Blar i Department of Electrical and Computer Engineering (TN-IDE) på tittel

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    • Extended Overview of the Living Labs for Information Retrieval Evaluation (LL4IR) CLEF Lab 2015 

      Schuth, Anne; Balog, Krisztian; Kelly, Liadh (Journal article, 2015)
      In this extended overview paper we discuss the first Living Labs for Information Retrieval Evaluation (LL4IR) lab which was held at CLEF 2015. The idea with living labs is to provide a benchmarking platform for researchers ...

    • Extending enterprise architecture models for cloud computing 

      Pantiuchovas, Dmitrijus (Masteroppgave/UIS-TN-IDE/2012;, Master thesis, 2012)
      The new wave of technology changes has introduced cloud computing. For an enterprise this innovation can bring great cost savings as well as risks. Therefore a special analysis process shall be done before the decision is ...

    • Extending the Snarl File Repair Component for Distributed Storage Systems 

      Stavnes, Eivind; Urdal, Daniel (Master thesis, 2021)
      This thesis extends the Snarl file repair component for distributed storage systems, and evaluates extensions. Snarl is an application using alpha entanglement codes to improve recovery rates of content stored in distributed ...

    • Extending the Snarl File Repair Component for Distributed Storage Systems 

      Stavnes, Eivind; Urdal, Daniel (Master thesis, 2021)
      This thesis extends the Snarl file repair component for distributed storage systems, and evaluates extensions. Snarl is an application using alpha entanglement codes to improve recovery rates of content stored in distributed ...

    • An Extensible Framework for Implementing and Validating Byzantine Fault-tolerant Protocols 

      Gogada, Hanish; Jehl, Leander; Meling, Hein; Olsen, John Ingve (Chapter, 2023-06)
      HotStuff is a Byzantine fault-tolerant state machine replication protocol that incurs linear communication costs to achieve consensus. This linear scalability promoted the protocol to be adopted as the consensus mechanism ...

    • Extracting coronary arteries in angiographic images 

      Moene, Alexander Kvale (Masteroppgave/UIS-TN-IDE/2017;, Master thesis, 2017-07-15)
      This master thesis has as propose to extract coronary arteries form angiographic video. With several stability issues with the easy to implement established functions in the time domain and other methods that is far too ...

    • 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 ...

    • Fact Checking using Knowledge Bases 

      Khurshid Adil; Ramesh Apoorva (Master thesis, 2022)
      In today’s society, the spread of incorrect information is becoming an increasingly serious issue. Verifying information using unstructured data, such as a text corpus, can be difficult for all claims since they lack ...

    • Fact-Checking using Knowledge bases 

      Ramesh, Apoorva; Khurshid, Adil (Master thesis, 2022)
      In today's society, the spread of incorrect information is becoming an increasingly serious issue. Verifying information using unstructured data, such as a text corpus, can be difficult for all claims since they lack ...

    • Factors Affecting the Course of Resuscitation From Cardiac Arrest With Pulseless Electrical Activity in Children and Adolescents 

      Skogvoll, Eirik; Nordseth, Trond; Sutton, Robert M.; Eftestøl, Trygve Christian; Irusta, Unai; Aramendi, Elisabete; Niles, Dana E.; Nadkarni, Vinay M.; Berg, Robert A.; Abella, Benjamin S.; Kvaløy, Jan Terje (Peer reviewed; Journal article, 2020)
      Background: Although in-hospital pediatric cardiac arrests and cardiopulmonary resuscitation occur >15,000/year in the US, few studies have assessed which factors affect the course of resuscitation in these patients. We ...

    • Fairness and Ethics in AI 

      Chakravorty Antorweep (Bachelor thesis, 2021)
      As the complexity and capabilities of AI technologies continue to increase, they will continue to pose a risk for their users. In this thesis, different techniques have been reviewed to see how the current research proposes ...

    • Fairness and Interpretability in Machine Learning Models 

      Weinbach, Bjørn Christian (Master thesis, 2022)
      Machine Learning has become more and more prominent in our daily lives as the Information Age and Fourth industrial revolution progresses. Many of these machine learning systems are evaluated in terms of how accurately ...

    • Fake News Data Generation and Augmentation 

      Botnevik, Bjarte (Master thesis, 2021)
      Fake news is becoming an increasingly more significant problem in today's society, especially on social media. The fact-checking field in Data Science is becoming more and more popular as people want to solve this. However, ...

    • Fake News Detection A Deep Neural Network 

      Chennam Lakhsmikumar, Priyanka (Masteroppgave/UIS-TN-IDE/2019;, Master thesis, 2019-06-15)
      News is an important source of information for people.Identifying the inaccurate news is a difficult problem. Fake news, defined by the New York Times ”as a made-up story with an intention to deceive”, often for a secondary ...

    • Fast and Reliable Byzantine Fault Tolerance 

      Freeman, Eric (Masteroppgave/UIS-TN-IDE/2016;, Master thesis, 2016-06)
      Byzantine faults, or arbitrary faults, are difficult to handle due to their unknown nature. They include software errors, hardware errors, and malicious behavior. There are several algorithms which handle Byzantine faults ...

    • Fault-Tolerant Control Based on Virtual Actuator and Sensor for Discrete-Time Descriptor Systems 

      Wang, Ye; Rotondo, Damiano; Puig, Vicenç; Cembrano, Gabriela (Peer reviewed; Journal article, 2020)
      This article proposes a fault-tolerant control (FTC) strategy based on virtual actuator and sensor for discrete-time descriptor systems subject to actuator and sensor faults. The fault-tolerant closed-loop system, which ...

    • Feature extraction for exploring infarcted regions in perfusion CT images of the brain 

      Hovland, Eivind (Masteroppgave/UIS-TN-IDE/2018;, Master thesis, 2018-06-15)
      In Norway, over 15 000 people suffer from acute cerebral stroke annually, it is the leading cause of adult long-term severe disability and a significant reason for admission to nursing homes. In Norway it is a prominent ...

    • Federated Learning for Dementia Classification in a European Multicentre Dementia Study 

      Hesseberg, Ruben; Minne, Petter (Masteroppgave/UIS-TN-IDE/2020;, Master thesis, 2020-07-15)
      Every year around 10 million people are diagnosed with dementia worldwide. Higher life expectancy and population growth could inflate this number even further in the near future. Currently the diagnostic process of dementia ...

    • Field Telemetry Drilling Dataset Modeling with Multivariable Regression, Group Method Data Handling, Artificial Neural Network, and the Proposed Group-Method-Data-Handling-Featured Artificial Neural Network 

      Amir, Mohammad; Agonafir, Mesfin Belayneh (Peer reviewed; Journal article, 2024)
      This paper presents data-driven modeling and a results analysis. Group method data handling (GMDH), multivariable regression (MVR), artificial neuron network (ANN), and new proposed GMDH-featured ANN machine learning ...

    • Finding Clusters in Petri Nets An approach based on GPenSIM 

      Davidrajuh, Reggie; Krenczyk, Damian; Skolud, Bozena (Peer reviewed; Journal article, 2019)
      Graph theory provides some methods for finding clusters in networks. Clusters reflect the invisible grouping of the elements in a network. This paper presents a new method for finding clusters in networks. In this method, ...