Digital Commons Network^™

Post-Wildfire Export Regimes Of Solutes Along The Gallinas-Pecos River-Santa Rosa Fluvial Network, Asmita Kaphle

Civil Engineering ETDs

Wildfires significantly contribute to water pollution when ash and sediments, including nutrients and metals, are released into fluvial systems, impacting aquatic ecosystems and surrounding communities. This study focuses on the impacts of the Hermits Peak-Calf Canyon Fire on the Gallinas and Pecos watersheds. It employs five monitoring stations along a 190km fluvial network to assess solute export regimes post-fire, where grab samples were collected for nutrient and metal analyses for a period of more than a year. The metrics used for characterizing mobilization, chemostatic, or dilution patterns indicated mobilization for most solutes at all sites upstream of Santa Rosa Lake. …

Detection Of Myofascial Trigger Points With Ultrasound Imaging And Machine Learning, Benjamin Formby

All Theses

Myofascial Pain Syndrome (MPS) is a common chronic muscle pain disorder that affects a large portion of the global population, seen in 85-93% of patients in specialty pain clinics [10]. MPS is characterized by hard, palpable nodules caused by a stiffened taut band of muscle fibers. These nodules are referred to as Myofascial Trigger Points (MTrPs) and can be classified by two states: active MTrPs (A-MTrPs) and latent MtrPs (L-MTrPs). Treatment for MPS involves massage therapy, acupuncture, and injections or painkillers. Given the subjectivity of patient pain quantification, MPS can often lead to mistreatment or drug misuse. A deterministic way …

Assessing The Thermodynamic Potential Of Deep Eutectic Solvents In The Absorption Of Greenhouse Gases Through Computational Methods, Thomas Michael Quaid

Theses and Dissertations

Greenhouse gas (GHG) capture is a fundamental technology in the fight against climate change. Some species of devastating GHGs like fluorinated compounds are released directly to the air from industrial processes. Some GHGs are co-produced in sustainably derived biofuels which require absorptive upgrading. The development of more efficient, cost effective, and environmentally friendly methods of capturing GHG’s from pollutant sources and industrial streams is of utmost importance in the fight against climate change. Deep eutectic solvents have entered the separations stage as potential disruptors to conventional solvent choices for a variety of applications. Deep eutectic solvents (DES) are compounds of …

Investigation On Mechanical, Tribological And Corrosion Resistance Properties Of Nano Sized Tio2/ Corrosion Resistance Properties Of Nano Sized Tio2/ B4c / Graphene Reinforced Aa 7075 Surface Composites B4c / Graphene Reinforced Aa 7075 Surface Composites Fabricated By Frictional Stir Processing Fabricated By Frictional Stir Processing, Majed Mohammed Hotami

Theses and Dissertations

Today, significant research efforts in the field of manufacturing engineering are focused on developing new lightweight, fuel-efficient and high-performance materials. The evolution of composite materials and related technologies has brought great advantages to material development throughout history. Composites are versatile materials with unique mechanical and physical properties tailored to specific application needs. Composites allow engineers to make design choices that traditional monolithic (unreinforced) materials cannot offer. Particle Reinforced Metal Matrix Composites (MMCs) offer a variety of advantages, including increased stiffness, improved fatigue resistance, increased wear resistance, and a low coefficient of thermal expansion. Aluminum MMC (AMMC) material systems outperform monolithic …

Deep Learning And Generative Ai Approaches For Automated Diagnosis And Personalized Treatment: Bridging Machine Learning, Medicine, And Biomechanics In Predicting Tissue Mechanics And Biomaterial Properties., Yasin Shokrollahi

Theses and Dissertations

Machine learning, particularly deep neural networks, has demonstrated significant potential in predicting high-dimensional tasks across various domains. This work encompasses a detailed review of Generative AI in healthcare and three studies integrating machine learning with finite element analysis for predicting biomechanical behaviors and properties. Initially, we provide a comprehensive overview of Generative AI applications in healthcare, focusing on Transformers and Denoising Diffusion models and suggesting potential research avenues to address existing challenges.

Subsequently, we addressed soccer-related ocular injuries by combining finite element analysis and machine learning to predict retinal mechanics following a soccer ball hit rapidly. The prediction errors are …

Effects Of Perforations On Internal Cathodic Protection And Recruitment Of Marine Organisms To Steel Pipes, Alexander John Paluzzi

Theses and Dissertations

Steel monopile support structures for offshore wind turbines require protection from corrosion on their external and internal surfaces. Cathodic protection (CP) works effectively to protect the external surfaces of monopiles, but internally, byproducts from aluminum sacrificial anode CP (SACP) and impressed current CP (ICCP) induce acidification that accelerates steel corrosion. This project investigated the effects of perforations on the performance of aluminum SACP and ICCP when used inside of steel pipes. Additionally, marine growth on the external and internal surfaces of the pipes was assessed to determine if CP byproducts affect marine organism development.

Two sealed and two perforated steel …

Assessing The Thermodynamic Potential Of Deep Eutectic Solvents In The Absorption Of Greenhouse Gases Through Computational Methods., Thomas Michael Quaid

Theses and Dissertations

Greenhouse gas (GHG) capture is a fundamental technology in the fight against climate change. Some species of devastating GHGs like fluorinated compounds are released directly to the air from industrial processes. Some GHGs are co-produced in sustainably derived biofuels which require absorptive upgrading. The development of more efficient, cost effective, and environmentally friendly methods of capturing GHG’s from pollutant sources and industrial streams is of utmost importance in the fight against climate change. Deep eutectic solvents have entered the separations stage as potential disruptors to conventional solvent choices for a variety of applications. Deep eutectic solvents (DES) are compounds of …

Upcyclying Of Polyethylene Terephtalate By Addition Of Thermoplastic Elastomer, Diego Francisco Bermudez

Open Access Theses & Dissertations

Continual overconsumption of single-use plastics has generated challenges of solid waste management across the United States. Common plastic waste management solutions, such as landfill, have caused the migration of contaminants into the environment consequently affecting not only the health of wildlife, but also that of human beings. Alternative strategies for the handling of single-use plastic such as polyethylene terephthalate (PET), used in the food packaging industry, can ultimately help mitigate the noxious consequences of single-use plastics affecting entire ecosystems. This study demonstrates a potential avenue of materials upcycling by studying the effects of coupling PET with the thermoplastic elastomer styrene-ethylene-butylene-styrene …

Development Of A 3d Printed Conductive Biopolymer For Cardiac Tissue Engineering, Britanny Lizeth Stark

Open Access Theses & Dissertations

Cardiovascular disease (CVD) is the leading cause of death in the US, with approximately 859,000 deaths each year. The major contributor to CVD is Acute Myocardial Infarction (AMI), which causes the death of approximately 25% of the cardiomyocytes present in the left ventricle of the heart. After AMI, the adult human heart has a very limited regenerative capacity. Moreover, the electrical propagation of the myocardium is severely disrupted, making the heart more susceptible to failure and patient death. However, current pharmacological treatments do not address the loss of cardiomyocytes and the disruption of electrical propagation in the heart. Tissue engineering …

Tracking Emissions In Power Systems, Kenji Santacruz

Open Access Theses & Dissertations

Greenhouse gas emissions have been increasing in concentration in the atmosphere, which poses risks to the environment. Since 2011, the 𝐶𝐶𝐶𝐶2 emissions reached an average of 410 parts per million (ppm). The burning of fossil fuels for energy production was identified as the primary source of these emissions, making up 25% of global emissions by sector in 2010. To promote sustainable practices, there is an increasing need to accurately track greenhouse gas emissions in power systems. To accomplish this, an emission tracking method that can provide emission information for each load point in real-time is needed. In addition, certain indices …

Sustainable Cities: Life-Cycle Cost Analysis Of Integrating Piezoelectric Harvesters Into Roadways, Heba Mohamed Gaber

Theses and Dissertations

Energy is essential in our modern era. Because of the increasing electricity consumption, sustainable and Renewable energy became a necessary global approach to fill the gap of the ongoing energy shortage in addition to the climate change crisis due to using conventional ways for energy production. Renewable energy is a global approach that has achieved great accomplishments during the last decades and is gradually increasing. Energy harvesting is considered one of the main resources for renewable energy. Energy harvesting from the roadways is an ingenious horizon for sustainable, clean, and renewable energy generation. Harvesting energy from the roadways by using …

Exploring The Impact Of Training Datasets On Turkish Stance Detection, Muhammed Sai̇d Zengi̇n, Berk Utku Yeni̇sey, Mücahi̇d Kutlu

Turkish Journal of Electrical Engineering and Computer Sciences

Stance detection has garnered considerable attention from researchers due to its broad range of applications, including fact-checking and social computing. While state-of-the-art stance detection models are usually based on supervised machine learning methods, their effectiveness is heavily reliant on the quality of training data. This problem is more prevalent in stance detection task because the stance of a text is intimately tied to the target under consideration. While numerous datasets exist for stance detection, determining their suitability for a specific target can be challenging. In this work, we focus on Turkish stance detection and explore the impact of training data …

A Comparative Study Of Blind Source Separation Methods, Burak Baysal, Mehmet Önder Efe

Turkish Journal of Electrical Engineering and Computer Sciences

Blind source separation is a popular research topic used for decomposing mixed signals, particularly in the field of music. In addition to exploring machine learning-based approaches, this study aims to examine the performance of classical algorithms in separating audio signal sources. The evaluation of different genres is a significant aspect of this study as the performance of the methods may vary across various musical genres and different audio components. This consideration provides a novel perspective and contributes to a comprehensive analysis of the algorithms. Using the MusDB-HQ dataset, we conducted experimental studies comparing classical algorithms, including FastICA, NMF, and DUET, …

A Comparative Study Of Yolo Models And A Transformer-Based Yolov5 Model For Mass Detection In Mammograms, Damla Coşkun, Dervi̇ş Karaboğa, Alper Baştürk, Bahri̇ye Akay, Özkan Ufuk Nalbantoğlu, Serap Doğan, İshak Paçal, Meryem Altin Karagöz

Turkish Journal of Electrical Engineering and Computer Sciences

Breast cancer is a prevalent form of cancer across the globe, and if it is not diagnosed at an early stage it can be life-threatening. In order to aid in its diagnosis, detection, and classification, computer-aided detection (CAD) systems are employed. You Only Look Once (YOLO)-based CAD algorithms have become very popular owing to their highly accurate results for object detection tasks in recent years. Therefore, the most popular YOLO models are implemented to compare the performance in mass detection with various experiments on the INbreast dataset. In addition, a YOLO model with an integrated Swin Transformer in its backbone …

Machine Learning Based Bioinformatics Analysis Of Intron Usage Alterations And Metabolic Regulation In Adipose Browning, Hamza Umut Karakurt, Pinar Pi̇r

Turkish Journal of Electrical Engineering and Computer Sciences

Adipose tissue is the major energy depot of the body and is considered an endocrine organ. Adipose tissue involves many different cell types, first and foremost, the adipocytes. White adipose cells that store fat and brown adipocytes that take part in lipid oxidation and heat generation are the most common cell types in adipose tissue. Even though brown adipocytes which have a high number of mitochondria and high fat-burning capacity are rare in adults, they are abundant in newborns and rodents. White adipocytes can gain a temporal brown-like character with a process called browning, which can be induced with cold …

Feature Selection Optimization With Filtering And Wrapper Methods: Two Disease Classification Cases, Serhat Ati̇k, Tuğba Dalyan

Turkish Journal of Electrical Engineering and Computer Sciences

Discarding the less informative and redundant features helps to reduce the time required to train a learning algorithm and the amount of storage required, improving the learning accuracy as well as the quality of results. In this study, we present different feature selection approaches to address the problem of disease classification based on the Parkinson and Cardiac Arrhythmia datasets. For this purpose, first we utilize three filtering algorithms including the Pearson correlation coefficient, Spearman correlation coefficient, and relief. Second, metaheuristic algorithms are compared to find the most informative subset of the features to obtain better classification accuracy. As a final …

The Effect Of Adding Aluminium On The Performance Of Zno Nrs/Pani In Their Application As Photoelectrochemical Water Splitting, Eprilia Trikusuma Sari, Nandang Mufti, Anissa Chairani Alfin Nadhira, Hari Wisodo, Markus Diantoro

Journal of Mechanical Engineering Science and Technology (JMEST)

Photoelectrochemical (PEC) is a new renewable energy technology that converts H2O into hydrogen and oxygen gas with the help of sunlight. A photoelectrochemical cell device consists of three main components, one of which is the photoanode. One of the materials that can be used as a photoanode is ZnO which has good electrical properties and is non-toxic. Nanorods-structured ZnO has the advantage of being able to increase light absorption due to its high surface area. However, the resulting performance is still quite low. So it is necessary to make modifications to the photoanode, one of which is by adding aluminium …

Image Semantic Segmentation Algorithm Based On Improved Deeplabv3+, Weiping Zhao, Yu Chen, Song Xiang, Yuanqiang Liu, Chaoyue Wang

Journal of System Simulation

Abstract: Mainstream image semantic segmentation networks currently face problems such as incorrec segmentation, discontinuous segmentation, and high model complexity, which cannot be flexibly and efficiently deployed in practical scenarios. To this end, an image semantic segmentation network that optimizes the DeepLabv3+ model is designed by comprehensively considering the network parameters, prediction time, and accuracy. The lightweight EfficientNetv2 is adopted to extract backbone network features and improve parameter utilization. In the atrous spatial pyramid pooling module, the mixed strip pooling is utilized to replace the global average pooling, and a depthwise separable dilated convolution is introduced to reduce parameters and improve …

A Novel Computing Scheme Based On Pattern Matching For Identification Of Nephron Loss And Chronic Kidney Disease Stage, Rehan Ahmad, Basant Mohanty

Turkish Journal of Electrical Engineering and Computer Sciences

Nephrons are the basic filtering units of the kidneys. Progression of chronic kidney disease (CKD) destroys nephrons permanently. Although there are many computing schemes suggested in recent years to identify CKD stages, no computing method has been suggested for identifying the nephron loss within kidney regions during CKD progression. In this paper, a novel pattern matching-based computation scheme is proposed to detect nephron loss in the kidney regions during CKD progression. We consider image registration (IR) with different transforms and a structural similarity index algorithm (SSIM) to match patterns of ultrasound images of kidney regions to identify the nephron loss. …

Fuzzycsampling: A Hybrid Fuzzy C-Means Clustering Sampling Strategy For Imbalanced Datasets, Abdullah Maraş, Çi̇ğdem Erol

Turkish Journal of Electrical Engineering and Computer Sciences

Classification model with imbalanced datasets is recently one of the most researched areas in machine learning applications since they induce to the emergence of low-performing machine learning models. The imbalanced datasets occur if target variables have an uneven number of examples in a dataset. The most prevalent solutions to imbalanced datasets can be categorized as data preprocessing, ensemble techniques, and cost-sensitive learning. In this article, we propose a new hybrid approach for binary classification, named FuzzyCSampling, which aims to increase model performance by ensembling fuzzy c-means clustering and data sampling solutions. This article compares the proposed approaches' results not only …

Rolling Bearing Fault Diagnosis Based On Weighted Domain Adaptive Convolutional Neural Network, Wenfeng Zhang, Zhichao Zhu, Dinghui Wu

Journal of System Simulation

Abstract: A rolling bearing fault diagnosis method based on a weighted domain adaptive convolutional neural network (WDACNN) is proposed to solve the problem that the data distribution of vibration signals of rolling bearings changes due to workload changes, which leads to poor generalization of fault diagnosis algorithm. In this method, the domain adaptation algorithm is embedded in the convolutional neural network to make the classifier based on the source domain achieve excellent generalization in the target domain, and the weight coefficient is introduced to weight the samples in the source domain to reduce the influence of the class weight deviation. …

Analyzing Transition Metallic Catalytic Converter Impact On Four-Stroke Motorcycle Fuel Consumption, Sudirman Rizki Ariyanto, Ata Syifa’ Nugraha, Wahyu Robby Cahyadi, Yelma Dianastiti, Muhammad Yandi Pratama

Journal of Mechanical Engineering Science and Technology (JMEST)

Increased exhaust emissions from motor vehicles have become a major concern in efforts to reduce air pollution. One developed solution is the use of transition metallic catalytic converter (TMCC) technology in vehicle exhaust systems. This study aims to compare the fuel consumption efficiency of three types of exhaust systems, namely standard exhaust without a catalyst (STD WC), the standard exhaust with Original Equipment Manufacturer catalyst (STD OEM), and an exhaust system equipped with a Copper-Coated Chrome Metallic Catalytic Converter (TMCC CuCr). The data analysis method employed a quantitative approach by collecting fuel consumption data at each rpm and analyzing the …

Validation Of Machine Vision And Action Sport Cameras For 3d Motion Analysis Model Reconstruction, John David Johnson, Michael Hales, Randy Emert

Faculty Articles

The study investigated the feasibility of using action sport cameras for motion analysis research. Data acquired from two different marker-based motion capture systems and six different camera combinations were analyzed for motion reconstruction accuracy. Two different calibration procedures were used to determine the influence on marker position reconstruction. Static and dynamic calibration mean merit score differences between the reference and experimental camera systems were 0.4 mm and 1.3 mm, respectively. Angular displacement difference between the reference and experimental camera systems range between 0.1 and 2.0 degrees. A systematic bias (− 0.54 to 0.19 degrees) was determined between the reference and …

Probability Distribution Fitting For Censored Data: A Practical Guide For Survival Analysis Of Nbi Data For Concrete Bridge Decks In Oregon, Asmaa Almeshaileh

Dissertations and Theses

Many sophisticated statistical models and analyses have been proposed to analyze datasets derived from the national bridge inventory (NBI). These objectives range from creating an understanding of the factors that drive the deterioration of bridge members to providing agencies with quantitative information for their maintenance and repair decisions. As these models become increasingly sophisticated and difficult to comprehend and implement, practicing engineers and owners are less likely to use them. Often, however, grouping data intuitively, for example, per a select structure type or condition rating and analyzing them using prescriptive statistics such as distribution fitting, does not only lie in …

Preparation And Lithium Storage Properties Of Carbon Confined Li3Vo4 Nano Materials, Jia-Qi Fan, Huan-Qiao Song, Jia-Ying An, Amantai A-Yi-Da-Na, Mo Chen

Journal of Electrochemistry

Li₃VO₄, as a promising anode material for lithium ion batteries, has been widely studied because of its low and safe voltage, and large capacity. However, its poor electronic conductivity impedes the practical application of Li₃VO₄ particularly at high rates. In this paper, carbon confined Li₃VO₄ nano materials (Li₃VO₄/C) were synthesized by hydrothermal and solid-phase method, and for comparison, the Li₃VO₄ (N) nano materials without carbon confinement and Li₃VO₄ (B) materials were also synthesized by pure solid-phase method. The composition, structure, …

Journal Of Roleplaying Studies And Steam (Jrpssteam) Vol. 2 [2023], (Issue 2)., Ricardo Morales-Carbajal, Cristo Leon, Sarah Lynne Bowman, Ligia-Estefania Estefania Canul-Noh, Vania C. Tovilla, Laura I. Quiroz, Elektra Diakolambrianou

Journal of Roleplaying Studies and STEAM

Editorial

Sangre, sudor, lágrimas y burocracia

Estamos muy contentos con la edición de este tercer número del Journal of Roleplaying Studies and STEAM, en primer lugar porque ¡ya contamos con ISSN!, suena a un logro menor pero debemos considerar los vericuetos burocráticos por los que hemos pasado semana tras semana para lograrlo. En segundo lugar, ¡por fin tenemos un artículo en inglés!, lo cual es motivo de celebración porque además es para nosotros un honor que sea de Elektra Diakolambrianou y Sarah Lynne Bowman, quienes en una gran muestra de confianza enviaron para dictamen su artículo denominado Dual Consciousness: What …

11.27.2023 Orsp Connect, Liz Williamson

ORED Newsletter

November 27, 2023 edition of the ORSP newsletter

Characteristics And Genetic Mechanism Of Low Sulfate In High-Salt Groundwater Of Permian Sandstone In Fudong Mining Area, Huainan, Jiang Chunlu, Huang Wendi, Fu Xianjie, Zheng Liugen, Cheng Shigui, Shan Chonglei

Coal Geology & Exploration

Hydrogeochemistry research of groundwater in coal mining areas is of great significance to the prevention and control of mine water and the comprehensive utilization of water resources. In terms of the low surfate of Permian sandstone water in Fudong mining area, Anhui Huainan Coalfield, the hydrochemical characteristics, water-rock interaction and low sulfate genesis of sandstone water were studied through water sampling and test by multivariate statistical method, in combination with the hydrogeological condition analysis and the sulfur and oxygen isotope technology. The results show that the Permian sandstone water in the study area is weakly alkaline, with an average TDS …

Evaluation Of Water Quality And Identification Of Pollution Factors In Mining Subsidence Area With High Phreatic Water Level, Hu Lin, Chen Yongchun, Xu Yanfei, Li Bing, Wang Jin, An Shikai, Chen Chen, Sun Hongjie, Miao Wei

Coal Geology & Exploration

Huainan mining area is characterized by a high phreatic water level, as well as a wide range and large area of coal mining subsidence areas, with the water quality monitoring data missing and prominent water environment. Therefore, the evaluation of water quality monitoring and identification of pollution factors in large subsidence area is of great significance to regional water environmental governance. Specifically, the water quality of the subsidence area was evaluated with the Nemerow pollution index method by testing the water samples collected from 175 sampling points in the study area. Meanwhile, the eutrophication state of water bodies was evaluated …

Towards A Virtual Reality Visualization Of Hand-Object Interactions To Support Remote Physical Therapy, Trudi Di Qi, Louanne Boyd, Scott Fitzpatrick, Meghna Raswan, Franceli L. Cibrian

Engineering Faculty Articles and Research

Improving object manipulation skills through hand-object interaction exercises is crucial for rehabilitation. Despite limited healthcare resources, physical therapists propose remote exercise routines followed up by remote monitoring. However, remote motor skills assessment remains challenging due to the lack of effective motion visualizations. Therefore, exploring innovative ways of visualization is crucial, and virtual reality (VR) has shown the potential to address this limitation. However, it is unclear how VR visualization can represent understandable hand-object interactions. To address this gap, in this paper, we present VRMoVi, a VR visualization system that incorporates multiple levels of 3D visualization layers to depict movements. In …