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Full-Text Articles in Physical Sciences and Mathematics

2d Respiratory Sound Analysis To Detect Lung Abnormalities, Rafia Sharmin Alice, Kc Santosh Feb 2023

2d Respiratory Sound Analysis To Detect Lung Abnormalities, Rafia Sharmin Alice, Kc Santosh

SDSU Data Science Symposium

Abstract. In this paper, we analyze deep visual features from 2D data representation(s) of the respiratory sound to detect evidence of lung abnormalities. The primary motivation behind this is that visual cues are more important in decision-making than raw data (lung sound). Early detection and prompt treatments are essential for any future possible respiratory disorders, and respiratory sound is proven to be one of the biomarkers. In contrast to state-of-the-art approaches, we aim at understanding/analyzing visual features using our Convolutional Neural Networks (CNN) tailored Deep Learning Models, where we consider all possible 2D data such as Spectrogram, Mel-frequency Cepstral Coefficients …


Polyethersulfone Thin-Film Nanocomposite Membrane Embedded With Amine-Functionalized Graphene Oxide For Desalination Applications, Ahmed Bahaeldin Jan 2023

Polyethersulfone Thin-Film Nanocomposite Membrane Embedded With Amine-Functionalized Graphene Oxide For Desalination Applications, Ahmed Bahaeldin

Theses and Dissertations

Thin-film nanocomposite (TFN) desalination membranes were prepared based on a polyethersulfone (PES) support, where the polyamide (PA) layer was embedded with amine-functionalized graphene oxide (GO). The effect of adding various concentrations of functionalized and un-functionalized GO on the desalination performance, hydrophilicity, and morphology of the membranes was additionally assessed throughout this work. Scanning electron microscopy (SEM) measurements were used to assess the morphology of the membranes in combination with Brunauer-Emmett-Teller (BET) analysis. Contact angle measurements were used to gauge the hydrophilicity of the synthesized membranes. The membrane with the best desalination performance contained 1x10-3 wt/vol% of functionalized GO in …


Electromagnetic Theory And Applications, Nicholas Madamopoulos, George Kliros Jan 2023

Electromagnetic Theory And Applications, Nicholas Madamopoulos, George Kliros

Open Educational Resources

This book intends to provide both the fundamentals of Electromagnetics but also some practical applications of the concepts covered. Having taught electromagnetics for several years, the authors feel that many times the field of electromagnetics comes as “old” and often times students do not appreciate the concepts and their importance in everyday applications. The authors intend to accompany the EM concepts with life applications. Hence, students may see the direct impact of the knowledge they acquire through the study of the field of electromagnetics and better appreciate the field.


Workforce Of The Future Begins With Aviation Stem, Lyndsay Digneo Jan 2023

Workforce Of The Future Begins With Aviation Stem, Lyndsay Digneo

National Training Aircraft Symposium (NTAS)

The United States has always been a world leader in aviation. This leadership position relies on the strength of the American STEM workforce and the quality of the nation’s educational, industrial, and government institutions. Therefore, it is imperative to nurture today’s students to become a well-trained STEM workforce in the future.

The Federal Aviation Administration (FAA) William J. Hughes Technical Center (WJHTC) recognizes that in pursuing its mission of aviation research, engineering, development, and test and evaluation, it is in a unique position to support aviation STEM activities for schools (K-12), post-secondary institutions, and community organizations. In 2016, the Technical …


A Bidirectional Deep Lstm Machine Learning Method For Flight Delay Modelling And Analysis, Desmond B. Bisandu, Irene Moulitsas Jan 2023

A Bidirectional Deep Lstm Machine Learning Method For Flight Delay Modelling And Analysis, Desmond B. Bisandu, Irene Moulitsas

National Training Aircraft Symposium (NTAS)

Flight delays can be prevented by providing a reference point from an accurate prediction model because predicting flight delays is a problem with a specific space. Only a few algorithms consider predicted classes' mutual correlation during flight delay classification or prediction modelling tasks. None of these existing methods works for all scenarios. Therefore, the need to investigate the performance of more models in solving the problem of flight delay is vast and rapidly increasing. This paper presents the development and evaluation of LSTM and BiLSTM models by comparing them for a flight delay prediction. The LSTM does the feature extraction …


Integrated Organizational Machine Learning For Aviation Flight Data, Michael J. Pritchard, Paul Thomas, Eric Webb, Jon Martin, Austin Walden Jan 2023

Integrated Organizational Machine Learning For Aviation Flight Data, Michael J. Pritchard, Paul Thomas, Eric Webb, Jon Martin, Austin Walden

National Training Aircraft Symposium (NTAS)

An increased availability of data and computing power has allowed organizations to apply machine learning techniques to various fleet monitoring activities. Additionally, our ability to acquire aircraft data has increased due to the miniaturization of small form factor computing machines. Aircraft data collection processes contain many data features in the form of multivariate time-series (continuous, discrete, categorical, etc.) which can be used to train machine learning models. Yet, three major challenges still face many flight organizations 1) integration and automation of data collection frameworks, 2) data cleanup and preparation, and 3) embedded machine learning framework. Data cleanup and preparation has …


Acknowledgments Of Reviewers Jan 2023

Acknowledgments Of Reviewers

Journal of Sustainable Mining

No abstract provided.


Potential Of Biduri Fiber (Calotropis Gigantea) As Material For Oil Spill Absorbent, Anne Sukmawati, Wulan Septiani Jan 2023

Potential Of Biduri Fiber (Calotropis Gigantea) As Material For Oil Spill Absorbent, Anne Sukmawati, Wulan Septiani

Journal of Materials Exploration and Findings (JMEF)

Biduri fiber (Calotropis gigantea) is a natural hollow fiber with hydrophobic and oleophilic properties potentially used as oil spilled sorbent from seawater. This study aims to determine the absorption capacity and efficiency of the Biduri fiber and membrane to fuel oil. Measurement of oil absorption to seawater was carried out at various fiber weights (0.5-1.5 g), fiber composition (50-95%), contact time (10-90 minutes), temperature (30 and 50°C), and compared with commercial products. The results showed that the fiber weight variation of 0.5-1.5 g has an average absorption efficiency of 96.67%, and the highest absorption was obtained in a weight of …


Development Of Battery Materials To Function As Corrosion Protection On Car Body Plates, Tubagus Noor Rohmannudin, Sulistijono Sulistijono, Noval Adrinanda, Faridz Wira Dharma, Samuel Areliano Jan 2023

Development Of Battery Materials To Function As Corrosion Protection On Car Body Plates, Tubagus Noor Rohmannudin, Sulistijono Sulistijono, Noval Adrinanda, Faridz Wira Dharma, Samuel Areliano

Journal of Materials Exploration and Findings (JMEF)

Most car bodies made for mass production are made from steel or aluminum. Both are strong metals, but steel is cheaper than aluminum and is more commonly used in lower-end cars for a broader consumer range. The weakness of steel compared to aluminum is that it is susceptible to corrosion under certain conditions, and thus it may deteriorate over time without proper care. To prevent corrosion, modern cars are coated with paint to prevent direct contact with the environment. As a second line of protection, a car battery can be connected to the body to create an impressed current cathodic …


Influence Of Synthesis Conditions On The Physicochemical And Electrocatalytic Properties Of Non-Stoichiometric Ba2sr2la2ti4o12 Perovskites, Ofeliya Kostadinova, Iliyan Popov, Simeon M. Stankov, Hristo Kolev, Tamara Petkov Jan 2023

Influence Of Synthesis Conditions On The Physicochemical And Electrocatalytic Properties Of Non-Stoichiometric Ba2sr2la2ti4o12 Perovskites, Ofeliya Kostadinova, Iliyan Popov, Simeon M. Stankov, Hristo Kolev, Tamara Petkov

Karbala International Journal of Modern Science

Present work studies the influence of the pretreatment milling media (deionized water (BLTOS-H) and isopropanol (BLTOS-i)) on the surface characteristics, structure, chemical composition and catalytic activity of non-stoichiometric Ba2Sr2La2Ti4O12 perovskites. The IR spectroscopy and XRD analyses shows a difference in the structure and phase composition of the two materials. X-ray photoelectron spectroscopy detects a Ba2+- and La3+-enriched and Sr2+-depleted surface. The BLTOS-i sample appears to exhibit higher specific surface area (SSA) and pore volume in comparison to BLTOS-H. The electrochemical tests showed that BLTOS-H sample have similar behavior to platinum at current densi-ties up to 10 mA cm-2, while BLTOS-i …


Using Dielectric Scatters To Selectively Excite Embedded Eigenstates In Cavity Resonators, Olugbenga Joshua Gbidi Jan 2023

Using Dielectric Scatters To Selectively Excite Embedded Eigenstates In Cavity Resonators, Olugbenga Joshua Gbidi

Theses and Dissertations

Bound states in the continuum (BICs) are waves that remain in the continuous spectrum of radiating waves that carry energy, however, still localized within the spectrum. BICs, also embedded eigenmodes, exhibit high quality factors that have been observed in optical and acoustic waveguides, photonic structures, and other material systems. Presently, there are limited means to select these BICs in terms of the quality factor and their excitation. In this work, we show that a different type of BIC, Quasi-BICs (Q-BICs), in open resonators can have their quality attuned by introducing embedded scatters. Using microwave cavities and dielectric scatters as an …


Hitting Two Birds With One Emissions-Based Maintenance Stone – A Literature Review On Improving Overall Productivity Of Underground Diesel Fleets, Johannes Deon Swanepoel, Jennifer Hines, Vinod Gopaldasani, Brian Davies Jan 2023

Hitting Two Birds With One Emissions-Based Maintenance Stone – A Literature Review On Improving Overall Productivity Of Underground Diesel Fleets, Johannes Deon Swanepoel, Jennifer Hines, Vinod Gopaldasani, Brian Davies

Journal of Sustainable Mining

Many industries regard occupational health and safety as a core value and an integral component to maintaining high productivity, and, thus, shareholder value. Diesel fleets’ engine maintenance is instrumental in ensuring affected workplaces meet production requirements while controlling health and safety hazards that these fleets introduce to the workplace. This systematic literature review focuses on production and occupational health and safety advantages associated with the implementation and adherence to an emissions-based maintenance (EBM) program. The literature review was conducted across eight databases relevant to workplace health and engineering. To be eligible for inclusion, the publication had to contain maintenance interventions …


Research On Vibration-Based Early Diagnostic System For Excavator Motor Bearing Using 1-D Cnn, Dorjsuren Yandagsuren, Tatsuki Kurauchi, Hisatoshi Toriya, Hajime Ikeda, Tsuyoshi Adachi, Youhei Kawamura Jan 2023

Research On Vibration-Based Early Diagnostic System For Excavator Motor Bearing Using 1-D Cnn, Dorjsuren Yandagsuren, Tatsuki Kurauchi, Hisatoshi Toriya, Hajime Ikeda, Tsuyoshi Adachi, Youhei Kawamura

Journal of Sustainable Mining

In mining, super-large machines such as rope excavators are used to perform the main mining operations. A rope excavator is equipped with motors that drive mechanisms. Motors are easily damaged as a result of harsh mining conditions. Bearings are important parts in a motor; bearing failure accounts for approximately half of all motor failures. Failure reduces work efficiency and increases maintenance costs. In practice, reactive, preventive, and predictive maintenance are used to minimize failures. Predictive maintenance can prevent failures and is more effective than other maintenance. For effective predictive maintenance, a good diagnosis is required to accurately determine motor-bearing health. …


"Semiclassical Mastermind", Curtis Bair, Alexa S. Cunningham, Joshua Qualls Jan 2023

"Semiclassical Mastermind", Curtis Bair, Alexa S. Cunningham, Joshua Qualls

Posters-at-the-Capitol

Games are often used in the classroom to teach mathematical and physical concepts. Yet the available activities used to introduce quantum mechanics are often overwhelming even to upper-level students. Further, the "games" in question range in focus and complexity from superficial introductions to games where quantum strategies result in decidedly nonclassical advantages, making it nearly impossible for people interested in quantum mechanics to have a simple introduction to the topic. In this talk, we introduce a straightforward and newly developed "Semiclassical Mastermind" based on the original version of mastermind but replace the colored pegs with 6 possible qubits (x+, x-, …


Lesker Pvd75 E-Beam/Thermal Evaporator (Pvd-02) Standard Operating Procedure, David S. Barth, Jason A. Röhr Jan 2023

Lesker Pvd75 E-Beam/Thermal Evaporator (Pvd-02) Standard Operating Procedure, David S. Barth, Jason A. Röhr

Standard Operating Procedures

Standard Operating Procedure for the Lesker PVD75 E-beam/Thermal Evaporator (PVD-02) located at the Quattrone Nanofabrication Facility within the Singh Center for Nanotechnology at the University of Pennsylvania


Predicting Young’S Modulus Of Indian Coal Measure Rock Using Multiple Regression And Artificial Neutral Network, Sayantan Chakraborty, Rohan Bisai, Rohit Roy, Sathish Kumar Palaniappan, Samir Kumar Pal, Karanam Uma Maheshwar Rao Jan 2023

Predicting Young’S Modulus Of Indian Coal Measure Rock Using Multiple Regression And Artificial Neutral Network, Sayantan Chakraborty, Rohan Bisai, Rohit Roy, Sathish Kumar Palaniappan, Samir Kumar Pal, Karanam Uma Maheshwar Rao

Journal of Sustainable Mining

Accurate information on Young’s modulus (E) is required for simulating rock deformation in mines; on the other hand, it is very cumbersome to obtain in the laboratory and collecting drilled cores in sufficient amounts, especially in the case of soft rocks, is quite impossible. Empirical equations were deducted for E from easily determinable rock properties, and the final model was selected through different statistical strength parameter tests. The generalization of the equation was verified through the normal distribution tests of residues of the equation. R2 came to be 0.609 and was validated using an artificial neural network with an improved …


Gravity And Electrostatic Separation Of Unburned Coal From A Selected Fly Ash, Krzysztof Wierzchowski, Agnieszka Klupa, Barbara Białecka, Joanna Całus Moszko Jan 2023

Gravity And Electrostatic Separation Of Unburned Coal From A Selected Fly Ash, Krzysztof Wierzchowski, Agnieszka Klupa, Barbara Białecka, Joanna Całus Moszko

Journal of Sustainable Mining

Unburned coal grains make it difficult to use fly ash economically, which causes energy losses in the fuel. The article presents the possibilities of separating unburned coal from selected fly ash. In order to assess the possibility of separation of unburned carbon, the analysis of grain density and ash composition was used. Unburned coal was separated by four methods – one wet gravity and three dry methods. It has been found that despite very fine ash grains, the quality and quantity of separation products are significantly dependent on the separation method used and the separated grains’ qualitative characteristics. The analysis …


Exploring The Characterization, Liberation And Flotation Response Of A Nigerian Low-Grade Copper Ore, Willie Nheta, Omoyemi O. Ola-Omole Jan 2023

Exploring The Characterization, Liberation And Flotation Response Of A Nigerian Low-Grade Copper Ore, Willie Nheta, Omoyemi O. Ola-Omole

Journal of Sustainable Mining

This study explores the characterization, liberation and flotation response of low-grade copper ore from Anka area, Zamfara state Nigeria. The ore was crushed, milled and sieved in accordance with BS 410 standard. It was characterized with XRD, XRF, SEM-EDS and AAS. Froth flotation was carried out with varying %solids, pH, retention time and collector dosages using SEX and sodium oleate. Particle size distribution of the ore shows its economic liberation between -150 and +106 µm while 80% passing corresponds to 175.7 µm using the Gaudin Schuhmann equation. However, according to metallurgical balance calculation, 63 µm proved to have the highest …


Production Management System In A Modern Coal And Coke Company Based On The Demand And Quality Of The Exploited Raw Material In The Aspect Of Building A Service-Oriented Architecture, Artur Dyczko Jan 2023

Production Management System In A Modern Coal And Coke Company Based On The Demand And Quality Of The Exploited Raw Material In The Aspect Of Building A Service-Oriented Architecture, Artur Dyczko

Journal of Sustainable Mining

The paper deals with the implementation of the JSW Capital Group’s (Poland) Demand and Quality Driven Production Management System (SPPJ – System Zarządzania Produkcją oparty na Popycie i Jakości) using a service-oriented architecture (SOA). The main components of the SPPJ architecture have been characterized, and the scope of their integration has been defined. The individual parts in the first area, i.e. quality management, have been described in detail. Due to the extensive nature of the issue, components in other areas, i.e. planning and scheduling, coal extraction and processing, coke production, as well as sales and logistics, have only been signalled. …


Improving Developers' Understanding Of Regex Denial Of Service Tools Through Anti-Patterns And Fix Strategies, Sk Adnan Hassan, Zainab Aamir, Dongyoon Lee, James C. Davis, Francisco Servant Jan 2023

Improving Developers' Understanding Of Regex Denial Of Service Tools Through Anti-Patterns And Fix Strategies, Sk Adnan Hassan, Zainab Aamir, Dongyoon Lee, James C. Davis, Francisco Servant

Department of Electrical and Computer Engineering Faculty Publications

Regular expressions are used for diverse purposes, including input validation and firewalls. Unfortunately, they can also lead to a security vulnerability called ReDoS (Regular Expression Denial of Service), caused by a super-linear worst-case execution time during regex matching. Due to the severity and prevalence of ReDoS, past work proposed automatic tools to detect and fix regexes. Although these tools were evaluated in automatic experiments, their usability has not yet been studied; usability has not been a focus of prior work. Our insight is that the usability of existing tools to detect and fix regexes will improve if we complement them …


Source Data For Xueyan Feng, Michael S. Dimitriyev & Edwin L. Thomas, "Soft, Malleable Double Diamond Twin", Xueyan Feng, Michael S. Dimitriyev, Edwin L. Thomas Jan 2023

Source Data For Xueyan Feng, Michael S. Dimitriyev & Edwin L. Thomas, "Soft, Malleable Double Diamond Twin", Xueyan Feng, Michael S. Dimitriyev, Edwin L. Thomas

Data and Datasets

Source data and code for Xueyan Feng, Michael S. Dimitriyev & Edwin L. Thomas, "Soft, malleable double diamond twin"


Machine Learning Predictions Of Electricity Capacity, Marcus Harris, Elizabeth Kirby, Ameeta Agrawal, Rhitabrat Pokharel, Francis Puyleart, Martin Zwick Jan 2023

Machine Learning Predictions Of Electricity Capacity, Marcus Harris, Elizabeth Kirby, Ameeta Agrawal, Rhitabrat Pokharel, Francis Puyleart, Martin Zwick

Systems Science Faculty Publications and Presentations

This research applies machine learning methods to build predictive models of Net Load Imbalance for the Resource Sufficiency Flexible Ramping Requirement in the Western Energy Imbalance Market. Several methods are used in this research, including Reconstructability Analysis, developed in the systems community, and more well-known methods such as Bayesian Networks, Support Vector Regression, and Neural Networks. The aims of the research are to identify predictive variables and obtain a new stand-alone model that improves prediction accuracy and reduces the INC (ability to increase generation) and DEC (ability to decrease generation) Resource Sufficiency Requirements for Western Energy Imbalance Market participants. This …


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). …


Cooperative Deep Q -Learning Framework For Environments Providing Image Feedback, Krishnan Raghavan, Vignesh Narayanan, Sarangapani Jagannathan Jan 2023

Cooperative Deep Q -Learning Framework For Environments Providing Image Feedback, Krishnan Raghavan, Vignesh Narayanan, Sarangapani Jagannathan

Publications

In this article, we address two key challenges in deep reinforcement learning (DRL) setting, sample inefficiency, and slow learning, with a dual-neural network (NN)-driven learning approach. In the proposed approach, we use two deep NNs with independent initialization to robustly approximate the action-value function in the presence of image inputs. In particular, we develop a temporal difference (TD) error-driven learning (EDL) approach, where we introduce a set of linear transformations of the TD error to directly update the parameters of each layer in the deep NN. We demonstrate theoretically that the cost minimized by the EDL regime is an approximation …


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 …


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. …


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 …


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 …


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 …


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 …