Engineering Commons^™

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 …

Toward Inclusive Online Environments: Counterfactual-Inspired Xai For Detecting And Interpreting Hateful And Offensive Tweets, Muhammad Deedahwar Mazhar Qureshi, Muhammad Atif Qureshi, Wael Rashwan

Articles

The prevalence of hate speech and offensive language on social media platforms such as Twitter has significant consequences, ranging from psychological harm to the polarization of societies. Consequently, social media companies have implemented content moderation measures to curb harmful or discriminatory language. However, a lack of consistency and transparency hinders their ability to achieve desired outcomes. This article evaluates various ML models, including an ensemble, Explainable Boosting Machine (EBM), and Linear Support Vector Classifier (SVC), on a public dataset of 24,792 tweets by T. Davidson, categorizing tweets into three classes: hate, offensive, and neither. The top-performing model achieves a weighted …

Discovering Child Sexual Abuse Material Creators’ Behaviors And Preferences On The Dark Web, Vuong Ngo, Rahul Gajula, Christina Thorpe, Susan Mckeever

Articles

Background: Producing, distributing or discussing child sexual abuse materials (CSAM) is often committed through the dark web in order to remain hidden from search engines and regular users. Additionally, on the dark web, the CSAM creators employ various techniques to avoid detection and conceal their activities. The large volume of CSAM on the dark web presents a global social problem and poses a significant challenge for helplines, hotlines and law enforcement agencies.

Objective: Identifying CSAM discussions on the dark web and uncovering associated metadata insights into characteristics, behaviours and motivation of CSAM creators.

Participants and Setting: We have conducted an …

The Evolution Of The Internet And Social Media: A Literature Review, Charles Alves De Castro, Isobel O'Reilly Dr, Aiden Carthy

Articles

This article reviews and analyses factors impacting the evolution of the internet, the web, and social media channels, charting historic trends and highlight recent technological developments. The review comprised a deep search using electronic journal databases. Articles were chosen according to specific criteria with a group of 34 papers and books selected for complete reading and deep analysis. The 34 elements were analysed and processed using NVIVO 12 Pro, enabling the creation of dimensions and categories, codes and nodes, identifying the most frequent words, cluster analysis of the terms, and creating a word cloud based on each word's frequency. The …

Knowtext: Auto-Generated Knowledge Graphs For Custom Domain Applications, Bojan Bozic, Jayadeep Kumar Sasikumar, Tamara Matthews

Articles

While industrial Knowledge Graphs enable information extraction from massive data volumes creating the backbone of the Semantic Web, the specialised, custom designed knowledge graphs focused on enterprise specific information are an emerging trend. We present “KnowText”, an application that performs automatic generation of custom Knowledge Graphs from unstructured text and enables fast information extraction based on graph visualisation and free text query methods designed for non-specialist users. An OWL ontology automatically extracted from text is linked to the knowledge graph and used as a knowledge base. A basic ontological schema is provided including 16 Classes and Data type Properties. The …

Rces: Rapid Cues Exploratory Search Using Taxonomies For Covid-19, Wei Li, Rishi Choudhary, Arjumand Younus, Bruno Ohana, Nicole Baker, Brendan Leen, Muhammad Atif Qureshi

Articles

To assist the COVID-19 focused researchers in life science and healthcare in understanding the pandemic, we present an exploratory information retrieval system called RCES. The system employs a previously developed EVE (Explainable Vector-based Embedding) model using DBpedia and an adopted model using MeSH taxonomies to exploit concept relations related to COVID-19. Various expansion methods are also developed, along with explanations and facets that collectively form rapid cues for a valuable navigational and informed user experience.

Hybrid Modelling For Stroke Care: Review And Suggestions Of New Approaches For Risk Assessment And Simulation Of Scenarios, Tilda Herrgårdh, Vince I. Madai, John Kelleher, Rasmus Magnusson, Mika Gustafsson, Lili Milani, Peter Gennemark, Gunnar Cedersund

Articles

Stroke is an example of a complex and multi-factorial disease involving multiple organs, timescales, and disease mechanisms. To deal with this complexity, and to realize Precision Medicine of stroke, mathematical models are needed. Such approaches include: 1) machine learning, 2) bioinformatic network models, and 3) mechanistic models. Since these three approaches have complementary strengths and weaknesses, a hybrid modelling approach combining them would be the most beneficial. However, no concrete approach ready to be implemented for a specific disease has been presented to date. In this paper, we both review the strengths and weaknesses of the three approaches, and propose …

Size Matters: The Impact Of Training Size In Taxonomically-Enriched Word Embeddings, Alfredo Maldonado, Filip Klubicka, John D. Kelleher

Articles

Word embeddings trained on natural corpora (e.g., newspaper collections, Wikipedia or the Web) excel in capturing thematic similarity (“topical relatedness”) on word pairs such as ‘coffee’ and ‘cup’ or ’bus’ and ‘road’. However, they are less successful on pairs showing taxonomic similarity, like ‘cup’ and ‘mug’ (near synonyms) or ‘bus’ and ‘train’ (types of public transport). Moreover, purely taxonomy-based embeddings (e.g. those trained on a random-walk of WordNet’s structure) outperform natural-corpus embeddings in taxonomic similarity but underperform them in thematic similarity. Previous work suggests that performance gains in both types of similarity can be achieved by enriching natural-corpus embeddings with …

A Framework For Evaluating Model-Driven Self-Adaptive Software Systems, Basel Magableh

Articles

In the last few years, Model Driven Development (MDD), Component-based Software Development (CBSD), and context-oriented software have become interesting alternatives for the design and construction of self-adaptive software systems. In general, the ultimate goal of these technologies is to be able to reduce development costs and effort, while improving the modularity, flexibility, adaptability, and reliability of software systems. An analysis of these technologies shows them all to include the principle of the separation of concerns, and their further integration is a key factor to obtaining high-quality and self-adaptable software systems. Each technology identifies different concerns and deals with them separately …

A Deep Recurrent Q Network Towards Self-Adapting Distributed Microservices Architecture (In Press), Basel Magableh

Articles

One desired aspect of microservices architecture is the ability to self-adapt its own architecture and behaviour in response to changes in the operational environment. To achieve the desired high levels of self-adaptability, this research implements the distributed microservices architectures model, as informed by the MAPE-K model. The proposed architecture employs a multi adaptation agents supported by a centralised controller, that can observe the environment and execute a suitable adaptation action. The adaptation planning is managed by a deep recurrent Q-network (DRQN). It is argued that such integration between DRQN and MDP agents in a MAPE-K model offers distributed microservice architecture …

Deep Q Learning For Self Adaptive Distributed Microservices Architecture (In Press), Basel Magableh

Articles

One desired aspect of a self-adapting microservices architecture is the ability to continuously monitor the operational environment, detect and observe anomalous behavior, and provide a reasonable policy for self-scaling, self-healing, and self-tuning the computational resources in order to dynamically respond to a sudden change in its operational environment. The behaviour of a microservices architecture is continuously changing overtime, which makes it a challenging task to use a statistical model to identify both the normal and abnormal behaviour of the services running. The performance of the microservices cluster could fluctuate around the demand to accommodate scalability, orchestration and load balancing demands. …

Context Oriented Software Middleware, Basel Magableh

Articles

This article proposes a new paradigm for building an adaptive middleware that supports software systems with self-adaptability and dependability. In this article, we wish to explore how far we can support the engineering of self- adaptive applications using a generic and platform-independent middleware architecture provided by non-specialised programming languages such as Context-Oriented Programming (COP), and Aspect-Oriented Programming (AOP), and not limited to a specific platform or framework. This gives the software developers the flexibility to construct a self-adaptive application using a generic and reusable middleware components that employ popular design patterns, instead of forcing the software developers to use a …

Design Of Event-Triggered Fault-Tolerant Control For Stochastic Systems With Time-Delays, Yi Gao, Yunji Li, Li Peng, Junyu Liu

Articles

This paper proposes two novel, event-triggered fault-tolerant control strategies for a class of stochastic systems with state delays. The plant is disturbed by a Gaussian process, actuator faults, and unknown disturbances. First, a special case about fault signals that are coupled to the unknown disturbances is discussed, and then a fault-tolerant strategy is designed based on an event condition on system states. Subsequently, a send-on-delta transmission framework is established to deal with the problem of fault-tolerant control strategy against fault signals separated from the external disturbances. Two criteria are provided to design feedback controllers in order to guarantee that the …

Quantitative Fine-Grained Human Evaluation Of Machine Translation Systems: A Case Study On English To Croatian, Filip Klubicka, Antonio Toral, Victor Manuel Sanchez-Cartagena

Articles

This paper presents a quantitative fine-grained manual evaluation approach to comparing the performance of different machine translation (MT) systems. We build upon the well-established Multidimensional Quality Metrics (MQM) error taxonomy and implement a novel method that assesses whether the differences in performance for MQM error types between different MT systems are statistically significant. We conduct a case study for English-to- Croatian, a language direction that involves translating into a morphologically rich language, for which we compare three MT systems belonging to different paradigms: pure phrase-based, factored phrase-based and neural. First, we design an MQM-compliant error taxonomy tailored to the relevant …

Energy Efficient Hybrid Routing Protocol Based On The Artificial Fish Swarm Algorithm And Ant Colony Optimisation For Wsns, Xinlu Li, Brian Keegan, Fredrick Mtenzi

Articles

Wireless Sensor Networks (WSNs) are a particular type of distributed self-managed network with limited energy supply and communication ability. The most significant challenge of a routing protocol is the energy consumption and the extension of the network lifetime. Many energy-efficient routing algorithms were inspired by the development of Ant Colony Optimisation (ACO). However, due to the inborn defects, ACO-based routing algorithms have a slow convergence behaviour and are prone to premature, stagnation phenomenon, which hinders further route discovery, especially in a large-scale network. This paper proposes a hybrid routing algorithm by combining the Artificial Fish Swarm Algorithm (AFSA) and ACO …

Experienced Mental Workload, Perception Of Usability, Their Interaction And Impact On Task Performance, Luca Longo

Articles

No abstract provided.

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.

Primitivec-Adl: Primitive Component Architecture Description Language, Basel Magableh

Articles

In this paper, we introduce an architecture descrip- tion language (ADL) for PCOMs (a context oriented component model). The language is described at three levels: (1) Building blocks (PCOMs context oriented components types) (2) Connec- tors, which connect components externally and internally, and (3) Architectural Configuration, which includes a full description of composition and decomposition mechanisms.

The contribution is designing ADL. That supports context- orinted component by providing new architecture elements, which fulfil the requirements of designing context oriented component based applications. Context oriented component is a behavioural unit composed of static parts and dynamic parts. A PCOMs component model …

The Implementation Of A Visco-Hyperelastic Numerical Material Model For Simulating The Behaviour Of Polymer Foam Materials, Conor Briody, Barry Duignan, Stephen Jerrams, John Tiernan

Articles

Polyurethane foam has been in use for some time in wheelchair seating systems as it offers good pressure relieving capabilities in most cases. However, little characterisation work has gone into seating foam materials by comparison with conventional elastomeric materials. Accurate material models could allow better prediction of foam in-service behaviour, which could potentially improve seating design practises. The objective of this work was to develop an approach for the validation of hyperelastic and viscoelastic material model parameters used to simulate polyurethane foam behaviour. Material parameters were identified from relevant test procedures and implemented in a Finite Element simulation of an …

Computation Of The Stochastic Volatility And Levy Index Using The Kolmogorov-Feller Equation With Applications To Carbon Price Data Analysis, Jonathan Blackledge, Marc Lamphiere, Afshin Panahi

Articles

We derive new algorithms for computing time variations in the Stochastic Volatility and the L´evy index using a standard financial price model and a Green’s function solution to the Kolmogorov-Feller equation. A principal condition upon which the algorithms are based is the Phase Only Condition which allows the Power Spectral Density Function of a financial time series (specifically the log price differences) to be taken to be a constant. The paper is composed of four component parts: (i) the Stochastic Volatility is derived and studied numerically; (ii) the Kolmogorov-Feller equation is studied and solved to provide a model for the …

Clinical Coverage Of An Archetype Repository Over Snomed-Ct., Sheng Yu, Damon Berry, Jesus Bisbal

Articles

Clinical archetypes provide a means for health professionals to design what should be communicated as part of an Electronic Health Record (EHR). An ever-growing number of archetype definitions follow this health information modelling approach, and this international archetype resource will eventually cover a large number of clinical concepts. On the other hand, clinical terminology systems that can be referenced by archetypes also have a wide coverage over many types of health-care information.

No existing work measures the clinical content coverage of archetypes using terminology systems as a metric. Archetype authors require guidance to identify under-covered clinical areas that may need …

An Evaluation Of The Eeg Alpha-To-Theta And Theta-To-Alpha Band Ratios As Indexes Of Mental Workload, Bujar Raufi, Luca Longo

Articles

Many research works indicate that EEG bands, specifically the alpha and theta bands, have been potentially helpful cognitive load indicators. However, minimal research exists to validate this claim. This study aims to assess and analyze the impact of the alpha-to-theta and the theta-to-alpha band ratios on supporting the creation of models capable of discriminating self-reported perceptions of mental workload. A dataset of raw EEG data was utilized in which 48 subjects performed a resting activity and an induced task demanding exercise in the form of a multitasking SIMKAP test. Band ratios were devised from frontal and parietal electrode clusters. …

A Full-Range, Multi-Variable, Cfd-Based Methodology To Identify Abnormal Near-Wall Hemodynamics In A Stented Coronary Artery, Jonathan Murphy, Fergal Boyle

Articles

The benefit of coronary stent implantation is reduced by excessive intimal hyperplasia which re-narrows the artery and the prevention of which is still a primary concern for clinicians. Abnormal hemodynamics create non-physiological viscous stress on the artery wall, one of the root causes of intimal hyperplasia following stent implantation. A methodology to comprehensively evaluate the viscous stress on the artery wall following stent implantation would be useful to evaluate a stent’s hemodynamic performance. The proposed methodology employs 3D computational fluid dynamics, the variables wall shear stress (WSS), WSS gradient (WSSG), WSS angle gradient (WSSAG) and a statistical analysis to evaluate …