Physical Sciences and Mathematics Commons^™

Trends And Patterns Of Plant Conservation Research In Borneo: A Review, Rizmoon Nurul Zulkarnaen, Sabri Mohd. Ali, Daniele Cicuzza

ASEAN Journal on Science and Technology for Development

Borneo hosts exceptional plant diversity, including numerous endemic species, but faces significant threats from rapid habitat loss driven by deforestation and land-use changes. This study aimed to analyze research trends and forecast future directions through a bibliometric analysis of Scopus data spanning from 1914 to 2023. The bibliometric analysis included publication outputs, citation patterns, thematic mapping, and keyword co-occurrence. We used VOSviewer to visualize bibliometric networks and the Bibliometrix package in R to perform advanced bibliometric analysis and interactive data exploration. The analysis revealed a continuous rise in publications (998 documents), with the Journal of Ecology identified as the most …

Policy Strategies For Developing Superior Human Resources For The Sugar Cane Agro-Industry In The Industrial Era 4.0 In Indonesia, Mursiti Mursiti, Illah Sailah, Marimin Marimin, Muhammad Romli, Alex Denni

ASEAN Journal on Science and Technology for Development

The development of Industry 4.0 creates new challenges for human resources. Research in the field of human resources for the sugarcane agro-industry is still rare and is important because it is a strategic commodity in Indonesian for the sustainability of the sugarcane industry. The scope of the research ranges from the cut load transportation to sugar refining. The aim of the research is to conduct human resource scenario planning towards Human Resource 4.0 in sugarcane agroindustry. The research method used is scenario planning. The data were obtained from primary and secondary data. The variables used are human resource readiness and …

Different Visions From Biosview: A Brief Report, Lucas N. Potter, Xavier-Lewis Palmer

Electrical & Computer Engineering Faculty Publications

In this collaborative research endeavor at the intersection of biological safety and cybersecurity for BiosView labs, the authors highlight their engagement with a diverse student cohort. The chapter delves into the motivation behind collaborations extending beyond traditional academic research environments, emphasizing inclusivity. The meticulous examination of student demographics, including gender, self-reported ethnicity, and national origin, is detailed in the methodology. A student-centric approach is central to the exploration, focusing on aligning teaching and management styles with unique student needs. The chapter elaborates on effective teaching methodologies and management practices tailored for BiosView labs. A dedicated section emphasizes the purpose of …

Domain Adaptive Federated Learning For Multi-Institution Molecular Mutation Prediction And Bias Identification, W. Farzana, M. A. Witherow, I. Longoria, M. S. Sadique, A. Temtam, K. M. Iftekharuddin

Electrical & Computer Engineering Faculty Publications

Deep learning models have shown potential in medical image analysis tasks. However, training a generalized deep learning model requires huge amounts of patient data that is usually gathered from multiple institutions which may raise privacy concerns. Federated learning (FL) provides an alternative to sharing data across institutions. Nonetheless, FL is susceptible to a few challenges including inversion attacks on model weights, heterogenous data distributions, and bias. This study addresses heterogeneity and bias issues for multi-institution patient data by proposing domain adaptive FL modeling using several radiomics (volume, fractal, texture) features for O6-methylguanine-DNA methyltransferase (MGMT) classification across multiple institutions. The proposed …

Using Feature Selection Enhancement To Evaluate Attack Detection In The Internet Of Things Environment, Khawlah Harahsheh, Rami Al-Naimat, Chung-Hao Chen

Electrical & Computer Engineering Faculty Publications

The rapid evolution of technology has given rise to a connected world where billions of devices interact seamlessly, forming what is known as the Internet of Things (IoT). While the IoT offers incredible convenience and efficiency, it presents a significant challenge to cybersecurity and is characterized by various power, capacity, and computational process limitations. Machine learning techniques, particularly those encompassing supervised classification techniques, offer a systematic approach to training models using labeled datasets. These techniques enable intrusion detection systems (IDSs) to discern patterns indicative of potential attacks amidst the vast amounts of IoT data. Our investigation delves into various aspects …

Quest For An Optimal Spin-Polarized Electron Source For The Electron-Ion Collider, J. Biswas, E. Wang, O. Rahman, J. Sharitka, K. Kisslinger, Adam Masters, S. Marsillac, T. Lee

Electrical & Computer Engineering Faculty Publications

Superlattice GaAs photocathodes play a crucial role as the primary source of polarized electrons in various accelerator facilities, including the Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson National Laboratory and the Electron-Ion Collider (EIC) at Brookhaven National Laboratory. To increase the quantum efficiency (QE) of GaAs/GaAsP superlattice photocathodes, a Distributed Bragg Reflector (DBR) is grown underneath using metal-organic chemical vapor deposition (MOCVD). There are several challenges associated with DBR photocathodes: the resonance peak may not align with the emission threshold of around 780 nm, non-uniform doping density in the top 5 nm may significantly impact QE and spin polarization, …

Beyond Binary: Revealing Variations In Islamophobic Content With Hierarchical Multi-Class Classification, Esraa Aldreabi, Khawlah M. Harahsheh, Mukul Dev Chhangani, Chung-Hao Chen, Jeremy Blackburn

Electrical & Computer Engineering Faculty Publications

In the digital age, the rise of Islamophobia-marked by an irrational fear or discrimination against Islam and Muslims-has emerged as a pressing issue, especially on social media platforms. In this paper we employs a multi-class classification system, moving beyond traditional binary models. We categorize Islamophobic content into three main classes and various subclasses, covering a range from subtle biases to explicit incitement. Comparative analysis of data from Reddit and Twitter illuminates the distinct prevalence and types of Islamophobic content specific to each platform. This paper deepens our understanding of digital Islamophobia and provides insights for crafting targeted online counter strategies. …

Thermal Diffusivity And Acoustic Properties Of Nb Thin Films Studied By Time-Domain Thermoreflectance, Md. Obidul Islam, Hani Elsayed-Ali

Electrical & Computer Engineering Faculty Publications

The thermal diffusion and acoustic properties of Nb impacts the thermal management of devices incorporating Nb thin films such as superconducting radiofrequency (SRF) cavities and superconducting high-speed electronic devices. The diffusion and acoustic properties of 200-800 nm thick Nb films deposited on Cu substrates were investigated using time-domain thermoreflectance (TDTR). The films were examined by X-ray diffraction, scanning electron microscopy, and atomic force microscopy. The grain size and thermal diffusivity increase with film thickness. The thermal diffusivity increased from 0.100± 0.002 cm²s^-1 to 0.237± 0.002 cm²s^-1 with the increase in film thickness from 200 …

Real-Time Spectroscopic Ellipsometry For Flux Calibrations In Multi-Source Co-Evaporation Of Thin Films: Application To Rate Variations In Cuinse₂ Deposition, Dhurba R. Sapkota, Balaji Ramanujam, Puja Pradhan, Mohammed A. Razooqi Alaani, Ambalanath Shan, Michael J. Heben, Sylvain Marsillac, Nikolas J. Podraza, Robert W. Collins

Electrical & Computer Engineering Faculty Publications

Flux calibrations in multi-source thermal co-evaporation of thin films have been developed based on real-time spectroscopic ellipsometry (RTSE) measurements. This methodology has been applied to fabricate CuInSe₂ (CIS) thin film photovoltaic (PV) absorbers, as an illustrative example, and their properties as functions of deposition rate have been studied. In this example, multiple Cu layers are deposited step-wise onto the same Si wafer substrate at different Cu evaporation source temperatures (TCu). Multiple In₂Se₃ layers are deposited similarly at different In source temperatures (TIn). Using RTSE, the Cu and In₂Se₃ deposition rates are determined as …

Parametrization Of Fluid Models For Electrical Breakdown Of Nitrogen At Atmospheric Pressure, Shirshak K. Dhali

Electrical & Computer Engineering Faculty Publications

In the transient phase of an atmospheric pressure discharge, the avalanche turns into a streamer discharge with time. Hydrodynamic fluid models are frequently used to describe the formation and propagation of streamers, where charge particle transport is dominated by the creation of space charge. The required electron transport data and rate coefficients for the fluid model are parameterized using the local mean energy approximation (LMEA) and the local field approximation (LFA). In atmospheric pressure applications, the excited species produced in the electrical discharge determine the subsequent conversion chemistry. We performed the fluid model simulation of streamers in nitrogen gas at …

Investigation Of The Effect Of Preparation Parameters On The Structural And Mechanical Properties Of Gelatin/Elastin/Sodium Hyaluronate Scaffolds Fabricated By The Combined Foaming And Freeze-Drying Techniques, Mansour Qamash, S. Misagh Imani, Meisam Omidi, Ciara Glancy, Lobat Tayebi

Electrical & Computer Engineering Faculty Publications

This paper aimed to evaluate the effects of different preparation parameters, including agitation speed, agitation time, and chilling temperature, on the structural and mechanical properties of a novel gelatin/elastin/sodium hyaluronate tissue engineering scaffold, recently developed by our research group. Fabricated using a combination of foaming and freeze-drying techniques, the scaffolds were assessed to understand how these parameters influence their morphology, internal microstructure, porosity, mechanical properties, and degradation behavior. The fabrication process used in this study involved preparing a homogeneous aqueous solution containing 8% gelatin, 2% elastin, and 0.5% sodium hyaluronate (w/v), which was then subjected to mechanical agitation at speeds …

Generalized Functions In The Study Of Signals And Systems, Erik I. Verriest, Gunther Dirr, W. Steven Gray

Electrical & Computer Engineering Faculty Publications

We collect three instances where the theory of generalized functions may still make contributions to the study of signals and systems. In the first, a purely algebraic approach is presented for LTI-ODE's, in terms of two operators, D and T, respectively the differentiation operator and the multiplication-by-the-independent-variable operator. This formalism adds simplicity, a duality theory, and nicely generalizes to other classes of operator equations and their solutions. In the second part we extend the classical bilateral Laplace transform to include Bohl functions with support in ℝ by invoking Sato's hyperfunctions. Finally, in the third case we use the Colombeau algebra …

Transfer Learning For Field Emission Mitigation In Cebaf Srf Cavities, K. Ahammed, J. Li, A. Carpenter, C. Tennant, R. Suleiman

Electrical & Computer Engineering Faculty Publications

The Continuous Electron Beam Accelerator Facility (CEBAF) operates hundreds of superconducting radio frequency (SRF) cavities in its two linear accelerators (linacs). Field emission (FE) is an ongoing operational challenge in higher gradient SRF cavities. FE generates high levels of neutron and gamma radiation leading to damaged accelerator hardware and a radiation hazard environment. During machine development periods, we performed invasive gradient scans to record data capturing the relationship between cavity gradients and radiation levels measured throughout the linacs. However, the field emission environment at CEBAF varies considerably over time as the configuration of the radio-frequency (RF) gradients changes or due …

An Enhanced Real-Time Intrusion Detection Framework Using Federated Transfer Learning In Large-Scale Iot Networks, Khawlah Harahsheh, Malek Alzaqebah, Chung-Hao Chen

Electrical & Computer Engineering Faculty Publications

The exponential growth of Internet of Things (IoT) devices has introduced critical security challenges, particularly in scalability, privacy, and resource constraints. Traditional centralized intrusion detection systems (IDS) struggle to address these issues effectively. To overcome these limitations, this study proposes a novel Federated Transfer Learning (FTL)-based intrusion detection framework tailored for large-scale IoT networks. By integrating Federated Learning (FL) with Transfer Learning (TL), the framework enhances detection capabilities while ensuring data privacy and reducing communication overhead. The hybrid model incorporates convolutional neural networks (CNNs), bidirectional gated recurrent units (BiGRUs), attention mechanisms, and ensemble learning. To address the class imbalance, Synthetic …

A Review Of Emerging Sensor Technologies For Tank Inspection: A Focus On Lidar And Hyperspectral Imaging And Their Automation And Deployment, Sergio Pallas Enguita, Chung-Hao Chen, Samuel Kovacic

Electrical & Computer Engineering Faculty Publications

This paper reviews various sensor technologies for tank inspection, focusing on Light Detection and Ranging (LiDAR) and Hyperspectral Imaging (HSI) as advanced solutions for corrosion detection. These technologies are evaluated alongside traditional methods such as ultrasonic, electromagnetic, and thermographic inspections. This review highlights their potential to enhance inspection accuracy, reduce the limitations of manual inspection, and support integrated data analysis for comprehensive asset management. Additionally, this paper proposes a pathway for automating these techniques to streamline inspection processes and improve implementation in practical applications.

An Overview Of The Relationships Between The Food Industry And Nanotechnology, Mehdi Koushki, Nasrin Amiri-Dashatan, Hossein Pourghadamyari, Hadi Khodabandehloo, Fatemeh Bagheri, Masoumeh Farahani, Lobat Tayebi

Electrical & Computer Engineering Faculty Publications

Background and Objective: Due to the growth of the global population, food demands are increasing. Hence, the need to develop more efficient methods for producing better quality, safer, and more sustainable food seems essential. In the past decades, the use of nanoscale materials has increased greatly due to the unique chemical, physical, and biological characteristics of nanomaterials compared to bulk materials. This research presents nanotechnology role in improving sensorial properties (taste, appearance, and texture) and safety aspects as well as processing and packaging of foods. The use of nano-omics-based technologies and artificial intelligence-nanotechnology-based technologies in the food industry is also …

Direct Measurement Of Microwave Loss In Nb Films For Superconducting Qubits, B. Abdisatarov, D. Bafia, A. Murthy, G. Eremeev, H. E. Elsayed-Ali, J. Lee, A. Netepenko, C. P. A. Carlos, S. Leith, G. J. Rosaz, A. Romanenko, A. Grassellino

Electrical & Computer Engineering Faculty Publications

Niobium films are a key component in modern two-dimensional superconducting qubits, yet their contribution to the total qubit decay rate is not fully understood. The presence of different layers of materials and interfaces makes it difficult to identify the dominant loss channels in present two-dimensional qubit designs. In this paper, we present the study that directly correlates measurements of RF losses in such films to material parameters by investigating a high-power impulse magnetron sputtered (HiPIMS) film atop a three-dimensional niobium superconducting radio frequency (SRF) resonator. By using a 3D SRF structure, we are able to isolate the niobium film loss …

Economic Material For Large-Scale H2 Storage And H2-Co2 Separation, Hussein R. Abid, Alireza Keshavarz, Header Jaffer, Basim K. Nile, Stefan Iglauer

Research outputs 2022 to 2026

Hydrogen is a clean fuel that can potentially completely decarbonize the energy supply chain and mitigate global warming. Hydrogen – a highly volatile gas – however, needs to be separated from CO2 during H2 production, and also from cushion gas in H2 geo-storage projects; in addition, large-scale H2 storage is a key obstacle. We thus tested and chemically upgraded common sub-bituminous coal as a material for H2-CO2 separation and H2 storage. The coal adsorbed significant amounts of H2 and CO2 and demonstrated an excellent H2-CO2 separation efficiency if chemically modified. The work presented here thus provides fundamental data required for …

Simulating Compatible Solute Biosynthesis Using A Metabolic Flux Model Of The Biomining Acidophile, Acidithiobacillus Ferrooxidans Atcc 23270, Himel N. Khaleque, Hadi Nazem-Bokaee, Yosephine Gumulya, Ross P. Carlson, Anna H. Kaksonen

Research outputs 2022 to 2026

Halotolerant, acidophilic, bioleaching microorganisms are crucial to biomining operations that utilize saline water. Compatible solutes play an important role in the adaptation of these microorganisms to saline environments. Acidithiobacillus ferrooxidans ATCC 23270, an iron- and sulfur-oxidizing acidophilic bacterium, synthesizes trehalose as its native compatible solute but is still sensitive to salinity. Recently, halotolerant bioleaching bacteria were found to use ectoine as their key compatible solute. Previously, bioleaching bacteria were recalcitrant to genetic manipulation; however, recent advancements in genetic tools and techniques allow successful genetic modification of A. ferrooxidans ATCC 23270. Therefore, this study aimed to test, in silico, the effect …

Pdf Malware Detection: Toward Machine Learning Modeling With Explainability Analysis, G. M.Sakhawat Hossain, Kaushik Deb, Helge Janicke, Iqbal H. Sarker

Research outputs 2022 to 2026

The Portable Document Format (PDF) is one of the most widely used file types, thus fraudsters insert harmful code into victims' PDF documents to compromise their equipment. Conventional solutions and identification techniques are often insufficient and may only partially prevent PDF malware because of their versatile character and excessive dependence on a certain typical feature set. The primary goal of this work is to detect PDF malware efficiently in order to alleviate the current difficulties. To accomplish the goal, we first develop a comprehensive dataset of 15958 PDF samples taking into account the non-malevolent, malicious, and evasive behaviors of the …

From Grain To Malt: Tracking Changes Of Ultra-Low-Gluten Barley Storage Proteins After Malting, Mahya Bahmani, Angéla Juhász, Utpal Bos, Mitchell G. Nye-Wood, Malcolm Blundell, Crispin A. Howitt, Michelle L. Colgrave

Research outputs 2022 to 2026

Barley (Hordeum vulgare L.) is a major cereal crop produced globally. Hordeins, the major storage proteins in barley, can trigger immune responses leading to celiac disease or symptoms associated with food allergy. Here, proteomics approaches were employed to investigate the proteome level changes of grain and malt from the malting barley cultivar, Sloop, and single-, double- and triple hordein-reduced lines. The triple hordein-reduced line is an ultra-low gluten barley cultivar, Kebari®. Using discovery proteomics, 2,688 and 3,034 proteins in the barley and malt samples were detected respectively. Through the application of targeted proteomics, a significant reduction in the quantity …

Modeling Apparent Pb Loss In Zircon U-Pb Geochronology, Glenn R. Sharman, Matthew A. Malkowski

Geosciences Faculty Publications and Presentations

The loss of radiogenic Pb from zircon is known to be a major factor that can cause inaccuracy in the U–Pb geochronological system; hence, there is a need to better characterize the distribution of Pb loss in natural samples. Treatment of zircon by chemical abrasion (CA) has become standard practice in isotope dilution–thermal ionization mass spectrometry (ID-TIMS), but CA is much less commonly employed prior to in situ analysis via laser ablation–inductively coupled plasma–mass spectrometry (LA-ICP-MS) or secondary ionization mass spectrometry (SIMS). Differentiating the effects of low levels of Pb loss in Phanerozoic zircon with relatively low-precision in situ U–Pb …

Extending Natural Mates In Euclidean 3-Space And Applications To Bertrand Pairs, Yun Myung Oh, Alexander Navarro

Faculty Publications

In Euclidean 3-space, a family of curves, the co-successor, is motivated and then introduced in relation to the natural mate. A complete characterization of co-successors is proved, followed by an application of the co-successor towards describing Bertrand curves and their mates.

Predictive Modeling Of Healthcare Traffic Using Machine Learning: A Comparative Study, Shadman Mahmood Khan Pathan, Sakan Binte Imran, M. M. Shabab Iqbal, Muhammad Enayetur Rahman, Md Nurul Absar Siddiky, Muhammad Rezaur Rahman, Md. Rafid Hassan, Nondon Lal Dey, Md. Sobuj Hossain

Electrical & Computer Engineering Faculty Publications

Effective healthcare traffic management is critical for ensuring prompt medical services, particularly in emergencies where delays can have life-threatening consequences. This study conducts a comparative analysis of three popular machine learning models—Linear Regression, Decision Trees, and Random Forests—for predicting healthcare-related traffic volumes. Utilizing a comprehensive dataset from a metropolitan interstate traffic system, the models were evaluated based on key performance metrics, including Mean Squared Error (MSE), R² Score, and execution time. The findings demonstrate that the Random Forest model outperforms the others, offering superior predictive accuracy and efficiency. These insights are valuable for optimizing traffic management in healthcare, ultimately contributing …

Foraging Economies: A Market Based Methodology For Robotic Swarm Foraging, John A. Little

Graduate Theses, Dissertations, and Problem Reports (ETD)

Swarm robotics involves coordinating large groups of autonomous agents to accomplish complex tasks through decentralized, adaptive behaviors, providing a robust and scalable approach suited to dynamic and unpredictable environments. While traditional swarm models frequently draw inspiration from biological systems such as ant colonies or bee foraging, other approaches use techniques from physics, control theory, and economics to achieve effective coordination. This study distinguishes itself by applying economic principles—specifically, market-driven mechanisms like auctions, utility functions based on opportunity cost, and supply-demand dynamics based on fluctuating resource values at a central base—to improve task allocation within a swarm foraging context. This approach …

Investigating Uncertainty In Gaussian Process Models, Wilson Strasilla

Master's Projects

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Investigation Of Deoxyfluorination Of Alkyl Alcohols Using Pentafluoropyridines Through A Covalent Intermediate, Christopher Allen Bias

Graduate Theses, Dissertations, and Problem Reports (ETD)

Organofluorines are an omnipresent class of organic molecules, especially in pharmaceuticals. Selective fluorination of drug molecules allows for the influence of properties including metabolic activity, solubility, and intrinsic potency. Deoxyfluorinations are typically performed via generation of nucleophilic fluoride from a deoxyfluorination agent. Traditionally, diethylaminosulfur trifluoride (DAST) is the reagent of choice for these reactions, and it remains a popular reagent today. However, it has a propensity to form elimination side products and explode. Several research groups have recently developed new classes of deoxyfluorination agents including imidazole-based reagents (PhenoFluor) and sulfonyl fluorides (PyFluor) that exhibit better functional group tolerance and much …

Machine Learning And Rna Bioinformatics, Jason Rafe Miller

Graduate Theses, Dissertations, and Problem Reports (ETD)

The applied science of bioinformatics encompasses computational analysis of molecular biology data. Advances in genomics and DNA sequencing technology have enabled computational analysis of ribonucleic acids (RNAs), which play diverse and critical roles in most cells. To assist the study of human RNA, we trained machine learning models on RNA nucleotide sequences, devoid of domain knowledge. We built models that distinguish long non-coding lncRNA from protein-coding mRNA, and models that predict the cytoplasmic vs. nuclear preferences of lncRNAs. In a review of published lncRNA subcellular localization classifiers, we show that the commonly used validation protocol generates optimistic performance measures, and …

Exploring Crystal Polymorphism In Additive-Assisted Chemical Vapor-Deposited Transition Metal Chalcogenides And Oxides, Lawrence Kirimi Mubwika

Graduate Theses, Dissertations, and Problem Reports (ETD)

Crystal polymorphism is a phenomenon in which compounds with the same chemical formula can be crystallized into different crystal structures. This phenomenon can be observed in elemental materials, such as diamond and graphite, as well as in compounds, such as the trigonal (1H) or octahedral (1T) prismatic MoS₂. Crystals can also exhibit polytypism by stacking different polymorphs in a certain order, with the stacking sequence determining the variation between polytypes. Although all polymorphs and polytypes have the same chemical composition, each polymorph and polytype possesses unique electronic and physical properties.

This study explores the additive-assisted chemical vapor deposition …

A Multi-Wavelength Determination Of The Total Luminosity And Star Formation Rate Of The Milky Way, Joshua L. Mascoop

Graduate Theses, Dissertations, and Problem Reports (ETD)

The star formation rate (SFR) of the Milky Way is poorly understood in comparison to the SFR of other galaxies. In order to better find the Galaxy's place in the universe, it is imperative to understand the star formation activity occurring within it. We characterize the Galactic \hii\ region luminosity function (LF) at multiple infrared and radio wavelengths using a sample of 797 first Galactic quadrant \hii regions compiled from the WISE Catalog of Galactic \hii Regions. This sample is statistically complete for all regions powered by single stars of type O9.5V and earlier.

We find that neither a single …