Digital Commons Network^™

Dual-Interface Wifi Packet Sniffer System Using Esp32-Cam With Real-Time Pcap Generation For Iot Network Analysis, Boy Setiawan Boy, Maghfiroh Maulani, Zico Pratama Putra, Muhammad Senoyodha Brennaf

Makara Journal of Technology

This study focuses on designing and implementing a cost-effective and energy-efficient WiFi packet sniffer system using the ESP32. The ESP32-CAM module, which combines WiFi, Bluetooth, and microSD support, is used to capture IEEE 802.11 frames in real-time via promiscuous mode. Packets are stored in packet capture format, which is compatible with tools such as Wireshark and Scapy. Developed using the official ESP-IDF, it offers low-level control and high performance. Two user interfaces were implemented: a UART-based text menu and a web-based HTTPS menu hosted on the ESP32 itself. Functional and performance evaluations were conducted with a focus on capturing broadcast …

Mathematical Modeling Of The Atmospheric Water Harvesting Process Using Cfd, Jasur Esirgapovich Safarov, Shakhnoza Abduvaxitovna Shaxnoza, Doston Ishmuxammat Ugli Samandarov, Azamat Bakir Ugli Usenov, Shahzod Faxriddin Ugli Dostqobilov

Technical science and innovation

This article presents the physical principles of Atmospheric Water Harvesting (AWH) technologies, including spectral radiation balance, air-sorbent interactions, thermodynamic constraints, and computational fluid dynamics (CFD) modeling approaches. The study provides models of water condensation, adsorption-desorption processes, and energy consumption. In addition, a detailed thermodynamic analysis was carried out to determine the partial vapor pressure, cooling demand, and theoretical energy limits of water extraction. The adsorption process is described using Langmuir isotherms, while desorption is represented through a kinetic model dependent on activation energy. To analyze the coupled processes of airflow, mass transfer, and heat transport, CFD models based on the …

Detection And Correction Of Object Orientation On Production Lines Using Photodetector-Based Systems, Utkirjon Ubaydullayev, Elmira Raxmanova

Technical science and innovation

This article addresses the issue of errors occurring in high-speed production lines, particularly those caused by misalignment or incorrect positioning of manufactured objects. Although production lines have significantly enhanced industrial efficiency worldwide, they are not immune to mistakes, especially under rapid operation conditions. To mitigate these errors without human intervention, the proposed solution integrates photodetector sensor matrices with robotic manipulators. The system uses high-resolution photodetector arrays, such as the Hamamatsu S13774 CMOS Linear Image Sensor, to capture shadows of objects on the production line, converting these into numerical data. This data is then processed using Principal Component Analysis (PCA) and …

Study Of The Influence Of Material Heterogeneities In Humidity Measurements In A Closed Volume, Hulkar Asadullayevna Usmanova, Asadulla Turgunbaev, Umid Uralovich Xudaykulov

Technical science and innovation

The article presents generalized theoretical studies of the errors arising in the conversion of material moisture into informative parameters of the microwave field. Such informative parameters of a material include structural inhomogeneities, non-uniform moisture distribution throughout the volume and by the forms of moisture bonding, density, temperature, and mass. The influence of material inhomogeneities during moisture measurements in an enclosed volume on the errors of primary measuring transducers is investigated, along with the errors accompanying the conversion of moisture into the dielectric characteristics of the material and the conversion of dielectric characteristics into informative parameters of the microwave field. A …

Empirical Analysis Of Machine Learning Models For Predicting Equipment Failures Using Iot Sensor Data, Yusuf Shodiyevich Avazov

Chemical Technology, Control and Management

This article examines the problem of detecting and predicting industrial equipment faults using IoT sensor data through machine learning techniques. Sensor readings such as temperature, vibration, pressure, voltage, and current, as well as FFT-based features, were statistically analyzed. Class imbalance and low signal informativeness were identified as key factors limiting model accuracy. Results obtained from Logistic Regression, Random Forest, and XGBoost models were comparatively evaluated, showing that when ROC-AUC values remain around 0.5, distinguishing fault and non-fault states becomes challenging. Correlation and feature-importance analyses confirmed the absence of strong dominant indicators. The findings highlight the need to improve sensor architecture …

Analog Systems Of Physical Quantities And Their Graph Models In Determining The Parameters Of Mechatronic Modules, Temurbek Omonboevich Rakhimov, Elmira Eshmurod Qizi Raxmanova, Guzal Khujaniyazova

Chemical Technology, Control and Management

This article is dedicated to the analogy systems of physical quantities and their graph models in determining the parameters of mechatronic modules. It presents the general sets and fundamental laws of analogy systems of physical quantities and their elements for determining the parameters of mechatronic modules. Based on the general sets and fundamental laws of analogy systems of physical quantities and their elements, principles have been developed for mechatronic modules with a heterogeneous structure consisting of electrical, magnetic, and mechanical parts. In these modules, the field as a form of matter exists, forming the basis for developing mathematical models to …

Comprehensive Mechatronic Design Methodology For 6-Dof Stationary Lower Limb Rehabilitation Exoskeleton Robot With Safety-Integrated Control Architecture, Javlonbek Rakhmatillaev Mr., Nodirbek Kimsanboyev Mr., Umidjon Takabaev Mr., Zafar Juraev3 Dr.

Chemical Technology, Control and Management

This paper presents the mechatronic design of a proposed six-degree-of-freedom (6-DOF) stationary lower limb rehabilitation exoskeleton (SLLRE) robot, developed through a comprehensive mechatronic design methodology that includes mechanical design, actuator and sensor selection, and the development of a control structure based on a safety-oriented control approach. The proposed 6-DOF SLLRE mechanical design introduces a comprehensive mechanical structure comprising bilateral hip, knee, and ankle joints, degrees of freedom, joint ranges of motion, human parameters for rehabilitation training, as well as the frames and structural elements of the proposed system. Furthermore, the selection of appropriate sensors, actuators, and control architecture for the …

Improving Self-Diagnostic Methods Of Flow Measurement Systems Based On Artificial Intelligence, Elbek Ortikov

Chemical Technology, Control and Management

The article examines methods for improving self-diagnostics of consumption measurement systems based on artificial intelligence in the context of industry digitalization and the development of cyber-physical systems. It has been shown that traditional flow meters used to measure the flow rate of liquids and gases are subject to mechanical, hydraulic, electronic, and hidden failures, which reduce the accuracy and reliability of measurements. A justification for the need to transition from classical maintenance methods to intelligent self-control methods that ensure the detection of anomalies and hidden malfunctions in real time is presented. A multi-level architecture of intelligent self-diagnosis is proposed, including …

Cache-Conscious Sparse Matrix Dense Matrix Multiplication On Gpus, Haoqiang Guo

LSU Doctoral Dissertations

Over the past decade, high-performance deep learning has evolved into a critical research domain, driven by the demand for efficient models and high inference throughput. Deep learning architectures have shifted from stacked convolutional layers to transformer-based models, while pruning techniques and graph-structured data have established sparse matrix–dense matrix multiplication (SpMM) as a fundamental kernel—particularly in graph neural networks (GNNs). Modern GPUs, with their massive parallelism and high-bandwidth memory, offer immense potential for accelerating these workloads. While SpMM implementations using the compressed sparse row (CSR) format remain common to avoid conversion overhead, preprocessing-based methods have recently demonstrated superior potential. In GNN …

A Parallel Interval Modeling Framework For Nonlinear Systems: Application To A Modified Duffing Oscillator, Roman Voliansky, Nina Volianska

Northeast Journal of Complex Systems (NEJCS)

The paper presents a mathematical framework for converting nonlinear dynamical systems into parallel forms. This framework replaces the exact system motion equations with interval equations, enabling the representation of nonlinear functions over piecewise linear domains. Such representation enables the description of system motions using linear-like differential equations, which can be analyzed and manipulated using well-known control methods. One such method is eigenvalue analysis, a powerful tool in classical control theory since many techniques rely on the system’s characteristic polynomial and its eigenvalues. We apply this method to define interval system eigenvalues and track their variation during system operation. These eigenvalues …

Traffic Study, Kennedy Case, Koryn Harms, Min Kaung, Abel Assefa, Eli Lockert, Dj Church

Student Scholar Symposium

No abstract provided.

Integration Of Renewable Energy Networks Into Smart Grid Infrastructure: A Matlab/Simulink-Based Simulation Approach, Saturday Noghayin Osaretin

Electrical Engineering Theses

The rising demand for sustainable and resilient energy systems has accelerated the transformation from traditional power grids toward smart grids integrated with renewable energy networks. This thesis explores the integration of solar energy sources into smart grids to replace conventional fossil-fuel-based generation. A simulation model is developed using MATLAB/Simulink to evaluate the operational performance, stability, and adaptability of the proposed smart grid architecture. Key challenges, including intermittency, synchronization, and bidirectional power flows, are identified, and corresponding solutions, such as energy storage systems, are proposed to address these issues. Simulation results demonstrate enhanced grid stability, reduced carbon footprint, and improved power …

Development Of An Iot-Based Energy Theft Detection System For A Single-Phase Smart Meter, Ojo Julius Oladele, Funso Kehinde Ariyo, Samson Oladayo Ayanlade, Ayooluwa Peter Adeagbo, Ismail Adeniyi Adeleke

Al-Bahir

Electricity theft causes annual global losses exceeding $96 billion, severely impacting distribution networks. This paper presents a novel IoT-based system integrating current differential sensing, physical tamper detection, and edge-cloud analytics to detect energy theft in single-phase smart meters. The design employs three ACS712 current sensors to monitor Kirchhoff-compliant current flow at the grid pole, meter input, and load output, coupled with a PIR sensor for cabinet intrusion. A SIM800L GSM module enables real-time theft alerts and remote disconnection, while closed-loop control autonomously restores power after tamper resolution — a feature absent in prior GSM-only systems. An Android application provides geotagged …

Puf-Based Digital Money With Propagation-Of-Provenance And Offline Transfers Between Two Parties, Benjamin Bean, Cyrus Minwalla, Eirini Eleni Tsiropoulou, Jim Plusquellic

Electrical and Computer Engineering ETDs

Building on prior concepts of electronic money (eCash), we introduce a digital currency where a physical unclonable function (PUF) engenders devices with the twin properties of being verifiably enrolled as a member of a legitimate set of eCash devices and possessing of a hardware-based root-of-trust. A hardware-obfuscated secure enclave (HOSE) is proposed as a means of enabling a PUF-based propagation-of-provenance (POP) mechanism, which allows eCash tokens (eCt) to be securely signed and validated by recipients without incurring any third party dependencies at transfer time. The POP scheme establishes a chain of custody starting with token creation, extending through multiple bilateral …

Fedchae: Federated Learning With Client Clustering And Hybrid Adaptive Engagement, Chaeeun Park

Electrical and Computer Engineering ETDs

As machine learning adoption expands, data privacy concerns have grown significantly. Federated Learning (FL) addresses this challenge by allowing clients to train locally and share only their model parameters with the server. However, conventional FL methods such as FedAvg suffer from high communication overhead, as all clients must participate in every global round.

This paper proposes FedChae (Federated Learning with Client Clustering and Hybrid Adaptive Engagement) to balance communication efficiency and model accuracy. FedChae alternates between Grouping Rounds, where all clients perform clustering, and Conventional Rounds, where one client per cluster updates the model.

Simulations with 100 clients using Multi-class …

Empowering Wireless Mesh Uav Networks Through Software-Defined Networking, Hieu Quang

Electrical and Computer Engineering ETDs

Unmanned Aerial Vehicles (UAVs) have been widely deployed in applications such as environmental monitoring, disaster response, and surveillance. Effective coordination between UAVs depends on low-latency inter-UAV communication to exchange state information, decisions, and other critical data. UAV networks are inherently dynamic which necessitates a framework capable of handling scenarios such as traffic re-routing, and resilience to communication failures. To address the challenges of managing dynamic UAV networks, this thesis proposes a dual network approach composed of three main components. First, the Better Approach to Mobile Ad-hoc Networking (BATMAN) protocol is used to enable communication among UAVs. Second, the OpenFlow protocol …

“Bridging The Gap To Midwave Infrared Event-Based Sensors: Design, Sensitivity, And Radiation-Hardness Characterization Of A Single-Pixel Iii-V Event-Based Infrared Sensor For Space Applications, Zinah M. Alsaad

Electrical and Computer Engineering ETDs

Event-based sensing presents a revolutionary paradigm shift for next-generation space surveillance systems, where power consumption is an ever-worsening constraint as temporal resolution demands increase. In addition to reduced power consumption, low latency, and wide dynamic range, the event-based sensor fundamentally only produces data when there is a change in illumination from which events are generated; no data is produced if the scene remains static. With their event-based datastream being inherently focused on the dynamic information of the scene, they are particularly well-suited to machine vision and autonomous sensing applications. While these sensors have many compelling advantages, there are presently no …

Emulation Of Orbital Dynamics And Control Of Fully Actuated Seven-Axis Prismatic Joint Systems, Bennett Russell

Electrical and Computer Engineering ETDs

This thesis details the system modeling, design, control, simulation, construction, and testing of a fully-actuated seven axis prismatic joint system created for the primary purpose of emulating on-orbit maintenance tasks. Additionally, it seeks to further research of space-based control schemas and investigate stiction as a case study with a mountable hybrid hinge system that emulates stiction. Controllers are evaluated under common limits and metrics, including time to escape, overshoot, mechanical work, and limit-exceedance counts. Comparisons span a PID baseline, deterministic MPC/MPPI, and a probabilistic POMDP policy. Results verify the emulator and hybrid hinge meet the intended design criteria and show …

Evaluation Of Internal Field In Ppln And Studies On Qpm Shg Efficiency Factor, Prasath Rk Mr

Theses and Dissertations

Periodically Poled Lithium Niobate (PPLN) crystals have attracted interest in optoelectronics and nonlinear optics. The response to the applied electric field is determined by their larger electro-optic and nonlinear optical coefficients. An internal electric field exists in congruent PPLN crystals due to its defects. Its evaluation is important in controlling the electro-optical behavior. A simple nondestructive diffraction method is proposed to estimate the internal electric field present in the congruent lithium niobate crystal.

Due to the presence of an unrelaxed internal field, the as-poled sample acts as an index grating. When a light is incident on such a sample, it …

Exploring Interactive Robotic Music Therapy Systems For Rehabilitation: A Survey Paper, Hector A. Salinas Gordillo

Discovery Undergraduate Interdisciplinary Research Internship

Interactive robotic music therapy introduces an innovative opportunity, where human guided musical interaction with robotic systems can create adaptive and engaging therapeutic experiences. This survey explores the current state of research at the intersection of robotics, music, and rehabilitation, focusing on emerging technologies such as human robot interaction methods and system designs that help enable real time, interactive music therapy.

Potential patient groups include individuals undergoing motor or cognitive rehabilitation, such as those recovering from stroke, living with Parkinson’s disease, cerebral palsy, or other motor impairments, as well as individuals with developmental disorders or limited mobility.

Traditional rehabilitation exercises may …

Career: Novel Direct Current Power Distribution For Large-Scale Electrified Transportation Charging, Hongjie Wang

Funded Research Records

No abstract provided.

Developing A Waste-To-Energy Assessment Framework Integrating Engineering And Policy Dimensions Using A Triple Bottom Line Approach, Izech Brian O. Edwin, King Harold A. Recto

Electronics, Computer, and Communications Engineering Faculty Publications

The management of municipal solid waste (MSW) in swiftly urbanizing Philippine cities has emerged as a critical concern in both energy and governance. Dependence on landfills is approaching critical thresholds as disposal sites near saturation, transportation costs escalate, and host communities increasingly resist garbage transfers. In response, this study proposes a comprehensive Waste-to-Energy (WtE) assessment framework that integrates engineering evaluation with policy and stakeholder analysis to support sustainable decision- making.

Using Baguio City as a case study, the framework applies a Triple Bottom Line (TBL) approach to evaluate three waste management scenarios: (1) current landfill-dominated practices, (2) engineered landfill with …

Iso-Detr: A Novel Detection Transformer For Industrial Small Object Detection, Faisal Saeed, Anand Paul

School of Public Health Faculty Publications

Effectively detecting and assessing real-time structural and ecological parameters in contemporary manufacturing environments poses significant challenges, particularly in identifying minute objects within product images. The swift evolution of the industrial sector underscores the necessity for intelligent manufacturing environments to uphold stringent product quality standards. However, accelerating production processes at high speeds heightens the risk of defective product outcomes. This research addresses the challenges inherent in small object detection within industrial contexts, proposing an innovative detection transformer model tailored to modern manufacturing environments. The proposed model integrates a feature-enhanced multi-head self-attention block (FEMSA), merging cross-channel communication network and multiple multi-head self-attention …

Isolated Dc-Dc Converter For An Ev Microgrid, Oscar Yu, William Leiker

Electrical Engineering

This product is a redesign of a DC-DC buck-boost converter which utilizes a new topology, the flyback converter, for use in an electric vehicle (EV) as a microgrid. The main driver behind the redesign is to provide electrical isolation between elements in the microgrid. The EV microgrid consists of the battery, motor, external DC and AC ports, and the power electronics (DC-DC converter and AC-DC inverter) which were designed and built in previous senior projects. Using EV’s as microgrids can help relieve stress from the main power grid caused by charging electric vehicles. Implementing EV’s as a microgrid enables the …

Ai-Optimized Resource Management In Next-Gen Wireless Networks, Fatemeh Lotfi

All Dissertations

Next-generation wireless networks must deliver highly adaptive, scalable, and intelligent connectivity to satisfy the heterogeneous demands of emerging services, including enhanced mobile broadband, massive machine-type communications, and ultra reliable low latency applications. The Open Radio Access Network (O-RAN) paradigm has emerged as a key enabler of this vision, introducing openness, virtualization, and artificial intelligence (AI)-driven control into the RAN ecosystem. O-RAN’s disaggregated architecture facilitates multi-vendor interoperability and empowers intelligent management through the RAN Intelligent Controller (RIC). However, achieving real-time, autonomous, and generalized optimization in such a dynamic environment remains a significant challenge due to its distributed nature, non-stationary traffic, and …

Adaptive Deep Learning In Physical Layer Applications, Ali Owfi

All Dissertations

Traditionally, signal processing models in communication systems have been designed based on solid foundations in statistics and information theory, often assuming linearity and optimizing for simplified models. However, real-world communication systems exhibit numerous imperfections and non-linearities that traditional linear models struggle to capture accurately. Deep Learning (DL)-based approaches, unconstrained by rigid mathematical models, have shown promise in optimizing system performance by accommodating specific hardware configurations and dynamic channel conditions as an alternative to the traditional methods. Despite all the recent research efforts on DL-based methods for physical layer applications, DL models have still not been widely applied to physical layer …

Implementation Of A Three-Port Solar Converter With A Battery Energy Storage System, Maison Christopher Phipps

Graduate Theses and Dissertations

The increasing deployment of distributed solar and energy storage systems has created the need for integrated power converters that can efficiently manage photovoltaic (PV) generation, battery energy storage, and grid-tied AC output. This thesis presents the implementation and validation of a 5kW non-isolated Three-Port Converter (TPC) adapted for residential solar applications. The converter consolidates three power stage into a high-frequency, compact architecture: a unidirectional boost converter for PV input, a bidirectional interleaved buck-boost converter for battery energy storage, and a configurable DC/AC inverter for 120Vac single-phase output. The system is controlled using a central controller implemented on a TI C2000™ …

Design And Optimization Of High-Frequency Medium-Voltage Dual Active Bridge Dc/Dc Converter Using Sic Device, Hui Cao

Graduate Theses and Dissertations

High frequency Dual Active Bridge (DAB) converters have become a key enabling technology in medium- and high-power applications such as renewable energy integration, electric vehicle fast charging, and emerging DC power distribution systems. However, when operating at high power and high frequency, DAB converters face critical challenges including limited soft-switching range, uneven semiconductor loss distribution, deadtime-induced resonance, switching-frequency constraints of wide-bandgap (WBG) devices, and transformer DC bias during dynamic transitions. This dissertation addresses these challenges through advancements in modulation strategies and converter architecture. First, an enhanced triple-phase-shift (E-TPS) modulation scheme is proposed to achieve balanced switching and conduction losses across …

Solar Powered Conservation: The Effects Of Solar Photovoltaic Facilities On Avian Community Composition, Michael Christopher Ferrara

Graduate Theses and Dissertations

The expansion of solar photovoltaic energy infrastructure is transforming landscapes worldwide. Increasingly, facilities are planted with native vegetation, yet how vegetation characteristics and landscape variables shape wildlife communities in solar facilities remains poorly understood. Because avian populations have been in decline and are sensitive to habitat changes, understanding how solar facilities influence avian communities is important. In Chapter 1, we used autonomous recording units, local vegetation measurements, and land use and land cover data to quantify how avian community occupancy is influenced by solar cover in solar facilities and comparable reference sites. We used a Bayesian multi-species occupancy model to …

Volume Status Detection With Integral Pulse Frequency Modulation Model Of Peripheral Venous Pressure, Jeremiah Rhys Wimer

Graduate Theses and Dissertations

This thesis studies the effectiveness of utilizing a modified integral pulse frequency modulation (IPFM) algorithm to synthesize peripheral venous pressure (PVP) waveforms for the detection of several physiological conditions using logistic regression. PVP waveforms are collected from 18 human patients and 4 porcine subjects. Human data are used to train models for determining the hypovolemic status of the patient, while the porcine data are used to train models for determining level of anesthesia and detecting internal hemorrhaging. In the human dataset, the waveforms collected from the 18 patients are classified into two groups according to serum chloride levels: resuscitated (≥100 …