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Missouri University of Science and Technology

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Communication-Efficient Federated Learning For Leo Constellations Integrated With Haps Using Hybrid Noma-Ofdm, Mohamed Elmahallawy, Tony T. Luo, Khaled Ramadan Jan 2024

Communication-Efficient Federated Learning For Leo Constellations Integrated With Haps Using Hybrid Noma-Ofdm, Mohamed Elmahallawy, Tony T. Luo, Khaled Ramadan

Computer Science Faculty Research & Creative Works

Space AI has become increasingly important and sometimes even necessary for government, businesses, and society. An active research topic under this mission is integrating federated learning (FL) with satellite communications (SatCom) so that numerous low Earth orbit (LEO) satellites can collaboratively train a machine learning model. However, the special communication environment of SatCom leads to a very slow FL training process up to days and weeks. This paper proposes NomaFedHAP, a novel FL-SatCom approach tailored to LEO satellites, that (1) utilizes high-altitude platforms (HAPs) as distributed parameter servers (PSs) to enhance satellite visibility, and (2) introduces non-orthogonal multiple access (NOMA) …

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Lease: Leveraging Energy-Awareness In Serverless Edge For Latency-Sensitive Iot Services, Aastik Verma, Anurag Satpathy, Sajal K. Das, Sourav Kanti Addya Jan 2024

Lease: Leveraging Energy-Awareness In Serverless Edge For Latency-Sensitive Iot Services, Aastik Verma, Anurag Satpathy, Sajal K. Das, Sourav Kanti Addya

Computer Science Faculty Research & Creative Works

Resource Scheduling Catering to Real-Time IoT Services in a Serverless-Enabled Edge Network is Particularly Challenging Owing to the Workload Variability, Strict Constraints on Tolerable Latency, and Unpredictability in the Energy Sources Powering the Edge Devices. This Paper Proposes a Framework LEASE that Dynamically Schedules Resources in Serverless Functions Catering to Different Microservices and Adhering to their Deadline Constraint. to Assist the Scheduler in Making Effective Scheduling Decisions, We Introduce a Priority-Based Approach that Offloads Functions from over-Provisioned Edge Nodes to Under-Provisioned Peer Nodes, Considering the Expended Energy in the Process Without Compromising the Completion Time of Microservices. for Real-World Implementations, …

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Landmark-Based Localization Using Stereo Vision And Deep Learning In Gps-Denied Battlefield Environment, Ganesh Sapkota, Sanjay Madria Jan 2024

Landmark-Based Localization Using Stereo Vision And Deep Learning In Gps-Denied Battlefield Environment, Ganesh Sapkota, Sanjay Madria

Computer Science Faculty Research & Creative Works

Localization in a battlefield environment is increasingly challenging as GPS connectivity is often denied or unreliable, and physical deployment of anchor nodes across wireless networks for localization can be difficult in hostile battlefield terrain. This paper proposes a novel framework for the localization of moving objects in non-GPS battlefield environments using stereo vision and a deep learning model by recognizing naturally existing or artificial landmarks as anchors. The proposed method utilizes a custom-calibrated stereo vision camera for distance estimation and the YOLOv8s model, which is trained and fine-tuned with our real-world dataset for landmark anchor recognition. The depth images are …

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Warmonger Attack: A Novel Attack Vector In Serverless Computing, Junjie Xiong, Mingkui Wei, Zhuo Lu, Yao Liu Jan 2024

Warmonger Attack: A Novel Attack Vector In Serverless Computing, Junjie Xiong, Mingkui Wei, Zhuo Lu, Yao Liu

Computer Science Faculty Research & Creative Works

We debut the Warmonger attack, a novel attack vector that can cause denial-of-service between a serverless computing platform and an external content server. The Warmonger attack exploits the fact that a serverless computing platform shares the same set of egress IPs among all serverless functions, which belong to different users, to access an external content server. As a result, a malicious user on this platform can purposefully misbehave and cause these egress IPs to be blocked by the content server, resulting in a platform-wide denial of service. To validate the effectiveness of the Warmonger attack, we conducted extensive experiments over …

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Distributed Solar Generation: Data Analytics Of The Existing Literature For Guiding Future Prospects, Gasser Ali, Islam H. El-Adaway Jan 2024

Distributed Solar Generation: Data Analytics Of The Existing Literature For Guiding Future Prospects, Gasser Ali, Islam H. El-Adaway

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Distributed Solar Generation (DSG) Systems Are Small-Scale Units That Are Located At Or Near End-Consumers Such As Residential Rooftop Photo-Voltaic (PV) Systems. DSG Has Driven A Plethora Of Multidisciplinary Research With Various Interrelated Topics And Perspectives. A Broad Understanding Of Research Directions And Potential Gaps In Knowledge Can Be Elusive. Accordingly, The Goal Of This Paper Is To Investigate The Research Trends Related To DSG And Explore Research Opportunities. This Is Achieved By Performing A Data-Driven Keyword Search And Network Analysis On A Large Dataset Of Publications Related To DSG To Quantify Topics Related To DSG And The Interconnectivity Between …

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Mild Cognitive Impairment Classification Using A Novel Finer-Scale Brain Connectome, Yanjun Lyu, Lu Zhang, Xiaowei Yu, Chao Cao, Tianming Liu, Dajiang Zhu Jan 2024

Mild Cognitive Impairment Classification Using A Novel Finer-Scale Brain Connectome, Yanjun Lyu, Lu Zhang, Xiaowei Yu, Chao Cao, Tianming Liu, Dajiang Zhu

Computer Science Faculty Research & Creative Works

Mild cognitive impairment (MCI) is recognized as a precursor to Alzheimer's disease (AD), a progressive and irreversible neurodegenerative disorder of the brain. The neurodegeneration of brain connectivity networks plays a pivotal role in the development and progression of MCI. Traditionally, brain networks are generated using coarse-grained brain regions, where the regions serve as nodes and their functional or structural connections are used as edges. Recently, a novel finer scale brain folding patterns named 3hinge gyrus (3HG) was identified, which is defined as the conjunctions coming from three directions on gyral crests. 3HGs have been shown playing an important role in …

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Cav-Ad: A Robust Framework For Detection Of Anomalous Data And Malicious Sensors In Cav Networks, Md Sazedur Rahman, Mohamed Elmahallawy, Sanjay Madria, Samuel Frimpong Jan 2024

Cav-Ad: A Robust Framework For Detection Of Anomalous Data And Malicious Sensors In Cav Networks, Md Sazedur Rahman, Mohamed Elmahallawy, Sanjay Madria, Samuel Frimpong

Computer Science Faculty Research & Creative Works

The adoption of connected and automated vehicles (CAVs) has sparked considerable interest across diverse industries, including public transportation, underground mining, and agriculture sectors. However, CAVs' reliance on sensor readings makes them vulnerable to significant threats. Manipulating these readings can compromise CAV network security, posing serious risks for malicious activities. Although several anomaly detection (AD) approaches for CAV networks are proposed, they often fail to: i) detect multiple anomalies in specific sensor(s) with high accuracy or F1 score, and ii) identify the specific sensor being attacked. In response, this paper proposes a novel framework tailored to CAV networks, called CAV-AD, for …

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Persistent Monitoring Of Insect-Pests On Sticky Traps Through Hierarchical Transfer Learning And Slicing-Aided Hyper Inference, Fateme Fotouhi, Kevin Menke, Aaron Prestholt, Ashish Gupta, Matthew E. Carroll, Hsin Jung Yang, Edwin J. Skidmore, Matthew O'Neal, Nirav Merchant, Sajal K. Das, Peter Kyveryga, Baskar Ganapathysubramanian, Asheesh K. Singh, Arti Singh, Soumik Sarkar Jan 2024

Persistent Monitoring Of Insect-Pests On Sticky Traps Through Hierarchical Transfer Learning And Slicing-Aided Hyper Inference, Fateme Fotouhi, Kevin Menke, Aaron Prestholt, Ashish Gupta, Matthew E. Carroll, Hsin Jung Yang, Edwin J. Skidmore, Matthew O'Neal, Nirav Merchant, Sajal K. Das, Peter Kyveryga, Baskar Ganapathysubramanian, Asheesh K. Singh, Arti Singh, Soumik Sarkar

Computer Science Faculty Research & Creative Works

Introduction: Effective monitoring of insect-pests is vital for safeguarding agricultural yields and ensuring food security. Recent advances in computer vision and machine learning have opened up significant possibilities of automated persistent monitoring of insect-pests through reliable detection and counting of insects in setups such as yellow sticky traps. However, this task is fraught with complexities, encompassing challenges such as, laborious dataset annotation, recognizing small insect-pests in low-resolution or distant images, and the intricate variations across insect-pests life stages and species classes. Methods: to tackle these obstacles, this work investigates combining two solutions, Hierarchical Transfer Learning (HTL) and Slicing-Aided Hyper Inference …

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Prediction Of Carbonation Capacity Of Scms Using Ensemble Learning Method, Kangyi Cai, Jian Liu, Edward Mwanza, Mahelet G. Fikru, Hongyan Ma, Donald C. Wunsch Jan 2024

Prediction Of Carbonation Capacity Of Scms Using Ensemble Learning Method, Kangyi Cai, Jian Liu, Edward Mwanza, Mahelet G. Fikru, Hongyan Ma, Donald C. Wunsch

Economics Faculty Research & Creative Works

The utilization of supplementary cementitious materials (SCMs) subjected to carbonation processing represents a viable strategy to mitigate anthropogenic CO2 emissions associated with concrete production, potentially contributing to the achievement of carbon neutrality. However, existing studies have limitations in effectively predicting the varying carbonation capacities of different SCMs, a gap that this research aims to address. Recent research efforts focused on the carbonation of waste-material-sourced SCMs are reviewed, along with a comparative discussion on diverse carbonation methods. A detailed data set encapsulating the properties of SCMs, and carbonation configurations was compiled. At the same time, six ensemble learning models were …

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Pattern Recognition For Wettability Alteration With Surfactants In Carbonate Reservoirs By Using Machine Learning, Y. Yao, Mingzhen Wei, M. Ali, Y. Qiu, Y. Cui, J. Leng Jan 2024

Pattern Recognition For Wettability Alteration With Surfactants In Carbonate Reservoirs By Using Machine Learning, Y. Yao, Mingzhen Wei, M. Ali, Y. Qiu, Y. Cui, J. Leng

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Surfactants Are Widely Applied Agents to Interact with the Adsorbates on Carbonate Rock Surface, Which Could Alter Wettability from Oil-Wetness to Water-Wetness and Thus Enhance Oil Recovery. Surfactant Huff-Puff is Often Conducted to Achieve Wettability Alteration and Has Been Applied under Various Conditions. Currently, Many Investigations Have Been Reported to Apply Conventional Data Analysis Methods to Analyze Different Sets of Surfactant Huff-Puff Projects. Yet the Application of Machine Learning Algorithms to Reveal the Inherent Patterns is Rarely Reported. in This Study, We Integrate Principal Component Analysis (PCA) with Hierarchical Clustering Algorithm (HCA) to Uncover the Hidden Patterns Embedded in Global …

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Thermo-Mechanical Stability Analysis Of Hollow Cellular Concrete Block Air Convection Embankments For Cold Regions, H. Wu, X. Zhang, J. Liu Jan 2024

Thermo-Mechanical Stability Analysis Of Hollow Cellular Concrete Block Air Convection Embankments For Cold Regions, H. Wu, X. Zhang, J. Liu

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Crushed-rock air convection embankment (ACE), as a highly open-graded porous medium, has been used to mitigate the thaw settlement of pavement structures in permafrost regions. Previous studies have revealed that cellular concrete has significant potential as a cost-effective material for ACE to solve the problem of crushed rock shortage in interior Alaska and improved the thermal stability of pavement structures in cold climates. the design configurations of the hollow cellular concrete block ACE were further designed to maximize the performance benefits and facilitate future implementation and field construction. However, the mechanical behaviors of the proposed structures and ice-rich subgrade were …

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Prediction Of Stratified Ground Consolidation Via A Physics-Informed Neural Network Utilizing Short-Term Excess Pore Water Pressure Monitoring Data, Weibing Gong, Linlong Zuo, Lin Li, Hui Wang Jan 2024

Prediction Of Stratified Ground Consolidation Via A Physics-Informed Neural Network Utilizing Short-Term Excess Pore Water Pressure Monitoring Data, Weibing Gong, Linlong Zuo, Lin Li, Hui Wang

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Predicting stratified ground consolidation effectively remains a challenge in geotechnical engineering, especially when it comes to quickly and dependably determining the coefficient of consolidation ((Formula presented.)) for each soil layer. This difficulty primarily stems from the time-intensive nature of the consolidation process and the challenges in efficiently simulating this process in laboratory settings and using numerical methods. Nevertheless, the consolidation of stratified ground is crucial because it governs ground settlement, affecting the safety and serviceability of structures situated on or in such ground. In this study, an innovative method utilizing a physics-informed neural network (PINN) is introduced to predict stratified …

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Assessing The Potential Of Uav-Based Multispectral And Thermal Data To Estimate Soil Water Content Using Geophysical Methods, Yunyi Guan, Katherine R. Grote Jan 2024

Assessing The Potential Of Uav-Based Multispectral And Thermal Data To Estimate Soil Water Content Using Geophysical Methods, Yunyi Guan, Katherine R. Grote

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Knowledge of the soil water content (SWC) is important for many aspects of agriculture and must be monitored to maximize crop yield, efficiently use limited supplies of irrigation water, and ensure optimal nutrient management with minimal environmental impact. Single-location sensors are often used to monitor SWC, but a limited number of point measurements is insufficient to measure SWC across most fields since SWC is typically very heterogeneous. To overcome this difficulty, several researchers have used data acquired from unmanned aerial vehicles (UAVs) to predict the SWC by using machine learning on a limited number of point measurements acquired across a …

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Geochemical Assessment Of Mineral Sequestration Of Carbon Dioxide In The Midcontinent Rift, Alsedik Abousif, David J. Wronkiewicz, Abdelmoniem Masoud Jan 2024

Geochemical Assessment Of Mineral Sequestration Of Carbon Dioxide In The Midcontinent Rift, Alsedik Abousif, David J. Wronkiewicz, Abdelmoniem Masoud

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

This Study Examines The Potential Of Midcontinent Rift Rocks To Facilitate Long-Term CO2 Sequestration By Providing The Necessary Ca And Mg For Carbonate Mineralization. Surface Samples Were Collected From The Oronto And Bayfield-Jacobsville Groups Around Lake Superior And Used For Petrography And X-Ray Diffraction To Determine Their Mineral Composition. Also, X-Ray Fluorescence Was Also Used To Assess Their Bulk Chemical Composition. The Samples Were Then Exposed To CO2 And Deionized Water In Teflon-Lined Vessels At 90°C, And The Resulting Leachate Fluids Were Analyzed For The Cation Released During The Testing. SEM Microscopy Was Used To Examine The Samples For Potential …

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Would Self-Supported Fracture Contribute To The Hydrocarbon Production In Shale Reservoir Besides Proppant-Supported Fracture, Y. Sun, G. Li, S. Zeng, J. Wu, J. Liu, M. Xu, C. Dai, Baojun Bai Jan 2024

Would Self-Supported Fracture Contribute To The Hydrocarbon Production In Shale Reservoir Besides Proppant-Supported Fracture, Y. Sun, G. Li, S. Zeng, J. Wu, J. Liu, M. Xu, C. Dai, Baojun Bai

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

During hydraulic fracturing in deep shale gas reservoirs, it is difficult to pump proppants long distances, and self-supported fractures are formed at the far and upper ends of the fractures. The self-supported fracture could hold the fracture space by its surface structure again fracture closure. However, it faces various aspects of impairment during shale gas reservoir development, which affect its conductivity. Among the impairment, long-term production results in a decline of bottom hole pressure, which will compact the fracture space, and self-supported fractures without proppant are more sensitive than those with proppant. In this paper, we conducted a series of …

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Circular Economy Strategies For Reducing Embodied Carbon In Us Commercial Building Stocks: A System Dynamics Modeling Approach, Radwa Eissa, Islam H. El-Adaway Jan 2024

Circular Economy Strategies For Reducing Embodied Carbon In Us Commercial Building Stocks: A System Dynamics Modeling Approach, Radwa Eissa, Islam H. El-Adaway

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Environmental concerns over embodied carbon - which is generated during the extraction, transportation, manufacturing, construction, and disposal of building materials - have been increasing as the industry shifts to renewable energy and grid decarbonization efforts prevail. Commercial buildings, a rapidly growing sector and a major source of embodied carbon, can contribute immensely to the national climate goals by transitioning into a circular economy (CE). Nevertheless, embodied carbon research is rather dispersed, with sparse data on the actual impact of different CE strategies and how they scale on nationwide commercial building stocks. To address this research need, the goal of this …

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The Impact Of Journalistic Cultures On Social Media Discourse: Us Primary Debates In Cross-Lingual Online Spaces, Lea Hellmueller, Lindita Camaj, Sebastián Vallejo Vera, Peggy Lindner Jan 2024

The Impact Of Journalistic Cultures On Social Media Discourse: Us Primary Debates In Cross-Lingual Online Spaces, Lea Hellmueller, Lindita Camaj, Sebastián Vallejo Vera, Peggy Lindner

Engineering Management and Systems Engineering Faculty Research & Creative Works

This cross-lingual project examines how social media posts of Spanish- and English-language media impact incivility in user comments during the 2020 primary political debates in the United States. We analyzed Facebook posts of news organizations that hosted the debates and used a state-of-the-art machine-learning model to analyze the corresponding comments. Our findings reveal distinct journalistic cultures on the post-level: English-language media are significantly more likely to use interpretation while Spanish-language media employ more audience-engagement and factual reporting strategies. We argue that in order to understand incivility in social media discourse during political debates, we need to consider journalistic cultures: While …

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Fe-Ni-Cu-Pge Sulfide Transport Mechanisms And Carbon-Sulfur Interactions In Lower Crustal Magmatic Settings: A Study From The Valmaggia Ultramafic Pipe, Ivrea-Verbano Zone, Italy, Shelby Leann Clark Jan 2024

Fe-Ni-Cu-Pge Sulfide Transport Mechanisms And Carbon-Sulfur Interactions In Lower Crustal Magmatic Settings: A Study From The Valmaggia Ultramafic Pipe, Ivrea-Verbano Zone, Italy, Shelby Leann Clark

Masters Theses

"Constraining the processes that control the transport and deposition of sulfides in the deep lithosphere is an important step in expanding ore deposit exploration search space to include exhumed lower crustal rocks. The ultramafic sulfide ore-bearing Valmaggia pipe in the Ivrea-Verbano Zone of NW Italy, an exhumed cross section of the overlying lower continental crust and subcontinental lithospheric mantle, gives critical insight into metallogenic processes in lower crustal settings. The ~300 m wide metasomatized pipe hosts Fe-Ni-Cu-(PGE±Co±Au) sulfide mineralization that is commonly associated with locally abundant carbonates and hydrous silicates (phlogopite, amphibole). Previous studies suggested that sulfides were physically transported …

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A Systematic Review Of Phenotypic And Epigenetic Clocks Used For Aging And Mortality Quantification In Humans, Brandon Warner, Edward Ratner, Anirban Datta, Amaury Lendasse Jan 2024

A Systematic Review Of Phenotypic And Epigenetic Clocks Used For Aging And Mortality Quantification In Humans, Brandon Warner, Edward Ratner, Anirban Datta, Amaury Lendasse

Engineering Management and Systems Engineering Faculty Research & Creative Works

Aging is the leading driver of disease in humans and has profound impacts on mortality. Biological clocks are used to measure the aging process in the hopes of identifying possible interventions. Biological clocks may be categorized as phenotypic or epigenetic, where phenotypic clocks use easily measurable clinical biomarkers, and epigenetic clocks use cellular methylation data. In recent years, methylation clocks have attained phenomenal performance when predicting chronological age and have been linked to various age-related diseases. Additionally, phenotypic clocks have been proven to be able to predict mortality better than chronological age, providing intracellular insights into the aging process. This …

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Lidar Technology For Future Wireless Networks: Use Cases And Challenges, Omar Rinchi, Ahmad Alsharoa Jan 2024

Lidar Technology For Future Wireless Networks: Use Cases And Challenges, Omar Rinchi, Ahmad Alsharoa

Electrical and Computer Engineering Faculty Research & Creative Works

Next-generation wireless networks are beset with challenges such as line-of-sight (LoS) shadowing and multipath scattering, significantly impacting service quality and reliability. Despite technological advances aimed at mitigating these issues, achieving consistent quality of service (QoS) standards continues to be an uphill task, particularly within the ever-changing urban landscapes and the intricate process of melding new technologies with pre-existing infrastructures. This paper delves into the integration of light detection and ranging (LiDAR) sensors as a novel solution to these persistent problems. We explore two potential use cases of LiDAR integration in wireless networks, offering detailed insights into the underlying motivation, technical …

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Generation Of Micro-Fracture Clouds In Rocks: Mechanisms And Applications, U. Mutlu, G. Boitnott, A. Lisjak, O. Mahabadi, Taghi Sherizadeh, D. Guner, S. Nowak, A. Ghassemi Jan 2024

Generation Of Micro-Fracture Clouds In Rocks: Mechanisms And Applications, U. Mutlu, G. Boitnott, A. Lisjak, O. Mahabadi, Taghi Sherizadeh, D. Guner, S. Nowak, A. Ghassemi

Mining Engineering Faculty Research & Creative Works

Volume increasing or decreasing processes in rocks can lead to inter or intragranular fractures in subsurface formations. The volume change can be caused by chemical reactions involving fluid, reactive transport, and coupling with the mechanical deformation of the grains. Depending on stress, material properties and coupled thermo-hydro-mechanical-chemical (THMC) conditions, grain scale fractures may propagate and coalesce, forming a cloud of well-connected fracture networks. The mechanisms responsible for propagation, coalescence and inhibition of cloud fractures are not well known. In this study, we review coupled micro-fracture network generation mechanisms as published in the literature and observed in field, experiments, and models. …

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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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Iterative Power Flow Control Architecture For Dc-Ac-Ac Triple Active Bridge Converters: Design, Simulation, And Hardware Testing, Jonathan Henri Saelens Jan 2024

Iterative Power Flow Control Architecture For Dc-Ac-Ac Triple Active Bridge Converters: Design, Simulation, And Hardware Testing, Jonathan Henri Saelens

Masters Theses

Driven by widespread electrification and escalating energy demands, efficient and cost-effective converter systems are necessary to maintain and improve our nation's electrical grid. Facilitating this necessity are power electronic converters in applications such as smart grids, renewable energy integration, and electric vehicles. Guided by the demand for improved converter topologies and conversion efficiency, much research has been conducted on varying designs, development, and control implementations. One such topology gaining significant research attention is the triple active bridge (TAB) converter. The TAB is a three-port power converter enabling both bidirectional power flow on each port and galvanic isolation for safety and …

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Identifying The Job Characteristics Affecting Construction Firm Employee Turnover Intention, Seog Jae Choi Jan 2024

Identifying The Job Characteristics Affecting Construction Firm Employee Turnover Intention, Seog Jae Choi

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Researchers have proved that employees who have the intention to quit the organization, called turnover intention, have decreased productivity and may not fulfill their duties properly. The turnover intention has a negative relationship with the quality of core job characteristics of the organization. As the construction industry has distinctive characteristics compared to other industries, the job characteristics that influence turnover intention need to be explored separately. This study identifies job characteristics of the construction industry that can affect turnover intention. Through the literature review, autonomy, task identity, required skill variety, task significance, justification in assigning work location, and job security …

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Energy Consumption Optimization Of Uav-Assisted Traffic Monitoring Scheme With Tiny Reinforcement Learning, Xiangjie Kong, Chenhao Ni, Gaohui Duan, Guojiang Shen, Yao Yang, Sajal K. Das Jan 2024

Energy Consumption Optimization Of Uav-Assisted Traffic Monitoring Scheme With Tiny Reinforcement Learning, Xiangjie Kong, Chenhao Ni, Gaohui Duan, Guojiang Shen, Yao Yang, Sajal K. Das

Computer Science Faculty Research & Creative Works

Unmanned Aerial Vehicles (UAVs) can capture pictures of road conditions in all directions and from different angles by carrying high-definition cameras, which helps gather relevant road data more effectively. However, due to their limited energy capacity, drones face challenges in performing related tasks for an extended period. Therefore, a crucial concern is how to plan the path of UAVs and minimize energy consumption. To address this problem, we propose a multi-agent deep deterministic policy gradient based (MADDPG) algorithm for UAV path planning (MAUP). Considering the energy consumption and memory usage of MAUP, we have conducted optimizations to reduce consumption on …

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Towards Fine-Gained Services: Nfv-Assisted Tracking And Positioning Using Micro-Services For Multi-Robot Cooperation, Bo Yi, Lin Qiu, Jianhui Lv, Yingpu Nian, Xingwei Wang, Sajal K. Das Jan 2024

Towards Fine-Gained Services: Nfv-Assisted Tracking And Positioning Using Micro-Services For Multi-Robot Cooperation, Bo Yi, Lin Qiu, Jianhui Lv, Yingpu Nian, Xingwei Wang, Sajal K. Das

Computer Science Faculty Research & Creative Works

Robotics as a Service (RaaS) emerges as a new paradigm to motivate diversified potential of the "remote-controlled economy" for flexible and efficient service provision with the help of cloud computing. The multi-robot cooperation (MRC) technology has been widely used in various intelligent logistics scenarios, such as warehouses, factories, airports and subway stations, benefiting from the advantages of high operational efficiency and low labor cost. While promising, the corresponding challenge is that the service functions deployed on logistics robots (LRs) are more prone to failures such as resource exhaustion and error configuration in the multi-robot system (MRS). In this way, it …

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Undeniable Authentication Of Digital Twin-Managed Smart Microfactory, Anusha Vangala, Ashok Kumar Das, Sajal K. Das Jan 2024

Undeniable Authentication Of Digital Twin-Managed Smart Microfactory, Anusha Vangala, Ashok Kumar Das, Sajal K. Das

Computer Science Faculty Research & Creative Works

Smart Microfactories Use Additive Manufacturing to Create Products with Mixed Materials and Variable Sizes. Digital Twin Technology Enhances Control of the Additive Manufacturing Equipment in These Factories, Increasing Productivity and Minimizing Errors. the Digital Twins Communicate with the Machines to Furnish Sensitive Data and Instructions, Which Must Be Protected from Tampering. Authentication Rescues the Digital and Physical Twins from Menacing Attacks Such as Privileged Insider, Impersonation, Ephemeral Secret Leakage (ESL) and Man-In-The-Middle (MiTM) Attacks. to This End, We Propose Lightweight Authentication among the Digital and Physical Twins with the Undeniability of Issued Commands and Deniable Key Agreement. It Achieves Perfect …

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Optimizing Uav-Assisted Data Collection In Iot Sensor Networks Using Dual Cluster Head Strategy, Keiwan Soltani, Federico Coro, Sajal K. Das Jan 2024

Optimizing Uav-Assisted Data Collection In Iot Sensor Networks Using Dual Cluster Head Strategy, Keiwan Soltani, Federico Coro, Sajal K. Das

Computer Science Faculty Research & Creative Works

The proliferation of the Internet of Things (IoT) has significantly impacted the integration of digital and physical realms, with Wireless Sensor Networks (WSN s) playing a crucial role. However, these sensor nodes often face challenges related to battery constraints and deployment in inaccessible terrains. The advent of Unmanned Aerial Vehicles (UAVs) presents a transformative solution, particularly for data collection from remote IoT devices. This work explores the application of UAV s to improve data collection in dense IoT sensor networks. We propose a novel approach called optimizing UAV-assisted data collection in IoT sensor networks using Dual Cluster Head (UAVDCH) that …

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Achieving Project Objectives And Improving Functions: The Benefits Of Ai And Construction Technologies, Fareed Salih, Islam H. El-Adaway Jan 2024

Achieving Project Objectives And Improving Functions: The Benefits Of Ai And Construction Technologies, Fareed Salih, Islam H. El-Adaway

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

The Construction Industry Is Increasingly Incorporating Artificial Intelligence (AI) And Construction Technologies Into Projects. However, It Lags Behind Other Industries In Terms Of Digital Transformation. One Of The Reasons For This Disparity Is The Lack Of Evidence-Based Information On AI And Technologies In Construction Projects. Hence, This Research Aims To Comprehensively Understand The Benefits Of AI Techniques And Construction Technologies And Their Role In Achieving Objectives And Improving Functions. To This End, The Authors Followed A Three-Step Research Methodology. Firstly, An Extensive Literature Review Was Conducted To Identify 4 AI Techniques, 13 Construction Technologies, And 28 Benefits Relevant To Their …

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Minerrouter : Effective Message Routing Using Contact-Graphs And Location Prediction In Underground Mine, Abhay Goyal, Sanjay Madria, Samuel Frimpong Jan 2024

Minerrouter : Effective Message Routing Using Contact-Graphs And Location Prediction In Underground Mine, Abhay Goyal, Sanjay Madria, Samuel Frimpong

Computer Science Faculty Research & Creative Works

Location-based distributed communication in underground mines has been a hard problem to solve due to unreliable centralized architecture such as leaky feeder systems, high attenuation, and the unavailability of GPS signals. Delay Tolerant Networks (DTN) enable decentralized message routing using the store-carry-forward method that can help in creating situational awareness needed to handle emergency and disaster scenarios. The ability to predict where the DTN nodes (miner) might have been at/are headed to (with respect to the mine regions and pillars) at different times, combined with contact-based routing and intelligent handling of buffer, can be used for better delivery of messages. …

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