeset, Tore (Peer reviewed; Journal article, 2024)
      Power distribution systems consist of critical infrastructure with various categories of assets that require rigorous maintenance programs to ensure their reliability and performance for all stakeholders. Maintenance program ...
    • 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 ...
    • Optimizing Document Classification: Unleashing the Power of Genetic Algorithms 

      Mustafa, Ghulam; Rauf, Abid; Al-Shamayleh, Ahmad Sami; Sulaiman, Muhammad; Afzal, Muhammad Tanvir; Akhunzada, Adnan (Peer reviewed; Journal article, 2023)
      Many individuals, including researchers, professors, and students, encounter difficulties when searching for scholarly documents, papers, and journals within a specific domain. Consequently, scholars have begun to focus ...
    • PSO-GA Based Resource AllocationStrategy for Cloud-Based SoftwareServices with Workload-Time Windows 

      Chen, Zheyi; Yang, Lijian; Huang, Yinhao; Chen, Xing; Zheng, Xianghan; Chunming, Rong (Peer reviewed; Journal article, 2020)
      Cloud-based software services necessitate adaptive resource allocation with the promise of dynamic resource adjustment for guaranteeing the Quality-of-Service (QoS) and reducing resource costs. However, it is challenging ...
    • Radar Emitter Localization Based on Multipath Exploitation Using Machine Learning 

      Catak, Ferhat Özgur; Imran, Md Abdullah Al; Dalveren, Yaser; Yildiz, Beytullah; Kara, Ali (Peer reviewed; Journal article, 2024)
      In this study, a Machine Learning (ML)-based approach is proposed to enhance the computational efficiency of a particular method that was previously proposed by the authors for passive localization of radar emitters based ...