• 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 ...
    • 5G-MEC Testbeds for V2X Applications 

      Wadatkar, Prachi Vinod; Garroppo, Rosario G.; Nencioni, Gianfranco (Peer reviewed; Journal article, 2023-05)
      Fifth-generation (5G) mobile networks fulfill the demands of critical applications, such as Ultra-Reliable Low-Latency Communication (URLLC), particularly in the automotive industry. Vehicular communication requires low ...
    • A secure user authentication protocol for sensor network in data capturing 

      Quan, Zhou; Chumning, Tan; Chunming, Rong; Xianghan, Zhen (Journal article; Peer reviewed, 2015-04)
      Sensor network is an important approach of data capturing. User authentication is a critical security issue for sensor networks because sensor nodes are deployed in an open and unattended environment, leaving them possible ...
    • Accountability Requirements in the Cloud Provider Chain 

      Jaatun, Martin Gilje; Tøndel, Inger Anne; Moe, Nils Brede; Cruzes, Daniela Soares; Bernsmed, Karin; Haugset, Børge (Journal article; Peer reviewed, 2018-04)
      In order to be responsible stewards of other people’s data, cloud providers must be accountable for their data handling practices. The potential long provider chains in cloud computing introduce additional accountability ...
    • Active Noise Control in the Offshore Industry 

      Mehus, Haakon (Masteroppgave/UIS-TN-IDE/2020;, Master thesis, 2020-06-29)
      Hearing damage among offshore workers has been a problem for many years, and it remains one of the most common disorders in this group. A proposal to use active noise control to improve the noise conditions has thus been ...
    • Adapt and Generalize Deep Learning Methods for Activity Recognition on Newborn Resuscitation Videos 

      Lapin, Håvard (Masteroppgave/UIS-TN-IDE/2020;, Master thesis, 2020-06-15)
      Low- and middle-income countries have nearly 99 % of deaths of children under 28 days. Complications during childbirths, such as birth asphyxia, account for most of these deaths. To prevent this, strengthening the quality ...
    • Advanced Deep Learning for Whale detection in VHR Satellite Images 

      Rabbani, Rabbir Bin (Masteroppgave/UIS-TN-IDE/2020;, Master thesis, 2020)
      With the use of very high resolution (VHR) satellite images we can locate whales. In this thesis, I have experimented with different advanced architectures in Deep Learning to detect whales in satellite images. I have also ...
    • Analyse og presentasjon av Mars rover data 

      Fjellheim, Markus (Masteroppgave/UIS-TN-IDE/2020;;, Master thesis, 2020-07-15)
      Space-crafts and their instruments tend to collect way more data on their missions than what can be transmitted back to earth in a timely manner. This leads to the need to prioritize what data is to be downloaded and what ...
    • 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 ...
    • Are you sure it’s an artifact? Artifact detection and uncertainty quantification in histological images 

      Kanwal, Neel; Lopez-Perez, Miguel; Kiraz, Umay; Zuiverloon, Tahlita C M; Molina, Rafael (Peer reviewed; Journal article, 2023)
      Modern cancer diagnostics involves extracting tissue specimens from suspicious areas and conducting histotechnical procedures to prepare a digitized glass slide, called whole slide image (WSI), for further examination. ...
    • ArXivDigest: A Living Lab for Personalized Scientific Literature Recommendation 

      Jekteberg, Øyvind; Gingstad, Kristian (Masteroppgave/UIS-TN-IDE/2020;, Master thesis, 2020-06-15)
      The purpose of this thesis is to explore different methods for recommending scientific literature to scientists and to explore different methods for doing topic extraction. We will update and use the already existing ...
    • Assistive Data Glove for Isolated Static Postures Recognition in American Sign Language Using Neural Network 

      Amin, Muhammad Saad; Rizvi, Syed Tahir Hussain; Mazzei, Alessandro; Anselma, Luca (Peer reviewed; Journal article, 2023)
      Sign language recognition is one of the most challenging tasks of today’s era. Most of the researchers working in this domain have focused on different types of implementations for sign recognition. These implementations ...
    • Attitude and Heading Reference System for a laboratory drilling rig control system 

      Alsaker-Haugen, Joakim Andrè (Masteroppgave/UIS-TN-IDE/2020;, Master thesis, 2020-07-13)
      This thesis describes the work done in contribution to the UiS Drillbotics 2020 drill rig design for the annual international Drillbotics competition. Drillbotic is a competition for universities to design and build a ...
    • Automated collection of multi-source spatial information for emergency management 

      Sandra, Moen (Masteroppgave/UIS-TN-IDE/2018;, Master thesis, 2018-06-22)
      Yearly influenza epidemics carries a tremendous societal cost and leads to a large loss of life and an immense strain on the national health care systems. People that become sick are less productive and the overall well-being ...
    • Automated Diagnosis of Prostate Cancer Using mpMRI Images: A Deep Learning Approach for Clinical Decision Support 

      Gavade, Anil B.; Nerli, Rajendra; Kanwal, Neel; Gavade, Priyanka A.; Pol, Shridhar Sunilkumar; Rizvi, Syed Tahir Hussain (Peer reviewed; Journal article, 2023)
      Prostate cancer (PCa) is a significant health concern for men worldwide, where early detection and effective diagnosis can be crucial for successful treatment. Multiparametric magnetic resonance imaging (mpMRI) has evolved ...
    • Automated test case generation for the Paxos single-decree protocol using a Coloured Petri Net model 

      Wang, Rui; Kristensen, Lars Michael; Meling, Hein; Stolz, Volker (Peer reviewed; Journal article, 2019-04)
      Implementing test suites for distributed software systems is a complex and time-consuming task due to the number of test cases that need to be considered in order to obtain high coverage. We show how a formal Coloured Petri ...
    • Automated test case generation for the Paxos single-decree protocol using a Coloured Petri Net model 

      Wang, Rui; Kristensen, Lars Michael; Meling, Hein; Stolz, Volker (Peer reviewed; Journal article, 2019-04)
      Implementing test suites for distributed software systems is a complex and time-consuming task due to the number of test cases that need to be considered in order to obtain high coverage. We show how a formal Coloured Petri ...
    • Automated Well Monitoring: Machine Learning and Web Application 

      Zhurda, Anisa (Masteroppgave/UIS-TN-IDE/2020;, Master thesis, 2020-06-15)
      The challenge within the oil and gas industry is that of complexity and therefore cost, specifically due to the tough working environments and delays/downtime . Therefore, digitization is proposed as a cost saving opportunity ...
    • 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 ...