Engineering Commons^™

Virtual Humans In Virtual Reality: A Scoping Review On Sociability, Fidelity, And Expression, J K Sangeeth Chandran, Marisa Llorens Salvador, Cathy Ennis

Articles

Introduction:

Virtual reality (VR) systems have evolved significantly over the past decade, enabling immersive experiences with enhanced realism and interactivity. This has motivated an interest in socially oriented applications. As user proxies, Virtual Humans (VHs) play essential roles in such applications. However, despite technological advancements, achieving realistic, expressive, and socially responsive VHs continues to present design and implementation challenges. In this scoping review, we present the state-of-the-art of VR VHs, examining the impact of VHs on the user experience.

Methodology:

We reviewed 59 papers retrieved from five databases across three core themes: the implementation and impact of VH facial expressions, …

Biomechanical Advancements In Hydroxyapatite, Magnesium-Substituted Hydroxyapatite, And Strontium-Substituted Hydroxyapatite In Clinical And Non-Clinical Studies For Maxillofacial Bone Tissue Engineering: A Review, Elham Zafarrazzaghnia, Stuart Hampshire, Aran Rafferty, Dermot Brabazon, Eamonn Debarra, Maura Kelleher

Articles

Hydroxyapatite (HA) is a bioceramic known for its bioactivity and osteoconductivity, which should make it an ideal candidate for maxillofacial bone regeneration. However, its brittleness limits its suitability for load-bearing applications. Over recent decades, substantial efforts have focused on enhancing its performance, particularly through ionic substitution, including magnesium-substituted HA (Mg-HA) and strontium-substituted HA (Sr-HA). This review summarises the available information on the structural, physical and mechanical properties of facial bones (maxilla, mandible, zygoma and frontal bone). The crystal structure, physical, and mechanical properties and in-vitro biological responses of dense and porous HA, Mg-HA and Sr-HA ceramics are described, with particular …

Bending Energy Schemes For Discrete-Spring-Network Structural Modelling Of Red Blood Cells, Osayomwanbor Ehi-Egharevba, Mingzhu Chen, Fergal Boyle

Articles

Red blood cells (RBCs) undergo large structural deformation, including bending, when passing through capillaries. They also exhibit a range of complex shapes such as stomatocytes, discocytes and echinocytes that form due to altered blood pH and salt levels, ingested drugs and adenosine triphosphate depletion. Discrete-spring-network structural models of RBCs employ different numerical treatments of the continuum bending energy. This affects bending accuracy and the prediction of accurate RBC shapes. This research compares three representations called bending energy scheme (BES) A, B and C to evaluate their accuracy in shape predictions. BES A, seen throughout the literature, is based on the …

Shrinkage Study In Photopolymerisable Hybrid Sol-Gel Through Holographic Patterning, Jamshed Aftab, Izabela Naydenova, Tatsiana Mikulchyk

Articles

Photopolymerisation induced shrinkage of holographic materials is one of the main factors which needs to be considered for designing holographic optical elements (HOEs) with high accuracy in light redirection with maximum efficiency. This work studies the shrinkage in photopolymerisable hybrid sol-gel (PHSG) by examining the properties of volume transmission gratings recorded in PHSG layers. It explores both the dependence of shrinkage on the holographic grating parameters (thickness, spatial frequency, slant angle) and the effect of material aging. By using the fringe-plane rotation model, shrinkage is found to have the maximum value of 1.37 % at 765 lines/mm (19.36° slant angle) …

An Empirical Evaluation Of Communication Technologies And Quality Of Delivery Measurement In Networked Microgrids, Ruairí De Fréin, Yasin Emir Kutlu

Articles

Networked microgrids (NMG) are gaining popularity as an example of smartgrids (SG), where power networks are integrated with communication technologies. Communication technologies enable NMGs to be monitored and controlled via communication networks. However, ensuring that communication networks in NMGs satisfy quality of delivery (QoD) metrics such as the round trip time (RTT) of NMG control data is necessary. This paper addresses the communication network types and communication technologies used in NMGs. We present various NMG deployments to demonstrate real-life applicability in different contexts. We develop a real-time NMG testbed using real hardware such as Cisco 4331 Integrated Services Routers (ISR). …

Integrating Standards For Infrastructure Improvement And Resilience In University Curricula, Lisa Greenwood, Jennifer Schneider, Sumita Mishra, Yewande S. Abraham, Shriram Karpoora Sundara Pandian

Articles

In today’s ever-changing world, we are increasingly vulnerable to shocks and stresses that disrupt industry and society. Persistent threats from natural and manmade hazards require our communities and infrastructure to be resilient despite possible disruption. Creating robust infrastructures is founded on operational and physical standards to withstand and respond to threats such as environmental exposures, climate change, and informational security breaches. The significant U.S. investment in infrastructure projects through the Infrastructure Investment and Jobs Act has amplified the need for professionals in engineering and related fields who – in addition to technical knowledge - possess the necessary knowledge and skill …

Flow Dynamics Of Agricultural Waste Nanofibers: Shear, Temperature, And Oscillatory Insights, Bilge N. Altay, Burak Aksoy, James Atkinson, Christopher Lewis, Carlos Diaz-Acosta, Raymond Francis

Articles

The rheology and fiber size of corn stover (CS) and cleaned cotton gin trash (CGT) cellulose nanofibers (CNFs) were studied including behaviors at both moderate and extremely high shear rates, to simulate industrial processes ranging from mixing and pumping to high-speed coating, printing, and extrusion. Particle size analyzer showed that 99% of CS fibers measured around 226 nm, while 85% of CGT fibers were approximately 143 nm. Both CS and CGT CNFs formed gel-like suspensions, and shear flow tests revealed that all samples exhibited shear-thinning behavior, allowing easy flow under shear forces. Gels with higher solid content (1%) demonstrated extended …

Quantifying The Role Of Active Listening And Reassurance In Virtual Health Coach Interactions, Ghulam Hussain, Brian Keegan, Robert Ross

Articles

Conversational Agents have the potential to support healthcare through coaching exercise routines, but are still lacking in demonstrating authentic social behaviours to support engagement. To this end, we present a series of experiments that we conducted in order to investigate how automated health care coaches can be more effective when their interaction style is tailored to demonstrate qualities associated with a good bedside manner, namely active listening and reassurance. To test this, we first developed a dataset of 135 dialogue excerpts from three distinct sources, i.e., original, handcrafted and LLMs, the latter two of which were tuned to demonstrate specific …

A Review Of Chemical Stabilisation Used To Enhance The Mechanical Properties Of Rammed Earth, David Thompson, Charles Augarde, Juan Pablo Osorio

Articles

Rammed earth is a sustainable construction method with a lower carbon footprint and embodied energy compared to traditional materials like steel and concrete. However, its lower mechanical properties when compared to these forms of construction make it vulnerable to seismic forces. This paper reviews the published literature on enhancing rammed earth's mechanical properties through both chemical stabilisation and fibre reinforcement, with a focus on reusing waste materials. The effectiveness of these techniques are highlighted by comparing experimental results with minimum specifications taken from relevant guidelines and standards for building rammed earth structures in seismic zones. These findings demonstrate that chemical …

Sustainable Enzymatic Extraction Of High-Purity Chitin From Button Mushroom (Agaricus Bisporus) Off-Production Waste: Influence Of Alkaline Pre-Treatment On Physicochemical Properties, Buliyaminu A. Alimi, Shivani Pathania, Jude Wilson, Brendan Duffy, Jesus Maria Frias

Articles

This study investigated chitin extraction from the stalks and atypical mushrooms, the often-produced waste in the mushroom production process, using a simultaneous application of protease and glucanase with or without an alkaline pretreatment stage. A commercial chitin, chemically extracted from A. bisporus was used as the control. The purity of extracted chitin (98.92–99.36 %) was slightly lower than commercial chitin (99.80 %), but with comparable physicochemical properties (p < 0.05). All enzymatically extracted chitin in this study exhibited an agglomerated, microfibrillar and irregular structure, while the control showed standalone granules with weathering and cracks on the surfaces. The XRD and FTIR spectra indicated that the extracted chitin and the control belong to the α-allotrope group. The degree of acetylation was higher in the extracted chitin (76.97–78.22 %) than in the control (75.05 %). The highest molecular weight obtained for the extracted chitin was 4.53 × 102 KDa (W0548). The study demonstrated the possibility of producing pure, high molecular weight chitin from the waste produced during the commercial production of button mushrooms, using a potentially more sustainable approach than the traditional one. This enzymatic approach reduces chemical waste, as shown by the excellent results obtained for samples without the pre-treatment stage, and improves environmental safety compared to traditional methods.

Enhancement Of Intersystem Crossing In Asymmetrically Substituted Bodipy Photosensitizers, Mikhail Filatov, Tatsiana Mikulchyk, Maxine Hodee, Metodej Dvoracek, Venkata N.K. Mamillapalli, Aimee Sheehan, Craig Newman, Sergey M. Borisov, Daniel Escudero, Izabela Naydenova

Articles

We present a novel method to promote intersystem crossing (ISC) and triplet state formation in boron dipyrromethenes (BODIPYs) through the asymmetrical introduction of functional groups within the chromophore. This approach enables the development of new BODIPY photosensitizers without relying on the incorporation of heavy atoms or large electron-donating aromatic groups. Demonstrated on a series of 14 synthesized asymmetrical BODIPY (aBDP) compounds, it significantly enhances photosensitization efficiency compared to the reference symmetrical BODIPYs. In particular, the asymmetrical introduction of ethoxycarbonyl groups into pyrrolic rings of the BODIPY core lead to efficient ISC and singlet oxygen generation, with quantum yields reaching 0.76 …

Hypnosis And Mindfulness Audio Recordings For Reducing Fatigue In Individuals With Multiple Sclerosis: A Randomized Controlled Study, Mark P. Jensen, Susan Robles, Michael G. Nash, Susanne May, Dwan M. Ehde, Melissa A. Day, Owen Gottlieb, Laurence I. Sugarman, Kevin N. Alschuler

Articles

Background

Fatigue is a common problem in individuals with multiple sclerosis (MS).

Objective

The objective was to evaluate the effects on fatigue of having 4 weeks of

access to audio recordings of therapeutic hypnosis (HYP) and mindfulness meditation

(MM) practices.

Methods

A total of 333 individuals with MS and fatigue were randomly assigned to

one of the three treatment conditions for 28 weeks: (1) access to therapeutic HYP audio

recordings, (2) access to MM audio recordings, or (3) no access to recordings

(treatment as usual or TAU). Fatigue impact (primary outcome) and other outcomes

were assessed at 4, 16, and …

Power Utilization In Open Ran: Key Findings From A Usa Testbed, Saish Urumkar, Byrav Ramamurthy, Seshu Tirupathi, Sachin Sharma

Articles

Open Radio Access Networks (Open RAN) provide flexible, scalable, and interoperable solutions to address the growing demands of mobile traffic while also aiming to reduce energy consumption. Most prior research on energy-efficient Open RAN has focused on switching techniques such as dynamic cell on/off strategies and adaptive resource allocation, primarily through simulations. This letter investigates Central Processing Unit (CPU) power utilization at the NodeB (base station) level, focusing on User Equipment (UE) connection states by making use of a USA testbed (i.e., POWDER testbed). Two scenarios are considered for the experimental setup: (1) a simulated virtual environment with a single …

Winter Solstice Phenomenon At Newgrange: Research Report 2024, Frank Prendergast

Articles

This report, commissioned by the National Monuments Service presents a comprehensive analysis of the high-resolution photographic and video recordings of the solar illumination inside the burial chamber at Newgrange passage tomb, located within the UNESCO World Heritage Site of Brú na Bóinne – Archaeological Ensemble of the Bend of the Boyne.

Sustainable Mobility: Machine Learning-Driven Deployment Of Ev Charging Points In Dublin, Ruairí De Fréin, Alexander Mutiso Mutua Mr

Articles

Electric vehicle (EV) drivers in urban areas face range anxiety due to the fear of running out of charge without timely access to charging points (CPs). The lack of sufficient numbers of CPs has hindered EV adoption and negatively impacted the progress of sustainable mobility. We propose a CP distribution algorithm that is machine learning-based and leverages population density, points of interest (POIs), and the most used roads as input parameters to determine the best locations for deploying CPs. The objects of the following research are as follows: (1) to allocate weights to the three parameters in a $6$ km …

Towards An Iot-Enabled Digital Earth For Sdgs: The Data Quality Challenge, Msb Syed, Paula Kelly, Paul Stacey, Damon Berry

Articles

Digital Earth (DE), a technology offering real-time visualisation of Earth's processes, has shown promising results in aiding decision-making for a sustainable world, raising awareness about individual impacts on our planet, and supporting the United Nations Sustainable Development Goals (UN SDGs) agenda. However, both DE and SDGs face a common obstacle: Data Quality (DQ). This review investigates the challenge of DQ in the context of DE for SDGs and explores how IoT can address this challenge and extend the reach of DE to support SDGs. Furthermore, the study discusses three core aspects; first, the potential of IoT as a data source …

A Global Model-Agnostic Rule-Based Xai Method Based On Parameterized Event Primitives For Time Series Classifiers, Ephrem T. Mekonnen, Luca Longo, Pierpaolo Dondio

Articles

Time series classification is a challenging research area where machine learning and deep learning techniques have shown remarkable performance. However, often, these are seen as black boxes due to their minimal interpretability. On the one hand, there is a plethora of eXplainable AI (XAI) methods designed to elucidate the functioning of models trained on image and tabular data. On the other hand, adapting these methods to explain deep learning-based time series classifiers may not be straightforward due to the temporal nature of time series data. This research proposes a novel global post-hoc explainable method for unearthing the key time steps …

Early Age Assessment Of A New Course Of Irish Fly Ash As A Cement Replacement, Niall Holmes Dr., Nikki Shaji, Mark Tyrer

Articles

This paper explores the potential of a new source of fly ash, deposited on the site of a coalfired power plant in Ireland dating from 1985 to 1995, as a cement replacement material. A series of X-ray diffraction (XRD) analyses on binder samples with cement replacement levels of 0, 10, 25 and 35% was undertaken to determine the fly ash’s mineralogical composition and to determine its suitability as a supplemental cementitious material (SCM). The XRD results reveal a unique mineral composition with promising characteristics for enhancing the strength and durability of concrete. The experimental results were used to calibrate a …

Explainable Machine Learning For The Regulatory Environment: A Case Study In Micro-Droplet Printing, Elaine Harris, Darragh F. Ryan, Gerard M. O'Connor

Articles

Micro-droplet printing remains an invaluable tool for the additive manufacturing industry due to its versatility, efficiency and cost-effectiveness. The design and deployment of a disposable micro-droplet dispenser seeks to facilitate a quick and easy way to alternate between different printing materials (such as ink, metals, bio-materials, pharmaceuticals, etc.) without the need for thorough cleaning or separate delivery systems. While this works well in principle, in practice achieving consistent performance between dispensers can prove challenging. This paper aims to tackle this issue through the use of Machine Learning (ML) in order to (1) build a model that predicts dispenser performance from …

Comparative Assessment Of Gold Nanoparticle-Antibody Conjugates With Two Differently Shaped Particles For Multimodal Colorimetric Lateral Flow Assay, Vinayak Sharma, Bilal Javed, Furong Tian

Articles

Novel detection strategies that exploit the unique properties of gold nanoparticles (AuNPs) hold great potential for the advancement of point-of-care (POC) diagnostics, such as lateral flow and dipstick immunoassay [1–3]. Owing to its biocompatibility and convenient surface modifications, gold nanoparticles with enhanced sensitivity reduce the sample-to-answer times to less than 5 min (Figure 1). Methods like covalent conjugation and electrostatic adsorption are explored for antibody immobilization to develop a gold nanoparticle-based biosensor for fast and sensitive localized surface plasmon resonance (LSPR) for both basic research and clinical diagnostics. The mounting of antibodies on the gold nanoparticle surface requires selective binding …

Comparing Anova And Powershap Feature Selection Methods Via Shapley Additive Explanations Of Models Of Mental Workload Built With The Theta And Alpha Eeg Band Ratios, Bujar Raufi, Luca Longo

Articles

Background: Creating models to differentiate self-reported mental workload perceptions is challenging and requires machine learning to identify features from EEG signals. EEG band ratios quantify human activity, but limited research on mental workload assessment exists. This study evaluates the use of theta-to-alpha and alpha-to-theta EEG band ratio features to distinguish human self-reported perceptions of mental workload. Methods: In this study, EEG data from 48 participants were analyzed while engaged in resting and task-intensive activities. Multiple mental workload indices were developed using different EEG channel clusters and band ratios. ANOVA’s F-score and PowerSHAP were used to extract the statistical features. At …

Hygrothermal Risk Assessment Of External Wall Insulation Retrofit To Non-Traditional Wall Types In An Irish Context, Using The Glaser Method And A Heat, Air And Moisture Transient Model, Gareth Mcdonnell, Joseph Little

Articles

The Climate Action Plan 2019 targets the low-energy retrofit of 500,000 existing Irish homes before 2030.1 Up to 80 per cent of building failures can be attributed to moisture risks.2 The literature indicated that external wall insulation (EWI, ETICS) failures are mostly due to moisture ingress at junctions and interfaces. A hygrothermal risk assessment of EWI on three walls with rendered concrete/concrete blockwork/cavity walls in Dublin, Belfast and Belmullet was undertaken using transient numerical simulation and the Glaser method. The guidance, common practice indicates a preference for Glaser. The initial simulation results were compared to assess the appropriateness of Glaser. …

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 …

Inclusive Counterfactual Generation: Leveraging Llms In Identifying Online Hate, M. Atif Qureshi, Arjumand Younus, Simon Caton

Articles

Counterfactually augmented data has recently been proposed as a successful solution for socially situated NLP tasks such as hate speech detection. The chief component within the existing counterfactual data augmentation pipeline, however, involves manually flipping labels and making minimal content edits to training data. In a hate speech context, these forms of editing have been shown to still retain offensive hate speech content. Inspired by the recent success of large language models (LLMs), especially the development of ChatGPT, which have demonstrated improved language comprehension abilities, we propose an inclusivity-oriented approach to automatically generate counterfactually augmented data using LLMs. We show …

Explainable Ai For 6g Use Cases: Technical Aspects And Research Challenges, Shen Wang, M. Atif Qureshi, Luis Miralles-Pechu{\'A}N, Thien Huynh-The, Thippa Reddy Gadekallu, Madhusanka Liyanage

Articles

Around 2020, 5G began its commercialization journey, and discussions about the next-generation networks (such as 6G) emerged. Researchers predict that 6G networks will have higher bandwidth, coverage, reliability, energy efficiency, and lower latency, and will be an integrated “human-centric” network system powered by artificial intelligence (AI). This 6G network will lead to many real-time automated decisions, ranging from network resource allocation to collision avoidance for self-driving cars. However, there is a risk of losing control over decision-making due to the high-speed, data-intensive AI decision-making that may go beyond designers’ and users’ comprehension. To mitigate this risk, explainable AI (XAI) methods …

A Multi-Life Cycle Assessment Of External Wall Insulation Strategies In An Irish Domestic Retrofit, Sara Carrigan, Patrick Daly, Alberta Congeduti

Articles

European Union (EU) policy and initiatives are driving both building renovation and the uptake of low-embodied carbon and circular design in the construction sector. The European Performance of Buildings Directive (EPBD) recast (2021) introduces global warming potential (GWP) methodology, and the future state will likely be embodied carbon targets for which life cycle assessment (LCA) of buildings will be required. External wall insulation (EWI) will have an important role to play in meeting targets. In this context, this paper compares the carbon emission payoff of three alternative EWI strategies that address conventional, low-carbon and circular solutions to EWI respectively, in …

Analysis Of Delta In-Out For Irish Natural Gas Distribution Network, Utkarsha Chavan, Anthony Reynolds, Michael Carr, L. Walsh

Articles

This article investigates the issue of Unaccounted for Gas (UAG) in the natural gas distribution network of Ireland, focusing on the DeltaIO (i.e. the difference between the gas entering and leaving the network). The study applies the DeltaIO methodology developed for Italian distribution networks to Gas Networks Ireland (GNI), the sole Distribution System Operator (DSO) in Ireland. The analysis covers the period from 2013 to 2019 and provides insights into the magnitude and trends of UAG in the Irish context. The results show that GNI's DeltaIO ranges from 0.93% to 1.57%, with an average of 1.15%. Comparisons with large Italian …

The Role Of Interpersonal Conflict As A Cause Of Work-Related Stress In Construction Managers In Ireland, Patrick J. Bruce, Victor Hrymak, Carol M. Bruce Dr, Joseph Byrne

Articles

Construction is a project-driven industry that places a high premium on product delivery on time, within budget and to required standards. Modern construction projects have become more complex in nature, the complex relational and lengthy process of designing and building makes construction a process in which conflict is virtually ensured (Jaffar et al., 2011; Wang et al., 2023). These characteristics of the industry contribute to workplace stress. Therefore, it is not surprising that research has confirmed a strong presence of workplace stress within the industry, (Lingard and Francis, 2004; Vaux and Dority, 2020). Many construction managers experience excessive levels of …

A Review On Machine Learning Methods For Customer Churn Prediction And Recommendations For Business Practitioners, Awais Manzoor, M. Atif Qureshi, Etain Kidney, Luca Longo

Articles

Due to market deregulation and globalisation, competitive environments in various sectors continuously evolve, leading to increased customer churn. Effectively anticipating and mitigating customer churn is vital for businesses to retain their customer base and sustain business growth. This research scrutinizes 212 published articles from 2015 to 2023, delving into customer churn prediction using machine learning methods. Distinctive in its scope, this work covers key stages of churn prediction models comprehensively, contrary to published reviews, which focus on some aspects of churn prediction, such as model development, feature engineering and model evaluation using traditional machine learning-based evaluation metrics. The review emphasises …

Disaggregating Longer-Term Trends From Seasonal Variations In Measured Pv System Performance, Chibuisi Chinasaokwu Okorieimoh, Brian Norton, Michael Conlon

Articles

Photovoltaic (PV) systems are widely adopted for renewable energy generation, but their performance is influenced by complex interactions between longer-term trends and seasonal variations. This study aims to remove these factors and provide valuable insights for optimising PV system operation. We employ comprehensive datasets of measured PV system performance over five years, focusing on identifying the distinct contributions of longer-term trends and seasonal effects. To achieve this, we develop a novel analytical framework that combines time series and statistical analytical techniques. By applying this framework to the extensive performance data, we successfully break down the overall PV system output into …