Digital Commons Network^™

Water-Driven Solid Electrolyte Interphase Governs Continuous-Flow Ammonia Electrosynthesis, Peng-Bo Liu, Sheng-Liang Zhai, Ji Huang, Zhong-Shuo Zhang, Jie Zeng, Shao-Feng Li

Journal of Electrochemistry

Flow-cell architectures have emerged as a powerful platform for continuous and stable lithium-mediated nitrogen reduction (Li-NRR), enabling ambient-condition electrochemical ammonia synthesis and offering a promising alternative to Haber-Bosch processes. However, Li-NRR is exceptionally sensitive to trace water, and even minor variations in water content can profoundly alter interfacial chemistry. Here, we systematically investigate how initial water concentration affects Li-NRR performance in a continuous-flow cell. Excess water drives the formation of a thick solid electrolyte interphase (SEI) layer, which may impede nitrogen access to metallic lithium and hinder lithium-ion transport. As a result, the ammonia Faradaic efficiency collapses from ~61% to …

Insertion Of Noble Metal Free Cathodic Catalyst Layer With Fe-N-C Catalyst For Boosted Performance Of Pemfc, Shi Zhou, Muhammad Tariq, Asif Nadeem Tabish, Muhammad Salman, Fan-Di Ning, Muhammad Rayyan Tayyab, Ran-Ran Peng, Meng-Geng Hao, Wen-Mu Li, Xiao-Chun Zhou

Journal of Electrochemistry

Economical Fe-N-C catalysts are considered as promising alternatives to platinum group metal catalysts for proton exchange membrane fuel cells (PEMFCs). Despite exhibiting robust activity on rotating disk electrodes, their performance within membrane electrode assemblies often experiences limitations, such as decreased O₂ diffusion, high H₂O₂ formation, low proton conduction, and a lower electron transfer number. In this study, key factors, including proton transport, electron conduction, and gas diffusion within air-breathing PEMFCs, have been investigated by adjusting cathode catalyst layer (CCL) compositions. From the experimental results, the optimal peak power density was obtained when the loading of Fe-N-C …

Molecular Catalysts For Electrochemical Nitrogen Activation Toward Sustainable Ammonia Synthesis, Jin-Xiu Han, Hao Xue, Xian-Biao Fu

Journal of Electrochemistry

Homogeneous electrocatalytic nitrogen reduction reaction (NRR) provides a powerful framework to interrogate molecular nitrogen-fixation pathways under mild conditions. By tuning the metal center, ligand architecture, and reaction medium, these systems enable capturing key intermediates and delivering mechanistic insight at the molecular-level resolution. Nevertheless, advances remain constrained by highly reduced operating potentials, intense competition from the hydrogen evolution reaction (HER), limited durability in turnover, and inadequate long-term stability.

In this review, we take electron delivery to the molecular active site as the guiding principle for organizing homogeneous electrochemical N₂ activation and transformation. We classify reported systems into direct electron transfer …

A Machine Learning Framework For Ddos Attack Detection In Sdn-Enabled Mobile Wireless Networks, Ishita Sharma, Satyam Agarwai, Shashi Shekhar Jha, Sumit Chakravarty

Faculty Articles

Attacks on network components and devices pose a significant threat to service continuity, necessitating robust detection mechanisms. This paper presents a Distributed Denial of Service (DDoS) attack detection framework tailored for heterogeneous mobile wireless networks within a Software-Defined Networking architecture. A two-tier model is proposed: localized attack detection at access points (APs) using a Multi-Layer Perceptron (MLP) classifier, and centralized detection under mobility at the controller using a Long Short-Term Memory (LSTM) model. The system incorporates novel traffic features such as flow count, speed of source IP, source and destination IP address entropy, proportion of bidirectional flows, and handover frequency, …

Diode-Pumped Solid-State (Dpss) Laser, Ryan Farrar, Kiahna Taylor, Jules Stone, Finn Mcmanus, Zoe Kreisler, Reis Knowles

Electrical Engineering and Computer Science Student Publications

The objective of this project is to create a working Nd:YAG laser design using an 808nm laser instead of a traditional flashlamp. The reason for the 808nm laser is to enable controlled lasing, and furthering accuracy & efficiency relative to a flashlamp.

Chess Observation Based Operable Technology (Cobot), Brandon Goerz, Jeremy Hay, Luke Jacobsen, Sean Kalkiewicz, Logan Steele

Electrical Engineering and Computer Science Student Publications

This project aims to develop an autonomous robotic chess system capable of interpreting board state and physically executing moves. With a focus in real time against a human opponent. Utilizing integrating computer vision, game logic, user friendly GUI, and a robotic arm.

Microgravity Simulator, Aruna Dookeran, Alexander Montano, Elias Orellana, Aiden Smart

Ocean Engineering and Marine Sciences Student Publications

Microgravity significantly affects biological growth, but space-based experiments are costly and difficult to access. Ground-based systems provide an alternative; however, many require continuous manual supervision to maintain operating conditions.

A Trojan Attack On Tdma Synchronization In Energy-Harvesting Wireless Networks, Ethan Berei

ONU Student Research Colloquium

This paper investigates a Trojan attack targeting the time-division multiple access (TDMA) synchronization mechanism in single-hop energy-harvesting wireless networks. The attack compromises a single node, which subtly skews its transmission timing to operate outside its assigned time slot, causing localized transmission overlaps and triggering repeated network-wide resynchronization events. This behavior shortens the synchronization interval, significantly increases control-plane traffic, and leads to higher energy consumption and delay in energy-constrained networks. The attack is modeled within a finite state machine (FSM) framework and experimentally evaluated under varying energy-harvesting conditions. Experimental results show that the number of synchronization events can increase by up …

Integration Of Bayesian Networks And Neural Networks For High-Dimensional Data Analysis, Cooper Schmer

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

High-dimensional biomedical datasets, such as omics data, present significant challenges for predictive modeling due to noise, redundancy, and computational complexity. This thesis proposes a hybrid framework that integrates Bayesian Networks (BNs) and Artificial Neural Networks (NNs) to improve classification performance of such data sets while reducing input dimensionality. Central to this work is a novel feature selection method based on d-separation, a structural property of Bayesian networks that encodes conditional independence relationships.

The proposed approach introduces a count-based d-separation metric to quantify the relevance of variables to a target outcome, along with a thresholding scheme to balance feature selection robustness …

Improving The Circuit Realization Of Grover’S Quantum Search Algorithm By Replacing Hadamard With √ × Gates, Ali Al-Bayaty, Ali Al-Shuwaili, Abbas Alzubaidi, Marek Perkowski

Electrical and Computer Engineering Faculty Publications and Presentations

Jozsa, Bernstein-Vazirani, and Grover, utilize Hadamard gates to create uniform superposition states for the input qubits of an oracle. However, Hadamard gates are non-native (non-supported) gates in all real quantum computers. For this reason, Hadamard gates are considered cost-expensive gates when realizing (transpiling) such algorithms into a real quantum computer. This paper introduces a new methodology for cost-effective transpilation of Grover’s algorithm into real quantum computers, by replacing all Hadamard gates with √ X gates. In quantum computing, the Hadamard and √ X gates create uniform superposition states of a qubit on the Xaxis and Y-axis of the Bloch sphere, …

Temperature Determination And Scene Change Artifact Mitigation When Using Fourier-Transform Spectroscopy On Targets With Time-Varying Temperature, Kody A. Wilson, Michael L. Dexter, Benjamin F. Akers, Anthony L. Franz

Faculty Publications

Fourier-transform spectroscopy is a widely used technique for determining the spectral and thermal properties of a target. However, target temperature variations during measurement can compromise the spectral accuracy. Temperature fluctuations induce oscillations superimposed on the target spectrum. These oscillations, referred to as scene-change artifacts, degrade the spectral accuracy. The literature is divided, with theoretical predictions suggesting negligible artifacts and growing experimental evidence reporting significant artifacts. This paper presents a theory and experimental validation of scene-change artifacts originating from target temperature variations. Traditionally, the interferogram offset is assumed to be constant, an invalid assumption for a changing scene. The error is …

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 …

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 …

Rioi: A Microwave-Photonic Rf-Interferometric Interrogation Technique For Enhanced Fiber Optic Sensing, Chen Zhu, Ruimin Jie, Chenxi Huang, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

Fiber optic interferometric (FOI) sensors are widely recognized for their high sensitivity, design flexibility, and multiplexing capabilities, making them ideal for applications ranging from structural health monitoring to biomedical diagnostics. However, conventional optical-domain interrogation techniques are often limited by the performance constraints of spectrometers. In this work, we present a radiofrequency (RF)-interferometric optical interrogation (RIOI) method for FOI sensors. This approach leverages microwave photonic (MWP) processing to encode the optical interference phase into an RF signal, which is then combined with a reference RF signal to produce a microwave-domain interferogram. By tracking spectral shifts in the RF domain, RIOI achieves …

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 …

Mathematical Modelling And Optimisation Of The Reactor For The Esterification Process Of Safflower Oil With N-Butyl Alcohol, Sadritdin Makhamatdinovich Turabdjanov Academician, Hasan Sadriddin Ugli Fozilov, Ozoda Bakhronovna Axmedova, Sadriddin Fayzullayevich Fozilov

Technical science and innovation

This study addresses the mathematical modelling and optimisation of a reactor for the esterification of safflower oil with n-butyl alcohol. To improve process controllability and reduce the need for numerous pilot-scale trials, an ideal-mixing continuous stirred-tank reactor (CSTR) model was adopted. Incorporating reaction kinetics, the effect of contact time on the relative viscosity of the product mixture was analysed. The modelling results indicate that achieving an acceptable degree of feedstock conversion is difficult when a single ideal-mixing reactor is used. Therefore, a CSTR cascade was proposed, and the configuration with N = 2 reactors was selected as the most appropriate …

Relationships Between The Parameters Of The Vegetable Oil Refining Process And Energy Consumption, Umidjon Abdimajitovich Ruziev, Marufjon Kobuljonovich Shodiev

Technical science and innovation

Vegetable oil refining is a multi-stage thermochemical process that is closely related to energy consumption, process parameters, product quality, and food safety requirements. Despite the extensive scientific literature on oil quality and pollutant formation, the quantitative relationship between purification parameters and relative energy consumption has not been sufficiently studied. In this work, a systematic analysis and engineering synthesis were carried out based on existing studies. According to the analysis results, the deodorization process accounts for 52–56% of the total thermal energy consumption, with a relative value ranging from 160 to 380 kJ/kg, depending on the enterprise's capacity and heat utilization …

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 …

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 …

Refinement Of Wind Speed Estimation At Turbine Hub Height Using Satellite Data And Regression Analysis Under Complex Terrain Conditions, Isroil Abriyevich Yuldoshev, Tulqin Rustamovich Jamolov, Sa'dullo Sayfiddin Ugli Fazliddinov, Jumanazar Farhodjon OʻGʻL Abdurashidov

Technical science and innovation

Reliable assessment of wind energy potential in regions characterized by complex terrain is often constrained by the limited availability of ground-based meteorological measurements. This study proposes an improved regression-based approach for refining wind speed estimates at the wind turbine hub height of 65 m using satellite-derived data from the NASA POWER database combined with a logarithmic vertical wind profile. The proposed methodology is validated using real operational data from a 750 kW wind power plant located in the mountainous Bostanlyk district of Uzbekistan for the period 2018–2021. The regression analysis demonstrates a strong linear relationship between the extrapolated wind speed …

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 …

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 …

Preliminary Study Of Circular Lithium-Ion Battery Thermal Management System With Intermittent Cooling, Muhammad Luthfi, Leo Van Gunawan, Yudhy Kurniawan, Sabda Ikhwal Rahmatullah, Alfarikh Muhammad Daen

Journal of Mechanical Engineering Science and Technology (JMEST)

The active battery thermal management system is important to maintain the lithium-ion battery temperature within the optimum and safe range. However, current research has not considered the potential for excessive energy consumption due to the continuous operation of a fluid flow source, such as a fan. This research aims to investigate the effect of a novel approach called intermittent cooling on the cooling efficacy and energy consumption of the circular-configuration BTMS. Both transient computational fluid dynamic simulation and experiment were conducted in this work with 30 pieces of 18650 Lithium-Ion batteries positioned in a staggered circular configuration. From the result, …

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 …