Viser treff 21-40 av 627

    • Sport and Nutrition Digital Analysis: A Legal Assessment 

      Juliussen, Bjørn Aslak; Rui, Jon Petter; Johansen, Dag (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-03-29)
      This paper presents and evaluates legal aspects related to digital technologies applied in the elite soccer domain. Data Protection regulations in Europe clearly indicate that compliance-by-design is needed when developing and deploying such technologies. This is particularly true when health data is involved, but a complicating factor is that the distinction between what is health data or not is ...
    • Accurate Lightweight Calibration Methods for Mobile Low-Cost Particulate Matter Sensors 

      Jørstad, Per Martin; Wojcikowski, Marek; Cao, Tuan-Vu; Lepioufle, Jean-Marie; Wojtkiewicz, Krystian; Ha, Hoai Phuong (Chapter; Bokkapittel, 2023-09-05)
      <p>Monitoring air pollution is a critical step towards improving public health, particularly when it comes to identifying the primary air pollutants that can have an impact on human health. Among these pollutants, particulate matter (PM) with a diameter of up to 2.5 μm (or PM2.5) is of particular concern, making it important to continuously and accurately monitor pollution related to PM. The emergence ...
    • Sleep Monitoring with Wearable Sensor Data in an eCoach Recommendation System: A Conceptual Study with Machine Learning Approach 

      Chatterjee, Ayan; Prinz, Andreas; Pahari, Nibedita; Das, Jishnu; Riegler, Michael (Chapter; Bokkapittel, 2023-04-25)
      The collective effects of sleep loss and sleep disorders are correlated with many adverse health consequences, including increased risk of high blood pressure, obesity, diabetes, depressive state, and cardiovascular symptoms. Research in eHealth can provide methods to enrich personal health care with information and communication technologies (ICTs). An eCoach system may allow people to manage a ...
    • Multi-Agent Collision Avoidance Method Using Fuzzy Risk Estimation and Information Sharing in Unknown Environments 

      Håkansson, Anne Eva Margareta; Karlsen, Randi; Bremdal, Bernt Arild; Dundar, Yigit Can (Chapter; Bokkapittel, 2023-09-22)
      Automated vehicles within Industry 4.0 are used as logistics units where they can move resources from one place to another safely and efficiently. The automated vehicles can be tasked to work in unknown environments where collision-free navigation is challenging due to uncertainty and lack of environmental information. Collisions can damage equipment and may even cause harm to human workers sharing ...
    • Dataset of motivational factors for using mobile health applications and systems 

      Henriksen, André; Issom, David-Zacharie; Woldaregay, Ashenafi Zebene; Pfuhl, Gerit; Årsand, Eirik; Sato, Keiichi; Hartvigsen, Gunnar (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-09-16)
      We created and carried out a cross-sectional anonymous structured questionnaire on what motivates users of mobile health applications and wearables to share their collected health related data. The questionnaire was distributed online in English, French, and Norwegian. In addition, a flyer with information of where to locate the online questionnaire was distributed during a Swiss health conference. ...
    • Enhancing mechanical performance of TiO<inf>2</inf> filler with Kevlar/epoxy-based hybrid composites in a cryogenic environment: a statistical optimization study using RSM and ANN methods 

      Natrayan, L.; Janardhan, Gorti; Paramasivam, Prabhu; Dhanasekaran, Seshathiri (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-11-24)
      This research aims to investigate the mechanical performance of the different weight proportions of nano-TiO<sub>2</sub> combined with Kevlar fiber-based hybrid composites under cryogenic conditions. The following parameters were thus considered: (i) Kevlar fiber mat type (100 and 200 gsm); (ii) weight proportions of TiO2 nanofiller (2 and 6 wt%); and (iii) cryogenic processing time (10–30 min at ...
    • Comprehensive Analysis of Solar Panel Performance and Correlations with Meteorological Parameters 

      Sarmah, Pranjal; Das, Dipankar; Saikia, Madhurjya; Kumar, Virendra; Yadav, Surendra Kumar; Paramasivam, Prabhu; Dhanasekaran, Seshathiri (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-12-08)
      To mitigate the adverse effects of fossil fuel-based energy, mankind is in constant search of clean and cost-effective sources of energy, such as solar energy. The economic viability of a power plant to harness solar energy mostly depends on the efficiency of solar panels. Investigations over the years show that the solar panel efficiency significantly depends on the different meteorological parameters. ...
    • Low-Cost Programmable Air Quality Sensor Kits in Science Education 

      Fjukstad, Bjørn; Angelvik, Nina; Hauglann, maria wulff; Knutsen, Joachim Sveia; Grønnesby, Morten; Gunhildrud, Hedinn; Bongo, Lars Ailo (Chapter; Bokkapittel, 2018-02-21)
      We describe our citizen science approach and technologies designed to introduce students in upper secondary schools to computational thinking and engineering. Using an Arduino microcontroller and low-cost sensors we have developed the air:bit, a programmable sensor kit that students build and program to collect air quality data. In our course, students develop their own research questions regarding ...
    • A Self-Configuration and Healing Controller To Analyze Misconfigurations of Clusters and IoT Edge Devices 

      Elgazazz, Areeg Samir Ahmed; Dagenborg, Håvard Johansen (Conference object; Konferansebidrag, 2023)
    • A Deep Diagnostic Framework Using Explainable Artificial Intelligence and Clustering 

      Thunold, Håvard Horgen; Riegler, Michael; Yazidi, Anis; Hammer, Hugo Lewi (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-11-09)
      An important part of diagnostics is to gain insight into properties that characterize a disease. Machine learning has been used for this purpose, for instance, to identify biomarkers in genomics. However, when patient data are presented as images, identifying properties that characterize a disease becomes far more challenging. A common strategy involves extracting features from the images and ...
    • Identifying Important Proteins in Meibomian Gland Dysfunction with Explainable Artificial Intelligence 

      Storås, Andrea; Magnø, Morten Schjerven; Fineide, Fredrik; Thiede, Bernd; Chen, Xiangjun; Strumke, Inga; Halvorsen, Pål; Utheim, Tor Paaske; Riegler, Michael Alexander; Jensen, Janicke L.; Galtung, Hilde (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-07-17)
      Meibomian gland dysfunction is the most common cause of dry eye disease and leads to significantly reduced quality of life and social burdens. Because meibomian gland dysfunction results in impaired function of the tear film lipid layer, studying the expression of tear proteins might increase the understanding of the etiology of the condition. Machine learning is able to detect patterns in ...
    • Use of a Data-Sharing System During Diabetes Consultations 

      Bradway, Meghan; Muzny, Miroslav; Årsand, Eirik (Journal article; Tidsskriftartikkel; Peer reviewed, 2023)
      Patient-gathered self-management data and shared decision-making are touted as the answer to improving an individual’s health situation as well as collaboration between patients and their providers leading to more effective treatment plans. However, there is a gap between this ideal and reality – a lack of data-sharing technology. Here, we present the impact that the FullFlow System for sharing ...
    • Prescriptive analytics for optimal multi-use battery energy storage systems operation: State-of-the-art and research directions 

      Haug, Martin; Bordin, Chiara; Mishra, Sambeet; Moisan, Julien (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-12-08)
      This paper presents the state-of-the-art and latest advances in implementing multi-use practices on BESS applications to the power system grid. Representative papers on modeling and optimization methods were selected, most of them working with realistic use cases, but none reporting on real-world implementations. Some major findings from reviewing key representative papers are that current optimization ...
    • Some new restricted maximal operators of Fejér means of Walsh–Fourier series 

      Baramidze, Davit; Baramidze, Lasha; Perssson, Lars-Erik; Tephnadze, George (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-09-12)
    • Numerical Investigation of Radiative Hybrid Nanofluid Flows over a Plumb Cone/Plate 

      Peter, Francis; Sambath, Paulsamy; Dhanasekaran, Seshathiri (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-10-18)
      Non-Newtonian fluids play a crucial role in applications involving heat transfer and mass transfer. The inclusion of nanoparticles in these fluids improves the efficiency of heat and mass transfer processes. This study employs a numerical solution approach to examine the flow of non-Newtonian hybrid nanofluids over a plumb cone/plate surface, considering the effects of magnetohydrodynamics (MHD) and ...
    • Revisiting the ‘Whys’ and ‘Hows’ of the Warm-Up: Are We Asking the Right Questions? 

      Afonso, José; Brito, João; Abade, Eduardo; Rendeiro-Pinho, Gonçalo; Matias Do Vale Baptista, Ivan Andre; Figueiredo, Pedro; Nakamura, Fábio Yuzo (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-09-02)
      The warm-up is considered benefcial for increasing body temperature, stimulating the neuromuscular system and overall preparing the athletes for the demands of training sessions and competitions. Even when warm-up–derived benefts are slight and transient, they may still beneft preparedness for subsequent eforts. However, sports training and competition performance are highly afected by contextual ...
    • Tanning Wastewater Sterilization in the Dark and Sunlight Using Psidium guajava Leaf-Derived Copper Oxide Nanoparticles and Their Characteristics 

      Lakshmaiya, Natrayan; Surakasi, Raviteja; Nadh, V. Swamy; Srinivas, Chidurala; Kaliappan, Seniappan; Ganesan, Velmurugan; Paramasivam, Prabhu; Dhanasekaran, Seshathiri (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-10-09)
      Employing Psidium guajava (P. guajava) extract from leaves, copper oxide nanoparticles (CuO NPs), likewise referred to as cupric oxide and renowned for their sustainable and harmless biogenesis, have the possibility of being useful for the purification of pollutants as well as for medicinal purposes. The current study examined the generated CuO NPs and their physical qualities by using ultraviolet−visible ...
    • Statistical experiment analysis of wear and mechanical behaviour of abaca/sisal fiber-based hybrid composites under liquid nitrogen environment 

      Natrayan, L.; Surakasi, Raviteja; Paramasivam, Prabhu; Dhanasekaran, Seshathiri; Kaliappan, S.; Patil, Pravin P. (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-08-04)
      Ice accretion on various onshore and offshore infrastructures imparts hazardous effects sometimes beyond repair, which may be life-threatening. Therefore, it has become necessary to look for ways to detect and mitigate ice. Some ice mitigation techniques have been tested or in use in aviation and railway sectors, however, their applicability to other sectors/systems is still in the research phase. ...
    • Deep Learning for Enhanced Fault Diagnosis of Monoblock Centrifugal Pumps: Spectrogram-Based Analysis 

      Chennai Viswanathan, Prasshanth; Venkatesh, Sridharan Naveen; Dhanasekaran, Seshathiri; Mahanta, Tapan Kumar; Sugumaran, Vaithiyanathan; Lakshmaiya, Natrayan; Paramasivam, Prabhu; Nanjagoundenpalayam Ramasamy, Sakthivel (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-08-31)
      Abstract The reliable operation of monoblock centrifugal pumps (MCP) is crucial in various industrial applications. Achieving optimal performance and minimizing costly downtime requires effectively detecting and diagnosing faults in critical pump components. This study proposes an innovative approach that leverages deep transfer learning techniques. An accelerometer was adopted to capture vibration ...
    • Privacy Concerns Related to Data Sharing for European Diabetes Devices 

      Randine, Pietro; Pocs, Matthias; Cooper, John Graham; Tsolovos, Dimitrios; Muzny, Miroslav; Besters, Rouven; Årsand, Eirik (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-11-13)
      Background: Individuals with diabetes rely on medical equipment (eg, continuous glucose monitoring (CGM), hybrid closed-loop systems) and mobile applications to manage their condition, providing valuable data to health care providers. Data sharing from this equipment is regulated via Terms of Service (ToS) and Privacy Policy documents. The introduction of the Medical Devices Regulation (MDR) and In ...