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Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Keyword
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- Lifelong learning (6)
- Experience replay (3)
- Multilayer neural networks (3)
- Optimal tracking control (3)
- Singular value decomposition (3)
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- Artificial neural networks (2)
- Blockchain and Machine Learning/Artificial Intelligence (2)
- Blockchain for Internet of Things (2)
- Catastrophic forgetting (2)
- Dermoscopy (2)
- Hybrid learning (2)
- Task analysis (2)
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- 2D image technology (1)
- Actor critic (1)
- Adaptive Resonance Theory (1)
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- Amino Acid (1)
- Australian continent (1)
- Autonomous vehicles (1)
- Barrier Lyapunov function (1)
- Barrier function (1)
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- Biomarkers (1)
- Blast exposure (1)
- Blocking agent (1)
- Chromium acetate (1)
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- Contact graph routing (1)
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- Publication
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- Electrical and Computer Engineering Faculty Research & Creative Works (15)
- Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works (10)
- Chemistry Faculty Research & Creative Works (2)
- Computer Science Faculty Research & Creative Works (2)
- Civil, Architectural and Environmental Engineering Faculty Research & Creative Works (1)
Articles 1 - 30 of 33
Full-Text Articles in Physical Sciences and Mathematics
Demo-Abstract: A Dtn System For Tracking Miners Using Gae-Lstm And Contact Graph Routing In An Underground Mine, Abhay Goyal, Sanjay Kumar Madria, Samuel Frimpong
Demo-Abstract: A Dtn System For Tracking Miners Using Gae-Lstm And Contact Graph Routing In An Underground Mine, Abhay Goyal, Sanjay Kumar Madria, Samuel Frimpong
Computer Science Faculty Research & Creative Works
Localization and prediction of movement of miners in underground mines have been a constant problem more so during a mine disaster. Due to the unavailability of GPS signals, the pillars are used as a method to locate these miners, and thus, location prediction is also carried out with reference to these pillars. In this work, we demon- strate a Delay-tolerant Network (DTN) system called Miner-Finder that leverages Machine Learning (ML) framework (GAE-LSTM) that works on edge devices (e.g., mobile phones, tablets) to predict the location of miners in an underground mine. The information such as speed, angle, time, nearest pillar …
Qc-Sane: Robust Control In Drl Using Quantile Critic With Spiking Actor And Normalized Ensemble, Surbhi Gupta, Gaurav Singal, Deepak Garg, Sarangapani Jagannathan
Qc-Sane: Robust Control In Drl Using Quantile Critic With Spiking Actor And Normalized Ensemble, Surbhi Gupta, Gaurav Singal, Deepak Garg, Sarangapani Jagannathan
Electrical and Computer Engineering Faculty Research & Creative Works
Recently Introduced Deep Reinforcement Learning (DRL) Techniques in Discrete-Time Have Resulted in Significant Advances in Online Games, Robotics, and So On. Inspired from Recent Developments, We Have Proposed an Approach Referred to as Quantile Critic with Spiking Actor and Normalized Ensemble (QC-SANE) for Continuous Control Problems, Which Uses Quantile Loss to Train Critic and a Spiking Neural Network (NN) to Train an Ensemble of Actors. the NN Does an Internal Normalization using a Scaled Exponential Linear Unit (SELU) Activation Function and Ensures Robustness. the Empirical Study on Multijoint Dynamics with Contact (MuJoCo)-Based Environments Shows Improved Training and Test Results Than …
Kinetic Particle Simulations Of Plasma Charging At Lunar Craters Under Severe Conditions, David Lund, Xiaoming He, Daoru Frank Han
Kinetic Particle Simulations Of Plasma Charging At Lunar Craters Under Severe Conditions, David Lund, Xiaoming He, Daoru Frank Han
Mathematics and Statistics Faculty Research & Creative Works
This paper presents fully kinetic particle simulations of plasma charging at lunar craters with the presence of lunar lander modules using the recently developed Parallel Immersed-Finite-Element Particle-in-Cell (PIFE-PIC) code. The computation model explicitly includes the lunar regolith layer on top of the lunar bedrock, taking into account the regolith layer thickness and permittivity as well as the lunar lander module in the simulation domain, resolving a nontrivial surface terrain or lunar lander configuration. Simulations were carried out to study the lunar surface and lunar lander module charging near craters at the lunar terminator region under mean and severe plasma environments. …
Repeated Low-Level Blast Exposure Alters Urinary And Serum Metabolites, Austin Sigler, Jiandong Wu, Annalise Pfaff, Olajide Adetunji, Paul Ki-Souk Nam, Donald James, Casey Burton, Honglan Shi
Repeated Low-Level Blast Exposure Alters Urinary And Serum Metabolites, Austin Sigler, Jiandong Wu, Annalise Pfaff, Olajide Adetunji, Paul Ki-Souk Nam, Donald James, Casey Burton, Honglan Shi
Chemistry Faculty Research & Creative Works
Repeated exposure to low-level blast overpressures can produce biological changes and clinical sequelae that resemble mild traumatic brain injury (TBI). While recent efforts have revealed several protein biomarkers for axonal injury during repetitive blast exposure, this study aims to explore potential small molecule biomarkers of brain injury during repeated blast exposure. This study evaluated a panel of ten small molecule metabolites involved in neurotransmission, oxidative stress, and energy metabolism in the urine and serum of military personnel (n = 27) conducting breacher training with repeated exposure to low-level blasts. The metabolites were analyzed using HPLC—tandem mass spectrometry, and the Wilcoxon …
Dual Crosslinked Poly(Acrylamide-Co-N-Vinylpyrrolidone) Microspheres With Re-Crosslinking Ability For Fossil Energy Recovery, Jingyang Pu, Baojun Bai, Jiaming Geng, Na Zhang, Thomas P. Schuman
Dual Crosslinked Poly(Acrylamide-Co-N-Vinylpyrrolidone) Microspheres With Re-Crosslinking Ability For Fossil Energy Recovery, Jingyang Pu, Baojun Bai, Jiaming Geng, Na Zhang, Thomas P. Schuman
Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works
Microspheres have been proposed to be applied in controlling wastewater production for mature oilfields and migrating leakage for gas and nuclear waste storage. However, it remains challenging for stacked microspheres to maintain strong blocking ability in micron-sized small pores or fractures. In this study, a novel microsphere was developed with comprehensive properties including high deformability and long re-crosslinking time upon tunable swelling ratio for the applications. A dual covalent and physical crosslinking strategy was used to develop novel microspheres reinforced by a hydrogen bond (H-bond, between pyrrole ring and amide group) and coordination bond (between chromium acetate (CrAc) and carboxyl …
Sharprazor: Automatic Removal Of Hair And Ruler Marks From Dermoscopy Images, Reda Kasmi, Jason Hagerty, Reagan Harris Young, Norsang Lama, Januka Nepal, Jessica Miinch, William V. Stoecker, R. Joe Stanley
Sharprazor: Automatic Removal Of Hair And Ruler Marks From Dermoscopy Images, Reda Kasmi, Jason Hagerty, Reagan Harris Young, Norsang Lama, Januka Nepal, Jessica Miinch, William V. Stoecker, R. Joe Stanley
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Background: The removal of hair and ruler marks is critical in handcrafted image analysis of dermoscopic skin lesions. No other dermoscopic artifacts cause more problems in segmentation and structure detection. Purpose: The aim of the work is to detect both white and black hair, artifacts and finally inpaint correctly the image. Method: We introduce a new algorithm: SharpRazor, to detect hair and ruler marks and remove them from the image. Our multiple-filter approach detects hairs of varying widths within varying backgrounds, while avoiding detection of vessels and bubbles. The proposed algorithm utilizes grayscale plane modification, hair enhancement, segmentation using tri-directional …
Are Natural Fractures In Sandstone Reservoir: Water Wet – Mixed Wet – Or Oil Wet?, Salah Almudhhi, Laila Abdullah, Waleed Al-Bazzaz, Saleh Alsayegh, Hussien Alajaj, Ralph E. Flori
Are Natural Fractures In Sandstone Reservoir: Water Wet – Mixed Wet – Or Oil Wet?, Salah Almudhhi, Laila Abdullah, Waleed Al-Bazzaz, Saleh Alsayegh, Hussien Alajaj, Ralph E. Flori
Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works
This study accurately measures the wettability contact angle of native Kuwaiti sandstone reservoir that hosts mixed pore size distributions in both the tight sandstone matrix as well as the natural fracture (NF) embedded in it. Also, this study, effectively, investigates the geometrical size and shape of natural available voids whether matrix voids or NF voids captured in the rock 2D image frame system. Correspondingly, this study is, successfully, measure tight matrix, NF Pore wall, and NF pore opening wettability performance and recovery efficiency contributions inside the sandstone reservoir. A model pore/ grain contact angle wettability is generated. Therefore, this study …
Seismic Azimuthal Anisotropy Beneath A Fast Moving Ancient Continent: Constraints From Shear Wave Splitting Analysis In Australia, Kailun Ba, Stephen S. Gao, Jianguo Song, Kelly H. Liu
Seismic Azimuthal Anisotropy Beneath A Fast Moving Ancient Continent: Constraints From Shear Wave Splitting Analysis In Australia, Kailun Ba, Stephen S. Gao, Jianguo Song, Kelly H. Liu
Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works
Seismic Azimuthal Anisotropy Beneath Australia is Investigated using Splitting of the Teleseismic PKS, SKKS, and SKS Phases to Delineate Asthenospheric Flow and Lithospheric Deformation Beneath One of the Oldest and Fast-Moving Continents on Earth. in Total 511 Pairs of High-Quality Splitting Parameters Were Observed at 116 Seismic Stations. Unlike Other Stable Continental Areas in Africa, East Asia, and North America, Where Spatially Consistent Splitting Parameters Dominate, the Fast Orientations and Splitting Times Observed in Australia Show a Complex Pattern, with a Slightly Smaller Than Normal Average Splitting Time of 0.85 ± 0.33 S. on the North Australian Craton, the Fast …
Coreflooding Evaluation Of Fiber-Assisted Recrosslinkable Preformed Particle Gel Using An Open Fracture Model, Shuda Zhao, Ali Al Brahim, Junchen Liu, Baojun Bai, Thomas P. Schuman
Coreflooding Evaluation Of Fiber-Assisted Recrosslinkable Preformed Particle Gel Using An Open Fracture Model, Shuda Zhao, Ali Al Brahim, Junchen Liu, Baojun Bai, Thomas P. Schuman
Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works
Recrosslinkable Preformed Particle Gels (RPPGs) Have Been Used to Treat the Problem of Void Space Conduits (VSC) and repair the "Short-Circuited" Waterflood in Alaska's West Sak Field. Field Results Showed a 23% Increase in Success Rates over Typical Preformed Particle Gel (PPG) Treatments. in This Paper, We Evaluated Whether Adding Fiber into RPPGs Can Increase the RPPG Plugging Efficiency and Thus Further Improve the Success Rate. We Designed Open Fracture Models to Represent vs.C and Investigated the Effect of Swelling Ratio (SR), Fracture Size, and Fiber Concentration on Gel Injection Pressure, Water Breakthrough Pressure, and Permeability Reduction. Results Show that …
Lysine Crosslinked Polyacrylamide─A Novel Green Polymer Gel For Preferential Flow Control, Tao Song, Baojun Bai, Yugandhara Eriyagama, Thomas P. Schuman
Lysine Crosslinked Polyacrylamide─A Novel Green Polymer Gel For Preferential Flow Control, Tao Song, Baojun Bai, Yugandhara Eriyagama, Thomas P. Schuman
Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works
Acrylamide-based polymer gels have been applied to control the preferential flow in the subsurface for decades. However, some commonly used crosslinkers, such as Cr (III) and phenol-formaldehyde, are highly toxic and are being phased out because of stringent environmental regulations. This work uses l-lysine as the green crosslinker to produce acrylamide-based polymer gels. This article systematically studied the effect of lysine and polymer concentration, salinity, pH, and temperature on gelation behavior and thermal stability. Besides, the gelation mechanism and crosslinking density were elucidated in this work. A high-permeability sandstone core was used to test the plugging efficiency of this novel …
A Dtn-Based Spatio-Temporal Routing Using Location Prediction Model In Underground Mines, Abhay Goyal, Sanjay Kumar Madria, Samuel Frimpong
A Dtn-Based Spatio-Temporal Routing Using Location Prediction Model In Underground Mines, Abhay Goyal, Sanjay Kumar Madria, Samuel Frimpong
Computer Science Faculty Research & Creative Works
Situational awareness during any disaster depends on effective communication and location tracking. In the case of underground mines, where the communication methods are mostly central, the whole communication channel would be rendered unusable during a disaster. To this end, we propose the use of Delay Tolerant Networks (DTN) to allow the miners to function in a distributed manner and help in locating the injured miners and routing distress messages. Due to the unavailability of GPS signals, the pillar numbers are used to identify the locations of the miners. For spatio-temporal routing of messages, we formulate a new scheme using Contact …
Lifelong Learning-Based Multilayer Neural Network Control Of Nonlinear Continuous-Time Strict-Feedback Systems, Irfan Ahmad Ganie, S. (Sarangapani) Jagannathan
Lifelong Learning-Based Multilayer Neural Network Control Of Nonlinear Continuous-Time Strict-Feedback Systems, Irfan Ahmad Ganie, S. (Sarangapani) Jagannathan
Electrical and Computer Engineering Faculty Research & Creative Works
In This Paper, We Investigate Lifelong Learning (LL)-Based Tracking Control for Partially Uncertain Strict Feedback Nonlinear Systems with State Constraints, employing a Singular Value Decomposition (SVD) of the Multilayer Neural Networks (MNNs) Activation Function based Weight Tuning Scheme. the Novel SVD-Based Approach Extends the MNN Weight Tuning to (Formula Presented.) Layers. a Unique Online LL Method, based on Tracking Error, is Integrated into the MNN Weight Update Laws to Counteract Catastrophic Forgetting. to Adeptly Address Constraints for Safety Assurances, Taking into Account the Effects Caused by Disturbances, We Utilize a Time-Varying Barrier Lyapunov Function (TBLF) that Ensures a Uniformly Ultimately …
Optimal Tracking Of Nonlinear Discrete-Time Systems Using Zero-Sum Game Formulation And Hybrid Learning, Behzad Farzanegan, S. (Sarangapani) Jagannathan
Optimal Tracking Of Nonlinear Discrete-Time Systems Using Zero-Sum Game Formulation And Hybrid Learning, Behzad Farzanegan, S. (Sarangapani) Jagannathan
Electrical and Computer Engineering Faculty Research & Creative Works
This paper presents a novel hybrid learning-based optimal tracking method to address zero-sum game problems for partially uncertain nonlinear discrete-time systems. An augmented system and its associated discounted cost function are defined to address optimal tracking. Three multi-layer neural networks (NNs) are utilized to approximate the optimal control and the worst-case disturbance inputs, and the value function. The critic weights are tuned using the hybrid technique, whose weights are updated once at the sampling instants and in an iterative manner over finite times within the sampling instants. The proposed hybrid technique helps accelerate the convergence of the approximated value functional …
Lifelong Deep Learning-Based Control Of Robot Manipulators, Irfan Ganie, Jagannathan Sarangapani
Lifelong Deep Learning-Based Control Of Robot Manipulators, Irfan Ganie, Jagannathan Sarangapani
Electrical and Computer Engineering Faculty Research & Creative Works
This study proposes a lifelong deep learning control scheme for robotic manipulators with bounded disturbances. This scheme involves the use of an online tunable deep neural network (DNN) to approximate the unknown nonlinear dynamics of the robot. The control scheme is developed by using a singular value decomposition-based direct tracking error-driven approach, which is utilized to derive the weight update laws for the DNN. To avoid catastrophic forgetting in multi-task scenarios and to ensure lifelong learning (LL), a novel online LL scheme based on elastic weight consolidation is included in the DNN weight-tuning laws. Our results demonstrate that the resulting …
Towards Robust Consensus For Intelligent Decision-Making In Iot Blockchain Networks, Charles Rawlins, S. (Sarangapani) Jagannathan
Towards Robust Consensus For Intelligent Decision-Making In Iot Blockchain Networks, Charles Rawlins, S. (Sarangapani) Jagannathan
Electrical and Computer Engineering Faculty Research & Creative Works
Distributed consensus is the core aspect of blockchain protocol security design. Recent protocols like IOTA have improved concurrency and scalability over Proof-of-work (PoW) with Bitcoin but have core design decisions that are inefficient for limited devices and do not take advantage of previous network experience to reduce calculations. This work proposes the first blockchain consensus protocol based on active machine-learning decisions, called Proof-of-history (PoH). PoH is setup as a distributed reinforcement-learning task for monitoring classification and training of blockchain transactions with an inner deep classifier. Early theoretical analysis and simulations show that PoH is robust to uncoordinated byzantine attacks through …
A Novel Technique For The Quantitative Determination Of Wettability Of A Severely Heterogeneous Tight Carbonate Reservoir, Saleh Al-Sayegh, Ralph E. Flori, Waleed Al-Bazzaz, Abdulaziz Abbas, Ali Qubian, Hasan Al-Saedi
A Novel Technique For The Quantitative Determination Of Wettability Of A Severely Heterogeneous Tight Carbonate Reservoir, Saleh Al-Sayegh, Ralph E. Flori, Waleed Al-Bazzaz, Abdulaziz Abbas, Ali Qubian, Hasan Al-Saedi
Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works
The objective of this study is to accurately measure the wettability contact angle of a cretaceous carbonate reservoir in a vertical well set-up known for as an unconventional tight carbonate oil reservoir. Also, to investigate the relative heterogeneity of these samples using digitally captured images; these images accurately capture natural pore-system in this carbonate rock samples and their wettability performance attributed towards building a vertical depth wettability/heterogeneity model. To capture, measure and model natural tight matrix static contact angle wettability in order to understand their new physics that will advance unconventional tight oil reservoir characterization. Entire vertical well depth reservoir …
Practical Imaging Applications Of Wettability Contact Angles On Kuwaiti Tight Carbonate Reservoir With Different Rock Types, Saleh Al-Sayegh, Ralph E. Flori, Waleed Al-Bazzaz, Sohaib Kholosy, Hasan Al-Saedi, Abdulaziz Abbas, Ali Qubian
Practical Imaging Applications Of Wettability Contact Angles On Kuwaiti Tight Carbonate Reservoir With Different Rock Types, Saleh Al-Sayegh, Ralph E. Flori, Waleed Al-Bazzaz, Sohaib Kholosy, Hasan Al-Saedi, Abdulaziz Abbas, Ali Qubian
Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works
This study focuses on a tight carbonate reservoir which is located in Northern Kuwait and is classified as an unconventional reservoir. A practical imaging technique of wettability contact angle (θ°) presents "big data" as well as relative-permeability (Krw and Kro) measurements. Also, modeling, through rock image technology, the vast well-documented grain/pore boundary morphology available inside fresh rock fragments have achieved good results. Conventional laboratory relative-permeability experiments are expensive and time-consuming. This study introduces a novel method to measure/calculate relative permeability through fast, less expensive, non-destructive, and environmentally friendly techniques of imaging technology. One tight carbonate reservoir is selected, imaged, processed, …
Transport And Plugging Performance Evaluation Of A Novel Re-Crosslinkable Microgel Used For Conformance Control In Mature Oilfields With Super-Permeable Channels, Adel Alotibi, T. Song, Baojun Bai, Thomas P. Schuman
Transport And Plugging Performance Evaluation Of A Novel Re-Crosslinkable Microgel Used For Conformance Control In Mature Oilfields With Super-Permeable Channels, Adel Alotibi, T. Song, Baojun Bai, Thomas P. Schuman
Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works
Preformed particle gels (PPG) have been widely applied in oilfields to control excessive water production. However, PPG has limited success in treating opening features because the particles can be flushed readily during post-water flooding. We have developed a novel micro-sized Re-crosslinkable PPG (micro-RPPG) to solve the problem. The microgel can re-crosslink to form a bulk gel, avoiding being washed out easily. This paper evaluates the novel microgels' transport and plugging performance through super-permeable channels. Micro-RPPG was synthesized and evaluated for this study. Its storage moduli after fully swelling are approximately 82 Pa. The microgel characterization, self-healing process, transportation behavior, and …
Investigating Pore Body, Pore Throat, Nano-Pore Wettability Preference In Several Unconventional Kuwaiti Carbonate Reservoirs, Saleh Al-Sayegh, Ralph E. Flori, Hussain Alajaj, Waleed Hussien Al-Bazzaz
Investigating Pore Body, Pore Throat, Nano-Pore Wettability Preference In Several Unconventional Kuwaiti Carbonate Reservoirs, Saleh Al-Sayegh, Ralph E. Flori, Hussain Alajaj, Waleed Hussien Al-Bazzaz
Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works
This study will investigate measuring the wettability contact angles of native unconventional tight carbonate as well as other unconventional pore system reservoir samples that hosts varied pore shapes and subsequent wettability contact angle distributions in both reservoir matrix and possible natural fractures. Also, the investigation will include validation of the grain/ pore-wall wettability regions and classify the natural wettability preference available inside pores of the rock and their overall wettability performance and recovery efficiency contributions. Further investigation will include modeling pore throat contact angle wettability, and to understand their new physics that will advance reservoir characterization and oil recovery improvement.
Kuwaiti Carbonate Reservoir Oil Recovery Prediction Through Static Wettability Contact Angle Using Machine Learning Modeling, Saleh Al-Sayegh, Ralph E. Flori, Waleed Hussien Al-Bazzaz, Hasan Al-Saedi, Mostafa Al-Kaouri, Ali Qubian
Kuwaiti Carbonate Reservoir Oil Recovery Prediction Through Static Wettability Contact Angle Using Machine Learning Modeling, Saleh Al-Sayegh, Ralph E. Flori, Waleed Hussien Al-Bazzaz, Hasan Al-Saedi, Mostafa Al-Kaouri, Ali Qubian
Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works
The objective of this study is to predict EOR efficiencies through static wettability contact angle measurement by Machine Learning (ML) modeling. Unlike conventional methods of measuring static wettability contact angle, the unconventional digital static wettability contact angle is captured and measured, then (ML) modeled in order to forecast the recovery based on wettability distribution phenomenon. Due to success in big data collection from reservoir imaging samples, this study applies data science lifecycle logic and utilizes Machine Learning (ML) models that can predict the recovery through wettability contact angles and thus identify the treatment of oil recovery for a candidate reservoir. …
Synthesis, Densification, And Cation Inversion In High Entropy (Co,Cu,Mg,Ni,Zn)Al2o4 Spinel, Cole A. Corlett, Nina Obradovic, Jeremy Lee Watts, Eric W. Bohannan, William Fahrenholtz
Synthesis, Densification, And Cation Inversion In High Entropy (Co,Cu,Mg,Ni,Zn)Al2o4 Spinel, Cole A. Corlett, Nina Obradovic, Jeremy Lee Watts, Eric W. Bohannan, William Fahrenholtz
Materials Science and Engineering Faculty Research & Creative Works
The synthesis, densification behavior, and crystallographic site occupancy were investigated for four different spinel-based ceramics, including a high-entropy spinel (Co0.2Cu0.2Mg0.2Ni0.2 Zn0.2)Al2O4. Each composition was reacted to form a single phase, but analysis of X-ray diffraction patterns revealed differences in cation site occupancy with the high-entropy spinel being nearly fully normal. Densification behavior was investigated and showed that fully dense ceramics could be produced by hot pressing at temperatures as low as 1375°C for all compositions. Vickers' hardness values were at least 10 GPa for all compositions. The …
Comprehensive Evaluation Of A Novel Re-Crosslinkable Preformed Particle Gel For The Water Management Of Reservoir With Concentrated Divalent Ions, Tao Song, Mohamed Ahdaya, Zhanmiao Zhai, Thomas P. Schuman, Baojun Bai
Comprehensive Evaluation Of A Novel Re-Crosslinkable Preformed Particle Gel For The Water Management Of Reservoir With Concentrated Divalent Ions, Tao Song, Mohamed Ahdaya, Zhanmiao Zhai, Thomas P. Schuman, Baojun Bai
Chemistry Faculty Research & Creative Works
As one of the most widely used technology to ameliorate the reservoir's heterogeneity, polymer gels have been applied for more than 60 years. However, how to plug fractured reservoirs with significant abnormal features, high temperature and high salinity, especially the divalent cations, is still a challenging target. This work systematically evaluated a novel salt-resistant re-crosslinkable preformed particle gel (SR-RPPG) designed for fractured reservoirs with excellent salt resistance (up to 5 % CaCl2). We evaluated the swelling kinetics, thermal stability and plugging efficiency of this SR-RPPG. We assessed the swelling kinetic and re-crosslinking behavior of the SR-RPPG through the …
Personalizing Student Graduation Paths Using Expressed Student Interests, Nicolas Dobbins, Ali R. Hurson, Sahra Sedigh
Personalizing Student Graduation Paths Using Expressed Student Interests, Nicolas Dobbins, Ali R. Hurson, Sahra Sedigh
Electrical and Computer Engineering Faculty Research & Creative Works
This paper proposes an intelligent recommendation approach to facilitate personalized education and help students in planning their path to graduation. The goal is to identify a path that aligns with a student's interests and career goals and approaches optimality with respect to one or more criteria, such as time-to-graduation or credit hours taken. The approach is illustrated and verified through application to undergraduate curricula at the Missouri University of Science and Technology.
Continual Learning-Based Optimal Output Tracking Of Nonlinear Discrete-Time Systems With Constraints: Application To Safe Cargo Transfer, Behzad Farzanegan, S. (Sarangapani) Jagannathan
Continual Learning-Based Optimal Output Tracking Of Nonlinear Discrete-Time Systems With Constraints: Application To Safe Cargo Transfer, Behzad Farzanegan, S. (Sarangapani) Jagannathan
Electrical and Computer Engineering Faculty Research & Creative Works
This Paper Addresses a Novel Lifelong Learning (LL)-Based Optimal Output Tracking Control of Uncertain Non-Linear Affine Discrete-Time Systems (DT) with State Constraints. First, to Deal with Optimal Tracking and Reduce the Steady State Error, a Novel Augmented System, Including Tracking Error and its Integral Value and Desired Trajectory, is Proposed. to Guarantee Safety, an Asymmetric Barrier Function (BF) is Incorporated into the Utility Function to Keep the Tracking Error in a Safe Region. Then, an Adaptive Neural Network (NN) Observer is Employed to Estimate the State Vector and the Control Input Matrix of the Uncertain Nonlinear System. Next, an NN-Based …
Securing The Transportation Of Tomorrow: Enabling Self-Healing Intelligent Transportation, Elanor Jackson, Sahra Sedigh Sarvestani
Securing The Transportation Of Tomorrow: Enabling Self-Healing Intelligent Transportation, Elanor Jackson, Sahra Sedigh Sarvestani
Electrical and Computer Engineering Faculty Research & Creative Works
The safety of autonomous vehicles relies on dependable and secure infrastructure for intelligent transportation. The doctoral research described in this paper aims to enable self-healing and survivability of the intelligent transportation systems required for autonomous vehicles (AV-ITS). The proposed approach is comprised of four major elements: qualitative and quantitative modeling of the AV-ITS, stochastic analysis to capture and quantify interdependencies, mitigation of disruptions, and validation of efficacy of the self-healing process. This paper describes the overall methodology and presents preliminary results, including an agent-based model for detection of and recovery from disruptions to the AV-ITS.
Rafid: A Lightweight Approach To Radio Frequency Interference Detection In Time Domain Using Lstm And Statistical Analysis, Luke A. Smith, Vishesh Kumar Tanwar, Maciej Jan Zawodniok, Sanjay Kumar Madria
Rafid: A Lightweight Approach To Radio Frequency Interference Detection In Time Domain Using Lstm And Statistical Analysis, Luke A. Smith, Vishesh Kumar Tanwar, Maciej Jan Zawodniok, Sanjay Kumar Madria
Electrical and Computer Engineering Faculty Research & Creative Works
Recently, the utilization of Radio Frequency (RF) devices has increased exponentially over numerous vertical platforms. This rise has led to an abundance of Radio Frequency Interference (RFI) continues to plague RF systems today. The continued crowding of the RF spectrum makes RFI efficient and lightweight mitigation critical. Detecting and localizing the interfering signals is the foremost step for mitigating RFI concerns. Addressing these challenges, we propose a novel and lightweight approach, namely RaFID, to detect and locate the RFI by incorporating deep neural networks (DNNs) and statistical analysis via batch-wise mean aggregation and standard deviation (SD) calculations. RaFID investigates the …
Analyzing Ground Motion Records With Cvi Fuzzy Art, Dustin Tanksley, Xinzhe Yuan, Genda Chen, Donald C. Wunsch
Analyzing Ground Motion Records With Cvi Fuzzy Art, Dustin Tanksley, Xinzhe Yuan, Genda Chen, Donald C. Wunsch
Civil, Architectural and Environmental Engineering Faculty Research & Creative Works
This paper explores using Cluster Validity Indices Fuzzy Adaptative Resonance Theory (CVI Fuzzy ART) to cluster ground motion records (GMRs). Clustering the features extracted from a supervised network trained for predicting the structure damage results in less overfitting from the trained network. Using Cluster Validity Indices (CVIs) to evaluate the clustering gives feedback to how well the data is being classified, allowing further separation of the data. By using CVI Fuzzy ART in combination with features extracted from a trained Convolutional Neural Network (CNN), we were able to form additional clusters in the data. Within the primary clusters, accuracy was …
Skin Lesion Segmentation In Dermoscopic Images With Noisy Data, Norsang Lama, Jason Hagerty, Anand Nambisan, Ronald Joe Stanley, William Van Stoecker
Skin Lesion Segmentation In Dermoscopic Images With Noisy Data, Norsang Lama, Jason Hagerty, Anand Nambisan, Ronald Joe Stanley, William Van Stoecker
Electrical and Computer Engineering Faculty Research & Creative Works
We Propose a Deep Learning Approach to Segment the Skin Lesion in Dermoscopic Images. the Proposed Network Architecture Uses a Pretrained Efficient Net Model in the Encoder and Squeeze-And-Excitation Residual Structures in the Decoder. We Applied This Approach on the Publicly Available International Skin Imaging Collaboration (ISIC) 2017 Challenge Skin Lesion Segmentation Dataset. This Benchmark Dataset Has Been Widely Used in Previous Studies. We Observed Many Inaccurate or Noisy Ground Truth Labels. to Reduce Noisy Data, We Manually Sorted All Ground Truth Labels into Three Categories — Good, Mildly Noisy, and Noisy Labels. Furthermore, We Investigated the Effect of Such …
Lifelong Learning Control Of Nonlinear Systems With Constraints Using Multilayer Neural Networks With Application To Mobile Robot Tracking, Irfan Ganie, S. (Sarangapani) Jagannathan
Lifelong Learning Control Of Nonlinear Systems With Constraints Using Multilayer Neural Networks With Application To Mobile Robot Tracking, Irfan Ganie, S. (Sarangapani) Jagannathan
Electrical and Computer Engineering Faculty Research & Creative Works
This Paper Presents a Novel Lifelong Multilayer Neural Network (MNN) Tracking Approach for an Uncertain Nonlinear Continuous-Time Strict Feedback System that is Subject to Time-Varying State Constraints. the Proposed Method Uses a Time-Varying Barrier Function to Accommodate the Constraints Leading to the Development of an Efficient Control Scheme. the Unknown Dynamics Are Approximated using a MNN, with Weights Tuned using a Singular Value Decomposition (SVD)-Based Technique. an Online Lifelong Learning (LL) based Elastic Weight Consolidation (EWC) Scheme is Also Incorporated to Alleviate the Issue of Catastrophic Forgetting. the Stability of the overall Closed-Loop System is Analyzed using Lyapunov Analysis. the …
Improved Intelligent Ledger Construction For Realistic Iot Blockchain Networks, Charles Rawlins, S. (Sarangapani) Jagannathan
Improved Intelligent Ledger Construction For Realistic Iot Blockchain Networks, Charles Rawlins, S. (Sarangapani) Jagannathan
Electrical and Computer Engineering Faculty Research & Creative Works
Scalability is essential for next generation blockchain technology to integrate with large mobile networks like Internet of Things (IoT). The IOTA distributed ledger protocol has combined transaction generation and verification to address this, but at the expense of increased reliance on connectivity to resolve conflicts with a novel ledger data structure. Intelligent Ledger Construction (ILC) was proposed as an auditable lightweight reinforcement-learning scheme to address this constraint with proposal of local conflict resolution with machine-learning classification. This effort presents an improved reliability reward model to enhance training for ILC and further reduce adversarial gaming and resource usage. Testing this revision …