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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 ... -
Integration of programming in Norwegian schools: The effects of prior programming experience on students in a university-level programming course
(Master thesis; Mastergradsoppgave, 2024-06-03)In 2020 a curriculum renewal in Norway integrated programming into multiple subjects at both elementary schools and upper secondary schools. This was done with the hopes of improving deep learning and introducing computational thinking to pupils attending the schools. Some criticism has been raised against the decision, with some declaring that this will hurt deep learning and that programming is ... -
AquaTrace: Secure Federated Identifiers for Product Tracing using Blockchain
(Master thesis; Mastergradsoppgave, 2024-05-31)This thesis proposes a secure and resilient system for generating and managing unique identification number series for tracing food products within the Norwegian fishing industry, without relying on a central authority. Given the context of mutual mistrust among stakeholders and the threat of hostile entities, this project proposes a blockchain-based solution to ensure the uniqueness and security ... -
AI Chatbots in Health: Implementing an LLM-Based Solution to Promote Physical Activity
(Mastergradsoppgave; Master thesis, 2024-06-16)With the emergence of powerful generative AI models comes the possibility of creating knowledgeable and engaging chatbots, which have the potential to significantly enhance several areas of the user’s life. This thesis focuses on the design and implementation of FysBot, an application with an integrated chatbot that aims to increase the user’s physical activity levels. In collaboration with a PhD ... -
Evaluating Continuous End-to-End Communication at Sea with Multi-Hop MANET Routing, Using AIS Data
(Mastergradsoppgave; Master thesis, 2024-06-03)The marine sector has unique and challenging problems supporting high bandwidth, low-latency internet connectivity, often unavailable or only avail able through satellite services. Multi-hop manets that utilise low-cost com modity hardware potentially offer a cost-effective solution compared to satellite services but come with their own limitations. This thesis is motivated by the need for reliable ... -
Haddock: A Smart-Contract Command Bus for the Fishing Industry
(Mastergradsoppgave; Master thesis, 2024-06-02)The global fishing industry, a critical food source, faces significant challenges due to criminal activities such as illegal fishing and over-exploitation. Traditional surveillance methods can be susceptible to tampering and cannot fully ensure the integrity of recorded events. This thesis introduces Haddock, a shared, distributed logging system leveraging a two-phase dissemination protocol and the ... -
Fault-Tolerant Distributed Declarative Programs
(Mastergradsoppgave; Master thesis, 2024-06-02)In our increasingly interconnected digital landscape, the constant generation and consumption of data on various computing devices present challenges for ensuring constant accessibility, particularly in intermittent network scenarios. The emerging focus on distributed systems is aimed at not only managing substantial data volumes but also guaranteeing storage on devices for low latency and high ...
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