Now showing items 81-100 of 415

    • Data Analysis Techniques for Smart Nudging 

      Dhanasekaran, Seshathiri; Andersen, Anders; Karlsen, Randi; Håkansson, Anne (Conference object; Konferansebidrag, 2021)
      <p>Nudge principles and techniques are significant in communications, marketing, and groups’ motivation to improve personal health, wealth, and well-being. We make numerous decisions in online situations. People’s health and well-being have garnered widespread interest and concern in this wearable’s age. Smart nudging is defined as “digital nudging, where the guidance of user behavior is tailored ...
    • UX-based personalization of timed media experiences 

      Arntzen, Ingar M; Borch, Njål Trygve (Conference object; Konferansebidrag, 2021)
      A client-side approach brings great opportunities for flexible personalization of timed media experiences. This, turns it into a challenge of UX development. However, UX development does not support time-driven rendering or shared interactivity, which are required by media related scenarios. Moreover, UX development is already quite complicated, so adding support for timed rendering and shared ...
    • Pedagogical Perspectives of Interdisciplinary Teaching and Research: An Energy System Modelling Outlook in Relation to Energy Informatics 

      Bordin, Chiara; Mishra, Sambeet; Benth, Fred Espen (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-08-02)
      The purpose of this paper is to present and discuss pedagogical frameworks and approaches to developing, delivering, and evaluating a new interdisciplinary course within the domain of energy informatics at both Master’s and PhD levels. This study is needed because many papers on sustainable energy engineering education concentrate on course content but provide very little information on the ...
    • Single image dehazing for a variety of haze scenarios using back projected pyramid network 

      Singh, Ayush; Bhave, Ajay; Prasad, Dilip K. (Conference object; Konferansebidrag, 2020)
      Learning to dehaze single hazy images, especially using a small training dataset is quite challenging. We propose a novel generative adversarial network architecture for this problem, namely back projected pyramid network (BPPNet), that gives good performance for a variety of challenging haze conditions, including dense haze and inhomogeneous haze. Our architecture incorporates learning of multiple ...
    • GEMM-eMFIS (FRI/E): A Novel General Episodic Memory Mechanism for Fuzzy Neural Networks 

      Pang, SW; Quek, Chai; Prasad, Dilip K. (Conference object; Konferansebidrag, 2020)
      In fields such as finance, medicine, engineering, and science, making real-time predictions during transient periods characterized by sudden and large changes is a hard challenge for machine learning. Humans keep memory of these transient events, abstractly learn the most relevant rules and reuse them when similar events occur, which stems from episodic memory that allows storage and recall of similar ...
    • Trusted Computing on Privacy Sensitive Data with Diggi 

      Gjerdrum, Anders Tungeland; Pettersen, Robert; Johansen, Håvard D.; Van Renesse, Robbert; Johansen, Dag (Conference object; Konferansebidrag, 2017)
    • Usefulness of Heat Map Explanations for Deep-Learning-Based Electrocardiogram Analysis 

      Storås, Andrea; Andersen, Ole Emil; Lockhart, Sam; Thielemann, Roman; Gnesin, Filip; Thambawita, Vajira L B; Hicks, Steven; Kanters, Jørgen K.; Strumke, Inga; Halvorsen, Pål; Riegler, Michael (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-07-11)
      Deep neural networks are complex machine learning models that have shown promising results in analyzing high-dimensional data such as those collected from medical examinations. Such models have the potential to provide fast and accurate medical diagnoses. However, the high complexity makes deep neural networks and their predictions difficult to understand. Providing model explanations can be a way ...
    • CSP at the Cyber-Physical Edge 

      Michalik, Lukasz Sergiusz; Murphy, Michael J.; Bjørndalen, John Markus; Anshus, Otto (Chapter; Bokkapittel, 2019)
      Today, to do ground-based in-situ observations of the arctic tundra, researchers carry wild life cameras and other observation units into the field, manually configure the devices while on the arctic tundra, and fetch the collected data several months later. This approach does not scale. Instead, observing and reporting of data must be automated using a distributed wireless network of autonomous ...
    • GridHTM: Grid-Based Hierarchical Temporal Memory for Anomaly Detection in Videos 

      Monakhov, Vladimir; Thambawita, Vajira L B; Halvorsen, Pål; Riegler, Michael (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-02-13)
      The interest in video anomaly detection systems that can detect different types of anomalies, such as violent behaviours in surveillance videos, has gained traction in recent years. The current approaches employ deep learning to perform anomaly detection in videos, but this approach has multiple problems. For example, deep learning in general has issues with noise, concept drift, explainability, ...
    • MRNG: Accessing Cosmic Radiation as an Entropy Source for a Non-Deterministic Random Number Generator 

      Kutschera, Stefan; Slany, Wolfgang; Ratschiller, Patrick; Gursch, Sarina; Dagenborg, Håvard (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-05-26)
      Privacy and security require not only strong algorithms but also reliable and readily available sources of randomness. To tackle this problem, one of the causes of single-event upsets is the utilization of a non-deterministic entropy source, specifically ultra-high energy cosmic rays. An adapted prototype based on existing muon detection technology was used as the methodology during the experiment ...
    • Fit-Twin: A Digital Twin of a User with Wearables and Context as Input for Health Promotion 

      Sulaiman, Muhammad; Håkansson, Anne; Karlsen, Randi (Journal article; Tidsskriftartikkel; Peer reviewed, 2023)
      Digital health contributes to health promotion by empowering the user with the holistic view of their health. Health promotion is to enable the user to take control over their health. The availability of wearables has contributed to the shift in healthcare, that is more connected, predictive, and proactive. Proactive in healthcare is to predict and prevent a situation, beforehand. This shift in ...
    • Experimental probe into an automative engine run on waste cooking oil biodiesel blend at varying engine speeds 

      Biswakarma, Keshab; Sarmah, Pranjal; Paramasivam, Prabhu; Dhanasekaran, Seshathiri; Kumar Yadav, Surendra; Kumar, Virendra (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-04-13)
      The present work attempts to evaluate the performance of an automotive diesel engine run on waste cooking oil biodiesel (WCO) blend at variable engine speeds. The composition of the blend (B40) used in the study is 40% WCO and 60% diesel by volume and the engine used for the experimentation is a naturally aspirated, watercooled and direct injection type having a compression ratio of 18:1. The ...
    • Unsupervised and supervised learning for the reliability analysis of complex systems 

      Gámiz, María Luz; Navas-Gómez, Fernando; Nozal Cañadas, Rafael; Raya-Miranda, Rocío (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-03-18)
      In this paper, a strategy to deal with high-dimensional reliability systems with multiple correlated components is proposed. The goal is to construct a state function that enables the classification of the states of components in one of two categories, that is, failure and operative, in case of dealing with a large number of units in the system. To this end, it is proposed a new algorithm that ...
    • The third country problem under the GDPR: enhancing protection of data transfers with technology 

      Juliussen, Bjørn Aslak; Kozyri, Elisavet; Johansen, Dag; Rui, Jon Petter (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-07-19)
      The overall objective of the General Data Protection Regulation (GDPR)1 is two-fold: To contribute to the protection of privacy and personal data and to promote the free flow of personal data within the protected area2 through uniform regulations and homogenized interpretations of those regulations.<p> <p>If a controller or processor in the protected area (the exporter) transfers personal data ...
    • An investigation of combined effect of infill pattern, density, and layer thickness on mechanical properties of 3D printed ABS by fused filament fabrication 

      Agrawal, Anant Prakash; Kumar, Virendra; Kumar, Jitendra; Paramasivam, Prabhu; Dhanasekaran, Seshathiri; Prasad, Lalta (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-05-23)
      Additive manufacturing technology and its benefits have a significant impact on different industrial applications. The 3D printing technologies help manufacture lightweight intricate geometrical designs with enhanced strengths. The present study investigates the blended effects of previously recommended parameters of different infill patterns (line, triangle, and concentric) and infill densities ...
    • Analyzing Mitochondrial Morphology Through Simulation Supervised Learning 

      Punnakkal, Abhinanda Ranjit; Godtliebsen, Gustav; Somani, Ayush; Acuna Maldonado, Sebastian Andres; Birgisdottir, Åsa birna; Prasad, Dilip K.; Horsch, Alexander; Agarwal, Krishna (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-03-03)
      The quantitative analysis of subcellular organelles such as mitochondria in cell fluorescence microscopy images is a demanding task because of the inherent challenges in the segmentation of these small and morphologically diverse structures. In this article, we demonstrate the use of a machine learning-aided segmentation and analysis pipeline for the quantification of mitochondrial morphology in ...
    • Framework of Transactive Energy Market Strategies for Lucrative Peer-to-Peer Energy Transactions 

      Loganathan, Arun S.; Ramachandran, Vijayapriya; Perumal, Angalaeswari Sendraya; Dhanasekaran, Seshathiri; Lakshmaiya, Natrayan; Paramasivam, Prabhu (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-12-20)
      Leading to the enhancement of smart grid implementation, the peer-to-peer (P2P) energy transaction concept has grown dramatically in recent years allowing the end-users to successfully exchange their excess generation and demand in a more profitable way. This paper presents local energy market (LEM) architecture with various market strategies for P2P energy trading among a set of end-users ...
    • Method for Designing Semantic Annotation of Sepsis Signs in Clinical Text 

      Yan, Melissa Y.; Gustad, Lise Tuset; Høvik, Lise Husby; Nytrø, Øystein (Chapter; Bokkapittel, 2023)
      Annotated clinical text corpora are essential for machine learning studies that model and predict care processes and disease progression. However, few studies describe the necessary experimental design of the annotation guideline and annotation phases. This makes replication, reuse, and adoption challenging. Using clinical questions about sepsis, we designed a semantic annotation guideline to ...
    • Selection of Response Reduction Factor Considering Resilience Aspect 

      Prasanth, S.; Ghosh, Goutam; Gupta, Praveen Kumar; Kumar, Virendra; Paramasivam, Prabhu; Dhanasekaran, Seshathiri (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-02-27)
      The selection of an adequate response reduction factor (R) in the seismic design of a reinforced concrete building is critical to the building’s seismic response. To construct a robust structure, the R factor should be chosen based on the building’s resilience performance. Since no background was provided for the selection of R factors, the study focuses on the right selection of R factors in relation ...
    • A Telemedicine System Intervention for Patients With Type 1 Diabetes: Pilot Feasibility Crossover Intervention Study 

      Vlasakova, Martina; Muzik, Jan; Holubova, Anna; Fiala, Dominik; Årsand, Eirik; Urbanová, Jana; Žďárská, Denisa Janíčková; Brabec, Marek; Brož, Jan (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-04-28)
      Background: Today’s diabetes-oriented telemedicine systems can gather and analyze many parameters like blood glucose levels, carbohydrate intake, insulin doses, and physical activity levels (steps). Information collected can be presented to patients in a variety of graphical outputs. Despite the availability of several technical means, a large percentage of patients do not reach the goals established ...