• A novel strategy for solving the stochastic point location problem using a hierarchical searching scheme 

      Yazidi, Anis; Granmo, Ole-Christoffer; Oommen, John; Goodwin, Morten (Journal article; Peer reviewed, 2014)
      Stochastic point location (SPL) deals with the problem of a learning mechanism (LM) determining the optimal point on the line when the only input it receives are stochastic signals about the direction in which it should ...
    • A Queue Model for Reliable Forecasting of Future CPU Consumption 

      Hammer, Hugo Lewi; Yazidi, Anis; Bratterud, Alfred; Haugerud, Hårek; Feng, Boning (Journal article; Peer reviewed, 2017)
      Statistical queuing models are popular to analyze a computer systems ability to process different types requests. A common strategy is to run stress tests by sending artificial requests to the system. The rate and sizes ...
    • Achieving Connectivity between Wide Areas Through Self-Organising Robot Swarms using Embodied Evolution 

      Erik Aaron, Hansen; Nichele, Stefano; Yazidi, Anis; Haugerud, Hårek; Abolpour Mofrad, Asieh; Alcocer, Alex (Chapter; Peer reviewed, 2018)
      Abruptions to the communication infrastructuremight occur occasionally, where manual intervention by dedi-cated personnel is needed to fix the interruptions, restoring com-munication abilities. However, sometimes this can ...
    • Achieving Fair Load Balancing by Invoking a Learning Automata-based Two Time Scale Separation Paradigm 

      Yazidi, Anis; Hassan, Ismail; Hammer, Hugo Lewi; Oommen, John (IEEE Transactions on Neural Networks and Learning Systems;, Journal article; Peer reviewed, 2020-08-05)
      In this article, we consider the problem of load balancing (LB), but, unlike the approaches that have been proposed earlier, we attempt to resolve the problem in a fair manner (or rather, it would probably be more appropriate ...
    • Achieving Intelligent Traffic-aware Consolidation of Virtual Machines in a Data Center Using Learning Automata 

      Jobava, Akaki; Yazidi, Anis; Oommen, John; Begnum, Kyrre (Chapter; Peer reviewed, 2016)
      Cloud Computing (CC) is becoming increasingly pertinent and popular. A natural consequence of this is that many modern-day data centers experience very high internal traffic within the data centers themselves. The ...
    • Adaptive Pursuit Learning for Energy‐efficient Target Coverage in Wireless Sensor Networks 

      Upreti, Ramesh; Rauniyar, Ashish; Kunwar, Jeevan; Haugerud, Hårek; Engelstad, Paal E.; Yazidi, Anis (Concurrency and Computation: Practice and Experience; e5975, Journal article; Peer reviewed, 2020-08-25)
      With the proliferation of technologies such as wireless sensor networks (WSNs) and the Internet of things (IoT), we are moving towards the era of automation without any human intervention. Sensors are the principal components ...
    • Advanced passive operating system fingerprinting using machine learning and deep learning 

      Hagos, Desta Haileselassie; Løland, Martin V.; Yazidi, Anis; Kure, Øivind; Engelstad, Paal E. (International Conference on Computer Communications and Networks (ICCCN); 2020 29th International Conference on Computer Communications and Networks (ICCCN), Journal article; Peer reviewed, 2020-09-30)
      Securing and managing large, complex enterprise network infrastructure requires capturing and analyzing network traffic traces in real-time. An accurate passive Operating System (OS) fingerprinting plays a critical role ...
    • Affinity Aware-Scheduling of Live Migration of Virtual Machines Under Maintenance Scenarios. 

      Yazidi, Anis; Ung, Frederik; Haugerud, Hårek; Begnum, Kyrre Matthias (Proceedings of the IEEE Symposium on Computers and Communications;2019 IEEE Symposium on Computers and Communications (ISCC), Conference object; Peer reviewed; Chapter, 2019)
      During maintenance and disaster recovery scenarios, Virtual Machine (VM) inter-site migrations usually take place over limited bandwidth–typically Wide Area Network (WAN)–which is highly affected by the amount of inter-VM ...
    • An aggregation approach for solving the non-linear fractional equality Knapsack problem 

      Yazidi, Anis; Jonassen, Tore Møller; Herrera-Viedma, Enrique (Expert systems with applications;Volume 110, 15 November 2018, Journal article; Peer reviewed, 2018-06-15)
      In this paper, we present an optimal, efficient and yet simple solution to a class of the deterministic non-linear fractional equality knapsack (NEFK) problem — a substantial resource allocation problem. The solution is shown ...
    • An inhomogeneous Hidden Markov model for efficient virtual machine placement in a cloud computing enviroment 

      Hammer, Hugo Lewi; Yazidi, Anis; Begnum, Kyrre (Journal article; Peer reviewed; Journal article, 2016-09-19)
      In a cloud environment virtual machines are created with different purposes like providing users with computers, handling web traffic etc. A virtual machine is created in such a way that a user will not notice any ...
    • An Analysis of Data Production Based on the Consistency of Decision Matrices 

      Sahin, Bekir; Yazidi, Anis; Roman, Dumitru; Uddin, Md Zia; Soylu, Ahmet (Lecture Notes in Networks and Systems;Volume 307, Peer reviewed; Journal article, 2021-08-24)
      Multi-criteria decision making methods are used to solve numerous problems related to several disciplines such as engineering, management and business. Consistency of a decision making application is of crucial importance ...
    • Analyzing automated activity and social deception on Twitter during the 2021 Norwegian election 

      Aune, Sverre Øystein (ACIT;2022, Master thesis, 2022)
      The growing concern of fake news and social bots as threats to democracy leaves society with motivation to investigate and research its presence. In this thesis, we look into social bot research and try to understand the ...
    • “Anti-Bayesian” Flat and Hierarchical Clustering Using Symmetric Quantiloids 

      Yazidi, Anis; Hammer, Hugo Lewi; Oommen, John (Chapter; Peer reviewed; Journal article, 2016)
      A myriad of works has been published for achieving data clustering based on the Bayesian paradigm, where the clustering sometimes resorts to Naïve-Bayes decisions. Within the domain of clustering, the Bayesian principle ...
    • “Anti-Bayesian” flat and hierarchical clustering using symmetric quantiloids 

      Hammer, Hugo Lewi; Yazidi, Anis; Oommen, John (Journal article; Peer reviewed, 2017)
      A Pattern Recognition (PR) system that does not involve labelled samples requires the clustering of the samples into their respective classes before the training and testing can be achieved. All of the reported clustering ...
    • Artificial intelligence in dry eye disease 

      Storås, Andrea Marheim; Strumke, Inga; Riegler, Michael Alexander; Grauslund, Jakob; Hammer, Hugo Lewi; Yazidi, Anis; Halvorsen, Pål; Gundersen, Kjell Gunnar; Utheim, Tor Paaske; Jackson, Catherine Joan (The ocular surface;Volume 23, January 2022, Peer reviewed; Journal article, 2021-12-01)
      Dry eye disease (DED) has a prevalence of between 5 and 50%, depending on the diagnostic criteria used and population under study. However, it remains one of the most underdiagnosed and undertreated conditions in ophthalmology. ...
    • Artificial intelligence in the fertility clinic: status, pitfalls and possibilities 

      Riegler, Michael Alexander; Stensen, Mette Haug; Witczak, Oliwia; Andersen, Jorunn Marie; Hicks, Steven; Hammer, Hugo Lewi; Delbarre, Erwan; Halvorsen, Pål; Yazidi, Anis; Holst, Nicolai; Haugen, Trine B. (Human Reproduction;Volume 36, Issue 9, Peer reviewed; Journal article, 2021-07-29)
      In recent years, the amount of data produced in the field of assisted reproduction technology [ART] has increased exponentially. The diversity of data is large, ranging from videos to tabular data. At the same time, ...
    • Automatic security classification by machine learning for cross-domain information exchange 

      Hammer, Hugo Lewi; Kongsgård, Kyrre Wahl; Yazidi, Anis; Bai, Aleksander; Nordbotten, Nils Agne; Engelstad, Paal E. (MILCOM IEEE Military Communications Conference;, Journal article; Peer reviewed, 2015)
      Cross-domain information exchange is necessary to obtain information superiority in the military domain, and should be based on assigning appropriate security labels to the information objects. Most of the data found ...
    • Autonomous configuration of network parameters in operating systems using evolutionary algorithms 

      Gembala, Bartosz Gembala; Yazidi, Anis; Haugerud, Hårek; Nichele, Stefano (Proceedings of the 2018 Conference on Research in Adaptive and Convergent Systems;, Chapter; Peer reviewed, 2018)
      By default, the Linux network stack is not configured for highspeed large file transfer. The reason behind this is to save memory resources. It is possible to tune the Linux network stack by increasing the network buffers ...
    • Balanced difficulty task finder: an adaptive recommendation method for learning tasks based on the concept of state of flow 

      Yazidi, Anis; Abolpour Mofrad, Asieh; Goodwin, Morten; Hammer, Hugo Lewi; Arntzen, Erik (Cognitive Neurodynamics;14, Journal article; Peer reviewed, 2020-08-27)
      An adaptive task difficulty assignment method which we reckon as balanced difficulty task finder (BDTF) is proposed in this paper. The aim is to recommend tasks to a learner using a trade-off between skills of the learner and ...
    • Building domain specific sentiment lexicons combining information from many sentiment lexicons and a domain specific corpus 

      Hammer, Hugo Lewi; Yazidi, Anis; Bai, Aleksander; Engelstad, Paal E. (Computer Science and Its Applications: 5th IFIP TC 5 International Conference, CIIA 2015, Saida, Algeria, May 20-21, 2015, Proceedings;, Peer reviewed; Chapter, 2015)
      Most approaches to sentiment analysis requires a sentiment lexicon in order to automatically predict sentiment or opinion in a text. The lexicon is generated by selecting words and assigning scores to the words, and the ...