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2024

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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 Jan 2024

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 …

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Region-Specific Drivers Cause Low Organic Carbon Stocks And Sequestration Rates In The Saltmarsh Soils Of Southern Scandinavia, Carmen Leiva-Dueñas, Anna E. L. Graversen, Gary T. Banta, Jeppe N. Hansen, Marie L. K. Schrøter, Pere Masqué, Marianne Holmer, Dorte Krause-Jensen Jan 2024

Region-Specific Drivers Cause Low Organic Carbon Stocks And Sequestration Rates In The Saltmarsh Soils Of Southern Scandinavia, Carmen Leiva-Dueñas, Anna E. L. Graversen, Gary T. Banta, Jeppe N. Hansen, Marie L. K. Schrøter, Pere Masqué, Marianne Holmer, Dorte Krause-Jensen

Research outputs 2022 to 2026

Saltmarshes are known for their ability to act as effective sinks of organic carbon (OC) and their protection and restoration could potentially slow down the pace of global warming. However, regional estimates of saltmarsh OC storage are often missing, including for the Nordic region. To address this knowledge gap, we assessed OC storage and accumulation rates in 17 saltmarshes distributed along the Danish coasts and investigated the main drivers of soil OC storage. Danish saltmarshes store a median of 10 kg OC m−2 (interquartile range, IQR: 13.5–7.6) in the top meter and sequester 31.5 g OC m−2 yr−1 (IQR: 41.6–15.7). …

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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 Jan 2024

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 …

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Professionalism In Artificial Intelligence: The Link Between Technology And Ethics, Anton Klarin, Hossein Ali Abadi, Rifat Sharmelly Jan 2024

Professionalism In Artificial Intelligence: The Link Between Technology And Ethics, Anton Klarin, Hossein Ali Abadi, Rifat Sharmelly

Research outputs 2022 to 2026

Ethical conduct of artificial intelligence (AI) is undoubtedly becoming an ever more pressing issue considering the inevitable integration of these technologies into our lives. The literature so far discussed the responsibility domains of AI; this study asks the question of how to instil ethicality into AI technologies. Through a three-step review of the AI ethics literature, we find that (i) the literature is weak in identifying solutions in ensuring ethical conduct of AI, (ii) the role of professional conduct is underexplored, and (iii) based on the values extracted from studies about AI ethical breaches, we thus propose a conceptual framework …

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Simulating Compatible Solute Biosynthesis Using A Metabolic Flux Model Of The Biomining Acidophile, Acidithiobacillus Ferrooxidans Atcc 23270, Himel N. Khaleque, Hadi Nazem-Bokaee, Yosephine Gumulya, Ross P. Carlson, Anna H. Kaksonen Jan 2024

Simulating Compatible Solute Biosynthesis Using A Metabolic Flux Model Of The Biomining Acidophile, Acidithiobacillus Ferrooxidans Atcc 23270, Himel N. Khaleque, Hadi Nazem-Bokaee, Yosephine Gumulya, Ross P. Carlson, Anna H. Kaksonen

Research outputs 2022 to 2026

Halotolerant, acidophilic, bioleaching microorganisms are crucial to biomining operations that utilize saline water. Compatible solutes play an important role in the adaptation of these microorganisms to saline environments. Acidithiobacillus ferrooxidans ATCC 23270, an iron- and sulfur-oxidizing acidophilic bacterium, synthesizes trehalose as its native compatible solute but is still sensitive to salinity. Recently, halotolerant bioleaching bacteria were found to use ectoine as their key compatible solute. Previously, bioleaching bacteria were recalcitrant to genetic manipulation; however, recent advancements in genetic tools and techniques allow successful genetic modification of A. ferrooxidans ATCC 23270. Therefore, this study aimed to test, in silico, the effect …

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An Ecosystem Of Knowledge: Relationality As A Framework For Teachers To Infuse Indigenous Perspectives In Curriculum, Maryanne Macdonald, Sarah Booth, Libby Jackson-Barrett Jan 2024

An Ecosystem Of Knowledge: Relationality As A Framework For Teachers To Infuse Indigenous Perspectives In Curriculum, Maryanne Macdonald, Sarah Booth, Libby Jackson-Barrett

Research outputs 2022 to 2026

New data is presented from two studies involving thirteen practising secondary teachers and twelve pre-service early childhood, primary and secondary teachers in Australia. The first study explored how non-Indigenous practising teacher identities, shaped by external and policy discourse, create obstacles to teachers’ willingness and confidence in infusing Indigenous perspectives in curriculum. With this knowledge in hand, the researchers utilised a Design-Based Research methodology to conduct a second study with pre-service (ITE) teachers, exploring the power of relationality as a framework to re-shape non-Indigenous pre-service teachers’ conceptualisation of racial and place-based identity. By enabling non-Indigenous pre-service teachers to construct an authentic …

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Dna Origami-Assisted Regioselective Organization Of Anisotropic Gold Nanotriangle Clusters, Wenyan Liu, Prashant Gupta, Yuwei Zhang, Krishna Thapa, Srikanth Singamaneni, Risheng Wang Jan 2024

Dna Origami-Assisted Regioselective Organization Of Anisotropic Gold Nanotriangle Clusters, Wenyan Liu, Prashant Gupta, Yuwei Zhang, Krishna Thapa, Srikanth Singamaneni, Risheng Wang

Chemistry Faculty Research & Creative Works

The manipulation of anisotropic nanoparticles, such as gold nanorods and nano prisms, has attracted great attention in nanotechnology due to their sensitive geometry-dependent properties. However. traditional synthesis and assembly methods for these particles face challenges in size uniformity and higher-order structuring. To address these limitations, this study presents a strategy using DNA origami triangles, not just as templates, but as encapsulating agents for gold nanotriangles (AuNTs). This method enables the construction of diverse nanoparticle clusters with precisely controlled distance and orientation. The formed clusters exhibit unique optical characteristics, demonstrated by UV-visible spectroscopy and supported by finite-difference time domain (FDTD) simulations. …

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High-Capacity Anode For Sodium-Ion Batteries Using Hard Carbons Derived From Polyurea-Cross-Linked Silica Xerogel Powders, Santhoshkumar Sundaramoorthy, Rushi U. Soni, Stephen Yaw Owusu, Sutapa Bhattacharya, A. B.M.Shaheen Ud Doulah, Vaibhav A. Edlabadkar, Chariklia Sotiriou-Leventis, Amitava Choudhury Jan 2024

High-Capacity Anode For Sodium-Ion Batteries Using Hard Carbons Derived From Polyurea-Cross-Linked Silica Xerogel Powders, Santhoshkumar Sundaramoorthy, Rushi U. Soni, Stephen Yaw Owusu, Sutapa Bhattacharya, A. B.M.Shaheen Ud Doulah, Vaibhav A. Edlabadkar, Chariklia Sotiriou-Leventis, Amitava Choudhury

Chemistry Faculty Research & Creative Works

In this article, we demonstrated carbon aerogel-silica composites derived from polyurea-cross-linked silica xerogel powders (C-PUA@silica) as anodes for Na-ion batteries. These xerogel-derived hard carbons with embedded silica showed a stable high capacity. Of the several hard carbon samples derived at different temperatures, the pyrolyzed sample at 800 °C (C-PUA@silica-800) showed a high capacity of 236 mAh/g at a current density of 10 mA/g and a stable cycle-life at 200 mAh/g. The galvanostatic charge-discharge curves displayed a sloping voltage profile reminiscent of the adsorption mechanism of Na+ storage. On the other hand, higher temperature-pyrolyzed samples at 1300 °C (C-PUA@silica-1300) displayed a …

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Boosting The Microbial Electrosynthesis Of Formate By Shewanella Oneidensis Mr-1 With An Ionic Liquid Cosolvent, Ashwini Dantanarayana, Wassim El Housseini, Kevin Beaver, Monica Brachi, Timothy P. Mcfadden, Shelley D. Minteer Jan 2024

Boosting The Microbial Electrosynthesis Of Formate By Shewanella Oneidensis Mr-1 With An Ionic Liquid Cosolvent, Ashwini Dantanarayana, Wassim El Housseini, Kevin Beaver, Monica Brachi, Timothy P. Mcfadden, Shelley D. Minteer

Chemistry Faculty Research & Creative Works

Microbial electrosynthesis (MES) is a rapidly growing technology at the forefront of sustainable chemistry, leveraging the ability of microorganisms to catalyze electrochemical reactions to synthesize valuable compounds from renewable energy sources. The reduction of CO2 is a major target application for MES, but research in this area has been stifled, especially with the use of direct electron transfer (DET)-based microbial systems. The major fundamental hurdle that needs to be overcome is the low efficiency of CO2 reduction largely attributed to minimal microbial access to CO2 owing to its low solubility in the electrolyte. With their tunable physical …

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Selected Trace Element Uptake By Rice Grain As Affected By Soil Arsenic, Water Management And Cultivar -A Field Investigation, Eric M. Farrow, Jianmin Wang, Honglan Shi, John Yang, Bin Hua, Baolin Deng Jan 2024

Selected Trace Element Uptake By Rice Grain As Affected By Soil Arsenic, Water Management And Cultivar -A Field Investigation, Eric M. Farrow, Jianmin Wang, Honglan Shi, John Yang, Bin Hua, Baolin Deng

Chemistry Faculty Research & Creative Works

Accumulation of arsenic (As) in rice grain was reported in many regions of the world, including the United States, which has been a threat to human health. This field research investigated the grain as accumulation and its relationship with the uptake of selenium (Se), molybdenum (Mo), and cadmium (Cd) in soils with and without monosodium methane arsonate (MSMA) amended, as effects of selected rice cultivars and water management. Results indicated that MSMA increased the accumulation of as and Se but decreased Mo for all six cultivars under four irrigation management. MSMA also increased grain-Cd in some cultivars. in no MSMA-amended …

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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 Jan 2024

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 …

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A Comparative Study Of Cationic Copper(I) Reagents Supported By Bipodal Tetramethylguanidinyl-Containing Ligands As Nitrene-Transfer Catalysts, Suraj Kumar Sahoo, Brent Harfmann, Himanshu Bhatia, Harish Singh, Srikanth Balijapelly, Amitava Choudhury, Pericles Stavropoulos Jan 2024

A Comparative Study Of Cationic Copper(I) Reagents Supported By Bipodal Tetramethylguanidinyl-Containing Ligands As Nitrene-Transfer Catalysts, Suraj Kumar Sahoo, Brent Harfmann, Himanshu Bhatia, Harish Singh, Srikanth Balijapelly, Amitava Choudhury, Pericles Stavropoulos

Chemistry Faculty Research & Creative Works

The Bipodal Compounds [(TMG2biphenN-R)CuI-NCMe](PF6) (R = Me, Ar (4-CF3Ph-)) And [(TMG2biphenN-Me)CuI-I] Have Been Synthesized With Ligands That Feature A Diarylmethyl- And Triaryl-Amine Framework And Superbasic Tetramethylguanidinyl Residues (TMG). The Cationic Cu(I) Sites Mediate Catalytic Nitrene-Transfer Reactions Between The Imidoiodinane PhI = NTs (Ts = Tosyl) And A Panel Of Styrenes In MeCN, To Afford Aziridines, Demonstrating Comparable Reactivity Profiles. The Copper Reagents Have Been Further Explored To Execute C-H Amination Reactions With A Variety Of Aliphatic And Aromatic Hydrocarbons And Two Distinct Nitrene Sources PhI = NTs And PhI = NTces (Tces = 2,2,2-Trichloroethylsulfamate) In Benzene/HFIP (10:2 V/v). Good Yields …

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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 Jan 2024

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 …

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Improving Aggregate Abrasion Resistance Prediction Via Micro-Deval Test Using Ensemble Machine Learning Techniques, Alireza Roshan, Magdy Abdelrahman Jan 2024

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 …

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Photogrammetry-Based Method For Measuring Volume Changes Of Soil Specimens During Critical Phases Of Triaxial Testing, Sara Fayek, Xiong Zhang, Pingxin Xia Jan 2024

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 …

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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 Jan 2024

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 …

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Spectrum And Quench-Induced Dynamics Of Spin-Orbit-Coupled Quantum Droplets, Sonali Gangwar, Rajamanickam Ravisankar, S. (Simeon) I. Mistakidis, Paulsamy Muruganandam, Pankaj Kumar Mishra Jan 2024

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 …

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Disseminating Over-The-Air Updates Via Intelligent Labeling In Multi-Tier Networks, Atefeh Asayesh, Asad Waqar Malik, Sajal K. Das Jan 2024

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 …

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A Model-Adaptive Random Search Actor Critic: Convergence Analysis And Inventory-Control Case Studies, Yuehan Luo, Jiaqiao Hu, Abhijit Gosavi Jan 2024

A Model-Adaptive Random Search Actor Critic: Convergence Analysis And Inventory-Control Case Studies, Yuehan Luo, Jiaqiao Hu, Abhijit Gosavi

Engineering Management and Systems Engineering Faculty Research & Creative Works

Reinforcement learning (RL) is an exciting area within the domain of Markov Decision Processes (MDPs) in which the underlying optimization problem is solved either in a simulator of the real-world system or via direct interaction with the real-world system, when its underlying transition probabilities are difficult to estimate. The latter is commonly true of large-scale, real-world MDPs with complex underlying transition dynamics. RL is currently being widely researched in the world of medicine/neuroscience after some spectacular success stories demonstrating super-human behavior in computer games. In this paper, we propose a new actor-critic-based RL algorithm for approximately solving continuous state/action MDPs …

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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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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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Stitching Satellites To The Edge: Pervasive And Efficient Federated Leo Satellite Learning, Mohamed Elmahallawy, Tony Tie Luo Jan 2024

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 …

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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 Jan 2024

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 …

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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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Mobility Management In Tsch-Based Industrial Wireless Networks, Marco Pettorali, Francesca Righetti, Carlo Vallati, Sajal K. Das, Giuseppe Anastasi Jan 2024

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 …

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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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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 Jan 2024

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 …

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Resource Aware Clustering For Tackling The Heterogeneity Of Participants In Federated Learning, Rahul Mishra, Hari Prabhat Gupta, Garvit Banga, Sajal K. Das Jan 2024

Resource Aware Clustering For Tackling The Heterogeneity Of Participants In Federated Learning, Rahul Mishra, Hari Prabhat Gupta, Garvit Banga, Sajal K. Das

Computer Science Faculty Research & Creative Works

Federated Learning Is A Training Framework That Enables Multiple Participants To Collaboratively Train A Shared Model While Preserving Data Privacy. The Heterogeneity Of Devices And Networking Resources Of The Participants Delay The Training And Aggregation. The Paper Introduces A Novel Approach To Federated Learning By Incorporating Resource-Aware Clustering. This Method Addresses The Challenges Posed By The Diverse Devices And Networking Resources Among Participants. Unlike Static Clustering Approaches, This Paper Proposes A Dynamic Method To Determine The Optimal Number Of Clusters Using Dunn Indices. It Enables Adaptability To The Varying Heterogeneity Levels Among Participants, Ensuring A Responsive And Customized Approach To …

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Collect Spatiotemporally Correlated Data In Iot Networks With An Energy-Constrained Uav, Wenzheng Xu, Heng Shao, Qunli Shen, Jian Peng, Wen Huang, Weifa Liang, Tang Liu, Xin Wei Yao, Tao Lin, Sajal K. Das Jan 2024

Collect Spatiotemporally Correlated Data In Iot Networks With An Energy-Constrained Uav, Wenzheng Xu, Heng Shao, Qunli Shen, Jian Peng, Wen Huang, Weifa Liang, Tang Liu, Xin Wei Yao, Tao Lin, Sajal K. Das

Computer Science Faculty Research & Creative Works

UAVs (Unmanned Aerial Vehicles) Are Promising Tools For Efficient Data Collections Of Sensors In IoT Networks. Existing Studies Exploited Both Spatial And Temporal Data Correlations To Reduce The Amount Of Collected Redundant Data, In Which Sensors Are First Partitioned Into Different Clusters, A Master Sensor In Each Cluster Then Collects Raw Data From Other Sensors And Compresses The Received Data. An Energy-Constrained UAV Finally Collects The Maximum Amount Of Compressed Data From Different Master Sensors. We However Notice That The Compressed Data From Only A Portion Of Clusters Are Collected By The UAV In The Existing Studies, While The Data …

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