Digital Commons Network^™

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 …

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 …

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, …

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 …

Evaluating Square Gradient Theory For Correlation And Prediction Of Surface Tension, J. Richard Elliot

University Research

The ESD EOS [Elliott, Suresh, and Dohohue, IECR 1990, 29, 1476] is incorporated into the open-source Square Gradient Theory (SGT) library published by Mejia et al. [Mejia, Müller, and Chaparro-Maldonado, J. Chem. Inf. Model. 2021, 61, 1244]. The combined formalism is evaluated for accuracy compared to experimental measurements and empirical correlation methods. Earlier evaluations of the ESD EOS have shown it to provide accuracy like other EOSs for vapor pressure, vapor–liquid, liquid–liquid, and solid–liquid equilibria where the databases covered roughly 500 compounds and 100–200 mixtures each. For surface tension, a database of measured values for roughly 1000 compounds has been …

Quantifying Dag-Ness: A Multi-Component Framework, Erik Csikos

Northeast Journal of Complex Systems (NEJCS)

Directed acyclic graphs (DAGs) are important structures across many disciplines, including mathematics and network science. They are especially useful in modeling causal and hierarchical relationships in a wide variety of applications. The primary
features of a DAG, directedness and acyclicity, are traditionally treated as binary. A graph is either DAG or it is not. Because of this, graphs are not usually interpreted as partially acyclic or partially directed. To address this gap in understanding, we
introduce a framework, consisting of five components, that will provide a continuous measure of DAG-ness. This measure will take into account edge acyclicity, node cyclicity, …

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 …

Reducing Systemic Bias In Behavioral Targeting Using Explainable Ai: The Harmonia Complex Systems Approach, Ruchira Deokar, Preethi Nanjundan, Jossy P. George, Carlos Gershenson

Northeast Journal of Complex Systems (NEJCS)

Behavioral targeting is a key part of the modern advertising web's algorithmic engine. However, it is unclear whether optimization processes worsen bias, promote unchecked spread in filter bubbles or lower overall users' trust levels. This paper introduces HARMONIA (Holistic Adaptive Regulatory Model for Optimizing Non-transparent Intelligent Advertising), a comprehensive, data-driven Explainable Artificial Intelligence (XAI) framework aimed at transforming behavioral targeting via transparency, interpretability, and adaptive ethical regulation. This paper conducted a comprehensive Explorative Data Analysis (EDA) on the public Criteo Display Advertising Dataset, which contains over 45 million records, to identify patterns in high-dimensional user-ad interaction space. This analysis uncovered …

Relation Between Swelling Potential And Swelling Pressure For Different Types Of Expansive Clay Of New Cairo, Sherouk Hany Mohamed, Amr Radwan, Mohammed Rabie, Hussein Mostafa

HBRC Journal

The purpose of this paper is to present correlations that may help in predicting swelling pressure (P_S) and swelling potential (SP) for expansive clay, which can contribute to solving engineering problems such as cracking, shifting or other structural damage, that may occur, if the behavior of this type of soil is not taken into consideration. Therefore, in this research, five different samples of expansive clay soils were collected from different site locations in New Cairo, Egypt. Then, these samples were dried, pulverized and passed through sieve No. 40 (0.425 mm). The samples were prepared initially at maximum dry …

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 …

Thermoacoustic Effects Of A Variable Equivalence Ratio In A Single Element Methane Combustor, Carter Green

Doctoral Dissertations and Master's Theses

Combustion instability is one of the leading factors in limiting the progress and innovations of liquid rocket engines and power plants. Under certain operating conditions, unsteady heat release and acoustic wave interactions can couple and lead to instabilities, such as self-sustaining pressure oscillations, that can lead to reduced combustor performance and potentially hardware damage. In this project, the thermoacoustic effects of controlling the equivalence ratio of a single-element natural gas combustor were modeled and analyzed. The project used Fidelity Pointwise for meshing, ANSYS Fluent for modeling, ERAU VEGA HPC for computing, and MATLAB for acoustic analysis. A numerical model of …

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 …

Scenario-Based Pareto Analysis For Multi-Objective Optimization Of Process Parameters To Improve Life Cycle Impacts: Case Study Of Ge Production, Dennis Dadzie

Miners Solving for Tomorrow Research Conference

Growing demand for critical minerals increases the need for clear evidence on the environmental burdens of their production. Life‑cycle assessment (LCA) quantifies impacts, but it does not by itself show how to navigate competing environmental performance improvement goals. We examine 63 process configurations for single‑crystal germanium made via chlorinated distillation using five indicators: global warming potential (GWP), water consumption (WC), fine particulate matter (FPM), terrestrial acidification (TA), and cumulative energy demand (CED). Across scenarios, WC is negatively correlated with GWP, weakly related to FPM, TA, and CED, while the other four indicators are strongly positively correlated. Pareto analysis highlights a …

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 …

Wettability Evaluation Via Contact Angle And Data Mining For Enhanced Oil Recovery, Syasya Wadihah Md. Ja’Afar, Bashir Busahmin

Journal of Sustainable Mining

The oil industry has used many enhanced oil recovery (EOR) strategies to increase crude oil production from reservoirs, particularly as production begins to fall. With a significant quantity of hydrocarbon reserves still existing in the reservoirs, improved oil recovery techniques have the potential to increase oil production, with wettability alteration playing a significant role. To date, there has been no comprehensive investigation of wettability in Brunei's sandstone reservoir. The goal of this research is to determine wettability by contact angle measurement and data mining approaches based on the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) algorithm. …

Online Path Planning For Disaster Response In The Presence Of Unknown Road Disruptions: A Comparison Of Research And Practice, Jannatul Shefa, Ashlea Bennett Milburn, Erica Gralla

Industrial Engineering Faculty Publications and Presentations

Purpose This paper aims to illuminate gaps between theory and practice in one crucial area of disaster logistics: transportation management between staging areas and final destinations, on uncertain and disrupted road networks. Relevant current practice in federal, state, nonprofit and private disaster response organizations in the USA is described and compared to pertinent assumptions in the literature on disaster response online path planning under uncertainty. Design/methodology/approach The study uses a qualitative approach. The disaster response routing literature informed the development of an interview guide used for in-depth interviews with disaster response logistics practitioners. Collected data were coded to identify how …

Ais26s: Genai And Llms For Cybersecurity, Political Sciences, Transportation Security, And Resiliency, Latifur Khan

Paul English Applied Artificial Intelligence (AI) Institute Publications

This presentation examines the role of generative artificial intelligence (GenAI) and large language models (LLMs) in addressing complex challenges across cybersecurity, political science, and transportation security. Dr. Latifur Khan discusses how advanced AI methods can be applied to threat detection, data analysis, and decision-making in high-risk and data-intensive environments. The talk highlights interdisciplinary applications of LLMs, emphasizing their ability to extract insights from large-scale data, improve system resilience, and support intelligent infrastructure. Emerging research directions and practical implications for real-world deployment are also discussed.

Triple Active Bridge Implementation And Control, Nehemiah Milton

Miners Solving for Tomorrow Research Conference

The Triple Active Bridge (TAB) is a three-port power converter that allows power flow in both directions with galvanic isolation. This has a wide range of applications, like high-frequency DC-DC conversion, electric vehicles, microgrids and renewable energy systems. To control the TAB during operation, two phase shift parameters between the bridges are adjusted. In this presentation, I will showcase the software and simulation optimizations which extend previous work by reproducing hardware results which align with simulations. I will also go over the knowledge I’ve gained and the skills acquired through this project.

Analysis Of Autonomous Vehicle Survivability To 5g Communication Errors, Sydney Clark

Miners Solving for Tomorrow Research Conference

Autonomous vehicles rely on low-latency, high-reliability data exchange for real-time perception and control. Disruptions such as packet loss, latency variation, protocol-level errors, and malicious interference can pose significant safety risks to both passengers and surrounding environments. This project aims to evaluate, quantify, and predict the survivability of autonomous vehicle systems to communication errors, with focus on 5G network environments. The impact of these communication impairments on vehicle stability and control will be investigated through high-fidelity cyber-physical simulation of the vehicle and its surrounding environment. Experiments designed to capture varying network conditions will be used to assess a broad range of …