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Identifying Design-Build Decision-Making Factors And Providing Future Research Guidelines: Social Network And Association Rule Analysis, Ramy Khalef, Islam H. El-Adaway Jan 2023

Identifying Design-Build Decision-Making Factors And Providing Future Research Guidelines: Social Network And Association Rule Analysis, Ramy Khalef, Islam H. El-Adaway

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

There is a dire need to rebuild existing infrastructure with strategic and efficient methods. Design-build (DB) becomes a potential solution that provides fast-tracked delivery as a more time and cost-efficient project delivery method. Past research studied factors influencing DB but without providing a holistic analytic approach. This paper fills this knowledge gap. First, a systematic literature review is performed using the preferred reporting items for systematic reviews and meta-analyses techniques, and a set of factors affecting DB projects are then identified and clustered, using k-means clustering, based on the whole literature discussions. Second, a graph theory approach, social network analysis …

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Assessing The Predictive Capability Of The Nno Ballistic Limit Equation For Low-Density Projectile Impact, William P. Schonberg Jan 2023

Assessing The Predictive Capability Of The Nno Ballistic Limit Equation For Low-Density Projectile Impact, William P. Schonberg

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

The design of nearly all Earth-orbiting spacecraft includes some sort of added shielding that protects the spacecraft against impacts by meteoroids and orbital debris. The effectiveness of the shielding is typically assessed using ballistic limit equations (BLEs) that are developed using data from high-speed impact tests on key spacecraft components and elements. These equations predict whether or not a particular system or structural element will sustain a critical failure following a specific impact event. As such, they are essential components of spacecraft system design as well as any quantitative spacecraft risk assessments that may need to be performed as part …

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Densifying Hydration Products Of Alite By A Bio-Inspired Admixture, Yi Fang, Jialai Wang, Liang Wang, Xin Qian, Xiaodong Wang, Wenyu Liao, Peiyuan Chen, Hongyan Ma Jan 2023

Densifying Hydration Products Of Alite By A Bio-Inspired Admixture, Yi Fang, Jialai Wang, Liang Wang, Xin Qian, Xiaodong Wang, Wenyu Liao, Peiyuan Chen, Hongyan Ma

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

A bio-inspired, plant-derived polyphenol, tannic acid (TA) was identified as a renewable admixture to improve the compressive strength of concretes. Aiming to understand the underlying mechanism responsible for this strength improvement, this study examines how TA mediates the hydration of tricalcium silicate (alite). Experimental study shows that TA can form complex with calcium ions through chelating, retarding the hydration of the alite and changing of the hydration products. Particularly, X-ray diffraction analysis shows that TA makes calcium hydroxide preferentially grow on the [0 0 1] face. Fourier-transform infrared spectroscopy and 29Si MAS NMR results reveal that the mean chain length …

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An Extendable High Step-Up Dc-Dc Converter For Renewable Energy Applications, Saeed Habibi, Ramin Rahimi, Mehdi Ferdowsi, Pourya Shamsi Jan 2023

An Extendable High Step-Up Dc-Dc Converter For Renewable Energy Applications, Saeed Habibi, Ramin Rahimi, Mehdi Ferdowsi, Pourya Shamsi

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, a high step-up DC-DC converter based on a switched-inductor-capacitor-diode (SLCD) cell is proposed. the proposed converter provides a high voltage gain, low voltage stress on the power switches and diodes, and a low input current ripple. Moreover, the proposed converter is extendable, meaning that the voltage gain could be further increased by using a higher number of proposed cells in the topology. the steady-state analysis and comparison of the proposed converter to the other existing converters are presented. a 200 W, 40 V to 380 V experimental setup is developed to verify the steady-state analysis of the …

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Small Signal Stability Analysis Of Virtual Impedance Control In Islanded Microgrid, Oroghene Oboreh-Snapps, Kartikeya J.P. Veeramraju, Arnold Fernandes, Alvaro Cardoza, Angshuman Sharma, Jonathan Saelens, Jonathan W. Kimball Jan 2023

Small Signal Stability Analysis Of Virtual Impedance Control In Islanded Microgrid, Oroghene Oboreh-Snapps, Kartikeya J.P. Veeramraju, Arnold Fernandes, Alvaro Cardoza, Angshuman Sharma, Jonathan Saelens, Jonathan W. Kimball

Electrical and Computer Engineering Faculty Research & Creative Works

This paper examines the impact of virtual impedance control in an inverter-dominated microgrid (MG) system. the goal is to provide a clear understanding of Virtual Impedance (VI) control toward MG stability. This analysis is performed by developing the system's Small-Signal Model (SSM) and studying the poles' trajectory change when the system's key control parameters are varied. the results indicate that VI will benefit system stability when considering MG with low X/R while negatively affecting MG with high X/R. Also, there is a trade-off between the coupling impedance of the inverter and the VI parameters, which needs to be considered when …

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Solving Electromagnetic Inverse Scattering Problems In Inhomogeneous Media By Deep Convolutional Encoder-Decoder Structure, Huan Huan Zhang, He Ming Yao, Lijun Jiang, Michael Ng Jan 2023

Solving Electromagnetic Inverse Scattering Problems In Inhomogeneous Media By Deep Convolutional Encoder-Decoder Structure, Huan Huan Zhang, He Ming Yao, Lijun Jiang, Michael Ng

Electrical and Computer Engineering Faculty Research & Creative Works

This communication proposes a novel deep learning (DL) approach to solve electromagnetic inverse scattering (EMIS) problems in inhomogeneous media. The conventional approaches for solving inhomogeneous EMIS problems generally have to consider inhomogeneous Green’s functions or conduct approximation operations to media, which inevitably introduces various challenges, including complex mathematical derivation, high computation cost, unavoidable nonlinearity, and even strong ill-posedness. To avoid these challenges, we propose a DL approach based on the complex-valued deep convolutional neural networks (DConvNets), which comprise the deep convolutional encoder–decoder (DCED) structure. Its training data are collected based on the simple synthetic dataset. While the scattered fields received …

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An Insight Into The Effect Of Sharp And Round Edges On The Flow Field-A Cfd Simulation, Abid Hussain, Gao Puzhen, M. Mustafa Azeem, Muhammad Zubair, Muhammad Aamir, Muhammad Irfan Khaleed Jan 2023

An Insight Into The Effect Of Sharp And Round Edges On The Flow Field-A Cfd Simulation, Abid Hussain, Gao Puzhen, M. Mustafa Azeem, Muhammad Zubair, Muhammad Aamir, Muhammad Irfan Khaleed

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

This paper presents a numerical investigation of pressure drop and distribution in a channel around a sharp edge and a disc that is connected to the base of a circular rod. We have employed computational fluid dynamics (CFD)-Fluent for the validation of our models. It was found that the edge sharpness of the disc influences the pressure drop., i.e. sharp edge has higher turbulence and pressure drop. We also observed that pressure drops in the case of the circular disc are less than that of the sharp edge. However, pressure drop has essentially the same values for both shapes after …

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Internal Structure And Breakage Behavior Of Biogenic Carbonate Sand Grains, Elieh Mohtashami, C. Guney Olgun, Chenglin Wu, Tara Selly Jan 2023

Internal Structure And Breakage Behavior Of Biogenic Carbonate Sand Grains, Elieh Mohtashami, C. Guney Olgun, Chenglin Wu, Tara Selly

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

This Study Investigates the Mechanical Behavior of Biogenic Carbonate Sands from Puerto Rico at Grain-Scale Level. Micro-Computed Tomography Has Also Been Used to Get Insights on the Internal Structure of These Particles Before and after Loading. the Crushing Strength of These Particles Are Smaller Comparing to the Values Reported for Silica Sands. It Has Also Been Shown that These Particles Have Complex Internal Structure Including a Network of Pores Connected with Channels. This Study Also Demonstrates the Effect of Intragrain Structure of Biogenic Carbonate Sands and Shows How Internal Grain Structure Plays a Role on Particle Fracture.

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Point Density For Soil Specimen Volume Measurements In Image-Based Methods During Triaxial Testing, Sara Fayek, Xiong Zhang, Javad Galinmoghadam, Jeffrey D. Cawlfield Jan 2023

Point Density For Soil Specimen Volume Measurements In Image-Based Methods During Triaxial Testing, Sara Fayek, Xiong Zhang, Javad Galinmoghadam, Jeffrey D. Cawlfield

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Discrete Measurement Targets Were Frequently Utilized in Image-Based Methods on the Specimen's Surface to Monitor the Soil Specimen during Triaxial Testing. However, the Required Density of Measurement Targets that Should Be Used in Triaxial Testing to Achieve Highly Accurate Volume Measurement Has Not Been Investigated. to overcome This Limitation, This Paper Presents a Parametric Study to Determine the Optimum Target/point Densities to Be Utilized on the Triaxial Soil Specimen Surface to Achieve the Desired Level of Volume Measurement Accuracy in Image-Based Methods. LiDAR Scanning Was Applied to Establish the "Ground Truth" Volume of the Specimen. the Effects of Deformation and …

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Evaluation Of Thermal And Rheological Properties Of Phase Change Material-Incorporated Asphalt Mastic With Porous Fillers, Farshad Saberi Kerahroudi, Yizhuang David Wang, Jenny Liu Jan 2023

Evaluation Of Thermal And Rheological Properties Of Phase Change Material-Incorporated Asphalt Mastic With Porous Fillers, Farshad Saberi Kerahroudi, Yizhuang David Wang, Jenny Liu

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Incorporating phase change material (PCM) into paving materials can regulate the pavement temperature, improve the pavement durability, and mitigate the heat-island effects. In this research, porous fillers were used as the PCM carrier, and the thermal and rheological behaviors of the asphalt mastic with the PCM were evaluated. Two different carrier materials (diatomite and expanded perlite) and four types of PCMs were used in the study. The candidate filler, PCM, and proper blending ratios were determined based on the results of scanning electron microscope image analysis, the filter paper test, and the temperature sweep test. The thermal and rheological behaviors …

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Fluorination Of Rubisco-Mimetic Co2 Capture Systems. Theoretical And Experimental Studies Of Ammonium Ion Acidity Depression And Carbamylation, Brian Michael Jameson Jan 2023

Fluorination Of Rubisco-Mimetic Co2 Capture Systems. Theoretical And Experimental Studies Of Ammonium Ion Acidity Depression And Carbamylation, Brian Michael Jameson

Doctoral Dissertations

"RuBisCO-inspired CO2 capture and release (CCR) systems featuring amines have been developed for the purpose of reversable CO2 capture from air. The enzyme active site consists of the tetrapeptide sequence Lys-Asp-Asp-Glu. The Lys sidechain amine undergoes carbamylation and an Mg2+ cation stabilizes the resulting carbamate. The Na-acyl-lysinyl-aspratyl-aspartyl-glutamide (Lys-Asp-Asp-Glu, KDDE) peptide featured maximum capture at pH ≈ 10; a pH region too high for Mg2+ ions to remain in solution. This work aims to achieve pKa depression by introducing fluorine in the proximity of the lysine’s sidechain amine. A comparative analysis was made of butylamine, …

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Motivators And Inhibitors For Business Analytics Adoption From The Cross-Cultural Perspectives: A Data Mining Approach, Hokey Min, Bih-Ru Lea Jan 2023

Motivators And Inhibitors For Business Analytics Adoption From The Cross-Cultural Perspectives: A Data Mining Approach, Hokey Min, Bih-Ru Lea

Business and Information Technology Faculty Research & Creative Works

In the increasingly knowledge-based world economy, the multinational firm's success often hinges on its business intelligence capability nurtured by business analytics (BA). Despite the growing recognition of BA's role in enhancing the firm's intellectual capital and subsequent competitiveness, it is still unknown what truly motivates and inhibits BA adoption. This study aims to identify key influencing factors for BA adoption such as organizational characteristics, information security/privacy, and information technology maturity (knowledge level). In so doing, this study employed data mining and data visualization techniques to develop specific patterns of BA adoption practices based on a combined sample of 224 Korean …

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Ptco/Mwcnts Prepared By A Microwave-Assisted Polyol Method For Selective Cinnamaldehyde Hydrogenation, Kaiying Wang, Yuzi Liu, Jee-Ching Wang, Xinhua Liang Jan 2023

Ptco/Mwcnts Prepared By A Microwave-Assisted Polyol Method For Selective Cinnamaldehyde Hydrogenation, Kaiying Wang, Yuzi Liu, Jee-Ching Wang, Xinhua Liang

Chemical and Biochemical Engineering Faculty Research & Creative Works

Using microwave irradiation, PtCo alloy nanoparticles were deposited within a few minutes on COOH-functionalized MWCNT supports. The obtained catalysts were used for selective hydrogenation of cinnamaldehyde, a reaction whose products are widely used in various fields. In the selective cinnamaldehyde hydrogenation to cinnamyl alcohol, microwave-prepared catalysts (generically, PtxCoy-MW) outperformed a catalyst prepared by the conventional method (Pt1Co2-con). The highest selective hydrogenation to cinnamyl alcohol, 89%, was obtained using Pt1Co2-MW, while Pt1Co2-con showed a selectivity of 76%. Characterization results confirmed that the microwave prepared samples …

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Kinetic Assessment Of Light Hydrocarbons Separation Over Fe-Doped 13x Composite Sorbents Under Multicomponent Feed Conditions, Khaled Baamran, Jimmy D.L. Moreno, Ali A. Rownaghi, Fateme Rezaei Jan 2023

Kinetic Assessment Of Light Hydrocarbons Separation Over Fe-Doped 13x Composite Sorbents Under Multicomponent Feed Conditions, Khaled Baamran, Jimmy D.L. Moreno, Ali A. Rownaghi, Fateme Rezaei

Chemical and Biochemical Engineering Faculty Research & Creative Works

Current sorbents investigated for light olefin/paraffin separation usually suffer from low selectivity. Besides, multicomponent analysis of this important separation is usually overlooked in the literature. To enhance the separation efficiency of zeolite 13X, we developed a series of Fe2O3/13X composite sorbents and assessed their separation performance using binary, ternary, and multicomponent gas mixtures of C2H4, C2H6, CH4, and H2. In these composites, nano- and micro Fe2O3 particles (NPs and MPs) with varied loadings were used, while Fe was also ion-exchanged into …

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Temperature Dependence Of The Electronic Absorption Spectrum Of No2, Steve Ndengué, Ernesto Quintas Sánchez, Richard Dawes, Christopher C. Blackstone, David L. Osborn Jan 2023

Temperature Dependence Of The Electronic Absorption Spectrum Of No2, Steve Ndengué, Ernesto Quintas Sánchez, Richard Dawes, Christopher C. Blackstone, David L. Osborn

Chemistry Faculty Research & Creative Works

The nitrogen dioxide (NO2) radical is composed of the two most abundant elements in the atmosphere, where it can be formed in a variety of ways including combustion, detonation of energetic materials, and lightning. Relevant also to smog and ozone cycles, together these processes span a wide range of temperatures. Remarkably, high-resolution NO2 electronic absorption spectra have only been reported in a narrow range below about 300 K. Previously, we reported [ J. Phys. Chem. A 2021, 125, 5519−5533 ] the construction of quasi-diabatic potential energy surfaces (PESs) for the lowest four electronic states (X̃, Ã, B̃, …

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Editorial: The Digitalization Of Neurology, Daniel B. Hier, Michael D. Carrithers, Jorge M. Rodríguez-Fernández, Benjamin Kummer Jan 2023

Editorial: The Digitalization Of Neurology, Daniel B. Hier, Michael D. Carrithers, Jorge M. Rodríguez-Fernández, Benjamin Kummer

Chemistry Faculty Research & Creative Works

No abstract provided.

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Dendrochemical Forensics As Material Evidence In Courts: How Could Trees Lie?, Chris Balouet, Joel Gerard Burken, Jacques Martelain, Jonathan Lageard, Frank Karg, David Megson Jan 2023

Dendrochemical Forensics As Material Evidence In Courts: How Could Trees Lie?, Chris Balouet, Joel Gerard Burken, Jacques Martelain, Jonathan Lageard, Frank Karg, David Megson

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

The legal admissibility of scientific tools, such as dendrochemistry providing forensic evidence for criminal or civil cases, critically relies on the quality of fundamental and applied scientific research. the "Daubert" and "Frye" criteria that federal courts in the U.S.A use for determining legal admissibility requires publication of the scientific basis for the tool, and general acceptance by the scientific community. the field of dendroforensics is rapidly evolving, with new methods constantly being developed. in this manuscript we investigate how this dendrochemical evidence has been used successfully in the courtroom. the study of tree rings using physical anatomical and dendrochronological methods …

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Assessment Of The Dimensionless Groups-Based Scale-Up Of Gas–Solid Fluidized Beds, Faraj M. Zaid, Haider Al-Rubaye, Thaar M. Aljuwaya, Muthanna H. Al-Dahhan Jan 2023

Assessment Of The Dimensionless Groups-Based Scale-Up Of Gas–Solid Fluidized Beds, Faraj M. Zaid, Haider Al-Rubaye, Thaar M. Aljuwaya, Muthanna H. Al-Dahhan

Chemical and Biochemical Engineering Faculty Research & Creative Works

The most common scale-up approach for gas–solids fluidized beds is based on matching the governing dimensionless parameters. in the literature, this approach has been validated only by means of measuring global parameters between different sizes of fluidized beds. However, such global measurements are not sufficient to depict all the interplaying hydrodynamic phenomena and hence verify the scale-up relationships. Therefore, to assess this approach, an advanced gas–solids optical probe and pressure transducer measurement techniques have been applied to quantify local hydrodynamic parameters in two different sized fluidized beds. Four different sets of experimental conditions were designed and conducted to examine the …

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Nanomaterial Payload Delivery To Central Nervous System Glia For Neural Protection And Repair, Jayant Saksena, Adelle E. Hamilton, Ryan J. Gilbert, Jonathan M. Zuidema Jan 2023

Nanomaterial Payload Delivery To Central Nervous System Glia For Neural Protection And Repair, Jayant Saksena, Adelle E. Hamilton, Ryan J. Gilbert, Jonathan M. Zuidema

Chemical and Biochemical Engineering Faculty Research & Creative Works

Central nervous system (CNS) glia, including astrocytes, microglia, and oligodendrocytes, play prominent roles in traumatic injury and degenerative disorders. Due to their importance, active pharmaceutical ingredients (APIs) are being developed to modulate CNS glia in order to improve outcomes in traumatic injury and disease. While many of these APIs show promise in vitro, the majority of APIs that are systemically delivered show little penetration through the blood–brain barrier (BBB) or blood-spinal cord barrier (BSCB) and into the CNS, rendering them ineffective. Novel nanomaterials are being developed to deliver APIs into the CNS to modulate glial responses and improve outcomes in …

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Natural Product Co-Metabolism And The Microbiota–Gut–Brain Axis In Age-Related Diseases, Mark Obrenovich, Sandeep Kumar Singh, Yi Li, George Perry, Bushra Siddiqui, Waqas Haq, V. Prakash Reddy Jan 2023

Natural Product Co-Metabolism And The Microbiota–Gut–Brain Axis In Age-Related Diseases, Mark Obrenovich, Sandeep Kumar Singh, Yi Li, George Perry, Bushra Siddiqui, Waqas Haq, V. Prakash Reddy

Chemistry Faculty Research & Creative Works

Complementary alternative medicine approaches are growing treatments of diseases to standard medicine practice. Many of these concepts are being adopted into standard practice and orthomolecular medicine. Age-related diseases, in particular neurodegenerative disorders, are particularly difficult to treat and a cure is likely a distant expectation for many of them. Shifting attention from pharmaceuticals to phytoceuticals and "bugs as drugs" represents a paradigm shift and novel approaches to intervention and management of age-related diseases and downstream effects of aging. Although they have their own unique pathologies, a growing body of evidence suggests Alzheimer's disease (AD) and vascular dementia (VaD) share common …

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Natural Product Co-Metabolism And The Microbiota–Gut–Brain Axis In Age-Related Diseases, Mark Obrenovich, Sandeep Kumar Singh, Yi Li, George Perry, Bushra Siddiqui, Waqas Haq, V. Prakash Reddy Jan 2023

Natural Product Co-Metabolism And The Microbiota–Gut–Brain Axis In Age-Related Diseases, Mark Obrenovich, Sandeep Kumar Singh, Yi Li, George Perry, Bushra Siddiqui, Waqas Haq, V. Prakash Reddy

Chemistry Faculty Research & Creative Works

Complementary alternative medicine approaches are growing treatments of diseases to standard medicine practice. Many of these concepts are being adopted into standard practice and orthomolecular medicine. Age-related diseases, in particular neurodegenerative disorders, are particularly difficult to treat and a cure is likely a distant expectation for many of them. Shifting attention from pharmaceuticals to phytoceuticals and "bugs as drugs" represents a paradigm shift and novel approaches to intervention and management of age-related diseases and downstream effects of aging. Although they have their own unique pathologies, a growing body of evidence suggests Alzheimer's disease (AD) and vascular dementia (VaD) share common …

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Advances In Bioelectrode Design For Developing Electrochemical Biosensors, Nabajyoti Kalita, Sudarshan Gogoi, Shelley D. Minteer, Pranab Goswami Jan 2023

Advances In Bioelectrode Design For Developing Electrochemical Biosensors, Nabajyoti Kalita, Sudarshan Gogoi, Shelley D. Minteer, Pranab Goswami

Chemistry Faculty Research & Creative Works

The critical performance factors such as selectivity, sensitivity, operational and storage stability, and response time of electrochemical biosensors are governed mainly by the function of their key component, the bioelectrode. Suitable design and fabrication strategies of the bioelectrode interface are essential for realizing the requisite performance of the biosensors for their practical utility. A multifaceted attempt to achieve this goal is visible from the vast literature exploring effective strategies for preparing, immobilizing, and stabilizing biorecognition elements on the electrode surface and efficient transduction of biochemical signals into electrical ones (i.e., current, voltage, and impedance) through the bioelectrode interface with the …

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An Explainable Deep Learning Model For Prediction Of Severity Of Alzheimer's Disease, Godwin Ekuma, Daniel B. Hier, Tayo Obafemi-Ajayi Jan 2023

An Explainable Deep Learning Model For Prediction Of Severity Of Alzheimer's Disease, Godwin Ekuma, Daniel B. Hier, Tayo Obafemi-Ajayi

Chemistry Faculty Research & Creative Works

Deep Convolutional Neural Networks (CNNs) have become the go-To method for medical imaging classification on various imaging modalities for binary and multiclass problems. Deep CNNs extract spatial features from image data hierarchically, with deeper layers learning more relevant features for the classification application. Despite the high predictive accuracy, usability lags in practical applications due to the black-box model perception. Model explainability and interpretability are essential for successfully integrating artificial intelligence into healthcare practice. This work addresses the challenge of an explainable deep learning model for the prediction of the severity of Alzheimer's disease (AD). AD diagnosis and prognosis heavily rely …

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Environmentally-Aware And Energy-Efficient Multi-Drone Coordination And Networking For Disaster Response, Chengyi Qu, Francesco Betti Sorbelli, Rounak Singh, Prasad Calyam, Sajal K. Das Jan 2023

Environmentally-Aware And Energy-Efficient Multi-Drone Coordination And Networking For Disaster Response, Chengyi Qu, Francesco Betti Sorbelli, Rounak Singh, Prasad Calyam, Sajal K. Das

Computer Science Faculty Research & Creative Works

In a Disaster Response Management (DRM) Scenario, Communication and Coordination Are Limited, and Absence of Related Infrastructure Hinders Situational Awareness. Unmanned Aerial Vehicles (UAVs) or Drones Provide New Capabilities for DRM to Address These Barriers. However, There is a Dearth of Works that Address Multiple Heterogeneous Drones Collaboratively Working Together to Form a Flying Ad-Hoc Network (FANET) with Air-To-Air and Air-To-Ground Links that Are Impacted By: (I) Environmental Obstacles, (Ii) Wind, and (Iii) Limited Battery Capacities. in This Paper, We Present a Novel Environmentally-Aware and Energy-Efficient Multi-Drone Coordination and Networking Scheme that Features a Reinforcement Learning (RL) based Location Prediction …

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Programmable Software-Defined Testbed For Visible Light Uav Networks: Architecture Design And Implementation, Yue Zhang, Nan Cen Jan 2023

Programmable Software-Defined Testbed For Visible Light Uav Networks: Architecture Design And Implementation, Yue Zhang, Nan Cen

Computer Science Faculty Research & Creative Works

As of Today, There Has Been Increasing Research on Designing Optimization Algorithms and Intelligent Network Control Methods for Visible Light Unmanned Aerial Vehicles (UAV) Networks to Provide Pervasive and Broadband Connections. for Those Theoretical Analysis based Algorithms, there is an Urgent Need to Have a Visible Light UAV Network Platform that Can Help Evaluate the Proposed Algorithms in Real-World Scenarios. However, to the Best of Our Knowledge, there is Currently No Dedicated High Data Rate and Flexible Visible Light UAV Networking Prototype. to Bridge This Gap, in This Paper, We First Design a Novel Programmable Software-Defined Architecture for Visible Light …

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Sigmoid Activation-Based Long Short-Term Memory For Time Series Data Classification, Sajal Das Jan 2023

Sigmoid Activation-Based Long Short-Term Memory For Time Series Data Classification, Sajal Das

Computer Science Faculty Research & Creative Works

With the enhanced usage of Artificial Intelligence (AI) driven applications, the researchers often face challenges in improving the accuracy of the data classification models, while trading off the complexity. In this paper, we address the classification of time series data using the Long Short-Term Memory (LSTM) network while focusing on the activation functions. While the existing activation functions such as sigmoid and tanh are used as LSTM internal activations, the customizability of these activations stays limited. This motivates us to propose a new family of activation functions, called log-sigmoid, inside the LSTM cell for time series data classification, and analyze …

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Unifying Threats Against Information Integrity In Participatory Crowd Sensing, Shameek Bhattacharjee, Sajal K. Das Jan 2023

Unifying Threats Against Information Integrity In Participatory Crowd Sensing, Shameek Bhattacharjee, Sajal K. Das

Computer Science Faculty Research & Creative Works

This article proposes a unified threat landscape for participatory crowd sensing (P-CS) systems. Specifically, it focuses on attacks from organized malicious actors that may use the knowledge of P-CS platform's operations and exploit algorithmic weaknesses in AI-based methods of event trust, user reputation, decision-making, or recommendation models deployed to preserve information integrity in P-CS. We emphasize on intent driven malicious behaviors by advanced adversaries and how attacks are crafted to achieve those attack impacts. Three directions of the threat model are introduced, such as attack goals, types, and strategies. We expand on how various strategies are linked with different attack …

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Reward Maximization For Disaster Zone Monitoring With Heterogeneous Uavs, Wenzheng Xu, Chengxi Wang, Hongbin Xie, Weifa Liang, Haipeng Dai, Zichuan Xu, Ziming Wang, Bing Guo, Sajal K. Das Jan 2023

Reward Maximization For Disaster Zone Monitoring With Heterogeneous Uavs, Wenzheng Xu, Chengxi Wang, Hongbin Xie, Weifa Liang, Haipeng Dai, Zichuan Xu, Ziming Wang, Bing Guo, Sajal K. Das

Computer Science Faculty Research & Creative Works

In this paper, we study the deployment of $K$ heterogeneous UAVs to monitor Points of Interest (PoIs) in a disaster zone, where a PoI may represent a school building or an office building, in which people are trapped. A UAV can take images/videos of PoIs and send its collected information back to a nearby rescue station for decision-making. Unlike most existing studies that focused on only homogeneous UAVs, we here study the scheduling of $K$ heterogeneous UAVs, where different UAVs have different energy capacities and functionalities that lead to different monitoring qualities (monitoring rewards) of each PoI. For example, one …

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Robust Federated Learning Against Backdoor Attackers, Priyesh Ranjan, Ashish Gupta, Federico Corò, Sajal K. Das Jan 2023

Robust Federated Learning Against Backdoor Attackers, Priyesh Ranjan, Ashish Gupta, Federico Corò, Sajal K. Das

Computer Science Faculty Research & Creative Works

Federated Learning is a Privacy-Preserving Alter-Native for Distributed Learning with No Involvement of Data Transfer. as the Server Does Not Have Any Control on Clients' Actions, Some Adversaries May Participate in Learning to Introduce Corruption into the Underlying Model. Backdoor Attacker is One Such Adversary Who Injects a Trigger Pattern into the Data to Manipulate the Model Outcomes on a Specific Sub-Task. This Work Aims to Identify Backdoor Attackers and to Mitigate their Effects by Isolating their Weight Updates. Leveraging the Correlation between Clients' Gradients, We Propose Two Graph Theoretic Algorithms to Separate Out Attackers from the Benign Clients. under …

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Message From The Ieee Mdm 2023 Test-Of-Time Committee, Christian S. Jensen, Sanjay Kumar Madria, Timos Sellis Jan 2023

Message From The Ieee Mdm 2023 Test-Of-Time Committee, Christian S. Jensen, Sanjay Kumar Madria, Timos Sellis

Computer Science Faculty Research & Creative Works

No abstract provided.

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