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Deepfake detection using deep feature stacking and meta-learning
(Journal article; Tidsskriftartikkel; Peer reviewed, 2024-02-15)Deepfake is a type of face manipulation technique using deep learning that allows for the replacement of faces in videos in a very realistic way. While this technology has many practical uses, if used maliciously, it can have a significant number of bad impacts on society, such as spreading fake news or cyberbullying. Therefore, the ability to detect deepfake has become a pressing need. This ... -
Digital Psychosocial Follow-up for Childhood Critical Illness Survivors: A Qualitative Interview Study on Health Professionals' Perspectives
(Journal article; Tidsskriftartikkel; Peer reviewed, 2024-07-18)Background: Digital solutions have been reported to provide positive psychological and social outcomes to childhood critical illness survivors, a group with an increased risk for long-term adverse psychosocial effects. Objective: To explore health professionals’ perspectives on the potential of digital psychosocial follow-up for childhood critical illness survivors.<p> <p>Methods: Using a ... -
Concatenated Modified LeNet Approach for Classifying Pneumonia Images
(Journal article; Tidsskriftartikkel; Peer reviewed, 2024-03-21)Pneumonia remains a critical health concern worldwide, necessitating efficient diagnostic tools to enhance patient care. This research proposes a concatenated modified LeNet classifier to classify pneumonia images accurately. The model leverages deep learning techniques to improve the diagnosis of Pneumonia, leading to more effective and timely treatment. Our modified LeNet architecture incorporates ... -
Diagnostics analysis of partial discharge events of the power cables at various voltage levels using ramping behavior analysis method
(Journal article; Tidsskriftartikkel; Peer reviewed, 2023-11-16)Partial discharge events can occur in high-voltage cables. It can be caused by defects in the cable insulation, contamination, or a combination of both. Partial discharge in cables can lead to insulation failure and cable failure. This investigation aims to identify the trends and patterns in the internal partial discharge (PD) occurrences in the power cables when exposed to different voltage ... -
Analyzing the MHD Bioconvective Eyring–Powell Fluid Flow over an Upright Cone/Plate Surface in a Porous Medium with Activation Energy and Viscous Dissipation
(Journal article; Tidsskriftartikkel; Peer reviewed, 2024-03-04)In the field of heat and mass transfer applications, non-Newtonian fluids are potentially considered to play a very important role. This study examines the magnetohydrodynamic (MHD) bioconvective Eyring–Powell fluid flow on a permeable cone and plate, considering the viscous dissipation (0.3 ≤ E<sub>c</sub> ≤ 0.7), the uniform heat source/sink (−0.1 ≤ Q<sub>0</sub> ≤ 0.1), and the activation energy ... -
Incidental Data: A Survey towards Awareness on Privacy-Compromising Data Incidentally Shared on Social Media
(Journal article; Tidsskriftartikkel; Peer reviewed, 2024-02-23)Sharing information with the public is becoming easier than ever before through the usage of the numerous social media platforms readily available today. Once posted online and released to the public, information is almost impossible to withdraw or delete. More alarmingly, postings may carry sensitive information far beyond what was intended to be released, so-called incidental data, which raises ... -
Revolutionizing Breast Cancer Diagnosis: A Concatenated Precision through Transfer Learning in Histopathological Data Analysis
(Journal article; Tidsskriftartikkel; Peer reviewed, 2024-02-14)Breast cancer remains a significant global public health concern, emphasizing the critical role of accurate histopathological analysis in diagnosis and treatment planning. In recent years, the advent of deep learning techniques has showcased notable potential in elevating the precision and efficiency of histopathological data analysis. The proposed work introduces a novel approach that harnesses ... -
An Improved Long Short-Term Memory Algorithm for Cardiovascular Disease Prediction
(Journal article; Tidsskriftartikkel, 2024-01-23)Cardiovascular diseases, prevalent as leading health concerns, demand early diagnosis for effective risk prevention. Despite numerous diagnostic models, challenges persist in network configuration and performance degradation, impacting model accuracy. In response, this paper introduces the Optimally Configured and Improved Long Short-Term Memory (OCI-LSTM) model as a robust solution. Leveraging the ... -
Response to “Microdosing: A Conceptual Framework for Use as Programming Strategy for Resistance Training in Team Sports”
(Journal article; Tidsskriftartikkel, 2024-07-19)<p>This letter was written in response to the article “Microdosing: A conceptual framework for use as programming strategy for resistance training in team sports”, recently published in the <i>Strength and Conditioning Journal</i>. The article proposes a framework for implementing microdosing of resistance training across several training and competitive contexts and presents a comprehensive proposal ... -
The Complexity of Defining and Assessing the Most Demanding Periods of Play in Team Sports: A Current Opinion
(Journal article; Tidsskriftartikkel, 2024-07-19)In the context of training load monitoring, the most demanding periods of play (MDPs) have increasingly caught the interest of researchers. However, the MDPs analysis is currently embryonic, raising some conceptual and methodological questions. This current opinion synthesizes the methods used for the MDPs analysis while highlighting conceptual and methodological gaps and proposing a broader perspective ... -
Artificial intelligence-assisted characterization and optimization of red mud-based nanofluids for high-efficiency direct solar thermal absorption
(Journal article; Tidsskriftartikkel; Peer reviewed, 2024-01-30)The utilization of nanofluids (NFs) holds promise for enhancing the thermal efficiency of solar thermal collectors. Among the various NF solutions, red mud (RM) NFs have gained attention due to their effective absorption of solar thermal energy. RM comprises precious metal oxides, making it a proficient medium for direct solar heat absorption. This study aimed to formulate waterbased RM NFs with ... -
An individually adjusted approach for communicating epidemiological results on health and lifestyle to patients
(Journal article; Tidsskriftartikkel; Peer reviewed, 2024-02-08)If scientific research on modifiable risk factors was more accessible to the general population there is a potential to prevent disease and promote health. Mobile applications can automatically combine individual characteristics and statistical models of health to present scientific information as individually tailored visuals, and thus there is untapped potential in incorporating scientific ... -
Visual explanations for polyp detection: How medical doctors assess intrinsic versus extrinsic explanations
(Journal article; Tidsskriftartikkel; Peer reviewed, 2024-05-31)Deep learning has achieved immense success in computer vision and has the potential to help physicians analyze visual content for disease and other abnormalities. However, the current state of deep learning is very much a black box, making medical professionals skeptical about integrating these methods into clinical practice. Several methods have been proposed to shed some light on these black ... -
Performance Evaluation of Lightweight Stream Ciphers for Real-Time Video Feed Encryption on ARM Processor
(Journal article; Tidsskriftartikkel; Peer reviewed, 2024-07-25)In resource-intensive Internet of Things applications, Lightweight Stream Ciphers (LWSCs) play a vital role in influencing both the security and performance of the system. Numerous LWSCs have been proposed, each offering certain properties and trade-offs that carefully balance security and performance requirements. This paper presents a comprehensive evaluation of prominent LWSCs, with a focus on ... -
Better Balance in Informatics: An Honest Discussion with Students
(Chapter; Bokkapittel, 2023-07-09)In recent years, there has been considerable effort to promote gender balance in the academic environment of Computer Science (CS). However, there is still a gender gap at all CS academic levels: from students, to PhD candidates, to faculty members. This general trend is followed by the Department of Computer Science at UiT The Arctic University of Norway. To combat this trend within the CS environment ... -
Analysis of peak locomotor demands in women’s football–the influence of different epoch lengths
(Journal article; Tidsskriftartikkel; Peer reviewed, 2024-05-23)The quantification of peak locomotor demands has been gathering researchers’ attention in the past years. Regardless of the different methodological approaches used, the most selected epochs are between 1-, 3-, 5- and 15-minutes time windows. However, the selection of these time frames is frequently arbitrary. The aim of this study was to analyse the peak locomotor demands of short time epochs (15, ... -
Lithium-ion battery digitalization: Combining physics-based models and machine learning
(Journal article; Tidsskriftartikkel; Peer reviewed, 2024-05-21)Digitalization of lithium-ion batteries can significantly advance the performance improvement of lithium-ion batteries by enabling smarter controlling strategies during operation and reducing risk and expenses in the design and development phase. Accurate physics-based models play a crucial role in the digitalization of lithium-ion batteries by providing an in-depth understanding of the system. ... -
Guided U-Net Aided Efficient Image Data Storing with Shape Preservation
(Chapter; Bokkapittel, 2023-11-02)The proliferation of high-content microscopes ( 32 GB for a single image) and the increasing amount of image data generated daily have created a pressing need for compact storage solutions. Not only is the storage of such massive image data cumbersome, but it also requires a significant amount of storage and data bandwidth for transmission. To address this issue, we present a novel deep learning ... -
Deidentifying a Norwegian clinical corpus - An effort to create a privacy-preserving Norwegian large clinical language model
(Journal article; Tidsskriftartikkel; Peer reviewed, 2024)This study discusses the methods and challenges of deidentifying and pseudonymizing Norwegian clinical text for research purposes. The results of the NorDeid tool for deidentification and pseudonymization on different types of protected health information were evaluated and discussed, as well as the extension of its functionality with regular expressions to identify specific types of sensitive ... -
Real-Time Change Detection with Convolutional Density Approximation
(Journal article; Tidsskriftartikkel; Peer reviewed, 2024-04-02)Background Subtraction (BgS) is a widely researched technique to develop online Change Detection algorithms for static video cameras. Many BgS methods have employed the unsupervised, adaptive approach of Gaussian Mixture Model (GMM) to produce decent backgrounds, but they lack proper consideration of scene semantics to produce better foregrounds. On the other hand, with considerable computational ...
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