Digital Commons Network^™

A Practical Low-Dimensional Feature Vector Generation Method Based On Wavelet Transform For Psychophysiological Signals, Erdem Erkan, Yasemi̇n Erkan

Turkish Journal of Electrical Engineering and Computer Sciences

High-dimensional feature vectors entail computational cost and computational complexity. However, a successful classification can be obtained with an optimally sized feature vector consisting of distinctive features. With the widespread use of the internet and mobile devices, the need for systems with low computational costs is increasing day by day. In this study, starting from the idea that each motor imagery is represented as a subject-specific pattern in the brain, we propose a new and practical method that can generate a low-dimensional feature vector based on wavelet transform. The feature vector is obtained from the correlation between each trial and each …

Lsav: Lightweight Source Address Validation In Sdn To Counteract Ip Spoofing-Based Ddos Attacks, Ali̇ Karakoç, Fati̇h Alagöz

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, we propose a design to detect and prevent IP spoofing-based distributed denial of service (DDoS) attacks on software-defined networks (SDNs). DDoS attacks are still one of the significant problems for internet service providers (ISPs) and individual users. These attacks can disrupt customer services by targeting the availability of the system, and in some cases, they can completely shut down the target infrastructure. Protecting the system against DDoS attacks is therefore crucial for ensuring the reliability and availability of internet services. To address this problem, we propose a lightweight source address validation (LSAV) framework that leverages the flexibility …

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, …

New Modified Carrier-Based Level-Shifted Pwm Control For Npc Rectifiers Considered For Implementation In Ev Fast Chargers, Merve Mollahasanoğlu, Hakki Mollahasanoğlu, Hali̇l İbrahi̇m Okumuş

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, the aim is to evaluate three-phase (3?) AC/DC neutral point-clamped (NPC) power factor corrected (PFC) multilevel converter performance for electric vehicle (EV) fast chargers. Power factor correction for EV fast chargers is very important in terms of efficient power usage and charger compatibility with the grid. Multilevel converters improve charging efficiency, reduce voltage stresses on components, minimize electromagnetic interference, and support high power capabilities. For this reason, multilevel converters with the PFC feature contribute to the reliable and effective operation of the fast-charging infrastructure. Rectifier analysis is tested with extensive simulations using a new modified carrier-based level-shifted …

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 …

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 …

Ai Assisted Workflows For Computational Electromagnetics And Antenna Design, Oameed Noakoasteen

Electrical and Computer Engineering ETDs

These days large volumes of data can be recorded and manipulated with relative ease. If valuable information can be extracted from them, these vast amounts of data can be a rich resource not just for the digital economy but also for scientific discovery and development of technology. When it comes to deriving valuable information from data, Machine Learning (ML) emerges as the key solution. To unlock the potential benefits of ML to science and technology, extensive research is needed to explore what algorithms are suitable and how they can be applied.

To shine light on various ways that ML can …

Lif-Sn Composite Modification Layer To Modify Garnet/Lithium Metal Interface, Wu Yang, Xue-Fan Zheng, Yu-Qi Wu, Zheng-Liang Gong

Journal of Electrochemistry

The growing demands for electric vehicles and consumer electronics; as well as the expanding renewable energy storage market; have promoted extensive research on energy storage technologies with low costhigh energy density and safety. Lithium (Li) metal and solid-state electrolytes are considered as important components for next-generation batteries because of their great potential for improvements in energy density and safety performance. Inorganic garnet-type solid electrolytes with high Li-ion conductivity (about 10^-3 S·cm^-1) and high shear modulus (55 GPa) are considered to be ideal solid-state electrolytes; however; the issue of Li dendrite growth still obstructs their practical application. Herein; …

Constructing Carbon-Encapsulated Nifev-Based Electrocatalysts By Alkoxide-Based Self-Template Method For Oxygen Evolution Reaction, En-Hui Ma, Xu-Po Liu, Tao Shen, De-Li Wang

Journal of Electrochemistry

The development of green and sustainable water-splitting hydrogen production technology is beneficial to reducing the over-reliance on fossil fuels and realizing the strategic goal of "carbon neutral". As one of the half reactions for water splitting, oxygen evolution reaction has suffered the problems of sluggish four-electron transfer process and relatively slow reaction kinetics. Therefore, exploring efficient and stable catalysts for oxygen evolution reaction is of critical importance for water-splitting technology. Metal alkoxides are a series of compounds formed by the coordination function of metal ions with alcohol molecules. Metal alkoxides possess the double advantages of organic materials and inorganic materials, …

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, …

Peg-Water Electrolyte For High-Performance Zinc Iodine Dual-Ion Batteries, Xiao-Feng Qu, Yu-Ting Tang, Xin-Cheng He, Jia-Sheng Zhou, Zi-Heng Tang, Wen-Hua Feng, Jun Liu

Journal of Electrochemistry

Thanks to abundant resource and rapid redox reaction kinetics, iodine is regarded as promising positive materials inthe batteries. However, the shuttling effect due to the high solubility of iodine in the electrolyte makes the performance of battery poor. In this paper, polyethylene glycol (PEG400) and potassium iodide were added into zinc-ion aqueous electrolyte. PEG400 could complex with iodine to reduce the dissolution of iodine, therefore alleviating the formation of soluble triiodide (I₃^–) from iodine and iodide ions. Furthermore, this electrolyte was used in the battery with double carbon cloths as the current collectors, double separators and zinc …

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 …

The Effects Of Engineering Summer Camps On Middle And High School Students’ Engineering Interest And Identity Formation: A Multi-Methods Study, Timothy Robinson, Adam Kirn, Jenny Amos, Indira Chatterjee

Journal of Pre-College Engineering Education Research (J-PEER)

This multi-methods study explores changes in engineering interest and identity of middle and high school students (n = 79) attending introductory-level engineering summer camps at a large western land grant university. Middle school is a critical time when student interest, identity, and subsequently career choice begin to emerge and hence it is important that at this age students are given accurate information about engineering majors in college and future career opportunities in engineering. Data were collected over a period of two years in six summer camps. Three separate populations of middle and high school students participated in the summer …

Resonance Damping Of Lcl Filters Using Capacitor-Current Proportional-Integral Positive Feedback Method For Grid-Integrated Fuel Cell System, Majid Hosseinpour, Amin Kholousi

Emirates Journal for Engineering Research

Nowadays, the use of grid-integrated inverter proton exchange membrane fuel cell (PEMFC) systems is becoming more prevalent due to their efficiency and favorable environmental effects. Switching the grid-connected inverters causes high-frequency harmonics, which are eliminated using LCL filters. These filters are susceptible to instability when their resonant frequency is affected by changes in network impedance. Active damping methods are used to weaken the resonance of LCL filters. However, the grid-connected inverter is prone to be unstable under grid impedance variations due to the negative equivalent resistance resulting by digital control delays. As a solution to this problem, the capacitor-current proportional-integral …

Modeling And Analysis Of The Selective Lightning Strike Phenomenon At Locations In A Chemical Manufacturing Plant, Terver Maor

Doctoral Dissertations

This research was motivated by the overly simplified claims, from a previous study, that attempted to explain the cause of the reportedly repeated lightning strikes at certain locations in the chemical manufacturing plant. The findings, without any model, claimed that the electronic monitoring and control devices’ fire damage occurred, due to the raised electrical ground potential during lightning strikes. It proceeded that the raised electrical ground potential caused a power flow reversal, which exceeded the ratings of the affected electronic control modules, damaging them. This claim is inconsistent with published research work in the failure mechanisms of industrial control systems, …

Food-Water-Energy Nexus In The Perspective Of Green Revolution, Green Energy, Legal And Institutional Framework: A Killian Based Adjusted Bootstrap Approach, Zia Ur Rahman

CBER Conference

Food and water energy is crucial for human well-being, sustainable development, and poverty reduction. The growing global demand driven by population growth, economic development, urbanization, changing diets, technological advancements, and climate change projections indicates a significant increase in the need for these resources. Understanding the intricate interdependencies between food, water, and energy is essential for effectively addressing these challenges and fostering a prosperous and sustainable future. Therefore, this study incorporated statistical data collected from the Pakistan Economic Survey and the World Governance Indicator from 1990 to 2022 to elucidate the complex connection between food, water, and energy.

Does Green Energy Really Matter For Environment And Economic Sustainability? Validating The Long-Standing Existing Empirics On Pakistan Economy, Syed Kafait Hussain Naqvi

CBER Conference

The empirical outcomes of the study validate the widespread concern of the literature on the existence of the “growth hypothesis” which supports, that there is a systematic positive causation running from green energy to economic sustainability. The study findings suggest that regulations in the energy sector can encourage the applications of green energy resources, particularly in the real sector of the economy, leading to reduced emissions.

Demand Analysis Of Energy Mix In District Kotli Azad Jammu And Kashmir, Pakistan, Syed Kafait Hussain Naqvi

CBER Conference

This study is an effort to empirically analyze the household’s demand for energy mix (electricity, liquefied petroleum gas (LPG), kerosene, and firewood) in the District Kotli, AJK. The study estimates the demand elasticities (price and expenditure) by employing the Linear Approximate Almost Ideal Demand System (LA-AIDS) to 384 households sampled across District Kotli, AJK in 2017. The empirical estimations are carried out by using the Seemingly Unrelated Regression (SUR), keeping intact the adding-up, homogeneity and symmetry restrictions.

Multi-Model Digital Twins With Ai Forecasting For Seed To Stand Supply Chain, Rania Sherif Elashmawy

USF Tampa Graduate Theses and Dissertations

The present dissertation embodies a multi-faceted investigation aimed at enhancing strawberry production pre-harvest and post-harvest quality through data-driven approaches. It unfolds multi-stages framework.

The first stage presents a complete data collection and its preliminary statistical analysis obtained from the first phase of a large-scale soil study on how to improve strawberry production and achieve sustainable and high-quality harvests through sensor-assisted real-time field monitoring. Six real-time loggers were placed in an operational commercial strawberry farm in Central Florida for the entirety of a harvest season from soil preparation to planting to harvesting. Along with high-resolution soil sensory measurements including water content, …

A Moving Target Architecture As A Side-Channel Countermeasure, Rachel M. Cazzola

Electrical and Computer Engineering ETDs

We investigate a novel side-channel attack countermeasure called Side-channel Power analysis Resistance for Encryption Algorithms using Dynamic partial reconfiguration (SPREAD). The countermeasure leverages a strategy that is best characterized as a moving target architecture. Modern field-programmable gate array (FPGA) architectures provide support for dynamic partial reconfiguration (DPR), a feature that allows real-time reconfiguration of portions of the programmable logic (PL) while the FPGA continues to carry out computing tasks. Using the Advanced Encryption Standard (AES), the proposed moving target architecture leverages DPR to change the implementation characteristics of the substitution boxes (SBOX) in real time. We present experimental hardware results …

Study Of Si-Gan Photoconductive Switches Operating Modes Using Near-Ir Radiation, Nicolas Eduardo Gonzalez Padilla

Electrical and Computer Engineering ETDs

One of the most promising solid-state devices for fast switching and radio frequency generation applications is the photoconductive switch (PCSS). These devices have been thoroughly explored since the late 1980s and exhibit remarkable switching properties in gallium arsenide (GaAs). With recent advances in wide bandgap (WBG) semiconductor manufacturing processes, there has been an increasing interest in using WBG semiconductors to implement PCSS. WBG semiconductors could exhibit the same switching characteristics as GaAs while overcoming their poor power management and short lifetime under pulsed power conditions, making PCSS a reliable option in high-power applications. Gallium Nitride (GaN) has emerged as one …

Design, Optimization, And Hardware Deployment Of A Deep Learning Model For Gps Spoofing Detection Using Gnss Satellite Receiver Protocol Data, Clarizza Morales Chacon

Electrical and Computer Engineering ETDs

The contemporary GPS infrastructure plays a vital role in advancing Position, Navigation, and Timing (PNT) applications across various sectors, including transportation, commerce, finance, and aviation. To provide a robust and authenticated infrastructure for users, it is important to develop a methodology for verifying the authenticity of satellite navigation signals, especially in civilian applications using the C/A code. This thesis explores Machine Learning (ML) techniques, focusing on the analysis of Global Navigation Satellite System (GNSS) protocol messages like UBX and NMEA to detect anomalies in receiver and satellite behavior, indicative of potential spoofing. The research demonstrates the deployment of Machine Learning …

Characterization Analysis And Design Of Mid-Wave Infrared Iii- V-Based Type-Ii Superlattice Nbn Photodetectors For Space Applications, Alexander Timothy Newell

Electrical and Computer Engineering ETDs

The performance of the mid-wave infrared InGaAs/InAsSb nBn photodetector is investigated and its viability for space applications is assessed. Three structures are grown with unique absorber layer doping profiles via molecular beam epitaxy. Material and device characterizations are performed and analyzed to determine the effects of doping on fundamental material parameters and detector performance. Noise-equivalent irradiance is calculated to be a factor of 4x that of an ideal detector exhibiting Rule 07 dark current and 100% quantum efficiency, demonstrating high sensitivity. The structures are then irradiated with 63 MeV protons to evaluate the extent of performance degradation over the course …

Comparative Evaluation Of Investigation Methods For Estimating The Load-Dependent State Of Charge And End Of Discharge Of A Multirotor Uav Battery, Hanna Dibbern, Morten Roßberg, Claudia Werner

Journal of Aviation Technology and Engineering

As the scope of multirotor unmanned aerial vehicle (UAV) applications increases, more attention is being paid to UAV energy requirements, which vary depending on the mission profile. To obtain accurate information about the UAV battery during flight, the idea of a digital twin including a battery state estimation model is promising. For battery state estimation, a Kalman filter combination is the preferred approach in the literature. Comparing different Kalman filters, the unscented Kalman filter has a more accurate estimation for nonlinear systems compared to the extended Kalman filter. In the application of UAV flight with load-dependent flight missions, the comparison …

Stereoscopic-Based Mass Properties Estimation For Warhead Fragments, Alessia Nocerino, Katharine Larsen, Riccardo Bevilacqua, Elisabetta L. Jerome

Student Works

FRAGMENTATION characteristics such as spatial distribution, number of fragments, fragment velocity, and fragment mass can be used to characterize the lethality of a fragmenting weapon or any metal cased explosive [1,2]. However, most warhead tests and evaluations are limited to static arena testing, where fragment characteristics must be collected by hand. Recently, stereoscopic imaging techniques have been added to static arena tests. Using this method, position tracks can be collected for each fragment, and then velocity information can be found. This paper proposes a method to estimate the mass and moment of inertia using data collected by a stereoscopic imaging …

Employment Of Intelligent Predictive Maintenance On Thermal Power Plant Component Parts Taking Condenser Vacuum As A Case Study, Titus Ajewole

Tanzania Journal of Engineering and Technology (TJET)

This work proposes deployment of machine learning in the maintenance of individual constituent parts of steam power plant assemblages. With the condenser vacuum of a steam turbine (in a six-turbine plant assemblage) taken as a case study, information on the past operating parameters of the selected plant component was used to forecast its future working condition. Based on Exponential Gaussian Process of Regression, a model was developed, trained using the diachronic operational data, and employed in determining the future. A quantitative evaluation was employed to provide the distribution of the test values of the data about the lines of regression, …