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Articles 1 - 17 of 17
Full-Text Articles in Computer Engineering
Ai And 6g Into The Metaverse: Fundamentals, Challenges And Future Research Trends, Muhammad Zawish, Fayaz Ali Dharejo, Sunder Ali Khowaja, Saleem Raza, Steven Davy, Kapal Dev, Paolo Bellavista
Ai And 6g Into The Metaverse: Fundamentals, Challenges And Future Research Trends, Muhammad Zawish, Fayaz Ali Dharejo, Sunder Ali Khowaja, Saleem Raza, Steven Davy, Kapal Dev, Paolo Bellavista
Articles
Since Facebook was renamed Meta, a lot of attention, debate, and exploration have intensified about what the Metaverse is, how it works, and the possible ways to exploit it. It is anticipated that Metaverse will be a continuum of rapidly emerging technologies, usecases, capabilities, and experiences that will make it up for the next evolution of the Internet. Several researchers have already surveyed the literature on artificial intelligence (AI) and wireless communications in realizing the Metaverse. However, due to the rapid emergence and continuous evolution of technologies, there is a need for a comprehensive and in-depth survey of the role …
Survey Of Routing Techniques-Based Optimization Of Energy Consumption In Sd-Dcn, Mohammed Nsaif, Gergely Kovásznai, Ali Malik, Ruairí De Fréin
Survey Of Routing Techniques-Based Optimization Of Energy Consumption In Sd-Dcn, Mohammed Nsaif, Gergely Kovásznai, Ali Malik, Ruairí De Fréin
Articles
The increasing power consumption of Data Center Networks (DCN) is becoming a major concern for network operators. The object of this paper is to provide a survey of state-of-the-art methods for reducing energy consumption via (1) enhanced scheduling and (2) enhanced aggregation of traffic flows using Software-Defined Networks (SDN), focusing on the advantages and disadvantages of these approaches. We tackle a gap in the literature for a review of SDN-based energy saving techniques and discuss the limitations of multi-controller solutions in terms of constraints on their performance. The main finding of this survey paper is that the two classes of …
Schizo-Net: A Novel Schizophrenia Diagnosis Framework Using Late Fusion Multimodal Deep Learning On Electroencephalogram-Based Brain Connectivity Indices, Nitin Grover, Aviral Chharia, Rahul Upadhyay, Luca Longo
Schizo-Net: A Novel Schizophrenia Diagnosis Framework Using Late Fusion Multimodal Deep Learning On Electroencephalogram-Based Brain Connectivity Indices, Nitin Grover, Aviral Chharia, Rahul Upadhyay, Luca Longo
Articles
Schizophrenia (SCZ) is a serious mental condition that causes hallucinations, delusions, and disordered thinking. Traditionally, SCZ diagnosis involves the subject’s interview by a skilled psychiatrist. The process needs time and is bound to human errors and bias. Recently, brain connectivity indices have been used in a few pattern recognition methods to discriminate neuro-psychiatric patients from healthy subjects. The study presents Schizo-Net , a novel, highly accurate, and reliable SCZ diagnosis model based on a late multimodal fusion of estimated brain connectivity indices from EEG activity. First, the raw EEG activity is pre-processed exhaustively to remove unwanted artifacts. Next, six brain …
Gated Deep Reinforcement Learning With Red Deer Optimization For Medical Image Classification, Narayanan Ganesh, Sambandan Jayalakshmi, Rama Chandran Narayanan, Miroslav Mahdal, Hossam Zawbaa, Ali Wagdy Mohamed
Gated Deep Reinforcement Learning With Red Deer Optimization For Medical Image Classification, Narayanan Ganesh, Sambandan Jayalakshmi, Rama Chandran Narayanan, Miroslav Mahdal, Hossam Zawbaa, Ali Wagdy Mohamed
Articles
The brain is one of the most important and complex organs in the body, consisting of billions of individual cells. Uncontrolled growth and expansion of aberrant cell populations within or around the brain are the main causes of brain tumors. These cells have the potential to harm healthy cells and impair brain function [1]. Tumors can be detected using medical imaging techniques, which are considered the most popular and accurate way to classify different types of cancer, and this procedure is even more crucial as it is noninvasive [2]. Magnetic resonance imaging (MRI) is one such medical imaging technique that …
Subnetwork Ensembling And Data Augmentation: Effects On Calibration, A. Çağrı Demir, Simon Caton, Pierpaolo Dondio
Subnetwork Ensembling And Data Augmentation: Effects On Calibration, A. Çağrı Demir, Simon Caton, Pierpaolo Dondio
Articles
Deep Learning models based on convolutional neural networks are known to be uncalibrated, that is, they are either overconfident or underconfident in their predictions. Safety-critical applications of neural networks, however, require models to be well-calibrated, and there are various methods in the literature to increase model performance and calibration. Subnetwork ensembling is based on the over-parametrization of modern neural networks by fitting several subnetworks into a single network to take advantage of ensembling them without additional computational costs. Data augmentation methods have also been shown to enhance model performance in terms of accuracy and calibration. However, ensembling and data augmentation …
Graph-Based Heuristic Solution For Placing Distributed Video Processing Applications On Moving Vehicle Clusters, Kanika Sharma, Bernard Butler, Brendan Jennings
Graph-Based Heuristic Solution For Placing Distributed Video Processing Applications On Moving Vehicle Clusters, Kanika Sharma, Bernard Butler, Brendan Jennings
Articles
Vehicular fog computing (VFC) is envisioned as an extension of cloud and mobile edge computing to utilize the rich sensing and processing resources available in vehicles. We focus on slow-moving cars that spend a significant time in urban traffic congestion as a potential pool of onboard sensors, video cameras, and processing capacity. For leveraging the dynamic network and processing resources, we utilize a stochastic mobility model to select nodes with similar mobility patterns. We then design two distributed applications that are scaled in real-time and placed as multiple instances on selected vehicular fog nodes. We handle the unstable vehicular environment …
Ml-Based Online Traffic Classification For Sdns, Mohammed Nsaif, Gergely Kovasznai, Mohammed Abboosh, Ali Malik, Ruairí De Fréin
Ml-Based Online Traffic Classification For Sdns, Mohammed Nsaif, Gergely Kovasznai, Mohammed Abboosh, Ali Malik, Ruairí De Fréin
Articles
Traffic classification is a crucial aspect for Software-Defined Networking functionalities. This paper is a part of an on-going project aiming at optimizing power consumption in the environment of software-defined datacenter networks. We have developed a novel routing strategy that can blindly balance between the power consumption and the quality of service for the incoming traffic flows. In this paper, we demonstrate how to classify the network traffic flows so that the quality of service of each flow-class can be guaranteed efficiently. This is achieved by creating a dataset that encompasses different types of network traffic such as video, VoIP, game …
Human Mental Workload: A Survey And A Novel Inclusive Definition, Luca Longo, Christopher D. Wickens, Gabriella Hancock, P.A. Hancock
Human Mental Workload: A Survey And A Novel Inclusive Definition, Luca Longo, Christopher D. Wickens, Gabriella Hancock, P.A. Hancock
Articles
Human mental workload is arguably the most invoked multidimensional construct in Human Factors and Ergonomics, getting momentum also in Neuroscience and Neuroergonomics. Uncertainties exist in its characterization, motivating the design and development of computational models, thus recently and actively receiving support from the discipline of Computer Science. However, its role in human performance prediction is assured. This work is aimed at providing a synthesis of the current state of the art in human mental workload assessment through considerations, definitions, measurement techniques as well as applications, Findings suggest that, despite an increasing number of associated research works, a single, reliable and …
On The Mandelbrot Set For I**2 = ±1 And Imaginary Higgs Fields, Jonathan Blackledge
On The Mandelbrot Set For I**2 = ±1 And Imaginary Higgs Fields, Jonathan Blackledge
Articles
We consider the consequence of breaking with a fundamental result in complex analysisby lettingi2=±1wherei=√−1is the basic unit of all imaginary numbers. An analysis of theMandelbrot set for this case shows that a demarcation between a Fractal and a Euclidean object ispossible based oni2=−1andi2= +1, respectively. Further, we consider the transient behaviourassociated with the two cases to produce a range of non-standard sets in which a Fractal geometricstructure is transformed into a Euclidean object. In the case of the Mandelbrot set, the Euclideanobject is a square whose properties are investigate. Coupled with the associated Julia sets and othercomplex plane mappings, this …
Rapid Restoration Techniques For Software-Defined Networks, Ali Malik, Ruairí De Fréin, Benjamin Aziz
Rapid Restoration Techniques For Software-Defined Networks, Ali Malik, Ruairí De Fréin, Benjamin Aziz
Articles
There is increasing demand in modern day business applications for communication networks to be robust and reliable due to the complexity and critical nature of such applications. As such, data delivery is expected to be reliable and secure even in the harshest of environments. Software-Defined Networking (SDN) is gaining traction as a promising approach for designing network architectures which are robust and flexible. One reason for this is that separating the data plane from the control plane, increases the controller’s ability to configure the network rapidly. When network failure events occur, the network manager may trade-off the optimality of the …
Applications Of Artificial Intelligence To Cryptography, Jonathan Blackledge, Napo Mosola
Applications Of Artificial Intelligence To Cryptography, Jonathan Blackledge, Napo Mosola
Articles
This paper considers some recent advances in the field of Cryptography using Artificial Intelligence (AI). It specifically considers the applications of Machine Learning (ML) and Evolutionary Computing (EC) to analyze and encrypt data. A short overview is given on Artificial Neural Networks (ANNs) and the principles of Deep Learning using Deep ANNs. In this context, the paper considers: (i) the implementation of EC and ANNs for generating unique and unclonable ciphers; (ii) ML strategies for detecting the genuine randomness (or otherwise) of finite binary strings for applications in Cryptanalysis. The aim of the paper is to provide an overview on …
Multi-Band Antenna Array Based On Double Negative Metamaterial For Multi Automotive Applications, Mohd Jamlos, Abdulrahman Alqadami,, Imtiaz Islam, Ping Soh, Rizalman Mamat, Khairil Khairi, Adam Narbudowicz
Multi-Band Antenna Array Based On Double Negative Metamaterial For Multi Automotive Applications, Mohd Jamlos, Abdulrahman Alqadami,, Imtiaz Islam, Ping Soh, Rizalman Mamat, Khairil Khairi, Adam Narbudowicz
Articles
Nowadays, the demand for antennas in wireless communication system for automotive applications is rising at a rapid rate [1, 2]. Their usage includes collision avoidance system (CAS), Vehicle-to-vehicle communications, pre-crash safety systems, Global Positioning Systems (GPS), tyre pressure monitoring system (TPMS), Wireless Local Area Network (WLAN), etc. To enhance its effectiveness in these new applications, a small, multi-band, multi-functional antenna is required instead of conventional single band antennas [2, 3]. Such multifunctional antennas with favourable radiation characteristics are more practical in addressing modern antenna design requirements. However, the achievement of the above mentioned antenna’s features using conventional materials and structures …
Source Separation Approach To Video Quality Prediction In Computer Networks, Ruairí De Fréin
Source Separation Approach To Video Quality Prediction In Computer Networks, Ruairí De Fréin
Articles
Time-varying loads introduce errors in the estimated model parameters of service-level predictors in Computer Networks. A load-adjusted modification of a traditional unadjusted service-level predictor is contributed, based on Source Separation (SS). It mitigates these errors and improves service-quality predictions for Video-on-Demand (VoD) by :6 to 2dB.
Monitoring Voip Speech Quality For Chopped And Clipped Speech, Andrew Hines, Jan Skoglund, Anil C. Kokaram, Naomi Harte
Monitoring Voip Speech Quality For Chopped And Clipped Speech, Andrew Hines, Jan Skoglund, Anil C. Kokaram, Naomi Harte
Articles
No abstract provided.
Integration Of Qos Metrics, Rules And Semantic Uplift For Advanced Iptv Monitoring, Ruairí De Fréin, Cristian Olariu, Yuqian Song, Rob Brennan, Patrick Mcdonagh, Adriana Hava, Christina Thorpe, John Murphy, Liam Murphy, Paul French
Integration Of Qos Metrics, Rules And Semantic Uplift For Advanced Iptv Monitoring, Ruairí De Fréin, Cristian Olariu, Yuqian Song, Rob Brennan, Patrick Mcdonagh, Adriana Hava, Christina Thorpe, John Murphy, Liam Murphy, Paul French
Articles
Increasing and variable traffic demands due to triple play services pose significant Internet Protocol Television (IPTV) resource management challenges for service providers. Managing subscriber expectations via consolidated IPTV quality reporting will play a crucial role in guaranteeing return-on-investment for players in the increasingly competitive IPTV delivery ecosystem. We propose a fault diagnosis and problem isolation solution that addresses the IPTV monitoring challenge and recommends problem-specific remedial action. IPTV delivery-specific metrics are collected at various points in the delivery topology, the residential gateway and the Digital Subscriber Line Access Multiplexer through to the video Head-End. They are then pre-processed using new …
Adaptive Ofdm For Wireless Interconnect In Confined Enclosures, Vit Sipal, Javier Gelabert, Christopher J. Stevens, Ben Allen, David Edwards
Adaptive Ofdm For Wireless Interconnect In Confined Enclosures, Vit Sipal, Javier Gelabert, Christopher J. Stevens, Ben Allen, David Edwards
Articles
This letter considers and recommends OFDM with adaptive subcarrier modulation as a suitable candidate for wireless UWB communication in computer chassis. A rigorous measurement campaign studies the guaranteed spectral efficiency. It concludes that enhancement of the existing WiMedia OFDM systems with a bandwidth of 528 MHz in order to support adaptive OFDM would enable data-rates above 1 Gbps over short ranges, i.e. the spectral efficiency would be doubled. Moreover, the guaranteed spectral efficiency is shown to increase with bandwidth, i.e. the guaranteed data-rate increases better than linearly with bandwidth.
Application Of Stochastic Diffusion For Hiding High Fidelity Encrypted Images, Jonathan Blackledge, Abdulrahman Al-Rawi
Application Of Stochastic Diffusion For Hiding High Fidelity Encrypted Images, Jonathan Blackledge, Abdulrahman Al-Rawi
Articles
Cryptography coupled with information hiding has received increased attention in recent years and has become a major research theme because of the importance of protecting encrypted information in any Electronic Data Interchange system in a way that is both discrete and covert. One of the essential limitations in any cryptography system is that the encrypted data provides an indication on its importance which arouses suspicion and makes it vulnerable to attack. Information hiding of Steganography provides a potential solution to this issue by making the data imperceptible, the security of the hidden information being a threat only if its existence …