Blar i Department of Information and Communication Technology på tittel
Viser treff 1208-1227 av 1317
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Tracking of Quantized Signals Based on Online Kernel Regression
(Peer reviewed; Journal article, 2021)Kernel-based approaches have achieved noticeable success as non-parametric regression methods under the framework of stochastic optimization. However, most of the kernel-based methods in the literature are not suitable to ... -
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 ... -
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 ... -
Transfer Learning Based Joint Resource Allocation for Underlay D2D Communications
(Chapter; Peer reviewed, 2022)In this paper, we investigate the application of transfer learning to train a Deep Neural Network (DNN) model for joint channel and power allocation in underlay device-todevice (D2D) communication. Based on the traditional ... -
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 ... -
Transformer Reinforcement Learning for Procedural Level Generation
(Master thesis, 2023)This paper examines how recent advances in sequence modeling translate for machine learning assisted procedural level generation. We explore the use of Transformer based models like DistilGPT-2 to generate platformer levels, ... -
Transformer Reinforcement Learning for Procedural Level Generation
(Master thesis, 2023)This paper examines how recent advances in sequence modeling translate for machine learning assisted procedural level generation. We explore the use of Transformer based models like DistilGPT-2 to generate platformer levels, ... -
Transient Performance Modelling of 5G Slicing with Mixed Numerologies for Smart Grid Traffic
(Chapter, 2021)Network slicing enabled by fifth generation (5G) systems has the potential to satisfy diversified service requirements from different vertical industries. As a typical vertical industry, smart distribution grid poses new ... -
Trådløs kommunikasjon i prosessindustrien : case Elkem Fiskaa Silicon
(Master thesis, 2000)Vil innføring av trådløs teknologi ved EFS få konsekvenser for organisasjonsstrukturen og operatørenes arbeidssituasjon? Dette er et av de sentrale spørsmålene i denne rapporten, og ved å analysere fem forskjellige teknologiske ... -
Triangulating Precision: A Comparative Study of Manual and Automated Annotations with YOLO,Azure Custom Vision and Grounded SAM on a Customized Data set for creation of a product for safety of recycling industries
(Master thesis, 2024)This thesis centers on the imperative task of detecting and segmenting batteries within the recycling industry, addressing the need for an efficient and accurate solution. The primary goal is to conduct a comprehensive ... -
Trust-aware RBAC
(Lecture Notes in Computer Science;7531, Chapter; Peer reviewed, 2012)In this paper we propose a trust-aware enhancement of RBAC (TA-RBAC) that takes trustworthiness of users into consideration explicitly before granting access. We assume that each role in the framework is associated with ... -
Tsetlin Machine for Fake News Detection: Enhancing Accuracy and Reliability
(Master thesis, 2023)This thesis aims to improve the accuracy of fake news detection by using Tsetlin Machines (TM). TMs are well suited for noisy and complex relations within the provided data, which on initial analysis, overlaps nicely with ... -
TsetlinGo : Solving the game of Go with Tsetlin Machine
(Master thesis, 2020)The Tsetlin Machine have already shown great promise on pattern recognition and text categorization. The board game GO is a highly complex game, and the Tsetlin Machine have not yet been tested extensively on strategic ... -
Tuning Suricata Intrusion Detection System for High Performance on a Single Non-Uniform Memory Access Node
(Master thesis, 2021)The rapid increase in network capacity poses a challenge in detecting cyber attacks. Suricata is a modern intrusion detection system(IDS) used to monitor network traffic to detect cyberattacks. Telenor is monitoring ... -
Two new sum-of-sinusoids-based methods for the efficient generation of multiple uncorrelated rayleigh fading waveforms
(Journal article; Peer reviewed, 2009)This paper deals with the design of a set of multiple uncorrelated Rayleigh fading waveforms. The Rayleigh fading waveforms are mutually uncorrelated, but each waveform is correlated in time. The waveforms are generated ... -
Two teletraffic-based schemes for energy saving in cellular networks with micro-cells
(Journal article; Peer reviewed, 2012)The energy consumption of Base Stations (BSs) is known to constitute a major part of the power consumption in a cellular network. In this paper, we propose a novel approach which may switch a BS off under light traffic ... -
Ultimate Order Statistics-Based Prototype Reduction Schemes
(Lecture Notes in Computer Science;8272, Chapter; Peer reviewed, 2013)The objective of Prototype Reduction Schemes (PRSs) and Border Identification (BI) algorithms is to reduce the number of training vectors, while simultaneously attempting to guarantee that the classifier built on the reduced ... -
Ultra Reliable Communication in 5G Networks: A Dependability-based Availability Analysis in the Space Domain
(Master thesis, 2017)As our daily life is becoming more dependent on wireless and mobile services, seamless network connectivity is of utmost importance. Wireless networks are expected to handle the growing demand for applications which ...