Digital Commons Network^™

A High-Precision Electron Emission Model: Computational Methods For Nanoscale Structures, Alister J. Tencate

Graduate Research Theses & Dissertations

The high-intensity, high-brightness and precision frontiers for charged particle beams are an increasingly important focus for study. Electron microscopy has demonstrated high quality beams from a single nanotip emitter, and cathodes of structured nanoscale arrays show promise as ultracold electron sources. Optimization of the cathode design for precision applications necessitates a detailed treatment of the interplay between the structure geometry, quantum mechanical emission mechanism, and electromagnetic interactions between the emitted electrons and the boundary interface. This dissertation details the numerical tools developed to simulate these processes efficiently with enough fidelity to be accurate even in the ultracold regime.

Conventional simulation …

Analysis Of Localization Algorithms For Wireless Sensor Networks Using Binary Data, Alexander Joseph Hart

Graduate Research Theses & Dissertations

The detection, localization, and tracking of environmental and physical conditions can be accomplished using wireless sensor networks (WSNs). Recent advancements in sensors, processors, and wireless communications have improved the quality and acquisition speed of data in WSNs. However, the data gathered by a WSN is inherently random due to component and environmental variations. Thus, statistical signal processing algorithms are needed to analyze the random data in a robust way. Though many algorithms for the analysis of random data are established and available, they are problem-specific and must be adapted to the application. This thesis provides an analysis of established localization …

Spherical Modes Driven Directional Modulation With A Compact Mimo Antenna, Abel Zamdemala, Nicola Marchetti, Max Ammann, Adam Narbudowicz

Articles

In this letter, a compact beamsteering MIMO antenna is proposed for Directional Modulation (DM) applications. A generalization of the beamsteering principle is presented and by exploiting the antenna’s unidirectional beamsteering capability within the entire azimuth plane, the system realizes secure steerable transmissions in the direction of the legitimate receiver, with a low Bit Error Rate (BER) of 10^(-5), while a high error rate of 10^(-1) is seen outside the desired regions. Numerical and experimental verifications are carried out to validate the proposed concept and comparisons with circular arrays are conducted, revealing that the system achieves comparable performance but with up …

Technical And Economic Feasibility Of A Microgrid For A Fire Station In Humboldt County, California., Nishaant Kumar Sinha

Cal Poly Humboldt theses and projects

Microgrids are emerging as a promising solution to unreliable grid energy. Today, California is not only witnessing grid resiliency challenges from natural disasters such as wildfires, earthquakes, floods and heatwaves, but it is also seeking to green the grid and bring more renewables online. For example, Humboldt County, where this project is focused, has recently experienced an earthquake of 6.4M (on December 22nd, 2022), which shut down the regional grid for ~20 hours.

Microgrid adoption enables critical facilities to operate seamlessly. The Humboldt Bay Fire Station (HBFS) No.1 is one such example, where first responders work to protect citizens against …

The Troubling Emergence Of Hallucination In Large Language Models--An Extensive Definition, Quantification, And Prescriptive Remediations, Vipula Rawte, Swagata Chakraborty, Agnibh Pathak, Anubhav Sarkar, S.M Towhidul Islam Tonmoy, Aman Chadha, Amit Sheth, Amitava Das

Publications

The recent advancements in Large Language Models (LLMs) have garnered widespread acclaim for their remarkable emerging capabilities. However, the issue of hallucination has parallelly emerged as a by-product, posing significant concerns. While some recent endeavors have been made to identify and mitigate different types of hallucination, there has been a limited emphasis on the nuanced categorization of hallucination and associated mitigation methods. To address this gap, we offer a finegrained discourse on profiling hallucination based on its degree, orientation, and category, along with offering strategies for alleviation. As such, we define two overarching orientations of hallucination: (i) factual mirage (FM) …

Programming A Texas Instruments Microcontroller Unit (Mcu) For A Single Stage Buck/Boost Power Converter, John Yang

Maseeh Summer Undergraduate Research Experience

A power converter allows DC to be converted to AC voltage. The power converter used for this project has two MOSFETs per phase and contains inherent filters. The gate driver control signals are sinusoidally pulse-width modulated (PWM) to generate AC output waveforms. The primary goal was to replace the Arduino with a Texas Instruments 280049 MCU. An in-house designed controller board, named Mobo, seats a TI microcontroller board and provides PWM outputs via USB. The TI 280049 MCU is capable of replacing the Arduino for power electronic applications. Due to asynchronized PWM signals, A new Mobo will need to designed …

A Novel Unidirectional Smart Charging Management Algorithm For Electric Buses, Nicolae Darii, Roberto Turri, Keith Sunderland, Fabio Bignucolo

Articles

The difficulty of controlling the charging of electric buses (EBs) and their effects on network demand are discussed in this study. The solutions suggest a call for worldwide, complex infrastructures that manage EVs and EBs equally. Additionally, the Distribution Network (DN) must be prepared for an increased prevalence of reverse power flow caused by widespread distributed renewable generation. This paper focuses exclusively on EBs since they have higher capacity and predictable charging patterns, which makes them more significant for the DN in the context of a transition to complete vehicle electrification and technologies that are mature enough to be hosted. …

Embedded Ai For Wheat Yellow Rust Infection Type Classification, Uferah Shafi, Rafia Mumtaz, Muhammad Deedahwar Mazhar Qureshi, Zahid Mahmood, Sikander Khan Tanveer, Ihsan Ul Haq, Syed Mohammad Hassan Zaidi

Articles

Wheat is the most important and dominating crop in Pakistan in terms of production and acreage, which is grown on 37% of the cultivated area, accounting for 70% of the total production. However, wheat yield is highly affected by stripe rust, which is considered the most devastating fungal disease, causing 5.5 million tonnes of loss per year globally. In order to minimize this loss, the accurate and timely detection of rust disease is crucial instead of manual inspection. Towards this end, we propose a system to detect wheat rust disease and classify its infection types into four classes, including healthy, …

Control And Protection Of Mmc-Based Hvdc Systems: A Review, Rashid Hussain Chandio, Faheem Akhtar Chachar, Jahangeer Badar Soomro, Jamshed Ahmed Ansari, Mudassir Munir Mudassir Munir, Hossam Zawbaa, Salah Kamel Salah Kamel

Articles

The voltage source converter (VSC) based HVDC (high voltage direct current system) offers the possibility to integrate other renewable energy sources (RES) into the electrical grid, and allows power flow reversal capability. These appealing features of VSC technology led to the further development of multi-terminal direct current (MTDC) systems. MTDC grids provide the possibility of interconnection between conventional power systems and other large-scale offshore sources like wind and solar systems. The modular multilevel converter (MMC) has become a popular technology in the development of the VSC-MTDC system due to its salient features such as modularity and scalability. Although, the employment …

Distributed Intermittent Fault Diagnosis In Wireless Sensor Network Using Likelihood Ratio Test, Bhabani Sankar Gouda, Meenakshi Panda, Trilochan Panigrahi, Sudhakar Das, Bhargav Appasani, Omprakash Acharya, Hossam Zawbaa, Salah Kamel

Articles

In current days, sensor nodes are deployed in hostile environments for various military and commercial applications. Sensor nodes are becoming faulty and having adverse effects in the network if they are not diagnosed and inform the fault status to other nodes. Fault diagnosis is difficult when the nodes behave faulty some times and provide good data at other times. The intermittent disturbances may be random or kind of spikes either in regular or irregular intervals. In literature, the fault diagnosis algorithms are based on statistical methods using repeated testing or machine learning. To avoid more complex and time consuming repeated …

Lightnet: A Novel Lightweight Convolutional Network For Brain Tumor Segmentation In Healthcare, Dongyuan Wu, Junyi Tao, Zhen Qin, Rao Asad Mumtaz, Jin Qin, Linfang Yu, Jane Courtney

Articles

Diagnosis, treatment planning, surveillance, and the monitoring of clinical trials for brain diseases all benefit greatly from neuroimaging-based tumor segmentation. Recently, Convolutional Neural Networks (CNNs) have demonstrated promising results in enhancing the efficiency of image-based brain tumor segmentation. Most current work on CNNs, however, is devoted to creating increasingly complicated convolution modules to improve performance, which in turn raises the computing cost of the model. This work proposes a simple and effective feed-forward CNN, LightNet (Light Network). Based on multi-path and multi-level, it replaces traditional convolutional methods with light operations, which reduces network parameters and redundant feature maps. In the …

Turbo Receivers For Multiple-Input Multiple-Output Underwater Acoustic Communications, Yahong Rosa Zheng, Weimin Duan, Chengshan Xiao

Patents

Aspects of the present disclosure include methods for communication using a MIMO channel, such as an acoustic channel for underwater communication. An acoustic receiver may receive a signal comprising information encoded in at least one transmitted symbol. Using a twolayer iterative process, the at least one transmitted symbol is estimated. The first layer of the two-layer process uses iterative exchanges of soft-decisions between an adaptive turbo equalizer and a MAP decoder. The second layer of the two-layer process uses a data-reuse procedure that adapts an equalizer vector of both a feedforward filter and a serial interference cancellation filter of the …

Setransformer: A Transformer-Based Code Semantic Parser For Code Comment Generation, Zheng Li, Yonghao Wu, Bin Peng, Xiang Chen, Zeyu Sun, Yong Liu, Paul Doyle

Conference Papers

Automated code comment generation technologies can help developers understand code intent, which can significantly reduce the cost of software maintenance and revision. The latest studies in this field mainly depend on deep neural networks, such as convolutional neural networks and recurrent neural network. However, these methods may not generate high-quality and readable code comments due to the long-term dependence problem, which means that the code blocks used to summarize information are far from each other. Owing to the long-term dependence problem, these methods forget the previous input data’s feature information during the training process. In this article, to solve the …

Detection Of Pause In A Pedestrian’S Movement On A Linear Walkway Using Bluetooth Low Energy Received Signal Strength Indicator, Mayank Parmar, Paula Kelly, Damon Berry

Conference papers

In recent years, Bluetooth Low Energy (BLE) has amassed significant attention in several applications. Its potential, however, remains largely unexplored for understanding pedestrian behaviour. This study focuses on investigating the potential of BLE in identifying pedestrian activity in an outdoor linear walkway. We specifically examine the likelihood of detecting pauses in the movement of pedestrians on a linear walkway using the strength of the signals obtained from a BLE device carried by the pedestrian. To accomplish this, a volunteer pedestrian intentionally pauses at selected points on the chosen walkway for varying predetermined intervals. The obtained data was conditioned using a …

Real-Time Air Gap And Thickness Measurement Of Continuous Caster Mold Flux By Extrinsic Fabry-Perot Interferometer, Abhishek Prakash Hungund, Hanok Tekle, Bohong Zhang, Ronald J. O'Malley, Jeffrey D. Smith, Rex E. Gerald, Jie Huang

Materials Science and Engineering Faculty Research & Creative Works

Mold Flux plays a critical role in continuous casting of steel. Along with many other functions, the mold flux in the gap between the solidifying steel shell and the mold serves as a medium for controlling heat transfer and as a barrier to prevent shell sticking to the mold. This manuscript introduces a novel method of monitoring the structural features of a mold flux film in real-time in a simulated mold gap. A 3-part stainless-steel mold was designed with a 2 mm, 4 mm and, 6 mm step profile to contain mold flux films of varying thickness. An Extrinsic Fabry-Perot …

Heart Disease Prediction Using Stacking Model With Balancing Techniques And Dimensionality Reduction, Ayesha Noor, Nadeem Javaid, Nabil Alrajeh, Babar Mansoor, Ali Khaqan, Safdar Hussain Bouk

School of Cybersecurity Faculty Publications

Heart disease is a serious worldwide health issue with wide-reaching effects. Since heart disease is one of the leading causes of mortality worldwide, early detection is crucial. Emerging technologies like Machine Learning (ML) are currently being actively used by the biomedical, healthcare, and health prediction industries. PaRSEL, a new stacking model is proposed in this research, that combines four classifiers, Passive Aggressive Classifier (PAC), Ridge Classifier (RC), Stochastic Gradient Descent Classifier (SGDC), and eXtreme Gradient Boosting (XGBoost), at the base layer, and LogitBoost is deployed for the final predictions at the meta layer. The imbalanced and irrelevant features in the …

Mwirgan: Unsupervised Visible-To Mwir Image Translation With Generative Adversarial Network, Mohammad Shahab Uddin, Chiman Kwan, Jiang Li

Electrical & Computer Engineering Faculty Publications

Unsupervised image-to-image translation techniques have been used in many applications, including visible-to-Long-Wave Infrared (visible-to-LWIR) image translation, but very few papers have explored visible-to-Mid-Wave Infrared (visible-to-MWIR) image translation. In this paper, we investigated unsupervised visible-to-MWIR image translation using generative adversarial networks (GANs). We proposed a new model named MWIRGAN for visible-to-MWIR image translation in a fully unsupervised manner. We utilized a perceptual loss to leverage shape identification and location changes of the objects in the translation. The experimental results showed that MWIRGAN was capable of visible-to-MWIR image translation while preserving the object’s shape with proper enhancement in the translated images and …

The Effect Of The Width Of The Incident Pulse To The Dielectric Transition Layer In The Scattering Of An Electromagnetic Pulse — A Qubit Lattice Algorithm Simulation, George Vahala, Linda Vahala, Abhay K. Ram, Min Soe

Electrical & Computer Engineering Faculty Publications

The effect of the thickness of the dielectric boundary layer that connects a material of refractive index n₁ to another of index n₂is considered for the propagation of an electromagnetic pulse. A qubit lattice algorithm (QLA), which consists of a specially chosen non-commuting sequence of collision and streaming operators acting on a basis set of qubits, is theoretically determined that recovers the Maxwell equations to second-order in a small parameter ϵ. For very thin boundary layer the scattering properties of the pulse mimics that found from the Fresnel jump conditions for a plane wave - except that …

Deep-Learning-Based Classification Of Digitally Modulated Signals Using Capsule Networks And Cyclic Cumulants, John A. Snoap, Dimitrie C. Popescu, James A. Latshaw, Chad M. Spooner

Electrical & Computer Engineering Faculty Publications

This paper presents a novel deep-learning (DL)-based approach for classifying digitally modulated signals, which involves the use of capsule networks (CAPs) together with the cyclic cumulant (CC) features of the signals. These were blindly estimated using cyclostationary signal processing (CSP) and were then input into the CAP for training and classification. The classification performance and the generalization abilities of the proposed approach were tested using two distinct datasets that contained the same types of digitally modulated signals, but had distinct generation parameters. The results showed that the classification of digitally modulated signals using CAPs and CCs proposed in the paper …

A Survey Of Using Machine Learning In Iot Security And The Challenges Faced By Researchers, Khawlah M. Harahsheh, Chung-Hao Chen

Electrical & Computer Engineering Faculty Publications

The Internet of Things (IoT) has become more popular in the last 15 years as it has significantly improved and gained control in multiple fields. We are nowadays surrounded by billions of IoT devices that directly integrate with our lives, some of them are at the center of our homes, and others control sensitive data such as military fields, healthcare, and datacenters, among others. This popularity makes factories and companies compete to produce and develop many types of those devices without caring about how secure they are. On the other hand, IoT is considered a good insecure environment for cyber …

An Adaptive Multiple-Object Tracking Architecture For Long-Duration Videos With Variable Target Density, Joachim Lohn-Jaramillo

Dartmouth College Ph.D Dissertations

Multiple-Object Tracking (MOT) methods are used to detect targets in individual video frames, e.g., vehicles, people, and other objects, and then record each unique target’s path over time. Current state-of-the-art approaches are extremely complex because most rely on extracting and comparing visual features at every frame to track each object. These approaches are geared toward high-difficulty-tracking scenarios, e.g., crowded airports, and require expensive dedicated hardware, e.g., Graphics Processing Units. In hardware-constrained applications, researchers are turning to older, less complex MOT methods, which reveals a serious scalability issue within the state-of-the-art. Crowded environments are a niche application for MOT, i.e., there …

Design Of Next-Generation Neural Interfaces For Decoding The Brain, Yi Qiang

Dartmouth College Ph.D Dissertations

The primary goal of neural interface technology is to establish a connection between the nervous system and the external world by recording and modulating neural signals. Over the past few decades, microelectrode array (MEA) technology has played an essential role in the acquisition of electrophysiological signals, with impressive progress being made towards developing high-density, large-throughput, and ultra-flexible MEAs. However, despite these advancements, there remain long-standing limitations in current neural interfaces. For example, electrophysiology is limited in its ability to distinguish cell types and has limited spatial resolution due to its electrical recording nature. Furthermore, conventional neural MEAs are limited to …

Advancing Vehicular Communication Systems: An Evolution From Dsrc To 5g Nr C-V2x Technology For Enhanced Safety, Reliability, And Efficiency In Intelligent Transportation Systems, Mehnaz Tabassum

Dissertations, Master's Theses and Master's Reports

This work focuses on the evolution of connected vehicles communication technologies and performance evaluation of vehicular communication systems, specifically in the context of Cellular Vehicle-to-Everything (C-V2X) technology and the Third Generation Partnership Project (3GPP) specifications. The dissertation also discusses the evolution of vehicle communication systems from Dedicated Short-Range Communication (DSRC) through 5G technologies. It examines the motivation for this shift, which are the growing demand for transportation safety, low latency, high data rate, low energy use, and seamless inter connectivity. The research delves into the greater capabilities and improved performance that 5G offers for direct V2V communications by analyzing the …

Wireless Environmental Weather Monitor, Joel Christie-Millett, Nathan Schroeder, Sylvester Wilson, Matthew Szijarto

Williams Honors College, Honors Research Projects

The goal of this senior design/honors project is to create a device that monitors environmental conditions in order to detect a wildfire. This device should notify a user of the status of the environment. The device should also last for 6 months without any human interaction. My role on the team is to design the power supply system that maximizes efficiency and uses renewable energy.

A Methodology For Predicting Improved Dipole Source Configurations From Near-Field Scan Data, Hossein Rezaei, Xin Yan, David J. Pommerenke, Daryl G. Beetner

Electrical and Computer Engineering Faculty Research & Creative Works

Equivalent sources found from near-electric and magnetic field scans are often used to predict and solve interference problems. While there are many ways to represent the source, the user lacks the ability to determine which of the many possible source configurations is more likely to represent the "true" source, and thus accurately represent field data outside the measurement area and in the presence of typical measurement errors. A methodology is proposed for estimating which of many possible dipole source representations of near-field scan data are likely to give better estimates of fields outside the measurement scan plane when utilizing imperfect …

Chemical Classification By Monitoring Liquid Evaporation Using Extrinsic Fabry-Perot Interferometer With Microwave Photonics, Abhishek Prakash Hungund, Bohong Zhang, Anand Nambisan, Wassana Naku, Rex E. Gerald, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

Identification of liquids is essential in chemical analysis, safety, environmental protection, quality control, and research. A novel liquid identification system based on Microwave Photonics (MWP) measured time transient evaporation signals is investigated. An extrinsic Fabry-Perot Interferometer (EFPI) based optical probe using single-mode fiber (SMF) is proposed to monitor evaporation of different liquids. The MWP system is used to measure the optical path changes during liquid evaporation due to its high sensitivity, selectivity, and Signal-to-Noise Ratio (SNR). The measured S21 continuous wave (CW) time Magnitude and Phase signals were processed to extract features such as histogram and Fast Fourier Transform (FFT) …

Filter-Based Fault Detection And Isolation In Distributed Parameter Systems Modeled By Parabolic Partial Differential Equations, Hasan Ferdowsi, Jia Cai, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

This paper covers model-based fault detection and isolation for linear and nonlinear distributed parameter systems (DPS). The first part mainly deals with actuator, sensor and state fault detection and isolation for a class of DPS represented by a set of coupled linear partial differential equations (PDE). A filter based observer is designed based on the linear PDE representation using which a detection residual is generated. A fault is detected when the magnitude of the detection residual exceeds a detection threshold. Upon detection, several isolation estimators are designed using filters whose output residuals are compared with predefined isolation thresholds. A fault …

Thermal Diffusivity Materials Characterization Via Active Microwave Thermography, Logan M. Wilcox, Kristen M. Donnell

Electrical and Computer Engineering Faculty Research & Creative Works

Active microwave thermography (AMT) is a relatively new nondestructive evaluation method which is proposed in this work for thermal materials characterization. Specifically, AMT is investigated as a single-sided measurement option for out-of-plane thermal diffusivity (a parameter traditionally measured using a two-sided technique). Simulation and measurement results support the use of AMT for such a characterization for materials backed by an electromagnetically absorptive material. Both lossless and lossy materials may be measured, with better accuracy for lossless materials. The effect of heating time was also considered. The results indicate that for the 50 W system used here, 100 seconds of electromagnetic …

Dipole-Moment-Based Reciprocity For Practical Desensitization Identification And Mitigation, Shengxuan Xia, Hanfeng Wang, Yansheng Wang, Zhonghua Wu, Chulsoon Hwang, Jun Fan

Electrical and Computer Engineering Faculty Research & Creative Works

Radio frequency interference can degrade the receiving sensitivity of antennas. The interference is usually caused by certain coupling structures, such as layouts without adequate grounding for the radio frequency signal return path. Those structures can be modeled as a set of equivalent dipole moments when they are electrically small. Herein, the dipole moment model-based coupling framework is applied to a practical cellphone design case to devise an engineering solution. The coupling framework incorporates dipole moments as radiation sources and a coupling model based on the reciprocity theorem. Unfortunately, near-field scan probes often lack access to all locations, owing to the …

Esd Events To Wearable Medical Devices In Healthcare Environments—Part 1: Current Measurements, Mehdi Kohani, Javad Meiguni, David J. Pommerenke, Michael G. Pecht

Electrical and Computer Engineering Faculty Research & Creative Works

Wearable medical devices are widely used for monitoring and treatment of patients. Electrostatic discharge can render these devices unreliable and cause a temporary or permanent disturbance in their operation. In a healthcare environment, severe electrostatic discharge (ESD) can occur while a patient, lying down or sitting on a hospital bed with a wearable device, discharges the device via a grounded bedframe. To protect the devices from ESD damage, the worst-case discharge conditions in the usage environment need to be identified. Previous studies by authors revealed that such events could be more severe than the conventional human metal model (HMM). However, …