Electrical and Electronics Commons^™

Resampling And Super-Resolution Of Hexagonally Sampled Images Using Deep Learning, Dylan Flaute, Russell C. Hardie, Hamed Elwarfalli

Electrical and Computer Engineering Faculty Publications

Super-resolution (SR) aims to increase the resolution of imagery. Applications include security, medical imaging, and object recognition. We propose a deep learning-based SR system that takes a hexagonally sampled low-resolution image as an input and generates a rectangularly sampled SR image as an output. For training and testing, we use a realistic observation model that includes optical degradation from diffraction and sensor degradation from detector integration. Our SR approach first uses non-uniform interpolation to partially upsample the observed hexagonal imagery and convert it to a rectangular grid. We then leverage a state-of-the-art convolutional neural network (CNN) architecture designed for SR …

Parents’ Perspectives On A Smartwatch Intervention For Children With Adhd: Rapid Deployment And Feasibility Evaluation Of A Pilot Intervention To Support Distance Learning During Covid-19, Franceli L. Cibrian, Elissa Monteiro, Elizabeth Ankrah, Jesus A. Beltran, Arya Tavakoulnia, Sabrina E. B. Schuck, Gillian R. Hayes, Kimberley D. Lakes

Engineering Faculty Articles and Research

Distance learning in response to the COVID-19 pandemic presented tremendous challenges for many families. Parents were expected to support children’s learning, often while also working from home. Students with Attention Deficit Hyperactivity Disorder (ADHD) are at particularly high risk for setbacks due to difficulties with organization and increased risk of not participating in scheduled online learning. This paper explores how smartwatch technology, including timing notifications, can support children with ADHD during distance learning due to COVID-19. We implemented a 6-week pilot study of a Digital Health Intervention (DHI) with ten families. The DHI included a smartwatch and a smartphone. Google …

Prevalence Of Pretransition Disordering In The Rutile-To-Cacl2 Phase Transition Of Geo2, G. Alexander Smith, Daniel Schacher, Jasmine K. Hinton, Daniel Sneed, Changyong Park, Sylvain Petitgirard, Keith V. Lawler, Ashkan Salamat

Physics & Astronomy Faculty Research

The ability to tailor a material's electronic properties using density driven disordering has emerged as a powerful route to materials design. The observation of anomalous structural and electronic behavior in the rutile to CaCl2 phase transition in SnO2 led to the prediction that such behavior is inherent to all oxides experiencing such a phase transition sequence [Smith et al., J. Phys. Chem. Lett. 10, 5351 (2019)1948-718510.1021/acs.jpclett.9b01633]. Here, the ultrawide band gap semiconductor GeO2 is confirmed to exhibit anomalous behavior during the rutile to CaCl2 phase transition. A phase pure rutile GeO2 sample synthesized under high-pressure, high-temperature conditions is probed using …

A 12-Bit 1gs/S Sar-Assisted Pipeline Adc With Harmonic Injecting Residue Amplifier, Liang Fang

Electrical Engineering Theses and Dissertations

Advanced wireless applications require a medium resolution Radio Frequency (RF) sampling Analog to Digital Converter (ADC). By performing sampling of ADC at RF frequency, the mixer and Intermediate Frequency (IF) amplifier can be implemented in the digital domain, which helps the receiver eliminate troublesome mixing spurs and potentially improves the software-defined ratio of the entire system. By combing the merits of the energy-efficient Successive Approximation Register (SAR) ADC and the high-speed pipeline ADC, the SAR-assisted pipeline ADC achieves superior performance in high-speed medium-resolution ADC. However, with the advance of the process, due to the pure analog implementation, the residue amplifier …

A Unified Framework Of Deep Learning-Based Facial Expression Recognition System For Diversified Applications, Sanoar Hossain, Saiyed Umer, Vijayan K. Asari, Ranjeet Kumar Rout

Electrical and Computer Engineering Faculty Publications

This work proposes a facial expression recognition system for a diversified field of appli- cations. The purpose of the proposed system is to predict the type of expressions in a human face region. The implementation of the proposed method is fragmented into three components. In the first component, from the given input image, a tree-structured part model has been applied that predicts some landmark points on the input image to detect facial regions. The detected face region was normalized to its fixed size and then down-sampled to its varying sizes such that the advantages, due to the effect of multi-resolution …

Real Time Simulation And Hardware In The Loop Methods For Power Electronics Power Distribution Systems, Michele Difronzo

Theses and Dissertations

System level testing of Power Electronics Power Distribution Systems (PEPDS) can be challenging when fine temporal resolution is required (time step below 100-200ns). In the recent years, our research group has proposed various methods to simulate in real-time PEPDS using FPGAs and time step as small as 50ns. While the proposed methods allow achieving the desired temporal resolution, they are extremely demanding in terms of resources usage and the size of the PEPDS that can be simulated on a single FPGA is strongly limited.

In this dissertation -work that takes as an example application the US Navy electric Ship Zonal …

Combined Devices Of Facts Technology, Bahrom Ravshanovich Normuratov Associate Lecturer, Misrikhan Misrikhanov, Shukhrat Khamidov

Technical science and innovation

FACTS - Flexible Alternative Current Transmission System technology is a family of devices, each of which can be used individually and in concert with other devices to control the interrelated parameters of the electrical power system. The mission of FACTS technology is to improve the control of power flows in both steady-state and transient modes of EPS. Flexibility of Electric Power Transmission, applied as "The ability to adapt to changes in transmission system or operating conditions while maintaining sufficient operating limits in steady-state and transient modes". Controlled Flexible AC Transmission Lines - Flexibility from Electric Power Transmission means "AC Power …

Optimal Placement Of Fuses And Switches In Active Distribution Networks Using Value-Based Minlp, N. Gholizadeh, S.H. Hosseinian, M. Abedi, Hamed Nafisi, P. Siano

Articles

Contingency conditions in distribution networks create financial losses for different parts of the system including electricity customers, electricity retailers, distributed generation (DG) units, etc. Therefore, protective device allocation methods have been introduced in recent years to enhance the reliability of the power system. In this study, a new formulation is proposed to find the optimal places of sectionalizing switches and fuses while taking the financial loss of both electricity customers and DG units into account. The current method has the flexibility to consider DG effect on any location of the network and its islanded operation in case of contingencies. Moreover, …

A Modular Open-Technology Device To Measure And Adjust Concentration Of Sperm Samples For Cryopreservation, Nikolas C. Zuchowicz

LSU Master's Theses

Repositories for aquatic germplasm can safeguard the genetic diversity of species of interest to aquaculture, research, and conservation. The development of such repositories is impeded by a lack of standardization both within laboratories and across the research community. Protocols for cryopreservation are often developed ad hoc and without close attention to variables, such as sperm concentration, that strongly affect the success and consistency of cryopreservation. The wide dissemination and use of specialized tools and devices can improve processing reliability, provide data logging, produce custom hardware to address unique problems, and save costs, time, and labor. The goal of the present …

Source Localization Of Electroencephalogram (Eeg) Waves With Convolutional Neural Network, Terence Onyewuenyi

Symposium of Student Scholars

This paper investigates the use of deep learning as a means for quantification and source localization of prioritizing electroencephalogram (EEG) waves for the purpose of detecting different eye states of human subjects. The Convolutional Deep Learning tool is trained to recognize EEG reading corresponding to a set of different eye movements as generated by watching different action scenes. The results also predict whether the subjects' eyes are open or closed. Source localization is performed next on the EEG data to focus on the different EEG components which primarily contribute to the activity. This was done by using a convolutional neural …

Colloidal Quantum Dot (Cqd) Based Mid-Wavelength Infrared Optoelectronics, Shihab Bin Hafiz

Dissertations

Colloidal quantum dot (CQD) photodetectors are a rapidly emerging technology with a potential to significantly impact today’s infrared sensing and imaging technologies. To date, CQD photodetector research is primarily focused on lead-chalcogenide semiconductor CQDs which have spectral response fundamentally limited by the bulk bandgap of the constituent material, confining their applications to near-infrared (NIR, 0.7-1.0 um) and short-wavelength infrared (SWIR, 1-2.5 um) spectral regions. The overall goal of this dissertation is to investigate a new generation of CQD materials and devices that advances the current CQD photodetector research toward the technologically important thermal infrared region of 3-5 ?m, known as …

Learning Of Radar System For Target Detection, Wei Jiang

Dissertations

In this dissertation, the problem of data-driven joint design of transmitted waveform and detector in a radar system is addressed. Two novel learning-based approaches to waveform and detector design are proposed based on end-to-end training of the radar system. The first approach consists of alternating supervised training of the detector for a fixed waveform and reinforcement learning of the transmitter for a fixed detector. In the second approach, the transmitter and detector are trained simultaneously. Various operational waveform constraints, such as peak-to-average-power ratio (PAR) and spectral compatibility, are incorporated into the design. Unlike traditional radar design methods that rely on …

The Effect Of A Ferrite-Core Relay Vs. An Air-Core Relay On The Output Power Characteristics Of A Three-Coil Wireless Power Transfer System, Jakob L. White

University Honors Theses

The purpose of this thesis is to determine the effect of using a ferrite-core relay on the output power characteristics of a three-coil, parallel-tuned, domino-resonator wireless power transfer (WPT) system in comparison to the effect of using an air-core relay in such a system. First, a general mathematical model is presented to describe both the ferrite-core-relay system and the air-core-relay system and to calculate their output power characteristics for seven different resistive loads at each of five different distance configurations between the coils. Next, experimental results are analyzed and compared to the mathematical results to confirm model accuracy. Finally, the …

Flexible Electronics For Neurological Electronic Skin With Multiple Sensing Modalities, Haochuan Wan

McKelvey School of Engineering Graduate Student Theses & Dissertations

The evolution of electronic skin (E-skin) technology in the past decade has resulted in a great variety of flexible electronic devices that mimic the physical and chemical sensing properties of skin for applications in advanced robotics, prosthetics, and health monitoring technologies. The further advancement of E-skin technology demands closer imitation of skin receptors' transduction mechanisms, simultaneous detection of multiple information from different sources, and the study of transmission, processing and memory of the signals among the neurons. Motivated by such demands, this thesis focuses on design, fabrication, characterization of novel flexible electronic devices and integration of individual devices to realize …

Algebraic, Computational, And Data-Driven Methods For Control-Theoretic Analysis And Learning Of Ensemble Systems, Wei Miao

McKelvey School of Engineering Graduate Student Theses & Dissertations

In this thesis, we study a class of problems involving a population of dynamical systems under a common control signal, namely, ensemble systems, through both control-theoretic and data-driven perspectives. These problems are stemmed from the growing need to understand and manipulate large collections of dynamical systems in emerging scientific areas such as quantum control, neuroscience, and magnetic resonance imaging. We examine fundamental control-theoretic properties such as ensemble controllability of ensemble systems and ensemble reachability of ensemble states, and propose ensemble control design approaches to devise control signals that steer ensemble systems to desired profiles. We show that these control-theoretic properties …

Continuous-Time And Complex Growth Transforms For Analog Computing And Optimization, Oindrila Chatterjee

McKelvey School of Engineering Graduate Student Theses & Dissertations

Analog computing is a promising and practical candidate for solving complex computational problems involving algebraic and differential equations. At the fundamental level, an analog computing framework can be viewed as a dynamical system that evolves following fundamental physical principles, like energy minimization, to solve a computing task. Additionally, conservation laws, such as conservation of charge, energy, or mass, provide a natural way to couple and constrain spatially separated variables. Taking a cue from these observations, in this dissertation, I have explored a novel dynamical system-based computing framework that exploits naturally occurring analog conservation constraints to solve a variety of optimization …

Machine Learning For Analog/Mixed-Signal Integrated Circuit Design Automation, Weidong Cao

McKelvey School of Engineering Graduate Student Theses & Dissertations

Analog/mixed-signal (AMS) integrated circuits (ICs) play an essential role in electronic systems by processing analog signals and performing data conversion to bridge the analog physical world and our digital information world.Their ubiquitousness powers diverse applications ranging from smart devices and autonomous cars to crucial infrastructures. Despite such critical importance, conventional design strategies of AMS circuits still follow an expensive and time-consuming manual process and are unable to meet the exponentially-growing productivity demands from industry and satisfy the rapidly-changing design specifications from many emerging applications. Design automation of AMS IC is thus the key to tackling these challenges and has been …

Elucidating And Leveraging Dynamics-Function Relationships In Neural Circuits Through Modeling And Optimal Control, Sruti Mallik

McKelvey School of Engineering Graduate Student Theses & Dissertations

A fundamental research question in neuroscience pertains to understanding how neural networks through their activity encode and decode information. In this research, we build on methods from theoretical domains such as control theory, dynamical systems analysis and reinforcement learning to investigate such questions. Our objective is two-fold: first, to use methods from engineering to identify specific objectives that neural circuits might be optimizing through their spatiotemporal activity patterns, and second, to draw motivation from neuroscience to formulate new engineering principles such as synthesis of dynamical networks for decentralized control applications. We specifically take a top-down, optimization driven approach in our …

Long-Term Neural Activity Recorders Using Energy-Based Sensing, Compressive Computation And Data Logging, Darshit Mehta

McKelvey School of Engineering Graduate Student Theses & Dissertations

Insects are ideal candidates for developing bio-robotic systems owing to their ability to thrive in almost any environment. For example, neurons in their exquisite olfactory sensory systems can be tapped to create a sensing platform for standoff chemical monitoring. However, for enabling such cyborg systems, it is vital that the neural activity of a freely behaving organism can be measured for long periods of time. The current state-of-the-art neural recording techniques are power-intensive and they either need batteries, which make them too bulky for insects, or they have to maintain a continuous telemetry link to an external power source which …

First Demonstration Of Orange-Yellow Light Emitter Devices In Ingap/ Inalgap Laser Structure Using A Strain-Induced Quantum Well Intermixing Technique, Bayan A. Alnahhas

Effat Undergraduate Research Journal

In this paper, a novel strain-induced quantum well intermixing (QWI) technique is employed on an InGaP/InAlGaP material system to promote interdiffusion via application of a thick-dielectric encapsulant layer, in conjunction with cycle annealing at elevated temperature. With this technique, we demonstrate the first yellow superluminescent (SLD) at a wavelength of 583nm with a total two-facet output power of ~4.5mW—the highest optical power ever reported at this wavelength in this material system. The demonstration of the yellow SLD without complicated multiquantum barriers to suppress the carrier overflow will have a great impact in realizing the yellow laser diode that cannot be …

Comparison Of Concrete And Steel Jacket Methods For Reinforcing A Concrete Bridge Pier By Numerical And Experimental Studies, Hadi Faghihmaleki

Makara Journal of Technology

Various rehabilitation and strengthening procedures have been developed in recent decades. A study to determine which methods can be implemented to increase the useful life of the bridge before strengthening must be performed. In this study, the seismic behavior of a reinforced concrete bridge pier with dimension 3.5 × 3.5 m, which was reinforced by two steel and a concrete jacket, was investigated. Nonlinear geometric models and materials were analyzed to estimate the seismic parameters of the pier. Results show an increase in energy absorption, ultimate strength, and ductility for the steel jacket, as well as a greater increase in …

Effect Of Arc Plasma Sintering On The Structural And Microstructural Properties Of Fe-Cr-Ni Austenitic Stainless Steels, Parikin Parikin, M. Dani, A. Dimyati, N. D. Purnamasari, B. Sugeng, M. Panitra, A. Insani, T. H. Priyanto, S. Mustofa, Syahbuddin Syahbuddin, A. Huang

Makara Journal of Technology

X-ray diffraction techniques were performed to determine the actual crystal structure of A2 austenitic stainless steel (ASS) as-cast and A2 ASS after arc plasma sintering (APS) for 2 s. Computations were conducted on the basis of the Bragg arithmetic formula by comparing the S2 arithmetic with the interplanar spacing. The Bragg arithmetic formula is a simple series for the determination of the crystalline phase of materials based on the Miller indices of cubic shapes or other shapes. A2 ASS as-cast was identified to have a crystal structure of face-centered cubic with lattice parameter a = 3.58 Å. A similar crystal …

Trend Significance Levels Of Rain Onset And Cessation And Lengths Of The Wet And Dry Seasons In Epe, Lagos State, Nigeria, Adekunle Adedeji Alli, Olorunwa Eric Omofunmi

Makara Journal of Technology

This study aims to reduce crop failure resulting from a dry spell, which is the first occurrence of unsustainable rainfall that deceives farmers into planting. Thus, trends need to be tested using hypothesis, kurtosis, and other statistics to analyze the risks associated with unstable planting calendars and their possible mitigation strategies. The daily rainfall data from 1982 to 2018 were obtained from the archive of NASA/POWER SRB/FLASH, and the research location is Epe, Lagos State, Nigeria, which lies at latitude 6.585° N and longitude 3.962° E. Microsoft Excel was used to perform the tests. Results show that the null hypothesis …

Kinetic Modeling Study Of Laminar Burning Velocity Of Gasoline–Ethanol–Methanol Blends At Elevated Temperature And Pressure, Ahmad Syihan Auzani, Cahyo Setyo Wibowo, Riesta Anggarani, Yulianto Sulistyo Nugroho, Bambang Sugiarto

Makara Journal of Technology

Gasoline–ethanol–methanol (GEM) blends have been considered to replace pure gasoline as spark ignition engine fuel. Their physical and chemical properties and performance and emission measurements from real engines have been reported previously. However, a fundamental study that can explain the unique results of GEM compared with those of pure gasoline is lacking. This study aims to compare the laminar burning velocity of GEM blends at different mixtures, equivalence ratios, temperatures, and pressures with that of pure gasoline. A laminar flame propagation model and reaction mechanisms from the literature were were for a numerical simulation. In this study, the chemical components …

Improvement Of Electrical Properties Of Cmc-Pva Doped With Various Contents Of Lino3 As An Application For Hybrid Polymer Electrolytes, Amalia Zulkifli, Norfatihah Mazuki, Ahmad Salihin Samsudin

Makara Journal of Technology

The present work was carried out with the development of hybrid polymer electrolytes (HPEs) by using carboxymethyl cellulose (CMC)–polyvinyl alcohol (PVA) doped with different contents of lithium nitrate (LiNO3) for the determination of their structural and conduction properties. The structural analysis was conducted by using Fourier transform infra-red spectroscopy and showed the interaction between the blend host polymer and ionic dopant, which formed via the coordinating site of CMC-PVA and Li+-NO3−. The complexes of CMC-PVA doped LiNO3 led to an increment in ionic conductivity, as observed by electrical impedance spectroscopy, and the sample containing 20 wt% LiNO3 obtained the highest …

Music Information Retrieval Based On Active Frequency, Hardianto Wibowo, Wildan Suharso, Yufis Azhar, Galih Wasis Wicaksono, Agus Eko Minarno, Dani Harmanto

Makara Journal of Technology

Music is the art of combining frequencies. A balance of frequencies gives rise to a harmonious tone. Several features of music can be analyzed, and they include sociocultural background, lyrics, mood, tempo, rhythm, harmony, melody, timbre, and instrumentation. In this study, we use the frequency of instrumentation as a feature for classification because each instrument has a frequency range. To test this frequency range, we use five music genres and one music playing skill. The five genres are dangdut, electronic dance music (EDM), metal, pop/rock, and reggae. The music playing skill is acoustic. Active frequencies are tested using the k-nearest …

Predictive Delivery Man Assignment Problem Using Deep Learning, Rahmadini Payla Juarsa, Taufik Djatna

Makara Journal of Technology

Dispatching is a critical part in current online shopping. It relates to how the delivery man assignment should minimize cost along with the service from a source to an end customer with an appropriate scheduled time. The problem arises as neither enough products to deliver nor delivery men are available for dispatch, resulting in suboptimal service and a waste of money. The study aimed to formulate the cost of restaurant dispatching for inducing a deep learning-based solution with the gated recurrent unit recurrent neural network to receive hourly order data and to engage the result for near feature delivery man …

Hardware For Quantized Mixed-Precision Deep Neural Networks, Andres Rios

Open Access Theses & Dissertations

Recently, there has been a push to perform deep learning (DL) computations on the edge rather than the cloud due to latency, network connectivity, energy consumption, and privacy issues. However, state-of-the-art deep neural networks (DNNs) require vast amounts of computational power, data, and energyâ??resources that are limited on edge devices. This limitation has brought the need to design domain-specific architectures (DSAs) that implement DL-specific hardware optimizations. Traditionally DNNs have run on 32-bit floating-point numbers; however, a body of research has shown that DNNs are surprisingly robust and do not require all 32 bits. Instead, using quantization, networks can run on …

Characterization Of Wide-Bandgap Sic Field Effect Transistors And Their Active Gate Driving Circuit In High Power Applications, Arijit Sengupta

Legacy Theses & Dissertations (2009 - 2024)

Silicon Carbide (SiC) devices are slowly becoming one of the most reliable choices for high power density, high switching frequency applications with higher efficiency than Gallium Nitride (GaN) and Silicon (Si) devices. For a wide range of applications, such as Electric Motor Drives, Switching Power Supplies, and Renewable Energy Circuits, SiC devices are being tested and are found to yield prominent results.In this research, the characterization of two similarly rated commercially available SiC devices - a trench Metal-Oxide-Semiconductor Field-Effect Transistor (MOSFET) and a cascoded Junction Field Effect Transistor (JFET) are done. It is followed by a comparative analysis of both …

Fast Magnetic Resonance Image Reconstruction With Deep Learning Using An Efficientnet Encoder, Tahsin Rahman

Open Access Theses & Dissertations

This thesis aims to develop an efficient, deep network based method for Magnetic Resonance Imaging (MRI) acceleration through undersampled MR image reconstruction. Deep Neural Networks, particularly Deep Convolutional Networks, have been demonstrated to be highly effective in a wide variety of computer vision tasks, including MRI reconstruction. However, modern highly efficient encoder structures, such as the EfficientNet can potentially reduce reconstruction times further while improving reconstruction quality. To that end, we have developed a multi-channel U-Net MRI reconstruction network which uses an EfficientNet encoder and a custom asymmetric. The network was trained and tested using 5x undersampled multi-channel brain MR …