Electrical and Computer Engineering Commons^™

A Near-Field Communication (Nfc) Multi-Sensor Node With Optimized Read Range And Adaptive Power Management For Remote Monitoring, Rishin Patra, Hilary Scott Nkimbeng Cho, Jin W. Choi

Michigan Tech Publications

This paper presents the design of a batteryless near-field communication (NFC) multi-sensor node with an integrated adaptive power-management system for sensing applications. The work focuses on harvesting energy from a 13.56 MHz NFC field to power an ultra-low power sensing platform. The design consists of the TI RF430FRL152H, an integrated NFC transponder with an embedded MSP430 microcontroller core and ferroelectric random-access memory (FRAM) non-volatile memory. The system combines an ISO/IEC 15693 NFC front end, a tuned loop antenna for optimized power harvesting, and multiple analog and digital sensor interfaces, and a firmware architecture for intermittent harvested energy operation. The aforementioned …

Dynamic Deep Prompt Optimization For Defending Against Jailbreak Attacks On Llms, Doniyorkhon Obidov, Honggang Yu, Xiaolong Guo, Kaichen Yang

Michigan Tech Publications

Large Language Models (LLMs) demonstrate impressive capabilities across many applications but remain vulnerable to jailbreak attacks, which elicit harmful or unintended content. While model fine-tuning is an option for safety alignment, it is costly and prone to catastrophic forgetting. Prompt optimization has emerged as a promising alternative, yet existing prompt-based defenses typically rely on static modifications (e.g., fixed prefixes or suffixes) that cannot adapt to diverse and evolving attacks.

We propose Dynamic Deep Prompt Optimization (DDPO), the first jailbreak defense based on deep prompt optimization. DDPO uses the target LLM’s own intermediate layers as feature extractors to dynamically generate defensive …

Remote Sensing Of Dynamic Ground Motion Via A Moiré-Based Apparatus, Adrian Ali Moazzam, Nontawat Srisapan, Gregory Waite, Durdu Guney, Roohollah Askari

Michigan Tech Publications

Highlights: What are the main findings? A Moiré-based optical apparatus enables long-range, non-contact ground displacement measurement in hazardous environments. Controlled indoor and outdoor experiments demonstrate reliable detection of dynamic and seismic-like ground motions with sub-millimeter resolution. What are the implications of the main findings? System performance is evaluated under atmospheric turbulence and wind, revealing key limits and mitigation strategies for field deployment. The proposed approach provides a low-cost, scalable complement to traditional seismic and geodetic monitoring techniques. Ground-based remote sensing of seismic and geophysical displacements remains a major challenge due to environmental hazards, signal attenuation, and practical deployment limitations of …

Ainet: Integrating Mamba And Cbam For Enhanced Camouflage Object Detection, Henry O. Velesaca, P. Andrea Mero, Abel A. Reyes-Angulo, Angel D. Sappa

Michigan Tech Publications

This paper introduces AINet, a novel deep learning architecture designed for detecting camouflaged objects in complex and diverse environments. The objective of this work is to design an end-to-end camouflaged object detection architecture that simultaneously captures long-range dependencies and refines subtle camouflage cues, improving segmentation accuracy and boundary delineation across both standard COD benchmarks and real-world agricultural scenarios. AINet leverages the strengths of Mamba, an efficient sequential state model for capturing long-range dependencies, and the Convolutional Block Attention Module (CBAM) for feature refinement through attention mechanisms. Detecting camouflaged objects is a significant challenge across a wide range of real-world applications, …

Silent Sabotage: Internal State Triggered Backdoor Attacks On Llm-Powered Robotic Systems, Doniyorkhon Obidov, Shivayogi Akki, Tan Chen, Kaichen Yang

Michigan Tech Publications

The integration of Large Language Models (LLMs) into robotic control systems is enabling a new generation of autonomous agents capable of complex reasoning and planning. While this paradigm shift accelerates progress, it also introduces novel security risks that remain largely unexplored. Current research into LLM backdoors has focused on attacks triggered by external stimuli, such as specific words, visual objects, or environmental states. These attacks, while potent, overlook a more insidious class of vulnerability where the trigger is internal to the agent’s own operational logic. This paper presents the first comprehensive study of history-based backdoor attacks on LLM-powered robotic systems. …

Recent Advancements Of Applied Robotics In Construction Project Management: A Life Cycle Perspective, Yifan Wang, Xiaoyu Hou, Tan Chen, Bo Xiao

Michigan Tech Publications

Robotic applications in the architecture, engineering, construction, and operation (AEC/O) industry have advanced rapidly, driven by innovations in sensing, artificial intelligence (AI), and automation. Yet, despite notable progress, existing studies are often confined to isolated systems, specific technologies, or individual project phases. This fragmentation has resulted in a diverse but disjointed body of knowledge, underscoring the need for a comprehensive synthesis that connects emerging practices into a holistic perspective. This study presents a systematic review of 315 peer-reviewed publications from 2016 to 2025, examined through a life cycle lens. A mixed-methods approach combining quantitative analysis with qualitative discussion is employed …

Siamese: Stealing Fine-Tuned Visual Foundation Models Via Diversified Prompting, Madhureeta Das, Gaurav Bagwe, Miao Pan, Kaichen Yang, Xiaoyong Yuan, Lan Zhang

Michigan Tech Publications

Visual foundation models, characterized by their robust generalization and adaptability, serve as the basis for a wide array of downstream tasks. When fine-tuned for specific tasks, these models encapsulate confidential and valuable task-specific knowledge, making them prime targets for model stealing (MS) attacks. While recent efforts have exposed MS threats in practical scenarios such as data-free and hard-label contexts, these attacks predominantly target traditional victim models trained from scratch. Fine-tuned visual foundation models, pre-trained on vast and diverse datasets and then fine-tuned on downstream tasks, present significant challenges for traditional MS attacks to extract task-specific knowledge. In this paper, we …

An Audio Data-Driven Roadway Digital Twin And Its Underlying Framework For A Digitized Transportation Construction Environment, Anisha Deria, Pedro J. Chacon Dominguez, Yong-Cheol Lee, Jin W. Choi

Michigan Tech Publications

The increasing need to build and maintain transportation systems has led project managers to manage multiple projects simultaneously. Roadway projects often entail several miles of job site, making it difficult to keep track of progress and maintenance activities. To improve the situation, this study proposes an audio data-driven roadway digital twin framework for real-time and remote monitoring of construction projects. The latent characteristics of a digital twin required for establishing a digitized work environment were investigated. As a primary method of seamlessly linking virtual and physical environments, audio data classified and analyzed by deep neural network (DNN) has been employed …

Investigation Of Insertion Loss In Inkjet-Printed Coplanar Waveguide Based On Drying Temperature, Jun Ho Yu, Sung Min Sim, Jin Woo Choi, Sang Ho Lee, Jung Mu Kim

Michigan Tech Publications

In this study, we propose an optimized inkjet printing process to improve the insertion loss of inkjet-printed coplanar waveguide (CPW) transmission lines. The process involves varying the drying temperature and adjusting the number of printing steps to investigate their effects on the electrical characteristics of the printed CPW. The relationships between surface roughness, surface cavities, morphological changes, and insertion loss are studied by conducting atomic force microscopy analysis and by examining the insertion loss up to 3 GHz. The printed CPW that underwent low-temperature drying after the first printing and high-temperature drying after the second printing before sintering showed improved …

Resilience Oriented Distribution System Service Restoration Considering Overhead Power Lines Affected By Hurricanes, Kehkashan Fatima, Hussain Shareef, Flavio Costa

Michigan Tech Publications

In recent years, there has been an increase in the frequency of severe weather events (like hurricanes). These events are responsible for most power outages in power distribution systems (PDSs). Particularly susceptible to storms are overhead PDSs. In this study, the dynamic Bayesian network (DBN)-based failure model was developed for different hurricane scenarios to predict the line failure of overhead lines. Based on the outcomes of the DBN model, a service restoration model was formulated to maximize restored loads and minimize power losses using Particle Swarm Optimization (PSO)-based distributed generation (DG) integration and system reconfiguration. Three different case studies based …

An Audio Data-Driven Roadway Digital Twin And Its Underlying Framework For A Digitized Transportation Construction Environment, Anisha Deria, Pedro J. Chacon Dominguez, Yong-Cheol Lee, Jin W. Choi

Michigan Tech Publications

The increasing need to build and maintain transportation systems has led project managers to manage multiple projects simultaneously. Roadway projects often entail several miles of job site, making it difficult to keep track of progress and maintenance activities. To improve the situation, this study proposes an audio data-driven roadway digital twin framework for real-time and remote monitoring of construction projects. The latent characteristics of a digital twin required for establishing a digitized work environment were investigated. As a primary method of seamlessly linking virtual and physical environments, audio data classified and analyzed by deep neural network (DNN) has been employed …

Performance Analysis Of Multivariable Control Structures Applied To A Neutral Point Clamped Converter In Pv Systems, Renato Santana Ribeiro Junior, Eubis Pereira Machado, Damásio Fernandes Júnior, Tárcio André Dos Santos Barros, Flavio Bezerra Costa

Michigan Tech Publications

This paper addresses the challenges encountered by grid-connected photovoltaic (PV) systems, including the stochastic behavior of the system, harmonic distortion, and variations in grid impedance. To this end, an in-depth technical and pedagogical analysis of three linear multivariable current control strategies is performed: proportional-integral (PI), proportional-resonant (PR), and deadbeat (DB). The study contributes to theoretical formulations, detailed system modeling, and controller tuning procedures, promoting a comprehensive understanding of their structures and performance. The strategies are investigated and compared in both the rotating ((Formula presented.)) and stationary ((Formula presented.)) reference frames, offering a broad perspective on system behavior under various operating …

Replicating Associative Learning Of Rodents With A Neuromorphic Robot In An Open-Field Arena, Tianze Liu, Kang Jun Bai, Hongyu An

Michigan Tech Publications

This study emulates associative learning in rodents by using a neuromorphic robot navigating an open-field arena. The goal is to investigate how biologically inspired neural models can reproduce animal-like learning behaviors in real-world robotic systems. We constructed a neuromorphic robot by deploying computational models of spatial and sensory neurons onto a mobile platform. Different coding schemes—rate coding for vibration signals and population coding for visual signals—were implemented. The associative learning model employs 19 spiking neurons and follows Hebbian plasticity principles to associate visual cues with favorable or unfavorable locations. Our robot successfully replicated classical rodent associative learning behavior by memorizing …

Benchmarking Model Predictive Control And Reinforcement Learning-Based Control For Legged Robot Locomotion In Mujoco Simulation, Shivayogi Akki, Tan Chen

Michigan Tech Publications

Model Predictive Control (MPC) and Reinforcement Learning (RL) are two prominent strategies for controlling legged robots. RL learns control policies through system interaction, adapting to various scenarios, whereas MPC relies on a predefined mathematical model to solve optimization problems in real-time. Despite their widespread use, there is a lack of direct comparative analysis under standardized conditions. This work addresses this gap by benchmarking MPC and RL controllers on a Unitree Go1 quadruped robot within the MuJoCo simulation environment, focusing on a standardized task, straight walking at a constant velocity. Performance is evaluated based on disturbance rejection, energy efficiency, and terrain …

Remote Sensing Of Seismic Signals Via Enhanced Moiré-Based Apparatus Integrated With Active Convolved Illumination, Adrian A. Moazzam, Anindya Ghoshroy, Durdu Güney, Roohollah Askari

Michigan Tech Publications

The remote sensing of seismic waves in challenging and hazardous environments, such as active volcanic regions, remains a critical yet unresolved challenge. Conventional methods, including laser Doppler interferometry, InSAR, and stereo vision, are often hindered by atmospheric turbulence or necessitate access to observation sites, significantly limiting their applicability. To overcome these constraints, this study introduces a Moiré-based apparatus augmented with active convolved illumination (ACI). The system leverages the displacement-magnifying properties of Moiré patterns to achieve high precision in detecting subtle ground movements. Additionally, ACI effectively mitigates atmospheric fluctuations, reducing the distortion and alteration of measurement signals caused by these fluctuations. …

Single-Entity Protein Electrochemistry Of A Diffusion-Limited Enzyme, Ziwen Zhao, Nikolaos Kostopoulos, Sagar Ganguli, Paul Bergstrom, Alina Sekretareva

Michigan Tech Publications

In this work, we present single-entity protein electrochemistry (SEPE) experiments on catalase, along with a theoretical model to simulate its enzymatic activity and predict the experimentally observed current responses. We perform SEPE measurements at various enzyme concentrations and use protein film voltammetry to investigate the origin of the observed electrochemical signals in SEPE. The modeling approach we develop combines finite element simulations in COMSOL Multiphysics with random walk simulations in MATLAB. The enzyme is represented as a partially active sphere, with an arc on the surface corresponding to the enzyme’s diffusion channel leading to the active site. Notably, the model …

Modeling, Control And Validation Of A Three-Phase Single-Stage Photovoltaic System, Eubis Pereira Machado, Adeon Cecílio Pinto, Rodrigo Pereira Ramos, Ricardo Menezes Prates, Jadsonlee Da Silva Sá, Joaquim Isídio De Lima, Flavio Bezerra Costa, Damásio Fernandes, Alex Coutinho Pereira

Michigan Tech Publications

The central inverter topology presents some advantages such as simplicity, low cost and high conversion efficiency, being the first option for interfacing photovoltaic mini-generation, whose shading and panel orientation studies are evaluated in the project planning phase. When it uses only one power converter, its control structures must ensure synchronization with the grid, tracking the maximum power generation point, appropriate power quality indices, and control of the active and reactive power injected into the grid. This work develops and contributes to mathematical models, the principles of formation of control structures, the decoupling process of the control loops, the treatment of …

Intelligent Transportation System With 5g Vehicle-To-Everything (V2x): Architectures, Vehicular Use Cases, Emergency Vehicles, Current Challenges, And Future Directions, Vaishali Pawar, Nilima Zade, Deepali Vora, Vaishali Khairnar, Aurenice M. Oliveira, Ketan Kotecha, Ambarish Kulkarni

Michigan Tech Publications

In recent years, connected vehicle technologies emerged to provide a safer and more connected environment for transportation systems, which has further evolved into cellular vehicle-to-everything (C-V2X) technology. The current study contributes in the direction of future research of smart India @2047 in connected vehicles. The study presents the diverse aspects of 5G V2X as a comprehensive overview of Vehicle-to-Everything (V2X) technology that covers the significant scope of V2X technology, including its development, components, functionality, use cases, and future potential. It is observed that few surveys are available that cover limited aspects of 5G V2X communication technologies, with one or two …

Backup Subscription Scheme For Differential Protection Using Iec61850-9-2 Sampled Values, Mohammad Khalili Katoulaei, Aamir Rahmani, Hans Kristian Høidalen, Irina Oleinikova, Bruce A. Mork

Michigan Tech Publications

In IEC-61850-based digital substations, the protection IED’s performance is dependent on merging unit’s vendor implementation, communication networks, and measurement circuit’s health conditions. As the process bus Sampled Value(SV) enables the availability of all sensor data on a communication network, this paper proposes a Backup Subscription scheme (BSS) for a transformer differential protection (87T, PDIF) function. BSS utilizes sensor data in digital substations to achieve a flexible protection scheme using a dynamic subscription feature. Thus, in case of failure of one sensor, differential protection would be maintained. The paper presents the implementation and verification of a prototyped scheme using a Hardware-in-the-loop …

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 …

Design And Analysis Of Self-Tanked Stepwise Charging Circuit For Four-Phase Adiabatic Logic, William Morell, Jin Woo Choi

Michigan Tech Publications

Adiabatic logic has been proposed as a method for drastically reducing power consumption in specialized low-power circuits. They often require specialized clock drivers that also function as the main power supply, in contrast to standard CMOS logic, and these power clocks are often a point of difficulty in the design process. A novel, stepwise charging driver circuit for four-phase adiabatic logic is proposed and validated through a simulation study. The proposed circuit consists of two identical driver circuits each driving two opposite adiabatic logic phases. Its performance relative to ideal step-charging and a standard CMOS across mismatched phase loads is …

Plc Multi-Robot Integration Via Ethernet For Human Operated Quality Sampling, Jeevan S. Devagiri, Paniz Khanmohammadi Hazaveh, Nathir Rawashdeh, Sai Revanth Reddy Dudipala, Pratik Mohan Desmuhk, Aditya Prasad Karmarkar

Michigan Tech Publications

In automation, quality control inspection is a critical requirement to ensure product standards. The goal of this work is to insure product quality without interrupting the production line flow. The multi-robot system presented, connects a programmable logic controller (PLC), as the main controller, to a conveyor belt and two FANUC industrial robotic arms via EtherNet/IP. Human interaction is implemented to pick a work piece from the moving conveyor and return it with a quality label. This label is used by the PLC to execute the correct robot action; either to return the inspected part to the conveyor or discard it …

Channel Prediction For Underwater Acoustic Communication: A Review And Performance Evaluation Of Algorithms, Haotian Liu, Lu Ma, Zhaohui Wang, Gang Qiao

Michigan Tech Publications

Underwater acoustic (UWA) channel prediction technology, as an important topic in UWA communication, has played an important role in UWA adaptive communication network and underwater target perception. Although many significant advancements have been achieved in underwater acoustic channel prediction over the years, a comprehensive summary and introduction is still lacking. As the first comprehensive overview of UWA channel prediction, this paper introduces past works and algorithm implementation methods of channel prediction from the perspective of linear, kernel-based, and deep learning approaches. Importantly, based on available at-sea experiment datasets, this paper compares the performance of current primary UWA channel prediction algorithms …

Monitoring Time Domain Characteristics Of Parkinson's Disease Using 3d Memristive Neuromorphic System, Md Abu Bakr Siddique, Yan Zhang, Hongyu An

Michigan Tech Publications

INTRODUCTION: Parkinson's disease (PD) is a neurodegenerative disorder affecting millions of patients. Closed-Loop Deep Brain Stimulation (CL-DBS) is a therapy that can alleviate the symptoms of PD. The CL-DBS system consists of an electrode sending electrical stimulation signals to a specific region of the brain and a battery-powered stimulator implanted in the chest. The electrical stimuli in CL-DBS systems need to be adjusted in real-time in accordance with the state of PD symptoms. Therefore, fast and precise monitoring of PD symptoms is a critical function for CL-DBS systems. However, the current CL-DBS techniques suffer from high computational demands for real-time …

Finding Ideal Parameters For Recycled Material Fused Particle Fabrication-Based 3d Printing Using An Open Source Software Implementation Of Particle Swarm Optimization, Shane Oberloier, Nicholas G. Whisman, Joshua M. Pearce

Michigan Tech Publications

As additive manufacturing rapidly expands the number of materials including waste plastics and composites, there is an urgent need to reduce the experimental time needed to identify optimized printing parameters for novel materials. Computational intelligence (CI) in general and particle swarm optimization (PSO) algorithms in particular have been shown to accelerate finding optimal printing parameters. Unfortunately, the implementation of CI has been prohibitively complex for noncomputer scientists. To overcome these limitations, this article develops, tests, and validates PSO Experimenter, an easy-to-use open-source platform based around the PSO algorithm and applies it to optimizing recycled materials. Specifically, PSO Experimenter is used …

Modular Open-Source Design Of Pyrolysis Reactor Monitoring And Control Electronics, Finn K. Hafting, Daniel G. Kulas, Etienne Michels, Sarvada Chipkar, Stefan Wisniewski, David Shonnard, Joshua M. Pearce

Michigan Tech Publications

Industrial pilot projects often rely on proprietary and expensive electronic hardware to control and monitor experiments. This raises costs and retards innovation. Open-source hardware tools exist for implementing these processes individually; however, they are not easily integrated with other designs. The Broadly Reconfigurable and Expandable Automation Device (BREAD) is a framework that provides many open-source devices which can be connected to create more complex data acquisition and control systems. This article explores the feasibility of using BREAD plug-and-play open hardware to quickly design and test monitoring and control electronics for an industrial materials processing prototype pyrolysis reactor. Generally, pilot-scale pyrolysis …

Finding Ideal Parameters For Recycled Material Fused Particle Fabrication-Based 3d Printing Using An Open Source Software Implementation Of Particle Swarm Optimization, Shane Oberloier, Nicholas G. Whisman, Joshua M. Pearce

Michigan Tech Publications

As additive manufacturing rapidly expands the number of materials including waste plastics and composites, there is an urgent need to reduce the experimental time needed to identify optimized printing parameters for novel materials. Computational intelligence (CI) in general and particle swarm optimization (PSO) algorithms in particular have been shown to accelerate finding optimal printing parameters. Unfortunately, the implementation of CI has been prohibitively complex for noncomputer scientists. To overcome these limitations, this article develops, tests, and validates PSO Experimenter, an easy-to-use open-source platform based around the PSO algorithm and applies it to optimizing recycled materials. Specifically, PSO Experimenter is used …

Nr Sidelink Performance Evaluation For Enhanced 5g-V2x Services, Mehnaz Tabassum, Felipe Henrique Bastos, Aurenice M. Oliveira, Aldebaro Klautau

Michigan Tech Publications

The Third Generation Partnership Project (3GPP) has specified Cellular Vehicle-to-Everything (C-V2X) radio access technology in Releases 15–17, with an emphasis on facilitating direct communication between vehicles through the interface, sidelink PC5. This interface provides end-to-end network slicing functionality together with a stable cloud-native core network. The performance of direct vehicle-to-vehicle (V2V) communications has been improved by using the sidelink interface, which allows for a network infrastructure bypass. Sidelink transmissions make use of orthogonal resources that are either centrally allocated (Mode 1, Release 14) or chosen by the vehicles themselves (Mode 2, Release 14). With growing interest in connected and autonomous …

Optimal Inverter-Based Resource Installation To Minimize Technical Energy Losses In Distribution Systems, Felipe B. Dantas, Damasio Fernandes, Washington L.A. Neves, Alana K.X.B. Branco, Flavio Costa

Michigan Tech Publications

This paper proposes an algorithm for the optimal installation of inverter-based resources (IBR) composed of wind energy conversion systems, photovoltaic systems, and battery energy storage systems in distribution systems using genetic algorithm (GA) and the cuckoo search (CS) as optimization techniques. The OpenDSS software is used to calculate the power flow in the distribution system with different penetration levels of IBRs. It is used a standard load shape of the IEEE 123 bus system programmed in OpenDSS and irradiance, temperature, and wind speed curves from Brazil. The proposed algorithm, using a genetic algorithm and cuckoo search, was able to define …

Synthetic Aperture Scatter Imaging, Qian Huang, Zhipeng Dong, Gregory Nero, Yuzuru Takashima, Timothy J. Schulz, David J. Brady

Michigan Tech Publications

Diffraction limits the minimum resolvable feature on remotely observed targets to $\lambda R_{c}/A_{c}$, where $\lambda$ is the operating wavelength, $R_{c}$ is the range to the target and $A_{c}$ is the diameter of the observing aperture. Resolution is often further reduced by scatter or turbulence. Here we show that analysis of scattered coherent illumination can be used to achieve resolution proportional to $\lambda R_{s}/A_{s}$, where $R_{s}$ is the range between the scatterer and the target and $A_{s}$ is the diameter of the observed scatter. Theoretical analysis suggests that this approach can yield resolution up to 1000× better than the diffraction limit. …