Engineering Commons^™

Acoustic Velocity Inversion Based On Convolutional Autoencoder Embedded With Fourier Neural Operator, Li Chen, Zhao Haixia, Bai Zhaowei, Hao Yufan

Coal Geology & Exploration

Background Seismic wave inversion serves as an effective method for obtaining the characteristics of structures, lithology, and physical properties of subsurface media using the arrival times, amplitude, and waveforms of seismic waves. Seismic inversion methods based on wave equations iteratively update model parameters using forward modeling. This generally involves extensive numerical simulations and optimization calculations, requiring large quantities of computational resources and time. In recent years, neural operators for deep learning, represented by the Fourier neural operator (FNO), have gained widespread attention. However, the original FNO structure fails to effectively learn the wavefield information with sharp changes in geological structures …

Intelligent Noise Suppression For 3d Post-Stack Seismic Data Of The Junggar Basin, Mao Haibo, Zhou Xin, Li Xiaofeng, Pan Long, Lin Juan, Liu Dawei, Wang Xiaokai

Coal Geology & Exploration

Objective The Junggar Basin is recognized as a significant petroliferous basin in China, and its hydrocarbon exploration targets have shifted to deeper strata. However, the 3D seismic data of this basin suffer from low signal-to-noise ratios (SNRs) and high data volumes due to the basin's complex near-surface conditions, the great depths of exploration targets, and seismic data acquisition methods characterized by wide azimuths, broadbands, and high density. This complicates the identification of hydrocarbon exploration targets, rendering the improvement in the quality of the 3D seismic data by noise suppression vitally important. Methods The progress in the deep learning theory and …

Transient Electromagnetic Numerical Simulation Based On The Transformer Neural Network, Wang Yunhong

Coal Geology & Exploration

Objective The deep learning-based transient electromagnetic (TEM) forward and inverse modeling methods are data-driven, requiring considerable numerical simulation results as supervisory data to train and assess neural networks. The conventional finite-difference time-domain (FDTD) method for TEM numerical simulation necessitates an iterative solution of time-domain Maxwell's equations. Therefore, this method is time-consuming and computationally intensive, failing to meet the data demand of deep learning-based TEM inversion. Methods This study introduced deep learning for TEM numerical simulation. Based on the transformer neural network architecture, a neural network for deep learning-based TEM numerical simulation was designed using an encoder-decoder structure. This neural network …

Surfaced-Related Multiple Attenuation Using The Cnn Method In The Nmo Domain, Huang Zhufu, Liu Jianfeng, Fang Wenqian, Fu Lihua

Coal Geology & Exploration

Objective The presence of surface-related multiples results in a lower accuracy in seismic data interpretations, and the effective multiple attenuation is a key step in seismic data processing. Multiples are coherent noise signals with similar characteristics to effective signals. It is difficult impossible to distinguish multiple signals from full-wave field data using a traditional convolutional neural network (CNN). Additionally, since the surface-related multiples vary significantly with surveyed areas, the CNN method will face more severe challenges when being transferred to other networks. Methods This study developed a CNN method based on the normal moveout correction (NMO) domain by introducing physical …

Impacts And Regulation Mechanisms Of Phase-Change Wall Microspheres On Cement Slurry Performance In Well Cementing, Zheng Mingming, Wu Zurui, Yan Shichun, Hu Yunpeng, He Juan, Zhang Yawei, Xiong Liang, Zhu Chengtao

Coal Geology & Exploration

Objective The current design of low-heat cement slurries prepared by adding microspheres with phase change materials as wall materials for well cementing in strata bearing natural gas hydrates (NGHs) fails to fully account for the impacts of the particle size and mass fraction of the microspheres on the performance of cement slurries. This leads to impaired cement slurry performance and increased costs, further inducing many problems with well cementing quality. Hence, it is significant to analyze the impacts and controlling mechanisms of the microspheres on cement slurry performance. Methods To eliminate the interference of the heat storage effect of the …

An Intelligent Identifying-While-Drilling Method For Geological Features Of Roof Strata In Coal Roadways Based On A 1dcnn-Bilstm-Cbam Model, Lei Zhiyong, Wang Jiawen, Fan Dong, Lu Feifei, Chen Weiming

Coal Geology & Exploration

Objective Most roof accidents in coal roadways occur in potential caving zones such as primary fissure-bearing zones and rock fracture zones. A significant approach to preventing roof accidents is to understand the geological features of roof strata in an accurate and timely manner and optimize support schemes and parameters of roofs. However, current methods for identifying the geological features of roof strata in roadways suffer from issues such as slow identification speeds, low efficiency, and high costs, thus failing to meet the demand for safe, efficient, and intelligent coal mining. Methods This study proposed a neural network model based on …

In-Situ Superconductor Temperature Sensor For Cryogenic Integrated Circuits, Emre Küçükyilmaz, Nazi̇f Orhun Tekci̇, Sasan Razmkhah, Ali̇ Bozbey

Turkish Journal of Electrical Engineering and Computer Sciences

Cryogenic circuits, such as those based on single flux quantum (SFQ) logic, function at extremely low temperatures. Therefore, the designs target the utilization of liquid helium (LHe) temperatures, maintaining them at 4.2 K. These specialized circuits can be subjected to measurement either within liquid helium (LHe) baths or enclosed within closed-cycle cryocoolers.However, when utilizing LHe in cryocooler systems, inherent weak thermal contact can lead to temperature gradients between the circuit chip and the cold head, where conventional temperature sensors are typically placed. To address this challenge, this study introduces an innovative on-chip temperature sensing approach that capitalizes on the temperature …

A New Dxccdita Based Meminductor Emulator And Its Application In Chaotic Oscillator, Bhawna Aggarwal, Shireesh Kumar Rai, Harsh Jain

Turkish Journal of Electrical Engineering and Computer Sciences

This work introduces a new dual-X current conveyor differential input transconductance amplifier (DXCCDITA) based meminductor emulator, alongside its application in chaotic oscillator has also been presented. To realize the designed meminductor emulator, one DXCCDITA, two resistors, and two capacitors are employed. Pinched hysteresis loops are achieved across a wide frequency range spanning from 100 Hz to 1.5 MHz, encompassing both decremental and incremental topologies. Additionally, the proposed circuit offers the flexibility to switch between incremental and decremental configurations using a simple switch. Through examination of non-volatility and transient responses, the efficiency of the presented emulator is evidently demonstrated. To further …

Fault Diagnosis Of Photovoltaic Array Based On Gated Residual Network With Multi-Head Self Attention Mechanism, Ahmed Mesai Belgacem, Mounir Hadef, Abdesslem Djerdir

Turkish Journal of Electrical Engineering and Computer Sciences

Effective fault identification and diagnosis in photovoltaic (PV) arrays is vital for improving the effectiveness, and safety of solar energy systems. While various artificial intelligence methods have successfully established fault detection and diagnosis models, introducing inefficiencies and potentially overlooking useful features. Moreover, these methods often employ neural networks with limited performance capabilities. In response to these challenges, this paper introduces an innovative intelligent model that integrates a combination of a gated residual neural network (GRN) and a multi-head self-attention mechanism (MHSA). To evaluate the proposed fault diagnosis model, the small-scale PV grid system is implemented, and fault simulation experiments, including …

A Surface-Based Approach For 3d Approximate Convex Decomposition, Onat Zeybek Kuşkonmaz, Yusuf Sahi̇lli̇oğlu

Turkish Journal of Electrical Engineering and Computer Sciences

Approximate convex decomposition enables the simplification of complex shapes into manageable convex components. In this work, we propose a novel surface-based method to achieve this which leads to efficient computation times and sufficiently convex results while avoiding over-approximating the input model. We start approximation using mesh simplification. Then we iterate over the surface polygons of the mesh and divide them into convex groups. We utilize planar and angular equations to determine suitable neighboring polygons for inclusion in forming convex groups. To ensure our method outputs a sufficient result for a wide range of input shapes, we run multiple iterations of …

Developing Linguistic Patterns To Mitigate Inherent Human Bias In Offensive Language Detection, Toygar Tanyel, Besher Alkurdi, Serkan Ayvaz

Turkish Journal of Electrical Engineering and Computer Sciences

With the proliferation of social media, there has been a sharp increase in offensive content, particularly targeting vulnerable groups, exacerbating social problems such as hatred, racism, and sexism. Detecting offensive language use is crucial to prevent offensive language from being widely shared on social media. However, the accurate detection of irony, implication, and various forms of hate speech on social media remains a challenge. Natural language-based deep learning models require extensive training with large, comprehensive, and labeled datasets. Unfortunately, manually creating such datasets is both costly and error-prone. Additionally, the presence of human-bias in offensive language datasets is a major …

A Cascade Genetic Algorithm Based Adaptive Backstepping Impedance Control For Upper Limb Rehabilitation Robot, Mawloud Aichaoui, Ameur Ikhlef

Turkish Journal of Electrical Engineering and Computer Sciences

This paper proposes a novel cascade impedance control architecture designed for the upper limb exoskeleton rehabilitation robot. The proposed architecture comprises two parts: Firstly, the impedance reference trajectory is shaped from the desired trajectory utilizing the desired impedance model and feedback contact torques. The second part of the proposed controller is an adaptive backstepping control, responsible for tracking the generated impedance reference trajectory. Notably, the proposed adaptive backstepping impedance controller is non-model-based control approach, eliminating the need for the robot's model. Furthermore, a genetic algorithm is employed as an offline tuning method for the inner position loop controller, namely the …

Lgformer: Informer-Based Personalized Modeling For Blood Glucose Prediction, Xue Yuewei, Shaopeng Guan, Jia Wanhai

Turkish Journal of Electrical Engineering and Computer Sciences

Effective diabetes management relies on precise prediction of blood glucose levels to minimize complications. However, the patterns and fluctuations in blood glucose vary significantly among patients, posing a challenge for existing prediction methods. Many current approaches fail to accommodate these individual differences, leading to less reliable predictions. In response to this challenge, we present LGformer, a novel prediction model based on the Informer architecture, designed to enhance both flexibility and accuracy. LGformer improves upon Informer by integrating LSTM and GRU layers into its probSparse Self-attention mechanism, allowing for personalized processing of blood glucose data tailored to each patient's unique profile. …

Towards Human-Machine Collaboration In Autonomous Material Handling On Construction Sites, Jyrki Oraskari, Lukas Kirner, Marit Zöcklein, Sigrid Brell-Cokcan

Human-Machine Communication

In the contemporary construction industry, the shortage of skilled labor has prompted the exploration of automation as a remedy and machine autonomy as a potential solution to the environmental conditions at the site. This research explores the balance between human oversight and the independent decision-making capabilities of robots for material delivery on construction sites. Using a scenario-based approach, autonomy in construction robotics is evaluated across four human-machine interaction cases with spatial and temporal dimensions. The expected outcomes revolve around improved safety through better human-machine communication and establishing an interoperable data model to enhance robot autonomy. This aims to automate tasks …

Characterizing West Florida Shelf Reef Fish Communities Using A Scientific Echosounder, Edmund A. Hughes

USF Tampa Graduate Theses and Dissertations

The advancement and application of non-invasive fisheries survey technologies, such as the scientific echosounder, have significantly enhanced our understanding of fish populations and their habitats, more recently in regions where traditional sampling methods are limited, such as complex reef habitats. This research, conducted as part of the Continental Shelf Characterization, Assessment, and Mapping Project (C-SCAMP) on the West Florida Shelf, leverages acoustic and visual technologies to investigate the distribution of fish densities, fish target strength and length relationships, and the relationship between seafloor topography and fish biomass distribution.

The first study compared reef fish densities estimated from near-concurrent acoustic (Simrad …

Analysing Sound Characteristics Of Cello And Violin Using Fast Fourier Transform, Sinin Hamdan, Khairul Anwar Mohamad Said, Ahmad Faudzi Musib, Marini Sawawi, Aaliyawani Ezzerin Sinin

ASEAN Journal on Science and Technology for Development

The unique sound characteristics of music are based on multiple harmonic frequencies that exist within the sound waves. Through Fast Fourier Transform (FFT) software, the wave can be broken down into frequency and amplitude components. Spectrum analysis can be used quantitatively to describe these sound characteristics. In this paper, the frequency range present in the spectrum and the average intensity of the first 10 high notes in the sound are used to classify the sound characteristics of the cello and violin. This is done by generating a frequency (x-axis) and amplitude (y-axis) graph for the sounds of the cello and …

Sdf-1Α Mediates Primary Tumor Escape In Glioblastoma Through Activation Of Mesenchymal Transitions, Charles T. Froman-Glover

The Cardinal Edge

Glioblastoma (GBM), a highly aggressive primary brain tumor originating in glial cells, poses a significant challenge due to its rapid growth and invasive nature within healthy brain tissue.

Current treatments involve surgical resection, chemotherapy, and radiation. These treatments alone are not enough to cure this disease, and a better understanding of the mechanics of the tumor's micro-environment is imperative to furthering the field of cancer research. This research focuses on understanding the tumor microenvironment's impact, specifically investigating the role of stromal cell-derived factor 1 (SDF-1) mechanics on GBM aggressiveness. SDF-1 is known to facilitate disease progression by facilitating chemotaxis toward …

Design And Implementation Of Attitude Control System For Gnssas 6u Cubesat, Anoud Nasser Alkatheeri

Thesis/ Dissertation Defenses

This thesis presents the design and simulation of the Attitude Control System (ACS) for the GNSSaS 6U CubeSat, developed by the National Space Science and Technology Center (NSSTC) at UAE University. The CubeSat's mission is to enhance GNSS signal accuracy, which requires precise attitude control to achieve this objective. The ACS utilizes magnetorquers and reaction wheels for actuation. The primary objective of this thesis is to design an ACS that fulfills the mission’s performance requirements, including maintaining pointing accuracy in both fine and medium pointing modes. To achieve this, a comprehensive disturbance analysis was conducted, leading to the selection of …

Motivating Sustainability Through The State Of Biologically Inspired Design, Bryan Watson

Sustainability Conference

There are multiple arguements for sustainability, but one that resonates with environmentalists and the public alike is the need for preservation to all us to discovery natural solutions to our problems. Common examples often given include medical discoveries, unique mechanisms, and new materials. This presentation focuses on two ideas to motivate sustainability. First, what is the current state of biologically inspired design? Is there more to learn from nature? To answer these questions, recent research is presented which examined 660 Biologically Inspired Design samples from three data sources: Google Scholar, Google News, and the Asknature.org “Innovations” database. The data were …

Sustainable Flight Training Schools And Their Role To Meet Net Zero Targets, Eva Maleviti

Sustainability Conference

This presentation is part of a wider research project to identify the elements that must be considered regarding flight training schools’ role in aviation sustainability. Net Zero Pathways and goals, emission schemes, design specifications, and sustainable fuels are some of the most popular changes for airlines and manufacturers. Flight training schools must be at the forefront of promoting aviation sustainability to tomorrow’s professionals. The ICAO Carbon Offsetting Requirement Scheme for International Airlines (CORSIA) relies heavily on the firm and reliable information in the operators’ system. Proper emission calculation requires flight crews to feed valid and accurate flight information data. Hence, …

Design Of A Safe And Sustainable Airplane For Future, Henil Patel, Carlie Vogt, Matthew Talty, Jemimah Davies, Kyle Smothers, Mellisa Pritchet

Sustainability Conference

As a part of Airplane Preliminary Design course, this Design Note estimates the capabilities, performance, and stability behaviors of our conceptual airplane design, Boeing 7S7 – Sanctum prior to proceeding to the preliminary stage. This aircraft seeks to create a solution to achieving Net Zero Emissions by 2050 and increasing the safety measures. The design of this aircraft uses various analytical methods such as the DAPCA IV model, other methods were derived from design books. This design involved the use of software such as CATIA, VSP, SURFACES, Microsoft Excel, and Python. Results demonstrates that this aircraft is able to fly …

Designing Customized Loss Functions For Training Deep Neural Networks, Ali Pourramezan Fard

Electronic Theses and Dissertations

This dissertation explores the critical role of loss functions in enhancing the predictive performance of deep machine learning models. Loss functions are an integral element of all the ongoing advances we witness daily in this domain. I design custom loss functions and their impacts on various machine learning tasks, particularly in computer vision.

In the first stage of my research, I aim to improve the prediction performance of deep learning models by providing them with more precise feedback associated with task requirements. This led me to create the concept of assistive loss functions. My first proposed loss function, inspired by …

The Impact Of Cumulative And Acute Loading On Achilles Tendon Health, Performance, And Reported Pain In Collegiate Gymnasts, Julio Serrano Samayoa

Electronic Theses and Dissertations

Gymnasts are at a high risk of Achilles tendon (AT) injuries due to intense loads during takeoffs and landings. To better understand better the relationship between impact loading and its effects on tendon adaptation and athletic performance, this study uses Inertial Measurement Units (IMUs) to track AT loading across a collegiate gymnastics season. This data were compared against physiological and athletic performance metrics, obtained through force plates and ultrasound imaging, to explore how mechanical load influences reported pain and athletic performance. Results varied, with cumulative impacts being correlated with improved jump height (Spearman 0.362, Pearson 0.348), while peak power and …

Model-Based Navigation And Control Of Multirotor Uavs: A Machine Learning Approach, Serhat Sönmez

Electronic Theses and Dissertations

In recent decades, unmanned systems, particularly Unmanned Aerial Vehicles (UAVs), have seen significant advancement and unprecedented growth in military, civilian and public domain applications. Scientists have focused on enhancing UAV navigation and control through cutting-edge technologies and support tools. UAVs find applications in many fields, except military, such as agriculture, infrastructure inspection, wildlife monitoring, search and rescue, emergency response, border protection, to name but a few relevant civilian applications. Given the faster-than-exponential increase of available computational power, learning-based algorithms have emerged as a prominent tool for (real-time) multirotor UAV navigation and control. This dissertation centers around the fusion of conventional …

Security Vulnerabilities In Mobile Operating Systems Used In Iot Devices: An Examination Of Current Challenges And Countermeasures, Isain Cortes Jr.

Cybersecurity Undergraduate Research Showcase

No abstract provided.

Implementing The Safe System Approach At Intersections In Utah, Ian Patrick Macgregor

Theses and Dissertations

This thesis investigates the principles and elements of the Safe System Approach, a new paradigm in roadway safety. A compendium of practice was created to determine recommendations on how to implement the Safe System Approach at intersections and observe how other jurisdictions are implementing it. Several strategies identified include the Safe Systems at Intersections (SSI) methodology, Safe System Alignment Frameworks, Vision Zero communities, incorporating the Safe System Approach into the Strategic Highway Safety Plan (SHSP) or Highway Safety Improvement Program (HSIP), mandating the Safe System Approach be considered in all projects, and the Organizational Safety Culture Self-Assessment. These policies do …

Transportation Policies, Programs And History, Ivonne Audirac, Amber B. Raley, Jenifer Reiner, Soheil Sharifi-Asl

Mavs Open Press Open Educational Resources - Archive

Transportation Policies, Programs and History is a text intended for advanced undergraduate and beginning graduate students in urban and transportation planning. Contents by chapter include:

1. Brief history of U.S. transportation policy and traffic congestion: A persistent transportation planning issue.
2. Transportation planning and modeling.
3. Transportation programming and evaluation.
4. Equity in transportation planning
5. Mobility modes.
6. Transportation, accessibility, and the built environment.
7. Transit and transit-oriented development.
8. Transportation and new technologies.
9. Sustainable transportation.
10. Transportation in the Global South.

This textbook is part of a six-volume series produced under the grant OERTransport: Enabling Transportation Planning Professional Advancement awarded to the University of Texas-Arlington (UTA) …

Applications Of Computer Vision In Biomechanics And Orthopaedics, William Stewart Burton Ii

Electronic Theses and Dissertations

Machine learning has emerged as a key technology for enabling advanced computer vision systems. These systems now permeate many industries, and have enhanced traditional processes through autonomous interpretation of visual data. In the field of orthopaedics, the increasing prevalence of imaging highlights a need for similar tools. In many cases, however, direct translation of available frameworks fails to resolve the complex problems currently facing this field. Stringent performance requirements, complex visual environments, data scarcity, and implications for patient safety represent domain-specific factors which pose unique challenges to proven techniques. Novel approaches are needed to realize the full benefits of visual …

Evaluating Diy Air Cleaner Variability And Potential For Post-Construction Emission Of Aromatic Vocs During Wildfire Events, Brett W. Stinson, Amity L. Deters, Elliott T. Gall

Mechanical and Materials Engineering Faculty Publications and Presentations

While do-it-yourself (DIY) air cleaners such as the Corsi-Rosenthal Box (CR Box) are an increasingly popular choice for low-cost, accessible air cleaning during a wildfire event, construction and performance variability remains a concern. Using the same set of instructions, materials, and location of assembly, seven CR Boxes are constructed by individuals with no prior DIY air cleaner experience and clean air delivery rates (CADRs) are experimentally determined for each of the devices. Against a challenge aerosol consisting of fresh smoke generated via pine needle combustion, average number-based, PM2.5 CR Box CADRs range from 313–396 m3/h (relative standard deviation = 7.6 …

Computational Study Of The Evolution Of The Grain Boundary Network During Anisotropic Grain Growth, Jose Nino

Theses and Dissertations

The grain boundary network (GBN) of polycrystalline materials changes during grain growth, affecting the material's properties. This research presents the results of fully anisotropic grain growth simulations. We perform simulations using three GB energy functions: an energy function that considers a GB's 5 degrees of freedom, the Read-Shockley model, and isotropic. We analyze the impact of these energy functions on the morphological evolution and various microstructural statistics, such as crystallographic texture and triple junction distribution. The results demonstrate that while individual grain evolution varies with GB energy function, certain microstructural statistics reach similar steady states across different models. In addition, …