Viser treff 21-40 av 389

    • 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 ...
    • Transfer Learning Based Fault Detection for Suspension System Using Vibrational Analysis and Radar Plots 

      Sai, Samavedam Aditya; Venkatesh, Sridharan Naveen; Dhanasekaran, Seshathiri; Balaji, Parameshwaran Arun; Sugumaran, Vaithiyanathan; Lakshmaiya, Natrayan; Paramasivam, Prabhu (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-07-26)
      The suspension system is of paramount importance in any automobile. Thanks to the suspension system, every journey benefits from pleasant rides, stable driving and precise handling. However, the suspension system is prone to faults that can significantly impact the driving quality of the vehicle. This makes it essential to find and diagnose any faults in the suspension system and rectify them ...
    • A Modified LeNet CNN for Breast Cancer Diagnosis in Ultrasound Images 

      Balasubramaniam, Sathiyabhama; Velmurugan, Yuvarajan; Jaganathan, Dhayanithi; Dhanasekaran, Seshathiri (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-08-24)
      Convolutional neural networks (CNNs) have been extensively utilized in medical image processing to automatically extract meaningful features and classify various medical conditions, enabling faster and more accurate diagnoses. In this paper, LeNet, a classic CNN architecture, has been successfully applied to breast cancer data analysis. It demonstrates its ability to extract discriminative ...
    • Role of transfer functions in PSO to select diagnostic attributes for chronic disease prediction: An experimental study 

      Malakar, Samir; Sen, Swaraj; Romanov, Sergei; Kaplun, Dmitrii; Sarkar, Ram (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-09-22)
      Particle Swarm Optimization (PSO) is a classic and popularly used meta-heuristic algorithm in many reallife optimization problems due to its less computational complexity and simplicity. The binary version of PSO, known as BPSO, is used to solve binary optimization problems, such as feature selection. Like other meta-heuristic optimization techniques designed on the continuous search space, PSO ...
    • A Multi-pronged Self-adaptive Controller for Analyzing Misconfigurations for Kubernetes Clusters and IoT Edge Devices 

      Elgazazz, Areeg Samir Ahmed; Al-Wosabi, Abdo; Khan, Mohsin; Dagenborg, Håvard Johansen (Conference object; Konferansebidrag, 2023-10-12)
      Kubernetes default configurations do not always provide optimal security and performance for all clusters and IoT edge devices deployed, making them vulnerable to security breaches and information leakage if misconfigured. Misconfiguration leads to a compromised system that disrupts the workload, allows access to system resources, and degrades the system’s performance. To provide optimal security ...
    • Adaptive Controller to Identify Misconfigurations and Optimize the Performance of Kubernetes Clusters and IoT Edge Devices 

      Elgazazz, Areeg Samir Ahmed; Dagenborg, Håvard Johansen (Conference object; Konferansebidrag, 2023-10-12)
      Kubernetes default configurations do not always provide optimal security and performance for all clusters and IoT edge devices deployed, affecting the scalability of a given workload and making them vulnerable to security breaches and information leakage if misconfigured. We present an adaptive controller to identify the type of misconfiguration and its consequence threat to optimize the system ...