Engineering Commons^™

Eye-Gaze-Controlled Hmds And Mfd For Military Aircraft, Lrd Murthy, Abhishek Mukhopadhyay, Somnath Arjun, Varshith Yelleti, Peter Thomas, Dilli Babu Mohan, Pradipta Biswas

Journal of Aviation Technology and Engineering

Eye-gaze-controlled interfaces allow the direct manipulation of a graphical user interface by looking at it. This technology has great potential in military aviation, in particular, operating different displays in situations where pilots’ hands are occupied with flying the aircraft. This paper reports studies on analyzing the accuracy of eye-gaze-controlled interfaces inside aircraft undertaking representative flying missions. We report that using eye-gaze-controlled interfaces, pilots can undertake representative pointing and selection tasks at less than two seconds on average in a transport aircraft. Further, we analyzed the accuracy of eye-gaze-tracking glasses under various G load factors and analyzed the failure modes. We …

Single Event Transient Sensitivity Measurement And Worst-Case Test Vector Exploration For Asic Devices Exposed To Space Single Event Environment, Mohamed Wael

Theses and Dissertations

Space radiation and nuclear reactors produce single event effects (SEE) in electronic circuits and impact their performance. The SEE phenomena cause circuits and electronic devices to fail by producing faulty results. Therefore, today’s circuit’s reliability is a significant concern for all circuit designers.

This thesis suggests a new automated flow to measure the single-event-transient (SET) effects in combinational circuits in application-specific integrated circuits (ASIC) while reaching full fault coverage. The developed flow characterizes the whole circuit nodes by identifying the most sensitive paths to the propagated SET pulses from the node under test to an observable primary output, causing single …

Physiological Signal Analysis For Emotion Estimation Of Children With Autism Spectrum Disorder, Janet Pulgares Soriano, Karla Conn Welch Phd

Posters-at-the-Capitol

The diagnosis of Autism Spectrum Disorder (ASD) in children is based on human observations by a clinician. The medical evaluation assesses deficits in social communication, social interaction, and restricted, repetitive behaviors. Robotic technology can assist in quantitatively measuring the observations to be used as a future tool for autism diagnosis and intervention. The project explores this technology to produce robotic partners that can adapt to the needs of the ASD population. This way, such robots could serve as instructors or learning peers. A friendly, partner robot, specifically designed for children with ASD could be used to investigate the effect of …

Solar Air Heater With Breathable Matrix Absorber Made Of Metal Wire Tangle, Yu. K. Rashidov, J. T. Orzimatov

Scientific-technical journal

In the article, a physical and mathematical thermal model of the operation of a solar air-heating collector with an air-permeable matrix absorber made of a metal wire tangle is developed, and analytical solutions of the model for boundary conditions of the first and second kind are obtained.

Application Of Deep Neural Networks To Distribution System State Estimation And Forecasting, James P. Carmichael, Yuan Liao

Electrical and Computer Engineering Faculty Publications

Classical neural networks such as feedforward multi-layer perceptron models (MLPs) are well established as universal approximators and as such, show promise in applications such as static state estimation in power transmission systems. The dynamic nature of distributed generation (i.e. solar and wind), vehicle to grid technology (V2G) and false data injection attacks (FDIAs), may pose significant challenges to the application of classical MLPs to state estimation (SE) and state forecasting (SF) in power distribution systems. This paper investigates the application of conventional neural networks (MLPs) and deep learning based models such as convolutional neural networks (CNNs) and long-short term networks …

Application Of Deep Neural Networks To Distribution System State Estimation And Forecasting, James P. Carmichael, Yuan Liao

Electrical and Computer Engineering Faculty Publications

Classical neural networks such as feedforward multi-layer perceptron models (MLPs) are well established as universal approximators and as such, show promise in applications such as static state estimation in power transmission systems. The dynamic nature of distributed generation (i.e. solar and wind), vehicle to grid technology (V2G) and false data injection attacks (FDIAs), may pose significant challenges to the application of classical MLPs to state estimation (SE) and state forecasting (SF) in power distribution systems. This paper investigates the application of conventional neural networks (MLPs) and deep learning based models such as convolutional neural networks (CNNs) and long-short term networks …

A Deep Neural Network For Early Detection And Prediction Of Chronic Kidney Disease, Vijendra Singh, Vijayan K. Asari, Rajkumar Rajasekaran

Electrical and Computer Engineering Faculty Publications

Diabetes and high blood pressure are the primary causes of Chronic Kidney Disease (CKD). Glomerular Filtration Rate (GFR) and kidney damage markers are used by researchers around the world to identify CKD as a condition that leads to reduced renal function over time. A person with CKD has a higher chance of dying young. Doctors face a difficult task in diagnosing the different diseases linked to CKD at an early stage in order to prevent the disease. This research presents a novel deep learning model for the early detection and prediction of CKD. This research objectives to create a deep …

Characteristic Mode Analysis Prediction And Guidance Of Electromagnetic Coupling Measurements To A Uav Model, Mohamed Z. M. Hamdalla, Benjamin Bissen, James D. Hunter, Yuanzhuo Liu, Victor Khilkevich, Daryl G. Beetner, Anthony N. Caruso, Ahmed M. Hassan

Electrical and Computer Engineering Faculty Research & Creative Works

In this work, we study the current coupled to a simplified Unmanned Aerial Vehicle (UAV) model using a dual computational and experimental approach. The simplified surrogate structure reduced the computational burden and facilitated the experimental measurement of the coupled currents. For a practical system, a wide range of simulations and measurements must be performed to analyze the induced current variations with respect to properties of the incident excitation waveform, such as the frequency, angle of incidence, and polarization. To simplify this analysis, Characteristic Mode Analysis (CMA) was used to compute the eigen-currents of the UAV model and predict where and …

A Deep Learning Approach To Design And Discover Sustainable Cementitious Binders: Strategies To Learn From Small Databases And Develop Closed-Form Analytical Models, Taihao Han, Sai Akshay Ponduru, Rachel Cook, Jie Huang, Gaurav Sant, Aditya Kumar

Electrical and Computer Engineering Faculty Research & Creative Works

To reduce the energy-intensity and carbon footprint of Portland cement (PC), the prevailing practice embraced by concrete technologists is to partially replace the PC in concrete with supplementary cementitious materials [SCMs: geological materials (e.g., limestone); industrial by-products (e.g., fly ash); and processed materials (e.g., calcined clay)]. Chemistry and content of the SCM profoundly affect PC hydration kinetics; which, in turn, dictates the evolutions of microstructure and properties of the [PC + SCM] binder. Owing to the substantial diversity in SCMs' compositions-plus the massive combinatorial spaces, and the highly nonlinear and mutually-interacting processes that arise from SCM-PC interactions-state-of-the-art computational models are …

An Interleaved High Step-Up Dc-Dc Converter Based On Integration Of Coupled Inductor And Built-In-Transformer With Switched-Capacitor Cells For Renewable Energy Applications, Ramin Rahimi, Saeed Habibi, Mehdi Ferdowsi, Pourya Shamsi

Electrical and Computer Engineering Faculty Research & Creative Works

This paper proposes an interleaved high step-up DC-DC converter with the coupled inductor (CI) and built-in transformer (BIT) for renewable energy applications. Two double-winding (2W) CIs and one triple-winding (3W) BIT are integrated with the switched-capacitor (SC) voltage multiplier cells (VMCs) to achieve high-voltage gains without extreme duty cycles. The CIs and BIT turns-ratios provide two other degrees of freedom -- in addition to the duty cycle -- to adjust the voltage gain that leads to increased design flexibility. The diodes turn off naturally under the zero-current switching (ZCS) conditions because their current falling rates are controlled by the leakage …

A Deep Learning Approach To Design And Discover Sustainable Cementitious Binders: Strategies To Learn From Small Databases And Develop Closed-Form Analytical Models, Taihao Han, Sai Akshay Ponduru, Rachel Cook, Jie Huang, Gaurav Sant, Aditya Kumar

Electrical and Computer Engineering Faculty Research & Creative Works

To reduce the energy-intensity and carbon footprint of Portland cement (PC), the prevailing practice embraced by concrete technologists is to partially replace the PC in concrete with supplementary cementitious materials [SCMs: geological materials (e.g., limestone); industrial by-products (e.g., fly ash); and processed materials (e.g., calcined clay)]. Chemistry and content of the SCM profoundly affect PC hydration kinetics; which, in turn, dictates the evolutions of microstructure and properties of the [PC + SCM] binder. Owing to the substantial diversity in SCMs' compositions–plus the massive combinatorial spaces, and the highly nonlinear and mutually-interacting processes that arise from SCM-PC interactions–state-of-the-art computational models are …

Hamilton’S Geoacoustic Model, Charles W. Holland, Stan E. Dosso

Electrical and Computer Engineering Faculty Publications and Presentations

Hamilton’s classic 1980 paper² formulated the modern concept of a seabed geoacoustic model, drawing on extensive literature to com- pile and synthesize information on seabed properties. Hamilton defined a geoacoustic model as a “model of the real seafloor with emphasis on measured, extrapolated, and predicted values of those properties important in underwater acoustics” that includes “the true thicknesses and properties of sediment and rock layers.” His work provided both the framework for predicting geoacoustic properties and the data to support it.

Hamilton complied geoacoustic information from diverse sources, including laboratory measurements, in situ probes, samples and cores, echo-sounder records, …

Module 01: Introduction To Architectural Cad, Keith Johnson, Mohammad Moin Uddin

ENTC 2160: Architectural CAD

No abstract provided.

Module 05: Plumbing Plans, Keith Johnson, Mohammad Moin Uddin

ENTC 2160: Architectural CAD

No abstract provided.

Module 03a: Floor Plan Intro, Keith Johnson, Mohammad Moin Uddin

ENTC 2160: Architectural CAD

No abstract provided.

Module 07: Wall Sections, Keith Johnson, Mohammad Moin Uddin

ENTC 2160: Architectural CAD

No abstract provided.

Module 03b: Detail Floor Plan Layout, Keith Johnson, Mohammad Moin Uddin

ENTC 2160: Architectural CAD

No abstract provided.

Module 04: Electrical Plans, Keith Johnson, Mohammad Moin Uddin

ENTC 2160: Architectural CAD

No abstract provided.

Module 08: Roof Plans, Keith Johnson, Mohammad Moin Uddin

ENTC 2160: Architectural CAD

No abstract provided.

Module 09: Site Plan, Keith Johnson, Mohammad Moin Uddin

ENTC 2160: Architectural CAD

No abstract provided.

Module 02: Residential Design, Keith Johnson, Mohammad Moin Uddin

ENTC 2160: Architectural CAD

No abstract provided.

Module 03c: Dimensioning, Keith Johnson, Mohammad Moin Uddin

ENTC 2160: Architectural CAD

No abstract provided.

A Trusted Platform For Unmanned Aerial Vehicle-Based Bridge Inspection Management System, Hwapyeong Song

Theses, Dissertations and Capstones

Bridge inspection has a pivotal role in assuring the safety of critical structures constituting society. However, high cost, worker safety, and low objectivity of quality are classic problems in traditional visual inspection. Recent trends in bridge inspection have led to a proliferation of research utilizing Unmanned Aerial Vehicles (UAVs). This thesis proposes a Trusted Platform for Bridge Inspection Management System (Trusted-BIMS) for safe and efficient bridge inspection by proving the UAV-based inspection process and improving the prototype of the previous study. Designed based on a Zero-Trust (ZT) strategy, Trusted-BIMS consist of (1) a database-driven web framework with security features for …

Enhanced Study Of Complex Systems By Unveiling Hidden Symmetries With Dynamical Visibility, Nhat Vu Minh Nguyen

2022 Symposium

One of the great challenges in complex and chaotic dynamics is to reveal its deterministic structures. These temporal dynamical structures are sometimes a consequence of hidden symmetries. Detecting and understanding them can allow the study of complex systems even without knowing the full underlying mathematical description of the system. Here we introduce a new technique, called Dynamical Visibility, that quantifies temporal correlations of the dynamics based upon some symmetry conditions. This visibility measures the departure of the dynamics from internal symmetries. We apply this technique to well-known chaotic systems, such as the logistic map and the circle map, as well …

Performance Of Xor Rule For Decentralized Detection Of Deterministic Signals In Bivariate Gaussian Noise, Xingjian Sun, Shailee Yagnik, Ramanarayanan Viswanathan, Lei Cao

Faculty and Student Publications

In this paper, we consider the performance of exclusive-OR (XOR) rule in detecting the presence or absence of a deterministic signal in bivariate Gaussian noise. Signals, when present at the two sensors, are assumed unequal, whereas the noise components have identical marginal distribution but are correlated. The sensors send their one-bit quantized data to a fusion center, which then employs the XOR rule to arrive at the final decision. Here we prove that, in the limit as the correlation coefficient r approaches 1, the optimum fusion rule for both parallel and tandem topologies is XOR with identical, alternating partitions (XORAP) …

Design, Analysis, And Application Of Flipped Product Chaotic System, Md Sakib Hasan, Partha Sarathi Paul, Anurag Dhungel, Maisha Sadia, Md Razuan Hossain

Faculty and Student Publications

In this paper, a novel method is proposed to build an improved 1-D discrete chaotic map called flipped product chaotic system (FPCS) by multiplying the output of one map with the output of a vertically flipped second map. Two variants, each with nine combinations, are shown with trade-off between computational cost and performance. The chaotic properties are explored using the bifurcation diagram, Lyapunov exponent, Kolmogorov entropy, and correlation coefficient. The proposed schemes offer a wider chaotic range and improved chaotic performance compared to the constituent maps and several prior works of similar nature. Wide chaotic window and improved chaotic complexity …

Cascading Cmos-Based Chaotic Maps For Improved Performance And Its Application In Efficient Rng Design, Partha Sarathi Paul, Maisha Sadia, Md Razuan Hossain, Barry Muldrey, Md Sakib Hasan

Faculty and Student Publications

We present a general framework for improving the chaotic properties of CMOS-based chaotic maps by cascading multiple maps in series. Along with two novel chaotic map topologies, we present the 45 $nm$ designs for four CMOS-based discrete-time chaotic map topologies. With the help of the bifurcation plot and three established entropy measures, namely, Lyapunov exponent, Kolmogorov entropy, and correlation coefficient, we present an extensive chaotic performance analysis on eight unique map circuits (two under each topology) to show that under certain constraints, the cascading scheme can significantly elevate the chaotic performance. The improved chaotic entropy benefits many security applications and …

Direct Femtosecond Laser Inscription Of High-Order Bragg Gratings In Fluoroaluminate Glass Fiber, Lin She, Niannian Xu, Pengfei Wang, Jiquan Zhang, Mo Liu, Nian Lv, Ruoning Wang, Zhenrui Li, Shijie Jia, Shunbin Wang, Gerald Farrell, Weimin Sun

Articles

This letter reports the fabrication of fiber Bragg gratings (FBGs) within in-house fabricated fluoroaluminate (AlF3) glass fibers using femtosecond (fs) laser inscription at 800 nm. The grating strength of the FBGs was investigated for different pulse energies and different orders, and a 3rd-order FBG with Bragg wavelength at 1557 nm was found to have the highest reflectivity of 99.5%. In addition, the reflectivity of the mid-IR grating peaks for different orders was also studied, and a 2nd-order FBG with a reflectivity of 98.8% was obtained at 2864 nm. Finally, the temperature characteristics of a mid-IR FBG were studied between 30 …

Recent Advances In Luminescence And Lasing Research In Zbya Glass, Changjun Xu, Jiquan Zhang, Mo Liu, Haiyan Zhao, Fengzi Ling, Shijie Jia, Gerald Farrell, Shunbin Wang, Pengfei Wang

Articles

In the last few decades, fluoride glasses have attracted a growing interest due to their unique advantages compared to multi-component oxide glasses. Among them, the most studied and widely used were fluorozirconate glasses, represented by ZrF4–BaF2–LaF3–AlF3–NaF (ZBLAN) glasses. However, compared with ZBLAN glasses, a kind of fluorozirconate glass with the components ZrF4–BaF2–YF3–AlF3 (ZBYA) has higher thermal and chemical stability. In this paper, we first introduce the advantages of ZBYA glasses compared to ZBLAN glasses. Then we review and discuss recent advances in research on luminescence and lasing in ZBYA glass and fiber. These studies suggest that ZBYA glass has strong …

Data-Enabled Distribution Grid Management, Zohreh Sadat Hosseini

Electronic Theses and Dissertations

In 2020, U.S. electric utilities installed more than 94 million advanced meters, which brought the percentage of residential customers equipped with smart meters to 75%. This significant investment allows collecting extensive customer data at the distribution level, however, the data are not currently leveraged effectively to help with system operations. This dissertation aims to use the smart meters’ data to improve the grid’s reliability, stability, and controllability by solving two of the most challenging problems at the distribution level, namely distribution network phase identification and outage identification.

Distribution networks have typically been the least observable and most dynamic and locally …