Browsing Department of Information and Communication Technology by Title
Now showing items 261-280 of 1303
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Data-Driven Pump Scheduling for Cost Minimization in Water Networks
(Chapter, 2021)Pumps consume a significant amount of energy in a water distribution network (WDN). With the emergence of dynamic energy cost, the pump scheduling as per user demand is a computationally challenging task. Computing the ... -
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, ... -
DDoS detection based on traffic profiles
(Master thesis, 2006)Distributed denial of service attacks has become a significant threat against Internet resources. These attacks aims at disrupting the victim’s service by commanding a massive number of compromised sources to send ... -
A decentralized Ethereum platform for smart energy trading : Designing and implementing an eAuction application for energy trading on the Ethereum blockchain by using smart contracts
(Master thesis, 2021)The modern energy grid is constantly improving its efficiency and flexibility by adopting new technology. Regional energy providers, however, have a monopolistic role in deciding market prices, and their motives have been ... -
Decentralized subspace projection in large networks
(Chapter; Peer reviewed, 2018) -
Decision-cache based XACML authorisation and anonymisation for XML documents
(Journal article; Peer reviewed, 2012)This paper describes a decision cache for the eXtensible Access Control Markup Language (XACML) that supports fine-grained authorisation and anonymisation of XML based messages and documents down to XML attribute and element ... -
A Decision-support Algorithm for Self-management of Anticoagulation Therapy Used in a Smartphone Application
(Chapter; Peer reviewed, 2019) -
Deep Convolutional Neural Networks for Semantic Segmentation of Multi-Band Satellite Images
(Master thesis, 2018)Semantic segmentation of images is of increasing interest in the eld of computer vision and machine learning. Accurate and e cient segmentation methods is required for many of todays modern applications. This the- sis ... -
Deep Crowd Anomaly Detection by Fusing Reconstruction and Prediction Networks
(Peer reviewed; Journal article, 2023)Abnormal event detection is one of the most challenging tasks in computer vision. Many existing deep anomaly detection models are based on reconstruction errors, where the training phase is performed using only videos of ... -
Deep Hybrid Neural Networks on Multi-temporal Satellite Data: Predicting Farm-scale Crop Yields
(Master thesis, 2021)Accurate farm-scale crop yield predictions can enable farmers to improve their yield per decare and inform subsequent sectors of the availability of grains sooner. Existing research on yield predictions is limited to ... -
A Deep Learning Approach for Energy Efficient Computational Offloading in Mobile Edge Computing
(Peer reviewed; Journal article, 2019)Mobile edge computing (MEC) has shown tremendous potential as a means for computationally intensive mobile applications by partially or entirely offloading computations to a nearby server to minimize the energy consumption ... -
Deep Learning for Crowd Anomaly Detection
(Master thesis, 2022)Today, public areas across the globe are monitored by an increasing amount of surveillance cameras. This widespread usage has presented an ever-growing volume of data that cannot realistically be examined in real-time. ... -
Deep Learning for Medical Image Cryptography: A Comprehensive Review
(Peer reviewed; Journal article, 2023)Electronic health records (EHRs) security is a critical challenge in the implementation and administration of Internet of Medical Things (IoMT) systems within the healthcare sector’s heterogeneous environment. As digital ... -
A Deep Learning-based approach for Fault Detection of Power Lines
(Master thesis, 2020)A transmission network is the most crucial part of modern infrastructure. However, it requires an extensive amount of power line inspection each year to maintain, and with an increased interest in replacing large ... -
A Deep Learning-Based Framework for Feature Extraction and Classification of Intrusion Detection in Networks
(Peer reviewed; Journal article, 2022)An intrusion detection system, often known as an IDS, is extremely important for preventing attacks on a network, violating network policies, and gaining unauthorized access to a network. The effectiveness of IDS is highly ... -
Deep Q-Learning With Q-Matrix Transfer Learning for Novel Fire Evacuation Environment
(Journal article; Peer reviewed, 2020) -
Deep Reinforcement Learning using Capsules in Advanced Game Environments
(Master thesis, 2018)Reinforcement Learning (RL) is a research area that has blossomed tremendously in recent years and has shown remarkable potential for artificial intelligence based opponents in computer games. This success is primarily due ... -
Deep Reinforcement Learning using Capsules in Advanced Game Environments
(Master thesis, 2017)Reinforcement Learning (RL) is a research area that has blossomed tremendously in recent years and has shown remarkable potential for arti cial intelligence based opponents in computer games. This success is primarily due ... -
Deep Transfer Learning Based Radio Map Estimation for Indoor Wireless Communications
(Chapter; Peer reviewed, 2022)This paper investigates the problem of transfer learning in radio map estimation for indoor wireless communications, which can be exploited for different applications, such as channel modelling, resource allocation, network ...