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Articles 2371 - 2400 of 13218
Full-Text Articles in Entire DC Network
A Collusion-Resistant Revocable Attribute-Based Encryption Scheme For Secure Data Sharing In Cloud, Azharul Islam, Sanjay Kumar Madria
A Collusion-Resistant Revocable Attribute-Based Encryption Scheme For Secure Data Sharing In Cloud, Azharul Islam, Sanjay Kumar Madria
Computer Science Faculty Research & Creative Works
Attribute-based encryption (ABE) is a prominent cryptographic tool for secure data sharing in the cloud because it can be used to enforce very expressive and fine-grained access control on outsourced data. The revocation in ABE remains a challenging problem as most of the revocation techniques available today, suffer from the collusion attack. The revocable ABE schemes which are collusion resistant require the aid of a semi-trusted manager to achieve revocation. More specifically, the semi-trusted manager needs to update the secret keys of nonrevoked users followed by a revocation. This introduces computation and communication overhead, and also increases the overall security …
Efficiently Discovering Users Connectivity With Local Information In Online Social Networks, Na Li, Sajal K. Das
Efficiently Discovering Users Connectivity With Local Information In Online Social Networks, Na Li, Sajal K. Das
Computer Science Faculty Research & Creative Works
People's activities in Online Social Networks (OSNs) have generated a massive volume of data to which tremendous attention has been paid in academia and industry. With such data, researchers and third-parties can analyze human beings’ behaviors in social communities and develop more user-friendly services and applications to meet people's needs. However, often times, they face a big challenge of acquiring the data, as the access to such data is restricted by their collectors (e.g., Facebook and Twitter), due to various reasons, such as their user's privacy. In this paper, we intend to shed light on leveraging limited local social network …
Critical Review Of Asphaltene Properties And Factors Impacting Its Stability In Crude Oil, Sherif Fakher, Mohamed Ahdaya, Mukhtar Elturki, Abdulmohsin Imqam
Critical Review Of Asphaltene Properties And Factors Impacting Its Stability In Crude Oil, Sherif Fakher, Mohamed Ahdaya, Mukhtar Elturki, Abdulmohsin Imqam
Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works
Asphaltene is a component of crude oil that has been reported to cause severe problems during production and transportation of the oil from the reservoir. It is a solid component of the oil that has different structures and molecular makeup which makes it one of the most complex components of the oil. This research provides a detailed review of asphaltene properties, characteristics, and previous studies to construct a guideline to asphaltene and its impact on oil recovery. The research begins with an explanation of the main components of crude oil and their relation to asphaltene. The method by which asphaltene …
Receiver Function Imaging Of The 410 And 660 Km Discontinuities Beneath The Australian Continent, Kailun Ba, Stephen S. Gao, Kelly H. Liu, Fansheng Kong, Jianguo Song
Receiver Function Imaging Of The 410 And 660 Km Discontinuities Beneath The Australian Continent, Kailun Ba, Stephen S. Gao, Kelly H. Liu, Fansheng Kong, Jianguo Song
Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works
To provide constraints on a number of significant controversial issues related to the structure and dynamics of the Australian continent, we utilize P-to-S receiver functions (RFs) recorded by 182 stations to map the 410 and 660 km discontinuities (d410 and d660, respectively) bordering the mantle transition zone (MTZ). The RFs are stacked in successive circular bins with a radius of 1° under a non-plane wave front assumption. The d410 and d660 depths obtained using the 1-D IASP91 earth model show a systematic apparent uplifting of about 15 km for both discontinuities in central and western Australia relative to eastern Australia, …
Improving The Background Of Gravitational-Wave Searches For Core Collapse Supernovae: A Machine Learning Approach, M. Cavaglià, S. Gaudio, T. Hansen, K. Staats, M. Szczepanczyk, M. Zanolin
Improving The Background Of Gravitational-Wave Searches For Core Collapse Supernovae: A Machine Learning Approach, M. Cavaglià, S. Gaudio, T. Hansen, K. Staats, M. Szczepanczyk, M. Zanolin
Physics Faculty Research & Creative Works
Based on the priorO1-O2observing runs, about30%of the data collected by Advanced LIGO and Virgo Internext observing runs are expected tobe single-interferometer data, i.e. they will be collected at times when only one detector in the network is operating in observing mode. Searches for gravitational-wave signals from supernova events do not rely on matched filtering techniques because of the stochastic nature of the signals. If a Galactic supernova occurs during single-interferometer times, separation of its unmodelled gravitational-wave signal from noise will be even more difficult due to lack of coherence between detectors. We present a novel machine learning method to perform …
Distributed Adaptive State Estimation And Tracking By Using Active-Passive Sensor Networks, Akhilesh Raj, Sarangapani Jagannathan, Tansel Yucelen
Distributed Adaptive State Estimation And Tracking By Using Active-Passive Sensor Networks, Akhilesh Raj, Sarangapani Jagannathan, Tansel Yucelen
Electrical and Computer Engineering Faculty Research & Creative Works
Heterogeneous sensor networks (HSN) find a wide range of applications in the field of military and civilian environments, where sensor nodes are utilized to estimate the position of a target with both dynamics and control input being unknown for the purposes of tracking. In the HSN, nodes are considered active depending upon their ability to sense the target output while the others are taken passive. Accurate estimation requires local information exchange among the spatially located sensor nodes, so that the active nodes as well as the passive nodes converge simultaneously to the same value. The local information exchange among the …
Flood Prediction And Uncertainty Estimation Using Deep Learning, Vinayaka Gude, Steven Corns, Suzanna Long
Flood Prediction And Uncertainty Estimation Using Deep Learning, Vinayaka Gude, Steven Corns, Suzanna Long
Engineering Management and Systems Engineering Faculty Research & Creative Works
Floods are a complex phenomenon that are difficult to predict because of their non-linear and dynamic nature. Therefore, flood prediction has been a key research topic in the field of hydrology. Various researchers have approached this problem using different techniques ranging from physical models to image processing, but the accuracy and time steps are not sufficient for all applications. This study explores deep learning techniques for predicting gauge height and evaluating the associated uncertainty. Gauge height data for the Meramec River in Valley Park, Missouri was used to develop and validate the model. It was found that the deep learning …
The Missouri Miner, February 26, 2020
The Missouri Miner, February 26, 2020
The Missouri Miner Newspaper
No abstract provided.
Faculty Senate Meeting Minutes January 23, 2020, Missouri University Of Science And Technology Faculty Senate
Faculty Senate Meeting Minutes January 23, 2020, Missouri University Of Science And Technology Faculty Senate
Minutes & Agendas
No abstract provided.
Faculty Senate Meeting Minutes February 20, 2020, Missouri University Of Science And Technology Faculty Senate
Faculty Senate Meeting Minutes February 20, 2020, Missouri University Of Science And Technology Faculty Senate
Minutes & Agendas
No abstract provided.
The Heuristic Dynamic Programming Approach In Boost Converters, Sepehr Saadatmand, Pourya Shamsi, Mehdi Ferdowsi
The Heuristic Dynamic Programming Approach In Boost Converters, Sepehr Saadatmand, Pourya Shamsi, Mehdi Ferdowsi
Electrical and Computer Engineering Faculty Research & Creative Works
In this study, a heuristic dynamic programming controller is proposed to control a boost converter. Conventional controllers such as proportional-integral-derivative (PID) or proportional-integral (PI) are designed based on the linearized small-signal model near the operating point. Therefore, the performance of the controller during the start-up, the load change, or the input voltage variation is not optimal since the system model changes by varying the operating point. The heuristic dynamic programming controller optimally controls the boost converter by following the approximate dynamic programming. The advantage of the HDP is that the neural network-based characteristic of the proposed controller enables boost converters …
The Voltage Regulation Of A Buck Converter Using A Neural Network Predictive Controller, Sepehr Saadatmand, Pourya Shamsi, Mehdi Ferdowsi
The Voltage Regulation Of A Buck Converter Using A Neural Network Predictive Controller, Sepehr Saadatmand, Pourya Shamsi, Mehdi Ferdowsi
Electrical and Computer Engineering Faculty Research & Creative Works
In this paper, a neural network predictive controller (NNPC) is proposed to control a buck converter. Conventional controllers such as proportional-integral (PI) or proportional-integral-derivative (PID) are designed based on the linearized small-signal model near the operating point. Therefore, the performance of the controller in the start-up, load change, or reference change is not optimal since the system model changes by changing the operating point. The neural network predictive controller optimally controls the buck converter by following the concept of the traditional model predictive controller. The advantage of the NNPC is that the neural network system identification decreases the inaccuracy of …
Quench Induced Vortex-Bright-Soliton Formation In Binary Bose-Einstein Condensates, K. Mukherjee, Simeon I. Mistakidis, P. G. Kevrekidis, P. Schmelcher
Quench Induced Vortex-Bright-Soliton Formation In Binary Bose-Einstein Condensates, K. Mukherjee, Simeon I. Mistakidis, P. G. Kevrekidis, P. Schmelcher
Physics Faculty Research & Creative Works
We Unravel The Spontaneous Generation Of Vortex-Bright-Soliton Structures In Binary Bose-Einstein Condensates With A Small Mass Imbalance Between The Species Confined In A Two-Dimensional Harmonic Trap Where One Of The Two Species Has Been Segmented Into Two Parts By A Potential Barrier. To Trigger The Dynamics The Potential Barrier Is Suddenly Removed And Subsequently The Segments Perform A Counterflow Dynamics. We Consider A Relative Phase Difference Of Π Between The Segments, While A Singly Quantized Vortex May Be Imprinted At The Center Of The Other Species. The Number Of Vortex Structures Developed Within The Segmented Species Following The Merging Of …
Crowdprivacy: Publish More Useful Data With Less Privacy Exposure In Crowdsourced Location-Based Services, Fang Jing Wu, Tie Luo
Crowdprivacy: Publish More Useful Data With Less Privacy Exposure In Crowdsourced Location-Based Services, Fang Jing Wu, Tie Luo
Computer Science Faculty Research & Creative Works
Location-based services (LBSs) typically crowdsource geo-tagged data from mobile users. Collecting more data will generally improve the utility for LBS providers; however, it also leads to more privacy exposure of users' mobility patterns. Although the tension between data utility and user privacy has been recognized, there lacks a solution that determines how much data to collect-in both spatial and temporal domains-is the "best" for both mobile users and the service provider. This article proposes a strategy toward making an optimal tradeoff such that a user submits data only if her mobility privacy will not be compromised and the data utility …
The Bridge Newsletter Spring 2020, Missouri University Of Science And Technology
The Bridge Newsletter Spring 2020, Missouri University Of Science And Technology
The Bridge Newsletter
-Studying fabrics, materials for facemasks
-New Missouri construction consortium
-Showalter honored by AGC
-New transportation center
Development Of Novel Adsorbent For Industrial Wastewater Treatment, Hassaan M. Shehata, Dalia A. Ali, Islam M. Al-Akraa, Hoda A. Elsawy, Hany A. Elazab
Development Of Novel Adsorbent For Industrial Wastewater Treatment, Hassaan M. Shehata, Dalia A. Ali, Islam M. Al-Akraa, Hoda A. Elsawy, Hany A. Elazab
Chemical and Biochemical Engineering Faculty Research & Creative Works
The main objective of this research project is to perform some experimental procedures to inform the ability of the novel adsorbent used in this project. The chemical modification of the adsorbent is the chemical oxidation of pure powder chitosan using some specific redox pairs which are potassium dichromate and sodium bisulphite. After preparing the modified chitosan, there are some parameters that must be discussed during the adsorption process. The first parameter is the time parameter, showing experimentally the optimum time for adsorption under certain conditions by collecting values of absorbance and concentration of thymol blue adsorbed after the process from …
Mathematica As An Efficient Tool To Optimize The Kinetic Study Of Ethyl Acetate Hydrolysis, M. H. El Dewaik, Mamdouh Gadalla, M. A. Sadek, Hany A. Elazab
Mathematica As An Efficient Tool To Optimize The Kinetic Study Of Ethyl Acetate Hydrolysis, M. H. El Dewaik, Mamdouh Gadalla, M. A. Sadek, Hany A. Elazab
Chemical and Biochemical Engineering Faculty Research & Creative Works
Mathematica is a powerful program for computing both numeric and algebraic calculations as well as graphing two- and three-dimensional curves and surfaces. It is used increasingly in many fields of science now such as physics, engineering, chemistry and even biology because of the fast interaction of mathematics with almost the fields of science nowadays. We report here, optimizing the kinetic data for the hydrolysis of ethyl acetate through caustic soda via using Mathematica.
Angular Correlation Using Rogers-Szego-Chaos, Christine Schmid, Kyle J. Demars
Angular Correlation Using Rogers-Szego-Chaos, Christine Schmid, Kyle J. Demars
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Polynomial chaos expresses a probability density function (pdf) as a linear combination of basis polynomials. If the density and basis polynomials are over the same field, any set of basis polynomials can describe the pdf; however, the most logical choice of polynomials is the family that is orthogonal with respect to the pdf. This problem is well-studied over the field of real numbers and has been shown to be valid for the complex unit circle in one dimension. The current framework for circular polynomial chaos is extended to multiple angular dimensions with the inclusion of correlation terms. Uncertainty propagation of …
A Flood Risk Management Program Of Wadi Baysh Dam On The Downstream Area: An Integration Of Hydrologic And Hydraulic Models, Jizan Region, Ksa, Mazen M. Abu-Abdullah, Ahmed M. Youssef, Norbert H. Maerz, Emad Abu-Alfadail, Hasan M. Al-Harbi, Nasser S. Al-Saadi
A Flood Risk Management Program Of Wadi Baysh Dam On The Downstream Area: An Integration Of Hydrologic And Hydraulic Models, Jizan Region, Ksa, Mazen M. Abu-Abdullah, Ahmed M. Youssef, Norbert H. Maerz, Emad Abu-Alfadail, Hasan M. Al-Harbi, Nasser S. Al-Saadi
Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works
For public safety, especially for people who dwell in the valley that is located downstream of a dam site, as well as the protection of economic and environmental resources, risk management programs are urgently required all over the world. Despite the high safety standards of dams because of improved engineering and excellent construction in recent times, a zero-risk guarantee is not possible, and accidents can happen, triggered by natural hazards, human actions, or just because the dam is aging. In addition to that is the impact of potential climate change, which may not have been taken into account in the …
Mantle Structure And Flow Beneath An Early-Stage Continental Rift: Constraints From P Wave Anisotropic Tomography, Youqiang Yu, Stephen S. Gao, Dapeng Zhao, Kelly H. Liu
Mantle Structure And Flow Beneath An Early-Stage Continental Rift: Constraints From P Wave Anisotropic Tomography, Youqiang Yu, Stephen S. Gao, Dapeng Zhao, Kelly H. Liu
Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works
To explore 3-D seismic velocity and radial anisotropy structures of the upper mantle and mantle transition zone beneath the Malawi and Luangwa rift zones of the East African Rift System, we conduct the first study of P wave anisotropic tomography using data recorded at 75 seismic stations including 34 stations that we installed along two profiles as part of the Seismic Arrays for African Rift Initiation experiment. Both rift zones are revealed to have normal or slightly low velocity anomalies in the lithosphere and upper asthenosphere. The surrounding cratonic lithosphere is characterized by high-velocity anomalies with amplitudes ranging from +1.0% …
Pulse- And Continuously Driven Many-Body Quantum Dynamics Of Bosonic Impurities In A Bose-Einstein Condensate, K. Mukherjee, Simeon I. Mistakidis, S. Majumder, P. Schmelcher
Pulse- And Continuously Driven Many-Body Quantum Dynamics Of Bosonic Impurities In A Bose-Einstein Condensate, K. Mukherjee, Simeon I. Mistakidis, S. Majumder, P. Schmelcher
Physics Faculty Research & Creative Works
We Unravel The Periodically Driven Dynamics Of Two Repulsively Interacting Bosonic Impurities Within A Bosonic Bath Upon Considering Either The Impact Of A Finite Pulse Or Continuous Shaking Of The Impurities Harmonic Trap. Following A Pulse Driving Of Initially Miscible Components, We Reveal A Variety Of Dynamical Response Regimes Depending On The Driving Frequency. At Resonant Drivings, The Impurities Decouple From Their Host, While If Exposed To A High-Frequency Driving, They Remain Trapped In The Bosonic Gas. For Continuous Shaking, We Showcase That In The Resonantly Driven Regime The Impurities Oscillate Back And Forth Within And Outside The Bosonic Medium. …
Polyphenols In Alzheimer’S Disease And In The Gut–Brain Axis, V. Prakash Reddy, Puspa Aryal, Sara Robinson, Raheemat Rafiu, Mark Obrenovich, George Perry
Polyphenols In Alzheimer’S Disease And In The Gut–Brain Axis, V. Prakash Reddy, Puspa Aryal, Sara Robinson, Raheemat Rafiu, Mark Obrenovich, George Perry
Chemistry Faculty Research & Creative Works
Polyphenolic antioxidants, including dietary plant lignans, modulate the gut–brain axis, which involves transformation of these polyphenolic compounds into physiologically active and neuroprotector compounds (called human lignans) through gut bacterial metabolism. These gut bacterial metabolites exert their neuroprotective effects in various neurodegenerative diseases, such as Alzheimer's disease (AD) and Parkinson's disease (PD), and also have protective effects against other diseases, such as cardiovascular diseases, cancer, and diabetes. For example, enterolactone and enterodiol, the therapeutically relevant polyphenols, are formed as the secondary gut bacterial metabolites of lignans, the non-flavonoid polyphenolic compounds found in plant-based foods. These compounds are also acetylcholinesterase inhibitors and …
The Voltage Regulation Of Boost Converters Using Dual Heuristic Programming, Sepehr Saadatmand, Sima Azizi, Mohammadamir Kavousi
The Voltage Regulation Of Boost Converters Using Dual Heuristic Programming, Sepehr Saadatmand, Sima Azizi, Mohammadamir Kavousi
Graduate Student Research & Creative Works
In this paper, a dual heuristic programming controller is proposed to control a boost converter. Conventional controllers such as proportional-integral-derivative (PID) or proportional-integral (PI) are designed based on the linearized small-signal model near the operating point. Therefore, the performance of the controller during start-up, load change, or input voltage variation is not optimal since the system model changes by varying the operating point. The dual heuristic programming controller optimally controls the boost converter by following the approximate dynamic programming. The advantage of the DHP is that the neural network–based characteristic of the proposed controller enables boost converters to easily cope …
Autonomous Control Of A Line Follower Robot Using A Q-Learning Controller, Sepehr Saadatmand, Sima Azizi, Mohammadamir Kavousi, Donald C. Wunsch
Autonomous Control Of A Line Follower Robot Using A Q-Learning Controller, Sepehr Saadatmand, Sima Azizi, Mohammadamir Kavousi, Donald C. Wunsch
Electrical and Computer Engineering Faculty Research & Creative Works
In this paper, a MIMO simulated annealing (SA)-based Q-learning method is proposed to control a line follower robot. The conventional controller for these types of robots is the proportional (P) controller. Considering the unknown mechanical characteristics of the robot and uncertainties such as friction and slippery surfaces, system modeling and controller designing can be extremely challenging. The mathematical modeling for the robot is presented in this paper, and a simulator is designed based on this model. The basic Q-learning methods are based pure exploitation and the ε -greedy methods, which help exploration, can harm the controller performance after learning completion …
Gehring Inequalities On Time Scales, Martin Bohner, S. H. Saker
Gehring Inequalities On Time Scales, Martin Bohner, S. H. Saker
Mathematics and Statistics Faculty Research & Creative Works
In this paper, we first prove a new dynamic inequality based on an application of the time scales version of a Hardy-type inequality. Second, by employing the obtained inequality, we prove several Gehring-type inequalities on time scales. As an application of our Gehring-type inequalities, we present some interpolation and higher integrability theorems on time scales. The results as special cases, when the time scale is equal to the set of all real numbers, contain some known results, and when the time scale is equal to the set of all integers, the results are essentially new.
Rejoinder On ‘A Selective Overview Of Sparse Sufficient Dimension Reduction’, Lu Li, Xuewong Meggie Wen, Zhou Yu
Rejoinder On ‘A Selective Overview Of Sparse Sufficient Dimension Reduction’, Lu Li, Xuewong Meggie Wen, Zhou Yu
Mathematics and Statistics Faculty Research & Creative Works
No abstract provided.
Existence And Multiplicity Of Weak Solutions For A Neumann Elliptic Problem With -Laplacian, Martin Bohner, Giuseppe Caristi, Fariba Gharehgazlouei, Shapour Heidarkhani
Existence And Multiplicity Of Weak Solutions For A Neumann Elliptic Problem With -Laplacian, Martin Bohner, Giuseppe Caristi, Fariba Gharehgazlouei, Shapour Heidarkhani
Mathematics and Statistics Faculty Research & Creative Works
We are interested in the existence of multiple weak solutions for the Neumann elliptic problem involving the anisotropic -Laplacian operator, on a bounded domain with smooth boundary. We work on the anisotropic variable exponent Sobolev space, and by using a consequence of the local minimum theorem due to Bonanno, we establish existence of at least one weak solution under algebraic conditions on the nonlinear term. Also, we discuss existence of at least two weak solutions for the problem, under algebraic conditions including the classical Ambrosetti-Rabinowitz condition on the nonlinear term. Furthermore, by employing a three critical point theorem due to …
Predicting Complex System Behavior Using Hybrid Modeling And Computational Intelligence, Vinayaka Gude
Predicting Complex System Behavior Using Hybrid Modeling And Computational Intelligence, Vinayaka Gude
Doctoral Dissertations
“Modeling and prediction of complex systems is a challenging problem due to the sub-system interactions and dependencies. This research examines combining various computational intelligence algorithms and modeling techniques to provide insights into these complex processes and allow for better decision making. This hybrid methodology provided additional capabilities to analyze and predict the overall system behavior where a single model cannot be used to understand the complex problem. The systems analyzed here are flooding events and fetal health care. The impact of floods on road infrastructure is investigated using graph theory, agent-based traffic simulation, and Long Short-Term Memory deep learning to …
Human Behavior Understanding For Worker-Centered Intelligent Manufacturing, Wenjin Tao
Human Behavior Understanding For Worker-Centered Intelligent Manufacturing, Wenjin Tao
Doctoral Dissertations
“In a worker-centered intelligent manufacturing system, sensing and understanding of the worker’s behavior are the primary tasks, which are essential for automatic performance evaluation & optimization, intelligent training & assistance, and human-robot collaboration. In this study, a worker-centered training & assistant system is proposed for intelligent manufacturing, which is featured with self-awareness and active-guidance. To understand the hand behavior, a method is proposed for complex hand gesture recognition using Convolutional Neural Networks (CNN) with multiview augmentation and inference fusion, from depth images captured by Microsoft Kinect. To sense and understand the worker in a more comprehensive way, a multi-modal approach …
Development Of Lightweight Materials By Meso- And Microstructure Control, Myranda Shea Spratt
Development Of Lightweight Materials By Meso- And Microstructure Control, Myranda Shea Spratt
Doctoral Dissertations
”In this work, two lightweight structures – lattice structures and metal matrix syntactic foams (MMSF) – were studied. Honeycomb lattices were manufactured by powder bed selective laser melting (SLM) from 304L stainless steel. The wall thicknesses of these structures ranged from 0.2 to 0.5 mm. Surface roughness was the primary cause of dimensional mismatch between the expected and as-built structures with an average wall thickness increase of 0.12 mm. The strength of the honeycombs increased with increasing wall thickness. A feature of the SLM microstructure, the melt pool boundary, was also studied as a part of this work. 3D models …