Digital Commons Network^™

Towards Sweetness Classification Of Orange Cultivars Using Short‑Wave Nir Spectroscopy, Ayesha Zeb, Waqar Shahid Qureshi, Abdul Ghafoor, Amanullah Malik, Muhammad Imran, Alina Mirza, Mohsin Islam Tiwana, Eisa Alanazi

Articles

The global orange industry constantly faces new technical challenges to meet consumer demands for quality fruits. Instead of traditional subjective fruit quality assessment methods, the interest in the horticulture industry has increased in objective, quantitative, and non-destructive assessment methods. Oranges have a thick peel which makes their non-destructive quality assessment challenging. This paper evaluates the potential of short-wave NIR spectroscopy and direct sweetness classification approach for Pakistani cultivars of orange, i.e., Red-Blood, Mosambi, and Succari. The correlation between quality indices, i.e., Brix, titratable acidity (TA), Brix: TA and BrimA (Brix minus acids), sensory assessment of the fruit, and short-wave NIR …

Do Games Reduce Math Anxiety? A Meta-Analysis, Pierpaolo Dondio, Viacheslav Filonenko, Mariana Rocha

Articles

In this paper, we meta-analyse the empirical evidence about the effectiveness of game-based interventions to reduce students' level of math anxiety. After performing a search for randomised controlled studies relevant to game-based intervention for math anxiety, 16 experimental studies with a total of 686 participants described in 11 peer-review articles met the selection criteria.A random-effects meta-analysis indicated a small and non-significant reduction of math anxiety (mean effect size ES=-0.32, CI=[-0.64,0.01]). The results were moderated by several factors: non-digital games were more effective, while digital games had a negligible mean effect size of $ES=-0.13$, $CI=[-0.33,0.08]$. The effect size was moderated also …

Rate Of Change Of Direct-Axis Current Component Protection Scheme For Inverter-Based Islanded Microgrids, Abdolhamid Farshadi, Behzad Keyvani Eydi, Hamed Nafisi, Hossein Askarian-Abyaneh, Arash Beiranvand

Articles

Rapid growth in the utilization of the inverter-interfaced distributed energy resources (IIDERs) in microgrids has brought new challenges in the network protection area. Microgrid protection specifically becomes a concern during operation in the islanded mode. There is a considerable reduction in fault current levels in this mode compared to when the microgrid is connected to the grid, which makes conventional algorithms operate with significant delay or, in many cases, not even pick up the fault. This paper proposes a protection algorithm based on the rate of change of direct-axis current component ( id ) to protect inverter-based microgrids (IBMGs). The …

Decision Making For Process Control Management In Control Rooms: A Survey Methodology And Initial Findings, Chidera Winifred Amazu, Ammar N. Abbas, Micaela Demichela, Davide Fissore

Articles

Control rooms and their operators are active elements in complex socio-technical systems such as process plants. Control room operators monitor process operations, respond to alarms, and manage process deviations until emergencies. The increase in automation of plants and equipment makes the operators less involved in manual process control or other physical roles while more exposed to cognitive load generated, for example, by increasing the number of alarms or potential system failures in abnormal situations. A shift in process control design and management techniques to holistically capture risks due to evolving process or monitoring capabilities and the related influencing factors is …

Opportunities Of Iot In Fog Computing For High Fault Tolerance And Sustainable Energy Optimization, A. Reyana, Sandeep Kautish, Khalid Abdulaziz Alnowibet, Hossam Zawbaa, Ali Wagdy Mohamed

Articles

Today, the importance of enhanced quality of service and energy optimization has promoted research into sensor applications such as pervasive health monitoring, distributed computing, etc. In general, the resulting sensor data are stored on the cloud server for future processing. For this purpose, recently, the use of fog computing from a real-world perspective has emerged, utilizing end-user nodes and neighboring edge devices to perform computation and communication. This paper aims to develop a quality-of-service-based energy optimization (QoS-EO) scheme for the wireless sensor environments deployed in fog computing. The fog nodes deployed in specific geographical areas cover the sensor activity performed …

A Multidimensionality Reduction Approach To Rainfall Prediction, Menatallah Abdel Azeem, Prasanjit Dey, Soumyabrata Dev

Articles

The rainfall has an impact on various fields and industries, including transportation, construction, tourism, health, and wildlife preservation. Accurate rainfall prediction is essential for mitigating the negative impact of rainfall on these sectors. However, previous studies on rainfall prediction have been mainly based on datasets from North America, Europe, Australia, and Central Asia, covering different periods. This study proposes using weather datasets covering the past 5 to 10 years to capture recent patterns in weather data. Additionally, the curse of dimensionality can impact model performance and lead to overfitting. Therefore, this study proposes utilizing dimensionality reduction techniques to ensure that …

An Integrated Model For Information Adoption&Trust In Mobile Social Commerce, Fulya Acikgoz, Abdelsalam Busalim, James Gaskin, Shahla Asadi

Articles

ABSTRACT Despite the growing importance of mobile social commerce (ms-commerce), little research has been conducted on the effects of informational and social factors on users’ post-adoption behavior. We, therefore, build on the understanding of mobile social commerce in the UK market and how it affects users’ post-adoption behaviors. Our theoretical model leverages the information adoption model, social support theory, and social influence theory. Data was gathered from 377 ms-commerce users from the UK and analyzed via Partial Least Squares (PLS-SEM). The research findings show that both informational and social factors have a positive impact on information adoption in ms-commerce apps. …

A Multi–Objective Gaining–Sharing Knowledge-Based Optimization Algorithm For Solving Engineering Problems, Nour Elhouda Chalabi, Abdelouahab Attia, Khalid Abdulaziz Alnowibet, Hossam Zawbaa, Hatem Masri, Ali Wagdy Mohamed

Articles

Metaheuristics in recent years has proven its effectiveness; however, robust algorithms that can solve real-world problems are always needed. In this paper, we suggest the first extended version of the recently introduced gaining–sharing knowledge optimization (GSK) algorithm, named multiobjective gaining–sharing knowledge optimization (MOGSK), to deal with multiobjective optimization problems (MOPs). MOGSK employs an external archive population to store the nondominated solutions generated thus far, with the aim of guiding the solutions during the exploration process. Furthermore, fast nondominated sorting with crowding distance was incorporated to sustain the diversity of the solutions and ensure the convergence towards the Pareto optimal set, …

Assessing The Impact Of Contact Tracing With An Agent-Based Model For Simulating The Spread Of Covid-19: The Irish Experience, Elizabeth Hunter, Sudipta Saha, Jwenish Kumawat, Ciara Carroll, John Kelleher, Claire Buckley, Conor Mcaloon, Patricia Kearney, Michelle Gilbert, Greg Martin

Articles

Contact tracing is an important tool in managing infectious disease outbreaks and Ireland used a comprehensive contact tracing program to slow the spread of COVID-19. Although the benefits of contact tracing seem obvious, it is difficult to estimate the actual impact contact tracing has on an outbreak because it is hard to separate the effects of contact tracing from other behavioural changes or interventions. To understand the impact contact tracing had in Ireland, we used an agent-based model that is designed to simulate the spread of COVID-19 through Ireland. The model uses real contact tracing data from the first year …

Interpreting Disentangled Representations Of Person-Specific Convolutional Variational Autoencoders Of Spatially Preserving Eeg Topographic Maps Via Clustering And Visual Plausibility, Taufique Ahmed, Luca Longo

Articles

Dimensionality reduction and producing simple representations of electroencephalography (EEG) signals are challenging problems. Variational autoencoders (VAEs) have been employed for EEG data creation, augmentation, and automatic feature extraction. In most of the studies, VAE latent space interpretation is used to detect only the out-of-order distribution latent variable for anomaly detection. However, the interpretation and visualisation of all latent space components disclose information about how the model arrives at its conclusion. The main contribution of this study is interpreting the disentangled representation of VAE by activating only one latent component at a time, whereas the values for the remaining components are …

Survey Data On Dysfunctional Attitudes, Personality Traits, And Agreement With Persuasive Techniques, Annye Braca, Pierpaolo Dondio

Articles

Persuasion techniques play a vital role in human commu- nication, influencing various aspects of our lives. With the increasing prevalence of digital platforms, these techniques have permeated online spaces such as websites, mobile apps, games, and social media. This article presents a dataset col- lected via a survey, designed to gather information about in- dividuals’ demographics, personality traits, dysfunctional at- titudes, and their responses to statements embedded with persuasion techniques. Core messages promoting paid news subscriptions, blood donations, and exercise serve as the fo- cus, while definitions and examples of persuasive techniques are provided. By analyzing this comprehensive dataset, re- …

Supporting Clinical Decision Making In The Emergency Department For Paediatric Patients Using Machine Learning: A Scoping Review Protocol, Fiona Leonard, Dympna O. Sullivan, John Gilligan, Nicola O. Shea, Michael J. Barrett

Articles

Introduction Machine learning as a clinical decision support system tool has the potential to assist clinicians who must make complex and accurate medical decisions in fast paced environments such as the emergency department. This paper presents a protocol for a scoping review, with the objective of summarising the existing research on machine learning clinical decision support system tools in the emergency department, focusing on models that can be used for paediatric patients, where a knowledge gap exists. Materials and methods The methodology used will follow the scoping study framework of Arksey and O'Malley, along with other guidelines. Machine learning clinical …

Analysis Of Attention Mechanisms In Box-Embedding Systems, Jeffrey Sardina Jeffrey Sardina, Callie Sardina, John Kelleher, Declan O’Sullivan

Conference papers

Large-scale Knowledge Graphs (KGs) have recently gained considerable research attention for their ability to model the inter- and intra- relationships of data. However, the huge scale of KGs has necessitated the use of querying methods to facilitate human use. Question Answering (QA) systems have shown much promise in breaking down this human-machine barrier. A recent QA model that achieved state-of-the-art performance, Query2box, modelled queries on a KG using box embeddings with an attention mechanism backend to compute the intersections of boxes for query resolution. In this paper, we introduce a new model, Query2Geom, which replaces the Query2box attention mechanism with …

Action Classification In Human Robot Interaction Cells In Manufacturing, Shakra S.M. Mehak, Maria Chiara Leva, John Kelleher, Michael Guilfoyle

Conference papers

Action recognition has become a prerequisite approach to fluent Human-Robot Interaction (HRI) due to a high degree of movement flexibility. With the improvements in machine learning algorithms, robots are gradually transitioning into more human-populated areas. However, HRI systems demand the need for robots to possess enough cognition. The action recognition algorithms require massive training datasets, structural information of objects in the environment, and less expensive models in terms of computational complexity. In addition, many such algorithms are trained on datasets derived from daily activities. The algorithms trained on non-industrial datasets may have an unfavorable impact on implementing models and validating …

Comprehensive Fault Diagnostics And Performance Forecasting Of Wind Turbines Through Condition Monitoring Solutions, Shuo Zhang

Doctoral

The operation and maintenance (O&M) issues of wind turbines (WTs) are challenging because unplanned maintenance, caused by sudden component failures, can bring about durable downtimes and significant revenue losses. It is important to carry out effective fault diagnostics and prognostics schemes under the rapid development of wind power generation. Hence, Condition Monitoring (CM) solutions focus on measurements and detections of high-risk WT components, which could result in high failure rates and long downtimes. Machine Learning (ML) models have been commonly applied in CM to allocate imminent indications of failure or degradation for curtailing the O&M costs of WTs. By way …

Pedagogical Approaches To Enhancing Student Self-Efficacy And Addressing Gender Inequality In Undergraduate Stem, Gintarė Lübeck

Theses

Previous research has shown that the success and retention of students in STEM university programmes are highly correlated with their self-efficacy beliefs, and women and gender minority students in STEM have been consistently found to possess lower self-efficacy than men. Since specific teaching and learning practices are known to contribute to increased self-efficacy and help diversify STEM education, this study sought to identify which pedagogical approaches are effective in creating a more equitable learning environment in introductory STEM classes by positively contributing to students’ self-efficacy. This study employed methodological triangulation and synthesised findings from self-efficacy questionnaires, classroom observations, and a …

Design And Fabrication Of Volume Holographic Optical Couplers For A Range Of Non-Normal Incidence Angles, Dipanjan Chakraborty, Rosen Georgiev, Sinead Aspell, Izabela Naydenova, Suzanne Martin

Conference Papers

A theoretical model has previously been developed to calculate the holographic recording beam angles required in air (at any recording wavelength) to produce a Volume Holographic Optical Element (VHOE) for operation as a coupler for different input and output angles. In this paper, the experimental study is extended to further validate the VHOE coupler design and fabrication approach for additional incident beam angles, comparing -40° -45° and -50° (in air). The output angle for each VHOE is +45° within the medium and the coupler operational wavelength is 633nm. Holographic recording in Bayfol HX 200 photopolymer at 532nm is used to …

Spherical Modes Driven Directional Modulation With A Compact Mimo Antenna, Abel Zamdemala, Nicola Marchetti, Max Ammann, Adam Narbudowicz

Articles

In this letter, a compact beamsteering MIMO antenna is proposed for Directional Modulation (DM) applications. A generalization of the beamsteering principle is presented and by exploiting the antenna’s unidirectional beamsteering capability within the entire azimuth plane, the system realizes secure steerable transmissions in the direction of the legitimate receiver, with a low Bit Error Rate (BER) of 10^(-5), while a high error rate of 10^(-1) is seen outside the desired regions. Numerical and experimental verifications are carried out to validate the proposed concept and comparisons with circular arrays are conducted, revealing that the system achieves comparable performance but with up …

A Secure Data Sharing Scheme In Community Segmented Vehicular Social Networks For 6g, Sunder Ali Khowaja, Parus Khuwaja, Kapal Dev, Ik Hyun Lee, Wali Ullah Khan, Weizheng Wang, Nawab Muhammad Faseeh Qureshi, Maurizio Magarini

Research Outputs: 2025-Present

The use of aerial base stations, AI cloud, and satellite storage can help manage location, traffic, and specific application-based services for vehicular social networks. However, sharing of such data makes the vehicular network vulnerable to data and privacy leakage. In this regard, this article proposes an efficient and secure data sharing scheme using community segmentation and a blockchain-based framework for vehicular social networks. The proposed work considers similarity matrices that employ the dynamics of structural similarity, modularity matrix, and data compatibility. These similarity matrices are then passed through stacked autoencoders that are trained to extract encoded embedding. A density-based clustering …

Supporting The Learning Of Women Middle Eastern Students Studying Engineering In Europe, Shannon M. Chance, B. Williams, Ines Direito

Research Outputs: 2025-Present

No abstract provided.

Internet Of Things (Iot)-Based Teaching And Learning: Modern Trends And Open Challenges, Ibrahim Ahmed Ghashim, Muhammad Arshad

Research Outputs: 2025-Present

The effect of technology has caused many institutions to intend to change their approach to teaching and learning, resulting in the current model of teaching and learning being an active collaborative and self-directed one. The connection between education and technology has received attention as part of educational policy and practice. Debatable topics like how to use technology in the classroom have therefore punctuated complaints about declining educational standards, unemployed learners, duplicate curricula, and archaic institutional structure. In the framework of information and communication technologies and societal growth, the Internet of Things (IoT) is asserting its vital position. Institutions may improve …

How Can Visual Programing Be Used To Aid The Development Of A Structural Scheme Design Process Utilising Geometric Data Within An Architectural Revit Model?, Ed Carthy, Kieran Lakhera O'Shea

Reports

The early-stage structural scheme design of a building is a complex task requiring the collection of multiple information categories such as geometry, loading and materials. The collection and review of this information is traditionally conducted in a 2D environment. This is inefficient, time-consuming, and tedious. This paper provides a review of how structural engineers’ understanding and implementation of BIM has evolved significantly in recent years, validated by extant literature in areas such as BIM automation, visual programming, and structural optimisation in the structural engineering sector. Structural engineers are growing more aware that BIM provides a vast repository of data to …

Persuasive Communication Systems: A Machine Learning Approach To Predict The Effect Of Linguistic Styles And Persuasion Techniques, Annye Braca, Pierpaolo Dondio

Articles

Prediction is a critical task in targeted online advertising, where predictions better than random guessing can translate to real economic return. This study aims to use machine learning (ML) methods to identify individuals who respond well to certain linguistic styles/persuasion techniques based on Aristotle’s means of persuasion, rhetorical devices, cognitive theories and Cialdini’s principles, given their psychometric profile.

Performance Evaluation Of Ingenious Crow Search Optimization Algorithm For Protein Structure Prediction, Ahmad M. Alshamrani, Akash Saxena, Shalini Shekhawat, Hossam Zawbaa, Ali Wagdy Mohamed

Articles

Protein structure prediction is one of the important aspects while dealing with critical diseases. An early prediction of protein folding helps in clinical diagnosis. In recent years, applications of metaheuristic algorithms have been substantially increased due to the fact that this problem is computationally complex and time-consuming. Metaheuristics are proven to be an adequate tool for dealing with complex problems with higher computational efficiency than conventional tools. The work presented in this paper is the development and testing of the Ingenious Crow Search Algorithm (ICSA). First, the algorithm is tested on standard mathematical functions with known properties. Then, the application …

The Role Of Teacher Agency In Using Gis To Teach Sustainability: An Evaluation Of A Lower Secondary School Story Mapping Gis Initiative In Ireland, Sasha Brown, Zerrin Doganca Kucuk, Angela Rickard, James Lonergan, Rachel Abernethy, Lorraine Mcnerney, Ronan Foley, Avril Behan, Aengus Byrne, Bernard Essel, Jack Ffrench, Jonathan Faull, Conor Cahalane

Articles

This paper investigates the role of teacher agency for those who were trained in using an innovative Geographic Information Systems (GIS) approach and incorporated GIS into their teaching. While national curricula increasingly emphasise STEM and sustainability approaches, there has been limited analysis of how teachers can bring new software, including GIS, and new approaches into the classroom. Through an evaluation of a teaching initiative “5*S: Space, Surveyors and Students – STEM and the Sustainable Development Goals” designed to bring GIS technology, satellite data, and the Sustainable Development Goals (SDGs) into classrooms as activities and resources for teachers and students in …

Approaches To Avoid Proteolysis During Protein Expression And Purification, Gary T. Henehan, Barry J. Ryan, Gemma K. Kinsella

Books/Book Chapters/ Proceedings

All cells contain proteases, which hydrolyze the peptide bonds between amino acids of a protein backbone. Typically, proteases are prevented from nonspecific proteolysis by regulation and by their physical separation into different subcellular compartments; however, this segregation is not retained during cell lysis, which is the initial step in any protein isolation procedure. Prevention of proteolysis during protein purification often takes the form of a two-pronged approach: first, inhibition of proteolysis in situ, followed by the early separation of the protease from the protein of interest via chromatographic purification. Protease inhibitors are routinely used to limit the effect of the …

Protein Extraction And Purification By Differential Solubilization, Barry J. Ryan, Gemma K. Kinsella, Gary T. Henehan

Books/Book Chapters/ Proceedings

The preparation of purified soluble proteins for biochemical studies is essential and the solubility of a protein of interest in various media is central to this process. Selectively altering the solubility of a protein is a rapid and economical step in protein purification and is based on exploiting the inherent physicochemical properties of a polypeptide. Precipitation of proteins, released from cells upon lysis, is often used to concentrate a protein of interest before further purification steps (e.g., ion exchange chromatography, size exclusion chromatography etc).

Recombinant proteins may be expressed in host cells as insoluble inclusion bodies due to various influences …

Clinical Radiobiology For Radiation Oncology, Peter Sminia, Olivier Guipaud, Kristina Viktorsson, Vidhula Ahire, Sarah Baatout, Tom Boterberg, Jana Cizkova, Marek Dostál, Cristian Fernandez-Palomo, Alzbeta Filipova, Agnès François, Mallia Geiger, Alistairl Hunter, Hussam Jassim, Nina Frederike Jeppesen Edin, Karl Jordan, Irena Koniarová, Vinodh Kumar Selvaraj, Aidan D. Meade, Fabien Milliat, Alegría Montoro, Constantinus Politis, Diana Savu, Alexandra Sémont, Ales Tichy, Vlastimil Válek, Guillaume Vogin

Books/Book Chapters

This chapter is focused on radiobiological aspects at the molecular, cellular, and tissue level which are relevant for the clinical use of ionizing radiation (IR) in cancer therapy. For radiation oncology, it is critical to find a balance, i.e., the therapeutic window, between the probability of tumor control and the probability of side effects caused by radiation injury to the healthy tissues and organs. An overview is given about modern precision radiotherapy (RT) techniques, which allow optimal sparing of healthy tissues. Biological factors determining the width of the therapeutic window are explained. The role of the six typical radiobiological phenomena …

Accessibility Of Health Data Representations For Older Adults: Challenges And Opportunities For Design, Peterson Jean, Emma Murphy, Enda Bates

Books/Book Chapters

Health data of consumer off-the-shelf wearable devices is often conveyed to users through visual data representations and analyses. However, this is not always accessible to people with disabilities or older people due to low vision, cognitive impairments or literacy issues. Due to trade-offs between aesthetics predominance or information overload, real-time user feedback may not be conveyed easily from sensor devices through visual cues like graphs and texts. These difficulties may hinder critical data understanding. Additional auditory and tactile feedback can also provide immediate and accessible cues from these wearable devices, but it is necessary to understand existing data representation limitations …

Advances In Precision Microfabrication Through Digital Light Processing: System Development, Material And Applications, Xinhui Wang, Jinghang Liu, Yang Zhang, Per Magnus Kristiansen, Aminul Islam, Michael Gilchrist, Nan Zhang

Articles

Digital Light Processing (DLP) is an advanced additive manufacturing technology which has garnered substantial recognition and has been extensively applications in various fields. This review focuses on the precision microfabrication process of DLP, providing an overview of the DLP 3D printing system, including the digital light engine, project lenses, motorised stage and resin vat for micro-structure fabrication. Additionally, this review paper comprehensively analyses commercially available DLP printers, covering resolution, cost and a detailed discussion on the importance of photopolymer resins, emphasising the monomer, photo-initiator, photoabsorber, etc. Based on the photopolymerisation theory, the DLP high-precision printing process is analysed, which is …