Digital Commons Network^™

Experimental Validation Of An Analytical Transient Model For Saturated Boosting Gain In Dc–Dc Converters With Variable Duty Cycle, Goliana Samir, Simon Ezzat, Wagdy Anis, Sameh O. Abdellatif

Electrical Engineering

No abstract provided.

Low-Power Dc-Dc Converters For Smart And Environmentally-Friendly Electric Vehicles: Design, Simulation, And Fabrication On A Glass Substrate, Michelle Makar, Sameh O. Abdellatif

Electrical Engineering

No abstract provided.

From Cnns To Transformers In Multimodal Human Action Recognition: A Survey, Muhammad Bilal Shaikh, Douglas Chai, Syed Muhammad Shamsul Islam, Naveed Akhtar

Research outputs 2022 to 2026

Due to its widespread applications, human action recognition is one of the most widely studied research problems in Computer Vision. Recent studies have shown that addressing it using multimodal data leads to superior performance as compared to relying on a single data modality. During the adoption of deep learning for visual modelling in the past decade, action recognition approaches have mainly relied on Convolutional Neural Networks (CNNs). However, the recent rise of Transformers in visual modelling is now also causing a paradigm shift for the action recognition task. This survey captures this transition while focusing on Multimodal Human Action Recognition …

Fundamental Limits In Measuring The Anisotropic Rotational Diffusion Of Single Molecules, Weiyan Zhou, Tingting Wu, Matthew D. Lew

Electrical & Systems Engineering Publications and Presentations

Many biophysical techniques, such as single-molecule fluorescence correlation spectroscopy, Förster resonance energy transfer, and fluorescence anisotropy, measure the translation and rotation of biomolecules to quantify molecular processes at the nanoscale. These methods often simplify data analysis by assuming isotropic rotational diffusion, e.g., that molecules wobble within a circular cone. This simplification ignores the anisotropy present in many biological contexts that may cause molecules to exhibit different degrees of diffusion in different directions. Here, we loosen this assumption and establish a theoretical framework for describing and measuring anisotropic rotational diffusion using fluorescence imaging. We show that anisotropic wobble is directly quantified …

Pulsed Secondary Electron Yield Measurements Of Metallic And Dielectric Materials Of Interest For High Power Vacuum Electron Devices, Bilal Ahmed Malik

Electrical and Computer Engineering ETDs

Secondary electron emission (SEE) from conductors is thought to play an important role in the initiation of Multipactor breakdown in vacuum electron devices. The SEE of dielectric materials plays a crucial role in numerous scientific and technological applications, including particle accelerators, spacecraft charging, and plasma diagnostics. Additionally, the SEE of an insulator may depend on its electrical stress history. In both cases, SEE strongly depends on any conditioning of the material surface. We present measurements on both conducting and insulating materials of interest in these applications. Measurements are being made in an existing test stand, recently modified to enable measurements …

Authenticated Diagnosing Of Covid-19 Using Deep Learning-Based Ct Image Encryption Approach, Mohamed Attia Abdelgwad, Amira Hassan Abed, Mahmoud Bahloul

Future Computing and Informatics Journal

Researchers are motivated to use artificial intelligence in biometrics, medical imaging encryption, as well as cybersecurity due to its rapid progress. An encryption method for CT scans—which are used to diagnose COVID-19 disease—is proposed in this study. The suggested encryption method creates a connection among an individual's face picture and CT image to increase confidentiality. The simple CT picture is first enhanced with a host image. An encryption key is multiplied by the final result. This key is produced by applying a Convolutional Neural Network (CNN) to recognize characteristics from people's face photographs. Additionally, a straightforward CNN with three convolutional …

Segmentation And Classification Of Left Ventricular Abnormalities In Cardiac Mri Using Initial Point Prediction Based Deformable Model, Md. Asadur Rahman, Md. Al Noman, A. B. M. Aowlad Hossain

Future Computing and Informatics Journal

The shape of the left ventricle (LV) of a cardiac magnetic resonance image (CMRI) helps physicians to diagnose different cardiac abnormalities. The similarity of pixel intensity and shape of LV with neighbor tissues, the imprecision of boundaries, and the presence of noise are the challenges to accurate segmentation of LV. This paper contributes to the successful implementation of an automatic edge contouring method to segment LV area from CMRI and detect whether the ventricle belongs to abnormalities. This method proposes the regression-based artificial neural network to predict the possible initial position of the deformable edge-based active contour model for precise …

"Blockchain-Enhanced Electronic Health Records: A Secure And Immutable Approach To Ehr Management", Mostafa Abdelwahed Eltabakh, Mohamed E. Nasr, Emad Abd-Elrahman, Roayat Ismail Abdelfatah

Journal of Engineering Research

Traditional Electronic Health Record (EHR) systems face security risks, data misuse, and audit trail concerns. This paper proposes leveraging blockchain technology to improve EHRs, emphasizing Blockchain's potential to enhance data security, accessibility, and privacy through its encrypted and interconnected data block system, thereby addressing the core challenges of conventional EHR practices. This paper introduces a blockchain-based framework designed to consolidate and secure patient data within a singular record owned by the patient. Developed on the Ethereum network utilizing Ganache, this system employs programming languages and tools such as Solidity and web3.js. It leverages the blockchain platform for storing patient data …

Multi-Classification Model For Brain Tumor Early Prediction Based On Deep Learning Techniques, Abdelrahman T. Elgohr, Mohamed S. Elhadidy, Mahmoud Elazab Dr, Raneem Ahmed Hegazii, Moataz M. El Sherbiny

Journal of Engineering Research

Brain tumor early prediction is a critical task in medical imaging, as early detection and classification of tumors can significantly improve patient outcomes and treatment planning. In this study, we propose multi-classification models based on deep learning techniques for early prediction of brain tumors using magnetic resonance imaging (MRI) scans. Specifically, we investigate the effectiveness of Convolutional Neural Networks (CNN) in the You Only Look Once (YOLO) approach for an accurate classification of brain tumors into multiple classes based on their morphological characteristics. The proposed model is designed to extract spatial features from MRI images, capturing local patterns and structures …

Investigation Of Various Mimo Antenna For 5g Mobile Phone Applications, Rajesh Kumar D

Theses and Dissertations

The rapid progress of wireless communication systems has been driven by the persistent demand for higher data rates, improved connectivity, and seamless user experiences. The introduction of fifth-generation (5G) wireless technology introduces fresh challenges and possibilities within the domain of antenna design, particularly concerning Multiple-Input Multiple-Output (MIMO) systems operating in the sub-6 GHz frequency range. This thesis conducts a comprehensive exploration and conceptualization of MIMO antennas expressly crafted for smooth integration into mobile phones, with a particular emphasis on addressing the distinctive requisites of sub-6 GHz 5G communication.

The proposed antenna designs effectively harnesses the advantages inherent in multiple-input multiple-output …

Deep Learning For Multiple Unmanned Aerial Vehicle Coordination In Air Corridors, Liangkun Yu

Electrical and Computer Engineering ETDs

In the future, city skies will be filled with Unmanned Aerial Vehicles (UAVs) for rapid urban transport, including parcel deliveries and air taxis. NASA's Urban Air Mobility (UAM) envisions UAVs navigating air corridors. These virtual pathways ensure safety and compliance with regulations. However, current research on UAM practical applications is limited. This dissertation focuses on designing air corridors, developing UAV control systems, and ensuring the robustness of control algorithms against disturbances in real-world environments.

Our design features an air corridor system with horizontal lanes and on-off ramps, conceptualized as cylindrical spaces and tori, respectively. To enable each UAV to locally …

Design And Implementation Of Truly Random Number Generation Using Memristors For In-Memory Computing, Nick Felker

Theses and Dissertations

This paper proposes a new security module based on non-volatile memory. The module uses a memristor-based true random number generator to generate random numbers which can be used for cryptography. The module is implemented in software using a modified RISC-V instruction set architecture. The paper evaluates the performance of the module using the RISC-V simulator Gem5. The results show that the module can generate random numbers at a rate of 63 microseconds per number, which is faster than the standard C library’s random number generator. The module can also be used to scramble strings of characters and generate hashes of …

Reconfigurable Metasurface For 5g & Beyond Wireless Communication, Monisha S

Theses and Dissertations

The potential new applications and increasing demands of future 5th generation (5G) and beyond wireless communication indicate a promising future for mobile communications. However, the transmission medium has traditionally been seen as an unpredictable factor between the sender and receiver. As we enter the digital era of wireless communications, signal quality is deteriorating due to environmental interferences.

With the continuous advancement of technology, there is an increasing need for advanced solutions that can handle complex applications such as haptic communications, the Internet of Things for smart cities, automation, and manufacturing. One technology that has received much attention is the reconfigurable …

New Improvements To Defend Against Power Analysis Attacks In Ijtag Access Protocol, Haoran Wei

Computer Science and Engineering Theses and Dissertations

More and more instruments are now integrated on the chip for testing, debugging, monitoring, and post-silicon validation. IEEE Std 1687 (IJTAG) provides efficient access to these instruments. At the same time, techniques for an attacker to steal important data through the IJTAG network have also emerged. To improve the security of the IJTAG network and especially the communication between software and a board, others have proposed a security access protocol with several possible implementations based on an information hiding method. For example, one version of this previously published bidirectional authentication access protocol uses multiple templates to embed keys to improve …

Balloon Borne Gps-Enabled Radiosondes That Enable Simultaneous Multi-Point Atmospheric Sensing With A Single Ground Station, Peter A. Ribbens

Doctoral Dissertations and Master's Theses

Radiosondes are balloon borne atmospheric instruments that are a critical tool for understanding dynamics in the lower layers of the atmosphere. The low-cost radiosondes developed in the Space and Atmospheric Instrumentation Lab have been further developed to improve the system's use as a science-quality atmospheric instrument that is unique in its ability to simultaneously track multiple sondes with a single ground station. Sensors to measure temperature and pressure were added to improve measurements of the atmospheric state. A printed circuit board shield and 3D-printed shell were designed to make mass manufacturing possible. A thermistor-based temperature sensor was developed and tested …

Multisensory System For Probing Scattering Media, Muralidhar Madabhushi Balaji

Electrical Engineering Theses and Dissertations

There are numerous problems in the physical sciences wherein the scattering of light fundamentally limits our ability to perceive and reason about objects within the visual field. Examples include navigation in foggy weather, detecting hidden contraband/explosives, detecting diseased regions in agricultural produce, and detecting tumors within tissue. In all these scenarios, the scrambling of light paths due to scattering reduces the ability to locate embedded objects and identify their spatial or spectral features.

Existing approaches address the challenge by augmenting optical sensing modalities with complementary techniques that do not rely on optical phenomenology, such as Magnetic Resonance Imaging (MRI) or …

Increasing Optical Channel Capacity By Integrating Pam4 Modulation With Wavelength Division Multiplexing And Spatial Domain Multiplexing, Swaroopini Harish

Theses and Dissertations

Spatial division multiplexing (SDM) is a technique used in telecommunications and networking to increase data transmission capacity over optical fiber communication channels. This multiplexing technique spatially reuses optical frequencies by allocating different spatial locations for inputs based on their inject angles. The signals travel in a helical pattern within the carrier fiber and exit as concentric rings. SDM enables more efficient utilization of available bandwidth and improved communication performance. In four-level pulse amplitude modulation (PAM4), each symbol represents a combination of four possible signal levels instead of the two levels in binary modulation. The four levels are denoted in different …

Parallel Communications In Single-Core Optical Fibers Utilizing Spatial Domain Multiplexing And Wavelength Division Multiplexing, Mingxuan Tu

Theses and Dissertations

This endeavor proposes a hybrid parallel optical communication architecture in single-core fibers combining WDM in O-band (1270 nm, 1310 nm, 1310 nm, and 1330 nm) and two-channel SDM. The proposed architecture applies carefully designed delays in each propagating channel to achieve synchronization and, therefore, realizes parallel transmission in single-core fibers without the help of Serializer/De-serializers (SerDes). A mathematical model of SDM, calculations on delays between each optical channel, simulation of the hybrid architecture, experimental setup, and the testing and analysis of channel performance have been provided. A design of a photonic integrated circuit based on thin film lithium niobate electro-optic …

Strengthening Power Systems For Net Zero: A Review Of The Role Of Synchronous Condensers And Emerging Challenges, Hamid Soleimani, Daryoush Habibi, Mehrdad Ghahramani, Asma Aziz

Research outputs 2022 to 2026

System strength is both supplied and demanded in a power system during normal operations and in the presence of disturbances. This is characterised by stable voltage and frequency, supporting renewable generation such as wind and solar. Because the retirement of synchronous generators reduces system strength supply, and the connection of new inverter-based resource (IBR) generators increases demand, there is an urgent need for new sources of system strength. This paper provides an overview of the challenges brought about by grid modernisation. It highlights tangible solutions provided by synchronous condensers (SCs) to bolster grid strength, stability, and reliability while accommodating the …

Battery Management System Development For Electric Vehicles And Fast Charging Infrastructure Improvement, Yu Yang, Hen-Geul Yeh, Cesar Ortiz

Mineta Transportation Institute

The electric vehicle (EV) has become increasingly popular due to its being zero-emission. However, a significant challenge faced by EV drivers is the range anxiety associated with battery usage. Addressing this concern, this project develops a more efficient battery management system (BMS) for electric vehicles based on a real-time, state-of-charge (SOC) estimation. The proposed study delivers three modules: (1) a new equivalent circuit model (ECM) for lithium-ion batteries, (2) a new SOC estimator based on the moving horizon method, and (3) an on-board FPGA implementation of the classical Coulomb counting method for SOC estimation. The research team extends the traditional …

Zero Dynamics Attacks On Unknown Bilinear Systems: Vulnerability And Detection, Mohammad Aminul Haq

Electrical & Computer Engineering Theses & Dissertations

Critical infrastructure requires a safe and secure operating environment because of its significant impact on society. Its large-scale size and distributed sensors and actuators make it vulnerable to cyber-physical attacks. A zero dynamics attack is a type of cyber-physical attack where an adversary keeps the output of the target constant (classically zero), while forcing some of the internal states to deviate from their nominal values. Most of the existing work in the literature assumes the system dynamics are linear and available to an adversary. The first goal of this dissertation is to show that an adversary can successfully execute a …

Growth And Simulation Of Dielectric-Metal Nanoheterostructured Thin Films By Ballistic Deposition, Shawn Wimer

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

This thesis is divided into two related topics: the structural and chemical characterization of dielectric-metal nanoheterostructured thin films grown by glancing angle deposition (GLAD) and the results of the simulated growth of films and structures by GLAD with discrete-space and continuous-space Monte Carlo ballistic simulation.

Individual structures comprising films grown by GLAD were investigated by S/TEM and SEM imaging, electron diffraction, and chemical characterization and mapping by EDX. Different intermolecular interactions within and between different materials, including Si, Ag, Au, and ZrO₂, are linked to differences in the shapes of individual materials in heterostructures, the shape of heterostructures …

Modelling, Design, Control, And Implementation Of Advanced Isolated Dc/Dc Converters For Renewable Energy Applications, Yuqi Wei, Quanming Luo, Di Mou, Shuang Zhao, Marco Liserre, H. Alan Mantooth

Electrical Engineering and Computer Science Faculty Publications and Presentations

Demand for high-efficient isolated DC/DC converters to achieve energy transfer among renewable energy sources, energy storage elements, and loads is increasing because of renewable energies’ increasing market penetration. Traditional converters pose significant challenges due to the wide voltage range operation nature of these components. Interest in improving the power converters’ performances for renewable energy applications is growing rapidly. Researchers are exploring accurate analysis methods, optimal design, and novel control strategies to improve the power converters’ performance. These strategies can improve the converters’ performance without any modifications to the traditional hardware. In addition, design automations are drawing more and more attention. …

Predicting Iot Distributed Ledger Fraud Transactions With A Lightweight Gan Network, Charles Rawlins, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

Decision-making and consensus in traditional blockchain protocols is formulated as a repeated Bernoulli trial that solves a computationally intense lottery puzzle, called Proof-of-Work (PoW) in Bitcoin. This approach has shown robustness through practice but does not scale with increasing network size and generation of new transactions. Resource constrained Internet of Things (IoT) networks are incompatible with full computation of schemes like Bitcoin's PoW. Our effort proposes a first step towards an alternative consensus using machine learning-based decision-making with prediction of fraud transactions to alleviate need for intense computation. To improve base approval probabilities for fraud detection in an ideal security …

Optical Frequency Domain Reflectometry-Based High-Performance Distributed Sensing Empowered By A Data And Physics-Driven Neural Network, Zhaopeng Zhang, Wei Peng, Osamah Alsalman, Lingmei Ma, Jie Huang, Chen Zhu

Electrical and Computer Engineering Faculty Research & Creative Works

Optical frequency domain reflectometry (OFDR) based distributed strain sensors are the preferred choice for achieving accurate strain measurements over extensive sensing ranges while maintaining exceptional spatial resolution. However, the simultaneous realization of high spatial resolution, high strain resolution, large strain range, and an extended sensing range presents an exceedingly challenging endeavor. In this study, we introduce and experimentally demonstrate a data and physics-driven neural network-empowered OFDR system designed to attain high-performance distributed sensing. In our experiments, we successfully maintained an impressive sensing resolution of sub-microstrain (0.91 µε) alongside a sharp spatial resolution of sub-millimeter (0.857 mm) across a 140-m sensing …

Ultrasonic Flow Meter Calibration Via The Internet Using An Analog-To-Digital Converter, Aliev Ravshan, A.U. Djalilov

Chemical Technology, Control and Management

The purpose of scientific research work is remote control of improving the metrological properties of the water flow measuring device. Therefore, the Arduino platform with an additional ESP8266 NodeMcu v3 and analog-to-digital converter, module was installed in the scientific article for automatic calibration/checking of ultrasonic flow meters used in irrigation networks. The module is integrated into a 32-bit microcontroller with low power consumption. The ESP8266 NodeMcu v3 module operates at 80 and 160 MHz clock frequencies, supports real-time operating system (RTOS), built-in Wi-Fi, and has a microstrip antenna on board. Through this, the data exchange between the computing equipment and …

Environmental Monitoring And Control System Of Greenhouse Based On Internet Of Things Technology, Ru Jiang, Nadirbek Yusupbekov

Chemical Technology, Control and Management

Greenhouse is an important application scene of modern agriculture. In this paper, a set of greenhouse environmental monitoring, facility remote control and production management system is designed and implemented based on Internet of Things technology for the development needs of modern agriculture in greenhouse. The system selects STM32F407 control board as the main controller to realize real-time monitoring of greenhouse environmental parameters including temperature and humidity, soil nutrients, soil pH and other greenhouse environmental information, and can adjust greenhouse environmental parameters by controlling the irrigation system, roller shutters, fans, shading curtains and other facilities in the greenhouse. The main controller …

Decision-Making Algorithms For Drilling Instrument Control Systems, Fuzayl Fozil Ugli Odilov

Chemical Technology, Control and Management

The control of the movement of the drilling tool and the structure of the well are considered. An effective control algorithm for drilling systems that provides control of well trajectory parameters is analyzed. In technological processes, it is necessary to control several parameters or several systems at the same time. It is considered necessary to create decision-making algorithms for the formation of managerial effects for the control system of such technological processes. The controlled oriented type of the bottom of the drill string was analyzed. Work was carried out on the decision-making algorithm for the processing of control effects. The …

Matrix Processing With Photonic Analog Computing, James Michael Garofolo

Theses and Dissertations

In the digital age, a wide variety of engineering problems have been solved, to a great deal of success, by digital computing techniques. The flexibility of software and relatively low cost of digital computing hardware make it an ideal starting point for solving a majority of tasks, and the numerical stability of software solutions make it highly appealing as the major workhorse for computational tasks. Despite this, many problems are actually suboptimally solved by digital methods, leading to systems with high latency, low throughput, power hungry parallel processing units and an excess of memory for discretizing sensor inputs. Computational photonic …

Surface Structures And Properties Of High-Voltage Licoo2: Reviews And Prospects, Jian-Jun Fang, Yu-Hao Du, Zi-Jian Li, Wen-Guang Fan, Heng-Yu Ren, Hao-Cong Yi, Qing-He Zhao, Feng Pan

Journal of Electrochemistry

Nowadays, the development of high-voltage LiCoO₂ (lithium cobalt oxide, LCO) cathodes has attracted the widespread attention from both the academic and industry fields. Among the multiple concerns, researches on the surface issues would provide the most effective performance optimization pathway for the synthesis of high-voltage LCO. In this work, the issues of high-voltage LCO, including the phase transitions and crack formation, the oxygen redox related issues and side reactions, as well as the surface structure degradation, have been systematically reviewed. Then, we further clarify the surface modulations, and the interplay between the surface modulation and electrolyte tuning. Finally, we …