Engineering Commons^™

An Evaluation Of Zero Trust Principles In Modern Software Development, Cezar Vararu, David White

Academic Poster Collection

An evaluation of Zero Trust Principles in modern software development

Cost Optimization In Open Telemetry, Niksa Jadric, Cormac Keogh

Academic Poster Collection

Cost Optimization in Open Telemetry

Exploring Rust’S Performance In A Serverless Environment, Saoirse Mullen, Gary Clynch

Academic Poster Collection

Exploring Rust’s Performance in a Serverless Environment

Performance Evaluation Of Zabbix And Azure Monitor In Hybrid It Infrastructure, Ivan Godoy, Cormac Keogh

Academic Poster Collection

Performance Evaluation of Zabbix and Azure Monitor in Hybrid IT Infrastructure

Ai-Based Predictive Analytics For Network Operations, Timur Nikisin, David White

Academic Poster Collection

AI-Based Predictive Analytics for Network Operations

Nobocap: Unlocking Mdr/Ivdr Regulations For Innovators In Europe, Graham Gavin, Claire Brougham

Conference Papers

The NoBoCap project (nobocap.eu) is aimed at addressing some of the challenges encountered by both SMEs and Notified Bodies across the EU. It is a multi-organizational consortium including universities, a Notified Body, and Bio-health and Innovation Hubs and Clusters. The NoBoCap project has several work packages focussed on:• Design and delivery of funded short-term courses.• Creating a dedicated NB job board.• Design and delivery of funded university accredited modules.• Design and development of e-tools to support manufacturers.• Develop a community platform to act as a voice for start-ups and SMEs

Power Saving In Open Ran By Using Advanced Cpu Scheduling Algorithm, Saish Urumkar, Sachin Sharma

Conference papers

Open RAN is an emerging wireless technology that is gaining significant attention for its potential to enable flexi- ble, cost-efficient, and interoperable networks. Reducing power utilization in Open RAN, particularly for 5G base stations (gNodeBs) deployed in remote areas, remains a critical challenge due to limited power availability. In our previous work, we developed a CPU scheduling algorithm that optimized core allocation based on load conditions, reducing power utilization for gNodeB in a virtualized Open RAN environment. Extending our previous work, this paper introduces an advanced CPU scheduling for Open RAN designed to reduce power utilization in real hardware Open …

Demonstrating The Impact Of Cpu Scheduling On Power Consumption In Virtualized Open Ran, Saish Urumkar, Sachin Sharma

Conference papers

Open RAN (Open Radio Access Network) is a next- generation wireless network gaining significant research interest globally due to its potential to provide a cost-efficient and scalable solution for growing network demands. Energy efficiency is an important area of focus in Open RAN deployments, as reducing power consumption while maintaining network performance is essential for sustainable wireless communication. This paper demonstrates the impact of CPU (Central Processing Unit) scheduling process priorities on power consumption and network performance in an Open RAN NodeB deployed on a testbed in the USA. The experimental results are demonstrated using two scenarios: (1) CPU Priority-Based …

Multi-Objective Deep Reinforcement Learning For Dynamic Algorithm Selection In Open Ran, Saish Urumkar, Byrav Ramamurthy, Sachin Sharma

Conference papers

Open Radio Access Networks (Open RAN) provide flexible, modular multi-vendor interoperability. Growing mobile data demand requires balancing network performance with power efficiency. Mobile operators need intelligent resource management to achieve Key Performance Indicator (KPI) targets while maintaining operational efficiency. This paper proposes a solution using a multi-objective deep reinforcement learning (MODRL) model deployed on the Open RAN Intelligent Controller (RIC). Three customizable operator profiles (Power Saving, Balanced, and Performance) are used which define specific priority ratios between performance and power saving objectives.

To evaluate, individual algorithms (CPU scheduling and UE connection state switching) are implemented in Open RAN, achieving 5–20%CPU …

Pac-Oran: Power Saving Cpu Scheduling Approach For Scalable Mobile Ues In Open Ran, Saish Urumkar, Byrav Ramamurthy, Somayeh Mohammady, Sachin Sharma

Conference papers

Open RAN is a next-generation wireless network technology that promotes flexibility, cost efficiency, and interoperability through disaggregation and open interfaces. Energy efficiency remains a key challenge, especially in scalable deployments with many connected User Equipments (UEs), where dynamic power management at the gNodeB is critical. In this paper PAC-ORAN (Power-saving Adaptive CPU Scheduling for Open RAN) is proposed which is an advanced CPU scheduling algorithm evaluated with a large number of connected UEs to gNodeb. PAC-ORAN includes an advanced method using moving average adaptive threshold selection and dynamically adjusting CPU core states and frequency tuning based on real-time CPU metrics. …

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.

Cnns And Transformers For Visual Understanding: From Feature Alignment To Image Captioning, Xuehao Liu

Doctoral

Deep learning has developed rapidly since the introduction of Deep Belief Networks during the past decade. As an area of machine learning, it still has many open challenges. Among these open challenges is the issue of transparency, with deep learning models known as black boxes. Both explainability of a model for understanding the decision making process, and the transparency of the relationship between the input and output are crucial for understanding a model. The understanding of models can build trust between AI systems and humans, verify models behavior, and identify potential biases or errors.

Navigating Human-Robotic Interaction Challenges In Teaching-By-Demonstration, Shakra Mehak

Doctoral

The advancement in interdisciplinary research domains, like robotics and HRI, presents a challenging task. It is an exception rather than the norm for research to extend beyond the boundaries of individual disciplines and encompass the challenges presented by other fields of study. This project is part of ”Collaborative Intelligence for Safety Critical Systems” (CISC), which is a Marie Curie Training Network funded by the European Commission to hire and train researchers with the expertise and skillset necessary to carry out the major tasks required to develop a Collaborative Intelligence system. The program encompasses four overarching themes: Artificial Intelligence (AI), Human …

Personalized Persuasion In The Digital Age: A Data-Driven Approach To Effective Communication, Annye Braca

Doctoral

This thesis investigates the potential of Machine Learning (ML) to personalize persuasive marketing messages. It explores the identification of individuals receptive to specific persuasion techniques based on their psychometric profiles. By developing ML models that incorporate these profiles, the thesis aims to predict the impact of tailored messages and improve the effectiveness of marketing communication.

Machine Learning Applications In Epigenomics And Its Association With Health And Disease, Trevor Doherty

Doctoral

Epigenetic modifications can lead to altered phenotypes without a change in the DNA sequence itself. Disrupted gene expression regulated by epigenetic processes can result in cancers, autoimmune diseases and various other maladies. Machine learning (ML) involves the use of algorithms and models which are trained to learn patterns in data, and has demonstrated remarkable success in solving diverse, complex challenges. Epigenomic studies, such as those that use DNA methylation (DNAm) data, increasingly make use of ML techniques to process extremely high dimensional data obtained from high throughput platforms e.g., DNAm arrays. These datasets suffer from the curse of dimensionality, increased …

Improving Visual Inspection Performance During Pre-Flight Visual Inspections By Aircraft Maintenance Technicians., Patrick Codd

Doctoral

Visual inspection is a critical task in aircraft maintenance and is the predominant inspection technique used in the global aviation sector. For safety reasons, visual inspections by Aircraft Maintenance Technicians are routinely conducted on a daily basis during pre-flight inspections. Its significance becomes evident when considering the potential consequences of Aircraft Maintenance Technicians not seeing observable defects during visual inspections. For example, an aircraft crash landing in 1989 resulted in 111 fatalities and was attributed to a visual inspection failure. The industrial quality control literature also illustrates the varying accuracy for the observation of defects and hazards, underscoring the inherent …

Agency, Index & Process: Investigating The Role Of The Artist’S Body In Digital Sculpture Production, Alan Magee

Doctoral

Contemporary Digital Sculpture has emerged out of recent developments in digital art, 3d modelling and virtual modes of production. These advances range from the creation of more powerful software and hardware systems to the to nascent XR sectors, and the potential for materialisation through technologies such as 3d printing, laser-cutting, or CNC1 machining. However, critical discourse remains predominantly focused on the end product, often overlooking the embodied labour processes inherent in its creation. As revealed through indexical traces of the artist’s body, these processes encapsulate the gestures, actions and subjective agency of artistic activity. Consequently, with the limitations of digital …

Enhancing Trust In Ai For Healthcare: A Quantative Evaluation Of Explainable Methods In Clinical Decision Support Systems, Abdul Aziz Noor

Masters

The integration of Artificial Intelligence (AI) into healthcare has revolutionized Clinical Decision Support Systems (CDSS) by enabling sophisticated predictive capabilities. However, the opaque nature of many machine learning models, commonly referred to as "black-box" systems, poses significant challenges to their adoption in critical clinical settings where transparency, interpretability, and trust are paramount. This thesis addresses these challenges by developing a rigorous, mathematically grounded framework to evaluate Explainable AI (XAI) methods and enhance their integration into CDSS.

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 …

Build Digital Annual Survey 2024 Results, Clare Eriksson, Robert Moore, Bilal Succar

Reports

The Build Digital Annual Survey 2024 presents a sector-wide snapshot of digital adoption and transformation across Ireland’s construction and built environment sector. Based on 137 responses, the report shows that most participating organisations have begun their digital transformation journey, with expected benefits including improved accuracy, operational efficiency, quality, cost reduction, and faster clash resolution. The findings indicate widespread use of common digital deliverables and increasing awareness of ISO 19650, CDEs, OpenBIM, and CWMF BIM requirements. However, the report also identifies persistent challenges, including skills gaps, uneven training provision, limited digital competence, and variable implementation of BIM requirements across public and …

Highly Sensitive Diffractive Optical Structures For Detection Of Volatile Organic Compounds, Faolan Radford Mcgovern

Doctoral

From aerospace to agriculture, sensors play a fundamental role in many aspects of modern life. Sensors form an integral part of the complex systems and devices required for the continued functioning and development of services and industries across society. The use of sensors is paramount in areas affecting human health, one such area being the monitoring of indoor air quality, in particular the detection of volatile organic compounds (VOCs). Human contact with VOCs has been associated with many health complications, including skin and eye irritation, cardiovascular damage, and cancers. Optical, electrical, gravimetric, and chemical sensors have been developed for VOC …

Antennas For Emerging Satellite Services, Jakub Przepiorowski

Doctoral

The NewSpace era has revolutionized access to space, driving advancements in satellite communication (SATCOM) systems and creating demand for low-cost, compact, and high-performance user terminals. This thesis addresses these needs by developing innovative antenna solutions tailored for user terminals designed for emerging satellite constellations and satellite Internet-of-Things (S-IoT) applications.

Bayesian Networks For Safety-Critical Systems, Joseph Mietkiewicz

Theses

This thesis addresses a operational challenge in modern industrial operations: the increasing complexity of systems and the consequent cognitive burden on operators. As industrial technologies advance, the human-computer interface has become the primary conduit for information flow, playing a pivotal role in operational decision-making. However, the proliferation of data often leads to information overload, potentially compromising rather than enhancing operator performance. This research explores an approach to this pressing issue through the application of Bayesian networks as decision support systems in safety- critical scenarios. Our study employs a multi-faceted approach, combining theoretical modeling with empirical testing. Through collaboration with industry …

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 …

The Digital Loophole: Evaluating The Effectiveness Of Child Age Verification Methods On Social Media, Fatmaelzahraa Eltaher, Rahul Gajula, Luis Miralles-Pechuán, Christina Thorpe, Susan Mckeever

Conference papers

Social media platforms are an integral part of daily life for nearly five billion people worldwide. However, the growing presence of underage users on these platforms raises significant concerns regarding children's exposure to harmful content and its impact on their mental health. This paper examines the effectiveness of age verification measures implemented on leading platforms Facebook, YouTube, Instagram, TikTok, Snapchat, and X. We evaluate the age verification processes required for account creation by simulating the registration steps for minors on these platforms. We also compare these methods to best practices in online age assurance in finance, betting and public transportation …

Information Management Plan – Delivery Team, Robert Moore

Tools

Information Management Plan – Delivery Team is a support in a spreadsheet format that contains a number of delivery team (tenderers) templates that ISO 19650 recommend the delivery team (tenderers) should consider when responding to a tender to deliver a project for an Asset.

Build Digital has created Industry templates to allow organisations work in accordance with ISO 19650. These templates start to address the information requirements in the ISO 19650 series of standards. The templates are also in accordance with CEN-TR17654-2021” Guideline for the implementation of Exchange Information Requirements (EIR) and BIM Execution Plans (BEP) on European level based …

How Will Ai Impact Knowledge Sharing Within Construction Clustering? Bringing Back The Conversation On Social Contagion Within Construction Clusters, Oluwasegun O. Seriki, Mark Mulville, Ruairi Hayden

Conference Papers

Construction clusters and innovation systems play a crucial role in enhancing competitiveness and fostering sustainable development in the construction sector. These clusters facilitate knowledge sharing, interactive learning, and collaborative innovation among firms, institutions, and other stakeholders. The success of construction clusters depends on numerous factors, including firm size, economic climate, and attitudes towards innovation. While some clusters transform into innovation systems by becoming tacit-knowledge intensive, there is not much data or investigation into how they may adapt to changing demands spurred by advances in artificial intelligence (AI). There is some preliminary research highlighting the lack of dispersed innovation networks within …

An Evaluation Of Features Extracted From Facial Images In The Context Of Accurate Age Estimation⋆, Malik Awais Khan, Aurelia Power, Peter Corcoran, Christina Thorpe

Conference papers

Age estimation by face image recognition can be used in numerous ways with regression models to manage access control, improve security, and guarantee the protection of children online. The approaches used for predicting age—including data selection, cleaning techniques, feature extraction, algorithm choice, and hyperparameter tuning—often struggles with generalization. Furthermore, a lot of methods neglect to specifically address how extracted face features might be used for prediction. To address the lack of racial diversity we acquired a dataset consisting of different races from literature. We also examined the ability of local, global and hybrid facial features to predict ages. Two variants …

Identifying Subject Bias In Wifi-Based Human Activity Recognition Evaluation Methods, Amany Elkelany, Robert J. Ross, Susan Mckeever

Conference papers

WiFi-based Human Activity Recognition (HAR) has emerged as a promising approach for monitoring and analysing human activities in a non-intrusive manner, leveraging WiFi signals for activity classification. Despite advancements, existing WiFi-based HAR research lacks consideration of subject (human) bias. This results in learning models performing well on individuals used in the training samples but failing to generalise to new/unseen subjects, in contrast to known good practices in machine learning. In this paper, we address this oversight directly by systematically examining the evaluation methodology for the WiFi-based HAR context. Specifically, we investigate the impact of Leave-One-Subject-Out Cross-Validation (LOSOCV) in a hybrid …

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.