Engineering Commons^™

Using Geoscience To Empower A Community And Provide Access To Potable Groundwater, Hendratta Ali Dr

SACAD: Scholarly Activities

Access to potable water remains challenging around the world and remains one of the UN Sustainable Development Goals for 2030. Barriers to clean water access are exacerbated by the lack of technical expertise, limited funding for education and training, and the absence of reliable infrastructure that provides access to clean water. The Geoscientists Without Borders program, supported FHSU with funding to test, explore and provide access to clean potable groundwater to a rural community in Cameroon. We conducted water quality analyses, identified, mapped and located deep aquifers in fractured metamorphic rocks. Water quality analyses showed acidic pH and elevated amounts …

Analysis And Study Of Telemetry Systems For Directional And Horizontal Well Drilling, Jahongir Abdiganiyev Erkin Ugli, Sherali Halloqovich Umedov

Technical science and innovation

The article discusses the issues of reducing non-productive drilling time during the construction of directional and horizontal wells. The main focus is on the analysis of drilling conditions in complex geological and high-temperature environments. Particular attention is paid to drilling conditions in the territory of the Republic of Uzbekistan, with a specific study of data from the Boysun and Ustyurt regions. An analysis and study of the performance of telemetry systems available on the market, as well as their main technical characteristics, have been conducted. Key factors affecting the accuracy of wellbore trajectory measurements under various geological and technical conditions …

Elemental And Mineralogical Characterization Of Permo-Carboniferous Coal In The Ngaka Coalfield, Southwest Tanzania: Implications For Coal Quality Variation, John W. Gama, Justina J. Saroni, Remigius L. Gama

Tanzania Journal of Science

Coal from heterolithic seams exhibits distinct chemical characteristics due to interbedded non-coal beds, which influence its quality and usability. Despite extensive research in these settings, the elemental and mineralogical characteristics of the heterolithic sequences of the Mchuchuma Formation (K2) in the Ngaka Coalfield remain poorly documented. This study provides the first detailed assessment of K2 seams across five active mine sites. Eleven representative samples were analyzed using proximate, elemental, and mineralogical techniques, supported by Pearson correlation, binary analysis, and Principal Component Analysis. Proximate analysis revealed that ash content varies across mine sites, with values ranging from 9.17 to 25.03%, volatile …

Design Of Virtual Impedance Controller For Parallel-Connected Converters In A Microgrid, Manyanda Makoye, Francis Mwasilu, Peter M. Makolo, Jackson Justo

Tanzania Journal of Science

This paper addresses the significant challenge of inaccurate power sharing among Distributed Generators (DGs) in islanded microgrids, which is primarily caused by mismatched feeder and line impedances. Conventional decentralized control solutions often fail to ensure accurate power sharing, especially when line impedances are resistive. To overcome this, the paper proposes a robust, coordinated Virtual Impedance Control (VIC) strategy for DGs. This method implements fixed virtual resistance and virtual inductance to standardize the output impedance characteristics of parallel-connected inverters, thereby minimizing impedance discrepancies and enhancing system stability through increased damping. The theoretical analysis and design of the VIC were validated through …

Mapping Of Petroleum-Prospective Structures In The Jurassic Complex Of The Western Aral Uplift Based On Seismic Attributes, Yuliya Leonidovna Salaydinova, Marina Georgievna Yuldasheva

Technical science and innovation

To solve the problems of identifying and mapping prospective structures, comprehensive analysis of 3D seismic attributes is widely used at the present stage of geological research; it was applied to assess the petroleum potential of the Jurassic rock complex in the Aral Sea offshore area of the Ustyurt region. The study integrates structural mapping on the tops of Permo-Triassic and Jurassic horizons, attribute volumes (Variance/Coherence, Sweetness, root-mean-square (RMS) amplitude, Envelope) and generalized spectral decomposition (GSD, 19-41 Hz), combined with well-log and well-test data from the Western Aral, Meros, Dengiz and Karakum areas. Variance attributes were used to delineate fault zones …

Impact Of Collodion Thickness On Fission Track Generation Within Lexan Employed For Nuclear Forensic Analyses, Ryan K. Chapman, Zachary P. Meisel, Abigail A. Bickley

Faculty Publications

We report results from a computational study of fission track damage within a Lexan substrate caused by ²³⁵U suspended within a collodion film of varied thickness. MCNP6.3 was used to model energy deposition and displacements per atom within a Lexan film coated by a film of collodion, located within the air-filled 6 inch dry tube of a TRIGA reactor. The collodion layer was varied between 20 and 100 μm thickness, resulting in an 8.8% difference in energy deposition and 12% difference in displacements-per-atom within the Lexan substrate. These findings indicate that collodion adhesive thickness has a moderate impact on …

A Dynamic Systems Framework For Customer Lifecycle Management: From Latent State Discovery To Robust Control Policy, Ali Nasirzonouzi

Northeast Journal of Complex Systems (NEJCS)

Traditional marketing often relies on static strategies that fail to capture dynamic customer behavior. This paper introduces an integrated framework to model and control the customer lifecycle, bridging the gap between empirical data and computational simulation. Using the Customer Personality Analysis dataset, we implemented a five-stage methodology. We first identified three distinct customer segments (At-Risk, Standard, High-Value) using Gaussian Mixture Models. To address the lack of longitudinal data, we calibrated a normative transition model based on customer inertia principles. Our analysis revealed that marketing effectiveness is highly state-dependent; notably, At-Risk customers exhibited a 33.5% lift when targeted with catalogs. Leveraging …

Escaping Isolation: An Analysis Of Virtual Machine And Container Breakout Vulnerabilities, Felix Iov

Cybersecurity Undergraduate Research Showcase

Cloud computing providers rely on multi-tenant architectures to maximize resource efficiency. This infrastructure depends on virtualization, which provides isolation between clients. This comes primarily in the form of Virtual Machines (VMs) and Containers. However, “breakout attacks” or “escapes” are a critical threat where attackers bypass these isolation layers to gain unauthorized access to the host system and neighboring environments. This paper surveys virtualization escape threats and analyzes three case studies: a runc container escape (Leaky Vessels), a VMware ESXi VM escape (VSOCKPuppet), and an NVIDIA GPU container escape (NVIDIAScape). Each demonstrates different attack surfaces, including file descriptor misuse, kernel driver …

Understanding The Binding Of Nickel(Ii) Bromide To A Zirconium Metal-Organic Cage For Heterogeneous Catalysis, Luci Green

Caroliniana Undergraduate Research Journal

Heterogeneous catalysts offer inherent advantages in improving the sustainability of industrial chemical processes. Their high ease of separation and recyclability has the potential to reduce the cost, waste, and energy consumption of processes that currently rely on homogeneous catalysts. Metal–organic cages (MOCs) are an attractive material for heterogeneous catalysis due to their discrete and highly tunable structures, which can be functionalized by binding these complexes with catalytically active metals. The specific objective of this study is to provide preliminary insight into the binding of nickel(II) bromide (NiBr₂) to zirconium MOCs, which was done by studying the binding of …

Aiw26s: Applied Llms, Chengjie Zheng

Paul English Applied Artificial Intelligence (AI) Institute Publications

This workshop introduces the concept of applied large language models (LLMs), focusing on how users can move from simple prompt-based interaction to building structured, repeatable AI-driven workflows. Participants explore how AI enables faster prototyping, lowers barriers to entry, and expands who can participate in building technology. Through a hands-on demonstration, attendees learn how to transform raw inputs into meaningful outputs such as summaries, key concepts, and actionable steps. The session emphasizes the importance of clear problem definition, iterative refinement, and critical evaluation when working with AI systems.

Comparison Of Anomaly Detection Methods On Event-Based Vision Sensor Data In A High Noise Environment, Will Johnston, Anthony L. Franz, Shannon R. Young, Rachel Oliver, Zachary Theis, Brian Mcreynolds, Michael L. Dexter

Faculty Publications

Event-based vision sensors (EVSs) provide unique frequency analysis opportunities due to their event data output and high temporal resolution. Anomaly detection methods used in hyperspectral analysis can be used on the event frequency spectra to detect targets. However, the introduction of a strong, flickering interfering source can reduce the EVS sensitivity and obscure targets of interest. Previous work presented a method showing that targets could still be detected through an overwhelming source using frequency analysis, background suppression, and statistical filtering. This paper extends that research and compares the ability of five different eigenanalysis anomaly detection methods (principal component background suppression …

Digital Transformation And Market Microstructure: Analyzing The Impact Of Algorithmic Trading On National Stock Exchange Of India Price Discovery Mechanisms Through Complex Systems Theory., Mukesh Bhaskar Ahirrao, Harshal Anil Salunkhe, Vishal Sunil Rana

Northeast Journal of Complex Systems (NEJCS)

Abstract

This research examines the evolution of market microstructure at the National Stock Exchange of India (NSE) from 2020 to 2024, a period characterized by substantial growth in algorithmic trading from 35% to 44% of total trading volume. Using market microstructure data and analytical techniques grounded in complex systems perspectives, the study documents temporal patterns in price discovery, liquidity, volatility, and market efficiency associated with this digital transformation.

The analysis reveals several notable changes in market characteristics. Transaction costs improved significantly, with bid-ask spreads declining by 23.4% and market depth increasing by 18.1%. Price adjustment half-life decreased by 50%, indicating …

Optimizing Controller Speed And Torque To Reduce Drivetrain Stress, Selene J. Welch

SACAD: Scholarly Activities

This project investigates how torque delivery from the motor controller affects mechanical stress on the rear freewheel ratchet mechanism of a three-wheel electric race car. Excessive initial torque has caused accelerated wear and tear on the ratchet mechanism, reducing drivetrain reliability during Kansas ElectroRally competitions. Preliminary testing showed that slower, gradual acceleration prevented malfunction and allowed the vehicle to maintain top speed reliably. Prior research shows that torque-control strategies strongly influence electric-drive performance. Current research focuses on optimizing the controller’s torque and speed using the Alltrax Software ToolKit to reduce drivetrain tension while preserving the car’s performance capabilities.

Analysis Of The Effects Of Magnetic Field, Heat Transfer, And Thermal Radiation On Blood Flow Through Bifurcated Artery To Enhance Tumor Treatments, Abdullahi Isah, Dauda Gulibur Yakubu, Ali Musa

Tanzania Journal of Science

The work presents the effects of some pertinent parameters on blood flow through bifurcated artery to enhance tumor treatments. Combining appropriately the basic equations, together with the fractionalized Maxwell fluid model allow us to determine the velocity, temperature and concentration of blood flow through bifurcated artery. The study adopted the Atangana-Baleanu fractional time derivative on fluid model to describe the non-Newtonian behavior of blood flow. The numerical simulations were performed using the combined Laplace transform and the method of undetermined coefficients and the results obtained with the aid of Mathcad software were simulated and presented graphically. From the graphical results, …

Complex Systems Mapping Of Fiscal Growth Dynamics At Strategic Maritime Chokepoints Using Time-Series Slopes, Rahul Balamurugan, Preethi Nanjundan, Avichal Sharma

Northeast Journal of Complex Systems (NEJCS)

This study examines how maritime and trading states allocate public resources between defence, health, and economic growth around three strategic chokepoints the Strait of Malacca, the Strait of Hormuz, and the Suez Canal. The analysis extends the classic “guns versus butter” framing by treating defence and health spending as co-evolving components of an interconnected fiscal-growth system. Using World Development Indicators data (1999-2024), trend slopes are estimated for military spending (% of GDP), healthcare spending (% of GDP), and GDP growth (annual %). Two derived indicators are computed, a defence-to-health slope ratio (military slope/health slope) and a fiscal-balance proxy (health slope …

Arum–D Nexus: Adaptive Reflexive Urban Metabolism For Complex Construction And Demolition Waste Governance In Bengaluru, Talat Naaz, Rosewine Joy

Northeast Journal of Complex Systems (NEJCS)

Urban material systems exhibit nonlinear dynamics governed by feedback, adaptation, and emergent coupling among institutions, markets, and behaviors. Construction and demolition (C&D) waste in Bengaluru is a great example of such complexity, where fragmented regulation, informal actors, and digital asymmetries coalesce into unstable waste flows and resource leakages. This study conceptualizes Bengaluru’s C&D waste system as a Complex Adaptive System (CAS), where institutional, market, behavioral, and metabolic subsystems co-evolve through nonlinear feedback interactions. A meta-analysis of secondary literature combined with benchmarking of government datasets is used to evaluate two key complexity indicators, i.e., response speed and feedback density. The advancement …

Ai Method For Classification Of Diagnosis Of Near-Infrared Breast Lesion Images, Kaiquan Chen, Fangyang Shen, Honggang Wang, Zhengchao Dong, Jizhong Xiao, Ming Ma, Afroza Aktar, Christopher Chow, Wenxiong Zhang

Publications and Research

In near-infrared optical breast lesion screening and diagnosis systems, high-speed four-dimensional scanners can dynamically acquire tens of thousands of lesion images within a five-minute period. Currently, manual computer annotation is required to generate standard samples from these scanned breast lesion images, a process that depends heavily on physicians with clinical expertise. On average, a single physician can annotate only approximately ten samples per working day. As a result, this process is time-consuming and labor-intensive, and the collected samples often suffer from low accuracy, large variability, and limited diagnostic reliability. Several AI-based annotation tools, such as QuPath, HALO AI™, and X-AnyLabeling, …

Multiple-Valued Quantum Automata For Robotics, Yuchen Huang

Dissertations and Theses

This dissertation introduces a new type of quantum automata, their encoding and circuit realization. I concentrate on possible applications in robotics. Several methods and application of quantum automata and quantum circuit-based controllers for elementary robotic systems, with a focus on humanoid robot motion, emotion, and behavior generation are illustrated in detail. The research introduces several novel methodologies that bridge quantum computing principles with robotic control, aiming to overcome the limitations of classical deterministic and probabilistic approaches.

The dissertation first presents a quantum-circuit-based framework for generating non-repetitive and expressive (e)motions in a humanoid robot actor, using superposition and entanglement to produce …

Solving Wordle Using Information Theory, Talal Aladaileh, Donald Stephens, Mallak Alqaisi, Congyu Wu

Northeast Journal of Complex Systems (NEJCS)

Wordle, a popular word-guessing game, challenges players to identify a five-letter secret word through iterative guesses and feedback on letter placement. The players must figure out the secret word within six guesses. After each guess, the letters will be color-coded based on different criteria. Optimizing the choice of guesses is critical for maximizing success within the limited attempts allowed. In this study, the application of Shannon entropy is explored as a strategy for selecting words that maximize information gain at each step of the game. By quantifying the uncertainty reduction achieved by potential guesses, this method prioritizes words that are …

A Multi-Layer Complex Adaptive System Framework For Ai-Driven Robo-Advisory Services, Jesty Mariam Philip, Mohit Boralkar, Alwin Joseph

Northeast Journal of Complex Systems (NEJCS)

The rapid integration of Artificial Intelligence (AI) into investment advisory services has changed financial decision-making, giving rise to adaptive robo-advisory systems capable of real-time analysis, personal recommendations, and autonomous portfolio optimization. Existing research evaluates these systems primarily through technological performance or investor adoption, overlooking the complex feedback-driven interactions that emerge when AI analytics, data environments, and human behavior operate together. This study addresses this gap by conceptualizing AI-enabled robo-advisors as a multi-layered Complex Adaptive System comprising historical data, real-time data, AI analytics, investor perception, and decision-making layers. A simulation model grounded in machine learning dynamics, behavioral finance, and complexity theory …

Regional Drought Modulation By Enso And Iod As Indicated By The Standardized Precipitation Index, Arpit Tiwari, Preethi Nanjundan, Tanu Sharma, Ravi Ranjan Kumar, Satyaban Bishoyi Ratna

Northeast Journal of Complex Systems (NEJCS)

Understanding the modulation of drought by large-scale ocean–atmosphere teleconnections is crucial for strengthening drought prediction and resilience in India. This study investigates the influence of the El Niño–Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD) on meteorological drought characteristics across India from 1950 to 2024 using the Standardized Precipitation Index (SPI) at a 12-month timescale. Drought events were quantified in terms of frequency, duration, severity, and intensity and linked to ENSO–IOD variability through composite, correlation, and mediation analyses. Results reveal that El Niño events consistently correspond to widespread and severe droughts, particularly over central and southern India, with drought …

Preliminary Sonification Of Enso Using Traditional Javanese Gamelan Scales, Sandy Hs Herho, Rusmawan Suwarman, Nurjanna J. Trilaksono, Iwan P. Anwar, Faiz R. Fajary

Northeast Journal of Complex Systems (NEJCS)

Sonification—the mapping of data to non-speech audio—offers an underexplored channel for representing complex dynamical systems. We treat El Niño-Southern Oscillation (ENSO), a canonical example of low-dimensional climate chaos, as a test case for culturally-situated sonification evaluated through complex systems diagnostics. Using parameter-mapping sonification of the Niño 3.4 sea surface temperature anomaly index (1870–2024), we encode ENSO variability into two traditional Javanese gamelan pentatonic systems (pelog and slendro) across four composition strategies, then analyze the resulting audio as trajectories in a two- dimensional acoustic phase space. Recurrence-based diagnostics, convex hull ge- ometry, and coupling analysis reveal that the sonification …

Threat-Analysis Oriented Digital Twinning Of Ml-Powered Future Autonomous Weapon Systems, Thomas Neubert

Doctoral Dissertations and Master's Theses

Warfare is undergoing a rapid transformation with the integration of artificial intelligence (AI) and machine learning (ML) into autonomous weapon systems (AWS) for perception, decision support, and control. As these systems become more software-defined, their cyber attack surface expands across sensing, communications, autonomy logic, and human-machine interfaces. As human oversight diminishes, ensuring the cybersecurity, resilience, and reliability of these systems becomes critical to mission success. This thesis investigates how a digital twin-driven threat modeling framework that integrates system-centric analysis with adversary-informed methodologies can support structured cybersecurity vulnerability evaluation and defensive strategy development associated with ML-powered AWS. First, the study analyzes …

Synthesis And Hydrothermal Evaluation Of Poly(Styrene Phosphonate) For Conformance Control In Geothermal Reservoirs, Sara Mccauley

Miners Solving for Tomorrow Research Conference

As atmospheric carbon dioxide levels continue to rise, geothermal energy has emerged as a promising energy alternative to fossil fuels. A barrier to widespread implementation and energy production efficiency is macro-heterogeneity of the rock matrix. Cracks, void spaces, and flow conduits divert fluid flow away from unswept portions of the geothermal reservoir and can cause cooling of the reservoir. Flow heterogeneity has been treated in oil reservoirs by injecting hydrogel particles that travel preferentially to ultra-high permeability zones and selectively block fluid flow in these regions. We are applying polymer hydrogels that withstand hydrothermal conditions of 225 up to 275°C …

Robustness Of Fuzzy Artmap To Adversarial Attacks And Progressive Adversarial Training For Streaming Learning, Shane Cairns

Miners Solving for Tomorrow Research Conference

Incremental learners deployed on streaming data must remain robust to evolving adversarial perturbations, yet most adversarial-robustness studies assume offline multi-epoch training with repeated access to historical data. We investigate adversarial robustness in Fuzzy ARTMAP, a prototype-based Adaptive Resonance Theory model that supports single-pass learning without replay. We propose WB-Softmax, a differentiable relaxation that aggregates category-level activations into class-level scores for gradient-based attacks. WB-Softmax PGD achieves 89–100% attack success on vanilla models, exceeding transfer and query-based baselines. We then study adversarial training under true streaming constraints by comparing offline versus online adversarial example generation and standard versus selective updates. Offline adversarial …

Controlled Gelation Of Co₂-Resistant Polymer Systems For Improved Conformance In Co₂-Eor, Maryam Sharifi Paroushi

Miners Solving for Tomorrow Research Conference

This presentation introduces a CO₂-resistant hydrogel developed to control fluid movement and improve CO₂ injection performance in subsurface reservoirs for Enhanced Oil Recovery (EOR) and Carbon Capture and Storage (CCS). Conventional polymer gels often lose strength in CO₂-rich environments, resulting in weak plugging, early breakdown, and ineffective flow control. To address this limitation, a sulfonated HPAM-based gel system crosslinked with chromium was developed. The effects of polymer concentration, molecular weight, crosslinker ratio, ionic strength, and pH were investigated to better understand gelation behavior and performance. The formulation exhibited controlled gelation, strong resistance to temperature and CO₂, and minimal shrinkage over …

A Method To Accelerate Rock Breakage With Soundless Chemical Demolition Agents, Patrick A. Darko, Hani S. Mitri

Journal of Sustainable Mining

Soundless chemical demolition agents (SCDA) are recognized as a safe and sustainable alternative for rock breakage, with the potential to reduce reliance on explosives in mining. However, their mechanical performance is considerably hampered in the extreme cold climate, with slow or no rock fracturing observed. To overcome this deficiency, two methods were developed in recent studies by 1) electric heating the SCDA borehole with high-temperature wire, and 2) increasing the SCDA mixing water temperature. Good results were obtained with both methods. This paper explores the merits of a hybrid approach combining the two methods to further enhance the SCDA efficiency …

Research Status And Development Trend Of Acidification And Permeability Improvement Technology For Low-Permeability Coal Seam, Shaochuan Chen, Yun Lei, Fuchao Tian, Jie Kang

Journal of Sustainable Mining

Low-permeability coal seams in China are often characterized by mineral-clogged pore-fracture systems, severely limiting coalbed methane (CBM) extraction efficiency. Acidification technology, which involves injecting acidic solutions into coal seams to dissolve minerals and enhance permeability, has emerged as a promising approach. This paper systematically reviews the mechanisms, laboratory findings, and field applications of acidification technology for permeability enhancement in low-permeability coal seams. Key findings include significant improvements in pore connectivity, reductions in gas adsorption capacity, and enhanced gas extraction rates post-acidification. Field tests demonstrate that acid fracturing can increase gas extraction volume by 4-7 times. The study also identifies current …

Improving Energy Reliability In Mining Areas Through Modelling And Control Of Resonance Phenomena In Solar-Integrated Power Systems, Yurii Papaika, Gennadiy Pivnyak, Maksim Malyshko, Yuliya Pazynich, Natalia Howaniec, Adam Smolinski

Journal of Sustainable Mining

This study addresses the emergency and operational transient processes that arise when integrating large-scale solar power plants (SPPs) into electrical load nodes, particularly under conditions of limited power system capacity. With the increasing penetration of distributed generation in Ukraine's energy landscape, challenges related to electromagnetic compatibility and harmonic resonance are becoming more prominent. The research builds upon the foundational work of leading Ukrainian scientific schools and focuses on the specific resonance phenomena observed during the operation of solar inverters in medium-voltage networks, especially in regions with high industrial and mining Energy demand. A novel algorithm is proposed for determining the …

Feasibility Study Of Barite Sourcing From Sediments Emerging Due To Treatment Of Waste Water From Coal Mining, Hubert Makuła, Zbigniew Bzowski, Bogusław Michalik

Journal of Sustainable Mining

The accumulation of mine water in settling ponds, which is discharged due to coal mining, allows them to be cleaned out of suspension, and it is the reason for the accumulation of hundreds of thousands of tons of sediments. One interesting mineral enclosed in these sediments is barite, which is considered in the EU as a critical raw material, but it also contains radium originating from formation water.

The effective barite separation and its beneficiation could constitute a win-win solution because then it would be possible to obtain the valuable radium concentrate for further processing, e.g., in nuclear medicine, and …