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

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

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

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

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Epitaxial Electrodeposition Of Ordered Inorganic Materials, Jay A. Switzer, Avishek Banik Jan 2023

Epitaxial Electrodeposition Of Ordered Inorganic Materials, Jay A. Switzer, Avishek Banik

Chemistry Faculty Research & Creative Works

Conspectus The quality of technological materials generally improves as the crystallographic order is increased. This is particularly true in semiconductor materials, as evidenced by the huge impact that bulk single crystals of silicon have had on electronics. Another approach to producing highly ordered materials is the epitaxial growth of crystals on a single-crystal surface that determines their orientation. Epitaxy can be used to produce films and nanostructures of materials with a level of perfection that approaches that of single crystals. It may be used to produce materials that cannot be grown as large single crystals due to either economic or …

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Insights To Surfactant Huff-Puff Design In Carbonate Reservoirs Based On Machine Learning Modeling, Ya Yao, Yue Qiu, Yue Cui, Mingzhen Wei, Baojun Bai Jan 2023

Insights To Surfactant Huff-Puff Design In Carbonate Reservoirs Based On Machine Learning Modeling, Ya Yao, Yue Qiu, Yue Cui, Mingzhen Wei, Baojun Bai

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Surfactants could react with adsorbates on carbonate rock surface to alter wettability from oil-wetness to water-wetness, which is effective to enhance oil recovery. Surfactant huff-puff treatment is mostly applied for this purpose and the resulting surfactant performance is the outcome of complex interfacial processes. Currently, the effect of important parameters on surfactant performance is not completely reported and the contribution of each parameter to surfactant performance is hard to be quantified. Traditional methods to optimize surfactant performance are time-consuming and show strong dependency on extensive experiments. in this paper, we address these problems from machine learning (ML) perspectives. Several ML …

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Ongoing Fragmentation Of The Subducting Cocos Slab, Central America, Tu Xue, Diandian Peng, Kelly H. Liu, Jonathan Obrist-Farner, Marek Locmelis, Stephen S. Gao, Lijun Liu Jan 2023

Ongoing Fragmentation Of The Subducting Cocos Slab, Central America, Tu Xue, Diandian Peng, Kelly H. Liu, Jonathan Obrist-Farner, Marek Locmelis, Stephen S. Gao, Lijun Liu

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Fundamental to plate tectonics is the subduction of cold and mechanically strong oceanic plates. While the subducted plates are conventionally regarded to be impermeable to mantle flow and separate the mantle wedge and the sub slab region, isolated openings have been proposed. by combining new shear wave splitting measurements with results from geodynamic modeling and recent seismic tomography and geochemical observations, we show that the upper ~200 km of the Cocos slab in northern Central America is intensively fractured. the slab there is strong enough to produce typical arc volcanoes and Benioff Zone earthquakes but allows mantle flow to traverse …

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Erratum: New Estimates Of The Magnitude Of The Sea-Level Jump During The 8.2 Ka Event, (Geology (2022), 50(1), (86–90), (10.1130/G49296.1)), Jonathan Obrist-Farner, Mark Brenner, Jeffery R. Stone, Marta Wojewódka-Przybył, Thorsten Bauersachs, Andreas Eckert, Marek Locmelis, Jason H. Curtis, Susan R.H. Zimmerman, Alex Correa-Metrio, Lorenz Schwark, Edward Duarte, Antje Schwalb, Etienne Niewerth, Paula Gabriela Echeverría-Galindo, Liseth Pérez Jan 2023

Erratum: New Estimates Of The Magnitude Of The Sea-Level Jump During The 8.2 Ka Event, (Geology (2022), 50(1), (86–90), (10.1130/G49296.1)), Jonathan Obrist-Farner, Mark Brenner, Jeffery R. Stone, Marta Wojewódka-Przybył, Thorsten Bauersachs, Andreas Eckert, Marek Locmelis, Jason H. Curtis, Susan R.H. Zimmerman, Alex Correa-Metrio, Lorenz Schwark, Edward Duarte, Antje Schwalb, Etienne Niewerth, Paula Gabriela Echeverría-Galindo, Liseth Pérez

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

No abstract provided.

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Deep Reinforcement Learning For Approximate Policy Iteration: Convergence Analysis And A Post-Earthquake Disaster Response Case Study, Abhijit Gosavi, L. (Lesley) H. Sneed, L. A. Spearing Jan 2023

Deep Reinforcement Learning For Approximate Policy Iteration: Convergence Analysis And A Post-Earthquake Disaster Response Case Study, Abhijit Gosavi, L. (Lesley) H. Sneed, L. A. Spearing

Engineering Management and Systems Engineering Faculty Research & Creative Works

Approximate Policy Iteration (API) is a Class of Reinforcement Learning (RL) Algorithms that Seek to Solve the Long-Run Discounted Reward Markov Decision Process (MDP), Via the Policy Iteration Paradigm, Without Learning the Transition Model in the Underlying Bellman Equation. Unfortunately, These Algorithms Suffer from a Defect Known as Chattering in Which the Solution (Policy) Delivered in Each Iteration of the Algorithm Oscillates between Improved and Worsened Policies, Leading to Sub-Optimal Behavior. Two Causes for This that Have Been Traced to the Crucial Policy Improvement Step Are: (I) the Inaccuracies in the Policy Improvement Function and (Ii) the Exploration/exploitation Tradeoff Integral …

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An Augmented Dataset For Vision-Based Unmanned Aerial Vehicles Detection And Tracking, Md Hasibur Rahman, Sanjay Madria Jan 2023

An Augmented Dataset For Vision-Based Unmanned Aerial Vehicles Detection And Tracking, Md Hasibur Rahman, Sanjay Madria

Computer Science Faculty Research & Creative Works

The rapid proliferation of Unmanned Aerial Vehicles (UAVs) or drones in military, disaster management, business, and entertainment applications has raised concerns about their potential airspace risks. Researchers are increasingly focused on developing methods for detecting and tracking UAVs with various data sources like radar, visual, acoustic, and radio-frequency data available. among these, visual data stands out as cost-effective and amenable to analysis using Computer Vision (CV) techniques. However, vision-Based tasks present challenges such as occlusions, shaky footage, and small UAVs at a distance, requiring timely and computationally efficient detection, especially given limited onboard computational power. to address these challenges, researchers …

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Landmark Stereo Dataset For Landmark Recognition And Moving Node Localization In A Non-Gps Battlefield Environment, Ganesh Sapkota, Sanjay Madria Jan 2023

Landmark Stereo Dataset For Landmark Recognition And Moving Node Localization In A Non-Gps Battlefield Environment, Ganesh Sapkota, Sanjay Madria

Computer Science Faculty Research & Creative Works

In this paper, we have proposed a new strategy of using the landmark anchor node instead of a radio-Based anchor node to obtain the virtual coordinates (landmarkID, DISTANCE) of moving troops or defense forces that will help in tracking and maneuvering the troops along a safe path within a GPS-denied battlefield environment. the proposed strategy implements landmark recognition using the Yolov5 model and landmark distance estimation using an efficient Stereo Matching Algorithm. We consider that a moving node carrying a low-power mobile device facilitated with a calibrated stereo vision camera that can capture stereo images of a scene containing landmarks …

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Neuemot: Mitigating Neutral Label And Reclassifying False Neutrals In The 2022 Fifa World Cup Via Low-Level Emotion, Ademola Adesokan, Sanjay Madria Jan 2023

Neuemot: Mitigating Neutral Label And Reclassifying False Neutrals In The 2022 Fifa World Cup Via Low-Level Emotion, Ademola Adesokan, Sanjay Madria

Computer Science Faculty Research & Creative Works

Sports have been extensively studied for their impact on people's emotional well-being, with research revealing that they have the ability to reduce anxiety and unhappiness while boosting positive emotions1. among all sports, soccer stands out as the most popular and controversial2, eliciting a wide range of emotional reactions from fans, players, officials, and spectators, particularly on social media. While sentiment classifications such as positive, negative, and neutral have been extensively studied, low-level emotions, which refer to more specific and granular emotional states beyond the three basic categories, have yet to be given much attention. This study scraped over 300,000 tweets …

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Fedfast: Selective Federated Learning Using Fittest Parameters Aggregation And Slotted Clients Training, Ferdinand Kahenga, Antoine Bagula, Sajal K. Das Jan 2023

Fedfast: Selective Federated Learning Using Fittest Parameters Aggregation And Slotted Clients Training, Ferdinand Kahenga, Antoine Bagula, Sajal K. Das

Computer Science Faculty Research & Creative Works

This paper proposes a novel selective federated learning (FL) algorithm, called fittest aggregation and slotted training (FedFaSt). It relies on a 'free-for-all' client training process to score clients' efficiency while applying the 'natural selection' principle to elect the fittest clients to be used in FL training and aggregation processes. While relying on a combined data quality and training performance metric for scoring clients, FedFaSt implements a slotted training model enabling teams of fittest clients to participate in the training and aggregation processes for a fixed number of successive rounds, called slots. Performance validation using X-ray datasets reveals that FedFaSt outperforms …

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Optimizing Stochastic Task Migration In Vehicular Edge Computing, Ankur Nahar, Debasis Das, Sajal K. Das Jan 2023

Optimizing Stochastic Task Migration In Vehicular Edge Computing, Ankur Nahar, Debasis Das, Sajal K. Das

Computer Science Faculty Research & Creative Works

The performance of vehicular edge computing (VEC) depends on the effective optimization of task offloading. However, uneven distribution of vehicular traffic, rapidly changing network conditions, and stochastic nature of vehicular networks motivate us to innovate approaches to efficient resource management while maintaining system's stability. to address these challenges, we propose a novel queue length-Based stochastic task migration strategy that leverages model predictive control (MPC) and Lyapunov optimization techniques. Our approach employs the queue length at the edge node as the criterion for offloading decisions. the MPC controller dynamically allocates the processing power and bandwidth resources to vehicles based on their …

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Using Geographic Location-Based Public Health Features In Survival Analysis, Navid Seidi, Ardhendu S. Tripathy, Sajal K. Das Jan 2023

Using Geographic Location-Based Public Health Features In Survival Analysis, Navid Seidi, Ardhendu S. Tripathy, Sajal K. Das

Computer Science Faculty Research & Creative Works

Time elapsed till an event of interest is often modeled using the survival analysis methodology, which estimates a survival score based on the input features. There is a resurgence of interest in developing more accurate prediction models for time-to-event prediction in personalized healthcare using modern tools such as neural networks. Higher quality features and more frequent observations improve the predictions for a patient, however, the impact of including a patient's geographic location-Based public health statistics on individual predictions has not been studied. This paper proposes a complementary improvement to survival analysis models by incorporating public health statistics in the input …

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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 Jan 2023

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 …

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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 Jan 2023

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, …

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Towards A Domain-Agnostic Knowledge Graph-As-A-Service Infrastructure For Active Cyber Defense With Intelligent Agents, Prasad Calyam, Mayank Kejriwal, Praveen Rao, Jianlin Cheng, Weichao Wang, Linquan Bai, V. Sriram Siddhardh Nadendla, Sanjay Kumar Madria, Sajal K. Das, Rohit Chadha, Khaza Anuarul Hoque, Kannappan Palaniappan, Kiran Neupane, Roshan Lal Neupane, Sankeerth Gandhari, Mukesh Singhal, Lotfi Othmane, Meng Yu Jan 2023

Towards A Domain-Agnostic Knowledge Graph-As-A-Service Infrastructure For Active Cyber Defense With Intelligent Agents, Prasad Calyam, Mayank Kejriwal, Praveen Rao, Jianlin Cheng, Weichao Wang, Linquan Bai, V. Sriram Siddhardh Nadendla, Sanjay Kumar Madria, Sajal K. Das, Rohit Chadha, Khaza Anuarul Hoque, Kannappan Palaniappan, Kiran Neupane, Roshan Lal Neupane, Sankeerth Gandhari, Mukesh Singhal, Lotfi Othmane, Meng Yu

Computer Science Faculty Research & Creative Works

Active cyber defense mechanisms are necessary to perform automated, and even autonomous operations using intelligent agents that defend against modern/sophisticated AI-inspired cyber threats (e.g., ransomware, cryptojacking, deep-fakes). These intelligent agents need to rely on deep learning using mature knowledge and should have the ability to apply this knowledge in a situational and timely manner for a given AI-inspired cyber threat. in this paper, we describe a 'domain-Agnostic knowledge graph-As-A-service' infrastructure that can support the ability to create/store domain-specific knowledge graphs for intelligent agent Apps to deploy active cyber defense solutions defending real-world applications impacted by AI-inspired cyber threats. Specifically, we …

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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 Jan 2023

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 …

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

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

Chemistry Faculty Research & Creative Works

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

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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 Jan 2023

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 …

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Reinforcement Learning-Guided Quadratically Constrained Quadratic Programming For Enhanced Convergence And Optimality, Chaoying Pei, Zhi Xu, Sixiong You, Jeffrey Sun, Ran Dai Jan 2023

Reinforcement Learning-Guided Quadratically Constrained Quadratic Programming For Enhanced Convergence And Optimality, Chaoying Pei, Zhi Xu, Sixiong You, Jeffrey Sun, Ran Dai

Mechanical and Aerospace Engineering Faculty Research & Creative Works

In the context of Quadratically Constrained Quadratic Programming (QCQP) with dynamic parameters, the effectiveness of various optimization approaches is heavily influenced by the quality of the initial guess. To address this challenge, this paper proposes a novel approach that leverages reinforcement learning (RL) to generate high-performing initial guesses for iterative algorithms, with the dynamic parameters serving as inputs. Our approach aims to accelerate convergence and improve the objective value, thereby enabling efficient and effective solutions to the QCQP problem under variability. In this study, we evaluate the proposed approach by applying it to an iterative algorithm, specifically the Iterative Rank …

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Charging Of Irregularly-Shaped Dust Grains Near Surfaces In Space, David Lund, Xiaoming He, Daoru Han Jan 2023

Charging Of Irregularly-Shaped Dust Grains Near Surfaces In Space, David Lund, Xiaoming He, Daoru Han

Mathematics and Statistics Faculty Research & Creative Works

This paper presents fully kinetic numerical investigation of the charging of dust grains in low temperature collision less plasmas (stationary) and collision less, cold-ion thermal-electron drifting plasmas. the Parallel Immersed-Finite-Element Particle-in-Cell (PIFE-PIC) code is utilized to self-consistently resolve the plasma environment and charging of immersed materials. This model explicitly includes the materials property (dielectric constant) of dust grains. Effects of materials property, inter-dust distance, and plasma conditions (stationery and drifting) will be investigated for both single-dust and multi-dust configurations.

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Inspire Newsletter Fall 2023, Missouri University Of Science And Technology. Inspire - University Transportation Center Jan 2023

Inspire Newsletter Fall 2023, Missouri University Of Science And Technology. Inspire - University Transportation Center

INSPIRE Newsletters

No abstract provided.

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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 Jan 2023

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.

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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 Jan 2023

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. …

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Insights Into Initial Continental Rifting Of Marginal Seas From Seismic Evidence For Slab Relics In The Mid-Mantle Of The Woodlark Rift, Southwestern Pacific, Youqiang Yu, Frederik Tilmann, Stephen S. Gao, Kelly H. Liu, Jiaji Xi Jan 2023

Insights Into Initial Continental Rifting Of Marginal Seas From Seismic Evidence For Slab Relics In The Mid-Mantle Of The Woodlark Rift, Southwestern Pacific, Youqiang Yu, Frederik Tilmann, Stephen S. Gao, Kelly H. Liu, Jiaji Xi

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

The initiation and evolution of marginal seas, especially those developing under a convergent setting, is one of the more enigmatic aspects of plate tectonics. Here, we report the presence of slab relics in the mid-mantle of the Woodlark rift in the southwestern Pacific based on a new map of the topography of the mantle discontinuities from a receiver function analysis and evidence from body-wave tomography. the widespread mantle transition-zone thickening rules out active mantle upwelling, and the revealed slab relics in both the upper and middle mantle may hydrate the upper mantle, which can be expected to further weaken the …

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Advances In Fiber-Optic Extrinsic Fabry-Perot Interferometric Physical And Mechanical Sensors: A Review, Chen Zhu, Hongkun Zheng, Lingmei Ma, Zheyi Yao, Bo Liu, Jie Huang, Yunjiang Rao Jan 2023

Advances In Fiber-Optic Extrinsic Fabry-Perot Interferometric Physical And Mechanical Sensors: A Review, Chen Zhu, Hongkun Zheng, Lingmei Ma, Zheyi Yao, Bo Liu, Jie Huang, Yunjiang Rao

Electrical and Computer Engineering Faculty Research & Creative Works

Fabry-Perot Interferometers Have Found a Multitude of Scientific and Industrial Applications Ranging from Gravitational Wave Detection, High-Resolution Spectroscopy, and Optical Filters to Quantum Optomechanics. Integrated with Optical Fiber Waveguide Technology, the Fiber-Optic Fabry-Perot Interferometers Have Emerged as a Unique Candidate for High-Sensitivity Sensing and Have Undergone Tremendous Growth and Advancement in the Past Two Decades with their Successful Applications in an Expansive Range of Fields. the Extrinsic Cavity-Based Devices, I.e., the Fiber-Optic Extrinsic Fabry-Perot Interferometers (EFPIs), Enable Great Flexibility in the Design of the Sensitive Fabry-Perot Cavity Combined with State-Of-The-Art Micromachining and Conventional Mechanical Fabrication, Leading to the Development of …

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Decoupling Optimization For Complex Pdn Structures Using Deep Reinforcement Learning, Ling Zhang, Li Jiang, Jack Juang, Zhiping Yang, Er Ping Li, Chulsoon Hwang Jan 2023

Decoupling Optimization For Complex Pdn Structures Using Deep Reinforcement Learning, Ling Zhang, Li Jiang, Jack Juang, Zhiping Yang, Er Ping Li, Chulsoon Hwang

Electrical and Computer Engineering Faculty Research & Creative Works

This Article Presents a New Optimization Method for Complex Power Distribution Networks (PDNs) with Irregular Shapes and Multilayer Structures using Deep Reinforcement Learning (DRL), Which Has Not Been Considered Before. a Fast Boundary Integration Method is Applied to Compute the Impedance Matrix of a PDN Structure. Subsequently, a New DRL Algorithm based on Proximal Policy Optimization (PPO) is Proposed to Optimize the Decoupling Capacitor (Decap) Placement by Minimizing the Number of Decaps While Satisfying the Desired Target Impedance. in the Proposed Approach, the PDN Structure Information is Encoded into Matrices and Serves as the Input of the DRL Algorithm, Which …

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A Throughput Fast Measurement Method For Two-Antenna Equipped Wireless Mimo Terminals, Penghui Shen, Quan Yu, Daryl G. Beetner, Yihong Qi Jan 2023

A Throughput Fast Measurement Method For Two-Antenna Equipped Wireless Mimo Terminals, Penghui Shen, Quan Yu, Daryl G. Beetner, Yihong Qi

Electrical and Computer Engineering Faculty Research & Creative Works

According to the Third Generation Partnership Project Specification, a Period of 8-12.8 H is Required to Evaluate the Multiple-Input-Multiple-Output (MIMO) Performance of a Wireless Terminal for a Single Frequency Point and Channel Model Combination. the Following Article Proposes a Semi-Simulation, Semi-Measurement-Based MIMO throughput Modeling Scheme Which Can Reduce the 8-12.8-H Measurement Time to 40-60 Min, Corresponding to More Than a Ten Times Improvement of the Test Efficiency, Without Loss of the Test Accuracy.

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Development Of A Matlab-Based Structural Analysis Toolbox For Sensor Placement In A Multi-Domain Physical System, Arnold A. Fernandes, Kartikeya J.P. Veeramraju, Jonathan W. Kimball Jan 2023

Development Of A Matlab-Based Structural Analysis Toolbox For Sensor Placement In A Multi-Domain Physical System, Arnold A. Fernandes, Kartikeya J.P. Veeramraju, Jonathan W. Kimball

Electrical and Computer Engineering Faculty Research & Creative Works

This paper discusses a Bond Graph (BG) Structural Analysis Toolbox developed in MATLAB® (MATSAT) that performs causal analysis on the BG and assists the user in the sensor selection process for a multi-domain physical system. MATSAT contains modules for performing the Sequential Causality Assignment Procedure (SCAP) and Causal Path Search (CaPS). The modules can be combined to check for structural properties such as structural observability (SO) for any sensor set. The working of MATSAT is shown for standard systems. Verification of SCAP, CaPS, and necessary and sufficient SO conditions is shown.

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Continual Reinforcement Learning Formulation For Zero-Sum Game-Based Constrained Optimal Tracking, Behzad Farzanegan, Sarangapani Jagannathan Jan 2023

Continual Reinforcement Learning Formulation For Zero-Sum Game-Based Constrained Optimal Tracking, Behzad Farzanegan, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

This study provides a novel reinforcement learning-based optimal tracking control of partially uncertain nonlinear discrete-time (DT) systems with state constraints using zero-sum game (ZSG) formulation. To address optimal tracking, a novel augmented system consisting of tracking error and its integral value, along with an uncertain desired trajectory, is constructed. A barrier function (BF) with a tradeoff factor is incorporated into the cost function to keep the state trajectories to remain within a compact set and to balance safety with optimality. Next, by using the modified value functional, the ZSG formulation is introduced wherein an actor–critic neural network (NN) framework is …

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Continual Optimal Adaptive Tracking Of Uncertain Nonlinear Continuous-Time Systems Using Multilayer Neural Networks, Irfan Ganie, S. (Sarangapani) Jagannathan Jan 2023

Continual Optimal Adaptive Tracking Of Uncertain Nonlinear Continuous-Time Systems Using Multilayer Neural Networks, Irfan Ganie, S. (Sarangapani) Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

This study provides a lifelong integral reinforcement learning (LIRL)-based optimal tracking scheme for uncertain nonlinear continuous-time (CT) systems using multilayer neural network (MNN). In this LIRL framework, the optimal control policies are generated by using both the critic neural network (NN) weights and single-layer NN identifier. The critic MNN weight tuning is accomplished using an improved singular value decomposition (SVD) of its activation function gradient. The NN identifier, on the other hand, provides the control coefficient matrix for computing the control policies. An online weight velocity attenuation (WVA)-based consolidation scheme is proposed wherein the significance of weights is derived by …

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