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The Impact Of Hybrid Working On Employee Way Of Life And The Need To Reshape The Employee Value Proposition, Kanishka Chandanamali Athalage

Dissertations

This dissertation details a post-pandemic qualitative investigation conducted to understand the impact of hybrid working solutions on reshaping the employee value proposition (EVP) in the health insurance industry of the UAE. The research aims to evaluate how the introduction of modern hybrid working solutions impacts employees in a post-pandemic environment and, in turn, whether this creates a demand for human resources to refocus drivers of the EVP. Traditionally, EVP is referred to as the overall give-and-get in an employment deal; however, the pandemic was an eye-opener for organizations to redefine what it entails. Since hybrid working has become the new …

Beyond The Cage: A Story Book For Children, Seemi Batool, Fozia Parveen

Institute for Educational Development Pakistan (IED-PK) Archives

This is an open and free resources created for parents and teachers to use in homes and classrooms.

In Vitro Assessment Of The Anti-Biofilm Effectiveness Of Copper And Zinc Enhanced Borate Bioactive Glass Using Processed Microscopic Images, Sarah Fakher, David J. Westenberg

Biological Sciences Faculty Research & Creative Works

The escalating burden of nosocomial infections presents a formidable challenge to healthcare systems worldwide, leading to increased morbidity, prolonged hospital stays, and elevated healthcare costs. These infections are often resistant to conventional antibiotic therapies due to their association with biofilms which contribute to the persistence and resistance of pathogens. In addressing the challenge of biofilm-associated nosocomial infections, borate bioactive glasses (BBGs) have emerged as promising biomaterials. Doping these glasses with antimicrobial metals could potentially harness their antibacterial properties to prevent biofilm formation. This study undertakes a rigorous evaluation of the anti-biofilm efficacy of copper and zinc-doped BBGs by employing processed …

Advanced Detection Of Sars-Cov-2 And Omicron Variants Via Mxene-Graphene Hybrid Biosensors Utilizing Nucleic Acid Probes, Jiaoli Li, Yuwei Zhang, Congjie Wei, Yanxiao Li, Zhekun Peng, Hsin Yin Chuang, Logan Pearce, Adrianus Boon, Yue-Wern Huang, Dong Hyun Kim, Risheng Wang, Chenglin Wu

Biological Sciences Faculty Research & Creative Works

Low-cost biosensors that can rapidly and widely detect viruses are critical for faster diagnosis and treatment decision-making, especially for infections. The commonly used field-effect transistor is sensitive to the biomarker's detection but struggles with precise detection, particularly of nontargets such as ions and proteins. To overcome this limitation, we developed a field-effect transistor biosensor design based on MXene-graphene materials to increase the accuracy and sensitivity of virus detection. Based on the hybridization process between two complementary DNA strands, single-stranded nucleic acids were immobilized on the sensing surface via 3-aminopropyltriethoxysilane and glutaraldehyde to capture the nucleic acids of the target virus. …

Body-Oriented Gesture Generation System For Medical Interpreter Robots Based On Reinforcement Learning From Human Feedback, Tung Ngo, Emma Murphy, Conor Mcginn, Robert Ross

Conference papers

Medical interpreters are crucial in facilitating communication between healthcare stakeholders who speak different languages. Body-oriented gestures convey critical information essential for accurate and high-quality interpretation in healthcare settings. This study introduces a body-oriented gesture generation system designed for medical interpreter robots based on reinforcement learning from human feedback (RLHF). The system allows robots to interpret more naturally and improve over time through interactions with humans. By adopting a human-centered development approach, we tailor our system to address the actual needs of healthcare stakeholders.

The Spree Of Principles And The Abuses Of The Balancing Doctrine In Brazil, Ronaldo Porto Macedo

FIU Law Review

This article delves into the nuanced distinction between principles and rules in legal discourse, emphasizing their differing grammatical functions. While acknowledging the necessity of principles in legal reasoning, it cautions against their unchecked proliferation, exemplified by the Ellwanger case. The analysis underscores the importance of contextual understanding in discerning between principles and policies, advocating for a philosophical-political reflective approach. It critiques the overreliance on balancing-proportionality as a universal method, warning against its potential for dogmatic reduction and infringement on fundamental rights like freedom of expression. Ultimately, it calls for a balanced, reflective interpretation of principles to mitigate the risks inherent …

Ai-Designed Clothing And Perceived Values: What Can Move Consumers' Minds With The Ai-Designed Clothing?, Dooyoung Choi, Ha Kyung Lee

STEMPS Faculty Publications

This study investigates the perceived values of AI-designed clothing (quality, emotion, ease) and their impact on willingness to pay (WTP) and word-of-mouth (WOM), with the moderating effect of gender differences. A total of 314 respondents completed the survey via MTurk. Participants watched a video clip demonstrating how an AI system creates various clothing designs by altering garment elements (e.g., style, size). After watching the video clip, they were asked to answer a series of questions about the AI-designed clothing and themselves. The collected data were analyzed using AMOS 26.0. Results showed that, for male and female consumers, the quality value …

Exploring Students' Perspectives On Generative Ai-Assisted Academic Writing, Jinhee Kim, Seongryeong Yu, Rita Detrick, Na Li

STEMPS Faculty Publications

The rapid development of generative artificial intelligence (GenAI), including large language models (LLM), has merged to support students in their academic writing process. Keeping pace with the technical and educational landscape requires careful consideration of the opportunities and challenges that GenAI-assisted systems create within education. This serves as a useful and necessary starting point for fully leveraging its potential for learning and teaching. Hence, it is crucial to gather insights from diverse perspectives and use cases from actual users, particularly the unique voices and needs of student-users. Therefore, this study explored and examined students' perceptions and experiences about GenAI-assisted academic …

Exploring Instructional Designers' Utilization And Perspectives On Generative Ai Tools: A Mixed Methods Study, Tian Luo, Pauline S. Muljana, Xinyue Ren, Dara Young

STEMPS Faculty Publications

The emergence of generative artificial intelligence (GenAI) has caused significant disruptions on a global scale in various workplace settings, including the field of instructional design (ID). Given the paucity of research investigating the impact of GenAI on ID work, we conducted a mixed methods study to understand instructional designers (IDs)’ perceptions and experiences of utilizing GenAI across a spectrum of ID tasks. A total of 70 IDs completed an online survey, and 13 of them participated in the semi-structured interviews. The survey results indicated IDs’ familiarity with and perceived usability of GenAI tools in performing various ID responsibilities in their …

Integrating Remote Sensing With Ground-Based Observations To Quantify The Effects Of An Extreme Freeze Event On Black Mangroves (Avicennia Germinans) At The Landscape Scale, Melinda Martinez, Michael J. Osland, James B. Grace, Nicholas M. Enwright, Camille L. Stagg, Camille L. Stagg, Simen Kaalstad, Gordon H. Anderson, Elena A. Flores, Alejandro Fierro-Cabo

School of Earth, Environmental, & Marine Sciences Faculty Publications

Climate change is altering the frequency and intensity of extreme weather events. Quantifying ecosystem responses to extreme events at the landscape scale is critical for understanding and responding to climate-driven change but is constrained by limited data availability. Here, we integrated remote sensing with ground-based observations to quantify landscape-scale vegetation damage from an extreme climatic event. We used ground- and satellite-based black mangrove (Avicennia germinans) leaf damage data from the northern Gulf of Mexico (USA and Mexico) to examine the effects of an extreme freeze in a region where black mangroves are expanding their range. The February 2021 …

Managing Inter-Organizational Trust And Risk Perceptions In Transboundary Fisheries Governance Networks, Evelyn Roozee, Dongkyu Kim, Antonia Sohns, Jasper R. De Vries, Owen Temby, Gordon M. Hickey

School of Earth, Environmental, & Marine Sciences Faculty Publications

Transboundary fishery management represents a significant governance challenge that requires ongoing inter-organizational communication, collaboration, and collective action to ensure sustainability. Previous research suggests that different dimensions of perceived risk, trust, and control interact in complex ways to affect inter-organizational collaborative performance, providing an administrative ‘architecture’ that enables partners to share resources, engage in teamwork, resolve conflict, and coordinate tasks and responsibilities while also allaying their concerns about the alliance. However, the extent to which different control mechanisms influence trust and mitigate the perceived risks of collaboration between the diverse organizations involved in transboundary fisheries management remains unclear. This paper presents …

Workshop: Active Learning Teaching Methods For Engineering Ethics Education, Shannon M. Chance

Research Outputs: 2025-Present

This workshop, conducted by the lead editor of the forthcoming Routledge International Handbook of Engineering Ethics Education, focuses on exploring active learning teaching methods in engineering ethics education. Beginning with a whole-group discussion to define ethics in engineering education, facilitators will present an overview of trends and teaching methods outlined in the handbook. These methods include case studies, project-based learning (PB), value-sensitive design, service-learning, arts-based methods, and reflective and dialogical approaches. Participants will then engage in hands-on activities, selecting one ethics topic (e.g., environmental sustainability, social justice, equity, diversity, and inclusion) and one active learning pedagogy (case studies and dilemmas, …

Guest Editorial Special Issue On Conceptual Learning Of Mathematics-Intensive Concepts In Engineering, Shannon Chance, Farrah Fayyaz, Anita L. Campbell, Nicole P. Pitterson, Sadia Nawaz

Research Outputs: 2025-Present

No abstract provided.

Exploring The Behavioural And Neural Bases Of Impulsivity In A Transdiagnostic Approach Relevant For Addiction., Kenza Kadri

School of Psychology Theses

This thesis aims to investigate the behavioural and neural basis of impulsivity, which is known to be a risk factor in the development of psychiatric disorders such as addiction. To tackle this issue, the thesis uses neuroimaging, behavioural, and machine-learning techniques to identify transdiagnostic markers of impulsivity and their relationship with striatal connectivity and decision-making variability. This thesis was divided into two studies. The first one aims to associate a set of transdiagnostic markers relevant to addiction with the connectivity profiles of the striatum, which is known to be implicated in processes of reward, motivation, and decision-making. In particular, this …

Double Testing With Lateral Flow Antigen Test Devices For Covid-19: Does A Second Test In Quick Succession Add Value?, Matthias E Futschik, Sarah A Tunkel, Elena Turek, David Chapman, Zareen Thorlu-Bangura, Raghavendran Kulasegaran-Shylini, Edward Blandford, Andrew Dodgson, Paul E Klapper, Malur Sudhanva, Derrick Crook, John Bell, Susan Hopkins, Tim Peto, Tom Fowler

School of Biomedical Sciences

BACKGROUND/OBJECTIVES: We investigated if performing two lateral flow device (LFD) tests, LFD2 immediately after LFD1, could improve diagnostic sensitivity or specificity for detecting severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) antigen.

STUDY DESIGN: Individuals aged ≥16 years attending UK community testing sites (February-May 2021) performed two successive LFD tests and provided a nose-and-throat sample for a polymerase chain reaction (PCR) test. Using the PCR result as the reference diagnosis, we assessed whether improvements could be achieved in sensitivity (by counting a positive result in either LFD as a positive overall test result) or specificity (by using LFD2 as confirmatory test). …

Flow Regimes In Bubble Columns With And Without Internals: A Review, Ayat N. Mahmood, Amer A. Abdulrahman, Laith S. Sabri, Abbas J. Sultan, Hasan Shakir Majdi, Muthanna H. Al-Dahhan

Chemical and Biochemical Engineering Faculty Research & Creative Works

Hydrodynamics characterization in terms of flow regime behavior is a crucial task to enhance the design of bubble column reactors and scaling up related methodologies. This review presents recent studies on the typical flow regimes established in bubble columns. Some effort is also provided to introduce relevant definitions pertaining to this field, namely, that of "void fraction" and related (local, chordal, cross-sectional and volumetric) variants. Experimental studies involving different parameters that affect design and operating conditions are also discussed in detail. In the second part of the review, the attention is shifted to cases with internals of various types (perforated …

Thermal Decomposition And Kinetic Parameters Of Three Biomass Feedstocks For The Performance Of The Gasification Process Using A Thermogravimetric Analyzer, Rania Almusafir, Joseph D. Smith

Chemical and Biochemical Engineering Faculty Research & Creative Works

Thermogravimetric analysis (TGA) is a powerful technique and useful method for characterizing biomass as a non-conventional fuel. A TGA apparatus has been utilized to experimentally investigate the impact of biomass feedstock diversity on the performance of the gasification of hardwood (HW), softwood (SW) pellets, and refuse-derived fuel (RDF) materials. The solid conversion rate and the volatile species formation rate have been estimated to quantify the rates of devolatilization for each material. In addition, the combustion kinetic characteristics of the three biomass feedstocks were investigated using TGA at different heating rates, and a thermal kinetic analysis was conducted to describe the …

Electromagnetic Near-Field Scanning With A Spatially Sparse Sampling Strategy Utilizing Kriging-Dmd, Yanming Zhang, Steven Gao, Lijun Jiang

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

This paper proposes a hybrid method for time-resolved electromagnetic near-field scanning, merging model-based (Gaussian processes regression model, a.k.a. Kriging method) and data-driven (dynamic mode decomposition) techniques. Specifically, Latin hypercube sampling enables spatially sparse measurements, followed by dynamic mode decomposition to analyze resulting sparse spatial-temporal data, extracting frequency information and sparse dynamic modes. The Kriging method is then employed for full-state reconstruction. The proposed approach is evaluated using crossed dipole antennas. Results indicate that, even with a spatial subsampling factor of 130, achieving a fully reconstructed field distribution suitable for engineering applications with frequency information extraction is feasible. This hybrid framework …

Towards A Concurrency Platform For Scalable Multi-Axial Real-Time Hybrid Simulation, Marion Sudvarg, Oren Bell, Tyler Martin, Benjamin Standaert, Tao Zhang, Sun Beom Kwon, Chris Gill, Arun Prakash

Computer Science Faculty Research & Creative Works

Multi-axial real-time hybrid simulation (maRTHS) uses multiple hydraulic actuators to apply loads and deform experimental substructures, enacting both translational and rotational motion. This allows for an increased level of realism in seismic testing. However, this also demands the implementation of multiple-input, multiple-output control strategies with complex nonlinear behaviors. To realize true real-time hybrid simulation at the necessary sub-millisecond timescales, computational platforms will need to support these complexities at scale, while still providing deadline assurance. This paper presents initial work towards supporting (and is influenced by the need for) envisioned larger-scale future experiments based on the current maRTHS benchmark: it discusses …

A Data-Driven Approach To Time-Domain Electromagnetic Modeling Based On Dynamic Mode Decomposition, Yanming Zhang, Steven Gao, Lijun Jiang

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

This paper presents a data-driven methodology that utilizes Dynamic Mode Decomposition (DMD) for the time-domain (TD) electromagnetic (EM) modeling of microwave devices. As an unsupervised machine learning technique, DMD leverages a limited set of unlabeled spatio-temporal electromagnetic (EM) data to determine DMD eigenvalues and eigenmodes. Then, the obtained DMD model reconstructs the dynamics as a series of exponential terms based on linear assumptions. The effectiveness of this approach is demonstrated through the TD EM modeling of photonic crystal waveguides. Comparative analysis with the finite-difference time-domain (FDTD) method shows that the DMD model not only achieves precise modeling but also facilitates …

Novel Re-Crosslinkable Preformed Particle Gels (Rppg) For Parent- And Infill-Well-Fracture Interactions Mitigation, Xiaojing Ge, Adel Alotibi, Ahmed Al-Hlaichi, Yanbo Liu, Tao Song, Junchen Liu, Baojun Bai, Thomas P. Schuman

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Hydraulic fracturing treatments in unconventional infill (or "child") wells can be significantly affected by depletion from existing parent-well, resulting in asymmetrical fracture growth. These issues may lead to excessive load-water production, proppant deposition, casing deformation in the parent well, and unbalanced stimulation of infill wells. To mitigate these effects, various strategies have been proposed, including the use of far-field diverters in child wells and repressurization of parent wells. Additionally, an increasingly popular strategy involves injecting near-wellbore diverters to temporarily plug entry points into the parent wellbores during frac operations on infill wells. To achieve better application, a novel low-cost, self-degradable, …

Would Self-Supported Fracture Contribute To The Hydrocarbon Production In Shale Reservoir Besides Proppant-Supported Fracture, Y. Sun, G. Li, S. Zeng, J. Wu, J. Liu, M. Xu, C. Dai, Baojun Bai

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

During hydraulic fracturing in deep shale gas reservoirs, it is difficult to pump proppants long distances, and self-supported fractures are formed at the far and upper ends of the fractures. The self-supported fracture could hold the fracture space by its surface structure again fracture closure. However, it faces various aspects of impairment during shale gas reservoir development, which affect its conductivity. Among the impairment, long-term production results in a decline of bottom hole pressure, which will compact the fracture space, and self-supported fractures without proppant are more sensitive than those with proppant. In this paper, we conducted a series of …

Comparative Analysis Of Critical Bond Strength Parameters Of Neat Class G Cement And Fly Ash Enhanced Cement To Steel, C. M. Potter, Andreas Eckert, James A. Jones, Z. Weicheng, M. Meng

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

In subsurface engineering applications, such as wellbore integrity, the interface between cement and steel is integral to expected functionality. The interface between steel and cement is often a structural weak point in many systems, however, the critical parameters for debonding evaluation are poorly understood and derived from outdated experimental procedures. Through experimental debonding tests, this study aims to analyze the tensile bond strength and fracture parameters and their sensitivity to cement composition with a pozzolanic additive (fly ash). Neat Class G cement testing resulted in an average tensile bond strength of 0.223 MPa, an average contact stiffness of 2.94x108 N/m3, …

Descriptive Statistical Analysis Of Experimental Data For Wettability Alteration With Smart Water Flooding In Carbonate Reservoirs, Muhammad Ali Buriro, Mingzhen Wei, Baojun Bai, Ya Yao

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Smart water flooding is a promising eco-friendly method for enhancing oil recovery in carbonate reservoirs. the optimal salinity and ionic composition of the injected water play a critical role in the success of this method. This study advances the field by employing machine learning and data analytics to streamline the determination of these critical parameters, which are traditionally reliant on time-intensive laboratory work. the primary objectives are to utilize data analytics to examine how smart water flooding influences wettability modification, identify key parameter ranges that notably alter the contact angle, and formulate guidelines and screening criteria for successful lab design. …

On The K-Weak Coverage Of Random Mobile Sensors, Sajal K. Das, Rafal Kapelko

Computer Science Faculty Research & Creative Works

This paper studies the fundamental problem of energy consumption in the movement of mobile random sensors ensuring k-weak coverage on the domain. In particular, we analyze two notions of k-weak coverage on the unit square, namely (1) (k, x)-weak coverage in which every straight-line path across the width of the unit square passes through the sensing range of at least k sensors; and (2) (k, x, y)-weak coverage in which every straight-line path across the width and the length of the unit square passes through the sensing range of at least k sensors. The number of reliable and p-reliable sensors …

Posca: Path Optimization For Solar Cover Amelioration In Urban Air Mobility, Debjyoti Sengupta, Anurag Satpathy, Sajal K. Das

Computer Science Faculty Research & Creative Works

Urban Air Mobility (UAM) encompasses both piloted and autonomous aerial vehicles, spanning from small unmanned aerial vehicles (UAVs) like drones to passenger-carrying personal air vehicles (PAVs), to revolutionize smart transportation in congested urban areas. This emerging paradigm is anticipated to offer disruptive solutions to the mobility challenges in congested cities. In this context, a pivotal concern centers on the sustainability of transitioning to this mode of transportation, especially with the focus on incorporating clean technology into developing innovative solutions from the ground up. Recent studies highlight that a significant portion of the total energy consumption in UAM can be attributed …

Tasr: A Novel Trust-Aware Stackelberg Routing Algorithm To Mitigate Traffic Congestion, Doris E.M. Brown, Venkata Sriram Siddhardh Nadendla, Sajal K. Das

Computer Science Faculty Research & Creative Works

A Stackelberg routing platform (SRP) reduces congestion in one-shot traffic networks by proposing optimal route recommendations to the selfish travelers. Traditionally, Stackel-berg routing is cast as a partial control problem where a fraction of the traveler flow complies with route recommendations, while the remaining responds as selfish travelers. In this paper, we formulate a novel Stackelberg routing framework where the agents exhibit probabilistic compliance by accepting SRP's route recommendations with a trust probability. Specifically, we propose a greedy Trust-Aware Stackelberg Routing algorithm (in short, TASR) for SRP to compute unique path recommendations to each traveler flow with a unique demand. …

Minerrouter : Effective Message Routing Using Contact-Graphs And Location Prediction In Underground Mine, Abhay Goyal, Sanjay Madria, Samuel Frimpong

Computer Science Faculty Research & Creative Works

Location-based distributed communication in underground mines has been a hard problem to solve due to unreliable centralized architecture such as leaky feeder systems, high attenuation, and the unavailability of GPS signals. Delay Tolerant Networks (DTN) enable decentralized message routing using the store-carry-forward method that can help in creating situational awareness needed to handle emergency and disaster scenarios. The ability to predict where the DTN nodes (miner) might have been at/are headed to (with respect to the mine regions and pillars) at different times, combined with contact-based routing and intelligent handling of buffer, can be used for better delivery of messages. …

Trusted Digital Twin Network For Intelligent Vehicles, Asad Malik, Ayan Roy, Sanjay Madria

Computer Science Faculty Research & Creative Works

Vehicle-to-vehicle (V2V) infrastructure facilitates wireless communication among vehicles within close proximity. This allows sharing of contextual information such as speed, location, direction, traffic, route closures, human behavior mental conditions to improve traffic flow, reduce collisions, and enhance safety on the road. However, the assumption of honest peers along with the over-reliability on the information shared in the network can pose a serious threat to human safety. A digital twin is a concept that enables a system to develop a virtual environment that mimics the real-life scenario for any situation. The availability of powerful computing equipment inside vehicles can be leveraged …

Unsafe Events Detection In Smart Water Meter Infrastructure Via Noise-Resilient Learning, Ayanfeoluwa Oluyomi, Sahar Abedzadeh, Shameek Bhattacharjee, Sajal K. Das

Computer Science Faculty Research & Creative Works

Residential smart water meters (SWMs) collect real-time water consumption data, enabling automated billing and peak period forecasting. The presence of unsafe events is typically detected via deviations from the benign profile of water usage. However, profiling the benign behavior is non-trivial for large-scale SWM networks because once deployed, the collected data already contain those events, biasing the benign profile. To address this challenge, we propose a real-time data-driven unsafe event detection framework for city-scale SWM networks that automatically learns the profile of benign behavior of water usage. Specifically, we first propose an optimal clustering of SWMs based on the recognition …