Digital Commons Network^™

Links Of Intensification Chemical Weathering And Nickel Enrichment With Volcanism In The North China Plate Around The Permian-Triassic Boundary, Wang Ye, Ye Chengzhuo, Zhang Tong, Yang Minfang, Zhou Kai, Zhang Peixin, Yang Yuzhu, Zhang Chu, Lu Jing

Coal Geology & Exploration

Objective The North China Plate serves as a pivotal region for deciphering the mechanisms underlying the links of volcanism and paleoenvironmental-climatic upheavals around the Permian-Triassic Boundary (PTB). The dramatic environmental perturbations during this period are closely linked to large-scale volcanic eruptions of the Siberian Traps Large Igneous Province (STLIP). These eruptions triggered global warming, extreme chemical weathering events, and mass extinctions, marking a significant turning point in the evolution of the Earth system.Methods This study investigated the Sunjiagou and Liujiagou formations in the WY-U-01H borehole in the Qinshui Basin, North China Plate. Using the chemical index of alteration (CIA), …

Global Representative Metallogenic Models And Geophysical Exploration Methods Of Sylvite: Current Research Status And Prospects, Qu Ping, Yue Hangyu, Huang Xiaobing, Song Jiong

Coal Geology & Exploration

Background Sylvite serves as a strategic mineral resource that plays a significant role in ensuring food safety and sustainable agricultural development, with approximately 90% of global potash resources used for potassium fertilizer production. However, developing countries such as China have long faced the challenges of heavy dependence on potash imports and insufficient potash resource continuity. Such a supply and demand framework causes China to speed up research on potash metallogenic patterns and technical innovations in potash exploration. This will help overcome resource bottlenecks. Objective This study presented a systematic summary of global potash metallogenic models and investigated the approaches of …

Neutrosophic Algebraic Structures For Precise Uncertainty Quantification In Outcome-Based Education Systems: A Rigorous Case Study Analysis, Mona Gharib, Imran Siddique, Miin Shen Yang

Neutrosophic Systems with Applications

Outcome-Based Education (OBE) emphasizes measurable learning results, yet the evaluation of professional talent training in physical education often involves uncertain, incomplete, or even contradictory indicators. Traditional assessment models are limited in capturing these indeterminacies. To address this challenge, we propose a novel neutrosophic algebraic framework that integrates neutrosophic probability, measure, and algebraic structures with OBE evaluation. This study introduces a neutrosophic evaluation framework that captures both determinate and indeterminate aspects of brand competitiveness. A case study on physical education professional training demonstrates how the proposed model captures hidden uncertainty and provides a more balanced assessment than classical methods. The results …

Evaluation Of Soil Quality Index For Sugar Beet Cultivation Under Neutrosophic Set Framework, Asiye Yilmaz Adkinson

Neutrosophic Systems with Applications

Evaluation of soil quality index for sugar beet cultivation is a decision-making problem. So, we use the decision-making methods to solve this problem. We use the ARAS method is a decision-making method to rank the alternatives. The average method is used to compute the criteria weights. Evaluation this problem contains uncertainty information. So, the neutrosophic set is used to solve this uncertainty information. This study uses ten criteria and 15 alternatives. The sensitivity analysis is conducted to show the stability of the ranks. We change the criteria weights by ten cases. Then we apply the steps of the proposed approach …

14th International Conference On Business, Technology And Innovation 2025, University For Business And Technology - Ubt

UBT International Conference

Welcome to IC – UBT 2025

UBT Annual International Conference is the 14th international interdisciplinary peer reviewed conference which publishes works of the scientists as well as practitioners in the area where UBT is active in Education, Research and Development. The UBT aims to implement an integrated strategy to establish itself as an internationally competitive, research-intensive university, committed to the transfer of knowledge and the provision of a world-class education to the most talented students from all background. The main perspective of the conference is to connect the scientists and practitioners from different disciplines in the same place and make …

Invisible Aircraft In U.S. Airspace: Regulatory Gaps And Mid-Air Collision Risk For Part 121 Operators, Philip Vandette

International Journal of Aviation, Aeronautics, and Aerospace

Scheduled air carrier aircraft operate at large and small commercial airports across the U.S. National Airspace System. These turbine-powered aircraft fly at high speeds during departure and approach, yet many commercial airports are not covered by regulations requiring general aviation aircraft to transmit their positions, and some remain exempt from existing requirements. This regulatory gap forces airline pilots to rely on see-and-avoid methods that are impractical at turbine aircraft speeds. This study conducts a quantitative exploratory analysis of three data sources, using a PRISMA-style flow diagram, to examine the frequency of near mid-air collisions involving airline and general aviation aircraft …

Design And Implementation Of A Cross-Platform, Modular Electronic-Nose System, Kaushika Rudraraju

USF Tampa Graduate Theses and Dissertations

Electronic noses (e-noses) are a subject of great research. They are useful in multiple platforms and serve a great purpose in both studies and safety. This thesis presents a portable, modular e-nose platform that spans the full pipeline from sensing to visualization, with emphasis on scalability, repeatability, and straightforward integration. The hardware is organized as swappable sensor modules each hosting multiple commercial sensors and local signal-conditioning networked to a master microcontroller via structured communication protocols. High-resolution acquisition, time alignment, and efficient streaming to a host enable reliable logging and analysis. A controlled exposure chamber and a repeatable sampling protocol (baseline-exposure-purge …

Fuel Adulteration Detection Using Open-Ended Coaxial Line And Circular Waveguide Techniques, Abdulrahman Alofi, Ahmed Shamseldin, Sharif Iqbal M. Sheikh, Hussein Attia

Faculty Publications

Fuel adulteration, the practice of blending lower-quality substances like kerosene with gasoline, poses significant challenges for ensuring fuel quality and safety. This study investigates two electromagnetic-based methods for detecting such adulteration: the open-ended coaxial line method and the circular waveguide method. The results reveal that the open-ended coaxial line technique is particularly effective in detecting kerosene contamination, identifying levels as low as 10% by measuring changes in the dielectric constant of the gasoline-kerosene mixture. Operating in the frequency range of 0.25–1.25 GHz, this method captures subtle changes in permittivity. In contrast, the circular waveguide method evaluates contamination by monitoring shifts …

Utilizing Ensemble Learning Techniques To Enhance Corn Price Prediction: A Case Study On South Dakota, Youssef Harrath, Jihene Kaabi, Ethan Price

Research & Publications

Predicting crop prices is a complex challenge that farmers must navigate each year, but machine learning algorithms can provide valuable insights to support more informed decision making. In recent years, agricultural price prediction models have made significant advances, with architectures achieving varying degrees of success. However, ensuring the accuracy and reliability of these models remains an ongoing challenge. This research explores the use of stacking, an ensemble learning technique, to enhance the performance of base models in predicting corn prices in many regions of the state of South Dakota in the USA. We propose a hybrid architecture that combines Long …

Systems Intelligence Manager: Warfighter Dominance 2025 Technical Review Key Program, Daniel Hornberger

Space Dynamics Laboratory Publications

Objective & Background

• Objective
• Provide a governing network framework that reduces network congestion and improves connectivity, stability, and resilience
• Provide a single point for systems to connect to on varied networks, which also federates data to required entities
• Manage complex military CONOPs, controlling one or many heterogeneous unmanned platforms while coordinating collection efforts of varying sensor suites on each platform

Formulation And Characterization Of Albumin Nanoparticles For Nsclc Photochemotherapy, Faisal Mohammad Shamim Khan

USF Tampa Graduate Theses and Dissertations

Non-small Cell Lung Cancer (NSCLC) is the most common type of lung cancer and is a leading cause of worldwide cancer-related death, which is a strong motivation to develop more efficacious approaches to its treatment. This thesis outlines the construction of folate-targeted bovine serum albumin (FA-BSA) nanoparticles co-loading Chlorin e6 (Ce6), a photodynamic therapy photosensitizer, and Evofosfamide (EVO), a hypoxia-activated prodrug, to enable synergistic photochemotherapy. The 1-Ethyl-3-(3-dimethylaminopropyl)carbodiimide (EDC) is a water-soluble carbodiimide coupling reagent and used for amide bonds between carboxylic acid and amines. FA-BSA nanoparticles were prepared through a desolvation approach and stabilized through crosslinking by the carbodiimide reagent …

An Integrated Decision Support System For Bim Level 3 Implementation, Lama Abumoeilak, Salwa Beheiry, Serter Atabay

Civil and Environmental Engineering Faculty Publications

The Architecture, Engineering, and Construction (AEC) sector accounts for 39% of greenhouse gas emissions, 40% of solid waste, and 12% of potablewater usage globally, underscoring the need for sustainable, efficient practices. Building Information Modeling (BIM) offers a digital framework to address these challenges through lifecycle management, collaboration, and efficiency gains. However, most organizations remain at BIM Level 2 maturity, which limits their potential for full integration. This study proposes a comprehensive Decision Support System (DSS) to facilitate the adoption of BIM Level 3, with an emphasis on collaboration, sustainability, and data interoperability. The DSS integrates Structural Equation Modeling (SEM), Analytical …

Insights On Ai-Supported Uncrewed And Autonomous Systems Education, Brent A. Terwilliger Ph. D, John Faraca

Publications

Artificial Intelligence (AI) related technology is reshaping the educational experience in programs focused on uncrewed and autonomous systems, aviation, robotics, and aerospace, with growing implications for workforce readiness and cross-sector innovation. Early survey data, capturing student, educator, and employer perspectives, reveals that AI-supported tools are notably changing student engagement, communication, and skills development. Initial indications underscores the importance of AI proficiency and technological familiarity in hiring and workforce development, particularly in technical and operational roles. Key areas of focus include the use of AI to strengthen outreach and interactivity; enrich instruction through intelligent simulations; inform curricular improvements using data analytics; …

Tacscope: A Miniaturized Vision-Based Tactile Sensor For Surgical Applications, Md Rakibul Islam Prince, Sheeraz Athar, Pokuang Zhou, Yu She

School of Industrial Engineering Faculty Publications

The lack of tactile feedback in robot-assisted minimally invasive surgery (RMIS) limits surgeons’ ability to palpate tissues, a critical technique for locating abnormalities such as tumors. To address this challenge, we introduce TacScope, a novel, vision-based tactile sensor leveraging the magnification properties of a spherical-surface elastomer to provide tactile feedback for advanced clinical applications. TacScope features a robust, low-cost, and easyly fabricate design, enabling seamless integration into surgical robotic setups. It reconstructs high-resolution 3D geometry from variations in particle-density distribution across its elastomer surface, requiring only a single image for calibration. The curved elastomer membrane alters particle-density distribution under …

Intrinsic Defects (Vacancies And Antisites) In Neutron Irradiated Cdsip2 Crystals, Timothy D. Gustafson, Elizabeth M. Scherrer, Nancy C. Giles, Kevin T. Zawilski, Peter G. Schunemann, Jonathan E. Slagle, Kent L. Averett, Larry E. Halliburton

Faculty Publications

Cadmium silicon phosphide (CdSiP₂) is a nonlinear optical material widely used in optical parametric oscillators. Intrinsic defects (vacancies and antisites) are responsible for unwanted broad optical absorption bands in these crystals that degrade the performance of the devices. In the present work, optical absorption and electron paramagnetic resonance (EPR) spectra are acquired (at room temperature and 12 K, respectively) from a neutron-irradiated CdSiP₂ crystal. After the irradiation, the crystal is highly absorbing from the band edge near 600 nm to beyond 1.3 μm because of overlapping defect-related absorption bands. Heating to 550 °C removes nearly all the …

The Method Of Power Networks Mode Optimization In Basis Of Genetic Algorithm, Tulkin Shernazarovich Gayibov, Gulnaz Makhmutovna Turmanova

Technical science and innovation

One of the main tasks solved in planning short-term and managing operational modes of electric power systems (EPS) is the optimization of their network modes on the adjustable parameters. For modern complex EPS, this task is often characterized by the multi-extremality of the objective function, the appearance of discontinuous functions, the presence of initial information of a probabilistic and partially uncertain nature. In such conditions, solving the problem by traditional algorithms using mainly linear and nonlinear programming methods, Lagrange, gradient, etc., is associated with a number of difficulties in simplifying them and bringing them to a convenient form for calculations. …

Measures To Improve The Structure And Operating Principle Of Perovsite Light-Emitting Devices, Latofat Utkir Qizi Shuhratova, Rustam Rashidovich Kabulov, Farrux Anvar Ugli Akbarov, Anvar Akbarovich Alimov

Technical science and innovation

Since the discovery of the unique properties of perovskite materials, these materials have been used as active layers in various optoelectronic devices. In particular, perovskite-based light-emitting diodes (LEDs) have attracted the attention of many researchers as a highly efficient and versatile technology for lighting and display devices. Perovskite-based LEDs allow for tunable light emission and can be manufactured at low cost and with flexible fabrication technology. These advantages make them suitable for use in devices ranging from modern displays to wearable electronics. Despite their potential, solving problems such as material stability and industrial scale is one of the current challenges …

Methodology For Creating An Intelligent Mechatron Module Based On A Synergistic Approach, Nurbek Rustamovich Matyokubov, Temurbek Omonboyevich Rakhimov

Technical science and innovation

This article is devoted to the methodology of creating an intelligent mechatron module based on a synergistic approach. Creating a multi-coordinate intelligent mechatron module and expanding the functional capabilities of the controlled object based on them, allows to optimize the dynamic characteristics. Also, the methodology for creating an intelligent mechatronic module based on a synergistic approach allows for the integration of electrical, magnetic, and mechanical components into a single circuit, the integration of technical parameter modification, and the integration of processing functions into a single information-measuring module. In addition, the article proposes a Eurorhythm scheme for expressing how …

Insights From A Simple Mathematical Model Of Autism Spectrum Disorders, Charles F. Babbs

Weldon School of Biomedical Engineering Faculty Working Papers

This preliminary report explores insights about mechanisms of autism spectrum disorders (ASDs) gained from a mathematical model of interconnected clusters of excitatory neurons. This local, integrate-and-fire, spiking neural network is subjected to random noise from other populations of excitatory and inhibitory neurons outside the network. Its emergent behavior in response to different ratios of inhibitory to excitatory noise mimics several aspects of ASDs. The spiking neural network functions according to rules of classical neurophysiology, involving resting membrane potential, threshold potential, excitatory or inhibitory post-synaptic potentials, action potential, and refractory period. Key parameters include the incremental change in membrane potential, p …

Climate Change Projections Through Optimized Machine Learning And Deep Learning Models: A Comprehensive Analysis, Hala H. Youssef, Salma S. Mohammed, Hanan M. Amer, Abeer T. Khalil

Mansoura Engineering Journal

One major worldwide issue that has far-reaching effects on environmental stability and the avoidance of natural disasters is climate change. Developing efficient mitigating strategies depends on precise climate change forecasts. To predict important climate change indicators, including temperature fluctuations, greenhouse gas (CO2, N2O, CH4, and SF6) emissions, population dynamics, sea level changes, Arctic Sea ice extent, and Antarctica mass, this study evaluated the predictive capabilities of several Machine Learning (ML) and Deep Learning (DL) techniques. The set of machine learning algorithms includes Multiple Linear Regression (MLR), K-Nearest Neighbors (KNN), Support Vector Machines (SVMs), Artificial Neural Networks (ANN), Random Forest (RF), …

An Integrated Pcb-Based Heating And Auto-Ranging Platform For Volatile Organic Compound (Voc) Detection Using Carbon Nanotube Based Sensors, Thomas Kalach

USF Tampa Graduate Theses and Dissertations

This thesis presents the development, characterization, and integration of a novel low-cost, high-dynamic-range sensor platform for the detection of volatile organic compounds (VOCs), leveraging the unique electrical properties of carbon nanotube (CNT) thin films. The platform introduces a fully integrated auto-ranging analog front-end circuit capable of real-time resistance measurement spanning over eight orders of magnitude ranging from tens of ohms to hundreds of megaohms, without compromising signal resolution or precision. This was achieved through a digitally controlled, multi-path feedback architecture and controllable current source.

To further enhance sensor performance, the system incorporates a copper trace heater beneath the sensor array, …

Chplx: The Hpx Solution For Bridging Chapel And C++, Shreyas Swanand Atre

LSU Master's Theses

Historically, domain scientists faced steep learning curves due to low-level programming models and fragmented tooling. Between 2003 and 2008, Cray, now part of HPE, introduced the Chapel language as part of DARPA’s High Productivity Computing Systems (HPCS) program. Today, Chapel remains under active development and is used across research and production projects. In parallel, the STE||AR Group has advanced C++-based parallel programming through HPX, a standards-conforming runtime that provides lightweight tasking, futures, and distributed execution while abstracting much of the algorithmic “heavy lifting.” Yet for many domain scientists, C++ presents a steeper learning curve than Chapel. To close this complexity …

Resilience Oriented Distribution System Service Restoration Considering Overhead Power Lines Affected By Hurricanes, Kehkashan Fatima, Hussain Shareef, Flavio Costa

Michigan Tech Publications

In recent years, there has been an increase in the frequency of severe weather events (like hurricanes). These events are responsible for most power outages in power distribution systems (PDSs). Particularly susceptible to storms are overhead PDSs. In this study, the dynamic Bayesian network (DBN)-based failure model was developed for different hurricane scenarios to predict the line failure of overhead lines. Based on the outcomes of the DBN model, a service restoration model was formulated to maximize restored loads and minimize power losses using Particle Swarm Optimization (PSO)-based distributed generation (DG) integration and system reconfiguration. Three different case studies based …

Synthetically Expressive: Evaluating Gesture And Voice For Emotion And Empathy In Vr And 2d Scenarios, Haoyang Du, Kiran Chhatre, Christopher Peters, Brian Keegan, Rachel Mcdonnell, Cathy Ennis

Conference papers

The creation of virtual humans increasingly leverages automated synthesis of speech and gestures, enabling expressive, adaptable agents that effectively engage users. However, the independent development of voice and gesture generation technologies, alongside the growing popularity of virtual reality (VR), presents significant questions about the integration of these signals and their ability to convey emotional detail in immersive environments. In this paper, we evaluate the influence of real and synthetic gestures and speech, alongside varying levels of immersion (VR vs. 2D displays) and emotional contexts (positive, neutral, negative) on user perceptions. We investigate how immersion affects the perceived match between gestures …

An Innovative Association Of Fusegate And Pk-Weir, F. Lempérière, A. Chapuis, F. Del Rey, C. Bessière

4th International Workshop on Labyrinth and Piano Key Weirs

The combination on the same dam of Piano Key weir (PK-Weir) and fusible structures offers a highly effective passive solution for managing flood discharges. This concept first introduced by Hydrocoop in 2015 as « Innovative Associated Spillways » can leverage the strength of each system. More than 30 years after its first application, the returns of experience of the Hydroplus Fusegate® system applications on more than 80 dams in 25 different countries have confirmed their reliability in terms of sequentially overturning on the downstream side for the correct design flood. With their high discharge capacity at low head, PK-Weirs optimize …

Control Of Ferroelectric And Dielectric Properties Of Undoped, Fe, And Nb-Doped Single-Crystalline (001) Oriented Pb (Zr0.5ti0.5) O3 Thin Films, Mahamudu H. Mtebwa

Tanzania Journal of Engineering and Technology (TJET)

While several factors that influence the properties of ferroelectric devices have been extensively studied in bulk ceramics and polycrystalline thin films, limited is known about the same on single crystalline thin films which have great potential in memory and energy applications. This knowledge gap is largely due to the limited availability of substrates with lattice parameters suitable for supporting high-quality epitaxial growth. In this study, undoped, Fe-doped, and Nb-doped (001)-oriented Pb(Zr₀.₅Ti₀.₅)O₃ thin films were deposited using pulsed laser deposition, each with a SrRuO₃ bottom electrode and a PrScO₃ substrate. The doping concentration used is 1% for both Fe and Nb. …

Maximum Likelihood Symbol Timing Algorithm Based On Cyclic Prefix For Ofdm Systems, Kwame S. Ibwe

Tanzania Journal of Engineering and Technology (TJET)

In this paper, a blind symbol synchronization algorithm is presented for orthogonal frequency-division multiplexing (OFDM) systems, and a timing function based on the redundancy of the cyclic prefix (CP) is introduced. The existing algorithms rely on the prior knowledge of the channel energy distribution i.e. channel power profile. In practical environment the channel power profile is unknown to the receiver and its statistics are expected to be highly changing. Nevertheless, the use of pilot symbols in channel profile estimation reduces efficiency as data subcarriers are used to carry pilots instead of payload. In this paper a timing function that accounts …

Condition Optimization For The Synthesis Of Castor Oil Templated Mesoporous Silica, Godlisten Namwel Shao

Tanzania Journal of Engineering and Technology (TJET)

The present work provides suitable conditions for the synthesis of mesoporous materials with improved porosity using an optimization technique. The proposed preparation method involves forming final products by varying the amount of castor oil, media, and template removal. The obtained samples were examined by TGA, XRD, DRIFT and nitrogen physisorption studies. It was observed that the porosity of the obtained samples was dependent on the conditions under which the materials were synthesized. All synthesized materials showed the Type IV adsorption-desorption isotherm features of mesoporous, regardless of the conditions utilized during the synthesis. The sample synthesized using 2.5 g of a …

Adoption Of Agrivoltaics In Developing Countries: A Review On Challenges, Opportunities And Future Prospects, Abdi J. Athumani, Pater Makolo

Tanzania Journal of Engineering and Technology (TJET)

This paper provides a review of agrivoltaics technology and how it has been applicable in developing countries, including African countries. Agrivoltaics, the integration of agricultural production with photovoltaic energy generation, offers promising solutions to water- energy-food nexus in developing countries. This technology offers the dual benefit of increasing agricultural productivity while generating clean energy, which is very important for regions facing frequent electricity shortages and declining agricultural yields due to climate change. However, despite its potential, the adoption of agrivoltaics in developing nations remains limited in comparison to developed countries due to financial, technical and policy constraints. This paper explores …

Cnn-Based Hybrid Model For Detecting Blight Diseases In Potato Crops With Advanced Image Processing Techniques, Farian S. Ishengoma

Tanzania Journal of Engineering and Technology (TJET)

Potato production plays a vital role in global agriculture as a major food source for large populations. However, potato crops are highly susceptible to diseases, particularly Early Blight and Late Blight, which result in substantial yield losses. Timely detection and effective control of these diseases are essential for maintaining stable crop output. This study explores the integration of Convolutional Neural Networks (CNNs) and advanced image processing techniques to differentiate between diseased and healthy potato plants accurately. Two datasets comprising original and enhanced images were used to train four CNN models: InceptionV3, Xception, Densenet201, and Resnet152V2. The original images underwent background …