Browsing Faculty of Engineering and Science by Title
Now showing items 2991-3010 of 3203
-
Towards Data-Driven Modelling of Saulekilen Wastewater Treatment Plant based on Artificial Intelligence
(Master thesis, 2019)The processes at a wastewater treatment plant (WWTP) are complex systems thatclean the wastewater before it is released into the environment. Total phosphorous(TP), biological oxygen demand (BOD) and chemical oxygen ... -
Towards Detecting Textual Plagiarism Using Machine Learning Methods
(Master thesis, 2015)Textual plagiarism is passing off someone else’s text as your own. The current state of the art in plagiarism detection performs well, but often uses a series of manually determined thresholds of metrics in order to ... -
Towards Efficient Use of Cement in Ultra High Performance Concrete
(Journal article; Peer reviewed, 2021)This paper presents an investigation on substituting the cement content with an inert material, in a typical locally produced UHPC mix. A structured literature review was performed to enrichen the discussion and to benchmark ... -
Towards farm-level health management of offshore wind farms for maintenance improvements
(Journal article; Peer reviewed, 2015) -
Towards Improved Healthcare Performance: Examining Technological Possibilities and Patient Satisfaction with Wireless Body Area Networks
(Journal article; Peer reviewed, 2010)This paper investigates the benefits of using less intrusive wireless technologies for heart monitoring. By replacing well established heart monitoring devices (i.e. Holter) with wireless ECG based Body Area Networks (BAN), ... -
Towards intelligent and trustworthy task assignments for 5G-enabled industrial communication systems
(Peer reviewed; Journal article, 2023)With the unprecedented prevalence of IIoT and 5G technology, various applications supported by industrial communication systems have generated exponentially increased processing tasks, which makes task assignment inefficient ... -
Towards Responsible AI for Financial Transactions
(Chapter; Peer reviewed, 2020)The application of AI in finance is increasingly dependent on the principles of responsible AI. These principles-explainability, fairness, privacy, accountability, transparency and soundness form the basis for trust in ... -
Towards safe reinforcement-learning in industrial grid-warehousing
(Peer reviewed; Journal article, 2020) -
Towards the definitive evaluation framework for cross-platform app development approaches
(Journal article; Peer reviewed, 2019) -
Towards Thompson Sampling for Complex Bayesian Reasoning
(Doctoral Dissertation at the University of Agder; no. 275, Doctoral thesis, 2020)Thompson Sampling (TS) is a state-of-art algorithm for bandit problems set in a Bayesian framework. Both the theoretical foundation and the empirical efficiency of TS is wellexplored for plain bandit problems. However, the ... -
Towards Using Reinforcement Learning for Autonomous Docking of Unmanned Surface Vehicles
(Communications in Computer and Information Science;1600, Chapter; Peer reviewed, 2022)Providing full autonomy to Unmanned Surface Vehicles (USV) is a challenging goal to achieve. Autonomous docking is a subtask that is particularly difficult. The vessel has to distinguish between obstacles and the dock, and ... -
Tracking mobile robot in indoor wireless sensor networks
(Journal article; Peer reviewed, 2014)This work addresses the problem of tracking mobile robots in indoor wireless sensor networks (WSNs). Our approach is based on a localization scheme with RSSI (received signal strength indication) which is used widely in ... -
Tracking the preferences of users using weak estimators
(Lecture Notes in Computer Science;7106, Chapter; Peer reviewed, 2011)Since a social network, by definition, is so diverse, the problem of estimating the preferences of its users is becoming increasingly essential for personalized applications which range from service recommender systems to ... -
A Trainable Approach to Zero-delay Smoothing Spline Interpolation
(Peer reviewed; Journal article, 2023)The task of reconstructing smooth signals from streamed data in the form of signal samples arises in various applications. This work addresses such a task subject to a zerodelay response; that is, the smooth signal must ... -
Training Deep Neural Networks with Novel Metaheuristic Algorithms for Fatigue Crack Growth Prediction in Aluminum Aircraft Alloys
(Peer reviewed; Journal article, 2022) -
A Trajectory-Driven 3D Non-Stationary mm-Wave MIMO Channel Model for a Single Moving Point Scatterer
(Peer reviewed; Journal article, 2021)This paper proposes a new non-stationary three-dimensional (3D) channel model for a physical millimeter wave (mm-Wave) multiple-input multiple-output (MIMO) channel. This MIMO channel model is driven by the trajectory of ... -
Trans-oceanic genomic divergence of Atlantic cod ecotypes is associated with large inversions
(Journal article; Peer reviewed, 2017)Chromosomal rearrangements such as inversions can play a crucial role in maintaining polymorphism underlying complex traits and contribute to the process of speciation. In Atlantic cod (Gadus morhua), inversions of several ... -
Transcriptomic responses to environmental change in fishes: Insights from RNA sequencing
(Journal article, 2017)The need to better understand how plasticity and evolution affect organismal responses to environmental variability is paramount in the face of global climate change. The potential for using RNA sequencing (RNA-seq) to ... -
Transform Diabetes - Harnessing Transformer-Based Machine Learning and Layered Ensemble with Enhanced Training for Improved Glucose Prediction.
(Master thesis, 2023)Type 1 diabetes is a common chronic disease characterized by the body’s inability to regulate the blood glucose level, leading to severe health consequences if not handled manually. Accurate blood glucose level predictions ... -
Transform Diabetes - Harnessing Transformer-Based Machine Learning and Layered Ensemble with Enhanced Training for Improved Glucose Prediction.
(Master thesis, 2023)Type 1 diabetes is a common chronic disease characterized by the body’s inability to regulate the blood glucose level, leading to severe health consequences if not handled manually. Accurate blood glucose level predictions ...