Engineering Commons^™

Design And Evaluation Of Unmanned Aerial System-Based Wireless Sensor Network For Irrigation Management, Jasreman Singh

Department of Agricultural and Biological Systems Engineering: Dissertations, Theses, and Student Research

Increasing pressure on food production, both in terms of quantity and quality, has called for intensification and modernization of the agricultural sector. The “Internet of Things” (IoT) is a highly promising technology capable of advancing agricultural operations. The IoT-based real-time monitoring of soil water status and crop canopy temperature in maize and soybean could potentially improve irrigation efficiency, leading to the profitability of field crop production and conservation of natural resources. The overall goal of the work presented here is to design, develop, and evaluate the unmanned aerial system-based wireless sensor system (UWSN) for the purpose of irrigation management by …

Survey Data On Energy And Fuel Use Of Firms In Economic Zones In The Philippines, Majah-Leah V. Ravago, Raul V. Fabella, Karl Robert L. Jandoc, Renzi G. Frias, J. Kathleen P. Magadia

Economics Department Faculty Publications

The data describe characteristics, operations, utilities, and fuels used in the production of 115 manufacturing and agro-industrial firms in Philippine special economic zones. The data include information on the firm's production, sales, and schedules; electricity sources, requirements, and uses; the importance of various conventional fuels, and the firms’ fuel expenditure in their major production processes. The data also include their employee's aptitude, knowledge, considerations, and opinions on alternative fuels and primary energies, and experiences in using them. The data were gathered through a series of focus group discussions (FGDs) in June 2019 and an online survey conducted in August to …

Integration Of Neural Architecture Within A Finite Element Framework For Improved Neuromusculoskeletal Modeling, Victoria L. Volk, Landon D. Hamilton, Donald R. Hume, Kevin B. Shelburne, Clare K. Fitzpatrick

Mechanical and Biomedical Engineering Faculty Publications and Presentations

Neuromusculoskeletal (NMS) models can aid in studying the impacts of the nervous and musculoskeletal systems on one another. These computational models facilitate studies investigating mechanisms and treatment of musculoskeletal and neurodegenerative conditions. In this study, we present a predictive NMS model that uses an embedded neural architecture within a finite element (FE) framework to simulate muscle activation. A previously developed neuromuscular model of a motor neuron was embedded into a simple FE musculoskeletal model. Input stimulation profiles from literature were simulated in the FE NMS model to verify effective integration of the software platforms. Motor unit recruitment and rate coding …

A Spatial Model Of Hepatic Calcium Signaling And Glucose Metabolism Under Autonomic Control Reveals Functional Consequences Of Varying Liver Innervation Patterns Across Species, Aalap Verma, Alexandra Manchel, Rahul Narayanan, Jan B. Hoek, Babatunde A Ogunnaike, Rajanikanth Vadigepalli

Department of Pathology, Anatomy, and Cell Biology Faculty Papers

Rapid breakdown of hepatic glycogen stores into glucose plays an important role during intense physical exercise to maintain systemic euglycemia. Hepatic glycogenolysis is governed by several different liver-intrinsic and systemic factors such as hepatic zonation, circulating catecholamines, hepatocellular calcium signaling, hepatic neuroanatomy, and the central nervous system (CNS). Of the factors regulating hepatic glycogenolysis, the extent of lobular innervation varies significantly between humans and rodents. While rodents display very few autonomic nerve terminals in the liver, nearly every hepatic layer in the human liver receives neural input. In the present study, we developed a multi-scale, multi-organ model of hepatic metabolism …

Gravity Field Changes During Deep Exploitation Of The Coal Longwall And Their Relation To Stress Distribution And Seismic Activity, Łukasz Kortas

Journal of Sustainable Mining

Mining operations cause volumetric deformations within the rock mass and changes in its density, to which the gravimetric method is sensitive. These changes are particularly well seen in periodic measurements of the local gravity field. The paper analyses the relationship between the movement of a longwall in a coal seam and the change in the distribution of the gravity field in time and space observed on the ground surface. Relative gravimetric measurements were carried out in six series between 2018 and 2020; before the start of coal extraction, with the progress of the longwall and after the cessation of mining. …

Study Of The Relationship Of Tidal Changes In Gravity With The Time Of Mining Tremors In The Area Of The Mining Longwall In A Coal Mine – Case Study In Uscb, Poland, Sławomir Siwek

Journal of Sustainable Mining

Deep mining of coal deposits in Upper Silesia Coal Basin in Poland over several hundred years has led to disturbances in the natural state of equilibrium. As a result of changes in stress distribution, mass distribution (changes in gravity forces) and deformation of the rock mass, seismic tremors with energy reaching up to 10E+09J are generated. In this paper, the time of mining tremors occurrence is linked with changes in the gravitational load of the rock mass caused by litosphere tides, which are considered to be one of the factors leading to occurrence of natural seismic tremors. The analysis used …

A Vision-Based Quality Control Model For Manufacturing Systems, Alejandra Figueroa-Lopez

Morehead State Theses and Dissertations

A thesis presented to the faculty of the College of Business and Technology at Morehead State University in partial fulfillment of the requirements for the Degree Master of Science by Alejandra Figueroa-Lopez on November 25, 2021.

Coupling Methylammonium And Formamidinium Cations With Halide Anions: Hybrid Orbitals, Hydrogen Bonding, And The Role Of Dynamics, Chinnathambi Kamal, Dirk Hauschild, Linsey Seitz, Ralph Steininger, Wanli Yang, Clemens Heske, Lothar Weinhardt, Michael Odelius

Chemistry and Biochemistry Faculty Research

The electronic structures of four precursors for organic-inorganic hybrid perovskites, namely, methylammonium chloride and iodide, as well as formamidinium bromide and iodide, are investigated by X-ray emission (XE) spectroscopy at the carbon and nitrogen K-edges. The XE spectra are analyzed based on density functional theory calculations. We simulate the XE spectra at the Kohn-Sham level for ground-state geometries and carry out detailed analyses of the molecular orbitals and the electronic density of states to give a thorough understanding of the spectra. Major parts of the spectra can be described by the model of the corresponding isolated organic cation, whereas high-emission …

Real-Time Bidding Campaigns Optimization Using User Profile Settings, Luis Miralles-Pechuán, Muhammad Atif Qureshi, Brian Mac Namee

Articles

Real-time bidding is nowadays one of the most promising systems in the online advertising ecosystem. In this study, the performance of RTB campaigns is improved by optimising the parameters of the users' profiles and the publishers' websites. Most studies concerning optimising RTB campaigns are focused on the bidding strategy, i.e., estimating the best value for each bid. However, this research focuses on optimising RTB campaigns by finding out configurations that maximise both the number of impressions and the average profitability of the visits. An online campaign configuration generally consists of a set of parameters along with their values such as …

Two-Dimensional Steady Boussinesq Convection: Existence, Computation And Scaling, Jeremiah S. Lane, Benjamin F. Akers

Faculty Publications

This research investigates laser-induced convection through a stream function-vorticity formulation. Specifically, this paper considers a solution to the steady Boussinesq Navier–Stokes equations in two dimensions with a slip boundary condition on a finite box. A fixed-point algorithm is introduced in stream function-vorticity variables, followed by a proof of the existence of steady solutions for small laser amplitudes. From this analysis, an asymptotic relationship is demonstrated between the nondimensional fluid parameters and least upper bounds for laser amplitudes that guarantee existence, which accords with numerical results implementing the algorithm in a finite difference scheme. The findings indicate that the upper bound …

System Identification Of Postural Tremor In Wrist Flexion-Extension And Radial-Ulnar Deviation, Sydney Bryanna Ward

Theses and Dissertations

Generic simulations of tremor propagation through the upper limb have been achieved using a previously developed postural tremor model, but this model had not yet been compared with experimental data or utilized for subject-specific studies. This work addressed these two issues, which are important for optimizing peripheral tremor suppression techniques. For tractability, we focused on a subsystem of the upper limb: the isolated wrist, including the four prime wrist muscles (extensor carpi ulnaris, flexor carpi ulnaris, extensor carpi radialis, and flexor carpi radialis) and the two degrees of freedom of the wrist (flexion-extension and radial-ulnar deviation). Muscle excitation and joint …

Multimodal Ensemble Deep Learning To Predict Disruptive Behavior Disorders In Children, Sreevalsan S. Menon, K. Krishnamurthy

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Oppositional defiant disorder and conduct disorder, collectively referred to as disruptive behavior disorders (DBDs), are prevalent psychiatric disorders in children. Early diagnosis of DBDs is crucial because they can increase the risks of other mental health and substance use disorders without appropriate psychosocial interventions and treatment. However, diagnosing DBDs is challenging as they are often comorbid with other disorders, such as attention-deficit/hyperactivity disorder, anxiety, and depression. In this study, a multimodal ensemble three-dimensional convolutional neural network (3D CNN) deep learning model was used to classify children with DBDs and typically developing children. The study participants included 419 females and 681 …

Ransomware Education: Availability, Accessibility, And Ease Of Use, Judson Gager, Judson Gager

Honors College Theses

With cybersecurity constantly in the media outlets with breaches, cybercrime, and cyberwarfare, it has become a significant concern for all. One of the most recent breaches in the summer of 2021 was the Colonial Pipeline breach, which has proven the country's reliance on these industrial control systems and networking. The systems were taken for ransom by a new type of ransomware written in a different programming language. Although the Colonial Pipeline breach was quickly addressed, the impact of the gas shortage and the response time were alarming at triaging the breach. However, this attack showed the public how dangerous ransomware …

Drug-Based Therapeutic Strategies For Covid-19-Infected Patients And Their Challenges, Khatereh Zarkesh, Elaheh Entezar-Almahdi, Parisa Ghasemiyeh, Mohsen Akbarian, Marzieh Bahmani, Shahrzad Roudaki, Rahil Fazlinejad, Soliman Mohammadi-Samani, Negar Firouzabadi, Majid Hosseini, Fatemeh Farjadian

Manufacturing & Industrial Engineering Faculty Publications

Emerging epidemic-prone diseases have introduced numerous health and economic challenges in recent years. Given current knowledge of COVID-19, herd immunity through vaccines alone is unlikely. In addition, vaccination of the global population is an ongoing challenge. Besides, the questions regarding the prevalence and the timing of immunization are still under investigation. Therefore, medical treatment remains essential in the management of COVID-19. Herein, recent advances from beginning observations of COVID-19 outbreak to an understanding of the essential factors contributing to the spread and transmission of COVID-19 and its treatment are reviewed. Furthermore, an in-depth discussion on the epidemiological aspects, clinical symptoms …

Self-Learned Kernel Low Rank Approach To Accelerated High Resolution 3d Diffusion Mri, Abhijit Baul, Nian Wang, Choyi Zhang, Yuchou Chang, Leslie Ying, Yuchou Chang, Ukash Nakarmi

Electrical and Computer Engineering Faculty Publications

Diffusion Magnetic Resonance Imaging (dMRI) is a promising method to analyze the subtle changes in the tissue structure. However, the lengthy acquisition time is a major limitation in the clinical application of dMRI. Different image acquisition techniques such as parallel imaging, compressed sensing, has shortened the prolonged acquisition time but creating high-resolution 3D dMRI slices still requires a significant amount of time. In this study, we have shown that high resolution 3D dMRI can be reconstructed from the highly undersampled k-space and q-space data using a Kernel Low Rank method. Our proposed method has outperformed the conventional CS methods in …

Interferometric Lithography- An Approach To Large Area And Cost Effective Nanopatterning, Vineeth Sasidharan

Optical Science and Engineering ETDs

In this dissertation interferometric lithography is approached in two different ways to address two important constraints of nanopatterning. One approach solves the problem of scaling up interferometric lithography to wafer scale (4 inch or larger) area. Through the second approach we have developed a nanopatterning technique based on interferometric lithography by using an inexpensive (~$100) diode laser as source, making interferometric lithography a very cost-effective technique.

Wafer-scale large-area nanopatterning was developed using an amplitude grating mask as a grating beam splitter along with spatial averaging of laser intensity by wobbling. The longitudinal and transverse coherence issues both are eased by …

Multi-Vendor And Multisite Evaluation Of Cerebrovascular Reactivity Mapping Using Hypercapnia Challenge, Peiying Liu, Dengrong Jiang, Marilyn Albert, Christopher E. Bauer, Arvind Caprihan, Brian T. Gold, Steven M. Greenberg, Karl G. Helmer, Kay Jann, Gregory A. Jicha, Pavel Rodriguez, Claudia L Satizabal, Sudha Seshadri, Herpreet Singh, Jeffrey F. Thompson, Danny J. J. Wang, Hanzhang Lu

Neuroscience Faculty Publications

Cerebrovascular reactivity (CVR), which measures the ability of cerebral blood vessels to dilate or constrict in response to vasoactive stimuli such as CO2 inhalation, is an important index of the brain's vascular health. Quantification of CVR using BOLD MRI with hypercapnia challenge has shown great promises in research and clinical studies. However, in order for it to be used as a potential imaging biomarker in large-scale and multi-site studies, the reliability of CO2-CVR quantification across different MRI acquisition platforms and researchers/raters must be examined. The goal of this report from the MarkVCID small vessel disease biomarkers consortium is to evaluate …

Constrained Nonlinear Heuristic-Based Mpc For Control Of Robotic Systems With Uncertainty, Tyler James Quackenbush

Theses and Dissertations

This thesis focuses on the development and extension of nonlinear evolutionary model predictive control (NEMPC), a control algorithm previously developed by Phil Hyatt of the BYU RaD Lab. While this controller and its variants are applicable to any high degree-of-freedom (DoF) robotic system, particular emphasis is given in this thesis to control of a soft robot continuum joint. First, speed improvements are presented for NEMPC. Second, a Python package is presented as a companion to NEMPC, as a method of establishing a common interface for dynamic simulators and approximating each system by a deep neural network (DNN). Third, a method …

Stochastic Lightning Damage Prediction Of Carbon/Epoxy Composites With Material Uncertainties, S.Z.H. Shah, Juhyeong Lee

Mechanical and Aerospace Engineering Faculty Publications

This study presents a novel stochastic modeling framework predicting lightning thermal damage in carbon/epoxy composites. The stochastic lightning damage model (SLDM) was developed with random distributions of composite’s electrical conductivity and void. The Box-Muller transformation was applied to generate random in-plane and through-thickness electrical conductivities with Gaussian distributions. The SLDM suggested that the predicted lightning thermal damage to carbon/epoxy composites increased slightly with the use of stochastic electrical conductivity, but the presence of voids did not significantly affect the damage development. The predicted size and shape of lightning thermal damage agreed fairly well with experimental results. In addition, the proposed …

Statistical Method For Extracting Radiation-Induced Multi-Cell Upsets And Anomalies In Sram-Based Fpgas, Juan Andres Perez Celis

Theses and Dissertations

FPGAs are susceptible to radiation-induced effects that change the data in the configuration memory. These effects can cause the malfunction of the system. Triple modular redundancy has extensively been used to improve the circuit's cross-section. However, TMR has shown to be particularly susceptible to radiation effects that affect more than one memory cell such as Multiple Cell Upsets (MCU) or micro-Single Event Functional Interrupts (micro-SEFI). This work describes a statistical technique to extract Multi-Cell Upset (MCU) and micro-SEFI events from raw radiation upset data. The technique uses Poisson statistics to identify patterns in the data. The most common patterns are …

Hydrolysis Of Rice Straw For Production Of Soluble Sugars, Mahmoud El-Wany

Archived Theses and Dissertations

No abstract provided.

Guidelines For The Application Of Recycled Concrete Aggregate In The Egyptian Construction Industry, Ahmed Mostafa Essam Aly Kamel

Archived Theses and Dissertations

No abstract provided.

Copycat Mass Killings: How Personality Might Moderate Identification With Antisocial Characters, Emily R. Mazzurco

Kean Quest

Research indicates that certain personality traits are prevalent within mass killers. Aggression, social rejection, narcissism, fame-seeking, low self-esteem, and depression are commonalities with mass killers, specifically mass shooters. Identification or idolizing antisocial fictional characters is also a common behavior within these types of offenders. These types of killers often draw inspiration for their own crimes from past criminals or from film and TV, thus committing what is known as a copycat crime. The purpose of the current study will be to examine the effects of social rejection and instigation on the likelihood of identifying with an antisocial character in young …

The Strategic Goals Of -Using Service Oriented Architecture Principles, Ashraf Saied Abdel Nabi

Future Computing and Informatics Journal

different platforms, different databases, and different language programs. These systems need to exchange information and reuse the same functionality to achieve integration between these systems.

Many Software companies failed to achieve information follow and reuse the same functionality

This paper introduces guidelines introduces Service-Oriented Architecture Principles guidelines and rules to help Applications developers to achieve information integrations and reuse the same functionality, SOA principles providing rules and guidelines that specify exactly how solution logic should be decomposed and molded into technology solutions

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The Factors Influencing The Acceptance Of Web-Based E-Learning System Among Academic Staffs Of Saudi Arabia, Ikhlas Zamzami

Future Computing and Informatics Journal

It is possible to learn more quickly and effectively with e-learning software development because it provides learners with convenient and flexible learning environments. This allows them to progress further in their careers. Reports on web-based e-learning systems for in-service education have frequently neglected to include the viewpoint of the instructor. In order to conduct quantitative research, a sample of 50 academic staff members was selected. The purpose of this study was to investigate various factors that influence the intention to use web-based e-learning, with the theoretical foundation being provided by university lecturers. According to the findings of the study, the …

Enhancing Academic Advising In Credit Hours System Using Dss, Alaa Salah Eldin Ghoneim

Future Computing and Informatics Journal

Academic advising plays a vital role in achieving higher educational institution’s purposes. Academic advising is a process where an academic advisor decides to select a certain number of courses for a student to register in each semester to fulfil the graduation requirements. This paper presents an Academic Advising Decision Support System (AADSS) to enhance advisors make better decisions regarding their students’ cases. AADSS framework divided into four layers, data preparation layer, data layer, processing layer and decision layer. The testing results from those participating academic advisors and students considered are that AADSS beneficial in enhancing their decision for selecting courses.

Image Hiding Using Qr Factorization And Discrete Wavelet Transform Techniques, Reham Ahmed El-Shahed, Maryam Al-Berry, Hala Ebied, Howida Shedeed

Future Computing and Informatics Journal

Steganography is one of the most important tools in the data security field as there is a huge amount of data transferred each moment over the internet. Hiding secret messages in an image has been widely used because the images are mostly used in social media applications. The proposed algorithm is a simple algorithm for hiding an image in another image. The proposed technique uses QR factorization to conceal the secret image. The technique successfully hid a gray and color image in another one and the performance of the algorithm was measured by PSNR, SSIM and NCC. The PSNR for …

A Statistical-Mining Techniques’ Collaboration For Minimizing Dimensionality In Ovarian Cancer Data, Mohamed Attia, Maha Farghaly, Mohamed Hamada, Amira M. Idrees Ami

Future Computing and Informatics Journal

A feature is a single measurable criterion to an observation of a process. While knowledge discovery techniques successfully contribute in many fields, however, the extensive required data processing could hinder the performance of these techniques. One of the main issues in processing data is the dimensionality of the data. Therefore, focusing on reducing the data dimensionality through eliminating the insignificant attributes could be considered one of the successful steps for raising the applied techniques’ performance. On the other hand, focusing on the applied field, ovarian cancer patients continuously suffer from the extensive analysis requirements for detecting the disease as well …

Machine Learning Identifies Liquids Employing A Simple Fiber-Optic Tip Sensor, Wassana Naku, Chen Zhu, Anand K. Nambisan, Rex E. Gerald, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

We proposed an extremely simple fiber-optic tip sensor system to identify liquids by combining their corresponding droplet evaporation events with analyses using machine learning techniques. Pendant liquid droplets were suspended from the cleaved endface of a single-mode fiber during the experiment. The optical fiber-droplet interface and the droplet-air interface served as two partial reflectors of an extrinsic Fabry-Perot interferometer (EFPI) with a liquid droplet cavity. As the liquid pendant droplet evaporated, its length diminished. A light source can be used to observe the effective change in the net reflectivity of the optical fiber sensor system by observing the resulting optical …

Data-Driven Damage Initiation Criteria For Carbon Fiber Reinforced Polymer Composites, Alexander Richard Post

College of Computing and Digital Media Dissertations

Computational progressive failure analysis (PFA) is vital for the design, verification, and validation of carbon fiber reinforced polymer (CFRP) composites. However, the computational cost of PFA is usually high due to the complexity of the model. The damage initiation criterion is one of the essential components of a PFA code to determine the transition of a material’s state from pristine or microscopically damaged to macroscopically damaged. In this thesis, data-driven models are developed to determine the matrix damage initiation based on the Mohr-Coulomb model and Hashin model. For 2D plane stress states, the computational cost for determining damage initiation can …