Digital Commons Network^™

Material Classification With Spectropolarimetric Lidar, Alexander J. Watson

Theses and Dissertations

A method for characterizing unknown targets using a hyperspectral polarimetric light detection and ranging (LiDAR) system is presented. Light reflected from manmade objects tends to be more polarized than light reflected from objects in the natural world. As such, polarization measurements can be used in remote sensing applications to differentiate artificial and natural objects. Previous works have attempted to characterize objects through passive polarimetric imagery. Methods developed by Cain and Lemaster and Cunningham facilitate reconstruction of the Stokes Vector from returning light. Martin used multispectral polarimetry to classify targets when the angle of incidence (AOI) is close to 0º. Here, …

Approximating Three-Body Trajectories With A Knot Theory Inspired Model For Orbit Generation And Determination, Mason R. Mill

Theses and Dissertations

This thesis explores a novel approach to approximating three-body trajectories using a knot theory-inspired model for orbit generation and determination. Traditional methods for solving the Circular Restricted Three-Body Problem (CR3BP) rely on numerical integration and correction schemes to generate trajectories, often requiring iterative refinements. This research investigates the application of knot theory principles—such as torus knots, Alexander polynomials, and Reidemeister moves—to categorize and model complex orbital trajectories in the CR3BP. By leveraging these mathematical tools, the study aims to enhance trajectory prediction, orbit determination, and mission planning for spacecraft operating in the cislunar environment. The results demonstrate that knot theory …

Increasing A-Type Co32− Substitution Decreases The Modulus Of Apatite Nanocrystals, Stephanie Wong, Abigail Eaton, Christina Krywka, Arun Nair, Christophe Drouet, Alix Deymier

Faculty Publications

Biological apatite mineral is highly substituted with carbonate (CO₃²⁻). CO₃²⁻ can exchange for either phosphate, known as B-type, or hydroxyl groups, known as A-type. Although the former has been extensively studied, A-type CO₃²⁻ substituted apatites are poorly understood. Therefore, A-type CO₃²⁻ apatites with biologically relevant levels of CO32− (1.7–5.8 wt%) were prepared and characterized. The addition of A-type CO₃²⁻ into the apatite structure caused the predicted expansion of the a-axis and contraction of the c-axis in the unit cell. This was accompanied by a significant modification in the atomic …

Image Forensics And Alteration Detection Using Image Preprocessing-Assisted Deep Learning Models, Rabindra Pokharel

Theses (2016-Present)

Technological advancements, combined with the widespread availability of digital images, have resulted in ubiquitous image forgery. The instances of forged images used for political propaganda, legal evidence manipulation, defamation of individuals, pornographic image creation of celebrities, and other actions that can cause social turmoil are proliferating. Verifying the integrity and authenticity of digital images is impractical for humans, necessitating the development of a robust image forgery detection model. This thesis demonstrates methods for copy-move, splicing, and deepfake image forgery detections by combining Error Level Analysis (ELA), Discrete Cosine Transformation (DCT), or Discrete Fourier Transformation (DFT) with a Deep Learning Convolutional …

Explainable Ai(Xai) In Genomic Medicine: Interpreting The Impact Of Genetic Variants On Breast Cancer Prognosis, Tooba Maryam Marith

Theses (2016-Present)

This study explores the integration of eXplainable Artificial Intelligence (XAI) techniques in genomic medicine to improve breast cancer prognosis and treatment decision-making. Using data from The Cancer Genome Atlas (TCGA), the research establishes a baseline through traditional machine learning (ML) models, including Random Forest (RF), Support Vector Classifier (SVC), Decision Tree, Naïve Bayes, K-Nearest Neighbors (KNN), and XGBoost. These models are evaluated for their predictive performance in assessing patient outcomes based on genetic variations. TCGA is a comprehensive public database that provides multidimensional genomic and clinical data for various cancer types, including breast cancer. It offers detailed molecular characterizations, such …

Evaluating The Health Performance Of Mass Housing Projects In Egypt Lighting Design Of Dar Masr Project, New Damietta, Hala Mohamed Raslan, Huda El-Baz M.

Mansoura Engineering Journal

The Egyptian government has recently established many governmental mass housing projects to meet the housing needs nationwide. These projects are characterized by their unified repetitive design that rarely consider geographic, climatic and social variations from one site to another. The study objectives are to examine the health performance of mass housing projects; “Dar Misr” as an example. Dar Misr consists of 150,000 units distributed over 15 different cities, and is fully finished with unified electrical installations and preinstalled luminaires. The study examines the health performance of the project’s lighting design, both natural and electrical light, using the “WELLV2 rating system …

Flow Dynamics Of Agricultural Waste Nanofibers: Shear, Temperature, And Oscillatory Insights, Bilge N. Altay, Burak Aksoy, James Atkinson, Christopher Lewis, Carlos Diaz-Acosta, Raymond Francis

Articles

The rheology and fiber size of corn stover (CS) and cleaned cotton gin trash (CGT) cellulose nanofibers (CNFs) were studied including behaviors at both moderate and extremely high shear rates, to simulate industrial processes ranging from mixing and pumping to high-speed coating, printing, and extrusion. Particle size analyzer showed that 99% of CS fibers measured around 226 nm, while 85% of CGT fibers were approximately 143 nm. Both CS and CGT CNFs formed gel-like suspensions, and shear flow tests revealed that all samples exhibited shear-thinning behavior, allowing easy flow under shear forces. Gels with higher solid content (1%) demonstrated extended …

A Novel Preprocessing Model For Multi Modal Brain Mri Image Classification For Stroke Prognosis, Alwin Joseph, Chandra J

Northeast Journal of Complex Systems (NEJCS)

Magnetic Resonance Imaging (MRI) is an imaging technique used for the diagnosis and observing the progression in various neurological disorders. Stroke is one of the prominent neurological disorders that creates significant impacts in the patients. It occurs when the blood supply to part of the brain is interrupted or reduced, preventing brain tissues from getting oxygen and nutrients. Multimodal data from various modalities help clinicians in proper prognosis of stroke. Ischemic Stroke Lesion Segmentation Challenge (ISLES22) provides data of stroke data for various stroke patients, the dataset consists of three modalities of data – Fluid Attenuated Inversion Recovery (FLAIR), Apparent …

A Comparative Mathematical Analysis Of Ice Modulation Measurement Techniques: Unifying Thermal Hysteresis, Freezing Point Depression, And Colligative Effects, Hayden Calvert Barry

Engineering Undergraduate Senior Theses

Thermal hysteresis (TH) measurement techniques for ice binding proteins (IBPs) have historically lacked standardization, making cross-study comparisons challenging and potentially impeding development of these materials for practical applications. This study provides a comprehensive comparison of three measurement techniques: differential scanning calorimetry (DSC), microlitre osmometry, and cryostage microscopy. Through systematic experimentation with Wild Type III Antifreeze Protein (AFP) at varying concentrations (10μM, 100μM, 1mM), along with cell lysate AFP and Pseudomonas syringe ice nucleating protein (INP), mathematical relationships were established between measurement techniques, and cryostage microscopy was identified as the most reproducible and reliable method. Regression analysis revealed strong relationships between …

Self-Thickening Materials Derived From Phenylpropanoid Ene Reactions, Atanu Biswas, Huai N. Cheng, Bret Chisholm, Ryan Beni, Zengshe Liu, Karl Vermillion, Michael Appell, Kelton Forson, Omar El Seoud, Carlucio R. Alves, Roselayne F. Furtado

Chemistry Faculty Research

In this work, we report the observation of uncatalyzed ene reactions between several phenylpropanoid compounds and diethyl azodicarboxylate (DEAD). For allylbenzene, the reaction produces the ene product at molar ratios of up to 1:2 of allylbenzene to DEAD. At higher levels of DEAD, more complex reactions are observed. For the reaction between methyl eugenol and DEAD, similar ene reaction products have been found. However, the reaction of eugenol with DEAD is more complex; in addition to the ene reaction, other reactions happen at the same time. Most of the structures of the resulting products have been elucidated using NMR spectroscopy …

There May Be A Safer Treatment Against A Virus That Can Cause Birth Defects And Hearing Loss, Kade Robison

Research on Capitol Hill

CMV is the leading cause of non-genetic birth defects and hearing loss.

Hagfish Protein Models Of Heart Tissue Reveal Processes Of Diabetes, Maelyn Andreasen

Research on Capitol Hill

Diabetic cardiomyopathy impairs and damages heart tissue through chronic exposure to hyperglycemia, or high blood sugar, in diabetic individuals. 

Studying the disease in heart tissue is difficult, so we set out to create a three-dimensional heart model that we can study under these hyperglycemic conditions.

Genetic Engineering In Alpacas May Unlock Cures For Currently Incurable Human Disease, James Cisneros

Research on Capitol Hill

We aimed to establish laparoscopic ovum pickup (L-OPU) techniques in alpaca to retrieve oocytes for in vitro maturation and fertilization. Our project successfully retrieved and matured alpaca oocytes in vitro, a crucial step toward genetic engineering. Next, we will apply CRISPR-Cas9 to deactivate the IGM gene in fertilized embryos, aiming to enhance HCAb production. This will lay the foundation for humanizing these antibodies, making them viable for therapeutic use in human medicine.

Zno Nanowires For Biosensing Applications, G.M. Mehedi Hossain, Daniel Garza, Emilio Chavez, Ahmed Hasnain Jalal, Fahmida Alam

Electrical and Computer Engineering Faculty Publications

Zinc oxide Nanowires (ZnO-NWs) are promising biosensor materials and hold the key to overcoming challenges in the field. This chapter provides an introductory overview of biosensing technology, focusing on the fundamental principles and comparing ZnO-NWs with other nanostructures regarding the surface area, reactivity, electrical properties, charge transport behavior, optical, magnetic, and piezoelectric properties, and mechanical flexibility. Providing the synthesis and characterization methods, ZnO-NWs’ biosensing processes are also elaborated on surface modification for selectivity, integration with microfluidic systems, enhancing signal transduction, and connecting with biological elements like enzymes, antibodies, and DNA. The chapter also discusses the applications of ZnO-NWs-based biosensors in …

Predicting The Indirect Cost Of Construction Projects In Egypt: An Artificial Neural Network Approach, Aya Effat

Theses and Dissertations

Cost estimation is one of the vital processes in construction management that needs to be done early in any project in order to determine the project's budget. The accuracy of the cost estimate is a key factor in the success of construction projects since it enables project managers to successfully control the project’s expenses. Construction costs mainly consist of direct cost and indirect cost. Generally, indirect costs can be categorized into two types: site overheads and general overheads. In a construction project, overheads, particularly site overhead costs, make up a considerable portion of a contractor's budget. Accordingly, accurately estimating the …

Interfacial Phenomena In Molten Salt Systems And Wetting Transitions In Microcavities, Aaron Essilfie

Theses and Dissertations

Interfacial phenomena are the processes that occur at the interface between two phases of matter: solid-liquid, solid-gas, liquid-liquid, and liquid-gas. Wetting, spreading, adsorption, and capillarity are some features of interfacial phenomena. This research explores two areas of interfacial phenomena: the interfacial tension between a liquid and gas, and wetting transitions in microcavities. Surface tension has been a widely studied topic in surface chemistry. Many techniques have been employed to study the surface tension of liquids in various studies and research areas, but the interfacial tension between a liquid and gas has not been extensively researched. For this reason, part of …

Change Detection Analysis Using Remote Sensing And Gis Approaches For Lake Manzala, Egypt, Mohamed Eraki, Rasha Abd El Ghany, Sameh El Kafrawy, Mostafa Rabah

Mansoura Engineering Journal

Manzala Lake, the largest natural freshwater body in Egypt, is situated in the northeastern part of the Nile Delta. It faces major environmental challenges, largely due to pollution from untreated industrial effluents, sewage, and agricultural runoff. As part of Egypt's national initiative to rehabilitate its lakes, a development project was launched in 2017 and concluded in June 2022. The project aimed to purify the lake by eliminating contaminants, clearing invasive vegetation, deepening the canals, the study focuses on assessing land cover changes using remote sensing and GIS, and offers some recommendations for sustainable lake use following the development efforts. The …

Recent Developments In Heterologous Expression Of Cellulases Using The Pichia Pastoris Expression System: A Comprehensive Literature Review, Nazish Muzaffar, Abdur Raziq, Muhammad Waseem Khan, Niaz Muhammad Khan, Bushra Shahid, Anbareen Gul, Hayat Ullah

Biological Engineering Student Research

Cellulosic biomass is considered an important and sustainable source of renewable energy, which needs a complex mixture of different enzymes for its degradation. After amylase, cellulases are the second most important enzymes, gain more importance due to their broad range of applications at the industrial level, and are considered more economical and environmentally friendly; researchers have focused more on the production of cellulase with its higher expression rate and low cost. Pichia pastoris, a methylotrophic yeast strain, has a more effective and well-established system for the production of heterologous proteins, particularly for industrial enzymes. Moreover, its readily achievable high-density …

Few-Shot Transfer Learning For Individualized Braking Intent Detection On Neuromorphic Hardware, Nathan A. Lutes, V. Sriram Siddhardth Nedendla, K. Krishnamurthy

Mechanical and Aerospace Engineering Faculty Research & Creative Works

This work explores use of a few-shot transfer learning method to train and implement a convolutional spiking neural network (CSNN) on a Brain Chip Akida AKD1000 neuromorphic system-on-chip for developing individual-level, instead of traditionally used group-level, models using electroencephalographic data. The efficacy of the method is studied on an advanced driver assist system related task of predicting braking intention. Approach. Data are collected from participants operating an NVIDIA JetBot on a testbed simulating urban streets for three different scenarios. Participants receive a braking indicator in the form of: (1) an audio countdown in a nominal baseline, stress-free environment; (2) an …

An Algorithm For Cloud-Based Web Service Combination Optimization Through Plant Growth Simulation, Qiang Li, Huawei Qin, Bingqin Qiao, Ruifang Wu

Journal of System Simulation

Abstract: In order to improve the efficiency of cloud-based web services, an improved plant growth simulation algorithm scheduling model. This model first used mathematical methods to describe the relationships between cloud-based web services and the constraints of system resources. Then, a lightinduced plant growth simulation algorithm was established. The performance of the algorithm was compared through several plant types, and the best plant model was selected as the setting for the system. Experimental results show that when the number of test cloud-based web services reaches 2 048, the model being 2.14 times faster than PSO, 2.8 times faster than the …

Super-Resolution Imaging Reveals Resistance To Mass Transfer In Functionalized Stationary Phases, Ricardo Monge Neria, Muhammad Zeeshan, Aman Kapoor, Tae Kyong John Kim, Nichole Hoven, Jeffrey Pigott, Burcu Gurkan, Christine Duval, Lydia Kisley

Faculty Scholarship

Chemical separations are costly in terms of energy, time, and money. Separation methods are optimized with inefficient trial-and-error approaches that lack insight into the molecular dynamics that lead to the success or failure of a separation and, hence, ways to improve the process. We perform super-resolution imaging of fluorescent analytes in five different commercial liquid chromatography materials. Unexpectedly, we observe that chemical functionalization can block more than 50% of the material’s porous interior, rendering it inaccessible to small-molecule analytes. Only in situ imaging unveils the inaccessibility when compared to the industry-accepted ex situ characterization methods. Selectively removing some of the …

The Efficacy Of Utilizing Artificial Intelligence Techniques In Developing Critical Thinking In Mathematics Among Secondary School Students And Their Attitudes Toward It, Mohammad A. Tashtoush, Aida B. Qasimi, Nawal H. Shirawia, Lubna A. Hussein

Iraqi Journal for Computer Science and Mathematics

The aim of this study is to investigate the efficacy of Artificial Intelligence (AI) techniques and programs in developing Critical Thinking Skills (CTSs) in mathematics among secondary school students, as well as their attitudes towards it. This study employed an experimental methodology, which was applied to a sample of 91 students. A critical thinking test and a scale to measure students' Attitudes Towards Mathematics (ATM) were also utilized. This study revealed significant improvements in the mean scores of critical thinking skills among secondary students who were exposed to Artificial Intelligence Techniques (AITs), particularly in deduction, interpretation, inference, and evaluation. Additionally, …

Email Spam Classification Based On Deep Learning Methods: A Review, Ekramul Haque Tusher, Mohd Arfian Ismail, Anis Farihan Mat Raffei

Iraqi Journal for Computer Science and Mathematics

Email spam is a significant issue confronting both email consumers and providers. The evolution of spam filtering has progressed considerably, transitioning from basic rule-based filters to more sophisticated machine learning algorithms. Deep learning has become a potent collection of techniques for addressing intricate issues such as spam classification in recent times. A thorough literature evaluation is required to have a comprehensive overview of the current research on utilizing deep learning methods for email spam classification. This review aims to identify the various deep learning techniques used for email spam, their effectiveness, and areas for future research. By synthesizing the outcomes …

Trpv4 Dominates High Shear-Induced Initial Traction Response And Long-Term Relaxation Over Piezo1, Mohanish Chandurkar, Manli Yang, Majid Rostami, Sangyoon J. Han

Michigan Tech Publications

Modulation of endothelial traction is critical for the responses of endothelial cells to fluid shear stress (FSS), which has profound implications for vascular health and atherosclerosis. Previously, we demonstrated that under high FSS, endothelial cells rapidly increase traction forces, followed by relaxation, with traction aligning in the flow direction. In contrast, low shear preconditioning induces a modest short-term increase in traction (min), followed by a secondary long-term (>14 hr) rise, with traction/cells aligning perpendicular to the flow. The upstream mechanosensors driving these responses, however, remain unknown. Here, we sought the roles of Piezo1 and TRPV4 ion channels in shear-induced …

Multimodal Search On A Line, Jared Coleman, Dmitry Ivanov, Evangelos Kranakis, Danny Krizanc, Oscar Morales Ponce

Computer Science Faculty Works

Inspired by the diverse set of technologies used in underground object detection and imaging, we introduce a novel multimodal linear search problem whereby a single searcher starts at the origin and must find a target that can only be detected when the searcher moves through its location using the correct of p possible search modes. The target’s location, its distance d from the origin, and the correct search mode are all initially unknown to the searcher. We prove tight upper and lower bounds on the competitive ratio for this problem. Specifically, we show that when p is odd, the optimal …

Structural Features And Morphology Of Biodegradable Composites Based On Polylactide And Corn Starch, Eygeniy N. Poddenezhny, Andrei A. Boiko, Ekaterina E. Trusova, Viktor M. Shapovalov

CHEMISTRY AND CHEMICAL ENGINEERING

The aim of the work was to study the morphology and structural features of biodegradable composites based on polylactide, filled with corn starch formed by extrusion method. The characteristics of the obtained materials were investigated by scanning electron microscopy, X-ray diffraction, IR spectroscopy. It was established that the presence of polyethylene glycol PEG–4000 as a plasticizer and surfactant – glycerin monostearate in the initial mixture leads to the formation of a nonporous heterogeneous system, in which starch particles are statistically distributed in the matrix. The starch concentration in the composite varied from 20 to 55 wt. %. When the starch …

Retracted: A Review Of Breast Cancer Histological Image Classification: Challenges And Limitations, Israa Faisal Jassam, Abdulrahman Abbas Mukhlif, Ahmed Adil Nafea, Mustafa Adnan Tharthar, Ahmed Isam Khudhair

Iraqi Journal for Computer Science and Mathematics

This paper comprehensively reviews the classification of breast cancer histological images. The paper discusses the research objectives, methodologies used, and conclusions drawn, as well as suggestions for the future. The study is based on the ICIAR 2018 database, which is considered one of the largest databases available to support this research. The paper also addresses major challenges such as lack of data, variation in tissue preparation, class imbalance, and computational requirements. Advanced techniques such as deep learning (DL), transfer learning and data augmentation are explored, along with innovative models such as convolutional neural networks (CNNs) and generative adversarial networks (GANs). …

Streamlined Production, Protection, And Purification Of Enzyme Biocatalysts Using Virus-Like Particles And A Cell-Free Protein Synthesis System, Seung O. Yang, Joseph P. Talley, Gregory H. Nielsen, Kristen M. Wilding, Bradley Charles Bundy

Faculty Publications

Enzymes play an essential role in many different industries; however, their operating conditions are limited due to the loss of enzyme activity in the presence of proteases and at temperatures significantly above physiological conditions. One way to improve the stability of these enzymes against high temperatures and proteases is to encapsulate them in protective shells or virus-like particles. This work presents a streamlined, three-step, cell-free protein synthesis (CFPS) procedure that enables rapid in vitro enzyme production, targeted encapsulation in protective virus-like particles (VLPs), and facile purification using a 6× His-tag fused to the VLP coat protein. This process is performed …

A Geomatic Appraisal On Restoration Of Tank Cascade Systems In Ambuliyar Watershed, Tamilnadu, Nasir N

Theses and Dissertations

Tanks and earthen embankments used for water harvesting and storage have been a significant part of India's irrigation system since the 2nd and 3rd centuries. In Tamil Nadu, around 39,202 tanks have storage capacities of around 178.94 million cubic feet. However, they have been impacted by natural and anthropogenic threats such as soil erosion, siltation, inadequate rainfall, and drought. This study aims to determine the current storage capacity of tanks, estimate the loss in storage capacity/volume of silt, estimate the rate of siltation and life of tanks, identify soil erosion-prone zones, and map deteriorating parameters along supply channels.

The study …

A Review On Exploring Artificial Intelligence Applications, Advancements, Issues, And Future Challenges, Sajid Naeem, Novman Nabeel, Waseem Beg, Shujaat Ali, Rajiv N. Kanojiya, Satish S. Mandawade, Chetan R. Yewale, Sc Kulkarni, Vt Salunke, Av Patil

Polytechnic Journal

Artificial intelligence (AI) is a transformative technology with diverse applications that is transforming several industries. AI is the use of systems and technology to replicate human intelligence and solve common real-world issues. Machine learning (ML) and deep learning are AI technologies that use algorithms to more accurately predict occurrences without the need for human intervention. Explainable Artificial Intelligence (XAI) refers to AI that can explain decisions or forecasts to human users. XAI seeks to improve AI systems' transparency, trustworthiness, and accountability, particularly when utilized in high-risk applications such as healthcare, finance, or security. This review article provides a thorough overview …