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Full-Text Articles in Entire DC Network
Elara Conference - Techniques & Technologies To Support Sustainable Education In The Academic Sphere Year Ii Book 2 Vol 1, European Common Laboratory For Pedagogical Action-Research And Student-Centred Learning (Elara)
Elara Conference - Techniques & Technologies To Support Sustainable Education In The Academic Sphere Year Ii Book 2 Vol 1, European Common Laboratory For Pedagogical Action-Research And Student-Centred Learning (Elara)
Publications
The Fourth Industrial Revolution was and s till is focused on digitalising processes and using AI to increase productivity. Industry 5.0, on the other hand, focuses on the human factor and the human as the centre of the production process. According to the new paradigm, technology should benefit humans, and human s, in turn, should actively collaborate with machines. In other words, while Industry 4.0 wa s based on the relationship between machines and IT systems, Industry 5.0 brings together the strengths of humans and machines. Following this train of thought, we have come up with the idea to initiate …
Quantification Of Swelling In Hematite Pellets Reduced Using Hydrogen–Nitrogen Gas Mixture, Amogh Meshram, Yuri Korobeinikov, Xingwen Wei, Ronald J. O'Malley, Seetharaman Sridhar
Quantification Of Swelling In Hematite Pellets Reduced Using Hydrogen–Nitrogen Gas Mixture, Amogh Meshram, Yuri Korobeinikov, Xingwen Wei, Ronald J. O'Malley, Seetharaman Sridhar
Materials Science and Engineering Faculty Research & Creative Works
Iron ore pellets are reduced in a 50%H2–50%N2 1 atm gas mixture at 750, 800, 850, 900, and 950 °C while simultaneously documenting swelling (change in pellet radius) and weight change. Swelling increases with increasing temperature, with catastrophic swelling (>20% of reduction swelling index) observed at 850, 900, and 950 °C. As the pellet is reduced, the pellet radius increases until 40–50% reduction is achieved, followed by a decrease in diameter beyond 40–50% reduction at 750 and 850 °C. At 950 °C, the pellet radius continues to increase with additional pellet reduction without any subsequent decrease in diameter. Scanning …
A 30-Year Time Series Analysis Of The Impact Of Climate Change On Corn Yield In Iowa Using The Autoregressive Distributed Lag Model – 1992 To 2022, Tesleem Ajisafe
A 30-Year Time Series Analysis Of The Impact Of Climate Change On Corn Yield In Iowa Using The Autoregressive Distributed Lag Model – 1992 To 2022, Tesleem Ajisafe
Dissertations and Theses @ UNI
Climate change poses significant socio-economic challenges globally, notably altering weather patterns and increasing the frequency and severity of extreme weather events (Seneviratne et al. 2021). This study investigates the impact of climate change on corn yield in Iowa from 1992 to 2022, using the autoregressive distributed lag (ARDL) model to analyze time series data on temperature, precipitation, and corn yield at the county level. Iowa, the leading corn producer in the US (Xu, Twine, & Girvetz 2016), has experienced an 8% increase in precipitation from 1873 to 2008, with notable effects in the eastern region (“Climate Change,” n.d.). A detrending …
A Novel Physics-Assisted Genetic Algorithm For Decoupling Capacitor Optimization, Li Jiang, Ling Zhang, Shurun Tan, Da Li, Chulsoon Hwang, Jun Fan, Er Ping Li
A Novel Physics-Assisted Genetic Algorithm For Decoupling Capacitor Optimization, Li Jiang, Ling Zhang, Shurun Tan, Da Li, Chulsoon Hwang, Jun Fan, Er Ping Li
Electrical and Computer Engineering Faculty Research & Creative Works
This article proposes a new physics-assisted genetic algorithm (PAGA) for decoupling capacitor (decap) optimization in power distribution networks (PDNs), which is a highly efficient approach to minimizing the number of decaps within an enormous search space. In the proposed PAGA method, the priority of the decap ports is first determined based on their physical loop inductances. Then, an initial solution is quickly obtained by placing decaps sequentially on the port with the highest priority. Subsequently, a GA with prior physical knowledge is developed to find better decap solutions progressively. A port removal scheme that eliminates the low-priority ports and a …
Statistical Eye Diagrams For High-Speed Interconnects Of Packages: A Review, Junyong Park, Donghyun Kim
Statistical Eye Diagrams For High-Speed Interconnects Of Packages: A Review, Junyong Park, Donghyun Kim
Electrical and Computer Engineering Faculty Research & Creative Works
An eye diagram, a critical metric in signal integrity analysis for high-speed interconnects such as packages, interposer, and printed circuit boards (PCBs), is generated by superposition of the received waveform. Obtaining an eye diagram is time-consuming, thus signal integrity analysis is inefficient. This article reviews that have been proposed to overcome this limitation. The statistical eye diagram provides a probability distribution depending on a sampling time and voltage, therefore it can be expanded to other metrics, such as the bit-error rate and shmoo plot. This article introduces previous research on statistical eye diagrams applied to complementary metal-oxide-semiconductors (CMOSs), noise, and …
A Segmentation Approach For Predicting Plane Wave Coupling To Pcb Structures, Shengxuan Xia, James Hunter, Aaron Harmon, Ahmed M. Hassan, Victor Khilkevich, Daryl G. Beetner
A Segmentation Approach For Predicting Plane Wave Coupling To Pcb Structures, Shengxuan Xia, James Hunter, Aaron Harmon, Ahmed M. Hassan, Victor Khilkevich, Daryl G. Beetner
Electrical and Computer Engineering Faculty Research & Creative Works
Evaluating the far-field radio frequency (RF) susceptibility of electronic devices often depends on extensive testing or full wave simulations. These methods are effective when complete system information is available but require substantial time and resources to evaluate a large number of variations in system configurations, where trace routings, integrated circuit (IC) package styles, trace terminations, arrival angle, and polarization of incoming wave, etc., are varied from one configuration to another. The goal of the following article is to develop simulation techniques for studying the statistical characteristics of coupling to typical printed circuit board (PCB) structures. Simulation time can be reduced …
Time-Resolved Electromagnetic Near-Field Scanning: Dual Sparse Sampling In Time And Space, Yanming Zhang, Peifeng Ma, Lijun Jiang, Steven Gao
Time-Resolved Electromagnetic Near-Field Scanning: Dual Sparse Sampling In Time And Space, Yanming Zhang, Peifeng Ma, Lijun Jiang, Steven Gao
Electrical and Computer Engineering Faculty Research & Creative Works
Time-resolved electromagnetic near-field scanning plays a pivotal role in antenna measurement and unraveling complex electromagnetic interference and compatibility issues. However, the rapid acquisition of high-resolution spatio–temporal data remains challenging due to physical constraints, such as moving the probe position and allowing sufficient time for sampling. This article presents a novel hybrid approach combining kriging for sparse spatial measurement, compressed sensing (cs) for sparse temporal sampling, and dynamic mode decomposition (dmd) for comprehensive analysis of the dual-sparse sampling electromagnetic near-field data. We leverage cs to optimize sparse sampling in the time domain and latin hypercube sampling to guide the probe position …
An Equivalent Coil Model Of A Wireless Power Transfer System Including Eddy Loss, Hanyu Zhang, Daryl G. Beetner
An Equivalent Coil Model Of A Wireless Power Transfer System Including Eddy Loss, Hanyu Zhang, Daryl G. Beetner
Electrical and Computer Engineering Faculty Research & Creative Works
A wireless power transfer (WPT) system suffers from eddy loss if a conductive object is placed near the coupling coil. In this paper, a 3-coil equivalent circuit model for the coupling coil in a WPT system is proposed for analyzing the eddy loss due to nearby conductors. This model uses a third coil with inductive coupling to the original transmitting and receiving coils to model the eddy loss. The proposed model was validated by comparing the Z-parameters with a full-wave simulation and showing good correlation over the frequency of interest, where the traditional 2-coil model fails. The 3-coil model is …
Sensor Tasking For Low Earth Orbit Objects: Leveraging Space Sensor Data For Ground-Based Optical Observations, Smriti Nandan Paul, Hang Woon Lee
Sensor Tasking For Low Earth Orbit Objects: Leveraging Space Sensor Data For Ground-Based Optical Observations, Smriti Nandan Paul, Hang Woon Lee
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Because of recent advancements in space technologies, easier and more economical access to space, and an increase in commercial interests, the near-Earth space environment has witnessed an exploding number of objects being put into orbit. In particular, the low Earth orbit (LEO) region is at an increased risk of orbital collisions from large satellite constellation projects. Thus, monitoring LEO objects for space situational awareness and space traffic management has become increasingly imperative. In this paper, we use the concept of limited-CDF (cumulative distribution function) surface and mutual information for designing sensor tasking algorithms focusing on regular observation of known catalog …
Damage Initiation Of 15v38 Steel Bar During Square-To-Round Hot Rolling Process, Siva Sai Krishna Dasari, Henry Adekola Haffner, K. Chandrashekhara, Mario F. Buchley, Simon N. Lekakh, Ronald J. O'Malley
Damage Initiation Of 15v38 Steel Bar During Square-To-Round Hot Rolling Process, Siva Sai Krishna Dasari, Henry Adekola Haffner, K. Chandrashekhara, Mario F. Buchley, Simon N. Lekakh, Ronald J. O'Malley
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Hot rolling processes have been extensively used to produce round bars by reducing the cross-sectional area of continuously cast steel. The current trend toward increasing productivity often requires a more aggressive reduction per pass. Establishing safe and optimized hot rolling parameters must be determined to avoid damage while deforming the specific steel composition. Understanding the damage mechanism during the metal forming process is vital for product quality. Herein, a combined experimental and simulation approach is developed to track the evolution potential damage during hot bar rolling. Hot tension tests are conducted on as-cast vanadium micro alloyed 15V38 steel at different …
L∞ Bounds For Transient Growth In Repetitive And Iterative Learning Control Systems, Douglas A. Bristow, John R. Singler
L∞ Bounds For Transient Growth In Repetitive And Iterative Learning Control Systems, Douglas A. Bristow, John R. Singler
Mechanical and Aerospace Engineering Faculty Research & Creative Works
This paper revisits the problem of large transient growth in Iterative Learning Control (ILC) and Repetitive Process Control (RPC) systems. In ILC and RPC problems a process is repeated iteratively, with new control calculations occurring in between each iteration. Large transient growth refers to the propensity of some control algorithms to grow error exponentially before eventually converging. While robust monotonic convergence algorithms (in which monotonic convergence is guaranteed usually in exchange for a small loss in performance) have largely eliminated the concern for large transient growth in ILC, similar results cannot always be obtained in RPC. The emergence of additive …
Optimal Tilt-Wing Evtol Takeoff Trajectory Prediction Using Regression Generative Adversarial Networks, Shuan Tai Yeh, Xiaosong Du
Optimal Tilt-Wing Evtol Takeoff Trajectory Prediction Using Regression Generative Adversarial Networks, Shuan Tai Yeh, Xiaosong Du
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Electric vertical takeoff and landing (eVTOL) aircraft have attracted tremendous attention nowadays due to their flexible maneuverability, precise control, cost efficiency, and low noise. The optimal takeoff trajectory design is a key component of cost-effective and passenger-friendly eVTOL systems. However, conventional design optimization is typically computationally prohibitive due to the adoption of high-fidelity simulation models in an iterative manner. Machine learning (ML) allows rapid decision making; however, new ML surrogate modeling architectures and strategies are still desired to address large-scale problems. Therefore, we showcase a novel regression generative adversarial network (regGAN) surrogate for fast interactive optimal takeoff trajectory predictions of …
Development Of A Regional Climate Change Model For Aedes Vigilax And Aedes Camptorhynchus (Diptera: Culicidae) In Perth, Western Australia, Kerry Staples, Peter J. Neville, Steven Richardson, Jacques Oosthuizen
Development Of A Regional Climate Change Model For Aedes Vigilax And Aedes Camptorhynchus (Diptera: Culicidae) In Perth, Western Australia, Kerry Staples, Peter J. Neville, Steven Richardson, Jacques Oosthuizen
Research outputs 2022 to 2026
Mosquito-borne disease is a significant public health issue and within Australia Ross River virus (RRV) is the most reported. This study combines a mechanistic model of mosquito development for two mosquito vectors; Aedes vigilax and Aedes camptorhynchus, with climate projections from three climate models for two Representative Concentration Pathways (RCPs), to examine the possible effects of climate change and sea-level rise on a temperate tidal saltmarsh habitat in Perth, Western Australia. The projections were run under no accretion and accretion scenarios using a known mosquito habitat as a case study. This improves our understanding of the possible implications of sea-level …
Enhancing Water Safety: Exploring Recent Technological Approaches For Drowning Detection, Salman Jalalifar, Andrew Belford, Eila Erfani, Amir Razmjou, Rouzbeh Abbassi, Masoud Mohseni-Dargah, Mohsen Asadnia
Enhancing Water Safety: Exploring Recent Technological Approaches For Drowning Detection, Salman Jalalifar, Andrew Belford, Eila Erfani, Amir Razmjou, Rouzbeh Abbassi, Masoud Mohseni-Dargah, Mohsen Asadnia
Research outputs 2022 to 2026
Drowning poses a significant threat, resulting in unexpected injuries and fatalities. To promote water sports activities, it is crucial to develop surveillance systems that enhance safety around pools and waterways. This paper presents an overview of recent advancements in drowning detection, with a specific focus on image processing and sensor-based methods. Furthermore, the potential of artificial intelligence (AI), machine learning algorithms (MLAs), and robotics technology in this field is explored. The review examines the technological challenges, benefits, and drawbacks associated with these approaches. The findings reveal that image processing and sensor-based technologies are the most effective approaches for drowning detection …
Tailored (La0.2pr0.2nd0.2tb0.2dy0.2)2ce2o7 As A Highly Active And Stable Nanocatalyst For The Oxygen Evolution Reaction, Sreya Paladugu, Ibrahim Munkaila Abdullahi, Palani Raja Jothi, Bo Jiang, Manashi Nath, Katharine Page
Tailored (La0.2pr0.2nd0.2tb0.2dy0.2)2ce2o7 As A Highly Active And Stable Nanocatalyst For The Oxygen Evolution Reaction, Sreya Paladugu, Ibrahim Munkaila Abdullahi, Palani Raja Jothi, Bo Jiang, Manashi Nath, Katharine Page
Chemistry Faculty Research & Creative Works
Designing highly active and robust catalysts for the oxygen evolution reaction is key to improving the overall efficiency of the water splitting reaction. It has been previously demonstrated that evaporation induced self-assembly (EISA) can be used to synthesize highly porous and high surface area cerate-based fluorite nano catalysts, and that substitution of Ce with 50% rare earth (RE) cations significantly improves electrocatalyst activity. Herein, the defect structure of the best performing nano catalyst in the series are further explored, Nd2Ce2O7, with a combination of neutron diffraction and neutron pair distribution function analysis. It is …
Perfect Polar Alignment Of Parallel Beloamphiphile Layers: Improved Structural Design Bias Realized In Ferroelectric Crystals Of The Novel “Methoxyphenyl Series Of Acetophenone Azines”, Harmeet Bhoday, Nathan Knotts, Rainer Glaser
Perfect Polar Alignment Of Parallel Beloamphiphile Layers: Improved Structural Design Bias Realized In Ferroelectric Crystals Of The Novel “Methoxyphenyl Series Of Acetophenone Azines”, Harmeet Bhoday, Nathan Knotts, Rainer Glaser
Chemistry Faculty Research & Creative Works
An Improved Design Is Described For Ferroelectric Crystals And Implemented With The "Methoxyphenyl Series" Of Acetophenone Azines, (MeO−Ph, Y)-Azines With Y=F (1), Cl (2), Br (3), Or I (4). The Crystal Structures Of These Azines Exhibit Polar Stacking Of Parallel Beloamphiphile Monolayers (PBAMs). Azines 1, 3, And 4 Form True Racemates Whereas Chloroazine 2 Crystallizes As A Kryptoracemate. Azines 1–4 Are Helical Because Of The N−N Bond Conformation. In True Racemates The Molecules Of Opposite Helicity (M And P) Are Enantiomers A(M) And A*(P) While In Kryptoracemates They Are Diastereomers A(M) And B*(P). The Stacking Mode Of PBAMs Is Influenced …
Improving Aggregate Abrasion Resistance Prediction Via Micro-Deval Test Using Ensemble Machine Learning Techniques, Alireza Roshan, Magdy Abdelrahman
Improving Aggregate Abrasion Resistance Prediction Via Micro-Deval Test Using Ensemble Machine Learning Techniques, Alireza Roshan, Magdy Abdelrahman
Civil, Architectural and Environmental Engineering Faculty Research & Creative Works
Aggregate is the most extracted material from the world's mines and widely used in civil and construction projects. The Micro-Deval abrasion test (MD) is one of the most important tests that provides characteristics of crushed aggregates that show their resistance against mechanical abrasive factors such as repeated impact loading. The impact of various factors on abrasive resistance properties of aggregates has led researchers to seek correlations, often focusing on limited data samples, leading to reduced accuracy. This study employs machine learning (ML) methods to predict MD abrasion values, considering diverse aggregate properties. Various ensemble ML methods were applied, revealing the …
Photogrammetry-Based Method For Measuring Volume Changes Of Soil Specimens During Critical Phases Of Triaxial Testing, Sara Fayek, Xiong Zhang, Pingxin Xia
Photogrammetry-Based Method For Measuring Volume Changes Of Soil Specimens During Critical Phases Of Triaxial Testing, Sara Fayek, Xiong Zhang, Pingxin Xia
Civil, Architectural and Environmental Engineering Faculty Research & Creative Works
Triaxial tests has been routinely used to measure the stress–strain relationship for geomaterials. During triaxial testing, many sources of errors that cannot be completely avoided but are often ignored or approximated using empirical equations. This paper presents a systematic investigation of soil volume change, volume strain nonuniformity, and cross-sectional calculation along the specimen during triaxial testing using a photogrammetry-based method. Consolidated drained triaxial tests were performed in which two parallel measurements were taken: (1) relative volume using the conventional triaxial testing and (2) absolute volume using the photogrammetry-based method. The difference in the observed volume and void ratio measurements between …
Two-Center And Path Interference In Dissociative Capture In P+ H2 Collisions, S. Bastola, M. Dhital, B. Lamichhane, A. Silvus, R. Lomsadze, A. Hasan, A. Igarashi, Michael Schulz
Two-Center And Path Interference In Dissociative Capture In P+ H2 Collisions, S. Bastola, M. Dhital, B. Lamichhane, A. Silvus, R. Lomsadze, A. Hasan, A. Igarashi, Michael Schulz
Physics Faculty Research & Creative Works
We have measured and calculated fully differential cross sections (FDCS) for dissociative capture in 75-keV p+H2 collisions. FDCS were analyzed in the kinetic energy release (KER) ranges 0 to 2.1 eV and 4 to 7 eV for two different molecular orientations. In the latter range, dissociation is dominated by electronic excitation to the 2pπu state. Here, we observed two-center interference for an orientation in the plane perpendicular to the initial beam axis and parallel to the transverse momentum transfer. The interference pattern is afflicted with a constant phase shift of π. In the range KER=0 to 2.1 eV, dissociation is …
Spectrum And Quench-Induced Dynamics Of Spin-Orbit-Coupled Quantum Droplets, Sonali Gangwar, Rajamanickam Ravisankar, S. (Simeon) I. Mistakidis, Paulsamy Muruganandam, Pankaj Kumar Mishra
Spectrum And Quench-Induced Dynamics Of Spin-Orbit-Coupled Quantum Droplets, Sonali Gangwar, Rajamanickam Ravisankar, S. (Simeon) I. Mistakidis, Paulsamy Muruganandam, Pankaj Kumar Mishra
Physics Faculty Research & Creative Works
We investigate the ground state and dynamics of one-dimensional spin-orbit coupled (SOC) quantum droplets within the extended Gross-Pitaevskii approach. As the SOC wave number increases, stripe droplet patterns emerge, with a flat-top background, for larger particle numbers. The surface energy decays following a power-law with respect to the interactions. At small SOC wave numbers, a transition from Gaussian to flat-top droplets occurs for either a larger number of atoms or reduced intercomponent attraction. The excitation spectrum shows that droplets for relatively small SOC wave numbers are stable, otherwise stripe droplets feature instabilities as a function of the particle number or …
Disseminating Over-The-Air Updates Via Intelligent Labeling In Multi-Tier Networks, Atefeh Asayesh, Asad Waqar Malik, Sajal K. Das
Disseminating Over-The-Air Updates Via Intelligent Labeling In Multi-Tier Networks, Atefeh Asayesh, Asad Waqar Malik, Sajal K. Das
Computer Science Faculty Research & Creative Works
Connected Vehicles Rely on Sophisticated Software Systems for Diverse Features, Including Navigation, Entertainment, Communication, and Safety Functions. as Technology Continues to Advance, the Reliance on Software in Connected Vehicles Becomes Increasingly Integral to their overall Performance and the Delivery of Innovative Features. Therefore, in the Domain of Software-Enabled Automobiles, the Implementation of over-The-Air (OTA) Software Updates is Deemed Essential for the Dissemination of Software and Fixes in Connected Vehicles. the Conventional Method of Addressing This Matter Entailed Manufacturers Undertaking the Task of Recalling Outdated Vehicles; However, the Central Issue Lies in the Considerable Challenge of Effectively Notifying Owners through Recall …
Undeniable Authentication Of Digital Twin-Managed Smart Microfactory, Anusha Vangala, Ashok Kumar Das, Sajal K. Das
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 …
Lease: Leveraging Energy-Awareness In Serverless Edge For Latency-Sensitive Iot Services, Aastik Verma, Anurag Satpathy, Sajal K. Das, Sourav Kanti Addya
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, …
Stitching Satellites To The Edge: Pervasive And Efficient Federated Leo Satellite Learning, Mohamed Elmahallawy, Tony Tie Luo
Stitching Satellites To The Edge: Pervasive And Efficient Federated Leo Satellite Learning, Mohamed Elmahallawy, Tony Tie Luo
Computer Science Faculty Research & Creative Works
In the Ambitious Realm of Space AI, the Integration of Federated Learning (FL) with Low Earth Orbit (LEO) Satellite Constellations Holds Immense Promise. However, Many Challenges Persist in Terms of Feasibility, Learning Efficiency, and Convergence. These Hurdles Stem from the Bottleneck in Communication, Characterized by Sporadic and Irregular Connectivity between LEO Satellites and Ground Stations, Coupled with the Limited Computation Capability of Satellite Edge Computing (SEC). This Paper Proposes a Novel FL-SEC Framework that Empowers LEO Satellites to Execute Large-Scale Machine Learning (ML) Tasks Onboard Efficiently. its Key Components Include I) Personalized Learning Via Divide-And-Conquer, Which Identifies and Eliminates Redundant …
Development Of A Deep Neural Network And Empirical Model For Predicting Local Gas Holdup Profiles In Bubble Columns, Sebastián Uribe, Ahmed Alalou, Mario E. Cordero, Muthanna H. Al-Dahhan
Development Of A Deep Neural Network And Empirical Model For Predicting Local Gas Holdup Profiles In Bubble Columns, Sebastián Uribe, Ahmed Alalou, Mario E. Cordero, Muthanna H. Al-Dahhan
Chemical and Biochemical Engineering Faculty Research & Creative Works
Estimating local gas holdup profiles in bubble columns is key for their performance evaluation and optimization, as well as for design and scale-up tasks. Up to the current day, there are important limitations in the accuracy and range of applicability of the available models in literature. Two alternatives for the prediction of such local fields can be found in the application of empirical models and the development of deep neural networks (DNN). The main drawback preventing the application of these techniques in previous years was the availability of a large enough databank of local gas holdup experimental measurements. Advances over …
Communication-Efficient Federated Learning For Leo Constellations Integrated With Haps Using Hybrid Noma-Ofdm, Mohamed Elmahallawy, Tony T. Luo, Khaled Ramadan
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) …
Mobility Management In Tsch-Based Industrial Wireless Networks, Marco Pettorali, Francesca Righetti, Carlo Vallati, Sajal K. Das, Giuseppe Anastasi
Mobility Management In Tsch-Based Industrial Wireless Networks, Marco Pettorali, Francesca Righetti, Carlo Vallati, Sajal K. Das, Giuseppe Anastasi
Computer Science Faculty Research & Creative Works
Wireless Sensor and Actuator Networks (WSANs) are an effective technology for improving the efficiency and productivity in many industrial domains and are also the building blocks for the Industrial Internet of Things (IIoT). To support this trend, the IEEE has defined the 802.5.4 Time-Slotted Channel Hopping (TSCH) protocol. Unfortunately, TSCH does not provide any mechanism to manage node mobility, while many current industrial applications involve Mobile Nodes (MNs), e.g., mobile robots or wearable devices carried by workers. In this article, we present a framework to efficiently manage mobility in TSCH networks, by proposing an enhanced version of the Synchronized Single-hop …
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
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 …
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
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 …
Personalized Federated Graph Learning On Non-Iid Electronic Health Records, Tao Tang, Zhuoyang Han, Zhen Cai, Shuo Yu, Xiaokang Zhou, Taiwo Oseni, Sajal K. Das
Personalized Federated Graph Learning On Non-Iid Electronic Health Records, Tao Tang, Zhuoyang Han, Zhen Cai, Shuo Yu, Xiaokang Zhou, Taiwo Oseni, Sajal K. Das
Computer Science Faculty Research & Creative Works
Understanding The Latent Disease Patterns Embedded In Electronic Health Records (EHRs) Is Crucial For Making Precise And Proactive Healthcare Decisions. Federated Graph Learning-Based Methods Are Commonly Employed To Extract Complex Disease Patterns From The Distributed EHRs Without Sharing The Client-Side Raw Data. However, The Intrinsic Characteristics Of The Distributed EHRs Are Typically Non-Independent And Identically Distributed (Non-IID), Significantly Bringing Challenges Related To Data Imbalance And Leading To A Notable Decrease In The Effectiveness Of Making Healthcare Decisions Derived From The Global Model. To Address These Challenges, We Introduce A Novel Personalized Federated Learning Framework Named PEARL, Which Is Designed For …