Blar i Faculty of Engineering and Science på tittel
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Cyber Security in Procurement of Third-Party Suppliers: A Case Study of the Norwegian Power Sector
(Master thesis, 2022)The Norwegian power sector is currently experiencing an increasingly complex supply chain, affected by digitalization. This case study examines how digitalization has changed the procurement of third-party suppliers of ... -
Cybersecurity Investment Incentives in Norwegian Small to medium sized-Businesses
(Master thesis, 2023)Cybersecurity continues to be a critical concern for businesses worldwide, particularly for Small and Medium-sized Businesses (SMBs) which often lack the resources and expertise to implement robust cybersecurity measures. ... -
Cybersecurity Mindfulness in the Age of Mindless AIs: Investigating AI Assistants Impact in High-Reliability Organizations
(Master thesis, 2023)The Focus: The focus of this Master Thesis is to investigate how AI tools, such as Large Learning Models (LLMs), impact cybersecurity operations in organizations that are regarded as highly reliable. To understand the ... -
Cybersecurity Mindfulness in the Age of Mindless AIs: Investigating AI Assistants Impact in High-Reliability Organizations
(Master thesis, 2023)The Focus: The focus of this Master Thesis is to investigate how AI tools, such as Large Learning Models (LLMs), impact cybersecurity operations in organizations that are regarded as highly reliable. To understand the ... -
Cybersecurity prioritizations and limitations in the power sector
(Master thesis, 2022)Oppgaven utforsker hvordan cybersikkerhetsprioriteringer i bedrifter i den norske kraftsektoren samsvarer med nylige sikkerhetshendelser og det nåværende trusselbildet. I tillegg utforskes hvilke begrensninger og utfordringer ... -
Cyclostationary Random Number Sequences for the Tsetlin Machine
(Peer reviewed; Journal article, 2022)The Tsetlin Machine (TM) constitutes an emerging machine learning algorithm that has shown competitive performance on several benchmarks. The underlying concept of the TM is propositional logic determined by a group of ... -
D-optimal design for parameter estimation in discrete-time nonlinear dynamic systems
(Journal article; Peer reviewed, 2012)An optimal input design method for parameter estimation in a discrete-time nonlinear system is presented in the paper to improve the observability and identification precision of model parameters. Determinant of the ... -
Daily energy expenditure through the human life course
(Journal article; Peer reviewed, 2021) -
Damage identification of a jacket support structure for offshore wind turbines
(Journal article; Peer reviewed, 2020) -
DASMcC: Data Augmented SMOTE Multi-Class Classifier for Prediction of Cardiovascular Diseases Using Time Series Features
(Peer reviewed; Journal article, 2023)One of the leading causes of mortality worldwide is cardiovascular disease (CVD). Electrocardiography (ECG) is a noninvasive and cost-effective tool to diagnose the heart’s health. This study presents a multi-class classifier ... -
Data collection and transmission for leisure time boats : based on Arduino WSNs and LTE
(Master thesis, 2013)There has been an astonishing research development in the field of wireless sensor networks (WSNs) in the last decade. A large number of low power capacity devices have been implemented in different vehicles, where sensor ... -
Data driven approach for the management of wind and solar energy integrated electrical distribution network with high penetration of electric vehicles
(Peer reviewed; Journal article, 2023)With the increased penetration of fluctuating renewables and growing population of contemporary loads such as electric vehicles, the uncertainties in the generation and demand in the electric power grids are increasing. ... -
Data Driven Seal Wear Classifications using Acoustic Emissions and Artificial Neural Networks
(Peer reviewed; Journal article, 2022)The work presented in this paper is built on a series of experiments aiming to develop a data-driven and automated method for seal diagnostics using Acoustic Emission (AE) features. Seals in machineries operate in harsh ... -
Data management and concurrency control in broadcast based asymmetric environments
(Master thesis, 2006)Tens of millions of users have personal handheld devices with several network interfaces built-in, and the number of users and of network interfaces included are only increasing. This growth suggests a need for new methods ... -
Data mining K-clustering problem
(Master thesis, 2012)In statistic and data mining, k-means clustering is well known for its efficiency in clustering large data sets. The aim is to group data points into clusters such that similar items are lumped together in the same cluster. ... -
Data quality-based resource management in enterprise service bus
(Master thesis, 2013)Enterprise Service Bus (ESB) is proposed to address the application integration problem by facilitating communication among di erent systems in a loosely coupled, standardbased, and protocol independent manner. Data ... -
Data-driven adaptive observer for fault diagnosis
(Journal article; Peer reviewed, 2012)This paper presents an approach for data-driven design of fault diagnosis system. The proposed fault diagnosis scheme consists of an adaptive residual generator and a bank of isolation observers, whose parameters are ... -
Data-driven green energy extraction: Machine learning-based MPPT control with efficient fault detection method for the hybrid PV-TEG system
(Peer reviewed; Journal article, 2023)The hybrid photovoltaic-thermoelectric generation system (PVTEG) gives two-fold benefits; firstly, it efficiently utilizes the available solar energy as it converts both solar irradiance and solar thermal energy into ... -
Data-Driven Spectrum Cartography via Deep Completion Autoencoders
(Journal article; Peer reviewed, 2020)Spectrum maps, which provide RF spectrum metrics such as power spectral density for every location in a geographic area, find numerous applications in wireless communications such as interference control, spectrum management, ... -
Dataset from a mesocosm experiment on brownification in the Baltic Sea
(Peer reviewed; Journal article, 2022)Climate change is projected to cause brownification of some coastal seas due to increased runoff of terrestrially derived organic matter. We carried out a mesocosm experiment over 15 days to test the effect of this on the ...