Digital Commons Network^™

Impact Of Fault Resistance On The Performance Of Ann-Based Faults Classification In The Farm Of Pv Systems, Anwer Mahmood Fadhil, Omar Sharaf Al-Deen Al-Yozbaky

AUIQ Technical Engineering Science

This research provides an analytical study of the effect of fault resistance on the accuracy of fault classification in solar farms, with the aim of evaluating the performance of classification algorithms in realistic environments where the characteristics of electrical signals resulting from faults change. A model of a 290kW photovoltaic farm, consisting of 100 strings each containing 7 solar panels, was adopted, and the simulation was carried out using MATLAB/Simulink software. The study included different scenarios for electrical faults, such as line-to-ground (LG) and line-to-line (LL) failures, with the failure impedance changing from 0 to 500 ohms by a step …

Effects Of Ambient Temperature On Nox Emissions From Heavy-Duty Diesel Vehicles Measured In Utah, Amber L. Gurecki Allen, Darrell Sonntag, Gary A. Bishop

FEAT Publications

No abstract provided.

Deterioration And Instability Mechanisms Of Water-Rich And Weakly Cemented Open-Pit Slopes, Wang Ming, Wu Zhang, Xu Changyou, Zhao Fu, Meng Xiangchun, Shi Bin, Liu Jingyu, Xu Yongchao, Wang Jingwei, Zhao Lichun

Coal Geology & Exploration

Background During the mining of an open-pit mine, denudated layers contain loose Neogene and Quaternary aeolian, alluvial, and diluvial deposits, facilitating water storage and conduction. This is prone to cause slope degradation and instability, severely threatening mining safety. Methods Based on results from field surveys and laboratory experiments, this study systematically analyzed the impacts of groundwater on the weak layer along a slope of an open-pit mine in the Huolinhe Coalfield, Inner Mongolia, focusing on its softening effect on mudstones. By establishing a mechanical model for unconsolidated strata, this study derived an equation for calculating the seepage force in the …

Pseudo-2d Mt Inversion Technique For Small-Frame Tem And Its Application In Advance Geological Prediction, Han Ziqiang, Wanma Longzhi, Li Xiangfeng, Yang Yongqiang, Zhu Xiaoming, Luo Chengxian, Tang Li

Coal Geology & Exploration

Objective To address the bottlenecks of low computational efficiency and impracticality of multi-dimensional inversion in the advance geological prediction based on the transient electromagnetic method (TEM), this study developed a pseudo-two-dimensional (2D) magnetotelluric (MT) inversion technique for small-frame TEM based on time-frequency transformation. Methods First, this study corroborated the significant similarity between the late-time apparent resistivity derived using small-frame TEM and the Cagniard apparent resistivity in the MT method under the parameters commonly used in advance geological prediction. Then, the optimal time-frequency transformation coefficient (C_TF) was introduced to achieve a rapid conversion from the late-time apparent resistivity …

3d Advanced Geological Prediction Based On Reflected Seismic Waves And Its Application Effects, Cai Sheng

Coal Geology & Exploration

Objective For the advance geological prediction of tunnels based on reflected seismic waves, the traditional 2D observation method tends to cause spatial positioning deviations of anomalies. To overcome this limitation, this study developed a 3D seismic wave-based advance geological prediction method according to the actual geometries of tunnels. Methods Using the technical path consisting of theoretical analysis, numerical simulation, and engineering verification, this study solved key technical challenges including 3D wavefield reconstruction, spatial modeling, and migration imaging in the 3D detection system. Based on the principle of geometric seismology, this study demonstrated the enhancement effects of 3D observation on the …

Intelligent Motion Tracking: A Low-Cost Surveillance Framework Using Soc Devices And Sensor Fusion, Aung Myat Khaung, Nicholas Michael Stiffler

Research from the Berry Summer Thesis Institute, 2025

This thesis presents the design and implementation of a lightweight surveillance system capable of realtime motion detection, object tracking, and behavioral history reconstruction in controlled environments. The system uses System-on-Chip devices such as Raspberry Pi boards equipped with NOIR cameras, monocular cameras, and break-beam sensors that work together to detect and track single or multiple moving objects like colored balls. The prototype is validated in structured settings with the goal of eventual deployment in more dynamic environments, addressing the challenge of reliably tracking visually similar objects with minimal distinguishing features. The architecture integrates computer vision with sensor fusion by combining …

An Investigation Of Hydro-Morphological Changes At The Estuarine Outlet Of Kitchener Drain, Northern Coast Of Egypt, Nada Mansour, Karim Nassar, Mahmoud El-Gamal, Tharwat Sarhan

Mansoura Engineering Journal

In recent years, sedimentation and coastline erosion have occurred in the Kitchener Drain, where its outflow meets the Mediterranean Sea. Several measures have been taken to mitigate the impact of these problems. Excavation continues toward the drain's outlet, and there have been multiple stages of hard protection work, such as groins along the drain's eastern and western banks. What would happen if the working near the drain was kept, where accretion and erosion are most severe. The Coastal Modelling System (CMS) was used to find it out. The two-dimensional hydrodynamic circulation model known as the CMS is outfitted with modules …

Sar Analog-To-Digital Converters For Point-Of-Care Biosensors: A Comparison, Eithar Alammari, Joud Alamro, Sara Alashwali, Ghadah S. Alyami, Aziza I. Hussein

Effat Undergraduate Research Journal

The SAR ADC, recognized for its low power consumption, moderate resolution, and satisfactory processing speed, stands as an ideal choice for ultra-low power biomedical applications. Recent efforts have been concentrated on enhancing the power efficiency of the SAR ADC sub-components through intricate refinements and innovative techniques. These efforts aim to minimize energy consumption without compromising the ADC's performance. Therefore, this paper aims to thoroughly examine various implementation approaches for the main components of the SAR ADC, highlighting their individual strengths, weaknesses, and limitations within wireless biomedical applications.

Continuous Versus Discrete-Time Sigma-Delta Analog To Digital Converters For Biomedical Applications: A Comparison, Haya H. Binsalim, Batool Alaidroos, Basma Shigdar, Salma Badaam, Aziza I. Hussein

Effat Undergraduate Research Journal

Continuous-time (CT) and discrete-time (DT) sigma-delta (ΔΣ) converters are two commonly used techniques for analog-to-digital conversion. While both methods operate based on the principles of oversampling and noise shaping, they differ in their implementation and performance characteristics. CT ΔΣ converters use analog circuits to sample and process signals continuously, while DT ΔΣ utilizes digital circuits to sample and process signals at discrete intervals. This paper presents a comprehensive comparison between CT and DT ΔΣ converters, highlighting their advantages and limitations. The comparison is made in terms of design complexity, power consumption, signal-to-noise ratio (SNR), and other essential parameters in medical …

Wideband Spectrum Sensing For Cognitive Radio Using Under-Sampled Successive Approximation Adc, Aziza I. Hussein

Effat Undergraduate Research Journal

The radio spectrum, an inherently limited resource, has been increasingly utilized owing to the recent exponential growth of wireless services. This has led to a new approach, termed cognitive radio, predicated upon exploitation of spectrum holes for omnipresent spectrum utilization. This is made possible via cognitive radio networks’ employment of spectrum sensing. Wideband spectrum sensing has been the focal challenge point in cognitive radio technology, since existing techniques are reliant on analog to digital converters (ADC) with sampling at the Nyquist rate. Unfortunately, in order to perform digitization of wideband RF signals at the Nyquist rate, a very high sampling …

Fault Detection In Analog Vlsi Circuits Based On Artificial Intelligence

Effat Undergraduate Research Journal

In thepastdecade,artificialintelligence(AI)hasbeenonthe rise asatooltobeutilizedacrossallthefieldsavailableintheindustry. Specificallyinthemicroelectronicsfield,exploringthecurrentoptionsof VLSI faultdetectionandtheirtypesiscrucialforadvancementandis importantinidentifyingwhetherthereisroomforimprovementorthe optimumisalreadybeingdone.Therefore,thepurposeofthisresearch is tocompareandcontrastbetweenVLSIfaultdetectionindigitaland analog circuitsusingAI.Techniquestoimproveefficiencysuchastrou- bleshootinginsmallsegmentsratherthanthewholesystemandsome resolutions todrawbacksthataren’tdetectibletohumansliketimingare discussed andresolvedinthispaper.Moreover,somenon-idealitiesand risks likemarginalstabilitywereconsidered.Finally,presentelements that areusedintoday’sfaultdetectioncircuitslikeneuralcontrollers and theANNswerediscussedaswell.Currently,theANNsarethemost utilized toolforfaultdiagnosesanddetection;however,forthecontinu- ation ofthistechnology’sgrowth,developersneedtofindmoreefficient methodstomovepastit.

Evaluation Of The Performance Of The Traveling Wave Differential Element In Protective Relays, Niranjan Kc

Master's Theses

This thesis evaluates the dependability, security, and limitations of the traveling wave differential protection function (TW87) in modern time-domain-based protective relays, using a combination of simulations and hardware testing in a laboratory environment. Fault transients are first generated using the electromagnetic transients program model of a real, 230 kV, 65.7 km long overhead transmission line, which are then played back on real time-domain-based protective relays. Various fault scenarios are chosen to evaluate the impacts of factors such as fault inception angle, distance to fault from line terminals, fault type, fault impedance, and external faults on the relay functions’ performance. Results …

The Design Of Coplanar Waveguide Traveling-Wave Kinetic-Impedance Parametric Amplifiers, Jordan Scott Savoie

Master's Theses

Astronomical observations and many physics experiments rely on cryogenic amplifiers for readout. Current sensitivity is limited by the noise figure of high-electronmobility transistor (HEMT) amplifiers, which have proven di!cult to decrease further in recent years. Traveling-wave kinetic-impedance parametric amplifiers (TKIPAs) are an emerging class of amplifiers which have the potential to substantially improve the sensitivity of microwave low-noise amplifiers (LNAs) while also accepting relatively high input powers and amplifying over a wide bandwidth. In this thesis, I present the design, modeling, and testing procedures for coplanar waveguide (CPW) TKIPAs developed by our group at the National Radio Astronomy Observatory. Using …

Advancing Rfid Systems: From Head Orientation To Robotic Localization Using Passive Tags, Guilherme Ricardo Mendes Da Silva Barreto De Figueiredo

Doctoral Dissertations

No abstract provided.

An Envisioned And Efficient Design Of Next Generation Decentralized Iot Bot Detection Model, Ahmed Abdullah Almalki

Doctoral Dissertations

The Industrial Internet of Things (IIoT) and Internet of Medical Things (IoMT) are revolutionizing critical infrastructures, but their expansion has also introduced severe cybersecurity vulnerabilities. Traditional IoT Bot Detection Systems (IBDS) struggle to scale in environments characterized by high-dimensional, large-scale, and redundant network traffic. These challenges hinder the development of reliable cloud-based intrusion detection systems. The limitations of static and rulebased methods in detecting evolving IoT botnet attacks—such as those launched by Mirai and Gafgyt—underscore the need for intelligent, adaptive approaches. To address this, the present study proposes a machine learning and deep learning-driven IoT Botnet Detection Model, validated through …

Equilibration And Transport Of Binary Mixtures On Planar And Porous Nanomaterials, Andrew Torres

Electronic Theses and Dissertations

We present results of a Kinetic Monte Carlo investigation of the adsorption dynamics of binary gas mixtures on planar and porous sorbents, with a focus on identifying and characterizing kinetic processes involved in uptake evolution and how they influence equilibrium conditions. We also investigate varying thermodynamic simulation parameters such as interactions, alkane lengths, partial pressures and pore configurations to determine how they impact these kinetic processes as well as equilibrium properties. This study matters both for better understanding how kinetics and equilibrium are connected and for improving practical techniques in separation applications. For planar surfaces, weak species overshoot kinetic processes …

Surgeon Ergonomics While Performing Total Knee Arthroplasty, Cameron Dahman

Electronic Theses and Dissertations

One of the most prevalent hazards to orthopedic surgeons are musculoskeletal disorders with 97% of arthroplasty surgeons reporting procedural-related musculoskeletal pain and 66% of orthopedic surgeons reporting procedural-related musculoskeletal injury [1], [2], [3]. With the annual number of total knee arthroplasties (TKA) on the rise, orthopedic surgeons are taking on larger annual caseloads and retiring later in life [4], [5]. The goal of this study was to quantify postural demand for 11 discrete surgical steps of TKA to identify ergonomically unfavorable positions surgeons experience while operating. Four orthopedic surgeons performed TKA while their motions were recorded using marker-based motion capture. …

Quantify The Impact Of Occupant Behavior On Building Retrofits To Achieve Net-Zero Target Under Future Climates, Pratik Raj Pandey

Dissertations - ALL

It is estimated that about 40% of all the electricity generated in the United States is consumed by the building sector. This scale of energy use by buildings can be understood by the fact that the U.S. alone consumes approximately 20% of all the energy produced globally, despite having only about 4.23% of the world's population. Given the threats posed by climate change, it is necessary to curtail the energy demand of this sector. Additionally, global climate change has increased the frequency, intensity, and duration of extreme climate events like heat waves, cold waves, hurricanes, floods, and droughts. Given the …

Research Synthesis Of Predicting Part 135 Accident Probability In Aviation: How The Bayesian Brain Ignores Declining Safety Standards, Jonathan R. Clarke

Journal of Aviation Technology and Engineering

Technological innovation has had an enormous effect on safety in aviation. However, in Part 135 operations, where technology is not as ubiquitous, the accident rates have plateaued. Human error is constantly misrepresented as being responsible for 70–80 percent of accidents, when it is clearly only one of several contributing factors. In commercial aviation, all accidents should be considered organizational failures, because by definition all defensive layers have been breached. Organizational failure, as it affects safety, should be identifiable and predictable from organizational behavior. Inevitably, in the aftermath of accidents the warning signs of poor behavior are seemingly obvious, yet there …

Investigating Resilience Of Cyberattack Detection Using Lyapunov-Based Economic Model Predictive Control To Data Poisoning, Helen Durand, Akkarakaran Francis Leonard

Chemical Engineering and Materials Science Faculty Research Publications

Cyberattacks may be performed on process control systems due to their integration of networking and computing with physical systems. Prior work in our group has developed detection strategies for nonlinear systems under sensor, actuator, and combined sensor and actuator attacks which can ensure, under characterizable conditions, that attacks can be detected before they cause safety issues. However, this work did not take into account the potential that an attacker could attempt to provide data to a process that causes an attack to remain undetected but that also is consistent with different process dynamics than those which the process has. This …

Response Of Dynamic Processes With Control Implemented On A Noisy Quantum Computer, Shilpa Narashimhan, Dominic Messina, Henrique Oyama, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

A major challenge to determining the applicability (and potential outperformance over classical computers) of a quantum computer (QC) within chemical manufacturing processes is quantum noise. Computations by a QC are error-prone due to the influence of quantum noise inherent to the hardware. Errors in control inputs may destabilize a chemical process and lead to unsafe conditions for manufacturing personnel and the environment. The response of a process with control implemented on a QC to errors due to noise must be investigated thoroughly. In this work, the impacts of control input errors due to quantum noise on a process are modeled …

Tools To Design Algorithms For Implementing Control Over Quantum Computers, Shilpa Narashimhan, Jihan Abou Halloun, Kip Nieman, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

Quantum computers (QCs) may find future applications within control systems that operate manufacturing processes. For application within control engineering, quantum algorithm development must be led by control engineers. However, control engineers may face challenges in designing quantum algorithms for control engineering problems. In this work, we provide several path-finding studies that leverage engineering tools such as optimization, encryption, and computational "short-cuts" toward making algorithm design for QC easier for control engineers.

The Innovative Technique For Obtaining The Solutions Of Jeffery Hamel Nano-Fluids Flow Problem, Haedir Abd Alrazak Namoos, Abeer Majeed Jasim

Iraqi Journal for Computer Science and Mathematics

The study of heat transfer in nanofluid flows is increasingly important in many engineering, medical, and industrial applications. These fluids offer enhanced thermal cooling properties compared to conventional fluids. The research problem lies in the challenges of solving the Jeffrey-Hammel flow model for nanofluids, which includes coupled nonlinear differential equations that describe the thermal and hydrodynamic behavior of this type of flow, taking into account the influence of multiple factors such as the type, size, and concentration of nanoparticles. This research aims to propose a new hybrid analytical technique that combines the Laplace transform and the q-homotopy analysis technique with …

Optimized Hybrid Watermarking: Dual-Scheme Strategies For Enhanced Robustness, Ooi Jessie, Liew Siau Chuin, Syifak Izhar Bt Hisham, Khor Hui Liang, Khoo Bee Ee, Jasni Mohamad Zain

Iraqi Journal for Computer Science and Mathematics

Digital watermarking is crucial in content identification and copyright protection, particularly multimedia and medical imaging. This paper introduces two novel hybrid watermarking methods, Entropy-Guided Singular Embedding (EGSE) and Entropy-Guided Hybrid Embedding (EGHE), that improve upon existing techniques by integrating entropy-based adaptive block selection with Particle Swarm Optimization (PSO) for dynamic embedding strength determination. Unlike traditional methods, which rely on fixed embedding regions or manual parameter tuning, the proposed approaches automatically identify high-entropy regions to embed watermark signals, ensuring stronger resistance to distortion while maintaining image quality. EGSE employs Integer Wavelet Transform (IWT) and Singular Value Decomposition (SVD), whereas EGHE enhances …

Retracted: Efficient Multi-User Computation Offloading And Reducing Latency In Mobile-Edge Computing For Iot Applications, Sarmad T. Abdul-Samad, Osamah Al-Hwaidi, Ali Abd Al-Rasool Muslem

Iraqi Journal for Computer Science and Mathematics

Mobile Edge Computing (MEC) is an inventive paradigm for computing that has the potential to notably diminish latency and energy consumption by transferring computationally demanding jobs to edge clouds near intelligent mobile users. This investigation aims to reduce offloading and latency between multiple users and edge computing in the context of Internet of Things (IoT) applications in the fifth generation (5G) by utilizing an optimization algorithm called the Bald Eagle Search Optimization Algorithm. Although employing deep learning methods might increase time consumption and computational complexity, an edge computing system enables devices to transfer their demanding jobs to edge servers, decreasing …

Retracted: Iot Flow Parameters Classification Based On Machine Learning Techniques, El-Sayed M. El-Kenawy, Marwa M. Eid, Ban Salman Shukur, Amel Ali Alhussan, Doaa Sami Khafaga

Iraqi Journal for Computer Science and Mathematics

In recent years, there has been a highly remarkable convergence of artificial intelligence (AI) and the Internet of Things (IoT), which has made rapid progress in smart city initiatives by developing smart devices for such cities. Since these devices are increasingly diversified, they require a resilient communication network to demonstrate high performance in managing consistent traffic flows. A machine learning model intended for identifying network parameters from diverse devices, in addition to proposing modifications meant for network performance enhancement, is developed in this study. In relation to packet data as a network traffic parameter, employing gateway devices can facilitate its …

Retracted: Metaguard: A Federated Learning Approach To Hybrid Xgboost And Meta-Learning Models For Proactive Cyber Threat Hunting, Shatha H. Jafer Al-Khalisy, Ghada Al-Kateb

Iraqi Journal for Computer Science and Mathematics

In an increasingly interconnected world, cybersecurity threats have become more sophisticated, necessitating advanced, scalable, and privacy-preserving solutions. MetaGuard emerges as a novel framework that integrates federated learning with hybrid machine learning models, specifically XGBoost and meta-learning, to enhance proactive cyber threat detection. This framework offers a robust, distributed approach to cybersecurity, ensuring high detection accuracy while preserving user privacy through the implementation of differential privacy and homomorphic encryption. MetaGuard leverages distributed nodes to collaboratively train a global model, enabling rapid adaptation to new threats without the need for centralized data aggregation. Experimental evaluations using the CYBER-2024 dataset demonstrate that MetaGuard …

Modeling Nato Joint Warfighting Through Space Combat Simulations, Grant Nehls, Apoorva Somani

Space and Defense

This article investigates NATO’s dependence on space systems in joint warfighting and explores the use of simulation to quantify degradation effects. Using a custom-built AFSIM model of a NATO Arctic operation, the study demonstrates how GNSS spoofing and crosslink jamming undermine data integrity, commander trust, and strike execution—even without kinetic losses. Results show that partial degradations can cause mission failure through decision paralysis. By moving beyond binary modeling, this research highlights the need for nuanced simulations to prepare NATO for contested space environments and the challenges of great power competition.

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Analyzing The Impact Of Passive Techniques On Aircraft Wing Hysteresis: An Experimental And Numerical Study, Brendan Worton

Masters Theses

This study investigates the effects of passive flow control techniques on aerodynamic hysteresis primarily in NACA 2412 (cambered) and 0012 (symmetric) wings. Computational Fluid Dynamics (CFD) was used to design and evaluate three passive techniques, including outward-facing dimples, leading-edge tubercles, and rectangular vortex generators, prior to experimental validation. These techniques demonstrated improvements in aerodynamic performance in CFD simulations and were therefore selected for wind tunnel testing to analyze their aerodynamic performance and influence on hysteresis behavior. A custom, cost-effective experimental setup was designed and developed to facilitate efficient angle-of-attack control and data acquisition. It incorporates a three-axis force sensor, stepper …

Early Detection Of Oak Wilt Using Unmanned Aerial Vehicles (Uav) & Computer Vision, Muttaki I. Bismoy

Masters Theses

Forests are critical ecosystems, delivering services such as biodiversity conservation, climate regulation, timber production, and recreation. However, they face increasing threats from pathogens like Bretziella fagacearum, which causes Oak Wilt, a lethal disease that disrupts water transport in oak trees, leading to canopy dieback and eventual death. Traditional detection methods rely on manual ground surveys, which are labor-intensive, time-consuming, and prone to error, particularly in early disease stages.

This research presents an automated, scalable, high-precision Oak Wilt detection system using Unmanned Aerial Vehicles (UAVs) combined with deep learning-based computer vision. Expanding on earlier work with a lightweight CNN achieving an …