Physical Sciences and Mathematics Commons^™

Advancing Iot Security Through Blockchain-Based Decentralized Platform And Ai-Powered Digital Forensics, Ruipeng Zhang

Masters Theses and Doctoral Dissertations

The proliferation of Internet of Things (IoT) devices, from smartphones, smart thermostats to smart home security systems, is revolutionizing our society and daily lives. However, it also has posed significant challenges to IoT security and forensics. To tackle those challenges, innovative solutions are designed to enhancing IoT security and accelerating investigation of cybersecurity incidents by leveraging recent technological advancements in Blockchain and Artificial Intelligence (AI). First, an IoT service platform, called DISP, is proposed to improve the security and interoperability of IoT systems. DISP utilizes the consortium blockchain technology to transform centralized, insecure IoT communications into decentralized, secure, and traceable …

Numerical Evaluation Of Wavenumbers Of The Acoustic Waves Propagating In An Ice-Covered Ocean, Mohammad Khan

Masters Theses and Doctoral Dissertations

We consider acoustic wave propagation in a layered ocean waveguide covered by thick ice. The standard method of separation of variables leads to a Sturm-Liouville problem in the crosssection of the waveguide. We are specifically interested in the two leading modes, the separated solutions for the maximal eigenvalues. We first consider the homogeneous waveguide. We prove the differentiability of the eigenvalues with respect to the frequency, the monotonicity of the eigenvalues with respect to the frequency, and the existence of the cut-off frequency. We compare these eigenvalues with the eigenvalues for the case of a waveguide with a free surface. …

A Comprehensive Review On Machine Learning In Healthcare Industry: Classification, Restrictions, Opportunities And Challenges, Qi An, Saifur Rahman, Jingwen Zhou, James Jin Kang

Research outputs 2022 to 2026

Recently, various sophisticated methods, including machine learning and artificial intelligence, have been employed to examine health-related data. Medical professionals are acquiring enhanced diagnostic and treatment abilities by utilizing machine learning applications in the healthcare domain. Medical data have been used by many researchers to detect diseases and identify patterns. In the current literature, there are very few studies that address machine learning algorithms to improve healthcare data accuracy and efficiency. We examined the effectiveness of machine learning algorithms in improving time series healthcare metrics for heart rate data transmission (accuracy and efficiency). In this paper, we reviewed several machine learning …

Design And Synthesis Of Peripherally Selective Endocannabinoid Enzyme Inhibitors For Ocular Indications, Kezia Reji Thomas

Senior Honors Theses

Peripherally selective compounds have been found to stimulate endocannabinoid receptor activity, which has been observed to have positive physiological effects such as ocular wound healing and inflammation control. The activation of the cannabinoid 1 receptor via binding of the endogenous ligands, anandamide and 2-arachidonoylglycerol, has been indicated to elicit these effects. Both ligands are controlled by two hydrolase enzymes, fatty acid amide hydrolase (FAAH) and monoacylglycerol lipase (MAGL), which can be targeted for therapeutic inhibition. Sulfonamide derivatives of JZL195 containing carbamate functionalities in the southern region of the inhibitor compounds were produced using novel carbamate exchange reactions. Polar functionalities were …

Small But Mighty: Examing The Utility Of Microstatistics In Modeling Ice Hockey, Matt Palmer

Senior Honors Theses

As research into hockey analytics continues, an increasing number of metrics are being introduced into the knowledge base of the field, creating a need to determine whether various stats are useful or simply add noise to the discussion. This paper examines microstatistics – manually tracked metrics which go beyond the NHL’s publicly released stats – both through the lens of meta-analytics (which attempt to objectively assess how useful a metric is) and modeling game probabilities. Results show that while there is certainly room for improvement in understanding and use of microstats in modeling, the metrics overall represent an area of …

Effect On Focusing Fields By Ferromagnetic Cell Cores In Linear Induction Accelerators, Cooper Guillaume

Senior Honors Theses

In the Los Alamos National Laboratories DARHT facility, there are two perpendicular linear induction accelerators, LIAs. The LIAs’ solenoids produce magnetic fields which focus the electron beam. Simultaneously, the accelerating pulse creates a magnetic field. These two field intensities act upon a ferromagnetic material in the cells to enhance magnetic flux density. Due to the nonlinearity of the material, this flux density will reach a saturation point. In turn, the magnetic field intensity of the axial solenoidal magnetic field will be affected and slightly altered. The width of the electron beam will increase, causing a decrease in effectiveness. Through simulation, …

An Exploration Of The Application Of Desalination In Disaster Relief, Emma Sager

Senior Honors Theses

This paper aims to explore the application of small-scale desalination systems to provide clean water in the wake of marine natural disasters. A lack of clean water is a devastating impact of many natural disasters. Desalination technologies, both thermal and membrane, show potential for being scaled down and self-powered by renewable energy. Desalination can transform ocean water and contaminated drinking water with a high salt content into drinkable, usable water. While these techniques are not perfected, and the solution to a need for clean water is multifaceted, desalination shows potential. Through further research and ever-advancing technology, small-scale desalination could develop …

Rattus Norvegicus As A Biological Detector Of Clandestine Remains And The Use Of Ultrasonic Vocalizations As A Locating Mechanism, Gabrielle M. Johnston

Master's Theses

In investigations, locating missing persons and clandestine remains are imperative. One way that first responder and police agencies can search for the remains is by using cadaver dogs as biological detectors. Cadaver dogs are typically used due to their olfactory sensitivity and ability to detect low concentrations of volatile organic compounds produced by biological remains. Cadaver dogs are typically chosen for their stamina, agility, and olfactory sensitivity. However, what is not taken into account often is the size of the animal and the expense of maintaining and training the animal. Cadaver dogs are typically large breeds that cannot fit in …

Phylogeny And Taxonomy Of Himerometroidea (Echinodermata: Crinoidea), Kristian H. Taylor, Gregory W. Rouse, Charles G. Messing

Marine & Environmental Sciences Faculty Articles

Himerometroidea is a clade of chiefly shallow-water, tropical, feather-star crinoids that is currently divided, based on morphology, into four families comprising 119 extant species in 31 genera. Our molecular phylogenetic results, based on three mitochondrial (CO1, 16S, CytB) and two nuclear (ITS and 28S) markers for 55 accepted species in 23 of the extant genera, allow for six clades within Himerometroidea to be given family ranks. Maximum parsimony, maximum likelihood, and Bayesian inference analyses recovered largely congruent topologies with varying nodal support. A new classification revises generic placements among five families: Himerometridae, Colobometridae, and Mariametridae, all retained, and Pontiometridae and …

Building Community Resiliency Against Disasters, Zachary L. Doering

Undergraduate Honors Thesis Collection

Disasters impact people in many different places around the world. The impact to communities by disasters is shaped by their constructed vulnerability. The goal of this research project was to better understand how the vulnerability and resiliency of different communities was shaped at six different sites across the U.S. and to construct a collection of best practices to raise the resiliency of populations and locations in the face of many different forms of possible disasters in the future. These concepts and conclusions were drawn from internet research of the chosen sites. Phase 1 of the research determined noteworthy sites and …

Brif: A Novel And Efficient Implementation Of Random Forests Based On Bit Packing And Parallel Computing, Yanchao Liu

Industrial and Systems Engineering Faculty Research Publications

Random forests are powerful and popular machine learning methods. While general principles of tree induction are straightforward and well-understood, the numerous algorithmic treatments implemented in software tools, as well as their impacts on performance, are less familiar to most users. This paper introduces a new random forest toolkit (the ‘brif’ package in R and Python) along with its key algorithmic design features, and demonstrates the effects of the forest’s hyper-parameters such as the split search method, tree depth and the voting mechanism, on the classification performance. Summaries of benchmarking experiments are also presented. Results show that ‘brif’ stands out among …

Novel Pathways To Tailor Charge And Spin In Materials And Investigating The Impact On Sensing And Electrochemical Energy Applications, Aruna Narayanan Nair

Open Access Theses & Dissertations

Catalysis is integral to our daily lives, as it streamlines and accelerates numerous chemical reactions essential for producing various materials, fuels, and chemicals. With the rising demand for clean, sustainable energy sources, optimizing catalytic materials and processes becomes increasingly vital. In the realm of renewable energy production, catalysis is crucial for efficiently converting energy from sustainable resources, such as solar, wind, and biomass, into chemical energy stored in fuels or directly into electrical energy.The electronic charge distribution in materials significantly influences their physical and chemical properties, facilitating the development of advanced electronic, optoelectronic, sensing, and energy conversion devices. Since catalysis …

Intrinsic Tame Filling Functions And Other Refinements Of Diameter Functions, Andrew Quaisley

Department of Mathematics: Dissertations, Theses, and Student Research

Tame filling functions are quasi-isometry invariants that are refinements of the diameter function of a group. Although tame filling functions were defined in part to provide a proper refinement of the diameter function, we show that every finite presentation of a group has an intrinsic tame filling function that is equivalent to its intrinsic diameter function. We then introduce some alternative filling functions—based on concepts similar to those used to define intrinsic tame filling functions—that are potential proper refinements of the intrinsic diameter function.

Adviser: Susan Hermiller and Mark Brittenham

Trace Dna Detection Using Diamond Dye: A Recovery Technique To Yield More Dna, Leah Davis

Master's Theses

This study aspires to find a new screening approach to trace DNA recovery techniques to yield a higher quantity of trace DNA from larger items of evidence. It takes the path of visualizing trace DNA on items of evidence with potential DNA so analysts can swab a more localized area rather than attempting to recover trace DNA through the general swabbing technique currently used for trace DNA recovery. The first and second parts consisted of observing trace DNA interaction with Diamond Dye on porous and non-porous surfaces.

The third part involved applying the Diamond Dye solution by spraying it onto …

Program And Proceedings: Nebraska Academy Of Sciences 1880–2023, 143rd Anniversary Year, One Hundred-Thirty-Third Annual Meeting, April 21, 2023

Nebraska Academy of Sciences: Programs and Proceedings

Program

Aeronautics and Space Science

Humans Past and Present

Applied Science and Technology Section

Biology

Biomedical Sciences

Chemistry

Earth Sciences

Environmental Science

Physics

Science Education

2023 Maiben Lecture: Jason Bartz

2023 Friend of Science Award: Ray Ward and Jim Lewis

The Full Degree Spanning Tree Problem, Sarah Acquaviva

Theses, Dissertations and Culminating Projects

Given a graph G, we study the problem of finding a spanning tree T that maximizes the number of vertices of full degree; that is, the number of vertices whose degree in T equals its degree in G. We prove a few general bounds and then analyze this parameter on various classes of graphs including grid graphs, hypercubes, and random regular graphs. We also explore a related problem that focuses on maximizing the number of leaves in a spanning tree of a graph.

Studies Of The Reaction Of Rongalite With Epoxides, Anuj Aryal

Theses, Dissertations and Culminating Projects

Reactions between Rongalite (Na⁺O^-SOCH₂OH) and epoxides were studied with the aim of developing new synthetic routes for the procurement of sulfone diols. This class of compounds contains essential building blocks in the construction of sulfur heterocycles, which have been implied in the development of several medicinal compounds. Thus far, the desired diols have not been isolated. During control experiments with bromo alcohols, an unknown product was isolated but remains to be identified.

Dynamics Of Inertial And Non-Inertial Particles In Geophysical Flows, Nishanta Baral

Theses, Dissertations and Culminating Projects

We consider the dynamics of inertial and non-inertial particles in various flows. We investigate the underlying structures of the flow field by examining their Lagrangian coherent structures (LCS), which are found by computing finitetime Lyapunov exponents (FTLE). We compare the behavior of massless noninertial particles using the velocity fields from four models, the Duffing oscillator, the Bickley jet, the double-gyre flow, and a quasi-geostrophic geophysical flow model, with that of inertial particles. For inertial particles with finite size and mass, we use the Maxey-Riley equation to describe the particle’s motion. We explore the preferential aggregation of inertial particles and demonstrate …

Curriculum Connectivity In Montclair State University’S Undergraduate Mathematics Program, Ana G. Da Silva Jesus

Theses, Dissertations and Culminating Projects

According to Piaget’s cognitive development theory and the constructivism learning theory of education, real learning occurs when students establish long term connections between disciplines by either adapting or redefining previously acquired knowledge. These ideologies have important teaching and learning implications that directly influence curriculum development and the design of a course of study. This thesis explores the interconnectedness of the subjects required for the successful completion of an undergraduate math program at Montclair State University. More specifically, it models students’ unique connections through a learning network and investigates the correlation between the interconnectivity of subjects and students’ overall performance. Results …

The Construction Of A Static Source Code Scanner Focused On Sql Injection Vulnerabilties In Java, Carla Zurita Rubin De Celis

Theses, Dissertations and Culminating Projects

SQL injection attacks are a significant threat to web application security, allowing attackers to execute arbitrary SQL commands and gain unauthorized access to sensitive data. Static source code analysis is a widely used technique to identify security vulnerabilities in software, including SQL injection attacks. However, existing static source code scanners often produce false positives and require a high level of expertise to use effectively. This thesis presents the design and implementation of a static source code scanner for SQL injection vulnerabilities in Java queries. The scanner uses a combination of pattern matching and data flow analysis to detect SQL injection …

Evaluating And Improving Snow Prediction In The National Water Model In New York State Using New York State Mesonet Data, Sierra Liotta

Atmospheric & Environmental Sciences

When snow melts, the water drains into nearby streams and rivers which can impact water supply and flood hazards. The National Water Model (NWM) provides high quality forecast data for streamflow in the continental United States using mathematical representations of hydrologic processes. This research evaluates how the land surface model (LSM), Noah-MP, in the NWM simulates snowpack and snowmelt in New York State. To evaluate the representation of snow melt in Noah-MP, we examine point simulations at the New York State Mesonet (NYSM) sites where Noah-MP is forced by NYSM meteorological observations to avoid biases in the meteorological input and …

Investigating The Difference Between Members In The High-Resolution Rapid Refresh Ensemble (Hrrre) During The February 23rd, 2022 Winter Storm, Michael Barletta

Atmospheric & Environmental Sciences

Probabilistic forecasting is one tool that is being used to help create more accurate and understandable forecasts. Using percentages and probabilities allows for more depth to a forecast and allows forecasters to be able to convey a clearer message of what exactly they are expecting. Ensembles are a set of forecast models that have either different starting conditions, boundary conditions or parameter settings. They are one way of creating probabilistic forecasts and can help in the understanding of the likelihood of a specific outcome. Forecasters use ensembles to attempt to analyze the range of possible outcomes and the likelihood of …

Subterraneans: A Regional Earth Dwelling For Comfort And Beauty, Isaak Benchoff

Architecture Undergraduate Honors Theses

Subterraneans is a study of an affordable, self-sufficient, sustainable, and dignified housing prototype for the region of Northwest Arkansas. It is a design process investigation based on the ideas of turning a local, sustainable material into affordable homes that can be built within a community of people sharing land and resources. The homes would utilize as many natural materials as possible to minimize the impact on the Earth and the cost to the owners.

Research looked at many different vernacular building precedents as well as the work done by contemporary design firms in the area of economical, low-impact, and passively …

Task Offloading And Resource Allocation Based On Dl-Ga In Mobile Edge Computing, Hang Gu, Minjuan Zhang, Wenzao Li, Yuwen Pan

Turkish Journal of Electrical Engineering and Computer Sciences

With the rapid development of 5G and the Internet of Things (IoT), the traditional cloud computing architecture struggle to support the booming computation-intensive and latency-sensitive applications. Mobile edge computing (MEC) has emerged as a solution which enables abundant IoT tasks to be offloaded to edge services. However, task offloading and resource allocation remain challenges in MEC framework. In this paper, we add the total number of offloaded tasks to the optimization objective and apply algorithm called Deep Learning Trained by Genetic Algorithm (DL-GA) to maximize the value function, which is defined as a weighted sum of energy consumption, latency, and …

Breath Analysis For Detection Of Lung Cancer With Hybrid Sensor-Based Electronic Nose, Ümi̇t Özsandikcioğlu, Ayten Atasoy

Turkish Journal of Electrical Engineering and Computer Sciences

Lung cancer has the highest death rates among all types of cancer worldwide. Detection of lung cancer in its early stages significantly increases the survival rate. In this study, the aim is to improve the lung cancer detection performance of electronic noses (e-noses) with breath analysis by using two different types of gas sensor-based e-nose. The developed e-nose system consists of 14 quartz crystal microbalance (QCM) sensors and 8 metal oxide semiconductor (MOS) sensors. Breath samples were collected from a total of 100 volunteers, including 60 patients with lung cancer, 20 healthy nonsmokers, and 20 healthy smokers, and were classified …

Integration Of Neural Network And Distance Relay To Improve The Fault Localization On Transmission Lines, Linh Tran

Turkish Journal of Electrical Engineering and Computer Sciences

Power transmission lines are integral and very important components of power systems. Because of the length of these lines and the complexity of the power grids, the lines may encounter various incidents such as lightning strike, shortage, and breakage. When an incident or a fault occurs, a fast process of identification, localization, and isolation of the fault is desired. An accurate fault localization would have a great impact in reducing the restoration time of the system. One of the most popular solutions for fault detection and localization is the distance relays using the impedance-based algorithms. However, these relays are still …

Quadratic Programming Based Partitioning For Block Cimmino With Correct Value Representation, Zuhal Taş, Fahreddi̇n Şükrü Torun

Turkish Journal of Electrical Engineering and Computer Sciences

The block Cimmino method is successfully used for the parallel solution of large linear systems of equations due to its amenability to parallel processing. Since the convergence rate of block Cimmino depends on the orthogonality between the row blocks, advanced partitioning methods are used for faster convergence. In this work, we propose a new partitioning method that is superior to the state-of-the-art partitioning method, GRIP, in several ways. Firstly, our proposed method exploits the Mongoose partitioning library which can outperform the state-of-the-art methods by combining the advantages of classical combinatoric methods and continuous quadratic programming formulations. Secondly, the proposed method …

Unbiased Federated Learning In Energy Harvesting Error-Prone Channels, Zeynep Çakir, Eli̇f Tuğçe Ceran Arslan

Turkish Journal of Electrical Engineering and Computer Sciences

Federated learning (FL) is a communication-efficient and privacy-preserving learning technique for collaborative training of machine learning models on vast amounts of data produced and stored locally on the distributed users. This paper investigates unbiased FL methods that achieve a similar convergence as state-of-the-art methods in scenarios with various constraints like an error-prone channel or intermittent energy availability. For this purpose, we propose FL algorithms that jointly design unbiased user scheduling and gradient weighting according to each user's distinct energy and channel profile. In addition, we exploit a prevalent metric called the age of information (AoI), which quantifies the staleness of …

Efficient Modelling Of Random Access Memory Cell: An Approach Using Qca Nanocomputing, Ali Newaz Bahar, Angshuman Khan

Turkish Journal of Electrical Engineering and Computer Sciences

Quantum-dot cellular automata (QCA) is innovative and potentially fruitful nanotechnology that provides a solution for transistor-based circuits with enhanced switching frequency, large-scale integration, and low power consumption. The random-access memory (RAM) cell is a fundamental component that is designed to operate quickly and effectively since memory is a core part of the semiconductor industry, thus the QCA family. The RAM cell design in this work is based on a multiplexer structure and is implemented without using coplanar crossovers of QCA technology. QCADesigner-2.0.3, a standard QCA layout design and verification tool, is used in the simulation and validation processes for the …

An Analytical Solution Of Fractional Order Pi Controller Design For Stable/Unstable/Integrating Processes With Time Delay, Erdal Çökmez, İbrahi̇m Kaya

Turkish Journal of Electrical Engineering and Computer Sciences

This paper aims to put forward an analytical solution for tuning parameters of a fractional order PI (FOPI) controller for stable, unstable, and integrating processes with time delay. Following this purpose, the analytical weighted geometrical center (AWGC) method has been extended to the design of fractional order PI controllers. To apply AWGC, the stability equations of the closed-loop system are written in terms of process and fractional order PI controller parameters. With the proposed method, the centroid can be calculated analytically, and the controller parameters can be easily calculated without the need of repetitive drawings of the stability boundary regions. …