Electrical and Computer Engineering Commons^™

External Direct Sum Invariant Subspace And Decomposition Of Coupled Differential-Difference Equations, Keqin Gu, Huan Phan-Van

SIUE Faculty Research, Scholarship, and Creative Activity

This article discusses the invariant subspaces that are restricted to be external direct sums. Some existence conditions are presented that facilitate finding such invariant subspaces. This problem is related to the decomposition of coupled differential-difference equations, leading to the possibility of lowering the dimensions of coupled differential-difference equations. As has been well documented, lowering the dimension of coupled differential-difference equations can drastically reduce the computational time needed in stability analysis when a complete quadratic Lyapunov-Krasovskii functional is used. Most known ad hoc methods of reducing the order are special cases of this formulation.

The Need For Energy Storage On Renewable Energy Generator Outputs To Lessen The Geeth Effect, I.E. Short-Term Variations Mainly Associated With Wind Turbine Active Power Output, Tony Kealy

Articles

Many studies investigating the short-term variations associated with the power output from wind turbine generators utilise simulated or modelled data in the analysis. This current study uses short-term empirical data downloaded directly from operational wind turbines via electrical power quality meters. The empirical data shows that the short-term variations (one-second or sub-one-second timeframe) occur continuously over most of the power output range. A novel name is proposed, the Geeth Effect, for this variability phenomenon. The Geeth Effect is measured using the coefficient of variation mathematical expression and is likely contributing to (i) lower-than-expected financial and environmental benefits associated with …

An Improved Genetic Algorithm Based Fractional Open Circuit Voltage Mppt For Solar Pv Systems, Aakash Hassan, Octavian Bass, Mohammad A. S. Masoum

Research outputs 2022 to 2026

To extract the maximum power from solar PV, maximum power point tracking (MPPT) controllers are needed to operate the PV arrays at their maximum power point under varying environmental conditions. Fractional Open Circuit Voltage (FOCV) is a simple, cost-effective, and easy to implement MPPT technique. However, it suffers from the discontinuous power supply and low tracking efficiency. To overcome these drawbacks, a new hybrid MPPT technique based on the Genetic Algorithm (GA) and FOCV is proposed. The proposed technique is based on a single decision variable, reducing the complexity and convergence time of the algorithm. MATLAB/Simulink is used to test …

Directional Microwave Emission From Femtosecond-Laser Illuminated Linear Arrays Of Superconducting Rings, Thomas J. Bullard, Kyle Frische, Charlie Ebbing, Stephen J. Hageman, John Morrison, John Bulmer, Enam A. Chowdury, Michael L. Dexter, Timothy J. Haugan, Anil K. Patniak

Faculty Publications

We examine the electromagnetic emission from two photo-illuminated linear arrays composed of inductively charged superconducting ring elements. The arrays are illuminated by an ultrafast infrared laser that triggers microwave broadband emission detected in the 1–26 GHz range. Based on constructive interference from the arrays a narrowing of the forward radiation lobe is observed with increasing element count and frequency demonstrating directed GHz emission. Results suggest that higher frequencies and a larger number of elements are achievable leading to a unique pulsed array emitter concept that can span frequencies from the microwave to the terahertz (THz) regime.

Gps-Denied Navigation Using Synthetic Aperture Radar, Tucker Hathaway

All Graduate Theses and Dissertations, Fall 2023 to Present

In most modern navigation systems, GPS is used to determine the precise location of the vehicle; however, GPS signals can easily be blocked, jammed, or spoofed. These signals can be blocked by canyons or tall buildings. Additionally, adversaries can transmit signals that either make GPS signals difficult to interpret or that imitate real GPS signals and cause a navigation system to think it is somewhere other than its true location. GPS-denied (GPS-D) navigation is the process of navigating in the absence of GPS.

Many methods of performing GPS-D navigation have been proposed and explored. One such method is to use …

On The Effect Of Emotion Identification From Limited Translated Text Samples Using Computational Intelligence, Madiha Tahir, Zahid Halim, Muhmmad Waqas, Shanshan Tu

Research outputs 2022 to 2026

Emotion identification from text data has recently gained focus of the research community. This has multiple utilities in an assortment of domains. Many times, the original text is written in a different language and the end-user translates it to her native language using online utilities. Therefore, this paper presents a framework to detect emotions on translated text data in four different languages. The source language is English, whereas the four target languages include Chinese, French, German, and Spanish. Computational intelligence (CI) techniques are applied to extract features, dimensionality reduction, and classification of data into five basic classes of emotions. Results …

Modeling Hydration Kinetics Of Sustainable Cementitious Binders Using An Advanced Nucleation And Growth Approach, Taihao Han, Jie Huang, Gaurav Sant, Narayanan Neithalath, Ashutosh Goel, Aditya Kumar

Electrical and Computer Engineering Faculty Research & Creative Works

Supplementary cementitious materials (SCMs) are utilized to partially substitute Portland cement (PC) in binders, reducing carbon-footprint and maintaining excellent performance. Nonetheless, predicting the hydration kinetics of [PC + SCM] binders is challenging for current analytical models due to the extensive diversity of chemical compositions and molecular structures present in both SCMs and PC. This study develops an advanced phase boundary nucleation and growth (pBNG) model to yield a priori predictions of hydration kinetics—i.e., time-resolved exothermic heat release profiles—of [PC + SCM] binders. The advanced pBNG model integrates artificial intelligence as an add-on, enabling it to accurately simulate hydration kinetics for …

Optimal And Robust Control Problems Of Microalgae Cultivation, Mariana Rodriguez-Jara, Luis A. Ricardez-Sandoval, Carlos E. Ramirez-Castelan, Hector Puebla

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Research Outreach Interdisciplinary Activity To Classify Olive Oil Blends Integrating Multicolor Imaging, Image Processing, And Machine Learning, Allan Abraham, Kameshwaran Balachandran

Undergraduate Research

This outreach undergraduate research project presents a low-cost method to distinguish the quality of different olive oils. The proposed method is based on an indirect measurement of the chlorophyll molecules present when a green laser diode illuminates the oil sample. Oil blends can be classified into five classes (no olive oil, light olive oil, medium olive oil, olive oil, and extra virgin olive oil) by quantifying the ratio of the red channel versus the green channel along the laser illumination path from a color image. After labeling each oil blend, a convolutional neural network has been implemented and trained to …

Charge-Dependence Of Dissolution/Deposition Energy Barrier On Cu(111) Electrode Surface By Multiscale Simulations, Hang Qiao, Yong Zhu, Sheng Sun, Tong-Yi Zhang

Journal of Electrochemistry

Behaviors of electrified interface under different applied potentials/charges play the central role in electroplating process and electrochemical corrosion. The mechanism, however, is unclear yet for a surface atom dissolving/depositing from/on an electrode surface under an applied potential. The energy barrier along the reaction path is the key variable. The present work conductes hybrid first-principle/hybrid calculations to study the direct and indirect dissolution/deposition of a Cu atom on perfect/stepped Cu(111) planar electrodes in an electrolyte under different excess charges. Energy profiles present a linear relationship between the energies of the initial/final state and the activation state of different reaction paths under …

Research Progress And Performance Improvement Strategies Of Hard Carbon Anode Materials For Sodium-Ion Batteries, Xiu-Ping Yin, Yu-Feng Zhao, Jiu-Jun Zhang

Journal of Electrochemistry

This paper systematically summarizes the research progress of hard carbon anode materials in sodium ion batteries(SIBs) and the development of the corresponding sodium storage mechanism in recent years, and reviews the performance improvement strategies of hard carbon materials from the aspects of structural design and electrolyte regulation. The effects of the selection of precursors, carbonization temperature, pretreatment, pore formers, heteroatom doping, material compounding, electrolyte regulation and pre-sodiumization on the sodium storage performance of hard carbon anode materials are briefly described. This paper provides new insights into the design, synthesis and electrolyte
matching of high-performance and low-cost hard carbon materials, and …

Surface Modifications Of Lini0.96Co0.02Mn0.02O2 With Tungsten Oxide And Phosphotungstic Acid, Gang Zhao, Zheng-Liang Gong, Yi-Xiao Li, Yong Yang

Journal of Electrochemistry

With the rapid development of electric vehicles, enormous demands are made for higher energy density, better cycling performance and lower cost of lithium-ion batteries (LIBs). As an important high capacity cathode material for LIBs, the high nickel layered oxide material LiNi_0.8Co_0.1Mn_0.1O₂(NCM811) can reach an energy density of 760 Wh·kg^–1. The ultra-high nickel ternary positive electrode material (LiNi_1-x-yCo_xMn_yO₂, x ≥ 0.90) has a specific capacity of more than 210 mAh·g^–1, and can realize higher energy density. Besides, an ultra-high nickel material …

Preparation And Electrocatalytic Performance Of Feni-Cop/Nc Bifunctional Catalyst, Si-Miao Liu, Jing-Jiao Zhou, Shi-Jun Ji, Zhong-Sheng Wen

Journal of Electrochemistry

Rechargeable zinc-air batteries have gradually attracted much attention worldwide due to their high capacity, high energy density and low price. Oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) correspond to the charging and discharging processes in rechargeable zinc-air battery, respectively. At present, commercial Pt/C and IrO₂ catalysts hinder the large-scale application of zinc-air batteries due to low reserves, high prices and poor stability. Therefore, exploring high performance, low cost and high stability with dual functional catalysts is important for the development of rechargeable zinc-Air batteries. The metal-organic frameworks (MOFs) have high specific surface area, structural stability, good catalytic …

Generation Of Dna Oligomers With Similar Chemical Kinetics Via In-Silico Optimization, Michael Tobiason, Bernard Yurke, William L. Hughes

Electrical and Computer Engineering Faculty Publications and Presentations

Networks of interacting DNA oligomers are useful for applications such as biomarker detection, targeted drug delivery, information storage, and photonic information processing. However, differences in the chemical kinetics of hybridization reactions, referred to as kinetic dispersion, can be problematic for some applications. Here, it is found that limiting unnecessary stretches of Watson-Crick base pairing, referred to as unnecessary duplexes, can yield exceptionally low kinetic dispersions. Hybridization kinetics can be affected by unnecessary intra-oligomer duplexes containing only 2 base-pairs, and such duplexes explain up to 94% of previously reported kinetic dispersion. As a general design rule, it is recommended that unnecessary …

Fortifying Iot Against Crimpling Cyber-Attacks: A Systematic Review, Usman Tariq, Irfan Ahmed, Muhammad Attique Khan, Ali Kashif Bashir

Karbala International Journal of Modern Science

The rapid growth and increasing demand for Internet of Things (IoT) devices in our everyday lives create exciting opportunities for human involvement, data integration, and seamless automation. This fully interconnected ecosystem considerably impacts crucial aspects of our lives, such as transportation, healthcare, energy management, and urban infrastructure. However, alongside the immense benefits, the widespread adoption of IoT also brings a complex web of security threats that can influence society, policy, and infrastructure conditions. IoT devices are particularly vulnerable to security violations, and industrial routines face potentially damaging vulnerabilities. To ensure a trustworthy and robust security framework, it is crucial to …

Smart Service Function Chain System For Dynamic Traffic Steering Using Reinforcement Learning (Chrl), Ahmed Nadhum, Ahmed Al-Saadi

Karbala International Journal of Modern Science

The rapid development of the Internet and network services coupled with the growth of communication infrastructure necessitates the employment of intelligent systems. The complexity of the network is heightened by these systems, as they offer diverse services contingent on traffic type, user needs, and security considerations. In this context, a service function chain offers a toolkit to facilitate the management of intricate network systems. However, various traffic types require dynamic adaptation in the sets of function chains. The problem of optimizing the order of service functions in the chain must be solved using the proposed approach, along with balancing the …

Furthering Development Of Smart Fabrics To Improve The Accessibility Of Music Therapy, Ellie Nguyen, Daisy Z. Fernandez-Reyes, Franceli L. Cibrian

Engineering Faculty Articles and Research

In this paper, we present the design and development of HarmonicThreads, a smart, cost-effective fabric augmented by generative machine learning algorithms to create music in real time according to the user's interaction. In this manner, we hypothesize that individuals with sensory differences could take advantage of the fabric's flexibility, the music will adapt according to users' interaction, and the affordable hardware we propose will make it more accessible. We follow a design thinking methodology using data from a multidisciplinary team in Mexico and the United States. Then we will close this paper by discussing challenges in developing accessible smart fabrics …

Cccd: Corner Detection And Curve Reconstruction For Improved 3d Surface Reconstruction From 2d Medical Images, Mriganka Sarmah, Arambam Neelima

Turkish Journal of Electrical Engineering and Computer Sciences

The conventional approach to creating 3D surfaces from 2D medical images is the marching cube algorithm, but it often results in rough surfaces. On the other hand, B-spline curves and nonuniform rational B-splines (NURBSs) offer a smoother alternative for 3D surface reconstruction. However, NURBSs use control points (CTPs) to define the object shape and corners play an important role in defining the boundary shape as well. Thus, in order to fill the research gap in applying corner detection (CD) methods to generate the most favorable CTPs, in this paper corner points are identified to predict organ shape. However, CTPs must …

Hybrid Machine Learning Model To Predict Chronic Kidney Diseases Using Handcrafted Features For Early Health Rehabilitation, Amjad Rehman, Tanzila Saba, Haider Ali, Narmine Elhakim, Noor Ayesha

Turkish Journal of Electrical Engineering and Computer Sciences

Chronic kidney diseases proliferate due to hypertension, diabetes, anemia, obesity, smoking etc. Patients with such conditions are sometimes unaware of first symptoms, complicating disease diagnosis. This paper presents chronic kidney disease (CKD) prediction model to classify CKD patients from NCKD (Non-CKD). The proposed study has two main stages. First, we found the odds ratio through logistic regression and comparison test to identify early risk factors from kidneys? MRI and differentiate CKD from NCKD subjects. In stage 2, LR, LDA, MLP classifiers were applied to predict CKD and NCKD by extracting features from MRI. The odds ratio of blood glucose random …

Multi-View Brain Tumor Segmentation (Mvbts): An Ensemble Of Planar And Triplanar Attention Unets, Snehal Rajput, Rupal Kapdi, Mehul Raval, Mohendra Roy

Turkish Journal of Electrical Engineering and Computer Sciences

3D UNet has achieved high brain tumor segmentation performance but requires high computation, large memory, abundant training data, and has limited interpretability. As an alternative, the paper explores using 2D triplanar (2.5D) processing, which allows images to be examined individually along axial, sagittal, and coronal planes or together. The individual plane captures spatial relationships, and combined planes capture contextual (depth) information. The paper proposes and analyzes an ensemble of uniplanar and triplanar UNets combined with channel and spatial attention for brain tumor segmentation. It investigates the significance of each plane and analyzes the impact of uniplanar and triplanar ensembles with …