Digital Commons Network^™

Translating Human Emotion Into Music: A Multimodal Machine-Learning Framework Linking Movement, Facial Expression, And Real-Time Generative Composition, Martin Mc Corry

School of Art, Design and Architecture Theses

This thesis investigates whether embodied human expression—captured through facial and full-body motion—can be translated into musically coherent behaviour using time-series machine learning and real-time generative systems. The project develops and evaluates a multimodal framework that links participant-specific emotion inference to an interpretable, artist-configurable generative music system.Across two sensing modalities, personalised BiLSTM-based models achieved ~99%window-level validation accuracy within participants under a strict leak-free protocol, with no evidence of overfitting. These models were deployed within a low-latency real-time inference system. The research introduces a structured translation layer comprising a consensus mapping matrix and a tiered control architecture, mediating between probabilistic inference and …

Analysis Of Volatility Between Macroeconomic Variables And Busan Port Cargo Throughput According To Global Risks, Sang Ho Cho

Plymouth Business School Theses

This study investigates how container (BPC) and non-container (BPB) cargo throughput at Busan Port responds to structural shocks in global and domestic macroeconomic variables, and how their relative importance changes over time. The selection of variables was based on a combination of a Systematic Literature Review (SLR) and semi-structured interviews (SSI). The econometric analysis applied a stepwise framework, employing cumulative Impulse Response Functions (IRF) and Forecast Error Variance Decomposition (FEVD) based on Vector Error Correction Model (VECM) estimations, as well as Historical Decomposition (HD) for specific crisis periods. While IRF and FEVD were used to capture dynamic properties under general …

In Trust We Trust: Role Of Trust In Business Negotiations In The Context Of Switzerland As A High-Trust Country, Aksana Babich

Plymouth Business School Theses

The present research examines the role of trust in business negotiations in the context of Switzerland, a high-trust country. Using a qualitative, practitioner-oriented design grounded in template analysis, the research draws on semi-structured interviews with thirty professionals from diverse sectors of the economy of the canton of Geneva. Switzerland’s high-trust environment provides an empirical context in which trust mechanisms are particularly visible and operational.The research advances conceptual, empirical and methodological knowledge of trust in negotiations. Conceptually, it clarifies the meaning of trust, demonstrating that trust is not a one-dimensional construct centred on risk and vulnerability, but a multifaceted moral value …

Examining The Nexus Between Social Capital, Value Co-Creation And Entrepreneurship In Nigeria: Assessing The Moderating Role Of Social Media In A Resource-Constrained Context, Ben Omoruyi

Plymouth Business School Theses

This research provides a transformative perspective on how Social Capital (SC), Value Co creation (VCC), and Social Media (SM) interact to shape Entrepreneurial Outcomes (EOs) in institutionally weak, resource-constrained contexts. Positioned within a positivist ontology and grounded in Social Capital Theory, the research reconceptualises SC not as a passive stock of relationships but as a dynamic entrepreneurial capability, strategically mobilised to access resources, legitimacy, and opportunities. Focusing on Nigeria’s fashion industry, a sector characterised by informality, weak institutions, and heavy network reliance, the study adopts a quantitative, deductive design. Data from a cross-sectional survey of 580 entrepreneurs aged 18–55, in …

Driving Venture Success: A Collaborative Framework For The Consumer Goods Industry, Mohammad Alhusaeini Mohammad

Plymouth Business School Theses

This thesis addresses the persistent gap between the strategic promise of external corporate venturing (ECV) and its frequently disappointing outcomes in the global consumer goods industry, with a specific focus on the non-durable consumer goods sub‑sector. Despite ECV’s recognised importance for innovation—particularly in a sector characterised by rapid consumer preference shifts, tight margins, and complex supply chains—collaborations with external start-ups are often undermined by cultural misalignment, strategic ambiguity, and ineffective performance measurement. Through an abductive, mixed-methods research design within an interpretivist paradigm—integrating archival analysis, six in-depth corporate case studies (P&G, PepsiCo, Unilever, Danone, Henkel, and L’Oréal), and 32 interviews with …

Pab-Pif: A Hybrid Architecture To Evaluate Mutable And Immutable Blockchains In Iot–Fog Networks, Marco Scarpa, Mohammad Sadeghzadeh, Saeed Javanmardi, Bahareh Pahlevanzadeh, Mauro Iacono

Research Outputs: 2025-Present

Blockchain provides secure and decentralized data storage. Normal blockchains permanently store data. Mutable blockchains allow users to change data, but this reduces tamper resistance. This paper tests both methods in PaB-PIF, a hybrid architecture for IoT-Fog networks. Our design uses an immutable mainchain in the cloud layer and mutable sidechains in the fog layer. We analyze throughput, latency, and tamper resistance using math models and simulations. Results show that blockchain greatly improves network security. Without blockchain, the network has zero tamper resistance. The mutable blockchain in the fog layer has a tamper resistance of 0.58. The immutable blockchain in the …

Browser-Based Phishing Detection System Using Modern Web Technologies, Muhammad Arshad, Beena Sherin Kuriakose, Choo Wou Onn, Farhan Ahmad Siddiqui, Mohammad Shahid Kamal

Research Outputs: 2025-Present

Phishing remains one of the most persistent cybersecurity threats, exploiting human trust to steal sensitive information through deceptive websites. Traditional detection methods, reliant on blacklists and reactive reporting, offer limited protection against rapidly evolving zero-day attacks. To address these challenges, this study proposes and evaluates a hybrid browser-resident phishing detection framework that combines three complementary detection mechanisms: a locally executed Random Forest model using URL lexical features, lightweight real-time DOM structure analysis, and VirusTotal’s multi-engine reputation service. Communication between the client and server is optimised using gRPC over the QUIC protocol, ensuring secure, high-performance data exchange with built-in retry mechanisms …

Educating The Next Generation Of Engineers: Spatial Thinking Is Key To Their Success, Sheryl Sorby, Gavin Duffy, Jack Parkinson, Gibin Raju, John Lynch, Muhammad Asghar

Research Outputs: 2025-Present

This paper attempts to answer questions regarding the link between engineering success and spatial skills through three themes. The previous research of the authors in examining the questions surrounding each theme is the focus of this paper; we acknowledge that others around the world may have conducted similar research, but the specific findings of the authors are the main focus of this paper. In the first theme, we examine data from several author-led studies where positive correlations have been found between spatial skill levels and proficiency in tasks that are a part of what it means to be an engineer. …

3d-Vit-Unet: 3d Vision Transformer Based Unet-Like Model For Volumetric Brain Tumor Segmentation, Sikandar Afridi, Atif Jan, Muhammad Abeer Irfan, Muhammad Irfan Khattak, Taimur Ahmed Khan

Research Outputs: 2025-Present

Accurate volumetric segmentation of 3D medical imaging modalities is critical for therapy planning and clinical diagnosis, particularly for brain tumor delineation. Traditional convolutional neural network (CNN)-based architectures face challenges while capturing global contextual information and modeling long-range dependencies in complex 3D volumetric data, limiting their segmentation performance. Transformer-based models have emerged as promising alternatives to CNNs for such tasks, addressing their limitations in capturing global spatial dependencies. We propose 3D-ViT-UNet, a novel U-shaped vision transformer (ViT)-based encoder-decoder architecture for end-to-end volumetric brain tumor segmentation. The model employs 3D Window Multi-Head Self-Attention (3D-W-MSA) to capture local features and a 3D Dilated-Window …

Sustainable Development And Faith, Tony Kealy

Research Outputs: 2025-Present

The contribution of faith-based input to the broader idea of sustainable development has not been widely acknowledged in the traditional sense; however, recent global events suggest it may warrant further exploration. This qualitative study examines how faith-based activities, such as missionary work, have historically and can continue to contribute significantly to the environmental, economic, and human/social aspects of organizational decision-making. The focus is on the Catholic faith, specifically the role played by the Irish-based Medical Missionaries of Mary religious congregation in the mid-to-late twentieth century. An initial literature review was conducted to gather information from various sources to define sustainable …

A Taxonomy And Empirical Evaluation Of Webassembly Runtimes For Performance And Energy Across Machine Learning And Arithmetic Workloads, Sallar Khan, Tania Malik, Khalid Hasanov

Research Outputs: 2025-Present

WebAssembly (Wasm) has emerged as a lightweight, portable, and secure execution environment beyond the browser, with growing adoption in data-intensive, machine learning, and performance-sensitive workloads. However, the runtime ecosystem remains fragmented, and a systems-level understanding of how runtime design affects performance and energy efficiency is still lacking. This paper makes two contributions. First, it presents a taxonomy of modern WebAssembly runtimes that classifies the runtime landscape by execution model, compilation strategy, integration style, and systemslevel capabilities. Second, it provides an empirical evaluation of 13WASI-compatible runtimes and a native baseline across eight benchmarks, namely, four machine learning workloads (Logistic Regression, K-Means, …

Ai For Prognosis Among People Living With Hiv: Protocol For A Systematic Review And Meta-Analysis, Degninou Yehadji, Markus Hofmann, Petros Isaakidis, Smaila Alidou, Olushina Ayo Junior Ale, Kofivi Mawouko Yena, Kodjo Guidigan, Geraldine Gray, Nadjime Pindra, Gayo Diallo

Research Outputs: 2025-Present

Background: Advanced HIV disease remains a major global health concern, with nearly 40.8 million people living with HIV as of 2024. Antiretroviral therapy has improved outcomes, but its success depends on timely intervention, adherence, and retention in care. AI, including machine learning and deep learning, offers promising tools for prognostic modeling that could support clinical decision-making and personalized treatment. Existing syntheses, however, have been largely narrative and have not systematically evaluated the performance, risk of bias, reporting quality, or clinical readiness of AI-based prognostic models, leaving a critical gap in understanding their validity and applicability. Objective: This study aims to …

Editorial: Harnessing Of Soil Microbiome For Sustainable Agriculture: Harnessing Of Soil Microbiome For Sustainable Agriculture, Debasis Mitra, Marika Pellegrini, Leonard Koolman

Research Outputs: 2025-Present

No abstract provided.

Cognitive Causal Modeling Of Blockchain Adoption In Agri-Food Supply Chains: A Fuzzy-Dematel Approach, Ali Ala, Behnam Malmir, Hamed Baziyad, Vladimir Simic

Research Outputs: 2025-Present

Background / Introduction: Blockchain can improve agri-food supply-chain transparency, but adoption decisions are cognitively complex because managers judge interdependent criteria under uncertainty. This study frames adoption as cognitive causal decision modeling, aligning with cognitive computation through expert judgment, linguistic uncertainty, causal reasoning, and explainable decision support. Methods: We applied Fuzzy Decision-Making Trial and Evaluation Laboratory (Fuzzy-DEMATEL) to judgments from 20 experts. Eight technology-adoption criteria were modeled using triangular fuzzy numbers, and an impact relationship map was used to classify criteria by outgoing influence (R), incoming influence (C), prominence (R + C), and net causality (R − C). Results: Smart Contracts …

High-Sensitivity Fiber Optic Temperature Sensor Based On Vernier Effect In A Polymethyl Methacrylate Capillary And Barium Titanate Microsphere, Zhuochen Wang, Ginu Rajan, Zhe Wang, Anuradha Rout, Rayhan Habib Jibon, Anand Vadakkedathu Raveendran, Yuliya Semenova

Research Outputs: 2025-Present

This paper proposes and investigates a novel fiber Fabry–Perot interferometer (FPI) temperature sensor that leverages the Vernier effect for enhanced sensitivity. The sensor comprises a cascade of two FPIs formed by a short polymethyl methacrylate capillary, a barium titanate microsphere, and a cleaved single-mode fiber. The Vernier effect, induced by the dual Fabry–Perot cavities, amplifies the temperature sensitivity. The fabrication process involves the precise alignment and gluing of components, resulting in a simple, cost-effective sensor. The experimental results indicate a temperature sensitivity of 1.90 nm °C⁻¹. The sensor also exhibits excellent repeatability and stability, making it suitable for …

Post: Pruning Oriented Security For Inversion Attack In Edge-Based Internet Of Things, Sunder Ali Khowaja, Abi Waqas, Mohammad Tabrez Quasim, Kapal Dev

Research Outputs: 2025-Present

With the recent emergence of artificial intelligence (AI), edge users in industries and manufacturing have been extensively using AI-based services, which pose privacy and security risks to data. Distributed learning approaches deployed in the manufacturing industries help reduce data risks. However, traditional approaches cannot handle deep models as well as the scalability of edge-based internet of things (E-IoT) devices, especially in the manufacturing sector. Studies have proposed SplitFed learning (SFL) by combining split learning and the federated learning paradigm, but they fail to achieve an optimal trade-off between communication and computational limitations and are vulnerable to inversion attacks. We present …

Influence Of Beamwidth, Gain Stability, And Antenna Element Spacing On Aoa Accuracy In Ieee 802.15.4z Uwb Systems, Hossein Raghib Hokmabadi, Wasi Ur Rehman Khan, Patrick Mcevoy, Max James Ammann

Research Outputs: 2025-Present

Precision is a crucial requirement in indoor localization, and the industrial sector increasingly demands technologies that provide both high accuracy and low cost. This work presents a hardware-based evaluation of dual-antenna arrays using an IEEE 802.15.4z-compliant UWB angle of arrival (AoA) development kit to assess antenna performance in terms of phase difference of arrival (PDoA)/AoA linearity. Four antenna types: 1) printed monopole; 2) CPW-fed slot; 3) stacked dielectric resonator antenna (DRA); and 4) dual-layer microstrip patch are evaluated on channels 5 and 9, with measurements performed in a calibrated anechoic chamber under controlled conditions. The results show that wide beamwidth …

Design And Optical Analysis Of A Non-Ideal Parabolic Trough Concentrator For Uniform Flux Distribution In Photovoltaic Applications, Muhammad Tayyab, Qamar Abbas, Muhammad Rizwan Shad, Philippe Lemarchand, Abida Shaheen, Sarah J. Mccormack, Hassan Bin Shahid, Jawad Sarwar

Research Outputs: 2025-Present

Concentrating photovoltaic (CPV) systems utilize optical elements to focus sunlight onto small-area solar cells. Among different concentrators, Parabolic trough concentrators (PTCs) have simple design and offer medium concentration ratios (typically 30–100 × ). But PTCs are line focus and their spatial non-uniform flux distribution limit their use in CPV applications. This study presents a geometric redesign of conventional PTCs, transforming their line focus into a spatially uniform focus and referred as a segmented non-ideal parabolic trough concentrator (NI-PTC). A numerical model is developed and validated. The validated model is used to investigate performance of NI-PTC by varying design parameters such …

Microbial Collagenase Activity Is Linked To Oral–Gut Translocation In Advanced Chronic Liver Disease, Shen Jin, Aurelie Cenier, Daniela Wetzel, Bethlehem Arefaine, Mar Moreno-Gonzalez, Marilena Stamouli, Merianne Mohamad, Mariia Lupatsii, Emilio Ríos, Sunjae Lee, Ane Zamalloa, Shilpa Chokshi, Adil Mardinoglu, Saeed Shoaie, Naiara Beraza, Vishal C. Patel, Melanie Schirmer

Peninsula Medical School

Microbiome perturbations are associated with advanced chronic liver disease (ACLD), but how microorganisms contribute to disease mechanisms is unclear. Here we analysed metagenomes of paired saliva and faecal samples from an ACLD cohort of 86 individuals, plus 2 control groups of 52 healthy individuals and 14 patients with sepsis. We identified highly similar oral and gut bacterial strains, including Veillonella and Streptococcus spp., which increased in absolute abundance in the gut of patients with ACLD compared with controls. These microbial translocators uniquely share a prtC gene encoding a collagenase-like proteinase, and its faecal abundance was a robust ACLD biomarker (area …

Investigating The Impact Of Carboxylated Polystyrene Nanoplastics In The Liver Using Cell Lines And Precision-Cut Liver Slices, Namrata Pandey, Paula Boeira, Nathaniel J. Clark, Eleanor T. Walker, Somaiah Aroori, Jemimah Denson, Richard C. Thompson, Matthew E. Cramp, Shilpa Chokshi, Ashwin Dhanda

Peninsula Medical School

Background and Aims: Increasing reports of plastic accumulation in human tissue have raised concerns about potential adverse health outcomes. Evidence of negative effects of nanoplastics is heterogeneous and provides limited insights into the underlying pathogenic toxicity mechanisms in humans. Methods: In the present study, carboxylate-modified fluorescently labelled polystyrene nanoparticles (PS NPs) were used to investigate uptake and cytotoxicity in three different hepatic models of varying complexity, including HepG2 cells, IHH cells, and human precision-cut liver slices (hPCLS). Results: The results show model- and dose-dependent effects on hepatocytes. 74.2% ± 13.4% of the IHH cells showed PS NPs uptake at 0.1 …

Designing A Mobile App For Post Traumatic Stress Disorder: Insights From Lived Experience And Clinical Practice, Rohit Shankar, Richard Laugharne, Michael Loizou, Marius Varga, Sivia Lin, Bojana Daw Srdanovic, Roger Farrell

Peninsula Medical School

Post-traumatic stress disorder (PTSD) is a disabling anxiety disorder precipitated by severe trauma. Many people with this condition have little access to clinical interventions, especially in low-middle-income countries. For the development of any digital health intervention, it is vital to know the opinions of PLE and clinicians to guide the developers. We conducted two focus groups, one with clinicians (n = 5) and one with people with lived experience (PLE) (n = 11), to gain knowledge of their views on the development of a PTSD App. Transcripts of both focus groups were coded and thematically analysed. The key themes that …

The Connectedness Between Awareness And Practice Of Waste Control And Recycling In Urban Villages: A Cross-Sectional Community-Based Study., Nelifer Shreya Ammanna, Jeenal Valine Mendonca, Chethan Kunder, Sushwetha Poojary, Swagath Nayak, Ansuya Ansuya, Mitchelle Shilpa Lewis

Manipal Journal of Nursing and Health Sciences

Introduction: Waste management is an increasing problem that occurs globally due to expanding population around the globe. Researchers worldwide are working towards ending this problem that impacts the environment and people's health. The knowledge of the wastes produced and how we manage them is vital for the population to understand; knowing about it and practicing the same will create a ripple effect on the waste generated by the people.

Objective: To determine the condition of the urban villages in terms of awareness and practice of waste management, and to know whether these are interrelated.

Methods: A quantitative approach with …