Digital Commons Network^™

Leveraging Convolutional Neural Networks For Through-The-Wall Radar Imaging: Challenges, Impacts, And Future Directions, Tumaini Edgar, Abdulla F. Ally, Abdi T. Abdalla

Tanzania Journal of Engineering and Technology (TJET)

Through-the-wall radar imaging (TWRI) is an essential technology for military and rescue applications; however, its performance in detecting and visualizing high-quality images of targets behind walls is significantly degraded by multipath reflections and signal attenuation. This paper reviews the current state of TWRI and its challenges, and explores the transformative potential of deep learning, particularly convolutional neural networks (CNNs), in addressing these challenges. Peer-reviewed articles published from 2018 to 2024 were analysed to examine CNN applications in addressing TWRI challenges. The analysis reveals that using CNNs, TWRI systems can be more effective by filtering wall distortions, reducing noise, lowering computational …

Emergent Dynamics In Multiplex Social Networks: Agent-Based Modeling Of Information Diffusion For Misinformation Control, Harshvardhan Prabhakar Ghongade, Anjali Ashokrao Bhadre, Shivani Agarwal, Harjitkumar Uttamrao Pawar, Harshal Subhash Rane

Northeast Journal of Complex Systems (NEJCS)

Information misrepresentation is widespread in multi-layered social networks which provide multiple avenues to communicate information. As such, it presents significant opportunities for both information integrity and public discourse to be undermined by disinformation. This paper outlines a new agent-based model, developed to capture emergent dynamics of multi-layered social networks and to help identify technical means to mitigate information misrepresentation in complex systems. A key component of this research includes a novel Multi-Layer Information Diffusion Model (MLIDM), integrating both cross-layer communication among agents, as well as heterogeneous agent behaviors and adaptive intervention strategies. Our methods employ a three-stage process to model …

Efficient Intrusion Detection For Iomt: Integrating Machine Learning, Feature Selection, And Fuzzy Logic, Ghaida Mansour Balhareth

Electronic Theses and Dissertations 2020 - Present

The internet of medical things (IoMT) has transformed healthcare by enabling real-time patient monitoring, remote diagnoses, and effective data exchange among connected medical devices and clinical systems. The increasing reliance on interconnected medical equipment has also intensified cybersecurity risks, as resource-constrained devices and wireless communication channels are vulnerable to attacks such as man-in-the-middle, spoofing, data injection, and ransomware. Intrusion Detection Systems (IDSs) play a critical role in mitigating these threats; however, traditional IDS approaches often struggle with high-dimensional IoMT data, class imbalance, and uncertainty in traffic patterns, which can increase false alarms and reduce reliability in safety-critical environments. This dissertation …

Design And Modeling Of A Piezoelectric Bimorph Energy Harvester For Automotive Structural Vibrations, Ali Abu Shawish

Thesis/ Dissertation Defenses

The focus of this thesis is on the design and modelling piezoelectric bimorph energy harvesters for vehicular utilization, particularly on harvesting energy from local structural vibrations of automotive components. The vibrations resulted from road–tire interaction and drivetrain dynamics offer the potential for harnessing electrical energy for low power electronic systems when coupled with low damping resonance harvesting devices. The main purpose of this thesis is to evaluate the potential of a piezoelectric bimorph cantilever tuned to 100–300 Hz local automotive structural vibrations for electrical energy harvesting, and to analyze its actual performance under realistic excitation conditions. The harvester's dynamic response, …

Modeling Flood-Induced Cascading Disruptions In The Indian Electronics Supply Chain Using Influence Network Analysis, Surendra Orupalli, Hiroki Sayama

Northeast Journal of Complex Systems (NEJCS)

This study investigates flood induced disruptions in the Indian electronics supply chain using influence network analysis. Monsoon floods are recurring hazards that significantly impact economic activities, logistics, and industrial productivity. This study integrates district-level rainfall data (2020 to 2025) with supply chain network models to quantify cascading failures. The methodology applies rainfall thresholds (≥ 300 mm/month) to identify flood-prone districts and constructs a stochastic influence matrix representing inter-firm dependencies. Flood propagation dynamics are modeled iteratively with a propagation coefficient (α = 0.6) and convergence threshold (ε = 10⁻⁴). The resulting disruption profiles are mapped onto company-level revenues calibrated to India-specific …

Predictive Analytics In Oncology And Ophthalmology: Machine Learning Applications For Diabetic Retinopathy And Breast Cancer, Ali Abidalkareem

Electronic Theses and Dissertations 2020 - Present

The convergence of artificial intelligence and healthcare represents one of the most transformative developments in modern medicine, with deep learning technologies emerging as powerful tools for addressing complex diagnostic challenges. This dissertation develops and validates machine learning frameworks that address critical challenges in medical diagnosis through innovative approaches to data augmentation, feature learning, and classification, focusing on two fundamental problems: Diabetic Retinopathy (DR) severity classification using multi-model convolutional neural networks (CNNs), and breast cancer stage identification using microRNA (miRNA) gene expression biomarkers. For diabetic retinopathy classification, this work proposes an ensemble deep learning framework that integrates Diffusion-based data augmentation for …

Familybloom: Examining Ecologies Of Collaboration In Family-Centered Health Tracking, Lucas M. Silva, Aehong Min, Evropi Stefanidi, Franceli L. Cibrian, Jesus A. Beltran, Cassie Zeiler, Sabrina E. B. Schuck, Kimberley D. Lakes, Gillian R. Hayes, Daniel A. Epstein

Engineering Faculty Articles and Research

Family health informatics tools can help support well-being with shared data tracking. Prior work typically focused on shared data review, but often in specific moments, like bedtime, or centered on caregiving of children or elderly members. To investigate how tracking can support mutual health collaboration between family members pervasively across daily contexts, we designed and deployed FamilyBloom, a glanceable smartwatch and home display system for mood and goal tracking. Twelve families with both neurotypical and ADHD members used FamilyBloom for three months on average. Our findings reveal how family-centered tracking created collaboration opportunities and tensions across multiple ecological systems: individual …

Implantable, Sensor-Embedded Vascular Graft Towards Wireless Monitoring Of Stenosis, Nnamdi Dike

LSU Master's Theses

Arteriovenous (AV) grafts are commonly used to provide vascular access for hemodialysis in patients with end-stage renal disease. Despite their widespread use, AV grafts are prone to complications such as stenosis and thrombosis. Early detection of these conditions remains challenging with current monitoring methods too costly or insufficient. This work presents the design, fabrication, and validation of an LC pressure sensor embedded within a model AV graft to enable real-time monitoring. The proposed system integrates a parallel-plate capacitive pressure sensor with a spiral inductor to form an LC circuit embedded within an elastomeric graft wall. The Ecoflex 00-30 dielectric layer …

Development Of New Methods For Calculating Pressure And Energy Losses For Pumping Station Water Intakes, Faxriddin Jaylovovich Nosirov, Oleg Yakovlevich Glovatsky, Jurabek Abdyrahmon O'G'Li Urolov, Abduqodirkhon Samatkhonovich Abdullakhaev, Anvar Mamur Ugli Uzokov

Technical science and innovation

The aim of this study is to improve the efficiency of water resource management methods. Improvements to the water intake of the Karshi Main Canal are considered using calculations of pressure losses at the entry and exit of liquid into the flow, which differ from pressure losses in a stationary medium. The article considers some of the methods for using renewable energy sources, where the change in gravitational potential energy does not depend on the way of using energy and the operating scheme is a gravitational energy pump. The implementation of control and monitoring systems is necessary to ensure optimal …

Theoretical And Practical Foundations Of Healthcare System Digitalization, Sanjarbek Bekturdiev Sharifboyevich Phd, Muxlisa G‘Ulom Qizi G‘Ofurova

Technical science and innovation

The digital transformation of healthcare represents a key direction in improving the accessibility, quality, and efficiency of medical services. This study examines the main components of eHealth, including telemedicine, electronic health records, cloud technologies, and mobile applications, as well as the role of international organizations in promoting national digital health strategies. Particular attention is given to the current state of digital healthcare in the Republic of Uzbekistan, where significant progress has been made in developing infrastructure and implementing information systems, although challenges related to integration, standardization, and regulatory support remain. The work identifies the main trends in the development of …

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 …

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 …

Proxyconnec: A Lora-Based Proactive Safety Communication System For Off-Grid Environments, Shruti Bhandari, Roza Shaimurat

ATU Scholars Symposium

Remote environments lacking cellular or satellite coverage present significant safety challenges. ProxyConnec was developed as a point-to-point communication system using ESP32 microcontrollers and REYAX RYLR998 LoRa modules to provide off-grid monitoring.

The system implements a proactive heartbeat model in which a beacon device transmits a signal every 1,000 milliseconds. A base station monitors this connection using a 5,000 millisecond watchdog timer. If communication is interrupted, the system immediately triggers audible and visual alerts. Unlike conventional tracking devices that depend on manual SOS activation, this design treats unexpected signal loss as a potential safety event.

The manufacturer rates the selected LoRa …

Automatic Three Phase Balancing In Utility Applications, Ryan Morris

ATU Scholars Symposium

Balancing three-phase power has become more important as modern loads like EVs and large agricultural fans create fast and uneven changes in distribution systems. Manual balancing is slow, inconsistent, and often only done during certain “seasons,” which leaves long periods of imbalance. This paper reviews existing automatic methods such as the Fast-Switching Relay method, the Practical Balancing Algorithm, and the Phase-EQ system and highlights their benefits and limitations. Based on this analysis, a new method called the Predicted Practical Balancing Algorithm (PPBA) is proposed. The PPBA combines the stability of threshold-based switching with historical data to predict when imbalances are …

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 …

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 …

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 …

Traditional And Machine-Learning Equalization Techniques For Bandwidth-Limited Short-Reach Optical Communication Channels, Abdullah Khawatmi

Thesis/ Dissertation Defenses

This thesis investigates equalization techniques for bandwidth-limited short-reach optical communication systems, with a focus on Visible Light Communication (VLC) and Step-Index Plastic Optical Fiber (SI-POF) links. Commercial light-emitting diodes and photodiode receivers impose severe bandwidth constraints, inter-symbol interference, and noise sensitivity, which fundamentally limit achievable data rates. The work addresses these impairments through systematic evaluation of traditional digital signal processing–based equalizers and modern machine-learning-based post-equalization methods.

The primary aim of this thesis is to enhance the achievable data rate and reliability of commercial short-reach optical links while maintaining practical computational complexity. Specifically, the objectives are to (i) design and experimentally …

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 …

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 …

A Platform For Acquiring And Classifying Low-Noise Electrocardiogram Signals For Applications In Cardiovascular Monitoring, Begmamat Berdimurodovich Dushanov, Narzullo Mamatov Dr.

Technical science and innovation

The early screening and continuous monitoring of cardiovascular diseases need effective acquisition and smart processing of electrocardiogram (ECG) signals. In this article, we introduce a compact platform designed for the acquisition of low-noise ECG signals and classification of the signals using a one-dimensional convolutional neural network (1D-CNN). Our compact platform consists of a low-noise analog front-end (AFE), including an instrumentation amplifier and a chain of analog filters, along with a data acquisition component designed to ensure effective suppression of baseline wander and high frequencies. Our compact platform consumes a low amount of power and can therefore be used for continuous …

Breath-Based Detection Of Liver Cancer Biomarkers Using An Swcnt-Fet Nanobiosensor: Quantumatk, Mohamed Mohieb Rashdan

Thesis/ Dissertation Defenses

There are still no tests to detect liver cancer in the early stages because it is a slow-growing and invasive type.

This study describes the use of a single-walled carbon nanotube-based field-effect transistor (SWCNT-FET) whose ability to detect hexanal, a volatile organic compound (VOC) found to be elevated in liver cancer, has been demonstrated through direct measurements from exhaled breath. The device is designed using QuantumATK with the semi-empirical Extended Hückel Hamiltonian framework in non-equilibrium Green’s function (NEGF) which shows realistic contact physics by using metallic SWCNT electrodes instead of common metal films. Through the analysis of two zigzag channels …

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 …

Ultragps: A Low-Cost, Open-Source Ultrasonic Positioning System, Scott Roelker Murillo, Nnamdi Jesse Onwuzurike

Posters - 2026

We want to raise the bar in high school robotics. In Texas, and likely in many other states as well, high school robotics has reached a roadblock when it comes to autonomous navigation. In many competitions, the autonomous portion sees few, teams successfully completing tasks that require positioning and guidance. In modern robotics, it is no longer sufficient for a robot merely be “remote controlled.” They need to be able to navigate independently and adapt to the environment around them. To achieve this goal a positioning system is needed to develop the foundational algorithms for autonomous controls. However, these systems …

Cooperative Unmanned Aerial System (Uas) Geolocation Of Emitters, Christopher Peters

Electrical Engineering Theses and Dissertations

A collection of unmanned aerial systems (UAS) can be networked as a cooperative wireless sensor array to geolocate an unknown-location RF emitter using time-based measurements. In operation, however, environmental multipath and hardware errors in sensor positioning and timing can degrade emitter localization accuracy and limit the practicality of single-snapshot solutions. This dissertation evaluates time-of-arrival and time-difference-of-arrival (TOA/TDOA) geolocation for cooperative UAS arrays under realistic error sources and develops geometry-control strategies that actively reduce localization uncertainty through iterative UAS repositioning.

This work studies the Location on a Conic Axis (LOCA) method for emitter localization. Using Monte Carlo simulations with hardware error …