Digital Commons Network^™

Production Box Cost Estimating Relationships For Dod Avionics, Carla J. Cisneros, Edward D. White, Brandon M. Lucas, Jonathan D. Ritschel, Robert D. Fass, Shawn M. Valentine

Faculty Publications

The authors use historical information obtained from the Cost Assessment Data Enterprise to estimate recurring production unit cost for DoD avionics via cost estimating relationships (CERs). The specific modeled responses include mean unit cost, median unit cost, and the 100th production unit cost (T100) utilizing learning curve theory. For T100, the authors adopt both a multiplicative and an additive error for CER comparison. Recommended CERs consist of the mean unit cost and the T100 utilizing a multiplicative error. Moreover, results reveal that weight has a significant effect on cost as well as a potential underaccounting of real price change or …

Real-Time Synthesis Of A Nonuniformly Correlated, Partially Coherent Beam Using An Optical Coordinate Tansformation, Milo W. Hyde Iv

Faculty Publications

We design, build, and validate an optical system for generating light beams with complex spatial coherence properties in real time. Beams of this type self-focus and are resistant to turbulence degradation, making them potentially useful in applications such as optical communications. We begin with a general theoretical analysis of our proposed design. Our approach starts by generating a Schell-model (uniformly correlated or shift-invariant) source by spatially filtering incoherent light. We then pass this light through an optical coordinate transformer, which converts the Schell-model source into a nonuniformly correlated field. After the general analysis, we discuss system engineering, including trade-offs among …

Design Of An Above Pavement Wireless Sensor Node (Apwsn) For Real-Time Roadway Monitoring Using Piezoelectric Energy-Harvesting, Jochy Jonathan Perez

Theses and Dissertations

The evolution of Smart Highway and Internet of Things (IoT) technologies offers new opportunities to improve the safety and efficiency of vehicular traffic on roads. This research effort describes the development of a wireless pavement sensor that provides a novel method to detect key pavement parameters while incorporating low-power energy harvesting that leverages the kinetic energy generated by vehicular traffic. The Above Pavement Wireless Sensor Node (APWSN) is the embodiment of the approach. APWSN can facilitate the strategic deployment of sensors on a wide variety of roads to enable real-time data collection to support decision-making processes for road infrastructure maintenance …

Electronic Communication Between Co And Ru Sites Decorated On Nitrogen-Doped Carbon Nanotubes Boost The Alkaline Hydrogen Evolution Reaction, Meng-Ting Gao, Ying Wei, Xue-Meng Hu, Wenj-Jie Zhu, Qing-Qing Liu, Jin-Yuan Qiang, Wan-Wan Liu, Ying Wang, Xu Li, Jian-Feng Huang, Yong-Qiang Feng

Journal of Electrochemistry

Designing highly efficient Pt-free electrocatalysts with low overpotential for an alkaline hydrogen evolution reaction (HER) remains a significant challenge. Here, a novel and efficient cobalt (Co), ruthenium (Ru) bimetallic electrocatalyst composed of CoRu nanoalloy decorated on the N-doped carbon nanotubes (CoRu@N-CNTs), was prepared by reacting fullerenol with melamine via hydrothermal treatment and followed by pyrolysis. Benefiting from the electronic communication between Co and Ru sites, the as-obtained CoRu@N-CNTs catalyst exhibited superior electrocatalytic HER activity. To deliver a current density of 10 mA·cm^–2, it required an overpotential of merely 19 mV along with a Tafel slope of 26.19 mV·dec …

Mention Detection In Turkish Coreference Resolution, Şeni̇z Demi̇r, Hani̇fi̇ İbrahi̇m Akdağ

Turkish Journal of Electrical Engineering and Computer Sciences

A crucial step in understanding natural language is detecting mentions that refer to real-world entities in a text and correctly identifying their boundaries. Mention detection is commonly considered a preprocessing step in coreference resolution which is shown to be helpful in several language processing applications such as machine translation and text summarization. Despite recent efforts on Turkish coreference resolution, no standalone neural solution to mention detection has been proposed yet. In this article, we present two models designed for detecting Turkish mentions by using feed-forward neural networks. Both models extract all spans up to a fixed length from input text …

A Single Operational Amplifier-Based Grounded Meminductor Mutators And Their Applications, Shalini Gupta, Kunwar Singh, Shireesh Kumar Rai

Turkish Journal of Electrical Engineering and Computer Sciences

In this work, three simple configurations of meminductor mutator are presented. The first two configurations of meminductor mutator have been implemented utilizing one CMOS-based operational amplifier, one memristor, one capacitor, and five resistors, while the third configuration of meminductor mutator is implemented utilizing one CMOS based operational amplifier, two memristors, one capacitor, and four resistors. The implementation and simulation of the proposed configurations are done by using LTspice tool. The viability of the proposed circuits is demonstrated by utilizing TSMC 180 nm CMOS technology parameters. The proposed circuits of the meminductor have a simple structure in contrast to many of …

Exploring Social Networks: An Analysis Of Intra-Organizational Networks, Ximeng Chen, Yiding Cao, Jiachen Liu, Danushka Bandara, Hiroki Sayama

Northeast Journal of Complex Systems (NEJCS)

This research investigates intra-organizational social networks by employing network science methods, aiming to provide actionable insights for both managers and employees. Using datasets from the Colorado Index of Complex Networks (ICON), this study examines four intra-organizational networks from a consulting firm and a research team, focusing on advice requests and skill awareness. The analysis includes network topology, degree distribution, community detection, correlation between communities and node attributes, maximal clique detection, and multilayer network analysis. The findings reveal that intra-organizational networks are intricate and significantly impact organizational efficiency and individual career development. Key insights include the importance of mid-level employees in …

Multiple-Point Metamaterial-Inspired Microwave Sensors For Early-Stage Brain Tumor Diagnosis, Nantakan Wongkasem, Gabriel Cabrera

Electrical and Computer Engineering Faculty Publications

Simple, instantaneous, contactless, multiple-point metamaterial-inspired microwave sensors, composed of multi-band, low-profile metamaterial-inspired antennas, were developed to detect and identify meningioma tumors, the most common primary brain tumors. Based on a typical meningioma tumor size of 5-20 mm, a higher operating frequency, where the wavelength is similar or smaller than the tumor target, is crucial. The sensors, designed for the microwave Ku band range (12-18 GHz), where the electromagnetic property values of tumors are available, were implemented in this study. A seven-layered head phantom, including the meningioma tumors, was defined using actual electromagnetic parametric values in the frequency range of interest …

Review Of Hardware Implementation For The Two-Wheeled Self-Balancing Robot, Ghaidaa Hadi Salih Elias

Al-Bahir

The working principle of a self-balancing robot is similar to that of an inverted pendulum, with the mobile robot's controller playing a crucial part in both self-balancing and stabilization. It is the kind that constantly modifies itself to keep balance when it rides on two wheels. This review will center on the basic construction of the suggested robot, summarize the recent studies relative to control methods and the building of the two-wheeled self-balancing robot, and discuss the outcomes of control experiments conducted on hardware systems. It will assist researchers in building and designing two-wheeled mobile robots in the future.

Advanced Transistor-Based Dynamic Equivalent Circuit Modeling Of Mesostructured-Based Solar Cells, Eman Farouk Sawires, Sameh O. Abdellatif

Electrical Engineering

This study introduces a pioneering transistor-based equivalent circuit model explicitly tailored for mesostructured-based solar cells, primarily focusing on dye-sensitized solar cells (DSSCs) and perovskite solar cells (PSCs). By incorporating the experimental data spanning various inorganic, organic, and hybrid solar cell technologies across different optical injection levels, the model aims to provide a comprehensive understanding of the electrical behavior of these advanced photovoltaic devices. In addition to the circuit schematic, a Verilog-A script was created to elucidate the behavior of the cells, facilitating the utilization of such a block by the research community in developing interfacing circuits and implementing dc–dc converters …

Flexible Load Conformance: A Work-In-Progress White Paper, Dana Paresa, Robert B. Bass

Electrical and Computer Engineering Faculty Publications and Presentations

Utilities have used residential loads for providing grid services to utility customers for decades, particularly for demand response. However, the number of customers participating in such programs remains low. New Flexible Load Management strategies for providing grid services have the potential to accelerate customer participation. Efforts to improve customer participation and experience will result in increased load balancing capacity of demand response, which will benefit both customers and electric utilities. This white paper investigates whether current smart grid devices (specifically water heaters) can provide needed services while meeting ANSI/CTA-2045 standard requirements.

High-Frequency-Based Transmission Line Percentage Differential Protection With Traveling Wave Alignment, Igor F. Prado, Flavio Costa, Kleber M. Silva, Rodrigo P. Medeiros, Bruce A. Mork

Michigan Tech Publications

This paper presents a wavelet-based differential protection algorithm for transmission lines. It uses restraint and operating components obtained with high-frequency components of a few kHz from instantaneous energy values of the real-time boundary stationary wavelet transform instead of low-frequency components from phasor estimation. It does not require capacitive current suppression as well. Therefore, the proposed method overcomes the limitations of conventional percentage differential protection. Furthermore, the proposed technique uses traveling wave theory to perform the current sample alignment at a few kHz, thereby, not requiring the global positioning system (GPS). The performance of the proposed method is evaluated through extensive …

Lyapunov-Based Cyberattack Detection For Distinguishing Between Sensor And Actuator Attacks, Dominic Messina, Helen E. Durand

Chemical Engineering and Materials Science Faculty Research Publications

Control-theoretic cyberattack detection strategies are control strategies where control theory can be used in the design of the detection policies and analysis of stability properties with and without cyberattacks. This work provides a step toward understanding how to diagnose cyberattacks using control-theoretic cyberattack detection mechanisms. Specifically, we analyze the conditions under which a control-theoretic cyberattack detection strategy developed in our prior work to handle detection of simultaneous actuator and sensor attacks can be extended to distinguish between whether attacks are occurring on sensors or actuators. We present and evaluate heuristic concepts for attempting to diagnose sensor attacks; these again demonstrate …

Low-Power Sensor Design And Fusion To Edge Devices For High-Speed Object Detection And Enhanced Soldier Situational Awareness, Scott Patrick Wood

Theses and Dissertations

Threat detection and physiological monitoring of soldiers from fused sensor data collected in real time is currently limited to running deep neural networks with substantial computing needs. The lack of data acquisition from sensor readings and efficient detection of novel enemy signatures motivates the need for a low-power, low-cost, wireless multisensor fusion computing system. We propose the current trends in Internet of Things to deploy a chargeable, wireless multi-channel acquisition system that can be interfaced to a high speed, Single Board Computer (SBC) such as the NVIDIA Jetson Orin capable of running object detection models, such as YOLOv7-tiny to enable …

Utilizing Deep Learning In Smart Glass System To Assist The Blind And Visually Impaired, Asmaa A. Hekal, Mohamed S. Sharaf, Ahmed A. Sayed, Ibrahim R. Abdelrahman, Ahmed A. Salem, Ahmed M. Elhussieny, Saeed Y. Kouta, Eman S. Abass

Future Engineering Journal

This paper presents a groundbreaking assistive technology designed to empower visually impaired individuals in their daily lives. With an estimated global population of 2.2 billion facing visual impairments, addressing the challenges they encounter is of paramount importance. The research introduces a comprehensive electronic device integrating advanced computer vision and deep learning techniques. The system incorporates real-time object detection, robust facial recognition, and precise currency denomination identification. Powered by a Raspberry Pi 4 Model B+ and an ESP32-CAM Development Board, the device offers users unparalleled environmental awareness. Utilizing YOLOv4-tiny for object detection and a hybrid face recognition model combining HaarCascades, Histogram …

Scene Decomposed Blind Deconvolution And Neural Network Based Multi-Frame Image Restoration Techniques For Astronomical Imagery, Joshua S. Sprang

Theses and Dissertations

Ground based astronomical imaging is an important method in gaining situational awareness of orbiting and far off objects in space. This method of imaging is accessible to everyone that can look up into the sky, but the accessibility to digital telescope systems allows for more exciting methods of extracting information. A use case for these telescopes is finding nearby objects to larger brighter known objects. The number satellites in low-earth orbit and geosynchronous earth orbit is becoming more congested as these orbits increase in population. Tens of thousands of satellites and debris now exist in this orbit, with the number …

An Analysis Of Electrical Energy Resilience Technologies As Applied To Air Force Operations, Eric D. Danko

Theses and Dissertations

An analysis of 46 Resilient Energy Devices and Technology Concepts was conducted to determine their suitability for use in supporting Air Force Operations both at home station and abroad. The research consisted of two endeavors: an extensive literature review and a rank-ordering matrix. The dual nature of the efforts was designed to maximize usability and understanding for the End User, who may not be familiar with some principles of energy technologies, resilience, or design. The results showed the superiority of novel Solid (Metal) Fuels and Lead-Acid Batteries for Energy Storage and Thermoelectric Generators, Solar Photovoltaic Panels, Geothermal Extraction, Diesel Generators, …

Design And Implementation Of An Inverted Short Baseline Acoustic Positioning System, Jakob Frabosilio

Master's Theses

This document details the design, implementation, testing, and analysis of an inverted short baseline acoustic positioning system. The system presented here is an above-water, air-based prototype for an underwater acoustic positioning system; it is designed to determine the position of remotely-operated underwater vehicles (ROVs) and autonomous underwater vehicles (AUVs) in the global frame using a method that does not drift over time.

A ground-truth positioning system is constructed using a stacked hexapod platform actuator, which mimics the motion of an AUV and provides the true position of an ultrasonic microphone array. An ultrasonic transmitter sends a pulse of sound towards …

Gamifying Energy Management: Leveraging Lokalytica Smartmeter For Sustainable Future, Emilio Roman Perez, King Harold A. Recto

Electronics, Computer, and Communications Engineering Faculty Publications

The gamification of software applications has emerged as an effective strategy to enhance user engagement and promote desired behaviors. This paper explores the gamification of the Lokalytica SmartMeter application, an energy management platform that leverages data from meter readings through its users. By incorporating a challenge-based system and a points-based leaderboard, Lokalytica rewards users who reduce their energy consumption. The gamification application of Lokalytica was built using NextJS, a full-stack framework, along with Tailwind CSS and DaisyUI for UI design, MongoDB Atlas for the database, and GitHub for version control, collaboration, and tracking. This paper discusses the development process, the …

Two-Dimensional Quantum Material Identification Via Self-Attention And Soft-Labeling In Deep Learning, Xuan Bac Nguyen, Apoorva Bisht, Benjamin Thompson, Hugh O.H. Churchill, Khoa Luu, Samee U. Khan

Electrical Engineering and Computer Science Faculty Publications and Presentations

Detecting two-dimensional (2D) materials in silicon chips presents a significant challenge in the field of quantum machines due to the difficulty of data collection. Specifically, among thousands of flakes, not all flakes are useful or well-annotated, resulting in noisy and hard samples within the dataset, which challenges the deep neural network (DNN) to learn. To address this problem, we propose a novel method for identifying quantum 2D flakes even when there is a high rate of missing annotations in the input images. In particular, we first propose a new mechanism for automatically detecting false negative flakes that are missing annotations. …

Paper-Recorded Ecg Digitization Method With Automatic Reference Voltage Selection For Telemonitoring And Diagnosis, Liang Hung Wang, Chao Xin Xie, Tao Yang, Hong Xin Tan, Ming Hui Fan, I. Chun Kuo, Zne Jung Lee, Tsung Yi Chen, Pao Cheng Huang, Shih Lun Chen, Patricia Angela R. Abu

Department of Information Systems & Computer Science Faculty Publications

In electrocardiograms (ECGs), multiple forms of encryption and preservation formats create difficulties for data sharing and retrospective disease analysis. Additionally, photography and storage using mobile devices are convenient, but the images acquired contain different noise interferences. To address this problem, a suite of novel methodologies was proposed for converting paper-recorded ECGs into digital data. Firstly, this study ingeniously removed gridlines by utilizing the Hue Saturation Value (HSV) spatial properties of ECGs. Moreover, this study introduced an innovative adaptive local thresholding method with high robustness for foreground–background separation. Subsequently, an algorithm for the automatic recognition of calibration square waves was proposed …

Design Frameworks For Ventilative Cooling: Perceptions From Building Design Practitioners In Ireland And The United Kingdom, Maha Sohail, Adam O'Donovan, Paul D. O'Sullivan

Publications

The global increase in building cooling demands poses a challenge for designers striving for net zero energy consumption. The prevalent use of mechanical cooling underscores the necessity for designers to consider Ventilative Cooling as a viable alternative in the early stages of building design. This paper presents findings from an exploratory survey and semi-structured interviews of industry experts in Ireland and the United Kingdom about their design processes and experienced-based approaches to designing Ventilative Cooling. The findings suggest that the pre-design stage has the same influence for promoting ventilative cooling strategies as the schematic and detailed design stages for practitioners, …

Performance Evaluation And Integration Of Distortion Mitigation Methods For Fisheye Video Object Detection, John Benedict Du, Gian Paolo Mayuga, Maria Leonora Guico

Electronics, Computer, and Communications Engineering Faculty Publications

The distortion observed in fisheye cameras has proven to be a persistent challenge for numerous state-of-the-art object detection algorithms, instigating the development of various techniques aimed at mitigating this issue. This study aims to evaluate various methods for mitigating distortion in fisheye camera footage and their impact on video object detection accuracy and speed. Using Python, OpenCV, and third-party libraries, the researchers modified and optimized said methods for video input and created a framework for running and testing different distortion correction methods and object detection algorithm configurations. Through experimentation with different datasets, the study found that undistorting the image using …

Machine Visual Perception For Autonomous Docking Maneuvers, Derek B. Worth

Theses and Dissertations

This dissertation presents a novel approach to autonomous docking using machine learning for visual perception, particularly during probe and drogue aerial refueling. Autonomous vehicles have become pervasive in both civilian and defense sectors, and their ability to interact with their surroundings and each other autonomously is critical for future operations. Traditional methods relying on signals or inertial sensors face significant limitations such as interference, jamming, and drift. This research focuses on developing a computer vision-based solution to overcome these limitations. A novel pipeline, termed relative vectoring, is introduced, which utilizes dual object detection and machine learning to estimate relative positions …

Deep Learning Technique For The Classification Of Stress Among The Students Using Physiological Biomarkers With A Hybrid Feature Approach, Rajendran Vg

Theses and Dissertations

Adolescence is a crucial part in life, and the presence of stress, anxiety, depression, and health issues during this stage is a great concern. This research aims to analyze and predict the cognitive stress in students during the examination period using EEG biomarkers. In this study, raw EEG data is acquired under two different experimental conditions, before and after examination, from 14 subjects with an eight-channel Enobio device. After preprocessing of the EEG signal, the brain rhythms such as theta, alpha, and beta sub-band energies and EEG band ratios such as neural activity, heart rate, arousal index, vigilance index and …

Remote Sensing Assessment Of Ionospheric Total Electron Content Over Thanjavur Gps Station Geomagnetic 2.91 N 152.22 E, Veera Kumar Maheswaran

Theses and Dissertations

A Global Positioning System (GPS) station for ionosphere studies was established during December 2019 in Thanjavur (Geographic 10.72◦ E, 79.01◦ N, Geomagnetic 2.91◦ N, 152.22◦ E). The study involved analysing Total Electron Content (TEC) data and correcting biases to estimate Slant Total Electron Content (STEC). STEC was then converted to Vertical Total Electron Content (VTEC), useful for space weather, navigation, surveying, and environmental monitoring.

During the course of our study, this Thanjavur station witnessed a Annular Solar eclipse of Dec-26, 2019. The Solar eclipses can impact ionospheric conditions, causing VTEC depletion. This study shows how the near-earth environment changes during …

Clustering Algorithm Based On Similarity Of Objects, Akhram Khasanovich Nishanov, Alisher Tulkunovich Tursunov, Fayzullo Farhod O'G'Li Ollamberganov

Chemical Technology, Control and Management

The article discusses the problem of drug clustering. Initially, k classes are randomly formed and the resulting training sample is preprocessed, then the similarity between objects of each class is assessed based on the proximity function and the criterion for assessing the contribution of objects to the formation of their own class. It is usually expressed as a percentage and represents the degree of mutual similarity of objects of each class. In the next steps of the algorithm, first one object is taken from the first class and by adding it to all k classes, the contribution of this object …

Developing Decision-Making Models And Algorithms To Help Prevent Emergencies, Mizaakbar Xakkulmirzayevich Hudayberdiyev, Oybek Zokirovich Koraboshev

Chemical Technology, Control and Management

The article is devoted to the solution of the scientific issue of decision-making support for the prevention and elimination of the consequences of emergency situations. The relevance of this issue is related to the need to develop a theoretical basis for optimizing the risk of adverse effects on human health and the environment in connection with emergency situations, and a predictive model for the development of emergency situations and their prevention or elimination of their consequences. The optimization of the importance measure of signs for predicting the values of the factors of fire conditions has been carried out. In addition, …

Scla 521 Ai In Society, Bert Chapman

Libraries Faculty and Staff Presentations

Provides access to information resources on societal impacts of artificial intelligence from multiple libraries databases covering multiple disciplines including government information resources.

Fpca-Setcn: A Novel Deep Learning Framework For Remaining Useful Life Prediction, Junde Chen, Yuxin Wen, Xuxue Sun, Adnan Zeb, Mohammad Saleh Meiabadi, Sasan Sattarpanah Karganroudi

Engineering Faculty Articles and Research

The accurate prediction of remaining useful life (RUL) can serve as a reliable foundation for equipment maintenance, thereby effectively reducing the incidence of failure and maintenance costs. In this study, a novel deep learning (DL) framework that incorporates functional principal component analysis (FPCA) and enhanced temporal convolutional network (TCN) is proposed for RUL prediction. Precisely, FPCA is employed to capture the changing patterns in multistream degradation trajectories. Subsequently, the reconstructed signals from FPCA are fed into a convolutional block for extracting deep-level features. An enhanced squeeze-and-excitation (ESE) block is then incorporated into the network for adaptive feature recalibration, enhancing the …