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 …

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 …

Conservative Estimation Of Inertial Sensor Errors Using Allan Variance Data, Kyle A. Lethander, Clark N. Taylor

Faculty Publications

To understand the error sources present in inertial sensors, both the white (time-invariant) and correlated noise sources must be properly characterized. To understand both sources, the standard approach (IEEE standards 647-2006, 952-2020) is to compute the Allan variance of the noise and then use human-based interpretation of linear trends to estimate the separate noise sources present in a sensor. Recent work has sought to overcome the graphical nature and visual-inspection basis of this approach leading to more accurate noise estimates. However, when using noise characterization in a filter, it is important that the noise estimates be not only accurate but …

Better Models For High-Stakes Tasks, Jacob Ryan Epifano

Theses and Dissertations

The intersection of machine learning and healthcare has the potential to transform medical diagnosis, treatment, and research. Machine learning models can analyze vast amounts of medical data and identify patterns that may be too complex for human analysis. However, one of the major challenges in this field is building trust between users and the model. Due to things like high false alarm rate and the black box nature of machine learning models, patients and medical professionals need to understand how the model arrives at its recommendations. In this work, we present several methods that aim to improve machine learning models …

Reducing Brain Kynurenic Acid Synthesis Precludes Kynurenine-Induced Sleep Disturbances, Katherine M. Rentschler, Snezana Milosavljevic, Annalisa M. Baratta, Courtney J. Wright, Maria V. Piroli, Zachary Tentor, Homayoun Valafar, Christian O'Reilly, Ana Pocivavsek

Publications

Patients with neurocognitive disorders often battle sleep disturbances. Kynurenic acid is a tryptophan metabolite of the kynurenine pathway implicated in the pathology of these illnesses. Modest increases in kynurenic acid, an antagonist at glutamatergic and cholinergic receptors, result in cognitive impairments and sleep dysfunction. We explored the hypothesis that inhibition of the kynurenic acid synthesising enzyme, kynurenine aminotransferase II, may alleviate sleep disturbances. At the start of the light phase, adult male and female Wistar rats received systemic injections of either: (i) vehicle; (ii) kynurenine (100 mg kg−1; i.p.); (iii) the kynurenine aminotransferase II inhibitor, PF-04859989 (30 mg kg−1; s.c.); …

System Strength Shortfall Challenges For Renewable Energy-Based Power Systems: A Review, Md O. Qays, Iftekhar Ahmad, Daryoush Habibi, Asma Aziz, Thair Mahmoud

Research outputs 2022 to 2026

Renewable energy sources such as wind farms and solar power plants are replacing conventional coal-based synchronous generators (SGs) to achieve net-zero carbon emissions worldwide. SGs play an important role in enhancing system strength in a power system to make it more stable during voltage/frequency disruptions. However, traditional coal-fired SGs are being decommissioned in many parts of the world, owing to stringent environmental regulations and low levelized cost of energy of renewables. Consequently, maintaining system strength in a renewable energy-dominated power system has become a major challenge, and without adequate mitigation techniques, low system strength can potentially cause widespread power outages. …

Pymaivar: An Open-Source Python Suit For Audio-Image Representation In Human Action Recognition, Muhammad B. Shaikh, Douglas Chai, Syed M. S. Islam, Naveed Akhtar

Research outputs 2022 to 2026

We present PyMAiVAR, a versatile toolbox that encompasses the generation of image representations for audio data including Wave plots, Spectral Centroids, Spectral Roll Offs, Mel Frequency Cepstral Coefficients (MFCC), MFCC Feature Scaling, and Chromagrams. This wide-ranging toolkit generates rich audio-image representations, playing a pivotal role in reshaping human action recognition. By fully exploiting audio data's latent potential, PyMAiVAR stands as a significant advancement in the field. The package is implemented in Python and can be used across different operating systems.

Multifunctional Organic Monolayer-Based Coatings For Implantable Biosensors And Bioelectronic Devices: Review And Perspectives, Taral Patel, Jie Huang, Katarzyna Krukiewicz

Electrical and Computer Engineering Faculty Research & Creative Works

The Emerging Field of Biosensors and Bioelectronics Seeks to Exploit Biology in Combination with the Recent Advances in Engineering. Even Though Biomedical Implants Can Significantly Improve Quality of Life, Problems Following the Process of Implantation Are Still an Issue. in This Review, We Point Out Organic Monolayer-Based Coatings as a Potential Solution to the Major Limitations of Implantable Biomaterials, Including Limited Biocompatibility, the Risk of Biofouling, Bacterial Colonization, and Stability under in Vivo Conditions. at First, Selected Current and Perspective Biomaterials Are Discussed, with the Focus on their Use as Implantable Biosensors and Biomedical Electrodes. Surface Modification Strategies for Implantable …

In Situ Monitoring Of The Hydration Of Calcium Silicate Minerals In Cement With A Remote Fiber-Optic Raman Probe, Bohong Zhang, Wenyu Liao, Hongyan Ma, Jie Huang

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

This study utilized a novel in situ fiber-optic Raman probe to continuously monitor the hydration progress of tricalcium silicate (C₃S) and dicalcium silicate (C₂S) without the need for sampling, from early hydration stage to later stages, and from fresh to hardened states of paste samples. By virtue of the remarkable ability of this technique in characterizing either dry or wet and crystalline or amorphous samples, the hydration processes of C₃S and C₂S pastes with different water-to-solid (w/s) ratios could be monitored from the start of the hydration reaction. The main hydration products, …

An Animated Introduction To Digital Logic Design, John D. Carpinelli

Open and Affordable Textbooks

This book is designed for use in an introductory course on digital logic design, typically offered in computer engineering, electrical engineering, computer science, and other related programs. Such a course is usually offered at the sophomore level. This book makes extensive use of animation to illustrate the flow of data within a digital system and to step through some of the procedures used to design and optimize digital circuits.

Synthesis And Evaluation Of Organic Additives For Copper Electroplating Of Interconnects, Yue-Hui Zhai, Yi-Xiao Peng, Yan Hong, Yuan-Ming Chen, Guo-Yun Zhou, Wei He, Peng-Ju Wang, Xian-Ming Chen, Chong Wang

Journal of Electrochemistry

Copper interconnects are essential to the functionality, performance, power efficiency, reliability, and fabrication yield of electronic devices. They are widely found in chips, packaging substrates and printed circuit boards, and are often produced by copper electroplating in an acidic aqueous solution. Organic additives play a decisive role in regulating copper deposition to fill microgrooves, and micro-vias to form fine lines and interlayer interconnects. Generally, an additive package consists of three components (brightener, suppressor, and leveler), which have a synergistic effect of super-filling on electroplating copper when the concentration ratio is appropriate. Many works of literature have discussed the mechanism of …

Effect Of Amine Additives On Thermal Runaway Inhibition Of Sic||Ncm811 Batteries, Bo-Wen Hou, Long He, Xu-Ning Feng, Wei-Feng Zhang, Li Wang, Xiang-Ming He

Journal of Electrochemistry

The high energy density of NCM batteries with high nickel content is a key advantage in replacing fossil fuels and promoting clean energy development, at the same time, is also a fundamental cause of serious safety hazards in batteries. Primary and secondary amines can lead to ring-opening polymerization of common ethylene carbonate electrolytes, resulting in an isolation layer between the cathode and the anode, and improving the thermal safety of the battery. In this work, the safety of batteries is considered both at the material level and at the cell level, based on the chemical reactions between amines and the …

Pulse Electroplating Of Nanotwinned Copper Using Mps-Peg Two-Additive System For Damascene Via Filling Process, Yu-Xi Wang, Li-Yin Gao, Yong-Qiang Wan, Zhe Li, Zhi-Quan Liu

Journal of Electrochemistry

High density nanotwinned copper films were pulse electroplated using an optimized electrolyte. In order to find out the influencing factors on the formation of nanotwins, series contents of MPS were added to the electrolyte during the pulse electroplating process. It was found that the copper films electroplated without MPS had large grains but a few nanotwins. And the grain size was about 0.9 μm on average, and the texture components of (110) and (111) crystal orientations were calculated as 49% and 27.8%, respectively. Differently, when 10 ppm MPS was added, the microstructure was changed to columnar grain with high density …

Effects Of Traps On Photo-Induced Interfacial Charge Transfer Of Ag-Tio2: Photoelectrochemical, Electrochemical And Spectroscopic Characterizations, Zhi-Hao Liang, Jia-Zheng Wang, Dan Wang, Jian-Zhang Zhou, De-Yin Wu

Journal of Electrochemistry

In the field of metal-semiconductor composites based plasmon-mediated chemical reactions, a clear and in-depth understanding of charge transfer and recombination mechanisms is crucial for improving plasmonic photocatalytic efficiency. However, the plasmonic photocatalytic reactions at the solid-liquid interface of the electrochemical systems involve complex processes with multiple elementary steps, multiple time scales, and multiple controlling factors. Herein, the combination of photoelectrochemical and electrochemical as well as spectroscopic characterizations has been successfully used to study the effects of traps on the photo-induced interfacial charge transfer of silver-titanium dioxide (Ag-TiO₂). The results show that the increase of surface hydroxyl groups may …

A Novel Method For Determining The Inherent Capabilities Of Computer And Robotic-Assisted Total Knee Arthroplasty Devices, Delaney R.G. Stevens

Electronic Thesis and Dissertation Repository

This thesis presents a method for evaluating and comparing assistive total knee arthroplasty (TKA) devices while controlling surgeon landmarking variability. To achieve consistent landmark selection by surgeons during TKA procedures, the method uses identical 3D-printed knees with indented landmarks. This method was used to compare a robotic and computer-assisted TKA device on three metrics: measurement accuracy, alignment accuracy, and cut-surface uniformity. Although both devices had considerable sagittal plane measurement errors, the robotic device had better measurement and alignment accuracy than the computer-assisted device. Furthermore, the robotic device's measuring error compensated for cutting errors, but the computer-assisted device's compounded them. However, …

Hierarchical Based Classifcation Method Based On Fusion Ofgaussian Map Descriptors Foralzheimer Diagnosis Using T1‑Weighted Magnetic Resonance Imaging, Nourhan Zayed, Shereen E. Morsy, Inas A. Yassine

Mechanical Engineering

Alzheimer’s disease (AD) is considered one of the most spouting elderly diseases. In 2015, AD is reported the US’s sixth cause of death. Substantially, non-invasive imaging is widely employed to provide biomarkers supporting AD screening, diagnosis, and progression. In this study, Gaussian descriptors-based features are proposed to be efcient new biomarkers using Magnetic Resonance Imaging (MRI) T1-weighted images to diferentiate between Alzheimer’s disease (AD), Mild Cognitive Impairment (MCI), and Normal controls (NC). Several Gaussian map-based features are extracted such as Gaussian shape operator, Gaussian curvature, and mean curvature. The aforementioned features are then introduced to the Support Vector Machine (SVM). …

Evaluating Eeg–Emg Fusion-Based Classification As A Method For Improving Control Of Wearable Robotic Devices For Upper-Limb Rehabilitation, Jacob G. Tryon

Electronic Thesis and Dissertation Repository

Musculoskeletal disorders are the biggest cause of disability worldwide, and wearable mechatronic rehabilitation devices have been proposed for treatment. However, before widespread adoption, improvements in user control and system adaptability are required. User intention should be detected intuitively, and user-induced changes in system dynamics should be unobtrusively identified and corrected. Development often focuses on model-dependent nonlinear control theory, which is challenging to implement for wearable devices.

One alternative is to incorporate bioelectrical signal-based machine learning into the system, allowing for simpler controller designs to be augmented by supplemental brain (electroencephalography/EEG) and muscle (electromyography/EMG) information. To extract user intention better, sensor …