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Articles 2911 - 2940 of 36785

Full-Text Articles in Engineering

Dyvir: Virtual Reality Generated Synthetic Training Datasets For Ai, Garrett Williams Mar 2024

Dyvir: Virtual Reality Generated Synthetic Training Datasets For Ai, Garrett Williams

Graduate Student and Postdoctoral Fellow Symposium

Artificial Intelligence (AI) can perform complex tasks quickly such as object detection. To perform these tasks, the AI algorithms are first trained on data. However, some data such as labeled imagery of aerial objects is hard to obtain. Utilizing Virtual Reality (VR) software, a custom tool called DyViR was made to generate synthetic training datasets. Users customize the virtual environment, aerial objects, and sensor modality to produce custom-tailored datasets.

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Cr-Sam: Curvature Regularized Sharpness-Aware Minimization, Tao Wu, Tony Tie Luo, Donald C. Wunsch Mar 2024

Cr-Sam: Curvature Regularized Sharpness-Aware Minimization, Tao Wu, Tony Tie Luo, Donald C. Wunsch

Computer Science Faculty Research & Creative Works

The Capacity to Generalize to Future Unseen Data Stands as One of the Utmost Crucial Attributes of Deep Neural Networks. Sharpness-Aware Minimization (SAM) Aims to Enhance the Generalizability by Minimizing Worst-Case Loss using One-Step Gradient Ascent as an Approximation. However, as Training Progresses, the Non-Linearity of the Loss Landscape Increases, Rendering One-Step Gradient Ascent Less Effective. on the Other Hand, Multi-Step Gradient Ascent Will Incur Higher Training Cost. in This Paper, We Introduce a Normalized Hessian Trace to Accurately Measure the Curvature of Loss Landscape on Both Training and Test Sets. in Particular, to Counter Excessive Non-Linearity of Loss Landscape, …

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Lrs: Enhancing Adversarial Transferability Through Lipschitz Regularized Surrogate, Tao Wu, Tony Tie Luo, Donald C. Wunsch Mar 2024

Lrs: Enhancing Adversarial Transferability Through Lipschitz Regularized Surrogate, Tao Wu, Tony Tie Luo, Donald C. Wunsch

Computer Science Faculty Research & Creative Works

The Transferability of Adversarial Examples is of Central Importance to Transfer-Based Black-Box Adversarial Attacks. Previous Works for Generating Transferable Adversarial Examples Focus on Attacking Given Pretrained Surrogate Models While the Connections between Surrogate Models and Adversarial Trasferability Have Been overlooked. in This Paper, We Propose Lipschitz Regularized Surrogate (LRS) for Transfer-Based Black-Box Attacks, a Novel Approach that Transforms Surrogate Models towards Favorable Adversarial Transferability. using Such Transformed Surrogate Models, Any Existing Transfer-Based Black-Box Attack Can Run Without Any Change, Yet Achieving Much Better Performance. Specifically, We Impose Lipschitz Regularization on the Loss Landscape of Surrogate Models to Enable a Smoother …

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Exploring The Morphological Surface Resistance And Optical Absorption Of Thin Black Carbon Nanotube Films For Electronic And Optoelectronic Devices, Ziad Khalifa, Sameh Osama Abdellatif Mar 2024

Exploring The Morphological Surface Resistance And Optical Absorption Of Thin Black Carbon Nanotube Films For Electronic And Optoelectronic Devices, Ziad Khalifa, Sameh Osama Abdellatif

Chemical Engineering

This study investigates the optical and electrical properties of thin black films of carbon nanotubes (CNTs) fabricated under various conditions to explore their potential integration as either a perfect broadband absorber or enhanced counter electrode. The study involves SEM measurements, surface resistance measurements, and UV–Vis. spectrometer analysis. The results show that the CNT thin films exhibit high electrical conductivity and strong light absorption across various wavelengths. Optically, we investigated the impact of varying the growth temperature and catalyst temperature on the absorption profile of the thin films. The fabricated and deposited CNTs showed broadband absorption spectra, reaching 92.8% of the …

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A Reliable Optimal Electric Vehicle Charging Stations Allocation, Mohamed Abdelaziz, A.A. Ali, R.A. Swief, Rasha Elazab Mar 2024

A Reliable Optimal Electric Vehicle Charging Stations Allocation, Mohamed Abdelaziz, A.A. Ali, R.A. Swief, Rasha Elazab

Renewable Electrical Energy Engineering

This paper presents a new and effective approach for optimally allocating Electric Vehicle (EV) stations in a distribution network by integrating electrical and road constraints. The proposed methodology, a two-stage optimization technology, addresses the challenges posed by the increasing energy demand caused by the adoption of EVs. In the first stage, the stochastic demand load of EVs is simulated considering the probability and hierarchic clustering of EV load based on the travelling distance of users. This stage focuses on emulating the uncertainty of EV user travel patterns, time of arrival and departure, and their impact on the EV load profile. …

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Development Demand, Power Energy Consumption And Green And Low-Carbon Transition For Computing Power In China, Xiaohong Chen, Liaoying Cao, Jiaolong Chen, Jinghui Zhang, Wenzhi Cao, Yangjie Wang Mar 2024

Development Demand, Power Energy Consumption And Green And Low-Carbon Transition For Computing Power In China, Xiaohong Chen, Liaoying Cao, Jiaolong Chen, Jinghui Zhang, Wenzhi Cao, Yangjie Wang

Bulletin of Chinese Academy of Sciences (Chinese Version)

As a critical digital infrastructure, computing power has become the core productivity and a new engine driving economic growth in the digital economy. Nevertheless, the power-hungry nature of computing/data centers, representing the computing infrastructure, consumes a significant amount of electrical energy. Currently, China’s economy is transitioning from high-speed growth to high-quality development. It is imperative to study how to coordinate the development of computing power while ensuring its safety and achieving green and low-carbon goals. Based on an overview of the current status of computing power development, this study predicts the future demand for computing power in China, analyzes the …

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Maximizing Ev Profit And Grid Stability Through Virtual Power Plant Considering V2g, A. Selim Türkoğlu, H. Cihan Güldorum, Ibrahim Sengor Mar 2024

Maximizing Ev Profit And Grid Stability Through Virtual Power Plant Considering V2g, A. Selim Türkoğlu, H. Cihan Güldorum, Ibrahim Sengor

Electrical & Electronic Engineering

The electrification of transportation through the widespread adoption of electric vehicles (EVs) has raised substantial concerns within the realm of power grid operations. This concern predominantly stems from the elevated electricity demand brought about by the surging population of EVs, consequently exerting strain on the power grid infrastructure which can be reduced with vehicle-to-grid (V2G) technology integration. To address this issue, this paper delves further into the realm of grid integration by introducing a Virtual Power Plant (VPP) concept to enhance the synergy between EVs and power grid. This study aims to compare different realistic objectives, ranging from total active …

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On The Use Of Machine Learning And Data-Transformation Methods To Predict Hydration Kinetics And Strength Of Alkali-Activated Mine Tailings-Based Binders, Sahil Surehali, Taihao Han, Jie Huang, Aditya Kumar, Narayanan Neithalath Mar 2024

On The Use Of Machine Learning And Data-Transformation Methods To Predict Hydration Kinetics And Strength Of Alkali-Activated Mine Tailings-Based Binders, Sahil Surehali, Taihao Han, Jie Huang, Aditya Kumar, Narayanan Neithalath

Electrical and Computer Engineering Faculty Research & Creative Works

The escalating production of mine tailings (MT), a byproduct of the mining industry, constitutes significant environmental and health hazards, thereby requiring a cost-effective and sustainable solution for its disposal or reuse. This study proposes the use of MT as the primary ingredient (≥70%mass) in binders for construction applications, thereby ensuring their efficient upcycling as well as drastic reduction of environmental impacts associated with the use of ordinary Portland cement (OPC). The early-age hydration kinetics and compressive strength of MT-based binders are evaluated with an emphasis on elucidating the influence of alkali activation parameters and the amount of slag or cement …

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Intelligent Protection Scheme Using Combined Stockwell-Transform And Deep Learning-Based Fault Diagnosis For The Active Distribution System, Latha Maheswari Kandasamy, Kanakaraj Jaganathan Mar 2024

Intelligent Protection Scheme Using Combined Stockwell-Transform And Deep Learning-Based Fault Diagnosis For The Active Distribution System, Latha Maheswari Kandasamy, Kanakaraj Jaganathan

Turkish Journal of Electrical Engineering and Computer Sciences

This study aims to perform fast fault diagnosis and intelligent protection in an active distribution network (ADN) with high renewable energy penetration. Several time-domain simulations are carried out in EMTP-RV to extract time-synchronized current and voltage data. The Stockwell transform (ST) was used in MATLAB/SIMULINK to preprocess these input datasets to train the adaptive fault diagnosis deep convolutional neural network (AFDDCNN) for fault location identification, fault type identification, and fault phase-detection for different penetration levels. Based on the AFDDCNN output, the intelligent protection scheme (IDOCPS) generates the signal for isolating a faulty section of the ADN. An intelligent fault diagnosis …

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Advanced Hyperthermia Treatment: Optimizing Microwave Energy Focus For Breast Cancer Therapy, Burak Acar, Tuba Yilmaz Abdolsaheb, Ali Yapar Mar 2024

Advanced Hyperthermia Treatment: Optimizing Microwave Energy Focus For Breast Cancer Therapy, Burak Acar, Tuba Yilmaz Abdolsaheb, Ali Yapar

Turkish Journal of Electrical Engineering and Computer Sciences

This paper presents a fast antenna phase optimization scheme to enable microwave power focusing for breast cancer hyperthermia. The power focusing is achieved through the maximization of the deposited electric field on the target malignant tumor tissue. To do so, a malignant breast tumor, the surrounding breast medium, and the skin of the breast are modeled as a cylindrical structure composed of eccentric cylinders, and electric field distribution is computed analytically in terms of cylindrical harmonics. This approach minimized the computational cost and simplified the breast medium model. To ensure applicability across various breast types, the dielectric properties (DPs) of …

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Atomic Comagnetometer Gyroscopes For Inertial Navigation Systems: A Review, Murat Salim Karabinaoglu, Bekir Çakir, Mustafa Engin Başoğlu Mar 2024

Atomic Comagnetometer Gyroscopes For Inertial Navigation Systems: A Review, Murat Salim Karabinaoglu, Bekir Çakir, Mustafa Engin Başoğlu

Turkish Journal of Electrical Engineering and Computer Sciences

In recent years, developments in quantum sensing, laser, and atomic sensor technologies have also enabled advancement in the field of quantum navigation. Atomic-based gyroscopes have emerged as one of the most critical atomic sensors in this respect. In this review, a brief technology statement of spin exchange relaxation free (SERF) and nuclear magnetic resonance (NMR) type atomic comagnetometer gyroscope (CG) is presented. Related studies in the literature have been gathered, and the fundamental compositions of CGs with technical basics are presented. A comparison of SERF and NMR CGs is provided. A basic simulation of SERF CG was carried out because …

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Uncovering And Mitigating Spurious Features In Domain Generalization, Saeed Karimi, Hamdi̇ Di̇bekli̇oğlu Mar 2024

Uncovering And Mitigating Spurious Features In Domain Generalization, Saeed Karimi, Hamdi̇ Di̇bekli̇oğlu

Turkish Journal of Electrical Engineering and Computer Sciences

Domain generalization (DG) techniques strive to attain the ability to generalize to an unfamiliar target domain solely based on training data originating from the source domains. Despite the increasing attention given to learning from multiple training domains through the application of various forms of invariance across those domains, the enhancements observed in comparison to ERM are nearly insignificant under specified evaluation rules. In this paper, we demonstrate that the disentanglement of spurious and invariant features is a challenging task in conventional training since ERM simply minimizes the loss and does not exploit invariance among domains. To address this issue, we …

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Lower Data Attacks On Advanced Encryption Standard, Orhun Kara Mar 2024

Lower Data Attacks On Advanced Encryption Standard, Orhun Kara

Turkish Journal of Electrical Engineering and Computer Sciences

The Advanced Encryption Standard (AES) is one of the most commonly used and analyzed encryption algorithms. In this work, we present new combinations of some prominent attacks on AES, achieving new records in data requirements among attacks, utilizing only 2 4 and 2 16 chosen plaintexts (CP) for 6-round and 7-round AES 192/256, respectively. One of our attacks is a combination of a meet-in-the-middle (MiTM) attack with a square attack mounted on 6-round AES-192/256 while another attack combines an MiTM attack and an integral attack, utilizing key space partitioning technique, on 7-round AES-192/256. Moreover, we illustrate that impossible differential (ID) …

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Effects Of Unobservable Bus States On Detection And Localization Of False Data Injection Attacks In Smart Grids, Moheb Abdelmalak Mar 2024

Effects Of Unobservable Bus States On Detection And Localization Of False Data Injection Attacks In Smart Grids, Moheb Abdelmalak

USF Tampa Graduate Theses and Dissertations

In an era increasingly marked by sophisticated cyber-attacks, this thesis investigates the critical issue of bus unobservability in smart grids and its impact on the effectiveness of cyber-attack detection and localization models. Given that unobservability is a prevalent challenge in smart grids due to various factors, researchers have developed numerous algorithms for optimal Phasor Measurement Unit (PMU) placement under scenarios of limited observability. However, these models primarily focus on enhancing network observability, often without considering whether this placement optimally facilitates attack detection. This research is driven by the hypothesis that a deeper understanding of the effects of unobservable buses can …

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Consensus-Based Virtual Leader Tracking Algorithm For Flight Formation Control Of Swarm Uavs, Berat Yıldız, Akif Durdu, Ahmet Kayabaşi Mar 2024

Consensus-Based Virtual Leader Tracking Algorithm For Flight Formation Control Of Swarm Uavs, Berat Yıldız, Akif Durdu, Ahmet Kayabaşi

Turkish Journal of Electrical Engineering and Computer Sciences

Technological developments in industrial areas also impact unmanned aerial vehicles (UAVs). Recent improvements in both software and hardware have significantly increased the use of many UAVs in social and military fields. In particular, the widespread use of these vehicles in social areas such as entertainment, shipping, transportation, and delivery and military areas such as surveillance, tracking, and offensive measures has accelerated the research on swarm systems. This study examined the previous investigations on swarm UAVs and aimed to create a more efficient algorithm. The effectiveness of the proposed algorithm was compared with other leader-based applications. A swarm consisting of 5 …

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Cascade Controller Design Via Controller Synthesis For Load Frequency Control Of Electrical Power Systems, Yavuz Güler, Mustafa Nalbantoğlu, Ibrahim Kaya Mar 2024

Cascade Controller Design Via Controller Synthesis For Load Frequency Control Of Electrical Power Systems, Yavuz Güler, Mustafa Nalbantoğlu, Ibrahim Kaya

Turkish Journal of Electrical Engineering and Computer Sciences

The regulation of tie-line electricity flow and frequency of electrical power systems (EPS) is crucial for ensuring their robustness to parameter changes and efficient management of disturbances. To this end, a novel cascade control design approach utilizing a serial Proportional-Integral-Derivative controller with a filter (PIDF) is proposed in this paper. The parameters of the controllers are derived analytically, and it is employed in both loops of the cascade control system to regulate the Load Frequency Control (LFC) of EPS. The implementation of PIDF controllers in both loops is utilized in the cascade control scheme for various power systems featuring different …

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Resolving The Nanoscale Structure Of Β-Sheet Peptide Self-Assemblies Using Single-Molecule Orientation–Localization Microscopy, Weiyan Zhou, Conor L. O'Neill, Tianben Ding, Oumeng Zhang, Jai S. Rudra, Matthew D. Lew Mar 2024

Resolving The Nanoscale Structure Of Β-Sheet Peptide Self-Assemblies Using Single-Molecule Orientation–Localization Microscopy, Weiyan Zhou, Conor L. O'Neill, Tianben Ding, Oumeng Zhang, Jai S. Rudra, Matthew D. Lew

Electrical & Systems Engineering Publications and Presentations

Synthetic peptides that self-assemble into cross-β fibrils are versatile building blocks for engineered biomaterials due to their modularity and biocompatibility, but their structural and morphological similarities to amyloid species have been a long-standing concern for their translation. Further, their polymorphs are difficult to characterize using spectroscopic and imaging techniques that rely on ensemble averaging to achieve high resolution. Here, we utilize Nile red (NR), an amyloidophilic fluorogenic probe, and single-molecule orientation-localization microscopy (SMOLM) to characterize fibrils formed by the designed amphipathic enantiomers KFE8L and KFE8D and the pathological amyloid-beta peptide Aβ42. Importantly, NR SMOLM reveals the helical (bilayer) …

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Miniature Optical Fiber Fabry-Perot Interferometer Based On A Single-Crystal Metal-Organic Framework For The Detection And Quantification Of Benzene And Ethanol At Low Concentrations In Nitrogen Gas, Farhan Mumtaz, Bohong Zhang, Narasimman Subramaniyam, Mohammad Roman, Peter Holtmann, Abhishek Prakash Hungund, Ryan O'Malley, Thomas M. Spudich, Michael Davis, Rex E. Gerald, Jie Huang Mar 2024

Miniature Optical Fiber Fabry-Perot Interferometer Based On A Single-Crystal Metal-Organic Framework For The Detection And Quantification Of Benzene And Ethanol At Low Concentrations In Nitrogen Gas, Farhan Mumtaz, Bohong Zhang, Narasimman Subramaniyam, Mohammad Roman, Peter Holtmann, Abhishek Prakash Hungund, Ryan O'Malley, Thomas M. Spudich, Michael Davis, Rex E. Gerald, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

This study reports for the first time, to the best of our knowledge, a real-time detection of ultralow-concentration chemical gases using fiber-optic technology, combining a miniaturized Fabry-Perot interferometer (FPI) with metal-organic frameworks (MOFs). The sensor consists of a short and thick-walled silica capillary segment spliced to a lead-in single-mode fiber (SMF), housing a tiny single crystal of HKUST-1 MOF, imparting chemo selectivity features. Ethanol and benzene gases were tested, resulting in a shift in the FPI interference signal. The sensor demonstrated high sensitivity, detecting ethanol gas concentrations (EGCs) with a sensitivity of 0.428 nm/ppm between 24.9 and 40.11 ppm and …

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Spatiotemporal Reaction Dynamics Control In Two-Photon Polymerization For Enhancing Writing Characteristics, Aofei Mao, Sarah Fess, Nada Kraiem, P. Li, Zhipeng P. Wu, Qiuchi Zhu, Xi Huang, Peixun Fan, Bai Cui, Jean-Francois Silvain, Suxing Hu, Mitchell Anthamatten, Sean P. Regan, David Harding, Yongfeng Lu Mar 2024

Spatiotemporal Reaction Dynamics Control In Two-Photon Polymerization For Enhancing Writing Characteristics, Aofei Mao, Sarah Fess, Nada Kraiem, P. Li, Zhipeng P. Wu, Qiuchi Zhu, Xi Huang, Peixun Fan, Bai Cui, Jean-Francois Silvain, Suxing Hu, Mitchell Anthamatten, Sean P. Regan, David Harding, Yongfeng Lu

Department of Electrical and Computer Engineering: Faculty Publications

Since 2001, 3D microfabrication based on two-photon polymerization (TPP) has drawn extensive attention and interest in biology, optics, photonics, material science, and high-energy physics. The in-volume fabrication capability due to the threshold behavior of two-photon absorption enables TPP higher flexibility compared with other nanofabrication techniques. However, as determined by the in-volume fabrication feature as well as various reaction dynamics, the writing characteristics of TPP, such as throughput, accuracy, surface quality, and fabrication capability, are still limited. Herein, a comprehensive study is performed on the spatiotemporal behavior of reaction dynamics during TPP fabrication, mainly focusing on spatiotemporal characteristics of radical diffusion, …

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Development Of A Plant Growth And Health Monitoring System Using Imaging And Sensor Array Information For Cubesat Applications, Kat-Kim Phan Mar 2024

Development Of A Plant Growth And Health Monitoring System Using Imaging And Sensor Array Information For Cubesat Applications, Kat-Kim Phan

USF Tampa Graduate Theses and Dissertations

Space exploration has been a topic of interest in the scientific community, such as the planned missions to Mars. To accomplish this would require being able to provide astronauts with a steady supply of food beyond freeze-dried foods leading to the need to grow food in space. Although this is a topic still being investigated, the CubeSat platform opens the possibility of carrying out studies on plant growth under more strenuous space conditions unlike that in the International Space Station (ISS). Developing a plant-focused mission for a CubeSat, though, entails being able to develop a system to sustain plant life …

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Comparison Of Conventional And Adaptive Acoustic Beamforming Algorithms Using A Tetrahedral Microphone Array In Noisy Environments, Megan Brittany Ewers Mar 2024

Comparison Of Conventional And Adaptive Acoustic Beamforming Algorithms Using A Tetrahedral Microphone Array In Noisy Environments, Megan Brittany Ewers

Dissertations and Theses

In situ acoustic measurements are often plagued by interfering sound sources that occur within the measurement environment. Both adaptive and conventional beamforming algorithms, when applied to the outputs of a microphone array arranged in a tetrahedral geometry, are able to capture sound sources in desired directions and reject sound from unwanted directions. Adaptive algorithms may be able to measure a desired sound source with greater spatial precision, but require more calculations and, therefore, computational power. A conventional frequency-domain phase-shift algorithm and a modified adaptive frequency-domain Minimum Variance Distortionless Response (MVDR) algorithm were applied to simulated and recorded signals from a …

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6d Single-Fluorogen Orientation-Localization Microscopy For Elucidating The Architecture Of Beta-Sheet Assemblies And Biomolecular Condensates, Tingting Wu, Weiyan Zhou, Jai S. Rudra, Rohit V. Pappu, Matthew D. Lew Mar 2024

6d Single-Fluorogen Orientation-Localization Microscopy For Elucidating The Architecture Of Beta-Sheet Assemblies And Biomolecular Condensates, Tingting Wu, Weiyan Zhou, Jai S. Rudra, Rohit V. Pappu, Matthew D. Lew

Electrical & Systems Engineering Publications and Presentations

We develop six-dimensional single-molecule orientation-localization microscopy (SMOLM) to measure the 3D positions and 3D orientations simultaneously of single fluorophores. We show how careful optimization of phase and polarization modulation components can encode phase, polarization, and angular spectrum information from each fluorescence photon into a microscope’s dipole-spread function. We used the transient binding and blinking of Nile red (NR) to characterize the helical structure of fibrils formed by designed amphipathic peptides, KFE8L and KFE8D, and the pathological amyloid-beta peptide Aβ42. We also deployed merocyanine 540 to uncover the interfacial architectures of biomolecular condensates.

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Comparing Task Graph Scheduling Algorithms: An Adversarial Approach, Jared Coleman, Bhaskar Krishnamachari Mar 2024

Comparing Task Graph Scheduling Algorithms: An Adversarial Approach, Jared Coleman, Bhaskar Krishnamachari

Computer Science Faculty Works

Scheduling a task graph representing an application over a heterogeneous network of computers is a fundamental problem in distributed computing. It is known to be not only NP-hard but also not polynomial-time approximable within a constant factor. As a result, many heuristic algorithms have been proposed over the past few decades. Yet it remains largely unclear how these algorithms compare to each other in terms of the quality of schedules they produce. We identify gaps in the traditional benchmarking approach to comparing task scheduling algorithms and propose a simulated annealing-based adversarial analysis approach called PISA to help address them. We …

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A Deep Learning Convolutional Neural Network For Antenna Near-Field Prediction And Surrogate Modeling, Md Rayhan Khan, Constantinos L. Zekios, Shubhendu Bhardwaj, Stavros V. Georgakopoulos Mar 2024

A Deep Learning Convolutional Neural Network For Antenna Near-Field Prediction And Surrogate Modeling, Md Rayhan Khan, Constantinos L. Zekios, Shubhendu Bhardwaj, Stavros V. Georgakopoulos

Department of Electrical and Computer Engineering: Faculty Publications

This study investigates the use of deep learning techniques for building a generalized surrogate model that can accurately and very efficiently predict antenna performance parameters. Notably, we focus on applications where a substantial amount of simulation time is required and prior data is available for deep learning use. Specifically, for these applications, we introduce deep learning models that efficiently and reliably model the near-field of the antenna. These models, in turn, accurately predict far-field properties and essential antenna metrics, such as the reflection coefficient. To demonstrate the efficiency of our method, the widely used rectangular patch antenna is considered, encompassing …

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Hybrid Deloading Control Strategy In Mmc-Based Wind Energy Conversion Systems For Enhanced Frequency Regulation, Jimiao Zhang, Jie Li Mar 2024

Hybrid Deloading Control Strategy In Mmc-Based Wind Energy Conversion Systems For Enhanced Frequency Regulation, Jimiao Zhang, Jie Li

Henry M. Rowan College of Engineering Departmental Research

The growing integration of renewable energy sources, especially offshore wind (OSW), is introducing frequency stability challenges to electric power grids. This paper presents a novel hybrid deloading control strategy that enables modular multilevel converter (MMC)-based wind energy conversion systems (WECSs) to actively contribute to grid frequency regulation. This research investigates a permanent-magnet synchronous generator (PMSG)-based direct-drive configuration, sourced from the International Energy Agency’s (IEA’s) 15 MW reference turbine model. Specifically, phase-locked loop (PLL)-free grid-forming (GFM) control is employed via the grid-side converter (GSC), and DC-link voltage control is realized through the machine-side converter (MSC), both of which boost the energy …

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Quantum-Powered Battery Scheduling In Modern Distribution Grids, Diba Ehsani Mar 2024

Quantum-Powered Battery Scheduling In Modern Distribution Grids, Diba Ehsani

Electronic Theses and Dissertations

The rising need for exploiting a novel and evolved computation is an increasing concern in the power distribution system to address the exponential growth of distribution-connected devices. Scheduling numerous battery energy storage systems in an optimal way is one of the emerging challenges that will be more noticeable as the number of batteries, including residential, community, and vehicle batteries, increases in the grid. This thesis focuses on this topic and offers a necessary component in building the quantum-compatible distribution system of the future. Using a constrained quadratic model (CQM) on D-Wave’s hybrid solver as well as a binary quadratic model …

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Data-Driven Approaches For Enhancing Power Grid Reliability, Behrouz Sohrabi Mar 2024

Data-Driven Approaches For Enhancing Power Grid Reliability, Behrouz Sohrabi

Electronic Theses and Dissertations

This thesis explores the transformative potential of data-driven approaches in addressing key operational and reliability issues in power systems. The first part of this thesis addresses a prevalent problem in power distribution networks: the accurate identification of load phases. This study develops a data-driven model leveraging consumption measurements from smart meters and corresponding substation data to reconstruct topology information in low-voltage distribution networks. The proposed model is extensively tested using a dataset with more than 5,000 real load profiles, demonstrating satisfactory performance for large-scale networks. The second part of the thesis pivots to a crucial safety concern: the risk and …

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Investigating Customer Churn In Banking: A Machine Learning Approach And Visualization App For Data Science And Management, Pahul Preet Singh, Fahim Islam Anik, Rahul Senapati, Arnav Sinha, Nazmus Sakib, Eklas Hossain Mar 2024

Investigating Customer Churn In Banking: A Machine Learning Approach And Visualization App For Data Science And Management, Pahul Preet Singh, Fahim Islam Anik, Rahul Senapati, Arnav Sinha, Nazmus Sakib, Eklas Hossain

Electrical and Computer Engineering Faculty Publications and Presentations

Customer attrition in the banking industry occurs when consumers quit using the goods and services offered by the bank for some time and, after that, end their connection with the bank. Therefore, customer retention is essential in today’s extremely competitive banking market. Additionally, having a solid customer base helps attract new consumers by fostering confidence and a referral from a current clientele. These factors make reducing client attrition a crucial step that banks must pursue. In our research, we aim to examine bank data and forecast which users will most likely discontinue using the bank’s services and become paying customers. …

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The Impact Of N-Doped Carbon Quantum Dots On Dye-Sensitized Solar Cells Operating Under Diffused- And Low-Light Intensity, Mona Samir, Ahmed Agour, Zahraa Ismail, Hassan Nageh, Sameh O. Abdellatif Mar 2024

The Impact Of N-Doped Carbon Quantum Dots On Dye-Sensitized Solar Cells Operating Under Diffused- And Low-Light Intensity, Mona Samir, Ahmed Agour, Zahraa Ismail, Hassan Nageh, Sameh O. Abdellatif

Electrical Engineering

This study investigates the double role of N-doped carbon quantum dots (N-CQDs) in dye-sensitized solar cells (DSSCs) that operate under diffused- and low-light intensity conditions. We demonstrate that the incorporation of N-CQDs leads to a substantial improvement in the performance of DSSCs. Under standard one-sun illumination, the maximum power conversion efficiency (PCE) achieved with N-CQDs is 2% higher than that of the bare cell. Moreover, we introduce two new metrics, the diffused-light coefficient and the low-light intensity coefficient, to evaluate the performance of DSSCs under nonideal illumination conditions. The diffused-light coefficient is recorded at 1.55, which indicates a notable enhancement …

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Chatreview: A Chatgpt-Enabled Natural Language Processing Framework To Study Domain-Specific User Reviews, Brittany Ho, Ta'rhonda Mayberry, Khanh Linh Nguyen, Manohar Dhulipala, Vivek Krishnamani Pallipuram Mar 2024

Chatreview: A Chatgpt-Enabled Natural Language Processing Framework To Study Domain-Specific User Reviews, Brittany Ho, Ta'rhonda Mayberry, Khanh Linh Nguyen, Manohar Dhulipala, Vivek Krishnamani Pallipuram

All Faculty Articles - School of Engineering and Computer Science

We present ChatReview, a ChatGPT-enabled natural language processing framework that effectively studies domain-specific user reviews to offer relevant and personalized search results at multiple levels of granularity. The framework accomplishes this task using four phases including data collection, tokenization, query construction, and response generation. The data collection phase involves gathering domain-specific user reviews from public and private repositories. In the tokenization phase, ChatReview applies sentiment analysis to extract keywords and categorize them into various sentiment classes. This process creates a token repository that best describes the user sentiments for a given user-review data. In the query construction phase, the framework …

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