Electrical and Computer Engineering Commons^™

How Do Social Network Models Compare To All-To-All Models For Forecasting Tuberculosis Epidemics? A Mathematical Modeling Study, Masabho Peter Milali, Hae-Young Kim, George Corliss, Anna Bershteyn

Electrical and Computer Engineering Faculty Research and Publications

Background. Mathematical models guide tuberculosis (TB) target-setting, yet most assume homogeneous “all-to-all” mixing. We compared projected intervention impacts between an all-to-all compartmental model and a Barabási–Albert (BA) scale‑free social network model under otherwise identical disease assumptions.

Methods. We calibrated transmission parameters so both models produced similar baseline trends, then introduced vaccination (coverage 30–70%; efficacy 80–95%) and treatment (20–50% increases in recovery) after a 400‑day burn‑in. Outcomes were assessed 300 days post‑intervention.

Results. Under 60% coverage, increasing vaccine efficacy from 80% to 95% yielded smaller projected reductions in active TB with the network model than with all‑to‑all mixing. Treatment improvements showed …

Applying Large Language Models For Surgical Case Length Prediction, Adhitya Ramamurthi, Bhabishya Neupane, Priya Deshpande, Ryan Hanson, Srujan Vegesna, Deborah Cray, Bradley H. Crotty, Melek Somai, Kellie R. Brown, Sachin S. Pawar, Bradley Taylor, Anai N. Kothari

Electrical and Computer Engineering Faculty Research and Publications

Importance Accurate prediction of surgical case duration is critical for operating room (OR) management, as inefficient scheduling can lead to reduced patient and surgeon satisfaction while incurring considerable financial costs.

Objective To evaluate the feasibility and accuracy of large language models (LLMs) in predicting surgical case length using unstructured clinical data compared to existing estimation methods.

Design, Setting, and Participants This was a retrospective study analyzing elective surgical cases performed between January 2017 and December 2023 at a single academic medical center and affiliated community hospital ORs. Analysis included 125493 eligible surgical cases, with 1950 used for LLM fine-tuning and …

Heat-Pipe-Based Thermal Management System Design For A 250-Kw Gan-Based Integrated Modular Motor Drive, Seyed Iman Hosseini Sabzevari, Salar Koushan, Armin Ebrahimian, Towhid Islam Chowdhury, Nathan Weise, Ayman El-Refaie

Electrical and Computer Engineering Faculty Research and Publications

Integrated modular motor drive (IMMD) is an effective approach for realizing high-efficiency, high-power-density, and fault-tolerant electric machines. However, designing an efficient thermal management system (TMS) for the motor drive becomes a challenge, particularly due to space constraints. This article presents the design of a TMS based on 3-mm heat pipes for a 250-kW IMMD intended for aviation applications. The power electronics module is simulated using PLECS software where an electrothermal analysis is conducted. A simplified thermal resistance model of the system is developed to estimate the die junction temperature of gallium nitride (GaN) semiconductors. The performance of the proposed TMS …

Performance Enhancement In Rewound Industrial Retrofit Solutions For Five- And Six-Phase Permanent Magnet Assisted Synchronous Reluctance Machines, Kotb B. Tawfiq, Ayman M. El-Refaie, Peter Sergeant, Hatem Zeineldin, Ahmed Al-Durra, Ehab F. El-Sadaany

Electrical and Computer Engineering Faculty Research and Publications

This paper investigates upgrading aging three-phase Permanent Magnet Assisted Synchronous Reluctance Machines (PMaSynRMs) into multiphase configurations—specifically six- and five-phase windings—without modifying the existing stator or rotor laminations. This retrofit supports circular economic principles by extending machine life and reducing material waste and cost. Four configurations are examined: the original three-phase winding, asymmetrical six-phase winding, symmetrical six-phase winding, and five-phase winding. The feasibility of rewinding existing three-phase stators is explored for different slot/pole combinations. Balanced rewound five-phase windings are feasible only when the stator's slot/pole ratio is greater than or equal to 9. Both symmetrical and asymmetrical rewound six-phase windings are …

Advanced Day-Ahead Scheduling Of Hvac Demand Response Control Using Novel Strategy Of Q-Learning, Model Predictive Control, And Input Convex Neural Networks, Rahman Heidarykiany, Cristinel Ababei

Electrical and Computer Engineering Faculty Research and Publications

In this paper, we present a Q-Learning optimization algorithm for smart home HVAC systems. The proposed algorithm combines new convex deep neural network models with model predictive control (MPC) techniques. More specifically, new input convex long short-term memory (ICLSTM) models are employed to predict dynamic states in an MPC optimal control technique integrated within a Q-Learning reinforcement learning (RL) algorithm to further improve the learned temporal behaviors of nonlinear HVAC systems. As a novel RL approach, the proposed algorithm generates day-ahead HVAC demand response (DR) signals in smart homes that optimally reduce and/or shift peak energy usage, reduce electricity costs, …

Optimization-Based Distributed Controller For Multi-Agents System In Microgrid Secondary Control, Fahad S. Alshammari, Ayman El-Refaie, Saleh Alyahya, Sheroz Khan

Electrical and Computer Engineering Faculty Research and Publications

Micro-grids function to connect to power system power produced by the renewable energy resources. In islanded micro-grids, grid-forming units collaborate to maintain the micro-grids voltage and frequency by utilizing droop control technique that includes primary, secondary and tertiary levels. Secondary control intervenes to improve power sharing and restore voltage and frequency to their nominal levels. However, the conventional droop control applied to a grid with mismatched line parameters experiences a trade-off between reactive power sharing and voltage regulations. This paper applies real-time trajectory tracking convex optimization to ensure by communicating power sharing between units in a consensus topology. The optimization …

Understanding The Breadth And Impact Of The Ias [President’S Message], Ayman El-Refaie

Electrical and Computer Engineering Faculty Research and Publications

No abstract provided.

Understanding The Breadth And Impact Of The Ias [Presidents Message], Ayman El-Refaie

Electrical and Computer Engineering Faculty Research and Publications

No abstract provided.

Heat-Pipe-Based Thermal Management System Design For A 250 Kw Gan-Based Integrated Modular Motor Drive, Seyed Iman Hosseini Sabzevari, Salar Koushan, Armin Ebrahimian, Towhid Islam Chowdhury, Nathan Weise, Ayman El-Refaie

Electrical and Computer Engineering Faculty Research and Publications

Integrated modular motor drive (IMMD) is an effective approach for realizing high-efficiency, high-power-density, and fault-tolerant electric machines. However, designing an efficient thermal management system (TMS) for the motor drive becomes a challenge, particularly due to space constraints. This article presents the design of a TMS based on 3-mm heat pipes for a 250-kW IMMD intended for aviation applications. The power electronics module is simulated using PLECS software where an electrothermal analysis is conducted. A simplified thermal resistance model of the system is developed to estimate the die junction temperature of gallium nitride (GaN) semiconductors. The performance of the proposed TMS …

Development And Validation Of An Artificial Intelligence System For Surgical Case Length Prediction, Adhitya Ramamurthi, Bhabishya Neupane, Priya Deshpande, Ryan Hanson, Kellie R. Brown, Kathleen K. Christians, Douglas B. Evans, Anai N. Kothari

Electrical and Computer Engineering Faculty Research and Publications

Background

Accurate case length estimation is a vital part of optimizing operating room use; however, significant inaccuracies exist with current solutions. The purpose of this study was to develop and validate an artificial intelligence system for improved surgical case length prediction by applying natural language processing and machine-learning methods.

Methods

All inpatient elective surgical cases longer than 30 minutes completed between 2017 and 2023 at a single, quaternary care hospital were considered. Data were split into training, test, and hold-out validation for model training and testing. Linear regression, CategoricalBoost, and feed-forward neural network each were trained and used embeddings created …

Industry Applications Society And Conferences [President’S Message], Ayman El-Refaie

Electrical and Computer Engineering Faculty Research and Publications

No abstract provided.

Industry Applications Society And Conferences [Presidents Message], Ayman El-Refaie

Electrical and Computer Engineering Faculty Research and Publications

No abstract provided.

An Iterative Shifting Disaggregation Algorithm For Multi-Source, Irregularly Sampled, And Overlapped Time Series, Colin O. Quinn, Ronald H. Brown, George F. Corliss, Richard J. Povinelli

Electrical and Computer Engineering Faculty Research and Publications

Accurate time series forecasting often requires higher temporal resolution than that provided by available data, such as when daily forecasts are needed from monthly data. Existing temporal disaggregation techniques, which typically handle only single, uniformly sampled time series, have limited applicability in real-world, multi-source scenarios. This paper introduces the Iterative Shifting Disaggregation (ISD) algorithm, designed to process and disaggregate time series derived from sensor-sourced low-frequency measurements, transforming multiple, nonuniformly sampled sensor data streams into a single, coherent high-frequency signal. ISD operates in an iterative, two-phase process: a prediction phase that uses multiple linear regression to generate high-frequency series from low-frequency …

Computer Vision-Based Framework For Data Extraction From Heterogeneous Financial Tables: A Comprehensive Approach To Unlocking Financial Insights, Iftakhar Ali Khandokar, Priya Deshpande

Electrical and Computer Engineering Faculty Research and Publications

Information extraction from financial document images is crucial in computer vision and NLP, as financial data often exists in image or PDF format, enabling organizations to analyze and make informed business decisions using OCR advancements. The table contents of financial document images are one of the prominent structures to confine important portions of data of the document and many Deep learning-based methods have been proposed to detect Table regions inside document images. The shortcomings of the current approach are that it is bounded within the detection of the table region and struggles in cases such as handling different layouts and …

Analysis Of Multivariable Sensor Responses To Multi-Analyte Gas Samples In The Presence Of Interferents And Humidity, Sakin Sarwar Satter, Florian Bender, Nicholas Post, Antonio J. Ricco, Fabien Josse

Electrical and Computer Engineering Faculty Research and Publications

This work presents an adaptive sensor signal-processing approach to enable quantification, using a single gas sensor or a small sensor array, of multianalyte mixtures of aromatic hydrocarbons in the presence of various interferents and humidity for environmental-monitoring applications. Dynamic sensor responses are analyzed by extracting multivariable sensing parameters to provide necessary sensitivity and selectivity. This is achieved by integrating the Levenberg–Marquardt-modified, exponentially weighted, recursive-least-squares-estimation (LM-modified EW-RLSE) algorithm and principal-component analysis (PCA). Achieving measured detection limits as low as 3 μg/L (≤1 ppm by volume) for 6 target analytes, the system exhibits excellent PCA cluster separation for all analytes in the …

Cross-Temporal Hierarchical Forecast Reconciliation Of Natural Gas Demand, Colin O. Quinn, George F. Corliss, Richard J. Povinelli

Electrical and Computer Engineering Faculty Research and Publications

Local natural gas distribution companies (LDCs) require accurate demand forecasts across various time periods, geographic regions, and customer class hierarchies. Achieving coherent forecasts across these hierarchies is challenging but crucial for optimal decision making, resource allocation, and operational efficiency. This work introduces a method that structures the gas distribution system into cross-temporal hierarchies to produce accurate and coherent forecasts. We apply our method to a case study involving three operational regions, forecasting at different geographical levels and analyzing both hourly and daily frequencies. Trained on five years of data and tested on one year, our model achieves a 10% reduction …

Data-Integrity Aware Stochastic Model For Cascading Failures In Power Grids, Rezoan Ahmed Shuvro, Pankaz Das, Jamir Shariar Jyoti, Joana M. Abreu, Majeed M. Hayat

Electrical and Computer Engineering Faculty Research and Publications

The reliable operation of power grids during cascading failures is heavily dependent on the interdependencies between the power grid components and the supporting communications and control networks. Moreover, the system operators' expertise in dealing with cascading failures can play a pivotal role during contingencies. In this paper, a dynamical probabilistic model is developed based on Markov-chains, which captures the dynamics of cascading failures in the power grid. Specifically, a previously developed Markov-chain based model is extended to capture the trade-off between the benefits of having a robust communication infrastructure and its vulnerability from data integrity (e.g., cyber-attacks). State-space reduction of …

A Comprehensive Characterization Of Hollow Conductor Additively Manufactured Coils And Thermal Management System For A 250 Kw Spm Machine, Sina Vahid, Salar Koushan, Towhid Islam Chowdhury, Ayman El-Refaie

Electrical and Computer Engineering Faculty Research and Publications

This paper provides an extensive and comprehensive analysis on characterization of additively manufactured coils and heat pipe based liquid cooling thermal management system, for a 250 kW and 5,000 rpm machine. AC and DC electrical tests at 140 Arms and 70 ADC are conducted on AlSi10Mg additively manufactured coils to extract their thermal and electrical characteristics. Heat pipes and liquid cooling test setups are described and discussed. The thermal discussion is concluded by experimental results showing the effectiveness of the thermal management system proposed in this paper. FEA are performed on the coils using ANSYS Maxwell to accurately predict the …

Mitigating Cascading Failures In Power Grids Via Markov Decision-Based Load-Shedding With Dc Power Flow Model, Pankaz Das, Rezoan Ahmed Shuvro, Kassie Povinelli, Francesco Sorrentino, Majeed M. Hayat

Electrical and Computer Engineering Faculty Research and Publications

Despite the reliability of modern power systems, large blackouts due to cascading failures (CFs) do occur in power grids with enormous economic and societal costs. In this article, CFs in power grids are theoretically modeled proposing a Markov decision process (MDP) framework with the aim of developing optimal load-shedding (LS) policies to mitigate CFs. The embedded Markov chain of the MDP, established earlier to capture the dynamics of CFs, features a reduced state-space and state-dependent transition probabilities. We introduce appropriate actions affecting the dynamics of CFs and associated costs. Optimal LS policies are computed that minimize the expected cumulative cost …

Comparative Study And Design Optimization Of A Dual-Mechanical-Port Electric Machine For Hybrid Electric Vehicle Applications, Hao Chen, Ayman M. El-Refaie, Yuefei Zuo, Shun Cai, Libing Cao, Christopher H. T. Lee

Electrical and Computer Engineering Faculty Research and Publications

A new dual-mechanical-port (DMP) electric machine for hybrid electric vehicle applications, particularly in the power-split continuously variable transmission systems, is proposed in this paper. In order to comprehensively and quantitatively evaluate the pros and cons of the proposed machine, a comparative study of four DMP electric machines with different topologies is conducted. These four investigated DMP electric machines include a conventional DMP machine, a DMP machine with spoke-type permanent magnets, a DMP machine with reluctance rotor, and a DMP machine with open slots which is the proposed machine in this paper. Even though these four machines have similar topologies, they …

Identification And Quantitation Of Aqueous Single- And Multianalyte Solutions Of The Isomers Ethylbenzene, M-, P-, And O-Xylene Using A Single Specifically Tailored Sensor Coating And Estimation Theory-Based Signal Processing, Nicholas Post, Florian Bender, Fabien Josse, Edwin E. Yaz, Antonio J. Ricco

Electrical and Computer Engineering Faculty Research and Publications

The isomer-specific detection and quantitation of m-, p-, and o-xylene and ethylbenzene, dissolved singly and as mixtures in aqueous solutions at concentrations from 100 to 1200 ppb by volume, is reported for a specifically designed polymer-plasticizer coating on a shear-horizontal surface acoustic wave (SH-SAW) device. The polystyrene-ditridecyl phthalate-blend coating was designed utilizing Hansen solubility parameters and considering the dipole moment and polarizability of the analytical targets and coating components to optimize the affinity of the sensor coating for the four chemical isomers. The two key coating sorption properties, sensitivity and response time constant, are determined by the …

Electrothermal Design Of A Gan-Based Axially Stator Iron-Mounted Fully Integrated Modular Motor Drive, Armin Ebrahimian, Waqar A. Khan, S. Iman Hosseini, Nathan Weise

Electrical and Computer Engineering Faculty Research and Publications

The concept of More Electric Aircraft (MEA) has gained a lot of attention from researchers recently. For such an application, two of the pivotal requirements are having a power dense and energy efficient propulsion system. To that end, in the design procedure of the electric motor and its drive system, high power density and efficiency over the entire operating range is the ultimate goal. Thus, the integration of the electric motor and drive system into a single unit has been introduced as an effective method to meet the design objectives. Therefore, this paper presents the design procedure of a module …

Supermodal Decomposition Of The Linear Swing Equation For Multilayer Networks, Kshitij Bhatta, Amirhossein Nazerian, Francesco Sorrentino, Majeed M. Hayat

Electrical and Computer Engineering Faculty Research and Publications

We study the swing equation in the case of a multilayer network in which generators and motors are modeled differently; namely, the model for each generator is given by second order dynamics and the model for each motor is given by first order dynamics. We also remove the commonly used assumption of equal damping coefficients in the second order dynamics. Under these general conditions, we are able to obtain a decomposition of the linear swing equation into independent modes describing the propagation of small perturbations. In the process, we identify symmetries affecting the structure and dynamics of the multilayer network …

Low-Latency And Fresh Content Provision In Information-Centric Vehicular Networks, Shan Zhang, Junjie Li, Hongbin Luo, Jie Gao, Lian Zhao, Xuemin Sherman Shen

Electrical and Computer Engineering Faculty Research and Publications

In this paper, the content service provision of information-centric vehicular networks (ICVNs) is investigated from the aspect of mobile edge caching, considering the dynamic driving-related context information. To provide up-to-date information with low latency, two schemes are designed for cache update and content delivery at the roadside units (RSUs). The roadside unit centric (RSUC) scheme decouples cache update and content delivery through bandwidth splitting, where the cached content items are updated regularly in a round-robin manner. The request adaptive (ReA) scheme updates the cached content items upon user requests with certain probabilities. The performance of both proposed schemes are analyzed, …

High-Resistance Connection Diagnosis In Five-Phase Pmsms Based On The Method Of Magnetic Field Pendulous Oscillation And Symmetrical Components, Hao Chen, Jiangbiao He, Xing Guan, Nabeel Demerdash, Ayman M. El-Refaie, Christopher H.T. Lee

Electrical and Computer Engineering Faculty Research and Publications

An online approach for diagnosing high-resistance connection (HRC) faults in five-phase permanent magnet synchronous motor drives is presented in this article. The development of this approach is based on a so-called “magnetic field pendulous oscillation (MFPO)” technique and symmetrical components method. Under HRC fault condition, a “swing-like” MFPO phenomenon is observed compared to the healthy condition. Furthermore, with the extracted current features in symmetrical components domain, different HRC fault types are successfully identified and distinguished. These fault types include single-phase faults, e.g., HRC fault in phase-A; two-phase nonadjacent faults, e.g., HRC fault in phase-A&C; and two-phase adjacent faults, e.g., HRC …

Collective Action On Behalf Of Women: Testing The Conceptual Distinction Between Traditional Collective Action And Small Acts In College Women, Anca M. Miron, Thomas C. Ball, Nyla R. Branscombe, Monica Fieck, Cristinel Ababei, Serena Raymer, Baylee Tkaczuk, Megan M. Meives

Electrical and Computer Engineering Faculty Research and Publications

The current study examines the nature of actions that U.S. college women (N = 267) engage in to promote, protect, or enhance the welfare of other women. The study had two goals: 1) to distinguish between traditional forms of action (traditional collective action) and more informal, interpersonal, forms of action (small acts) among college women; and 2) to test whether the classic antecedents of collective action (gender identity, feminist identity, women’s activist identity, efficacy, appraisals of gender inequality, and injustice standards) are differentially predictive of these two types of participation. A confirmatory factor analysis provided strong support for these two …

A Comparison Of Two Generalizations To The Linear Sampling Method For Inverse Scattering, Yeasmin Sultana, James E. Richie

Electrical and Computer Engineering Faculty Research and Publications

The linear sampling method (LSM) is a very popular method for determining the boundary of an object from the scattered field. However, there are instances where LSM provides the convex hull of the boundary rather than the true boundary. There are two common generalizations to LSM: the Generalized Linear Sampling Method (GLSM) and the Multipoles-based Linear Sampling Method (MLSM). In this paper, the ability of GLSM and MLSM to overcome some of the deficiencies of LSM are investigated. It is found that GLSM may be ideal for imaging thin features of scatterers and that MLSM can provide an improvement over …

On-Site/In Situ Continuous Detecting Ppb-Level Metal Ions In Drinking Water Using Block Loop-Gap Resonators And Machine Learning, Sangmin Oh, Imtiaz Hossen, Juan R. Luglio, Gusphyl Justin, James Richie, Henry Medeiros, Chung-Hoon Lee

Electrical and Computer Engineering Faculty Research and Publications

Microwave measurements and machine learning algorithms are presented to estimate metal ion concentrations in drinking water. A novel block loop gap resonator (BLGR) as a microwave probe is designed and fabricated to estimate Pb ion concentrations in city water as low as 1 ppb with an rms error of 0.18 ppb. No physical contact between the BLGR probe and the water sample allows on-site/in situ continuous detection of ppb-level metal ion concentrations. The S₁₁ raw data (amplitude and phase) from the BLGR are used to classify and estimate metal ion concentrations using a support vector regression algorithm. The performance …

Mac For Machine-Type Communications In Industrial Iot—Part I: Protocol Design And Analysis, Jie Gao, Weihua Zhuang, Mushu Li, Xuemin Shen, Xu Li

Electrical and Computer Engineering Faculty Research and Publications

In this two-part paper, we propose a novel medium access control (MAC) protocol for machine-type communications in the Industrial Internet of Things. The considered use case features a limited geographical area and a massive number of devices with sporadic data traffic and different priority types. We target supporting the devices while satisfying their Quality-of-Service (QoS) requirements with a single access point and a single channel, which necessitates a customized design that can significantly improve the MAC performance. In Part I of this paper, we present the MAC protocol that comprises a new slot structure, corresponding channel access procedure, and mechanisms …

Mac For Machine-Type Communications In Industrial Iot—Part Ii: Scheduling And Numerical Results, Jie Gao, Mushu Li, Weihua Zhuang, Xuemin Shen, Xu Li

Electrical and Computer Engineering Faculty Research and Publications

In the second part of this article, we develop a centralized packet transmission scheduling scheme to pair with the protocol designed in Part I and complete our medium access control (MAC) design for machine-type communications in the industrial Internet of Things. For the networking scenario, fine-grained scheduling that attends to each device becomes necessary, given stringent Quality-of-Service (QoS) requirements and diversified service types, but prohibitively complex for a large number of devices. To address this challenge, we propose a scheduling solution in two steps. First, we develop algorithms for device assignment based on the analytical results from Part I, when …