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2022

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A Fast Cascading Method For Predicting The Coupling From External Plane Waves To Pcbs, Shengxuan Xia, James Hunter, Aaron Harmon, Mohamed Z.M. Hamdalla, Ahmed M. Hassan, Chulsoon Hwang, Victor Khilkevich, Daryl G. Beetner Jan 2022

A Fast Cascading Method For Predicting The Coupling From External Plane Waves To Pcbs, Shengxuan Xia, James Hunter, Aaron Harmon, Mohamed Z.M. Hamdalla, Ahmed M. Hassan, Chulsoon Hwang, Victor Khilkevich, Daryl G. Beetner

Electrical and Computer Engineering Faculty Research & Creative Works

The radio frequency (RF) coupling to electronic devices impacts their EMC performance. The functionalities of a working electronic device may be disrupted when the electromagnetic (EM) coupling reaches a certain level. Studies of the EM coupling to printed circuit boards (PCBs) are therefore essential for RF susceptibility and EMC purposes. For decades, researchers focused on the analytical modeling of EM coupling to transmission lines. However, when it comes to more realistic PCBs the analysis usually still relies heavily on full-wave simulations because of the complexity of the structures and the lack of analytical solutions. Using a traditional full-wave modeling approach, …

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A Practical Simulation Flow For Singing Capacitor Based Acoustic Noise Analysis, Xin Yan, Songping Wu, Mingfeng Xue, Chi Kin Benjamin Leung, Daryl G. Beetner, Jianmin Zhang Jan 2022

A Practical Simulation Flow For Singing Capacitor Based Acoustic Noise Analysis, Xin Yan, Songping Wu, Mingfeng Xue, Chi Kin Benjamin Leung, Daryl G. Beetner, Jianmin Zhang

Electrical and Computer Engineering Faculty Research & Creative Works

Multilayer ceramic capacitors (MLCCs) are widely used in modern electronics. Due to the piezoelectric effect of the ceramic material, however, MLCCs subjected to electrical noise may vibrate and generate acoustic noise, as 'singing'. Acoustic noise can be annoying for users, especially within mobile devices, so it becomes important to perform acoustic noise analysis before a product is released. In this paper, a practical simulation flow for singing capacitor based acoustic noise is presented. The simulation flow and analysis method are developed on Ansys Sherlock and Mechanical. In Ansys Sherlock, local library and Approved Vendor List (AVL) files were used to …

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Optimizing The Placement Of Non-Functional Pads On Signal Vias Using Multiple Reflection Analysis, Muqi Ouyang, Kevin Cai, Chaofeng Li, Anna Gao, Felen Fu, Hannah Bian, Bidyut Sen, Donghyun Kim Jan 2022

Optimizing The Placement Of Non-Functional Pads On Signal Vias Using Multiple Reflection Analysis, Muqi Ouyang, Kevin Cai, Chaofeng Li, Anna Gao, Felen Fu, Hannah Bian, Bidyut Sen, Donghyun Kim

Electrical and Computer Engineering Faculty Research & Creative Works

In this study, the effects of using non-functional pads to optimize the performance of high-speed signal vias are investigated based on multiple reflection analysis. The non-functional pads on signal vias introduce more capacitive coupling and are possible to improve the response of the via structure if the original via has relatively larger impedance compared to the system reference impedance. The effectiveness of the non-functional pad optimization is validated through a numerical example, and the eye diagram of the via structure without and with non-functional pads are compared. The eye opening becomes 5.4 times larger after the via optimization using non-functional …

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A Methodical Approach For Pcb Pdn Decoupling Minimizing Overdesign With Genetic Algorithm Optimization, F. De Paulis, Y. Ding, M. Cocchini, Chulsoon Hwang, S. Connor, M. Doyle, S. Scearce, W. D. Becker, Albert E. Ruehli, James L. Drewniak Jan 2022

A Methodical Approach For Pcb Pdn Decoupling Minimizing Overdesign With Genetic Algorithm Optimization, F. De Paulis, Y. Ding, M. Cocchini, Chulsoon Hwang, S. Connor, M. Doyle, S. Scearce, W. D. Becker, Albert E. Ruehli, James L. Drewniak

Electrical and Computer Engineering Faculty Research & Creative Works

An optimization routine is applied for the decoupling capacitor placement on Power Distribution Networks to identify the limit beyond which the placement of additional decaps is no longer effective, thus leading to wasting layout area and components, and to a cost increase. A specific test example from a real design is used together with the required target impedance and frequency band of interest for the PDN design. The effectiveness of the decap placement while selecting different layers of the stack-up, and while moving the upper limit of the PDN design band is analyzed. Such analysis leads to helpful insights based …

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Physics-Based Modeling For Determining Transient Current Flow In Multi-Layer Pcb Pi Designs, Yifan Ding, Matthew S. Doyle, Samuel Connor, Dale Becker, James L. Drewniak Jan 2022

Physics-Based Modeling For Determining Transient Current Flow In Multi-Layer Pcb Pi Designs, Yifan Ding, Matthew S. Doyle, Samuel Connor, Dale Becker, James L. Drewniak

Electrical and Computer Engineering Faculty Research & Creative Works

A physics-based modeling methodology for determining the transient current flow path in multi-layer PI designs is given in this paper using a commercial board with a complicated structure as an example. Board structure analysis is done first to provide a physical basis of post-layout analytical and equivalent circuit modeling. A match of the PDN impedance between commercial tool simulation, post-layout analytical calculation, and the physics-based equivalent circuit modeling was achieved to support the model for the transient simulation. By analyzing the current response in all the vias, a clear representation of transient current flow across all via segments can be …

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Identifying Sources Of Conducted Emissions By Measuring The Coherence Function, Xin Yan, Fuwei Ma, Wei Zhang, Kaustav Ghosh, Sameer Walunj, Philippe Sochoux, Victor Khilkevich Jan 2022

Identifying Sources Of Conducted Emissions By Measuring The Coherence Function, Xin Yan, Fuwei Ma, Wei Zhang, Kaustav Ghosh, Sameer Walunj, Philippe Sochoux, Victor Khilkevich

Electrical and Computer Engineering Faculty Research & Creative Works

Conducted emissions (CE) is one of the electromagnetic interference (EMI) issues that pose serious compliance problems for electronic devices. For a system with several sources, estimating the contribution of each source to conducted emission at different frequencies can be a challenge. In this article, a coherence function-based signal separation method is presented and validated on two commercial power supply units (PSU). The noise generated by the PSU and measured at the line impedance stabilization network (LISN) port contains two predominantly uncorrelated signals associated with the power factor correction (PFC) and H -bridge/rectifier circuits with unknown contributions at different frequencies. Two …

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Incremental Cluster Validity Index-Guided Online Learning For Performance And Robustness To Presentation Order, Leonardo Enzo Brito Da Silva, Nagasharath Rayapati, Donald C. Wunsch Jan 2022

Incremental Cluster Validity Index-Guided Online Learning For Performance And Robustness To Presentation Order, Leonardo Enzo Brito Da Silva, Nagasharath Rayapati, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

In streaming data applications, the incoming samples are processed and discarded, and therefore, intelligent decision-making is crucial for the performance of lifelong learning systems. In addition, the order in which the samples arrive may heavily affect the performance of incremental learners. The recently introduced incremental cluster validity indices (iCVIs) provide valuable aid in addressing such class of problems. Their primary use case has been cluster quality monitoring; nonetheless, they have been recently integrated in a streaming clustering method. In this context, the work presented, here, introduces the first adaptive resonance theory (ART)-based model that uses iCVIs for unsupervised and semi-supervised …

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A Meander Line-Based Frequency Selective Surface For Strain Sensing, Swathi Muthyala Ramesh, Kristen M. Donnell Jan 2022

A Meander Line-Based Frequency Selective Surface For Strain Sensing, Swathi Muthyala Ramesh, Kristen M. Donnell

Electrical and Computer Engineering Faculty Research & Creative Works

Frequency selective surfaces (FSSs) are periodic arrays of conductive elements that have distinct reflection and transmission responses. In this work, an FSS sensor designed to operate in Ka-band to measure a wide range of uni-directional strain using a meander line-based unit cell is presented. Specifically, the proposed unit cell of the sensor consists of a convoluted meander line geometry designed on a thin dielectric substrate. Strain sensing is achieved by monitoring the change in the resonant frequency of the FSS when under strain that is parallel to an interrogating signal linearly polarized and aligned with the convoluted dimension of the …

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Influence Of Conformal Coatings On The Emc Performance Of A Printed Circuit Board, Haran Manoharan, Ruijie He, Fuwei Ma, Daryl G. Beetner, Brian Booth, Kerry Martin Jan 2022

Influence Of Conformal Coatings On The Emc Performance Of A Printed Circuit Board, Haran Manoharan, Ruijie He, Fuwei Ma, Daryl G. Beetner, Brian Booth, Kerry Martin

Electrical and Computer Engineering Faculty Research & Creative Works

Conformal coatings are often applied to printed circuit boards to protect the board and its components from environmental factors like moisture, chemicals, and vibration. The impact of a conformal coating on crosstalk and radiated emissions was studied in the following paper. Two coating materials were characterized in terms of their permittivity and permeability. The impact of the conformal coating was evaluated based on the crosstalk between microstrip traces, the radiated emissions from a switch-mode power supply (SMPS), and on coupling from an EMI filter to nearby components. The coatings increased crosstalk between microstrip traces by up to 5 ~ 6 …

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Modeling Of Rf Interference Caused By Solid-State Drive Noise, Junho Joo, Woncheol Song, Taelim Song, Sunkyu Kong, Jungcheol Lim, Inmyung Song, Jongjoo Lee, Chulsoon Hwang Jan 2022

Modeling Of Rf Interference Caused By Solid-State Drive Noise, Junho Joo, Woncheol Song, Taelim Song, Sunkyu Kong, Jungcheol Lim, Inmyung Song, Jongjoo Lee, Chulsoon Hwang

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, modeling of RFI problem caused by a solid-state drive (SSD) in a laptop is proposed. Two noise sources (one outside and one inside a cavity) in the SSD are reconstructed as dipole moments with magnitude-only near-field scanning data. The dipole moment inside a cavity is then replaced by a Huygens' box covering four side surfaces of the cavity using a numerical simulation. The noise voltage at an RF antenna port is calculated by combining the two reconstructed noise sources with measured transfer functions. The model is successfully validated through a comparison of the calculation with measurement results.

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Insertion Loss Reduction Using Rounded Corners To Mitigate Surface Roughness Effect In Pcb Transmission Lines, Yuandong Guo, Donghyun Kim, Yuanzhuo Liu, Xiaoning Ye, Jimmy Hsu, Jun Fan Jan 2022

Insertion Loss Reduction Using Rounded Corners To Mitigate Surface Roughness Effect In Pcb Transmission Lines, Yuandong Guo, Donghyun Kim, Yuanzhuo Liu, Xiaoning Ye, Jimmy Hsu, Jun Fan

Electrical and Computer Engineering Faculty Research & Creative Works

Signal integrity (SI) can be interpreted as a measure of the distortion of the incident pulse, which is attributed to various contributors, e.g., inter-symbol interference (ISI), crosstalk, jitter, etc. The channel insertion loss is generally the most critical concern in SI designs, since it determines the working bandwidth of a high-speed channel, and the bandlimited channels are known as the root cause of ISI. At the tens of Gigabit rates in use today, PCB transmission lines may have appreciable losses, which can be divided into frequency-dependent dielectric loss and conductor loss, and noticeable amount of losses can be generated at …

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Concurrent Learning-Based Neuro-Adaptive Robust Tracking Control Of Wheeled Mobile Robot: An Event-Triggered Design, Krishanu Nath, Manas Kumar Bera, Sarangapani Jagannathan Jan 2022

Concurrent Learning-Based Neuro-Adaptive Robust Tracking Control Of Wheeled Mobile Robot: An Event-Triggered Design, Krishanu Nath, Manas Kumar Bera, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, an event-based neuro-adaptive robust tracking controller for a perturbed and networked differential drive mobile robot (DMR) is designed with concurrent learning. A radial basis function neural network, which approximates an unknown perturbation, is used to design an adaptive sliding mode controller (SMC). The RBFNN weights and SMC parameters are estimated online using an adaptive tuning law to ensure performance with reduced chattering. To improve the convergence of RBFNN weight estimation error, a concurrent learning-based adaptive law is derived, which uses measured online and recorded data. Further, a suitable triggering condition is designed to achieve a reduced number …

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An Energy-Efficient Internet Of Things Relaying System For Delay-Constrained Applications, Abdullah M. Almasoud, Ahmad Alsharoa, Daji Qiao, Ahmed E. Kamal Jan 2022

An Energy-Efficient Internet Of Things Relaying System For Delay-Constrained Applications, Abdullah M. Almasoud, Ahmad Alsharoa, Daji Qiao, Ahmed E. Kamal

Electrical and Computer Engineering Faculty Research & Creative Works

The emerging Internet-of-things (IoT) systems contain a large number of small wireless devices with limited energy, communication, and computational capabilities. In such systems, a helping station located between the IoT devices and backhaul servers can be deployed to broadcast the IoT devices to the backhaul networks. This paper investigates a hybrid energy-efficient framework using multiple energy harvested relays with data buffering capabilities. The relays are powered by a hybrid energy supply consisting of a traditional electric grid and renewable energy grid. We propose an energy efficient novel approach aiming to support the wireless uplink transmission from IoT devices to backhaul …

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Pulsed-Active Microwave Thermography, Logan M. Wilcox, Mathias Bonmarin, Kristen M. Donnell Jan 2022

Pulsed-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 thermographic nondestructive testing and evaluation technique that utilizes an electromagnetic-based excitation with a subsequent infrared measurement of the surface thermal profile of the material or structure of interest. AMT has been successfully applied to several aerospace and civil infrastructure applications. This work seeks to expand the performance of AMT by incorporating a signal processing technique common to traditional (flash-lamp) thermography, referred to as pulsed thermography (PT). PT operates on the premise of a pulsed excitation, as opposed to a constant or step excitation (ST) over a given time-period that is typical to traditional active …

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Generation Expansion Planning Considering Discrete Storage Model And Renewable Energy Uncertainty: A Bi-Interval Optimization Approach, Siyuan Wang, Guangchao Geng, Qy Jiang, Rui Bo Jan 2022

Generation Expansion Planning Considering Discrete Storage Model And Renewable Energy Uncertainty: A Bi-Interval Optimization Approach, Siyuan Wang, Guangchao Geng, Qy Jiang, Rui Bo

Electrical and Computer Engineering Faculty Research & Creative Works

Both discrete storage model (DSM) and continuous storage model (CSM) have been used in the power system planning literature. In this work, we conduct a sizing-error analysis for the use of CSM in generation expansion planning (GEP), which shows more reasonable storage sizing decisions are offered by the DSM in comparison to the CSM. However, when the DSM is considered in the context of interval optimization, the discrete status variables in mutually exclusive constraints and the strong temporal coupling in state-of-charge (SOC) constraints create significant challenges. To tackle this, a tailored interval optimization approach is proposed to consider both DSM …

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A New Discontinuous Conduction Mode In A Transformer Coupled High Gain Dc-Dc Converter, Kartikeya J.P. Veeramraju, Jacob Eisen, Joshua L. Rovey, Jonathan W. Kimball Jan 2022

A New Discontinuous Conduction Mode In A Transformer Coupled High Gain Dc-Dc Converter, Kartikeya J.P. Veeramraju, Jacob Eisen, Joshua L. Rovey, Jonathan W. Kimball

Electrical and Computer Engineering Faculty Research & Creative Works

Electrospray space propulsion thrusters often employ transformer coupled high gain dc-dc converters. These thrusters have a unique load resistance profile that can vary dramatically during operation. Transformer coupled high gain dc-dc converters working in very low power modes can enter a unique discontinuous conduction mode (DCM) caused by a coupling effect between the boost and magnetization inductors in the converter. The transformer magnetization current prevents the boost inductors from discharging properly, which causes premature loss of boost action and higher than expected boost inductor voltages. This mechanism generates abnormally high voltages on the converter's output side, leading to converter and …

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Optimal Adaptive Output Regulation Of Uncertain Nonlinear Discrete-Time Systems Using Lifelong Concurrent Learning, R. Moghadam, B. Farzanegan, S.(Sarangapani) Jagannathan, P. Natarajan Jan 2022

Optimal Adaptive Output Regulation Of Uncertain Nonlinear Discrete-Time Systems Using Lifelong Concurrent Learning, R. Moghadam, B. Farzanegan, S.(Sarangapani) Jagannathan, P. Natarajan

Electrical and Computer Engineering Faculty Research & Creative Works

This Paper Addresses Neural Network (NN) based Optimal Adaptive Regulation of Uncertain Nonlinear Discrete-Time Systems in Affine Form using Output Feedback Via Lifelong Concurrent Learning. First, an Adaptive NN Observer is Introduced to Estimate Both the State Vector and Control Coefficient Matrix, and its NN Weights Are Adjusted using Both Output Error and Concurrent Learning Term to Relax the Persistency Excitation (PE) Condition. Next, by Utilizing an Actor-Critic Framework for Estimating the Value Functional and Control Policy, the Critic Network Weights Are Tuned Via Both Temporal Different Error and Concurrent Learning Schemes through a Replay Buffer. the Actor NN Weights …

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Review Of Fiber Optic Displacement Sensors, Chen Zhu, Yiyang Zhuang, Bo Liu, Jie Huang Jan 2022

Review Of Fiber Optic Displacement Sensors, Chen Zhu, Yiyang Zhuang, Bo Liu, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

Displacement Measurements Are of Significant Importance in a Variety of Critical Scientific and Engineering Fields, Such as Gravitational Wave Detection, Geophysical Research, and Manufacturing Industries. Due to the Inherent Advantages Such as Compactness, High Sensitivity, and Immunity to Electromagnetic Interference, in Recent Years, Fiber Optic Sensors Have Been Widely Used in an Expansive Range of Sensing Applications, Ranging from Infrastructural Health Monitoring to Chemical and Biological Sensing. of Particular Interest Here, Fiber Optic Displacement Sensors Have Gained Wide Interest and Have Evolved from Basic Intensity Modulation-Based Configurations to More Advanced Structures, Such as Fiber Bragg Grating (FBG)-Based and Interferometric Configurations. …

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Message From The 2022 Program Chairs-In-Chief, Hong Va Leong, Sahra Sedigh Sarvestani, Yuuichi Teranishi Jan 2022

Message From The 2022 Program Chairs-In-Chief, Hong Va Leong, Sahra Sedigh Sarvestani, Yuuichi Teranishi

Electrical and Computer Engineering Faculty Research & Creative Works

No abstract provided.

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Temperature-Insensitive Inclinometer Based On Transmission Line Fabry-Perot Resonators, Jing Guo, Chen Zhu, Yan Tang, Jie Huang Jan 2022

Temperature-Insensitive Inclinometer Based On Transmission Line Fabry-Perot Resonators, Jing Guo, Chen Zhu, Yan Tang, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

This Article Reports a Novel Self-Compensated Inclinometer with a Wide Dynamic Range and High Measurement Resolution based on Two Hollow Coaxial Cable Fabry-Perot Resonators (HCC-FPRs). the HCC-FPR is Formed between a Metal Post that Shorts the Inner Conductor and the Outer Conductor of the HCC and the Water Level Inside the HCC. Changes in Tilt Angles Result in Variations of the Water Level in the HCC, Leading to Changes in the Cavity Length of the HCC-FPR. by Tracking the Shift of the Resonance Wavelength of the HCC-FPR, a Single HCC-FPR Can Be Used as a Sensor Device for Tilt Measurements. …

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Een 1101, Clas Jan 2022

Een 1101, Clas

Executive Actions

No abstract provided.

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Een 4301, Clas Jan 2022

Een 4301, Clas

Executive Actions

No abstract provided.

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Prediction Of Formation Conditions Of Gas Hydrates Using Machine Learning And Genetic Programming, Anupama Kumari, Mukund Madhaw, Vishnu S. Pendyala Jan 2022

Prediction Of Formation Conditions Of Gas Hydrates Using Machine Learning And Genetic Programming, Anupama Kumari, Mukund Madhaw, Vishnu S. Pendyala

Faculty Research, Scholarly, and Creative Activity

The formation of gas hydrates in the pipelines of oil, gas, chemical, and other industries has been a significant problem for many years because the formation of gas hydrates may block the pipelines. Hence, the knowledge of the phase equilibrium conditions of gas hydrate became necessary for the economic and safe working of oil, gas, chemical industries. Various thermodynamic approaches with various mathematical techniques are available for the prediction of formation conditions of gas hydrates. In this chapter, the authors have discussed the least square support vector machine and artificial neural network models for the prediction of stability conditions of …

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An Overview Of Carbon Footprint Mitigation Strategies. Machine Learning For Societal Improvement, Modernization, And Progress, Vishnu S. Pendyala, Saritha Podali Jan 2022

An Overview Of Carbon Footprint Mitigation Strategies. Machine Learning For Societal Improvement, Modernization, And Progress, Vishnu S. Pendyala, Saritha Podali

Faculty Research, Scholarly, and Creative Activity

Among the most pressing issues in the world today is the impact of globalization and energy consumption on the environment. Despite the growing regulatory framework to prevent ecological degradation, sustainability continues to be a problem. Machine learning can help with the transition toward a net-zero carbon society. Substantial work has been done in this direction. Changing electrical systems, transportation, buildings, industry, and land use are all necessary to reduce greenhouse gas emissions. Considering the carbon footprint aspect of sustainability, this chapter provides a detailed overview of how machine learning can be applied to forge a path to ecological sustainability in …

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3d-Printed Gelatin-Alginate Hydrogel Dressings For Burn Wound Healing: A Comprehensive Study, Fateme Fayyazbakhsh, Michael J. Khayat, Ming-Chuan Leu Jan 2022

3d-Printed Gelatin-Alginate Hydrogel Dressings For Burn Wound Healing: A Comprehensive Study, Fateme Fayyazbakhsh, Michael J. Khayat, Ming-Chuan Leu

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Burn Wound Treatment is Still a Clinical Challenge Due to the Severity of Tissue Damage and Dehydration. among Various Wound Dressings, Hydrogel Materials Have Gained Significant Attention for Burn Wound Treatment in Clinical Practice Due to their Soothing and Moisturizing Activity. in This Study, 3D-Printed Dressings Were Fabricated using Clinically Relevant Hydrogels for Deep Partial-Thickness Burn (PTB) Wounds. Different Ratios of Gelatin and Alginate Mixture Were 3D-Printed and Examined in Terms of Rheological Behavior, Shear Thinning Behavior, Mechanical Properties, Degradation Rate, and Hydration Activity to Tune the Hydrogel Composition for Best Functionality. the Cell-Laden Dressings Were Bioprinted to Evaluate the …

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Satellite Drag Coefficient Modeling For Thermosphere Science And Mission Operations, Piyush M. Mehta, Smriti N. Paul, Nicholas H. Crisp, Philip L. Sheridan, Christian Siemes, Günther March, Sean Bruinsma Jan 2022

Satellite Drag Coefficient Modeling For Thermosphere Science And Mission Operations, Piyush M. Mehta, Smriti N. Paul, Nicholas H. Crisp, Philip L. Sheridan, Christian Siemes, Günther March, Sean Bruinsma

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Satellite drag modeling remains the largest source of uncertainty affecting space operations in low Earth orbit. The uncertainty stems from inaccurate models for mass density and drag coefficient. Drag coefficient modeling also impacts scientific knowledge on the physics and dynamics of the upper atmosphere through the estimation of high-fidelity mass density from measurements of acceleration on-board satellites. Efforts over the last decade have pushed drag coefficient modeling in the right direction, however, have resulted in multiple methods and tools. We provide a comprehensive review of the drag coefficient modeling methods and tools. Current scale differences between thermospheric data sets mostly …

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Effects Of Wheel Rotation On Long-Period Wake Dynamics Of The Drivaer Fastback Model, Matthew Aultman, Rodrigo Auza-Gutierrez, Kevin Disotell, Lian Duan Jan 2022

Effects Of Wheel Rotation On Long-Period Wake Dynamics Of The Drivaer Fastback Model, Matthew Aultman, Rodrigo Auza-Gutierrez, Kevin Disotell, Lian Duan

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Lattice Boltzmann method (LBM) simulations were performed to capture the long-period dynamics within the wake of a realistic DrivAer fastback model with stationary and rotating wheels. The simulations showed that the wake developed as a low-pressure torus regardless of whether the wheels were rotating. This torus shrank in size on the base in the case of rotating wheels, leading to a reduction in the low-pressure footprint on the base, and consequently a 7% decrease in the total vehicle drag in comparison to the stationary wheels case. Furthermore, the lateral vortex shedding experienced a long-period switching associated with the bi-stability in …

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Efficient Routing Protection Algorithm Based On Optimized Network Topology, Haijun Geng, Zikun Jin, Jiangyuan Yao, Han Zhang, Zhiguo Hu, Bo Yang, Yingije Guo, Wei Wang, Qidong Zhang, Guoao Duan Jan 2022

Efficient Routing Protection Algorithm Based On Optimized Network Topology, Haijun Geng, Zikun Jin, Jiangyuan Yao, Han Zhang, Zhiguo Hu, Bo Yang, Yingije Guo, Wei Wang, Qidong Zhang, Guoao Duan

Faculty Research, Scholarly, and Creative Activity

Network failures are unavoidable and occur frequently. When the network fails, intra-domain routing protocols deploying on the Internet need to undergo a long convergence process. During this period, a large number of messages are discarded, which results in a decline in the user experience and severely affects the quality of service of Internet Service Providers (ISP). Therefore, improving the availability of intra-domain routing is a trending research question to be solved. Industry usually employs routing protection algorithms to improve intra-domain routing availability. However, existing routing protection schemes compute as many backup paths as possible to reduce message loss due to …

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Commuter Mobility Patterns In Social Media: Correlating Twitter And Lodes Data, Andreas Petutschnig, Jochen Albrecht, Bernd Resch, Laxmi Ramasubramanian, Aleisha Wright Jan 2022

Commuter Mobility Patterns In Social Media: Correlating Twitter And Lodes Data, Andreas Petutschnig, Jochen Albrecht, Bernd Resch, Laxmi Ramasubramanian, Aleisha Wright

Faculty Research, Scholarly, and Creative Activity

The Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics (LODES) are an important city planning resource in the USA. However, curating these statistics is resource-intensive, and their accuracy deteriorates when changes in population and urban structures lead to shifts in commuter patterns. Our study area is the San Francisco Bay area, and it has seen rapid population growth over the past years, which makes frequent updates to LODES or the availability of an appropriate substitute desirable. In this paper, we derive mobility flows from a set of over 40 million georeferenced tweets of the study area and compare them with LODES data. …

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Word Embeddings For Fake Malware Generation, Quang Duy Tran, Fabio Di Troia Jan 2022

Word Embeddings For Fake Malware Generation, Quang Duy Tran, Fabio Di Troia

Faculty Research, Scholarly, and Creative Activity

Signature and anomaly-based techniques are the fundamental methods to detect malware. However, in recent years this type of threat has advanced to become more complex and sophisticated, making these techniques less effective. For this reason, researchers have resorted to state-of-the-art machine learning techniques to combat the threat of information security. Nevertheless, despite the integration of the machine learning models, there is still a shortage of data in training that prevents these models from performing at their peak. In the past, generative models have been found to be highly effective at generating image-like data that are similar to the actual data …

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