Blar i Publikasjoner fra CRIStin - SINTEF AS på tidsskrift "IEEE Access"

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    • Accumulation and Prioritization of Architectural Debt in Three Companies Migrating to Microservices 

      Soares de Toledo, Saulo; Martini, Antonio; Nguyen, Phu Hong; Sjøberg, Dag (Peer reviewed; Journal article, 2022)
      Many companies migrate to microservices because they help deliver value to customers quickly and continuously. However, like any architectural style, microservices are prone to architectural technical debt (ATD), which can ...

    • A data-driven approach for twitter hashtag recommendation 

      Belhadi, Asma; Djenouri, Youcef; Lin, Jerry Chun-Wei; Cano, Alberto (Peer reviewed; Journal article, 2020)
      This paper addresses the hashtag recommendation problem using high average-utility pattern mining. We introduce a novel framework called PM-HRec (Pattern Mining for Hashtag Recommendation). It consists of two main stages. ...

    • A Data-Driven Approach for Twitter Hashtag Recommendation 

      Djenouri, Youcef; Asma, Belhadi; Chun-Wei Lin, Jerry; Alberto, Cano (Peer reviewed; Journal article, 2020)
      This paper addresses the hashtag recommendation problem using high average-utility pattern mining. We introduce a novel framework called PM-HRec (Pattern Mining for Hashtag Recommendation). It consists of two main stages. ...

    • Efficient Chain Structure for High-Utility Sequential Pattern Mining 

      Lin, Jerry Chun-Wei; Li, Yuanfa; Fournier-Viger, Philippe; Djenouri, Youcef; Zhang, Ji (Peer reviewed; Journal article, 2020)
      High-utility sequential pattern mining (HUSPM) is an emerging topic in data mining, which considers both utility and sequence factors to derive the set of high-utility sequential patterns (HUSPs) from the quantitative ...

    • Evolution of Software Testing Strategies and Trends: Semantic Content Analysis of Software Research Corpus of the Last 40 Years 

      Gurcan, Fatih; Dalveren, Gonca Gokce Menekse; Cagiltay, Nergiz Ercil; Roman, Dumitru; Soylu, Ahmet (Peer reviewed; Journal article, 2022)
      From the early days of computer systems to the present, software testing has been considered as a crucial process that directly affects the quality and reliability of software-oriented products and services. Accordingly, ...

    • Exploring Pattern Mining Algorithms for Hashtag Retrieval Problem 

      Belhadi, Asma; Djenouri, Youcef; Lin, Jerry Chun-Wei; Zhang, Chongsheng; Cano, Alberto (Peer reviewed; Journal article, 2020)
      Hashtag is an iconic feature to retrieve the hot topics of discussion on Twitter or other social networks. This paper incorporates the pattern mining approaches to improve the accuracy of retrieving the relevant information ...

    • Exploring Pattern Mining Algorithms for Hashtag Retrieval Problem 

      Djenouri, Youcef; Asma, Belhadi; Jerry, Chun-Wei Lin; Chongsheng, Zhang; Alberto, Cano (Peer reviewed; Journal article, 2020)
      Hashtag is an iconic feature to retrieve the hot topics of discussion on Twitter or other social networks. This paper incorporates the pattern mining approaches to improve the accuracy of retrieving the relevant information ...

    • FastPathology: An open-source platform for deep learning-based research and decision support in digital pathology 

      Pedersen, André; Valla, Marit; Bofin, Anna Mary; Perez de Frutos, Javier; Reinertsen, Ingerid; Smistad, Erik (Peer reviewed; Journal article, 2021)
      Deep convolutional neural networks (CNNs) are the current state-of-the-art for digital analysis of histopathological images. The large size of whole-slide microscopy images (WSIs) requires advanced memory handling to read, ...

    • GNSS Technology for Precise Positioning in CCAM: A Comparative Evaluation of Services 

      Schiess, Samuel; Berget, Gunhild Elisabeth; Arnesen, Petter; Brunes, Morten Taraldsten; Seter, Hanne; Muggerud, Astrid Marie Flattum (Peer reviewed; Journal article, 2023)
      Cooperative, connected, and automated mobility (CCAM) can lead to a significantly improved transport system by increasing safety and efficiency, and reducing emissions. To achieve the goal of fully automated mobility and ...

    • Investigating the Technological and Political Challenges of V2V Communication in Light of an Experimental Scenario Set Up 

      Arnesen, Petter; Dahl, Erlend; Hjelkrem, Odd Andre; Seter, Hanne (Peer reviewed; Journal article, 2021)
      The suggested benefits of automated vehicles are plentiful, but many of the benefits depend on connectivity with other vehicles and infrastructure to be useful to the society at large. This paper identifies two main research ...

    • Multichannel Residual Cues for Fine-Grained Classification in Wireless Capsule Endoscopy 

      Vats, Anuja; Raja, Kiran; Pedersen, Marius; Mohammed, Ahmed Kedir (Peer reviewed; Journal article, 2022)
      Early diagnosis of gastrointestinal pathologies leads to timely medical intervention and prevents disease development. Wireless Capsule Endoscopy (WCE) is used as a non-invasive alternative for gastrointestinal examination. ...

    • Ontology-Based Fault Tree Analysis Algorithms in a Fuzzy Environment for Autonomous Ships 

      Sahin, Bekir; Yazidi, Anis; Roman, Dumitru; Soylu, Ahmet (Peer reviewed; Journal article, 2021)
      This study deals with fault tree analysis algorithms based on an ontology-based approach in a fuzzy environment. We extend fuzzy fault tree analysis by embedding ontology-based fault tree structures. The ontology-based ...

    • Review and Alignment of Domain-Level Ontologies for Materials Science 

      de Baas, Anne F; Del Nostro, Pierluigi; Friis, Jesper; Ghedini, Emanuele; Goldbeck, Gerhard; Paponetti, Ilaria Maria; Pozzi, Andrea; Sarkar, Arkopaul; Yang, Lan; Zaccarini, Francesco Antonio; Toti, Daniele (Peer reviewed; Journal article, 2023)
      The growing complexity and interdisciplinary nature of Materials Science research demand efficient data management and exchange through structured knowledge representation. Domain-Level Ontologies (DLOs) for Materials ...

    • Taming an autonomous surface vehicle for path following and collision avoidance using deep reinforcement learning 

      Meyer, Eivind; Robinson, Haakon; Rasheed, Adil; San, Omer (Peer reviewed; Journal article, 2020)
      In this article, we explore the feasibility of applying proximal policy optimization, a state-of-the-art deep reinforcement learning algorithm for continuous control tasks, on the dual-objective problem of controlling an ...

    • A Tertiary Review on Blockchain and Sustainability With Focus on Sustainable Development Goals 

      Jiang, Shanshan; Jakobsen, Kine Charlotte; Bueie, Jonas; Li, Jingyue; Haro, Peter (Peer reviewed; Journal article, 2022)
      Sustainable development is crucial to securing the future of humanity. Blockchain as a disruptive technology and a driver for social change has exhibited great potential to promote sustainable practices and help organizations ...

    • Ultra-Wideband Radar-Based Activity Recognition Using Deep Learning 

      Noori, Farzan Majeed; Uddin, Md Zia; Tørresen, Jim (Peer reviewed; Journal article, 2021)
      With recent advances in the field of sensing, it has become possible to build better assistive technologies. This enables the strengthening of eldercare with regard to daily routines and the provision of personalised care ...

    • When the Decomposition Meets the Constraint Satisfaction Problem 

      Djenouri, Youcef; Djenouri, Djamel; Habbas, Zineb; Lin, Jerry Chun-Wei; Michalak, Tomasz P.; Cano, Alberto (Peer reviewed; Journal article, 2020)
      This paper explores the joint use of decomposition methods and parallel computing for solving constraint satisfaction problems and introduces a framework called Parallel Decomposition for Constraint Satisfaction Problems ...