Digital Commons Network^™

Substantial Blue Carbon Sequestration In The World’S Largest Seagrass Meadow, Chuancheng Fu, Sofia Frappi, Michelle N. Havlik, Wells Howe, S. David Harris, Elisa Laiolo, Austin J. Gallagher, Pere Masqué, Carlos M. Duarte

Research outputs 2022 to 2026

Seagrass meadows are important sinks for organic carbon and provide co-benefits. However, data on the organic carbon stock in seagrass sediments are scarce for many regions, particularly The Bahamas, which accounts for up to 40.7% of the documented global seagrass area, limiting formulation of blue carbon strategies. Here, we sampled 10 seagrass meadows across an extensive island chain in The Bahamas. We estimate that Bahamas seagrass meadows store 0.42–0.59 Pg organic carbon in the top-meter sediments with an accumulation rate of 2.1–2.9 Tg annually, representing a substantial global blue carbon hotspot. Autochthonous organic carbon in sediments decreased from ~1980 onwards, …

Multivariate Analysis Approach To Factor-Affected Tuberculosis Disease, Zuli Agustina Gultom, Farid Akbar Siregar, Mahardika Abdi Prawira Tanjung, Al-Hamidy Hazidar

Knowledge Engineering and Data Science

Tuberculosis is a disease caused by infection with the mycobacterium tuberculosis complex. Tuberculosis attack organ besides the lung, such as the pleura, lining of the brain, lining of the heart, lymph gland, bones, joint, skin, intestines, kidney, urinary tract, and genital. This disease is found in densely populated settlements with poor sanitation, lack of ventilation and sunlight and lack of rest. Moreover, the factors that will be analyzed in this research are Population Density (X1), Number of HIV/AIDS (X2), number of toddlers who experience nutrition (X3), Number of toddlers who experience BCG immunization (X4), number of toddlers who get exclusive …

Systematic Literature Review On Ontology-Based Indonesian Question Answering System, Fadhila Tangguh Admojo, Adidah Lajis, Haidawati Nasir

Knowledge Engineering and Data Science

Question-Answering (QA) systems at the intersection of natural language processing, information retrieval, and knowledge representation aim to provide efficient responses to natural language queries. These systems have seen extensive development in English and languages like Indonesian present unique challenges and opportunities. This literature review paper delves into the state of ontology-based Indonesian QA systems, highlighting critical challenges. The first challenge lies in sentence understanding, variations, and complexity. Most systems rely on syntactic analysis and struggle to grasp sentence semantics. Complex sentences, especially in Indonesian, pose difficulties in parsing, semantic interpretation, and knowledge extraction. Addressing these linguistic intricacies is pivotal for …

Evidence Of Students’ Academic Performance At The Federal College Of Education Asaba Nigeria: Mining Education Data, Arnold Adimabua Ojugo, Christopher Chukwufunaya Odiakaose, Frances Emordi, Rita Erhovwo Ako, Winifred Adigwe, Kizito Eluemonor Anazia, Victor Geteloma

Knowledge Engineering and Data Science

One main objective of higher education is to provide quality education to its students. One way to achieve the highest level of quality in the higher education system is by discovering knowledge for prediction regarding enrolment of students in a particular course, alienation of traditional classroom teaching model, detection of unfair means used in online examination, detection of abnormal values in the result sheets of the students, and prediction about students’ performance. The knowledge is hidden among the educational data set and is extractable through data mining techniques. The present paper is designed to justify the capabilities of data mining …

Eeg Classification While Listening To Murottal Al-Quran And Classical Music Using Random Forest Method, Heni Sumarti, Fahira Septiani, Agus Sudarmanto, Wahyu Caesarendra, Rizki Edmi Edison

Knowledge Engineering and Data Science

This study is aimed to classify the brain activity of adolescents associated with audio stimuli; murottal Al-Quran and classical music. The raw data were filtered using Independent Component Analisys (ICA) and followed by band-pass filter in Python on the Google Colab Extraction was processed with Power Spectral Density (PSD) and the Random Forest Method in Weka Machine Learning was used for classification. The research results showed the same results between the two types of stimulation, namely the order of brain waves from highest to lowest were delta, alpha, theta and beta. The average brain waves of teenagers when given murottal …

Deep Learning Approaches With Optimum Alpha For Energy Usage Forecasting, Aji Prasetya Wibawa, Agung Bella Putra Utama, Ade Kurnia Ganesh Akbari, Akhmad Fanny Fadhilla, Alfiansyah Putra Pertama Triono, Andien Khansa’A Iffat Paramarta, Faradini Usha Setyaputri, Leonel Hernandez

Knowledge Engineering and Data Science

Energy use is an essential aspect of many human activities, from individual to industrial scale. However, increasing global energy demand and the challenges posed by environmental change make understanding energy use patterns crucial. Accurate predictions of future energy consumption can greatly influence decision-making, supply-demand stability and energy efficiency. Energy use data often exhibits time-series patterns, which creates complexity in forecasting. To address this complexity, this research utilizes Deep Learning (DL), Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Long Short-term Memory (LSTM), Bidirectional LSTM (Bi-LSTM), and Gated Recurrent Unit (GRU) models. The main objective is to improve the accuracy of …

Recurrent Session Approach To Generative Association Rule Based Recommendation, Tubagus Arief Armanda, Ire Puspa Wardhani, Tubagus M. Akhriza, Tubagus M. Adrie Admira

Knowledge Engineering and Data Science

This article introduces a generative association rule (AR)-based recommendation system (RS) using a recurrent neural network approach implemented when a user searches for an item in a browsing session. It is proposed to overcome the limitations of the traditional AR-based RS which implements query-based sessions that are not adaptive to input series, thus failing to generate recommendations. The dataset used is accurate retail transaction data from online stores in Europe. The contribution of the proposed method is a next-item prediction model using LSTM, but what is trained to develop the model is an associative rule string, not a string of …

Comparison Of Machine Learning Algorithms For Species Family Classification Using Dna Barcode, Lala Septem Riza, M Ammar Fadhlur Rahman, Yudi Prasetyo, Muhammad Iqbal Zain, Herbert Siregar, Topik Hidayat, Khyrina Airin Fariza Abu Samah, Miftahurrahma Rosyda

Knowledge Engineering and Data Science

Classifying plant species within the Liliaceae and Amaryllidaceae families presents inherent challenges due to the complex genetic diversity and overlapping morphological traits among species. This study explores the difficulties in accurate classification by comparing 11 supervised learning algorithms applied to DNA barcode data, aiming to enhance the precision of species family classification in these taxonomically intricate plant families. The ribulose-1,5-bisphosphate carboxylase-oxygenase large sub-unit (rbcL) gene, selected as a DNA barcode locus for plants, is used to represent species within the Amaryllidaceae and Liliaceae families. The experimental results demonstrate that nearly all tested models achieve accurate species classification into the appropriate …

Insight Into The Binding Of Argon To Cyclic Water Clusters From Symmetry-Adapted Perturbation Theory, Carly A. Rock, Gregory S. Tschumper

Chemistry Faculty Research & Creative Works

This work systematically examines the interactions between a single argon atom and the edges and faces of cyclic H (Formula presented.) O clusters containing three–five water molecules (Ar(H (Formula presented.) O) (Formula presented.)). Full geometry optimizations and subsequent harmonic vibrational frequency computations were performed using MP2 with a triple- (Formula presented.) correlation consistent basis set augmented with diffuse functions on the heavy atoms (cc-pVTZ for H and aug-cc-pVTZ for O and Ar; denoted as haTZ). Optimized structures and harmonic vibrational frequencies were also obtained with the two-body–many-body (2b:Mb) and three-body–many-body (3b:Mb) techniques; here, high-level CCSD(T) computations capture up through the …

Comment On Marsigliante Et Al Effects On Children's Physical And Mental Well-Being Of A Physical-Activity-Based School Intervention Program: A Randomized Study, Raphiel Murden, Jon Agley, Lilian Golzarri-Arroyo, Armando Peña, Danny Valdez, Abu Bakkar Siddique, Moonseong Heo, David B Allison

Children’s Nutrition Research Center Staff Publications

We conducted a critical review of the article “Effects on Children’s Physical and Mental Well-Being of a Physical-Activity-Based School Intervention Program: A Randomized Study”, published in the International Journal of Environmental Research and Public Health in 2023 as part of the Special Issue “Psychomotricity and Physical Education in School Health”. We identified multiple mistakes in the statistical analyses applied. First, the authors claim to have found a statistically significant association between the proposed intervention and change in body composition (body mass index (BMI) percentiles, relative fat mass, and BMI classes) by way of exhibiting differences in nominal significance between the …

Space-Time-Frequency Characterization In Electromagnetic Near-Field Scanning: A Data-Driven Approach, Yanming Zhang, Lijun Jiang

Electrical and Computer Engineering Faculty Research & Creative Works

Near-field scanning has become a widely used tool for diagnosing electromagnetic compatibility and electromagnetic interference issues. However, the transient signal of the device under test often contains multiple frequency bands and exhibits nonstationarity, which poses a challenge for near-field scanning analysis. To address this issue, this article presents a method for analyzing time-resolved near-field radiation based on multiresolution dynamic mode decomposition (MRDMD). The MRDMD approach recursively and hierarchically applies the traditional dynamic mode decomposition (DMD) method. The distribution of DMD eigenvalues determines the slow and fast modes in each level's decomposition, where the slow modes are preserved, and the fast …

Electromagnetic-Thermal Co-Design Of Base Station Antennas With All-Metal Ebg Structures, Huan Huan Zhang, Jun Bo Chao, Yi Wei Wang, Ying Liu, Yun Xue Xu, Heming Yao, Lijun Jiang, Xiang Hua Li

Electrical and Computer Engineering Faculty Research & Creative Works

In order to improve the heat dissipation capability of the 5G base station, the electromagnetic and thermal performances of a base station antenna array are co-designed by adopting all-metal electromagnetic bandgap (EBG) structures. The geometrical dimension of the EBG structure is determined through balancing the electromagnetic and thermal performances of the antenna array. The operating frequency band (voltage standing wave ratio (VSWR) < 1.5) of the proposed antenna array can cover 3.4-3.8 GHz. Its realized gains, isolation, cross-polarized discrimination ratio, and half-power beamwidth are satisfactory compared with other state-of-the-art base station antennas. Most importantly, more than 9 C temperature reduction can be observed when comparing the heat dissipation capability of the proposed antenna array with the reference antenna array.

The Effects Of One-On-One Interventions On Kindergarten Students., Laura Peterson

Dissertations, Theses, and Projects

This 2023 study focuses on the impact that one-on-one interventions have on the academic achievement of kindergarten students. My focus is on whether one-on-one interventions play a significant role in the outcome of student scores on trimester achievement assessments, or if one-on-one interventions do not show success in student progress. Students will be assessed daily for 20 days on interventions in areas they are struggling with. The research took place in a Minnesota school, specifically five Kindergarten students who are in the same classroom. The data and results will follow.

Experiments And Simulations Of Liquid Mass Gauging And Slosh Dynamics In Microgravity, Jedediah Morse Storey

Theses and Dissertations

Advancements in liquid propellant management science and technologies are key to increasing safety, decreasing cost, and increasing payload mass of space missions. Propellant usually comprises a large portion of the total mass of launch vehicles and spacecraft, so liquid propellant sensing, as well as predicting and controlling the motion of it, are important. Electrical Capacitance Tomography (ECT) is an emerging sensing technology that is capable of measuring the distribution of liquid anywhere inside of a tank, potentially making it useful for measuring slosh and gauging mass. An ECT-instrumented tank was successfully tested in microgravity for the first time. Basics of …

Development Of A Physics-Informed Neural Network For Prediction Of Blood Flow, Marcello Vittorio Mattei Di Eugenio

Theses and Dissertations

Abstract—Objective: We propose a new neural network architecture that accepts point clouds and outputs 3D velocity profiles for aneurysm geometries. Methods: We generated a synthetic aneurysm 3D flow dataset using CFD and used it to train our model architecture and compare it with other popular architectures like U-net and PointNet. We incorporate tools for improving model performance such as incorporating a distance function, a physics-informed loss to enforce the law of mass conservation, and the Huber loss to learn patterns across heterogeneous velocity components of multiple dimensions. Results: The tools implemented together with our architecture achieved the best performance on …

The Relationship Between Biofouling Adhesion And Frequency Of Mechanical Cleaning To Control The Recruitment To Clear Coatings, Dylan Thomas Eggers

Theses and Dissertations

There is a need to control biofouling on sensors and transparent windows in the marine environment. Clear silicone coatings offer a method to reduce the adhesion strength of marine organisms to the surface, however, these also require mechanical cleaning to maintain the surfaces free of fouling. This research evaluated the performance of eighty seven formulations and took the top two candidates to investigate a) the frequencies of wiping required by a brush to maintain two coatings and uncoated glass surfaces free of fouling and b) the effects of clear silicone coatings fouling release properties on required frequencies. The panels were …

Underwater Image Enhancement: A Pipeline For Underwater Computer Visions, Humberto Lebron Rivera

Theses and Dissertations

Ocean exploration has surged in popularity and significance in recent years, including diverse areas like maritime archeology, underwater resources, and submerged structure inspection. The activities mentioned above heavily depend on vision and imagery, a challenge in the unpredictable marine world. This thesis presents a conditional generative adversarial network model for image-to-image translation problems. We designed and trained the model with the end goal of enhancing underwater images. Five metrics were employed for validation to quantify our model’s resulting enhanced images. By doing so, we aim to establish a pipeline that can leverage aerial computer vision algorithms for marine applications.

Our …

How Students Learn: Examining The Differences In Learning Strategies Between Flight And Nonflight Students, Jennifer A. Torres

Theses and Dissertations

The purpose of this study was to determine if there were any differences in learning strategies between undergraduate flight and nonflight students attending a 4-year university that offered a Part 141 flight training program. Learning strategies were measured using Panadero et al.’s (2021) 30-item Deep Learning Strategies Questionnaire and its four subscales—Basic Learning Self-Regulation Strategies, Visual Elaboration and Summarizing Strategies, Deep Information Processing Strategies, and Social Learning Self-Regulation Strategies—all of which were the dependent variables. The primary independent variable was group membership, but the study also incorporated two covariates—self-efficacy and intrinsic value—which were measured using the respective subscales of Pintrich …

Path Planning Development Framework For Mobile Robots, Lauren-Ann Elizabeth Graham

Theses and Dissertations

Planetary exploration relies on methods of path planning to achieve autonomous navigation in hazardous environments. Simulating harsh terrain, real-time varying physics, and robotics applications is vital for testing control algorithms here on Earth. Robotics Operating System (ROS) is a set of software libraries and tools that allow you to build and simulate robotic applications. Utilizing ROS, Gazebo, and Blender, a rough terrain simulation framework is created to explore and compare path planning algorithms using various desired robots and maps. ROS supports multiple path planning algorithms given its open-source abilities. This research focuses on path planning implementation of Proportional-Integral-Derivative (PID) control …

Gpu Based Monte Carlo Estimation Of Eddy Current Losses In Electromagnetic Coil-Core System, Adwaith Ravichandran

Theses and Dissertations

A novel parallelizable probabilistic approach to model eddy currents in AC electromagnets is presented in this research. Consequently, power loss associated with the formation of these eddy currents is estimated and validated using experimental data. Furthermore, predicting the effect of ferromagnetic alternating field enhancement on power loss in the source excitation winding has been an active area of research. Unlike a stationary field, an alternating sinusoidal field diffuses partially into the ferromagnetic material leading to a predictably sub-optimal field enhancement. To model these physics, finite element techniques employ nonlinear iterative solvers which are time consuming. A novel method is developed …

Project Thetis: A Low-Cost, Low-Profile Inertial Data Logger, Braidan Duffy

Theses and Dissertations

This thesis details the design, testing, calibration, and verification of a nine degree of freedom inertial measurement data logger for use with floating bodies. The instrument was conceived to address limitations of equipment used in classes within the Ocean Engineering department at Florida Institute of Technology. By meeting with several stakeholders and end users, a series of stakeholder requirements, capabilities, and component-level requirements were de- veloped that informed the design constraints. There were several hardware iterations of the board, culminating in Revision F5 which was extensively tested and proven. The design was inspected after testing concluded to determine which capabilities …

Algorithm Selection Using Edge Ml And Case-Based Reasoning, Rahman Ali, Muhammad Sadiq Hassan Zada, Asad Masood Khatak, Jamil Hussain

All Works

In practical data mining, a wide range of classification algorithms is employed for prediction tasks. However, selecting the best algorithm poses a challenging task for machine learning practitioners and experts, primarily due to the inherent variability in the characteristics of classification problems, referred to as datasets, and the unpredictable performance of these algorithms. Dataset characteristics are quantified in terms of meta-features, while classifier performance is evaluated using various performance metrics. The assessment of classifiers through empirical methods across multiple classification datasets, while considering multiple performance metrics, presents a computationally expensive and time-consuming obstacle in the pursuit of selecting the optimal …

Predicting New Crescent Moon Visibility Applying Machine Learning Algorithms, Murad Al-Rajab, Samia Loucif, Yazan Al Risheh

All Works

The world's population is projected to grow 32% in the coming years, and the number of Muslims is expected to grow by 70%—from 1.8 billion in 2015 to about 3 billion in 2060. Hijri is the Islamic calendar, also known as the lunar Hijri calendar, which consists of 12 lunar months, and it is tied to the Moon phases where a new crescent Moon marks the beginning of each month. Muslims use the Hijri calendar to determine important dates and religious events such as Ramadan, Haj, Muharram, etc. Till today, there is no consensus on deciding on the beginning of …

Role Of Authentication Factors In Fin-Tech Mobile Transaction Security, Habib Ullah Khan, Muhammad Sohail, Shah Nazir, Tariq Hussain, Babar Shah, Farman Ali

All Works

Fin-Tech is the merging of finance and technology, to be considered a key term for technology-based financial operations and money transactions as far as Fin-Tech is concerned. In the massive field of business, mobile money transaction security is a great challenge for researchers. The user authentication schemes restrict the ability to enforce the authentication before the account can access and operate. Although authentication factors provide greater security than a simple static password, financial transactions have potential drawbacks because cybercrime expands the opportunities for fraudsters. The most common enterprise challenge is mobile-based user authentication during transactions, which addresses the security issues …

Patterns In Winter Stonefly Distribution Along A River Continuum And Land-Use Gradient In Northwest Arkansas Streams, Zachary Tipton

Graduate Theses and Dissertations

Freshwater ecosystems are facing a crisis with extinction rates of aquatic species exceeding those of their terrestrial counterparts by up to fivefold. This decline is predominantly attributed to evolving land use patterns within watersheds, leading to chemical and physical transformations in freshwater habitats. Northwest Arkansas (NWA) represents one of the fastest-growing regions in the United States, undergoing substantial shifts in land use. Consequently, the status of aquatic life in this region remains uncertain. Addressing this concern, the latest Arkansas Wildlife Action Plan emphasizes the necessity of distribution and population data to guide conservation efforts for Species of Greatest Conservation Need …

Theistic Open Futurism: A Critical Philosophical Investigation, Elijah Hess

Graduate Theses and Dissertations

In this dissertation I critically evaluate and develop a model of God I dub “theistic open futurism”—the view that an omniscient, omnipotent, and omnibenevolent being exists but fails to know future contingent statements because such statements are not true. Contrary to what their free will critics have supposed, I argue that theistic open futurists do not subscribe to a metaphysical vision of the future that is logically or religiously incoherent. With respect to the latter, I suggest that while some open theists have overstated their case concerning the amount of providential control God could have given the reality of an …

The Study Of The Polarization Domains Of Mbe-Grown Barium Titanate Thin Films And Nanodots Using Pfm, Mohammad Zamani-Alavijeh

Graduate Theses and Dissertations

Polarization domains are the fundamental elements in ferroelectric materials that contribute to their properties. A natural polarization domain, which possesses a specific polarization direction or state, typically ranges in size from one unit cell to a few micrometers. Therefore, studying polarization domains requires the fabrication of materials and the measurement of ferroelectric properties at the nanoscale. In this study, molecular beam epitaxy (MBE) is employed to fabricate barium titanate (BTO) crystals, and piezoresponse force microscopy (PFM) is used to measure the properties of polarization domains at the nanoscale. In the beginning, this study identifies the reflection of high-energy electron diffraction …

Modeling The Peak Ground Acceleration And Assessing The Economic Loss And Casualty Due To Potential Earthquakes Of Various Magnitudes In The New Madrid Seismic Zone, Mahmud Afroz

Graduate Theses and Dissertations

The New Madrid Seismic Zone (NMSZ) is one of the active tectonic zones capable of producing big earthquakes in the southcentral USA. The objective of this study was to assess the economic losses and casualties that might be caused by various magnitudes of seismic events in the NMSZ. The manifestation is the estimation for each magnitude which is using the Peak Ground Acceleration (PGA) that might occur during an earthquake. It is calculated using an attenuation function that correlates the intensity of local ground movement, the earthquake magnitude, and the distance from its epicenter. The assessment of casualties was conducted …

Exploring The Interrelationships Among Structural Complexity, Multi-Trophic Biodiversity, And Ecosystem Productivity In Forested Ecosystems., Ayanna St. Rose

Graduate Theses and Dissertations

Forests play a pivotal role in sustaining global biodiversity and mitigating the global climate, as they serve as the primary refuge for terrestrial biodiversity and effectively capture and store atmospheric carbon dioxide. However, changing climate and land use are altering the geographic distribution, physical structure, and productivity of forested ecosystems that can have profound impacts on biodiversity conservation, forest productivity, and global climate. This dissertation contributes to our understanding of multifaceted interactions between the physical and biological structural complexity and ecosystem functions in forested landscapes across the United states by using openly available data from two national networks: the National …

The Spatial And Temporal Distribution Of Large Rock Blocks And Control On Landscape Evolution In The Ozarks, Chelsea Moran

Graduate Theses and Dissertations

Geologists often use landscape form to infer landscape processes through time. While climate and tectonics shape geomorphic form, the potential range of spatial or temporal scales that can shape any specific landscape can render landscape process-form based hypotheses too general for consideration. Contributions by mathematical modeling have helped bridge the gap between inferring processes from form, notably in how sediment transport dynamics shape hillslopes. However, few models encapsulate the movement of large rock blocks ( >2 meters across) and their potential impact as hillslope sediment transport disruptors. The Upper Buffalo River watershed (BRW) in the Ozarks of northern Arkansas has …