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Articles 7081 - 7110 of 75378

Full-Text Articles in Engineering

Vertical Interconnect Technology In Silicon, Package, And Printed Circuit Board (Pcb) With Coaxial Structure, Junyong Park, Chaofeng Li, Eddie Mok, Joe Dickson, Joan Tourne, Donghyun Kim Jan 2024

Vertical Interconnect Technology In Silicon, Package, And Printed Circuit Board (Pcb) With Coaxial Structure, Junyong Park, Chaofeng Li, Eddie Mok, Joe Dickson, Joan Tourne, Donghyun Kim

Electrical and Computer Engineering Faculty Research & Creative Works

This paper introduces vertical interconnect technology in silicon, package, and printed circuit board (PCB) levels with a coaxial structure, respectively. The coaxial structure has been known to be advantageous in terms of signal integrity (SI) compared to the non-coaxial structure. The coaxial structure is easy to control the characteristic impedance Z0 and robust to crosstalk. The silicon-level interconnect includes the wire bonding (WB) and through-silicon via (TSV) technology, the package-level interconnect includes an elastomer package test socket. The PCB-level interconnect includes the vias, and vertical conductive structure (VeCS). For each level, the non-coaxial and coaxial interconnects are compared with the …

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Mechanisms For Unwanted Magnetic Field Coupling To A Shielded Magnetic Near-Field Probe, Xin Yan, Wei Zhang, Sajjad Sadeghi, Mehdi Gholizadeh, David J. Pommerenke, Daryl G. Beetner Jan 2024

Mechanisms For Unwanted Magnetic Field Coupling To A Shielded Magnetic Near-Field Probe, Xin Yan, Wei Zhang, Sajjad Sadeghi, Mehdi Gholizadeh, David J. Pommerenke, Daryl G. Beetner

Electrical and Computer Engineering Faculty Research & Creative Works

Unwanted field coupling is a major concern when using magnetic near-field probes for high-frequency scanning. The unwanted coupling of the tangential electric field to a tangential magnetic field probe has been studied extensively. This article shows a second unwanted coupling mechanism: coupling from a vertical magnetic field. The standing wave of a shorted pure TEM microstrip in air is utilized to separate the magnetic and electric field coupling. Simulations show that the eddy currents induced within the probe by the vertical magnetic field couple inductively to the pickup loop if the layer stack up is not symmetric. The unwanted magnetic …

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Coupling-Informed Data-Driven Scheme For Joint Angle And Frequency Estimation In Uniform Linear Array With Mutual Coupling Present, Yanming Zhang, Wenchao Xu, A. Long Jin, Min Li, Peifeng Ma, Lijun Jiang, Steven Gao Jan 2024

Coupling-Informed Data-Driven Scheme For Joint Angle And Frequency Estimation In Uniform Linear Array With Mutual Coupling Present, Yanming Zhang, Wenchao Xu, A. Long Jin, Min Li, Peifeng Ma, Lijun Jiang, Steven Gao

Electrical and Computer Engineering Faculty Research & Creative Works

This paper proposes a novel coupling-informed data-driven algorithm tailored for the concurrent estimation of frequency and angle within a uniform linear array (ULA), while addressing the complicating influence of mutual coupling. Leveraging the hybrid dynamic mode decomposition (DMD) methodology, termed as averaged DMD, we incorporate moving average techniques to achieve effective denoising. The averaged DMD further decomposes the received signal into eigenvalues and corresponding eigenvectors. The frequency information is derived from the eigenvalues and the corresponding eigenvectors represent the steering vectors of sources. Subsequently, mutual coupling is informed into the calibration of the steering vector for each source. Specifically, the …

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Design Of The Tm010 Mode Cylindrical Cavity Resonator For Pcb Dielectric Characterization, Reza Asadi, Chaofeng Li, Seyedmehdi Mousavi, Seyed Moastafa Mousavi, Reza Vahdani, Xiaoning Ye, Donghyun Kim Jan 2024

Design Of The Tm010 Mode Cylindrical Cavity Resonator For Pcb Dielectric Characterization, Reza Asadi, Chaofeng Li, Seyedmehdi Mousavi, Seyed Moastafa Mousavi, Reza Vahdani, Xiaoning Ye, Donghyun Kim

Electrical and Computer Engineering Faculty Research & Creative Works

This paper presents the study of the TM010 mode cylindrical resonator, which can be used for printed circuit board (PCB) material properties extraction, e.g., the dielectric constant (Dk) and the loss tangent (Df) extraction. The theoretical formulas of the resonance frequency and Q-factor of the resonator are presented. In real measurement, the TM010 mode cylindrical cavity resonator needs to be excited by the probe. The study emphasizes the impact of probe orientation, location, and field distribution on the accuracy of material property extraction. The relationship between cavity dimensions and resonance frequency is explored, highlighting the influence of cavity …

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Experimental Study Of Pcb Vibration Induced By Mlcc Assembly Orientation And Process Variations, Yifan Ding, Ming Feng Xue, Jianmin Zhang, Xin Hua, Benjamin Leung, Eric A. Macintosh, Chulsoon Hwang Jan 2024

Experimental Study Of Pcb Vibration Induced By Mlcc Assembly Orientation And Process Variations, Yifan Ding, Ming Feng Xue, Jianmin Zhang, Xin Hua, Benjamin Leung, Eric A. Macintosh, Chulsoon Hwang

Electrical and Computer Engineering Faculty Research & Creative Works

The piezoelectric effect will cause the multilayer ceramic capacitor (MLCC) to deform in several directions. When it is soldered to the printed circuit board (PCB) and powered on, these deformations will exert a certain force on the PCB, causing the PCB to vibrate and emit acoustic noise at a certain frequency. Determining the dominant deformation direction that MLCC can affect the PCB is relevant and important for efficiently extracting the equivalent source of noise. This paper provides a method to determine the dominant deformation direction produced by MLCC, explores it through experimental measurement results, and finally provides a conclusion to …

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A Tensor-Based Data-Driven Approach For Multidimensional Harmonic Retrieval And Its Application For Mimo Channel Sounding., Yanming Zhang, Wenchao Xu, A. Long Jin, Min Li, Ping Yuan, Lijun Jiang, Steven Gao Jan 2024

A Tensor-Based Data-Driven Approach For Multidimensional Harmonic Retrieval And Its Application For Mimo Channel Sounding., Yanming Zhang, Wenchao Xu, A. Long Jin, Min Li, Ping Yuan, Lijun Jiang, Steven Gao

Electrical and Computer Engineering Faculty Research & Creative Works

In wireless channel sounding, accurately estimating multiple parameters within a multipath signal, such as azimuth, elevation, Doppler shift, and delay, necessitates addressing the challenges posed by the multidimensional harmonic retrieval (MHR) problem. To overcome these complexities, we propose a framework based on high-order dynamic mode decomposition (HODMD) that designed for robustly estimating frequencies of interest from high-dimensional sinusoidal signals, particularly in additive white Gaussian noise conditions. The HODMD approach, a hybrid algorithm amalgamating high-order singular value decomposition (HOSVD) and dynamic mode decomposition (DMD), operates by initially decomposing observed tensorial data into a core tensor and R mode matrices through HOSVD. …

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Lifelong Safe Optimal Adaptive Tracking Control Of Nonlinear Strict-Feedback Discrete-Time Systems, Behzad Farzanegan, S. Jagannathan Jan 2024

Lifelong Safe Optimal Adaptive Tracking Control Of Nonlinear Strict-Feedback Discrete-Time Systems, Behzad Farzanegan, S. Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

This paper presents a comprehensive approach for achieving multi-task safe optimal adaptive tracking (MSOAT) for a class of nonlinear discrete-time systems, particularly those in strict-feedback form, utilizing a multi-layer neural network (MNN)-based framework. To begin, a cost function with a novel Barrier function (BF) term is introduced for each subsystem to address the weak safely reachable problem, serving as a crucial tool for guiding the system's trajectory toward the safe set while avoiding unwanted sets. To deal with the tracking problem, the Hamilton-Jacobi-Bellman (HJB) framework is used through the actor-critic MNN-based backstepping technique to estimate the solution of the value …

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Cascading Of 2d And 3d Simulations Of Asic Substrate Interconnect Up To 100 Ghz, Zhekun Peng, Junyong Park, Sathvika Bandi, Santosh Pappu, Srinivas Venkataraman, Xu Wang, Granthana Ranzaswamy, Donghyun Kim Jan 2024

Cascading Of 2d And 3d Simulations Of Asic Substrate Interconnect Up To 100 Ghz, Zhekun Peng, Junyong Park, Sathvika Bandi, Santosh Pappu, Srinivas Venkataraman, Xu Wang, Granthana Ranzaswamy, Donghyun Kim

Electrical and Computer Engineering Faculty Research & Creative Works

A method of cascading 3D models and 2D models to model the full channel of ASIC package substrate interconnects is proposed, showing good match to full-wave results in S-parameter and TDR up to 100 GHz.

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Impact Of Non-Functional Pads Location On Eye Diagram Performance, Mehdi Mousavi, Kevin Cai, Junyong Park, Chaofeng Li, Manish K. Mathew, Reza Asadi, Shameem Ahmed, Donghyun Kim, Bidyut Sen Jan 2024

Impact Of Non-Functional Pads Location On Eye Diagram Performance, Mehdi Mousavi, Kevin Cai, Junyong Park, Chaofeng Li, Manish K. Mathew, Reza Asadi, Shameem Ahmed, Donghyun Kim, Bidyut Sen

Electrical and Computer Engineering Faculty Research & Creative Works

This study shows that placing four NFPs in selective PCB layers significantly improves signal integrity, reducing minimum jitter from 18.28 ps to 12.81 ps and maximum jitter from 27.66 ps to 22.03 ps.

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Rapid Control Prototyping Platform For Grid Connected Electrical Energy Conversion Systems, Shruti Pandey, Noah Damron, Michael Mcintyre Jan 2024

Rapid Control Prototyping Platform For Grid Connected Electrical Energy Conversion Systems, Shruti Pandey, Noah Damron, Michael Mcintyre

Electrical and Computer Engineering Faculty Research & Creative Works

Electrical Energy Conversion Systems (EECSs) are extensively utilized in contemporary stand-alone systems to supply power to isolated loads. They are also integrated into distributed generation systems, micro grids, and smart grids. In each of these contexts, it is essential to conduct efficient energy management procedures to optimize the electrical energy systems output and ensure the effective and high-quality delivery of electric energy to consumers. To create the energy management system for such a system, careful consideration must be given to the configuration of the power conversion and conditioning system, as well as the specific hardware devices that make up this …

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Variation-Aware Non-Linear Mapping For Honey-Memristor Based Neuromorphic System, Harshvardhan Uppaluru, Md Mehedi Hasan Tanim, Md Omar Faruque, Mohammed Rafeeq Khan, Zoe Templin, Feng Zhao, Jinhui Wang Jan 2024

Variation-Aware Non-Linear Mapping For Honey-Memristor Based Neuromorphic System, Harshvardhan Uppaluru, Md Mehedi Hasan Tanim, Md Omar Faruque, Mohammed Rafeeq Khan, Zoe Templin, Feng Zhao, Jinhui Wang

Electrical and Computer Engineering Faculty Research & Creative Works

Natural organic memristors are promising synapse candidates for neuromorphic systems due to their significant benefits, such as environmental sustainability, low production and disposal cost, non-volatile storage capability, and bio/CMOS-compatibility. In this paper, experimental evaluations of a neuromorphic system based on honey-memristors are reported. First, honey-memristors are manufactured and tested based on our in-house technology, and then the non-linear characteristics inherent to honey-memristors, which causes inaccurate weight updates and reduces the inference accuracy, are explored. A non-linear mapping (NMP) method is applied to mitigate the effects of non-linearity in honey-memristor, under different scenarios including multiple cycle-to-cycle variations and Analog-to-Digital Converter (ADC) …

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Profitability Analysis Of Time-Restricted Double-Spending Attack On Pow-Based Large Scale Blockchains With The Aid Of Multiple Attacks, Yiming Jiang, Jiangfan Zhang Jan 2024

Profitability Analysis Of Time-Restricted Double-Spending Attack On Pow-Based Large Scale Blockchains With The Aid Of Multiple Attacks, Yiming Jiang, Jiangfan Zhang

Electrical and Computer Engineering Faculty Research & Creative Works

We consider the time-restricted double-spending attack (TR-DSA) on the Proof-of-Work-based blockchain, where an adversary conducts a DSA within a finite timeframe and simultaneously launches multiple types of attacks on the blockchain. To be specific, the adversary can conduct attacks to isolate some honest miners and cause block propagation delays among miners to enhance the success probability of the TR-DSA. We first develop the closed-form expression for the success probability of a TR-DSA with the aid of multiple types of attacks, which is leveraged to develop the closed-form expression for the expected profit of a TR-DSA. The numerical analysis reveals that …

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Frequency Division Multiplexing And Random Phasing For Improved Uniformity In Microwave Heating Applications, Logan M. Wilcox, Ali Mirala, Mohammad Tayeb Al Qaseer, Kristen M. Donnell Jan 2024

Frequency Division Multiplexing And Random Phasing For Improved Uniformity In Microwave Heating Applications, Logan M. Wilcox, Ali Mirala, Mohammad Tayeb Al Qaseer, Kristen M. Donnell

Electrical and Computer Engineering Faculty Research & Creative Works

Microwave heating has been recently used as an active thermal excitation method in thermography. Within the nondestructive testing and evaluation (NDT&E) realm, this method is referred to as active microwave thermography, or AMT. In AMT, unlike other thermal excitation methods utilized in thermography, microwave heating inherently provides a nonuniform heating pattern. This is a direct result of the radiating antenna used to deliver the energy. This nonuniform pattern may result in defect detection errors (i.e., false positives and/or negatives). To reduce this potential for detection error and improve the overall robustness of the technique, a new electromagnetic system, consisting of …

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High-Sensitivity Fabry-Perot Interferometric Sensor Based On Microwave Photonics With Phase Demodulation, Ruimin Jie, Hongkun Zheng, Osamah Alsalman, Jie Huang, Chen Zhu Jan 2024

High-Sensitivity Fabry-Perot Interferometric Sensor Based On Microwave Photonics With Phase Demodulation, Ruimin Jie, Hongkun Zheng, Osamah Alsalman, Jie Huang, Chen Zhu

Electrical and Computer Engineering Faculty Research & Creative Works

Optical fiber sensors have emerged as vital tools in various applications. Among them, Fabry-Perot interferometers (FPIs), have gained prominence due to their compactness and versatility in sensor design. Microwave photonics (MWP) techniques offer enhanced performance and flexibility for developing optical sensor interrogation methods. This paper proposes and experimentally demonstrates a novel MWP interrogation technique based on phase measurement for short-cavity FPI sensors. The technique utilizes the phase response of the FPI sensor within an MWP-assisted single radio frequency bandpass filter, providing improved sensitivity and dynamic sensing capabilities compared to traditional methods. Simulation and experimental results validate the effectiveness of the …

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Lidar From The Sky: Uav Integration And Fusion Techniques For Advanced Traffic Monitoring, Baya Cherif, Hakim Ghazzai, Ahmad Alsharoa Jan 2024

Lidar From The Sky: Uav Integration And Fusion Techniques For Advanced Traffic Monitoring, Baya Cherif, Hakim Ghazzai, Ahmad Alsharoa

Electrical and Computer Engineering Faculty Research & Creative Works

Light detection and ranging (LiDAR) technology's expansion within the autonomous vehicles industry has rapidly motivated its application in numerous growing areas, such as smart cities, agriculture, and renewable energy. In this article, we propose an innovative approach for enhancing aerial traffic monitoring solutions through the application of LiDAR technology. The objective is to achieve precise and real-time object detection and tracking from aerial perspectives by integrating unmanned aerial vehicles with LiDAR sensors, thereby creating a potent Aerial LiDAR (A-LiD) solution for traffic monitoring. First, we develop a novel deep learning algorithm based on pointvoxel-region-based convolutional neural network (RCNN) to conduct …

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Effect Of Signal Modulation On Active Microwave Thermography, Logan M. Wilcox, Mathias Bonmarin, Kristen M. Donnell Jan 2024

Effect Of Signal Modulation On Active Microwave Thermography, Logan M. Wilcox, Mathias Bonmarin, Kristen M. Donnell

Electrical and Computer Engineering Faculty Research & Creative Works

Active microwave thermography (AMT) is a coupled electromagnetic and thermographic nondestructive testing and evaluation (NDT&E) technique. AMT utilizes an active electromagnetic source to induce heat on or within a specimen under test (SUT) with subsequential infrared measurements via an infrared camera. AMT has been successfully employed in multiple fields, including aerospace, space, and infrastructure, among others. Generally, for AMT, the excitation (electromagnetic source) is applied over a specified period of time (referred to as the heating time). If inspection continues for additional time after the excitation is removed (turned off), this period is referred to as the cooling time. This …

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Recent Progress In Microrna Detection Using Integrated Electric Fields And Optical Detection Methods, Logeeshan Velmanickam, Dharmakeerthi Nawarathna Jan 2024

Recent Progress In Microrna Detection Using Integrated Electric Fields And Optical Detection Methods, Logeeshan Velmanickam, Dharmakeerthi Nawarathna

Electrical & Computer Engineering Faculty Publications

Low-cost, highly-sensitivity, and minimally invasive tests for the detection and monitoring of life-threatening diseases and disorders can reduce the worldwide disease burden. Despite a number of interdisciplinary research efforts, there are still challenges remaining to be addressed, so clinically significant amounts of relevant biomarkers in body fluids can be detected with low assay cost, high sensitivity, and speed at point-of-care settings. Although the conventional proteomic technologies have shown promise, their ability to detect all levels of disease progression from early to advanced stages is limited to a limited number of diseases. One potential avenue for early diagnosis is microRNA (miRNA). …

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Advanced Nested Coaxial Thin-Film Zno Nanostructures Synthesized By Atomic Layer Deposition For Improved Sensing Performance, Pengtao Lin, Lari S. Zhang, Kai Zhang, Helmut Baumgart Jan 2024

Advanced Nested Coaxial Thin-Film Zno Nanostructures Synthesized By Atomic Layer Deposition For Improved Sensing Performance, Pengtao Lin, Lari S. Zhang, Kai Zhang, Helmut Baumgart

Electrical & Computer Engineering Faculty Publications

We report a new synthesis method for multiple-walled nested thin-film nanostructures by combining hydrothermal growth methods with atomic layer deposition (ALD) thin-film technology and sacrificial films, thereby increasing the surface-to-volume ratio to improve the sensing performance of novel ZnO gas sensors. Single-crystal ZnO nanorods serve as the core of the nanostructure assembly and were synthesized hydrothermally on fine-grained ALD ZnO seed films. Subsequently, the ZnO core nanotubes were coated with alternating sacrificial coaxial 3D wrap-around ALD Al2O3 films and ALD ZnO films. Basically, the center nanorod was coated with an ALD 3D wrap-around Al₂O₃ sacrificial layer to realize a nested …

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Neurosymbolic Value-Inspired Ai (Why, What, And How), Amit Sheth, Kaushik Roy Jan 2024

Neurosymbolic Value-Inspired Ai (Why, What, And How), Amit Sheth, Kaushik Roy

Publications

The rapid progression of Artificial Intelligence (AI) systems, facilitated by the advent of Large Language Models (LLMs), has resulted in their widespread application to provide human assistance across diverse industries. This trend has sparked significant discourse centered around the ever-increasing need for LLM-based AI systems to function among humans as part of human society, sharing human values, especially as these systems are deployed in high-stakes settings (e.g., healthcare, autonomous driving, etc.). Towards this end, neurosymbolic AI systems are attractive due to their potential to enable easy-tounderstand and interpretable interfaces for facilitating valuebased decision-making, by leveraging explicit representations of shared values. …

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K-Perm: Personalized Response Generation Using Dynamic Knowledge Retrieval And Persona-Adaptive Queries, Kanak Raj, Kaushik Roy, Vamshi Bonagiri, Priyanshul Govil, Krishnaprasad Thirunarayan, Raxit Goswami, Manas Gaur Jan 2024

K-Perm: Personalized Response Generation Using Dynamic Knowledge Retrieval And Persona-Adaptive Queries, Kanak Raj, Kaushik Roy, Vamshi Bonagiri, Priyanshul Govil, Krishnaprasad Thirunarayan, Raxit Goswami, Manas Gaur

Publications

Personalizing conversational agents can enhance the quality of conversations and increase user engagement. However, they often lack external knowledge to tend to a user’s persona appropriately. This is particularly crucial for practical applications like mental health support, nutrition planning, culturally sensitive conversations, or reducing toxic behavior in conversational agents. To enhance the relevance and comprehensiveness of personalized responses, we propose using a two-step approach that involves (1) selectively integrating user personas and (2) contextualizing the response with supplementing information from a background knowledge source. We develop K-PERM (Knowledge-guided PErsonalization with Reward Modulation), a dynamic conversational agent that combines these elements. …

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Causal Event Graph-Guided Language-Based Spatiotemporal Question Answering, Kaushik Roy, Alessandro Oltramari, Yuxin Zi, Chathurangi Shyalika, Vignesh Narayanan, Amit Sheth Jan 2024

Causal Event Graph-Guided Language-Based Spatiotemporal Question Answering, Kaushik Roy, Alessandro Oltramari, Yuxin Zi, Chathurangi Shyalika, Vignesh Narayanan, Amit Sheth

Publications

Large Language Models have excelled at encoding and leveraging language patterns in large text-based corpora for various tasks, including spatiotemporal event-based question answering (QA). However, due to encoding a text-based projection of the world, they have also been shown to lack a fullbodied understanding of such events, e.g., a sense of intuitive physics, and cause-and-effect relationships among events. In this work, we propose using causal event graphs (CEGs) to enhance language understanding of spatiotemporal events in language models, using a novel approach that also provides proofs for the model’s capture of the CEGs. A CEG consists of events denoted by …

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Exploring Alternative Approaches To Language Modeling For Learning From Data And Knowledge, Yuxin Zi, Kaushik Roy, Vignesh Narayanan, Amit Sheth Jan 2024

Exploring Alternative Approaches To Language Modeling For Learning From Data And Knowledge, Yuxin Zi, Kaushik Roy, Vignesh Narayanan, Amit Sheth

Publications

Despite their wide applications to language understanding tasks, large language models (LLMs) still face challenges such as hallucinations - the occasional fabrication of information, and alignment issues - the lack of associations with human-curated world models (e.g., intuitive physics or common-sense knowledge). Additionally, the black-box nature of LLMs makes it highly challenging to train them meaningfully in order to achieve a desired behavior. Specifically, the attempt to adjust LLMs’ concept embedding spaces can be highly intractable, which involves analyzing the implicit impact on LLMs’ numerous parameters and the resulting inductive biases. This paper proposes a novel architecture that wraps powerful …

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Tutorial: Knowledge-Infused Artificial Intelligence For Mental Healthcare, Kaushik Roy Jan 2024

Tutorial: Knowledge-Infused Artificial Intelligence For Mental Healthcare, Kaushik Roy

Publications

Artificial Intelligence (AI) systems for mental healthcare (MHCare) have been ever-growing after realizing the importance of early interventions for patients with chronic mental health (MH) conditions. Social media (SocMedia) emerged as the go-to platform for supporting patients seeking MHCare. The creation of peer-support groups without social stigma has resulted in patients transitioning from clinical settings to SocMedia supported interactions for quick help. Researchers started exploring SocMedia content in search of cues that showcase correlation or causation between different MH conditions to design better interventional strategies. User-level Classification-based AI systems were designed to leverage diverse SocMedia data from various MH conditions, …

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Ai Trustworthy: Ethical Challenges And Strategies, Jian Liu, Iwan Sandjaja, Donald C. Wunsch Jan 2024

Ai Trustworthy: Ethical Challenges And Strategies, Jian Liu, Iwan Sandjaja, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

This paper explores the pivotal role of trust in the widespread application of Artificial Intelligence (AI) across various domains. We review AI applications in sectors like energy, healthcare, and autonomous vehicles and discuss the crisis of human trust they face. This paper introduces a novel framework that delineates the relationship between AI transparency and user trust, highlighting specific industry applications. Through a systematic review of recent literature, we first delve into factors such as emotional response, acceptance, transparency, accuracy, and interpretability that shape human trust in AI. We then underscore the necessity of ethical AI practices and highlight the importance …

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Designing High-Performance Identity-Based Quantum Signature Protocol With Strong Security, Sunil Prajapat, Pankaj Kumar, Sandeep Kumar, Ashok Kumar Das, Sachin Shetty, M. Shamim Hossain Jan 2024

Designing High-Performance Identity-Based Quantum Signature Protocol With Strong Security, Sunil Prajapat, Pankaj Kumar, Sandeep Kumar, Ashok Kumar Das, Sachin Shetty, M. Shamim Hossain

VMASC Publications

Due to the rapid advancement of quantum computers, there has been a furious race for quantum technologies in academia and industry. Quantum cryptography is an important tool for achieving security services during quantum communication. Designated verifier signature, a variant of quantum cryptography, is very useful in applications like the Internet of Things (IoT) and auctions. An identity-based quantum-designated verifier signature (QDVS) scheme is suggested in this work. Our protocol features security attributes like eavesdropping, non-repudiation, designated verification, and hiding sources attacks. Additionally, it is protected from attacks on forgery, inter-resending, and impersonation. The proposed scheme benefits from the traditional designated …

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Embedding Software Engineering In Mixed Methods: Computationally Enhanced Risk Communication, Ann Marie Reinhold, Madison H. Munro, Elizabeth A. Shanahan, Ross J. Gore, Barry C. Ezell, Clemente I. Izurieta Jan 2024

Embedding Software Engineering In Mixed Methods: Computationally Enhanced Risk Communication, Ann Marie Reinhold, Madison H. Munro, Elizabeth A. Shanahan, Ross J. Gore, Barry C. Ezell, Clemente I. Izurieta

VMASC Publications

Mixed methods research ameliorates many convergent research challenges within the contemporary sociotechnical landscape. We suggest the integration of software engineering in mixed methods studies is a critical step to address some of the remaining and persistent challenges. One such research challenge where software engineering is particularly well suited is in hazard preparedness—in particular, the creation of risk communication messages to mitigate or prevent harm. Computationally enhanced risk communication is convergent research that integrates software engineering and social science research for the benefit of protecting humans and infrastructure. To this end, we developed a mixed methods framework for the efficient construction …

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Kinetic Simulations Of Dust Grain Charging Near Surfaces Under Various Plasma Conditions, David Lund, Daoru Han Jan 2024

Kinetic Simulations Of Dust Grain Charging Near Surfaces Under Various Plasma Conditions, David Lund, Daoru Han

Mechanical and Aerospace Engineering Faculty Research & Creative Works

This paper presents fully kinetic numerical investigations of the charging of spherical and irregular shaped dust grains in multiple configurations utilizing the Parallel Immersed-Finite-Element Particle-in-Cell Dusty (PIFE-PIC-D) framework. The simulations account for both surface charging and in-depth charging of the dust grains immersed in various ambient plasma conditions near a floating or biased surface. PIFE-PIC-D explicitly resolves the geometrical and material properties (permittivity and photoelectron emissions) of each individual dust grain. PIFE-PIC-D will model self-consistently the unsteady and stochastic charging of grains directly from the deposition of electrons and ions onto them. PIFE-PIC-D will also simulate the charging of irregular-shaped …

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L∞ Bounds For Transient Growth In Repetitive And Iterative Learning Control Systems, Douglas A. Bristow, John R. Singler Jan 2024

L∞ Bounds For Transient Growth In Repetitive And Iterative Learning Control Systems, Douglas A. Bristow, John R. Singler

Mechanical and Aerospace Engineering Faculty Research & Creative Works

This paper revisits the problem of large transient growth in Iterative Learning Control (ILC) and Repetitive Process Control (RPC) systems. In ILC and RPC problems a process is repeated iteratively, with new control calculations occurring in between each iteration. Large transient growth refers to the propensity of some control algorithms to grow error exponentially before eventually converging. While robust monotonic convergence algorithms (in which monotonic convergence is guaranteed usually in exchange for a small loss in performance) have largely eliminated the concern for large transient growth in ILC, similar results cannot always be obtained in RPC. The emergence of additive …

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Development Of Digital Twin For Fdm Printer With Preventive Cyber-Attack And Control Algorithms, Md Hazrat Ali, Asad Malik, Nursultan Jyeniskhan, Muhammad Arif Mahmood, Essam Shehab, Frank Liou Jan 2024

Development Of Digital Twin For Fdm Printer With Preventive Cyber-Attack And Control Algorithms, Md Hazrat Ali, Asad Malik, Nursultan Jyeniskhan, Muhammad Arif Mahmood, Essam Shehab, Frank Liou

Mechanical and Aerospace Engineering Faculty Research & Creative Works

This paper presents a developed model of a Digital Twin (DT) for a fused deposition modeling (FDM) printer, real-time defect detection, and proposed frameworks for preventing cyber-attacks in real-time. It also highlights a model predictive control (MPC) algorithm for controlling the material feed based on a real-time feedback system. The system is designed and developed based on DT, and MPC with integrated machine learning (ML) algorithms to establish real-time process control and enhance the safety and reliability of the physical plant. ML algorithm is used for anomaly detection based on the convolutional neural network (CNN) model. The developed system can …

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Quantifying The Impact Of A Constructed Wetland On Downstream Nitrate Concentrations And Loads In The U.S. Midwest, Elliot Anderson, Keith E. Schilling, Craig L. Just, Bong Chul Seo Jan 2024

Quantifying The Impact Of A Constructed Wetland On Downstream Nitrate Concentrations And Loads In The U.S. Midwest, Elliot Anderson, Keith E. Schilling, Craig L. Just, Bong Chul Seo

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Constructed wetlands are standard conservation practices used to reduce nitrate loads in agricultural watersheds. Many studies have examined the efficiency of denitrification in wetlands under various scenarios, but quantifying the watershed-scale impact of wetlands on downstream nitrate levels is rarely done using field observations. In this study, we estimated nitrate removal in a constructed wetland in the headwaters of Mud Creek, a HUC12 watershed in eastern Iowa, from May–September 2022 and May–September 2023 (a ten-month period). We also measured nitrate loads at four successive downstream sites, three along Mud Creek and one below its confluence with the larger Cedar River. …

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