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Full-Text Articles in Engineering

Development Of A Data Science Curriculum For An Engineering Technology Program, Salih Sarp, Murat Kuzlu, Otilia Popescu, Vukica M. Jovanovic, Zafer Acar Jan 2023

Development Of A Data Science Curriculum For An Engineering Technology Program, Salih Sarp, Murat Kuzlu, Otilia Popescu, Vukica M. Jovanovic, Zafer Acar

Engineering Technology Faculty Publications

Data science has gained the attention of various industries, educators, parents, and students thinking about their future careers. Statistics departments have traditionally offered data science courses for a long time. The main objective of these courses is to examine the fundamental concepts and theories. However, teaching data science courses has also expanded to other disciplines due to the vast amount of data being collected by numerous modern applications. Also, someone needs to learn how to collect and process data, especially from industrial devices, because of the recent development of Internet of Things (IoT) technologies. Hence, integrating data science into the …

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Development Of Sensing And Programming Activities For Engineering Technology Pathways Using A Virtual Arduino Simulation Platform, Murat Kuzlu, Vukica Jovanovic, Otilia Popescu, Salih Sarp Jan 2023

Development Of Sensing And Programming Activities For Engineering Technology Pathways Using A Virtual Arduino Simulation Platform, Murat Kuzlu, Vukica Jovanovic, Otilia Popescu, Salih Sarp

Engineering Technology Faculty Publications

The Arduino platform has long been an efficient tool in teaching electrical engineering technology, electrical engineering, and computer science concepts in schools and universities and introducing new learners to programming and microcontrollers. Numerous Arduino projects are widely available through the open-source community, and they can help students to have hands-on experience in building circuits and programming electronics with a wide variety of topics that can make learning electrical prototyping fun. The educational fields of electrical engineering and electrical engineering technology need continuous updating to keep up with the continuous evolution of the computer system. Although the traditional Arduino platform has …

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An Adaptive Image Restoration Algorithm Based On Hybrid Total Variation Regularization, Cong Thang Pham, Thi Thu Thao Tran, Hung Vi Dang, Hoai Phuong Dang Jan 2023

An Adaptive Image Restoration Algorithm Based On Hybrid Total Variation Regularization, Cong Thang Pham, Thi Thu Thao Tran, Hung Vi Dang, Hoai Phuong Dang

Turkish Journal of Electrical Engineering and Computer Sciences

In imaging systems, the mixed Poisson-Gaussian noise (MPGN) model can accurately describe the noise present. Total variation (TV) regularization-based methods have been widely utilized for Poisson-Gaussian removal with edge-preserving. However, TV regularization sometimes causes staircase artifacts with piecewise constants. To overcome this issue, we propose a new model in which the regularization term is represented by a combination of total variation and high-order total variation. We study the existence and uniqueness of the minimizer for the considered model. Numerically, the minimization problem can be efficiently solved by the alternating minimization method. Furthermore, we give rigorous convergence analyses of our algorithm. …

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Deep Learning-Based Classification Of Chaotic Systems Over Phase Portraits, Sezgi̇n Kaçar, Süleyman Uzun, Burak Aricioğlu Jan 2023

Deep Learning-Based Classification Of Chaotic Systems Over Phase Portraits, Sezgi̇n Kaçar, Süleyman Uzun, Burak Aricioğlu

Turkish Journal of Electrical Engineering and Computer Sciences

This study performed a deep learning-based classification of chaotic systems over their phase portraits. To the best of the authors' knowledge, such classification studies over phase portraits have not been conducted in the literature. To that end, a dataset consisting of the phase portraits of the most known two chaotic systems, namely Lorenz and Chen, is generated for different values of the parameters, initial conditions, step size, and time length. Then, a classification with high accuracy is carried out employing transfer learning methods. The transfer learning methods used in the study are SqueezeNet, VGG-19, AlexNet, ResNet50, ResNet101, DenseNet201, ShuffleNet, and …

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A Type-2 Fuzzy Rule-Based Model For Diagnosis Of Covid-19, İhsan Şahi̇n, Erhan Akdoğan, Mehmet Emi̇n Aktan Jan 2023

A Type-2 Fuzzy Rule-Based Model For Diagnosis Of Covid-19, İhsan Şahi̇n, Erhan Akdoğan, Mehmet Emi̇n Aktan

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, a type-2 fuzzy logic-based decision support system comprising clinical examination and blood test results that health professionals can use in addition to existing methods in the diagnosis of COVID-19 has been developed. The developed system consists of three fuzzy units. The first fuzzy unit produces COVID-19 positivity as a percentage according to the respiratory rate, loss of smell, and body temperature values, and the second fuzzy unit according to the C-reactive protein, lymphocyte, and D-dimer values obtained as a result of the blood tests. In the third fuzzy unit, the COVID-19 positivity risks according to the clinical …

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Transmission Network Planning For Realistic Egyptian Systems Via Encircling Prey Based Algorithms, Abdullah M. Shaheen, Ragab Elsehiemy, Mohammed Kharrich, Salah Kamel Jan 2023

Transmission Network Planning For Realistic Egyptian Systems Via Encircling Prey Based Algorithms, Abdullah M. Shaheen, Ragab Elsehiemy, Mohammed Kharrich, Salah Kamel

Turkish Journal of Electrical Engineering and Computer Sciences

Transmission network planning problem (TNPP) is one of the pertinent issues of the planning activities in power systems. It aims to optimally pick out the routs, types, and number of the new installed lines to confront the expected future loading conditions. In this line, this study proposes a new economic model to the TNPP. The aim of the model is to find the optimal transmission routes at least investment and operating costs. Three recent algorithms called grey wolf optimization algorithm (GWOA), spotted hyena optimization algorithm (SHOA) and whale optimization algorithm (WOA) are developed to solve the TNPP. The concept of …

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An Effective Hilbert-Huang Transform-Based Approach For Dynamic Eccentricity Fault Diagnosis In Double-Rotor Double-Sided Stator Structure Axial Flux Permanent Magnet Generator Under Various Load And Speed Conditions, Makan Torabi, Yousef Alinejad Beromi Jan 2023

An Effective Hilbert-Huang Transform-Based Approach For Dynamic Eccentricity Fault Diagnosis In Double-Rotor Double-Sided Stator Structure Axial Flux Permanent Magnet Generator Under Various Load And Speed Conditions, Makan Torabi, Yousef Alinejad Beromi

Turkish Journal of Electrical Engineering and Computer Sciences

Eccentricity fault in double-sided axial flux permanent magnet generator is very difficult to be detected as the fault generated variations in terminal electrical parameters are very weak and chaotic, especially at the initial stages of the fault occurrence. In addition, one of the most important problems in any fault diagnosis approach is the investigation of load and speed variation on the proposed indices. To overcome the aforementioned difficulty and problems, this paper adopts a novelty detection algorithm based on Hilbert-Huang transform (HHT) which is a time-frequency signal analysis approach based on empirical mode decomposition and the Hilbert transform. It is …

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Early Diagnosis Of Pancreatic Cancer By Machine Learning Methods Using Urine Biomarker Combinations, İrem Acer, Firat Orhan Bulucu, Semra İçer, Fatma Lati̇foğlu Jan 2023

Early Diagnosis Of Pancreatic Cancer By Machine Learning Methods Using Urine Biomarker Combinations, İrem Acer, Firat Orhan Bulucu, Semra İçer, Fatma Lati̇foğlu

Turkish Journal of Electrical Engineering and Computer Sciences

The most common type of pancreatic cancer is pancreatic ductal adenocarcinoma (PDAC), which accounts for the vast majority of pancreatic cancers. The five-year survival rate for PDAC due to late diagnosis is 9%. Early diagnosed PDAC patients survive longer than patients diagnosed at a more advanced stage. Biomarkers can play an essential role in the early detection of PDAC to assist the health professional. Machine learning and deep learning methods are used with biomarkers obtained in recent studies for diagnostic purposes. In order to increase the survival rates of PDAC patients, early diagnosis of the disease with a noninvasive test …

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Two New Mathematical Models For Two Level Electricity Network Design With Distributed Generation, Burçi̇n Çakir Erdener, Berna Dengi̇z, Zülal Güngör, İmdat Kara Jan 2023

Two New Mathematical Models For Two Level Electricity Network Design With Distributed Generation, Burçi̇n Çakir Erdener, Berna Dengi̇z, Zülal Güngör, İmdat Kara

Turkish Journal of Electrical Engineering and Computer Sciences

In the new millennium, traditional electrical power systems have undergone a significant change driven by a set of requirements arising from evolving and changing technology. Thus, fundamental changes have occurred in the way electrical energy is produced, transmitted, and distributed. This situation has revealed the need to expand existing networks or to establish new networks. The available literature revealed that particular attention to the latter one is still limited due to the complexity of the power system. The purpose of this study is to contribute to the body of literature that tries to address the gap at overall design of …

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Basismap: Sequence-Based Similarity Search For Geomagnetic Positioning, Tevfi̇k Kadioğlu, Burcu Erkmen Jan 2023

Basismap: Sequence-Based Similarity Search For Geomagnetic Positioning, Tevfi̇k Kadioğlu, Burcu Erkmen

Turkish Journal of Electrical Engineering and Computer Sciences

Indoor localization has become a popular topic with the development of location-based services (LBS) and indoor navigation systems. Beside these circumstances indoor positioning has been the focus of attention for researchers as the most important component of these applications. Many signals are used as distinguishable features for indoor positioning. RF-based Wi-Fi and BLE systems are the most popular ones and these have been preferred because of their high distinguishable feature. The use of geomagnetism, a natural signal found all over the world, has also been of interest to many researchers. Geomagnetic signals being distorted in the indoor area due to …

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The Effects Of The Dielectric Substrate Thickness And The Loss Tangent On The Absorption Spectrum: A Comprehensive Study Considering The Resonance Type, The Ground Plane Coupling, And The Characterization Setup, Umut Köse, Evren Ekmekçi̇ Jan 2023

The Effects Of The Dielectric Substrate Thickness And The Loss Tangent On The Absorption Spectrum: A Comprehensive Study Considering The Resonance Type, The Ground Plane Coupling, And The Characterization Setup, Umut Köse, Evren Ekmekçi̇

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, the effects of dielectric substrate thickness and the dielectric loss tangent on the absorption spectrum are investigated parametrically in S-band. The study has been conducted on two different absorber topologies, one is closed ring resonator (CRR) and the other is composed of a split ring resonator (SRR), to observe the effects on both LC - and dipole-type resonances. The studies on the substrate thickness have been performed both numerically and experimentally, whereas the studies on the dielectric loss tangent have been performed numerically. The results agree with the literature such that the substrate thickness has significant effects …

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Variational Autoencoder-Based Anomaly Detection In Time Series Data For Inventory Record Inaccuracy, Hali̇l Arğun, Sadetti̇n Emre Alpteki̇n Jan 2023

Variational Autoencoder-Based Anomaly Detection In Time Series Data For Inventory Record Inaccuracy, Hali̇l Arğun, Sadetti̇n Emre Alpteki̇n

Turkish Journal of Electrical Engineering and Computer Sciences

Retail companies monitor inventory stock levels regularly and manage them based on forecasted sales to sustain their market position. Inventory accuracy, defined as the difference between the warehouse stock records and the actual inventory, is critical for preventing stockouts and shortages. The root causes of inventory inaccuracy are the employee or customer theft, product damage or spoilage, and wrong shipments. In this paper, we aim at detecting inaccurate stocks of one of Turkey's largest supermarket chain using the variational autoencoder (VAE), which is an unsupervised learning method. Based on the findings, we showed that VAE is able to model the …

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Binary Text Classification Using Genetic Programming With Crossover-Based Oversampling For Imbalanced Datasets, Mona Aljero, Nazi̇fe Di̇mi̇li̇ler Jan 2023

Binary Text Classification Using Genetic Programming With Crossover-Based Oversampling For Imbalanced Datasets, Mona Aljero, Nazi̇fe Di̇mi̇li̇ler

Turkish Journal of Electrical Engineering and Computer Sciences

It is well known that classifiers trained using imbalanced datasets usually have a bias toward the majority class. In this context, classification models can present a high classification performance overall and for the majority class, even when the performance for the minority class is significantly lower. This paper presents a genetic programming (GP) model with a crossover-based oversampling technique for oversampling the imbalanced dataset for binary text classification. The aim of this study is to apply an oversampling technique to solve the imbalanced issue and improve the performance of the GP model that employed the proposed technique. The proposed technique …

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Lvq Treatment For Zero-Shot Learning, Firat İsmai̇loğlu Jan 2023

Lvq Treatment For Zero-Shot Learning, Firat İsmai̇loğlu

Turkish Journal of Electrical Engineering and Computer Sciences

In image classification, there are no labeled training instances for some classes, which are therefore called unseen classes or test classes. To classify these classes, zero-shot learning (ZSL) was developed, which typically attempts to learn a mapping from the (visual) feature space to the semantic space in which the classes are represented by a list of semantically meaningful attributes. However, the fact that this mapping is learned without using instances of the test classes affects the performance of ZSL, which is known as the domain shift problem. In this study, we propose to apply the learning vector quantization (LVQ) algorithm …

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On Evaluation Of The Indian Standard Topography Factor For Design Wind Speed On Escarpments, Abdul Haseeb Wani, Rajendra Kumar Varma, Ashok Kumar Ahuja Jan 2023

On Evaluation Of The Indian Standard Topography Factor For Design Wind Speed On Escarpments, Abdul Haseeb Wani, Rajendra Kumar Varma, Ashok Kumar Ahuja

ASEAN Journal on Science and Technology for Development

Standards on wind loads of various countries give wind loading map of respective country in which basic wind speeds are mentioned. Design wind speeds for designing buildings and other structures are evaluated by the structural designers from these basic wind speed values by incorporating many factors. One of these factors taken into consideration is for the local topography effect such as escarpments and hills. Standards on wind loads including Indian Standard give certain recommendations for the same. However, the steps involved in evaluating relevant modification factor for local topography as given in Indian Standard on Wind Loads are many. An …

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Liquid Waste Treatment For Sustainable Tapioca Industry: A Comparison Between Biogas And Liquid Sugar, Lilik Sulistyowati, Novi Andareswari, Rifqi Rahmat Hidayatullah, Nurul Amri Komarudin, Yuni Yolanda Jan 2023

Liquid Waste Treatment For Sustainable Tapioca Industry: A Comparison Between Biogas And Liquid Sugar, Lilik Sulistyowati, Novi Andareswari, Rifqi Rahmat Hidayatullah, Nurul Amri Komarudin, Yuni Yolanda

ASEAN Journal on Science and Technology for Development

There have been many studies examining the processing of tapioca wastewater. However, most studies have only researched at a laboratory scale without considering whether the treatment is appropriate. The study's purpose is to compare the processing technology of biogas and liquid sugar using technical, environmental, social, and cost-benefit analysis criteria to determine the appropriate technology to be applied. Literature study, observation, and interviews were used to determine the characteristics of each criterion. Cost-benefit analysis is calculated using the R/C Ratio. Furthermore, priority determination is carried out using the Exponential Comparison Method (MPE) using assessments from environmental and industrial experts on …

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Disintegration Evaluation Of Mudrock Fragment Through Wet-Dry Cycle By Quantitative Indices, Misbahudin Misbahudin, Dian Yesy Fatimah, Elfarino Trizani Jan 2023

Disintegration Evaluation Of Mudrock Fragment Through Wet-Dry Cycle By Quantitative Indices, Misbahudin Misbahudin, Dian Yesy Fatimah, Elfarino Trizani

ASEAN Journal on Science and Technology for Development

The disintegration of mudrock during moisture content change caused severe cases in several engineering works in Indonesia. One interesting site is Hambalang, Bogor Regency, West Java Province. The wetting and drying cycle is the easiest and fastest test to evaluate disintegration. After undergoing the process, samples of mudrocks disintegrate into smaller fragments. This paper evaluated the characteristics of the slaked material of mudrock by quantitative indices. The mudrock evaluated in this study underwent rapid disintegration in a short period, indicated by megascopic description and quantitative indices. In addition, evolutionary disintegration up to eight cycles has the same characteristics as the …

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A Survey On Artificial Intelligence-Based Acoustic Source Identification, Ruba Zaheer, Iftekhar Ahmad, Daryoush Habibi, Kazi Y. Islam, Quoc Viet Phung Jan 2023

A Survey On Artificial Intelligence-Based Acoustic Source Identification, Ruba Zaheer, Iftekhar Ahmad, Daryoush Habibi, Kazi Y. Islam, Quoc Viet Phung

Research outputs 2022 to 2026

The concept of Acoustic Source Identification (ASI), which refers to the process of identifying noise sources has attracted increasing attention in recent years. The ASI technology can be used for surveillance, monitoring, and maintenance applications in a wide range of sectors, such as defence, manufacturing, healthcare, and agriculture. Acoustic signature analysis and pattern recognition remain the core technologies for noise source identification. Manual identification of acoustic signatures, however, has become increasingly challenging as dataset sizes grow. As a result, the use of Artificial Intelligence (AI) techniques for identifying noise sources has become increasingly relevant and useful. In this paper, we …

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Comparative Static And Dynamic Analyses Of Solvents For Removal Of Asphaltene And Wax Deposits Above- And Below-Surface At An Iranian Carbonate Oil Field, Milad Norouzpour, Amin Azdarpour, Rafael M. Santos, Ali Esfandiarian, Moein Nabipour, Erfan Mohammadian, Abbas K. Manshad, Alireza Keshavarz Jan 2023

Comparative Static And Dynamic Analyses Of Solvents For Removal Of Asphaltene And Wax Deposits Above- And Below-Surface At An Iranian Carbonate Oil Field, Milad Norouzpour, Amin Azdarpour, Rafael M. Santos, Ali Esfandiarian, Moein Nabipour, Erfan Mohammadian, Abbas K. Manshad, Alireza Keshavarz

Research outputs 2022 to 2026

During production from oil wells, the deposition of asphaltene and wax at surface facilities and porous media is one of the major operational challenges. The crude oil production rate is significantly reduced due to asphaltene deposition inside the reservoir. In addition, the deposition of these solids inside the surface facilities is costly to oil companies. In this study, the efficiency of different solvents in dissolving asphaltene and wax was investigated through static and dynamic tests. The analysis of solid deposits from the surface choke of one of the Iranian carbonate oil fields showed that they consisted of 41.3 wt % …

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Stem Education And Retention For Black Women Using High-Impact Practices: Historically Black Colleges And Universities Vs. Predominantly White Liberal Arts Colleges, Annette Njei Jan 2023

Stem Education And Retention For Black Women Using High-Impact Practices: Historically Black Colleges And Universities Vs. Predominantly White Liberal Arts Colleges, Annette Njei

CMC Senior Theses

Black women are significantly underrepresented within the fields of science, technology, engineering, and mathematics (STEM). To address this, the Association of American Colleges & Universities crafted ten high-impact practices to increase student engagement and promote retention. This research paper examines how three specific high-impact practices (learning communities, mentoring, and undergraduate research experience) are utilized in STEM education.This research paper explores and compares the best high impact approaches that successfully teach and retain Black women within the various fields of STEM within the differing academic environments of historically Black colleges & universities ( HBCUs) and predominantly white liberal art colleges (PWLACs). …

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Effect Of Decorating Super Paramagnetic Iron Oxide Nanoparticles With Silver Nanoparticles On Their Magneto-Photo Thermal Heating Efficiency, Anthony Joseph Afful Jan 2023

Effect Of Decorating Super Paramagnetic Iron Oxide Nanoparticles With Silver Nanoparticles On Their Magneto-Photo Thermal Heating Efficiency, Anthony Joseph Afful

All Graduate Theses, Dissertations, and Other Capstone Projects

Cancer treatment is rather dangerous to the body, often involving many secondary effects, including nausea, hair loss, and weight fluctuations. The search for non-invasive, highly efficient, and targetable treatments ameliorates these issues. Super paramagnetic iron oxide nanoparticles (SPIONS) have been used for other medical purposes such as magnetic resonance imaging contrast agent and is being extensively studied as a potential candidate for many cancer therapeutic and diagnostic approaches due to its biocompatibility and superior magnetic properties. When subjected to an external alternating magnetic field SPIONS generate heat mainly due to the friction of the SPIONS against the fluid it is …

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Outstanding Advantages, Current Drawbacks, And Significant Recent Developments In Mechanochemistry: A Perspective View, Silvina Pagola Jan 2023

Outstanding Advantages, Current Drawbacks, And Significant Recent Developments In Mechanochemistry: A Perspective View, Silvina Pagola

Chemistry & Biochemistry Faculty Publications

Although known since antiquity, mechanochemistry has remained dormant for centuries. Nowadays, mechanochemistry is a flourishing research field at the simultaneous stages of gathering data and (often astonishing) observations, and scientific argumentation toward their analysis, for which the combination of interdisciplinary expertise is necessary. Mechanochemistry’s implementation as a synthetic method is constantly increasing, although it remains far from being fully exploited, or understood on the basis of fundamental principles. This review starts by describing many remarkable advantages of mechanochemical reactions, simplifying and “greening” chemistry in solutions. This description is followed by an overview of the current main weaknesses to be addressed …

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More On The Demons Of Thermodynamics, Daniel P. Sheehan, Garret Moddel, James W. Lee Jan 2023

More On The Demons Of Thermodynamics, Daniel P. Sheehan, Garret Moddel, James W. Lee

Chemistry & Biochemistry Faculty Publications

No abstract provided.

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Patch-Wise Training With Convolutional Neural Networks To Synthetically Upscale Cfd Simulations, John P. Romano, Alec C. Brodeur, Oktay Baysal Jan 2023

Patch-Wise Training With Convolutional Neural Networks To Synthetically Upscale Cfd Simulations, John P. Romano, Alec C. Brodeur, Oktay Baysal

Mechanical & Aerospace Engineering Faculty Publications

This paper expands the authors’ prior work[1], which focuses on developing a convolutional neural network (CNN) model capable of mapping time-averaged, unsteady Reynold’s-averaged Navier-Stokes (URANS) simulations to higher resolution results informed by time-averaged detached eddy simulations (DES). The authors present improvements over the prior CNN autoencoder model that result from hyperparameter optimization, increased data set augmentation through the adoption of a patch-wise training approach, and the predictions of primitive variables rather than vorticity magnitude. The training of the CNN model developed in this study uses the same URANS and DES simulations of a transonic flow around several NACA 4-digit airfoils …

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Model Based Systems Engineering With A Docs-As-Code Approach For The Sealion Cubesat Project, Kevin Chiu, Sean Marquez, Sharanabasaweshwara Asundi Jan 2023

Model Based Systems Engineering With A Docs-As-Code Approach For The Sealion Cubesat Project, Kevin Chiu, Sean Marquez, Sharanabasaweshwara Asundi

Mechanical & Aerospace Engineering Faculty Publications

The SeaLion mission architecture team sought to create a model-based systems engineering approach to assist improving CubeSat success rates as well as for the SeaLion CubeSat project to guide an implementation for the flight software. This is important because university CubeSat teams are growing in number but often have untrained students as their core personnel. This was done using a document-as-code, or docs-as-code, approach. With this the team created tools for the systems architecture with the Mach 30 Modeling Language to create an architecture that is easy to learn and use even for newly admitted team members with little to …

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Convolutional-Neural-Network-Based Des-Level Aerodynamic Flow Field Generation From Urans Data, John P. Romano, Oktay Baysal, Alec C. Brodeur Jan 2023

Convolutional-Neural-Network-Based Des-Level Aerodynamic Flow Field Generation From Urans Data, John P. Romano, Oktay Baysal, Alec C. Brodeur

Mechanical & Aerospace Engineering Faculty Publications

The present paper culminates several investigations into the use of convolutional neural networks (CNNs) as a post-processing step to improve the accuracy of unsteady Reynolds-averaged Navier–Stokes (URANS) simulations for subsonic flows over airfoils at low angles of attack. Time-averaged detached eddy simulation (DES)-generated flow fields serve as the target data for creating and training CNN models. CNN post-processing generates flow-field data comparable to DES resolution, but after using only URANS-level resources and properly training CNN models. This document outlines the underlying theory and progress toward the goal of improving URANS simulations by looking at flow predictions for a class of …

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Climate Change And The Law Of National Security Adaptation, Mark P. Nevitt Jan 2023

Climate Change And The Law Of National Security Adaptation, Mark P. Nevitt

Faculty Articles

The Department of Defense (DoD) is the largest employer in the world, owns and operates an enormous global real estate portfolio, and emits more Greenhouse Gases (GHGs) than many nations. Entrusted with the national security, the DoD is now threatened by a new enemy—climate change. Climate change imperils national security infrastructure while undermining the military’s capacity to respond to climate-driven disasters at home and abroad. However, legal scholarship has yet to address what I call “the law of national security adaptation” and related questions. For example, how do environmental and climate change laws apply to the U.S. military? What laws …

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Real-Time Polyp Analysis On Endoscopic Images Using Deep Learning Approach: Detection, Characterization And Size Estimation, Phanukorn Sunthornwetchapong Jan 2023

Real-Time Polyp Analysis On Endoscopic Images Using Deep Learning Approach: Detection, Characterization And Size Estimation, Phanukorn Sunthornwetchapong

Chulalongkorn University Theses and Dissertations (Chula ETD)

As medical devices advance, doctors adopt endoscopes to perform endoscopes for gastrointestinal disease screenings. For colonoscopy, skills such as polyp detection, polyp characterisation, and polyp size estimation needed to be practised while screening patients. This work aims to develop a deep learning model for performing polyp detection, characterisation, and size estimation to assist fellow doctors in these tasks. To maximise usability in assisting fellow doctors, the model must be able to perform in a real-time fashion. The work utilises existing object detection models for performing size estimation tasks. With the problems of data imbalances, we use depth information but without …

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Methyl Isobutyrate Production Via Hydrogenation Of Methyl Methacrylate Derived From Pyrolysis Of Acrylic Plastic Waste, Ramzi Nasser Ahmed Saif Jan 2023

Methyl Isobutyrate Production Via Hydrogenation Of Methyl Methacrylate Derived From Pyrolysis Of Acrylic Plastic Waste, Ramzi Nasser Ahmed Saif

Chulalongkorn University Theses and Dissertations (Chula ETD)

According to zero waste and upcycling policy, this work aims to utilize waste polymethyl methacrylate (PMMA) to methyl isobutyrate (MIB) via hydrogenation over nickel (Ni) based catalysts supported on commercial zeolites: HY, H-Beta-27 (SiO2/Al2O3 = 27 by mole), H-Beta-40 (SiO2/Al2O3 = 40 by mole) and H-ZSM-5. The appropriate catalyst support was first screen by using MMA monomer as the substrate for hydrogenation. Under 30 bar initial H2 pressure (PH2) at 250 °C for 3 h, Ni/H-Beta-27 catalyst effectively promoted hydrogenation to achieve 85% MMA conversion with 56.2 wt% MIB yield because of its larger external surface area and pore size. …

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A Review Of Piezoelectric Footwear Energy Harvesters: Principles, Methods, And Applications, Bingqi Zhao, Feng Qian, Alexander Hatfield, Lei Zuo, Tian-Bing Xu Jan 2023

A Review Of Piezoelectric Footwear Energy Harvesters: Principles, Methods, And Applications, Bingqi Zhao, Feng Qian, Alexander Hatfield, Lei Zuo, Tian-Bing Xu

Mechanical & Aerospace Engineering Faculty Publications

Over the last couple of decades, numerous piezoelectric footwear energy harvesters (PFEHs) have been reported in the literature. This paper reviews the principles, methods, and applications of PFEH technologies. First, the popular piezoelectric materials used and their properties for PEEHs are summarized. Then, the force interaction with the ground and dynamic energy distribution on the footprint as well as accelerations are analyzed and summarized to provide the baseline, constraints, potential, and limitations for PFEH design. Furthermore, the energy flow from human walking to the usable energy by the PFEHs and the methods to improve the energy conversion efficiency are presented. …

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