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Articles 4531 - 4560 of 5216
Full-Text Articles in Engineering
Lift And Drag Benefits Of Morphing Aircraft, Joseph Lombardi
Lift And Drag Benefits Of Morphing Aircraft, Joseph Lombardi
Master’s Theses
Aircraft use the ability to change the geometry of their wings to produce lift and drag as needed to maintain flight conditions. While the wings themselves are not physically changing shape, flaps and ailerons are used to alter the lift and drag coefficients experienced. Flaps have been used and changed over the years in order to produce better lift to drag ratios. The most commonly used flaps have been plain, slotted, and double slotted. Each type features slightly different mechanical structures, thus producing differing amounts of lift and drag. The introduction of new materials allow for a morphing flap to …
Electronic Bills Of Lading And Blockchain Technology: A Regulatory Perspective, Hsin-Hua Tsai
Electronic Bills Of Lading And Blockchain Technology: A Regulatory Perspective, Hsin-Hua Tsai
Journal of Marine Science and Technology–Taiwan
Information and communications technology (ICT) systems are increasingly relevant to the maritime sector. Regarding the revolution of the bill of lading, many shipping lines and other technology startups have been looking into developing viable electronic transport documents that have the same functions as paper bills of lading to reduce supply chain risks. The limitations of the paper-based process have become increasingly visible in the COVID-19 crisis. The main purpose of the article is to analyze the application of blockchain bills of lading, which utilizes computational logic to create the digital ledger, and users can set up algorithms and rules to …
Intelligent Formation Control Using Orfbls And Adaptive Backstepping Sliding-Mode Control To Address Uncertain Tilting In Multi-Quadrotors During Wind Gusts, Ching-Chih Tsai, Chun-Fu Mao, Kumail Hussain
Intelligent Formation Control Using Orfbls And Adaptive Backstepping Sliding-Mode Control To Address Uncertain Tilting In Multi-Quadrotors During Wind Gusts, Ching-Chih Tsai, Chun-Fu Mao, Kumail Hussain
Journal of Marine Science and Technology–Taiwan
In terms of aerial robotics, stable and precise formation control is a significant challenge for tilting multi-quadrotors during disturbances. This paper proposes a fixed-time formation control strategy for tilting multi-quadrotors to address the effect of external wind gusts. The observer accurately predicts environmental disturbances and an adaptive backstepping sliding-mode control (ABSMC) method with an output recurrent fuzzy broad learning system (ORFBLS) addresses these disturbances within a finite time. ORFBLS dynamically adjusts its structure through a growing ORFBLS structure to allow nodes to be added as needed. The method's stability is validated using Lyapunov stability theory and ensures the convergence of …
Visually Guided Landing System On Ship Deck For Multicopter, Dong-Lin Li, Shih-Kai Lee, Tzu-Hsiang Chou
Visually Guided Landing System On Ship Deck For Multicopter, Dong-Lin Li, Shih-Kai Lee, Tzu-Hsiang Chou
Journal of Marine Science and Technology–Taiwan
Traditionally, high-value fish have been located at sea using helicopters. However, with advancements in technology, maritime drones have become increasingly important in recent years. Compared to traditional helicopter-based methods, drones offer significantly lower operational costs, making them cost-effective. However, the challenging sea conditions, including strong winds and the swaying motion of vessels, pose significant challenges for drone landings.
This paper proposes a stable approach for multicopter landing on ships at sea, incorporating improved marker detection, enhanced wind resistance control, and more accurate deck motion prediction. In the marker detection phase, we introduce a method to improve the accuracy of ArUco …
Social Safety And Social Security: Validating Context-Specific Instruments For Slums, Liss D. Romero, Katherine Palacio, Zacheous Ako Abang, Valeria Silgado, Humberto Llinas, Leidy González, Erika Frydenlund, Daniel Bolivar, Jose J. Padilla
Social Safety And Social Security: Validating Context-Specific Instruments For Slums, Liss D. Romero, Katherine Palacio, Zacheous Ako Abang, Valeria Silgado, Humberto Llinas, Leidy González, Erika Frydenlund, Daniel Bolivar, Jose J. Padilla
VMASC Publications
Social safety and social security are concepts that help explain a community's well-being by assessing how it manages and mitigate existing, or perceived, risks. However, these terms are often conflated, which can limit understanding, particularly in areas with unstable living conditions. This study explores both concepts in the context of residents living in slums. As the number of displaced people grows, slums and informal settlements are becoming increasingly common worldwide, making it essential to clarify these concepts. Residents of slums face numerous hazards, including crime, violence, inadequate housing, overcrowding, and limited access to essential services. To measure social safety and …
Autonomous Uav Mission Planning Under Threat Using Model Predictive Control With Proportional-Navigation Pursuers, Mehmet B. Ozcelik
Autonomous Uav Mission Planning Under Threat Using Model Predictive Control With Proportional-Navigation Pursuers, Mehmet B. Ozcelik
Mechanical and Aerospace Engineering Theses
Autonomous unmanned aerial vehicles (UAVs) operating in contested environments must
complete mission objectives while avoiding restricted regions, radar exposure, and pos-
sible interception. This thesis develops a MATLAB-based simulation framework for
two-dimensional UAV mission planning under threat using model predictive control and
proportional-navigation chasers. The mission requires the UAV to travel from a start
location to a goal while visiting required checkpoints and avoiding no-fly zones and radar
regions. A chaser attempts to intercept the UAV using either a basic pure-pursuit-style
law or a proportional-navigation guidance law.
The framework integrates environment generation, augmented visibility-graph rout-
ing, waypoint management, UAV kinematic …
Llm-Driven Closed-Loop Uav Control With Obstacle-Aware Model Predictive Control, Halimcan Yasar
Llm-Driven Closed-Loop Uav Control With Obstacle-Aware Model Predictive Control, Halimcan Yasar
Mechanical and Aerospace Engineering Theses
This thesis presents a closed-loop control architecture for uncrewed aerial vehicles (UAVs) in which a large language model (LLM) serves as a high-level decision module operating over a persistent, metric 3D world model.
Rather than generating low-level commands or open-loop plans, the LLM selects one parameterized maneuver per decision step from a small, verified library of flight primitives conditioned on a structured representation of the drone state, tracked object positions, and mission specification.
Translational motion is executed by a planar model predictive controller (MPC) with soft obstacle avoidance, using obstacle hypotheses provided by the LLM, so that safety-critical constraint handling …
Hall Current And Nth Order Chemical Reaction Effects On Unsteady 3d Mhd Williamson Nanofluid Flow With Thermophoresis And Brownian Motion Over An Inclined Stretching Sheet, Polavarapu Sudheer, Ramachandra Reddy Vaddemani, Raghunath Kodi
Hall Current And Nth Order Chemical Reaction Effects On Unsteady 3d Mhd Williamson Nanofluid Flow With Thermophoresis And Brownian Motion Over An Inclined Stretching Sheet, Polavarapu Sudheer, Ramachandra Reddy Vaddemani, Raghunath Kodi
Mansoura Engineering Journal
This study examines the influence of Hall current and nth-order chemical reaction on unsteady three-dimensional magnetohydrodynamic (MHD) Williamson nanofluid flow over an inclined stretching sheet. The model incorporates thermal radiation, heat source, Brownian motion, and thermophoresis effects. The governing nonlinear partial differential equations are transformed into a system of ordinary differential equations using similarity transformations and solved numerically using the shooting method with a fourth-order Runge–Kutta scheme. The results indicate that an increase in the magnetic parameter significantly reduces velocity profiles while enhancing temperature and concentration distributions. The Hall parameter reduces surface drag and improves heat transfer, while decreasing mass …
Preserving The Identity Of Historic Coptic Orthodox Monasteries In Egypt Under Contemporary Pressures: Case Studies Of St. Bishoy And St. Anthony Monasteries, George Medhat Adeeb, Mohamed Khairy Amin, Mohamed Ahmed Al-Sherbiny
Preserving The Identity Of Historic Coptic Orthodox Monasteries In Egypt Under Contemporary Pressures: Case Studies Of St. Bishoy And St. Anthony Monasteries, George Medhat Adeeb, Mohamed Khairy Amin, Mohamed Ahmed Al-Sherbiny
Mansoura Engineering Journal
Historic Coptic Orthodox monasteries in Egypt (HCOMEs) represent an important component of Christian heritage, integrating architectural value with enduring spiritual traditions that reflect both tangible and intangible dimensions. However, contemporary development and changing functional demands are generating transformations that may affect their identity if not carefully managed. Despite extensive scholarship, limited research has systematically examined these transformations through a structured evaluative approach. This study addresses this gap by developing and applying an analytical and evaluation framework to examine how contemporary pressures influence the historical, architectural-spatial, and spiritual identity of HCOMEs, and to assess the effectiveness of monastic responses. The framework …
Optimization Of Mechanical Properties Of Copper Nanofiller Reinforced Banana Fiber Polyester Composites Using Grey–Taguchi Method, Nikhil Janardan Rathod, Mayur Jayant Gitay, Markala Karthik, Harshwardhan Ghongade, Upendra Rajak, Rajendra Sopan Narkhede
Optimization Of Mechanical Properties Of Copper Nanofiller Reinforced Banana Fiber Polyester Composites Using Grey–Taguchi Method, Nikhil Janardan Rathod, Mayur Jayant Gitay, Markala Karthik, Harshwardhan Ghongade, Upendra Rajak, Rajendra Sopan Narkhede
Mansoura Engineering Journal
Mechanical performance of banana fiber-reinforced polyester composites maximized using a composite Taguchi and a Grey Relational Analysis (GRA) process. This will aim at enhancing dispensation limits to enhance better tensile, flexural and impact belongings. The hand lay-up method was used to create composites by variable three key limits and they included banana fiber content (30 wt%), copper nanoparticle content (15 wt%), and curing temperature (80 o C). Trial design and mechanical properties were being measured in form of ASTM values on a L9 orthogonal array.
The multi-response optimization was performed with the help of the Grey Relational Analysis, which was …
Evaluating Matching Frontier Methods For Crash Modification Factor Estimation, Usama Elrawy Shahdah, Eman K . Ali, Sania Reyad Elagamy
Evaluating Matching Frontier Methods For Crash Modification Factor Estimation, Usama Elrawy Shahdah, Eman K . Ali, Sania Reyad Elagamy
Mansoura Engineering Journal
This study evaluates "matching frontier" methods against conventional approaches for estimating Crash Modification Factors (CMFs). Thirty-four method-model combinations were tested, including 16 frontier variants, 8 propensity-score-matching algorithms with negative binomial and mixed-effects models, and two benchmarks (empirical Bayes and cross-sectional), across multiple sample sizes and three true CMF values (0.80, 1.00, and 1.30). Of these, 30 converged successfully; 4 mixed-effects models with replacement-based matching failed due to duplicate control observations. Each scenario was evaluated across 10 Monte Carlo replications to quantify performance uncertainty.
Synthetic crash data were generated with known treatment effects, examining scenarios ranging from ideal (386 treated, 21,000 …
Remote Sensing-Based Rice Detection: Novel Indices From Optical And Sar Synergy, Kaifi Chomani
Remote Sensing-Based Rice Detection: Novel Indices From Optical And Sar Synergy, Kaifi Chomani
Mansoura Engineering Journal
Accurate rice mapping is challenging due to the lack of a simple, efficient approach and the complexity and limited ability of existing methods to distinguish rice fields from non-rice fields. This study proposes two novel indices: the Multispectral Rice Detection Index (MRDI), which utilises optical imagery, and the OptiRadar Rice Index (ORRI), which incorporates both optical and Synthetic Aperture Radar (SAR) data. Ground-truth data from the Cropland Cropping Systems (CROS) were used to assess the performance of both indices. The findings indicated that MRDI achieved an overall accuracy of 97.97% with perfect recall (100%) but lower precision (78.65%). However, the …
An Iterative & Analytical Hybrid Deep Learning Framework For Enhanced Brain Tumor Detection And Segmentation In Mri Video Scans, Swati V. Sakhare
An Iterative & Analytical Hybrid Deep Learning Framework For Enhanced Brain Tumor Detection And Segmentation In Mri Video Scans, Swati V. Sakhare
Mansoura Engineering Journal
The critical need for accurate and robust brain tumor detection in MRI video scans is for early diagnosis and treatment planning operations. However, the existing methods suffer from several limitations, such as not being able to capture spatio-temporal features, handling class imbalances, and generalizing across datasets with diverse characteristics. To address these challenges, I propose a hybrid deep learning framework that integrates multiple advanced techniques to enhance the detection and segmentation of brain tumors. My approach starts by using the 3D CNN-LSTM (ResNet3D-LSTM) to extract spatio-temporal feature, which utilizes ResNet3D for spatial detail extraction and LSTM for temporal coherence across …
Optimizing The Lightweight Steel Fibre Reinforced Bacterial Concrete With Nano-Silica And Coconut Shell Aggregates Using Taguchi Method, Damodaran Pooja, Mayilsamy Yuvaperiyasamy
Optimizing The Lightweight Steel Fibre Reinforced Bacterial Concrete With Nano-Silica And Coconut Shell Aggregates Using Taguchi Method, Damodaran Pooja, Mayilsamy Yuvaperiyasamy
Mansoura Engineering Journal
Concrete is essential for construction due to its high strength and durability. It supports most modern infrastructure globally. Cement production is a major source of CO₂ emissions, posing serious environmental concerns. Additionally, the rising demand for concrete is straining the limited supply of essential raw materials, such as aggregates. Researchers are examining alternative materials to improve Sustainability while maintaining structural strength to address these issues. This research aims to improve concrete performance by enhancing cement durability with nano-silica. Coconut shell, an agricultural by-product, functions as an eco-friendly alternative to conventional coarse aggregates, alleviating their scarcity. Microbiologically induced calcium carbonate precipitation …
Trident-Bladder: A Resolution-Aware Multimodal System For Robust, Calibrated Bladder Cancer Diagnosis Across Endoscopy, Histopathology, And Liquid Biopsy, K. Sankar, S. Venkata Lakshmi, Gummadi Reshma, V. Gokula Krishnan, M. Ganesan, V. Vijayaraja
Trident-Bladder: A Resolution-Aware Multimodal System For Robust, Calibrated Bladder Cancer Diagnosis Across Endoscopy, Histopathology, And Liquid Biopsy, K. Sankar, S. Venkata Lakshmi, Gummadi Reshma, V. Gokula Krishnan, M. Ganesan, V. Vijayaraja
Mansoura Engineering Journal
Bladder cancer diagnosis demands the integration of cystoscopy, histopathology, and biomarker testing, yet the majority of AI systems continue to be modality, specific and sensitive to acquisition variations. TRIDENT, Bladder is a resolution, aware multimodal framework that we have developed to address this issue. The method combines cystoscopic lesion segmentation, whole, slide image (WSI) molecular subtype prediction, and urine miRNAclinical data through reliability, weighted fusion and a utility, aware decision policy. The endoscopic branch features a quality, gated super, resolution component, resulting in mDice 87.5, sensitivity 92.1%, precision 91.4%, boundary, F1 85.3%, and ECE 0.023 at 32 FPS. mDice on …
Analysis Of Policies And Incentives For The Successful Implementation Of Hydrogen-Fueled Medium-Duty And Heavy-Duty Vehicles In Humboldt County, California, Alka Verma
Cal Poly Humboldt theses and projects
The 21st century has seen a significant rise in global greenhouse gas (GHG) emissions, with the transportation sector contributing 23% of these emissions. Medium-duty and heavy-duty vehicles (MD/HD) are particularly impactful, accounting for over a quarter of transport-related emissions. In Humboldt County, California, transportation represents 53% of total emissions, with MD/HD vehicles being a major contributor. As light-duty vehicles shift to zero-emission alternatives, the MD/HD sector faces unique challenges. Hydrogen fuel cell vehicles offer a promising solution, providing longer range, higher energy density, and quicker refueling compared to battery electric vehicles (BEVs). These features make hydrogen an attractive option for …
Sustainable Safety Planning On Two-Lane Highways: A Random Forest Approach For Crash Prediction And Resource Allocation, Fahmida Rahman, Cidambi Srinivasan, Xu Zhang, Mei Chen
Sustainable Safety Planning On Two-Lane Highways: A Random Forest Approach For Crash Prediction And Resource Allocation, Fahmida Rahman, Cidambi Srinivasan, Xu Zhang, Mei Chen
Civil Engineering Faculty Publications
During the safety planning stage, accurate crash prediction tools are critical for prioritizing countermeasures and allocating resources effectively. Traditional statistical approaches, while long applied in this field, often depend on distributional assumptions that may introduce bias and limit model accuracy. To address these issues, studies have started exploring Machine Learning (ML)-based techniques for crash prediction, particularly for higher functional class roads. However, the application of ML models on two-lane highways remains relatively limited. This study aims to develop an approach to integrate traffic, geometric, and critically, speed-based factors in crash prediction using Random Forest (RF) and SHapley Additive exPlanations (SHAP) …
Detection And Management Of Attacks On Synchronized Networks, Michael T. Spearman
Detection And Management Of Attacks On Synchronized Networks, Michael T. Spearman
Honors Theses and Capstones
The Precision Time Protocol (IEEE 1588) provides sub-microsecond clock synchronization across packet-switched networks and has become foundational infrastructure in 5G fronthaul, industrial control systems, and financial exchanges. Despite its criticality, most deployed PTP networks operate without active security monitoring, and no standardized detection mechanism exists for the class of attacks that deliberately stay below conventional jitter thresholds. This thesis investigates whether hardware-level ptp4l offset logs alone are sufficient to reliably detect two such attacks, slowly wandering packet delay injection and rogue master spoofing, and whether detection can occur before severe synchronization failure.
A hardware-in-the-loop testbed was constructed using two hosts …
Deep Learning Approaches For Voltammetric Analysis Of Coffee, Ryan Koes
Deep Learning Approaches For Voltammetric Analysis Of Coffee, Ryan Koes
Honors Theses
This thesis investigates deep learning approaches for voltammetric analysis of brewed coffee using a low-cost electrochemical system and screen-printed electrodes (SPEs). Traditional analytical methods, such as high-performance liquid chromatography (HPLC) and gas chromatography-mass spectrometry (GC-MS), provide precise quantification of key compounds but require expensive instrumentation and specialized expertise, limiting accessibility. While SPEs offer a more accessible alternative, they yielded poor results with traditional processing; however, when combined with a neural network, the system proved more effective. In experiments with 132 coffee samples, mean errors for caffeine, CGA, and TDS predictions were 52.98 ppm, 70.48 ppm, and 0.08%, respectively. These findings …
A Web-Based Wizard-Of-Oz Platform For Collaborative And Reproducible Human-Robot Interaction Research, Sean O'Connor
A Web-Based Wizard-Of-Oz Platform For Collaborative And Reproducible Human-Robot Interaction Research, Sean O'Connor
Honors Theses
The Wizard-of-Oz (WoZ) technique is widely used in Human-Robot Interaction (HRI) research, but two persistent problems limit its effectiveness: existing tools impose technical barriers that exclude non-engineering domain experts (the Accessibility Problem), and the fragmented landscape of robot-specific implementations makes interaction scripts difficult to port across platforms (the Reproducibility Problem- concerning execution consistency and portability, not third-party replication). Through a literature review, I identified three design principles to address both: a hierarchical specification model, an event-driven execution model, and a plugin architecture that decouples experiment logic from robot-specific implementations. I realized these principles in HRIStudio, an open-source, web-based platform providing …
Combining Haptic Feedback With Electromyography To Study Knee Injury In Stationary Cycling, Christopher Kirby
Combining Haptic Feedback With Electromyography To Study Knee Injury In Stationary Cycling, Christopher Kirby
Honors Theses
Patellofemoral Pain Syndrome (PFPS) is the most prevalent overuse injury in cycling, often linked to altered neuromuscular activation patterns of the quadriceps and hamstrings. While sensory feedback has successfully modified cyclists posture, there is a critical lack of evidence-based interventions targeting the underlying muscle activation imbalances associated with chronic knee pain. This study aimed to develop and validate a novel, real-time biofeedback system that utilizes electromyography (EMG) to trigger vibrotactile cues, aiming to shift muscle onset timing earlier in the pedal stroke to mitigate PFPS-related imbalances. A closed-loop system was engineered by integrating a Delsys EMG system with a SageMotion …
Design And Analysis Of Energy Recovery Methods For Reduced Aircraft Emissions, Joshua C. Hauck
Design And Analysis Of Energy Recovery Methods For Reduced Aircraft Emissions, Joshua C. Hauck
Honors Theses
Aircraft flights are an increasingly popular mode of transportation. However, their harmful impacts on the environment are a growing concern. Many engineers have worked to develop fully electric aircraft to address this issue. Although they are much more sustainable than conventional aircraft, electric aircraft encounter severe limitations imposed by current battery technology. One alternative route engineers have taken is developing energy recovery methods (ERMs). These are marketed as devices that reduce aircraft fuel consumption without significantly changing their structure and functionality, making them an excellent short-term solution. However, there is little to no consideration of the tradeoffs induced by the …
Buckling Analysis Of Auxetic Composite Laminates And Optimal Design Using Lamination Parameters And Machine Learning, Hans Bendon Maria Tamil Selvan
Buckling Analysis Of Auxetic Composite Laminates And Optimal Design Using Lamination Parameters And Machine Learning, Hans Bendon Maria Tamil Selvan
Mechanical and Aerospace Engineering Theses
Composite materials are widely used as structural panels in aerospace, automotive, and civil engineering applications, where buckling is often a critical failure mode. This thesis focuses on the analysis and design of composite laminates that maximize buckling performance under prescribed stiffness and thickness constraints.
The first part of the study investigates the buckling behavior of auxetic laminates, which exhibit a negative Poisson's ratio. While previous studies suggest that auxetic laminates can achieve higher critical buckling loads than non-auxetic laminates under simply supported boundary conditions with lateral restraint, the influence of other boundary conditions and plate aspect ratios has not been …
Flood Damage And Social Vulnerability In Coastal New Hampshire, Mitchell S. Berry
Flood Damage And Social Vulnerability In Coastal New Hampshire, Mitchell S. Berry
Honors Theses and Capstones
This study investigates the relationship between flood-induced building damage and social vulnerability in coastal New Hampshire, with a focus on communities increasingly affected by sea-level rise, storm surge, and high tide events. Using a dataset of 2,528 single-family homes, the analysis integrates flood depth maps (coastal, pluvial, and fluvial), building-level damage estimates, and a housing-burden-based metric to assess how physical and social factors interact to shape flood impacts. Results show that flood depth is the primary driver of building damage, with the most severe impacts concentrated in coastal areas experiencing deeper inundation. However, when buildings are grouped by vulnerability, higher …
Assessment Of Advanced Glazing Systems For Building Energy Efficiency In Hot-Arid Climates, Ahmad I. Elshamy, Yousef Elgefly, Yara El-Metwally, Serag Salem
Assessment Of Advanced Glazing Systems For Building Energy Efficiency In Hot-Arid Climates, Ahmad I. Elshamy, Yousef Elgefly, Yara El-Metwally, Serag Salem
Architectural Engineering
The built environment is considered among the most contributing factors to energy consumption. The building envelope plays a crucial role in determining the building energy consumption, regulating heat transfer and maintaining adequate indoor environmental quality. Hence, optimizing the thermal performance of the building envelope by achieving optimal glazing solutions while fulfilling the Sustainable Development Goal (SDG 7) is the main aim of this research. This study investigates the impact of various facade glazing systems on the building energy performance, focusing on the cooling energy consumption of an office building in a hot arid climate, Cairo, Egypt. The novelty of this …
Effects Of Metal-Modified Catalysts On The Desorption Performance Of Mixed Amine Solutions And Machine Learning Prediction, Xunxuan Heng, Zhenzhen Zhang, Longhua Zhu, Li Yang, Shugang Xie, Zeyu Wang, Dongtai Han, Fang Liu, Kunlei Liu
Effects Of Metal-Modified Catalysts On The Desorption Performance Of Mixed Amine Solutions And Machine Learning Prediction, Xunxuan Heng, Zhenzhen Zhang, Longhua Zhu, Li Yang, Shugang Xie, Zeyu Wang, Dongtai Han, Fang Liu, Kunlei Liu
Mechanical Engineering Faculty Publications
The high energy penalty associated with solvent regeneration is still a major bottleneck in amine-based CO2 capture. In this work, the effects of five solid acid catalysts on the desorption performance of a mixed-amine solvent were compared, and the HY catalyst with superior desorption behavior was selected and further modified with four transition metals (Co, Mn, Gr and Ce) to enhance its catalytic activity. The findings indicate that the CO2 desorption capacity and maximum desorption rate of the Co-modified HY catalyst reach 48.96 mmol and 0.02211 mmol/s, corresponding to increases of 36.80% and 35.39% relative to the blank …
Sewer Pipe Condition Assessment Using An Ensemble Machine Learning Framework For Infrastructure Decision Support, Mahnaz Rouhi
Sewer Pipe Condition Assessment Using An Ensemble Machine Learning Framework For Infrastructure Decision Support, Mahnaz Rouhi
Civil Engineering Dissertations
Aging wastewater infrastructure presents significant challenges for municipalities across the United States, with many sewer networks approaching or exceeding their design life. Conventional inspection methods, such as closed-circuit television (CCTV), are limited by subjectivity, cost, and inefficiency. To address these challenges, this study develops an ensemble machine learning framework for assessing the structural condition of sewer pipelines using inspection records enriched with geospatial attributes.
The primary objective of this research is to enhance predictive accuracy, interpretability, and decision-support for risk-based asset management. The scope of the study encompasses 4,802 CCTV inspection records from Dallas, TX, and Tampa, FL, integrating physical, …
Videoscoop: A Non-Traditional, Domain-Independent Framework For Video Analysis, Umme Hafsa Billah
Videoscoop: A Non-Traditional, Domain-Independent Framework For Video Analysis, Umme Hafsa Billah
Computer Science and Engineering Dissertations
Due to the proliferation of cameras in handheld devices and the widespread use of CCTV, images and videos have become a preferred alternative for capturing and disseminating information. Automated analysis for understanding image or video contents (e.g., objects, activities, backgrounds, situations of interest, etc.) is critical for many applications such as Civic Monitoring, Surveillance (in general), monitoring activities in Assisted Living environments, and many more. Image and Video Analysis (IVA) research has been ongoing for several decades, resulting in numerous techniques for algorithmically analyzing and understanding image and video contents.
Image Analysis (IA) has advanced in several areas, including object …
Deep Learning For Wireless Communications, Swarada Ajit Kulkarni
Deep Learning For Wireless Communications, Swarada Ajit Kulkarni
Electrical Engineering Dissertations
The rapid evolution of wireless communication imposes stringent requirements for ultra-reliable, low-latency transmission in dynamic, interference-prone environments. Traditional model-driven signal processing struggles to adapt to nonlinear hardware effects, time-varying channels, and complex interference patterns. Deep learning (DL) offers a transformative, data-driven alternative, enabling end-to-end optimization and robust adaptation under uncertain propagation conditions.
This dissertation investigates deep learning architectures for intelligent and resilient wireless communication through three complementary contributions. The first introduces a Vision Transformer (ViT)-based modulation classification framework that leverages self-attention to capture local and global dependencies in spectrogram representations of Quadrature Amplitude Modulation (QAM) signals. The ViT achieves superior …
Artificial Sense-Making Dataset, Jason A. Bengtson, John Sandstrom, Nathan Camp
Artificial Sense-Making Dataset, Jason A. Bengtson, John Sandstrom, Nathan Camp
NMSU Library: Datasets
No abstract provided.