Engineering Commons^™

Synthesis Of N-Doped Tio2 Nanoparticles With Enhanced Photocatalytic Activity For 2,4-Dichlorophenol Degradation And H2 Production, Javed Ali Khan, Murtaza Sayed, Noor S. Shah, Sanaullah Khan, Ashfaq Ahmad Khan, Muhammad Sultan, Ammar M. Tighezza, Jibran Iqbal, Grzegorz Boczkaj

All Works

Nitrogen-doped titanium dioxide (N-TiO2) nanoparticles were prepared using a modified sol-gel method. The as-prepared nanoparticles were characterized by state-of-the-art techniques for their optical, structural and morphological properties. The crystallite size, surface area and bandgap energy of reference TiO2 and N-TiO2 nanoparticles were found to be 16.1 and 10.9nm, 83.6 and 131.8 m2 g−1 and 3.23 and 2.89eV, respectively. The photocatalytic activities, in terms of 2,4-dichlorophenol (2,4-DCP) degradation, of reference TiO2 and N-TiO2 were found to be 46.9 and 65.4% at 120min of treatments under UV light irradiation and 21.5 and 77.6% at 240min of treatment under visible light irradiation, employing …

Investigation Of Additives And Ingredients Of Bio-Resin For Visible Wavelength Laser-Induced Polymerization, Patrick Riggs

College of Graduate Studies: Theses & Dissertations

Optical 3D printing is a branch of Additive manufacturing (AM) that utilizes low-waste production leading to efficient and rapid prototyping. Currently, this method of AM is associated with mainly petroleum-based resins. Bio-resin polymerization is an emerging research area for finding replacements for petroleum-based resins, but curing the resin with laser energy is not normally a practical use case. Current optical 3D printing uses lasers to cure liquid resins to form solid 3D objects in a layer-by-layer process which is time consuming, defect prone, and a leading limiting factor for high volume production; so, finding a way to incorporate bio-resin into …

Understanding The Feasibility Of Improving Interfacial Properties In Direct Ink Writing Of Silicone-Polyurethane Resin Hybrid Material, Ayobami Samuel Akinfenwa

College of Graduate Studies: Theses & Dissertations

The progress in materials engineering and the ability to make various models possible have made soft robotics a popular alternative to traditional robotics. Still, soft robots need various parts, like Printed Circuit Boards (PCBs), batteries, cables, fittings, and more, to work correctly or to get attached to other complex parts. These parts can have different material properties, like elastic moduli, strength, etc. Because of these differences, mechanical failures happen at the points where two materials meet, making soft robots less durable and less lasting in real-life situations due to failure. Conventionally, the fabrication of soft robot parts is through moulding. …

Tutorial - Shodhguru Labs: Knowledge-Infused Artificial Intelligence For Mental Healthcare, Kaushik Roy

Publications

Artificial Intelligence (AI) systems for mental healthcare (MHCare) have been ever-growing after realizing the importance of early interventions for patients with chronic mental health (MH) conditions. Social media (SocMedia) emerged as the go-to platform for supporting patients seeking MHCare. The creation of peer-support groups without social stigma has resulted in patients transitioning from clinical settings to SocMedia supported interactions for quick help. Researchers started exploring SocMedia content in search of cues that showcase correlation or causation between different MH conditions to design better interventional strategies. User-level Classification-based AI systems were designed to leverage diverse SocMedia data from various MH conditions, …

Metal-Organic Framework-Based Biosensing Platforms For The Sensitive Determination Of Trace Elements And Heavy Metals: A Comprehensive Review, Hessamaddin Sohrabi, Shahin Ghasemzadeh, Sama Shakib, Mir Reza Majidi, Amir Razmjou, Yeojoon Yoon, Alireza Khataee

Research outputs 2022 to 2026

Heavy metals in food and water sources are potentially harmful to humans. Determination of these pollutants is critical for improving safety. Effective recognition systems are a contemporary challenge; several novel technologies for the quick, easy, selective, and sensitive determination of these compounds are in demand. Metal-organic framework (MOF)-based sensors and biosensors have crucial applications in identifying these potentially harmful substances. Here, we review electrochemical and optical biosensors for in situ sensing that are sensitive and cost effective, with a simple protocol and wide linear range. Despite the abundance of articles in this field, we assessed and checked out various basic …

Dfhic: A Dilated Full Convolution Model To Enhance The Resolution Of Hi-C Data, Bin Wang, Kun Liu, Yaohang Li, Jianxin Wang

Computer Science Faculty Publications

Motivation: Hi-C technology has been the most widely used chromosome conformation capture(3C) experiment that measures the frequency of all paired interactions in the entire genome, which is a powerful tool for studying the 3D structure of the genome. The fineness of the constructed genome structure depends on the resolution of Hi-C data. However, due to the fact that high-resolution Hi-C data require deep sequencing and thus high experimental cost, most available Hi-C data are in low-resolution. Hence, it is essential to enhance the quality of Hi-C data by developing the effective computational methods.

Results: In this work, we propose …

Hashes Are Not Suitable To Verify Fixity Of The Public Archived Web, Mohamed Aturban, Martin Klein, Herbert Van De Sompel, Sawood Alam, Michael L. Nelson, Michele C. Weigle

Computer Science Faculty Publications

Web archives, such as the Internet Archive, preserve the web and allow access to prior states of web pages. We implicitly trust their versions of archived pages, but as their role moves from preserving curios of the past to facilitating present day adjudication, we are concerned with verifying the fixity of archived web pages, or mementos, to ensure they have always remained unaltered. A widely used technique in digital preservation to verify the fixity of an archived resource is to periodically compute a cryptographic hash value on a resource and then compare it with a previous hash value. If the …

A Bibliometric Analysis And Review On The Performance Of Polymer-Modified Bitumen, Adham M. Alnadish, Herda Y. B. Katman, Mohd R. Ibrahim, Yaser Gamil, Nuha S. Mashaan

Research outputs 2022 to 2026

The addition of polymer to a base binder has been documented as a successful approach in terms of improving physical and rheological properties of the base bitumen. However, the main drawbacks of polymer-modified bitumen are incompatibility and degradation of polymer due to aging. This article aims to introduce a bibliometric analysis and review on modifying bitumen with polymers. Additionally, this article intent to highlight the significant gaps and recommendations for future work. Furthermore, another objective of this article is to provide a worth attempt regrading reducing the negative impact of polymer’s drawbacks on the performance of polymer-modified base binder. The …

A Survey On Artificial Intelligence-Based Acoustic Source Identification, Ruba Zaheer, Iftekhar Ahmad, Daryoush Habibi, Kazi Y. Islam, Quoc Viet Phung

Research outputs 2022 to 2026

The concept of Acoustic Source Identification (ASI), which refers to the process of identifying noise sources has attracted increasing attention in recent years. The ASI technology can be used for surveillance, monitoring, and maintenance applications in a wide range of sectors, such as defence, manufacturing, healthcare, and agriculture. Acoustic signature analysis and pattern recognition remain the core technologies for noise source identification. Manual identification of acoustic signatures, however, has become increasingly challenging as dataset sizes grow. As a result, the use of Artificial Intelligence (AI) techniques for identifying noise sources has become increasingly relevant and useful. In this paper, we …

Instantaneous Frequency Estimation Of Fm Signals Under Gaussian And Symmetric Alpha-Stable Noise: Deep Learning Versus Time-Frequency Analysis, Huda Saleem Razzaq, Zahir M. Hussain

Research outputs 2022 to 2026

Deep learning (DL) and machine learning (ML) are widely used in many fields but rarely used in the frequency estimation (FE) and slope estimation (SE) of signals. Frequency and slope estimation for frequency-modulated (FM) and single-tone sinusoidal signals are essential in various applications, such as wireless communications, sound navigation and ranging (SONAR), and radio detection and ranging (RADAR) measurements. This work proposed a novel frequency estimation technique for instantaneous linear FM (LFM) sinusoidal wave using deep learning. Deep neural networks (DNN) and convolutional neural networks (CNN) are classes of artificial neural networks (ANNs) used for the frequency and slope estimation …

Driving Training-Based Optimization (Dtbo) For Global Maximum Power Point Tracking For A Photovoltaic System Under Partial Shading Condition, Haroon Rehman, Injila Sajid, Adil Sarwar, Mohd Tariq, Farhad I. Bakhsh, Shafiq Ahmad, Haitham A. Mahmoud, Asma Aziz

Research outputs 2022 to 2026

The presence of bypass diodes in photovoltaic (PV) arrays can mitigate the negative effects of partial shading conditions (PSCs), which can cause multiple peak characteristics at the output. However, conventional maximum power point tracking (MPPT) methods can develop errors and detect the local maximum power point (LMPP) instead of the global maximum power point (GMPP) under certain circumstances. To address this issue, several artificial intelligence (AI)-based methods have been proposed, but they result in complicated and unreliable methodologies. This study introduces the driving training-based optimization (DTBO) method, which aims to address the partial shading (PS) problem quickly and reliably in …

Confined Tri-Functional Feox@Mno2@Sio2 Flask Micromotors For Long-Lasting Motion And Catalytic Reactions, Yangyang Yang, Lei Shi, Jingkai Lin, Panpan Zhang, Kunsheng Hu, Shuang Meng, Peng Zhou, Xiaoguang Duan, Hongqi Sun, Shaobin Wang

Research outputs 2022 to 2026

H2O₂-fueled micromotors are state-of-the-art mobile microreactors in environmental remediation. In this work, a magnetic FeO_x@MnO₂@SiO₂ micromotor with multi-functions is designed and demonstrated its catalytic performance in H₂O₂/peroxymonosulfate (PMS) activation for simultaneously sustained motion and organic degradation. Moreover, this work reveals the correlations between catalytic efficiency and motion behavior/mechanism. The inner magnetic FeO_x nanoellipsoids primarily trigger radical species (OH and O₂−) to attack organics via Fenton-like reactions. The coated MnO₂ layers on FeO_x surface are responsible for decomposing H₂O₂ into O_{2 …}

Predictive Models For Concrete Cone Capacity Of Cast-In Headed Anchors In Geopolymer Concrete, Trijon Karmokar, Alireza Mohyeddin, Jessey Lee

Research outputs 2022 to 2026

The scope of current state-of-the-art prediction models for concrete cone capacity of cast-in headed anchors is limited to normal concrete. In this study, the difference in the tensile performance of cast-in headed anchors embedded in ambient-temperature cured fly ash-based geopolymer concrete and normal concrete is investigated using both experimental and numerical analysis. The concrete cone capacity obtained for anchors investigated in this study is compared with current prediction models namely: Concrete Capacity Design (CCD) model, which overestimated the results by a maximum of 41%, and Linear Fracture Mechanics (LFM), which underestimated the results by a maximum of 53%. Anchors of …

Experimental Study On The Mechanical Controlling Factors Of Fracture Plugging Strength For Lost Circulation Control In Shale Gas Reservoir, Chengyuan Xu, Lingmao Zhu, Feng Xu, Yili Kang, Haoran Jing, Zhenjiang You

Research outputs 2022 to 2026

The geological conditions of shale reservoir present several unique challenges. These include the extensive development of multi-scale fractures, frequent losses during horizontal drilling, low success rates in plugging, and a tendency for the fracture plugging zone to experience repeated failures. Extensive analysis suggests that the weakening of the mechanical properties of shale fracture surfaces is the primary factor responsible for reducing the bearing capacity of the fracture plugging zone. To assess the influence of oil-based environments on the degradation of mechanical properties in shale fracture surfaces, rigorous mechanical property tests were conducted on shale samples subsequent to their exposure to …

Memory-Based Adaptive Sliding Mode Load Frequency Control In Interconnected Power Systems With Energy Storage, Farhad Farivar, Octavian Bass, Daryoush Habibi

Research outputs 2022 to 2026

This paper presents a memory-based adaptive sliding mode load frequency control (LFC) strategy aimed at minimizing the impacts of exogenous power disturbances and parameter uncertainties on frequency deviations in interconnected power systems with energy storage. First, the dynamic model of the system is constructed by considering the participation of the energy storage system (ESS) in the conventional decentralized LFC model of a multiarea power system. A disturbance observer (DOB) is proposed to generate an online approximation of the lumped disturbance. In order to enhance the transient performance of the system and effectively mitigate the adverse effects of power fluctuations on …

Optimum Design, Socioenvironmental Impact, And Exergy Analysis Of A Solar And Rice Husk-Based Off-Grid Hybrid Renewable Energy System, Barun K. Das, Rakibul Hassan, Polamarasetty P. Kumar, Ismail Hoque, Ramakrishna S.S. Nuvvula, Anas M. Maruf, Arnob Das, Paul C. Okonkwo, Baseem Khan

Research outputs 2022 to 2026

This study examines the optimal sizing of an off-grid hybrid system comprising solar photovoltaic (PV), rice husk-based biomass, and lead-acid battery for meeting the electric demand of a rural community. Considering a selected remote village in Bangladesh as a case study, the proposed optimized system is primarily compared with the diesel generator and the micro gas turbine (MGT)-based options in techno-economic and environmental terms. The potential social benefits, such as the employment creation and the improvement in the human development index in the locality, have been investigated in this study. Moreover, the impacts of operational greenhouse gas emissions on the …

Uncertainties In Wave-Driven Longshore Sediment Transport Projections Presented By A Dynamic Cmip6-Based Ensemble, Amin Reza Zarifsanayei, José A.A. Antolínez, Nick Cartwright, Amir Etemad-Shahidi, Darrell Strauss, Gil Lemos, Alvaro Semedo, Rajesh Kumar, Mikhail Dobrynin, Adem Akpinar

Research outputs 2022 to 2026

In this study four experiments were conducted to investigate uncertainty in future longshore sediment transport (LST) projections due to: working with continuous time series of CSIRO CMIP6-driven waves (experiment #1) or sliced time series of waves from CSIRO-CMIP6-Ws and CSIRO-CMIP5-Ws (experiment #2); different wave-model-parametrization pairs to generate wave projections (experiment #3); and the inclusion/exclusion of sea level rise (SLR) for wave transformation (experiment #4). For each experiment, a weighted ensemble consisting of offshore wave forcing conditions, a surrogate model for nearshore wave transformation and eight LST models was used. The results of experiment # 1 indicated that the annual LST …

Application Of A Novel Green Nano Polymer For Chemical Eor Purposes In Sandstone Reservoirs: Synergetic Effects Of Different Fluid/Fluid And Rock/Fluid Interacting Mechanisms, Abbas K. Manshad, Alireza Kabipour, Erfan Mohammadian, Lei Yan, Jagar A. A., Stefan Iglauer, Alireza Keshavarz, Milad Norouzpour, Amin Azdarpour, S. Mohammad Sajadi, Siyamak Moradi

Research outputs 2022 to 2026

In this research, a novel natural-based polymer, the Aloe Vera biopolymer, is used to improve the mobility of the injected water. Unlike most synthetic chemical polymers used for chemical-enhanced oil recovery, the Aloe Vera biopolymer is environmentally friendly, thermally stable in reservoir conditions, and compatible with reservoir rock and fluids. In addition, the efficiency of the Aloe Vera biopolymer was investigated in the presence of a new synthetic nanocomposite composed of KCl-SiO2-xanthan. This chemically enhanced oil recovery method was applied on a sandstone reservoir in Southwest Iran with crude oil with an API gravity of 22°. The Aloe Vera biopolymer’s …

Enhancing Professional Skills Among Engineering Students By Interdisciplinary International Collaboration, Thomas Mejtoft, Helen Cripps, Melissa Fong-Emmerson, Christopher Blöcker

Research outputs 2022 to 2026

Providing necessary knowledge and skills for engineering students to become successful professionals is a tricky task. Besides disciplinary knowledge, e.g., communication skills, ability to work in teams, and international experience are often mentioned as important. Regarding internationalization, most engineering programs in Sweden rely on either student exchange or low-level internationalization-at-home, such as international literature and lecturers. This paper explores sustainable international experiences for students on their home turf provided through an international interdisciplinary collaboration where engineering students in Sweden and marketing students in Australia work together on a project. The setup simulates a consultancy firm with development and marketing offices …

Assessing The Performance Of A Particle Swarm Optimization Mobility Algorithm In A Hybrid Wi-Fi/Lora Flying Ad Hoc Network, William David Paredes

UNF Graduate Theses and Dissertations

Research on Flying Ad-Hoc Networks (FANETs) has increased due to the availability of Unmanned Aerial Vehicles (UAVs) and the electronic components that control and connect them. Many applications, such as 3D mapping, construction inspection, or emergency response operations could benefit from an application and adaptation of swarm intelligence-based deployments of multiple UAVs. Such groups of cooperating UAVs, through the use of local rules, could be seen as network nodes establishing an ad-hoc network for communication purposes.

One FANET application is to provide communication coverage over an area where communication infrastructure is unavailable. A crucial part of a FANET implementation is …

Evaluating Human Eye Features For Objective Measure Of Working Memory Capacity, Yasasi Abeysinghe, Enkelejda Kasneci (Ed.), Frederick Shic (Ed.), Mohamed Khamis (Ed.)

Computer Science Faculty Publications

Eye tracking measures can provide means to understand the underlying development of human working memory. In this study, we propose to develop machine learning algorithms to find an objective relationship between human eye movements via oculomotor plant and their working memory capacity, which determines subjective cognitive load. Here we evaluate oculomotor plant features extracted from saccadic eye movements, traditional positional gaze metrics, and advanced eye metrics such as ambient/focal coefficient , gaze transition entropy, low/high index of pupillary activity (LHIPA), and real-time index of pupillary activity (RIPA). This paper outlines the proposed approach of evaluating eye movements for obtaining an …

Inclusion4eu: Co-Designing A Framework For Inclusive Software Design And Development, Dympna O'Sullivan, Emma Murphy, Andrea Curley, John Gilligan, Damian Gordon, Anna Becevel, Svetland Hensman, Mariana Rocha, Claudia Fernandez, Michael Collins, J. Paul Gibson, Gordana Dodig-Crnkovic, Gearoid Kearney, Sarah Boland

Articles

Digital technology is now pervasive, however, not all groups have uniformly benefitted from technological changes and some groups have been left behind or digitally excluded. Comprehensive data from the 2017 Current Population Survey shows that older people and persons with disabilities still lag behind in computer and internet access. Furthermore unique ethical, privacy and safety implications exist for the use of technology for older persons and people with disabilities and careful reflection is required to incorporate these aspects, which are not always part of a traditional software lifecycle. In this paper we present the Inclusion4EU project that aims to co-design …

Survey Of Routing Techniques-Based Optimization Of Energy Consumption In Sd-Dcn, Mohammed Nsaif, Gergely Kovásznai, Ali Malik, Ruairí De Fréin

Articles

The increasing power consumption of Data Center Networks (DCN) is becoming a major concern for network operators. The object of this paper is to provide a survey of state-of-the-art methods for reducing energy consumption via (1) enhanced scheduling and (2) enhanced aggregation of traffic flows using Software-Defined Networks (SDN), focusing on the advantages and disadvantages of these approaches. We tackle a gap in the literature for a review of SDN-based energy saving techniques and discuss the limitations of multi-controller solutions in terms of constraints on their performance. The main finding of this survey paper is that the two classes of …

Governance-Aware Cloud Architectures For Enterprise Information Systems, Manikantha Varaprasad Inakollu

Computer Science and Engineering Faculty Publications

Enterprise cloud adoption has accelerated dramatically, yet governance frameworks struggle to keep pace with evolving architectural complexity. This research examines how organizations can embed governance principles directly into cloud architecture designs rather than treating compliance as an afterthought. We investigate the integration of regulatory requirements, risk management protocols, and organizational policies into cloud infrastructure patterns that enforce governance automatically. The study addresses critical gaps where traditional governance approaches fail in dynamic cloud environments, particularly around data sovereignty, access control, audit requirements, and regulatory compliance. Through analysis of existing cloud governance challenges and architectural patterns, we propose a comprehensive framework that …

Post-Implementation Erp Value Realization: A Decision Intelligence Framework, Manikantha Varaprasad Inakollu

Computer Science and Engineering Faculty Publications

Enterprise Resource Planning systems represent substantial organizational investments, yet many organizations struggle to realize expected benefits after implementation. This research develops a decision intelligence framework specifically designed to maximize ERP value realization during the critical post-implementation phase. While extensive literature addresses ERP implementation challenges, significantly less attention focuses on extracting value after systems go live. Our framework integrates data analytics, organizational learning, and strategic decision-making into a cohesive approach that transforms ERP systems from operational tools into strategic assets. Through analysis of post-implementation patterns across multiple organizations, we identify key decision points where intelligent interventions dramatically improve value capture. The …

Erp As A Digital Backbone: Redefining Enterprise Systems For Continuous Value Creation, Manikantha Varaprasad Inakollu

Computer Science and Engineering Faculty Publications

Enterprise Resource Planning systems have evolved from transactional processing tools into strategic digital backbones that orchestrate organizational value creation. This research examines how modern ERP implementations transcend traditional operational efficiency goals to enable continuous innovation, real-time decision-making, and ecosystem integration. Through analysis of contemporary ERP architectures and their impact on organizational capabilities, we demonstrate that successful digital transformation requires reconceptualizing ERP not as a software package but as an adaptive infrastructure supporting diverse business models. Our findings reveal that organizations treating ERP as a digital backbone achieve 35% higher agility scores and 42% faster time-to-market for new capabilities compared to …

Suitability Of Quantized Devs-Lim Methods For Simulation Of Power Systems, Navid Gholizadeh

Theses and Dissertations

This research presents an investigation of behavioral intricacies of the Quantized DEVS Latency Insertion Method (QDL) method and proposes resolutions to the previously unsolved and unexplained discrepancies between the reference solution and the QDL method. QDL method is a combination of two other methods namely the Latency Insertion Method (LIM) and Linear Implicit Quantized State (LIQSS)method. This technique is rigorously evaluated across a diverse array of systems and scenarios, with the aim of unearthing nuanced insights into its respective functionalities.

The research seeks to discern novel attributes of this method while gauging its comparative efficacy against conventional discrete-time methodologies, both …

Image-Based Malware Classification On Noise Extraction, Venkata Sai Sathwik Nadella

Master's Projects

Any malicious software designed to cause harm or damage to a computer system can be termed as malware. One common form of malware is as executable files. Such files are often used as a delivery mechanism for malware since they can be easily disguised as legitimate software and can be executed without raising suspicion. They are often used to exploit vulnerabilities in software, allowing malware to bypass security measures and gain access to sensitive information.

There are several methods used to detect malware in executable files, including Signaturebased detection, Behavioral-based detection, Heuristic-based detection, Sandboxing, Machine Learning and Artificial Intelligence (AI). …

Group-Invariant Reinforcement Learning, Fnu Ankur

Master's Theses

Our work introduces a way to learn an optimal reinforcement learning agent accompanied by intrinsic properties of the environment. The extracted properties helps the agent to extrapolate the learning to unseen states efficiently. Out of all the various types of properties, we are intrigued towards equivariant and invariant properties, which essentially translates to symmetry. Contrary to many approaches, we do not assume the symmetry, rather learn them, making the approach agnostic to the environment and the property. The learned properties offers multiple perspective of the environment to exploit it to benefit decision making while interacting with the environment. By building …

Automatic Presentation Slide Generation Using Llms, Tanya Gupta

Master's Theses

Presentation slides are widely used for conveying information in academic and professional contexts. However, manual slide creation can be time-consuming. Our research focuses on automated slide generation, specifically for scientific research papers. Automating the creation of presentation slides for scientific documents is a rather novel task and hence, there’s limited training data available and there also exists the token constraints of language models like BERT, with a maximum sequence length of 512 tokens. In this study, we fine-tune large language models, including Longformer-Encoder-Decoder (supporting sequences up to 16,834 tokens) and BIGBIRD-Pegasus (supporting sequences up to 4,096 tokens). We tackle this …