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Articles 2911 - 2940 of 13214
Full-Text Articles in Entire DC Network
Scanning Tunneling Spectroscopy Investigations Of Superconducting-Doped Topological Insulators: Experimental Pitfalls And Results, Stefan Wilfert, Paolo Sessi, Zhiwei Wang, Henrik Schmidt, M. Carmen Martínez-Velarte, Seng Huat Lee, Yew San Hor, Alexander F. Otte, Yoichi Ando, Weida Wu, Matthias Bode
Scanning Tunneling Spectroscopy Investigations Of Superconducting-Doped Topological Insulators: Experimental Pitfalls And Results, Stefan Wilfert, Paolo Sessi, Zhiwei Wang, Henrik Schmidt, M. Carmen Martínez-Velarte, Seng Huat Lee, Yew San Hor, Alexander F. Otte, Yoichi Ando, Weida Wu, Matthias Bode
Physics Faculty Research & Creative Works
Recently, the doping of topological insulators has attracted significant interest as a potential route towards topological superconductivity. Because many experimental techniques lack sufficient surface sensitivity, however, definite proof of the coexistence of topological surface states and surface superconductivity is still outstanding. Here we report on highly surface sensitive scanning tunneling microscopy and spectroscopy experiments performed on Tl-doped Bi2Te3, a three-dimensional topological insulator which becomes superconducting in the bulk at TC=2.3 K. Landau level spectroscopy as well as quasiparticle interference mapping clearly demonstrated the presence of a topological surface state with a Dirac point energy …
Dynamics Of Paramagnetic And Ferromagnetic Ellipsoidal Particles In Shear Flow Under A Uniform Magnetic Field, Christopher A. Sobecki, Jie Zhang, Yanzhi Zhang, Cheng Wang
Dynamics Of Paramagnetic And Ferromagnetic Ellipsoidal Particles In Shear Flow Under A Uniform Magnetic Field, Christopher A. Sobecki, Jie Zhang, Yanzhi Zhang, Cheng Wang
Mathematics and Statistics Faculty Research & Creative Works
We investigate the two-dimensional dynamic motion of magnetic particles of ellipsoidal shapes in shear flow under the influence of a uniform magnetic field. In the first part, we present a theoretical analysis of the rotational dynamics of the particles in simple shear flow. By considering paramagnetic and ferromagnetic particles, we study the effects of the direction and strength of the magnetic field on the particle rotation. The critical magnetic-field strength, at which particle rotation is impeded, is determined. In a weak-field regime (i.e., below the critical strength) where the particles execute complete rotations, the symmetry property of the rotational velocity …
A Study Of The Genetic Algorithm Parameters For Solving Multi-Objective Travelling Salesman Problem, Romit S. Beed, Sunita Sarkar, Arindam Roy, Shubham Chatterjee
A Study Of The Genetic Algorithm Parameters For Solving Multi-Objective Travelling Salesman Problem, Romit S. Beed, Sunita Sarkar, Arindam Roy, Shubham Chatterjee
Computer Science Faculty Research & Creative Works
The objective of this work is to present a solution to a multiple-objective optimization problem using genetic algorithms (GA). Generally, the objectives (minimizing cost, maximizing performance, reducing carbon footprints, maximizing profit) are conflicting for multiple-objective problems, hindering concurrent optimization of each objective. A bi-objective traditional combinatorial optimization of Travelling Salesman Problem is undertaken named as the Multi-Objective Travelling Salesman Problem (MTSP). The two objectives are minimization of the distance travelled by the salesman and minimization of the time taken to travel. The purpose of this paper is to model the problem as a single objective optimization problem using the weighted …
Mac Layer Misbehavior Detection Using Time Series Analysis, Maggie X. Cheng, Yi Ling, Wei Biao Wu
Mac Layer Misbehavior Detection Using Time Series Analysis, Maggie X. Cheng, Yi Ling, Wei Biao Wu
Computer Science Faculty Research & Creative Works
This paper presents a solution to the real-time detection of MAC layer misbehaviors in IEEE 802.11 networks. Among the wide range of misbehaviors, we focus on the sender side selfish behavior that creates a channel- capturing effect by using favorable parameters, and the receiver side selfish behavior that does not respond with CTS and ACK upon receiving RTS and data packets, which clears the channel for itself and causes its sender to waste resources. These misbehaviors are subtle to detect and yet can undermine the performance of the well-behaved nodes significantly. This paper shows a powerful real-time detection method that …
Towards Distributed Cyberinfrastructure For Smart Cities Using Big Data And Deep Learning Technologies, Shayan Shams, Sayan Goswami, Kisung Lee, Seungwon Yang, Seung Jong Park
Towards Distributed Cyberinfrastructure For Smart Cities Using Big Data And Deep Learning Technologies, Shayan Shams, Sayan Goswami, Kisung Lee, Seungwon Yang, Seung Jong Park
Computer Science Faculty Research & Creative Works
Recent advances in big data and deep learning technologies have enabled researchers across many disciplines to gain new insight into large and complex data. For example, deep neural networks are being widely used to analyze various types of data including images, videos, texts, and time-series data. In another example, various disciplines such as sociology, social work, and criminology are analyzing crowd-sourced and online social network data using big data technologies to gain new insight from a plethora of data. Even though many different types of data are being generated and analyzed in various domains, the development of distributed city-level cyberinfrastructure …
Analysis Of Grapevine Gene Expression Data Using Node-Based Resilience Clustering, Jeffrey Dale, John Matta, Susanne Howard, Gunes Ercal, Wenping Qiu, Tayo Obafemi-Ajayi
Analysis Of Grapevine Gene Expression Data Using Node-Based Resilience Clustering, Jeffrey Dale, John Matta, Susanne Howard, Gunes Ercal, Wenping Qiu, Tayo Obafemi-Ajayi
Electrical and Computer Engineering Faculty Research & Creative Works
Powdery mildew is the most economically important disease of cultivated grapevines worldwide. In the agricultural community, there is a great need for better understanding of the complex genetic basis of powdery mildew (PM) resistance by delineating possible gene biomarkers associated with the plants' defense mechanisms. Machine learning techniques can be applied to analysis of gene expression data to aid knowledge discovery of disease fighting genes. In this work, we apply a data-driven computational model, utilizing a graph-based clustering algorithm - Node-Based Resilience Clustering (NBRClust), to analyze grapevine gene expression data to identify possible gene biomarkers associated with powdery mildew disease …
Steric Control Of The Rate-Limiting Step Of Udp-Galactopyranose Mutase, Gustavo Pierdominici-Sottile, Rodrigo Cossio-Pérez, Isabel Da Fonseca, Karina Kizjakina, John J. Tanner, Pablo Sobrado
Steric Control Of The Rate-Limiting Step Of Udp-Galactopyranose Mutase, Gustavo Pierdominici-Sottile, Rodrigo Cossio-Pérez, Isabel Da Fonseca, Karina Kizjakina, John J. Tanner, Pablo Sobrado
Chemistry Faculty Research & Creative Works
Galactose is an abundant monosaccharide found exclusively in mammals as galactopyranose (Galp), the six-membered ring form of this sugar. In contrast, galactose appears in many pathogenic microorganisms as the five-membered ring form, galactofuranose (Galf). Galf biosynthesis begins with the conversion of UDP-Galp to UDP-Galf catalyzed by the flavoenzyme UDP-galactopyranose mutase (UGM). Because UGM is essential for the survival and proliferation of several pathogens, there is interest in understanding the catalytic mechanism to aid inhibitor development. Herein, we have used kinetic measurements and molecular dynamics simulations to explore the features of UGM that control the rate-limiting step (RLS). We show that …
Repeated Loading Model For Elastic-Plastic Contact Of Geomaterial, Jian Wang, Qimin Li, Changwei Yang, Caizhi Zhou
Repeated Loading Model For Elastic-Plastic Contact Of Geomaterial, Jian Wang, Qimin Li, Changwei Yang, Caizhi Zhou
Materials Science and Engineering Faculty Research & Creative Works
A new nonlinear hysteretic model with considering the loading, unloading, and reloading processes is developed based on Drucker—Prager yield criterion and finite-element analysis. This model can be used for multiple repeated elastic—plastic normal direction contact problems between two identical spherical geomaterials. After examining the influence of material properties, strain hardening, and loading histories, we found that the hysteretic phenomena (represented by residual displacement and plastic work) become weak after the first cycle, and the subsequent cycles step into elastic shakedown state eventually. A critical number of cycles can be used to estimate the state of ratchetting, plastic shakedown, as well …
Multi-Objective Optimization Based Allocation Of Heterogeneous Spatial Crowdsourcing Tasks, Liang Wang, Zhiwen Yu, Qi Han, Bin Guo, Haoyi Xiong
Multi-Objective Optimization Based Allocation Of Heterogeneous Spatial Crowdsourcing Tasks, Liang Wang, Zhiwen Yu, Qi Han, Bin Guo, Haoyi Xiong
Computer Science Faculty Research & Creative Works
With the rapid development of mobile networks and the proliferation of mobile devices, spatial crowdsourcing, which refers to recruiting mobile workers to perform location-based tasks, has gained emerging interest from both research communities and industries. In this paper, we consider a spatial crowdsourcing scenario: in addition to specific spatial constraints, each task has a valid duration, operation complexity, budget limitation, and the number of required workers. Each volunteer worker completes assigned tasks while conducting his/her routine tasks. The system has a desired task probability coverage and budget constraint. Under this scenario, we investigate an important problem, namely heterogeneous spatial crowdsourcing …
A Network Tomography Approach For Traffic Monitoring In Smart Cities, Ruoxi Zhang, Sara Newman, Marco Ortolani, Simone Silvestri
A Network Tomography Approach For Traffic Monitoring In Smart Cities, Ruoxi Zhang, Sara Newman, Marco Ortolani, Simone Silvestri
Computer Science Faculty Research & Creative Works
Traffic monitoring is a key enabler for several planning and management activities of a Smart City. However, traditional techniques are often not cost efficient, flexible, and scalable. This paper proposes an approach to traffic monitoring that does not rely on probe vehicles, nor requires vehicle localization through GPS. Conversely, it exploits just a limited number of cameras placed at road intersections to measure car end-to-end traveling times. We model the problem within the theoretical framework of network tomography, in order to infer the traveling times of all individual road segments in the road network. We specifically deal with the potential …
Automated Design Of Network Security Metrics, Aaron Scott Pope, Daniel R. Tauritz, Robert Morning, Alexander D. Kent
Automated Design Of Network Security Metrics, Aaron Scott Pope, Daniel R. Tauritz, Robert Morning, Alexander D. Kent
Computer Science Faculty Research & Creative Works
Many abstract security measurements are based on characteristics of a graph that represents the network. These are typically simple and quick to compute but are often of little practical use in making real-world predictions. Practical network security is often measured using simulation or real-world exercises. These approaches better represent realistic outcomes but can be costly and time-consuming. This work aims to combine the strengths of these two approaches, developing efficient heuristics that accurately predict attack success. Hyper-heuristic machine learning techniques, trained on network attack simulation training data, are used to produce novel graph-based security metrics. These low-cost metrics serve as …
The Automated Design Of Probabilistic Selection Methods For Evolutionary Algorithms, Samuel N. Richter, Daniel R. Tauritz
The Automated Design Of Probabilistic Selection Methods For Evolutionary Algorithms, Samuel N. Richter, Daniel R. Tauritz
Computer Science Faculty Research & Creative Works
Selection functions enable Evolutionary Algorithms (EAs) to apply selection pressure to a population of individuals, by regulating the probability that an individual's genes survive, typically based on fitness. Various conventional fitness based selection methods exist, each providing a unique relationship between the fitnesses of individuals in a population and their chances of selection. However, the full space of selection algorithms is only limited by max algorithm size, and each possible selection algorithm is optimal for some EA configuration applied to a particular problem class. Therefore, improved performance may be expected by tuning an EA's selection algorithm to the problem at …
Evolution Of Network Enumeration Strategies In Emulated Computer Networks, Sean Harris, Eric Michalak, Kevin Schoonover, Adam Gausmann, Hannah Reinbolt, Joshua Herman, Daniel R. Tauritz, Chris Rawlings, Aaron Scott Pope
Evolution Of Network Enumeration Strategies In Emulated Computer Networks, Sean Harris, Eric Michalak, Kevin Schoonover, Adam Gausmann, Hannah Reinbolt, Joshua Herman, Daniel R. Tauritz, Chris Rawlings, Aaron Scott Pope
Computer Science Faculty Research & Creative Works
Successful attacks on computer networks today do not often owe their victory to directly overcoming strong security measures set up by the defender. Rather, most attacks succeed because the number of possible vulnerabilities are too large for humans to fully protect without making a mistake. Regardless of the security elsewhere, a skilled attacker can exploit a single vulnerability in a defensive system and negate the benefits of those security measures. This paper presents an evolutionary framework for evolving attacker agents in a real, emulated network environment using genetic programming, as a foundation for coevolutionary systems which can automatically discover and …
Detonation Synthesis Of Alpha-Variant Silicon Carbide, Martin Langenderfer, Catherine E. Johnson, William Fahrenholtz, Vadym Mochalin
Detonation Synthesis Of Alpha-Variant Silicon Carbide, Martin Langenderfer, Catherine E. Johnson, William Fahrenholtz, Vadym Mochalin
Mining Engineering Faculty Research & Creative Works
A recent research study has been undertaken to develop facilities for conducting detonation synthesis of nanomaterials. This process involves a familiar technique that has been utilized for the industrial synthesis of nanodiamonds. Developments through this study have allowed for experimentation with the concept of modifying explosive compositions to induce synthesis of new nanomaterials. Initial experimentation has been conducted with the end goal being synthesis of alpha variant silicon carbide (α-SiC) in the nano-scale. The α-SiC that can be produced through detonation synthesis methods is critical to the ceramics industry because of a number of unique properties of the material. Conventional …
Tuning A Random-Field Mechanism In A Frustrated Magnet, Shashikant Singh Kunwar, Arnab Sen, Thomas Vojta, Rajesh Narayanan
Tuning A Random-Field Mechanism In A Frustrated Magnet, Shashikant Singh Kunwar, Arnab Sen, Thomas Vojta, Rajesh Narayanan
Physics Faculty Research & Creative Works
We study the influence of spinless impurities on a frustrated magnet featuring a spin-density wave (stripe) phase by means of Monte Carlo simulations. We demonstrate that the interplay between the impurities and an order parameter that breaks a real-space symmetry triggers the emergence of a random-field mechanism which destroys the stripe-ordered phase. Importantly, the strength of the emerging random fields can be tuned by the repulsion between the impurity atoms; they vanish for perfect anticorrelations between neighboring impurities. This provides a way of controlling the phase diagram of a many-particle system. In addition, we also investigate the effects of the …
Scholars' Mine Annual Report For Fiscal Year Ending June 2018, James Roger Weaver
Scholars' Mine Annual Report For Fiscal Year Ending June 2018, James Roger Weaver
Scholars’ Mine Statistics
Scholars' Mine annual statistics report for the fiscal year ending June 2018.
Discontinuous Galerkin Time-Domain Modeling Of Graphene Nanoribbon Incorporating The Spatial Dispersion Effects, Ping Li, Li (Lijun) Jun Jiang, Hakan Bagci
Discontinuous Galerkin Time-Domain Modeling Of Graphene Nanoribbon Incorporating The Spatial Dispersion Effects, Ping Li, Li (Lijun) Jun Jiang, Hakan Bagci
Electrical and Computer Engineering Faculty Research & Creative Works
It is well known that graphene demonstrates spatial dispersion properties, i.e., its conductivity is nonlocal and a function of spectral wavenumber (momentum operator) q. In this paper, to account for effects of spatial dispersion on transmission of high-speed signals along graphene nanoribbon (GNR) interconnects, a discontinuous Galerkin time-domain (DGTD) algorithm is proposed. The atomically thick GNR is modeled using a nonlocal transparent surface impedance boundary condition (SIBC) incorporated into the DGTD scheme. Since the conductivity is a complicated function of q (and one cannot find an analytical Fourier transform pair between q and spatial differential operators), an exact time-domain SIBC …
Kinetic Solvent Viscosity Effects As Probes For Studying The Mechanisms Of Enzyme Action, Giovanni Gadda, Pablo Sobrado
Kinetic Solvent Viscosity Effects As Probes For Studying The Mechanisms Of Enzyme Action, Giovanni Gadda, Pablo Sobrado
Chemistry Faculty Research & Creative Works
The study of enzyme reaction mechanisms is fundamentally important to our understanding of biochemistry, cellular metabolism, and drug development. This Perspective focuses on the use of kinetic solvent viscosity effects (KSVEs) to study enzyme reactions. This technique is easily implemented and uses steady-state kinetic analyses to probe whether substrate binding is diffusion-controlled and whether product release is the rate-limiting step in the catalytic cycle. In addition, KSVEs can identify isomerization steps that are important for catalysis. The use of KSVEs in combination with other techniques, such as kinetic isotope effects, pH effects, and site-directed mutagenesis, can provide a detailed view …
A Novel Hybrid 2d/Q-2d Finite Element Method For Power/Ground Plane Analysis, Ping Li, Li (Lijun) Jun Jiang, Hakan Bagci
A Novel Hybrid 2d/Q-2d Finite Element Method For Power/Ground Plane Analysis, Ping Li, Li (Lijun) Jun Jiang, Hakan Bagci
Electrical and Computer Engineering Faculty Research & Creative Works
By realizing the TMz modal distribution property between the power/ground plate-pairs, the magnetic field actually has only azimuthal components while longitude component is zero. Thus, if the magnetic field wave equation is solved, only a Quasi-2D issue is considered. Furthermore, since the high-order modes are only located in the near region of the anti-pad, thus for the domain far-away from the antipad has only the TEM mode. Thereby, in this region, the magnetic field is invariable along the vertical direction, which consequently is a pure 2D domain. As a result, the conventional 3D computational domain is naturally transformed to a …
Evaluating Classroom-Based, Online, Blended And Laboratory Teaching Interactions, University Of Missouri Intercampus Faculty Council
Evaluating Classroom-Based, Online, Blended And Laboratory Teaching Interactions, University Of Missouri Intercampus Faculty Council
Campus Resources for Faculty
No abstract provided.
Flexible To Rigid Nanoporous Polyurethane-Acrylate (Puac) Type Materials For Structural And Thermal Insulation Applications, Nicholas Leventis, Chariklia Sotiriou-Leventis, Abhishek Bang
Flexible To Rigid Nanoporous Polyurethane-Acrylate (Puac) Type Materials For Structural And Thermal Insulation Applications, Nicholas Leventis, Chariklia Sotiriou-Leventis, Abhishek Bang
Chemistry Faculty Research & Creative Works
Novel urethane-acrylate (UAC) Star monomers and polyurethane-acrylate (PUAC) aerogel polymers derived therefrom are described herein, along with other novel, related monomers and polymers. Also described herein are processes for preparing the UAC Star monomers, the PUAC aerogel polymers, and the other related monomers and polymers. The PUAC and related polymers herein are useful in various applications including in structural and thermal insulation.
Improving Performance Of Iterative Methods By Lossy Checkponting, Dingwen Tao, Sheng Di, Xin Liang, Zizhong Chen, Franck Cappello
Improving Performance Of Iterative Methods By Lossy Checkponting, Dingwen Tao, Sheng Di, Xin Liang, Zizhong Chen, Franck Cappello
Computer Science Faculty Research & Creative Works
Iterative methods are commonly used approaches to solve large, sparse linear systems, which are fundamental operations for many modern scientific simulations. When the large-scale iterative methods are running with a large number of ranks in parallel, they have to checkpoint the dynamic variables periodically in case of unavoidable fail-stop errors, requiring fast I/O systems and large storage space. To this end, significantly reducing the checkpointing overhead is critical to improving the overall performance of iterative methods. Our contribution is fourfold. (1) We propose a novel lossy checkpointing scheme that can significantly improve the checkpointing performance of iterative methods by leveraging …
Message From The Program Chairs - Volume 1, Jiannong Cao, Stelvio Cimato, Yasuo Okabe, Sahra Sedighsarvestani
Message From The Program Chairs - Volume 1, Jiannong Cao, Stelvio Cimato, Yasuo Okabe, Sahra Sedighsarvestani
Electrical and Computer Engineering Faculty Research & Creative Works
No abstract provided.
Evolution Of Structure And Superconductivity In Ba(Ni₁₋ₓcoₓ)₂As₂, Chris Eckberg, Limin Wang, Halyna Hodovanets, Hyunsoo Kim, Daniel J. Campbell, Peter Zavalij, Philip Piccoli, Johnpierre Paglione
Evolution Of Structure And Superconductivity In Ba(Ni₁₋ₓcoₓ)₂As₂, Chris Eckberg, Limin Wang, Halyna Hodovanets, Hyunsoo Kim, Daniel J. Campbell, Peter Zavalij, Philip Piccoli, Johnpierre Paglione
Physics Faculty Research & Creative Works
The effects of Co substitution on Ba(Ni1-xCox)2As2 (0 ≤ x ≤ 0.251) single crystals grown out of Pb flux are investigated via transport, magnetic, and thermodynamic measurements. BaNi2As2 exhibits a first-order tetragonal to triclinic structural phase transition at Ts = 137 K upon cooling, and enters a superconducting phase below Tc = 0.7 K. The structural phase transition is sensitive to cobalt content and is suppressed completely by x ≥ 0.133. The superconducting critical temperature, Tc, increases continuously with x, reaching a maximum of Tc …
Performance Of Carbon Aerogel/Fiber Paper As Capacitive Deionization Electrodes Under Variable Operating Conditions, Md Ashique Ahmed, Sanjay Tewari
Performance Of Carbon Aerogel/Fiber Paper As Capacitive Deionization Electrodes Under Variable Operating Conditions, Md Ashique Ahmed, Sanjay Tewari
Civil, Architectural and Environmental Engineering Faculty Research & Creative Works
The capacitive deionization has garnered renewed interested with recent modifications resulting in efficient (energy and cost) alternatives to desalinate brackish water (salt concentration less than 10 g/L). Recent research efforts, to improve the technology, have been focused mainly on electrode material development and modifications of operational parameters for optimized performance. This research is focused on performance evaluation of carbon aerogel/fiber paper as capacitive deionization electrodes under variable operating conditions. The main operational parameters that were varied are applied voltage, influent temperature and initial concentration. The highest adsorption capacity achieved in this on-going study is 4.61 mg/g at 33.5 oC with …
Identity-Adaptive Facial Expression Recognition Through Expression Regeneration Using Conditional Generative Adversarial Networks, Huiyuan Yang, Zheng Zhang, Lijun Yin
Identity-Adaptive Facial Expression Recognition Through Expression Regeneration Using Conditional Generative Adversarial Networks, Huiyuan Yang, Zheng Zhang, Lijun Yin
Computer Science Faculty Research & Creative Works
Subject variation is a challenging issue for facial expression recognition, especially when handling unseen subjects with small-scale labeled facial expression databases. Although transfer learning has been widely used to tackle the problem, the performance degrades on new data. In this paper, we present a novel approach (so-called IA-gen) to alleviate the issue of subject variations by regenerating expressions from any input facial images. First of all, we train conditional generative models to generate six prototypic facial expressions from any given query face image while keeping the identity related information unchanged. Generative Adversarial Networks are employed to train the conditional generative …
Worker Activity Recognition In Smart Manufacturing Using Imu And Semg Signals With Convolutional Neural Networks, Wenjin Tao, Ze-Hao Lai, Ming-Chuan Leu, Zhaozheng Yin
Worker Activity Recognition In Smart Manufacturing Using Imu And Semg Signals With Convolutional Neural Networks, Wenjin Tao, Ze-Hao Lai, Ming-Chuan Leu, Zhaozheng Yin
Mechanical and Aerospace Engineering Faculty Research & Creative Works
In a smart manufacturing system involving workers, recognition of the worker's activity can be used for quantification and evaluation of the worker's performance, as well as to provide onsite instructions with augmented reality. In this paper, we propose a method for activity recognition using Inertial Measurement Unit (IMU) and surface electromyography (sEMG) signals obtained from a Myo armband. The raw 10-channel IMU signals are stacked to form a signal image. This image is transformed into an activity image by applying Discrete Fourier Transformation (DFT) and then fed into a Convolutional Neural Network (CNN) for feature extraction, resulting in a high-level …
Modeling Of Cloud-Based Digital Twins For Smart Manufacturing With Mt Connect, Liwen Hu, Ngoc-Tu Nguyen, Wenjin Tao, Ming-Chuan Leu, Xiaoqing Frank Liu, Rakib Shahriar, S M Nahian Al Sunny
Modeling Of Cloud-Based Digital Twins For Smart Manufacturing With Mt Connect, Liwen Hu, Ngoc-Tu Nguyen, Wenjin Tao, Ming-Chuan Leu, Xiaoqing Frank Liu, Rakib Shahriar, S M Nahian Al Sunny
Mechanical and Aerospace Engineering Faculty Research & Creative Works
The common modeling of digital twins uses an information model to describe the physical machines. The integration of digital twins into productive cyber-physical cloud manufacturing (CPCM) systems imposes strong demands such as reducing overhead and saving resources. In this paper, we develop and investigate a new method for building cloud-based digital twins (CBDT), which can be adapted to the CPCM platform. Our method helps reduce computing resources in the information processing center for efficient interactions between human users and physical machines. We introduce a knowledge resource center (KRC) built on a cloud server for information intensive applications. An information model …
Learning Adaptivity In Support Of Flipped Learning: An Ontological Problem-Solving Approach, Yu Liang Chi, Tsang Yao Chen, Chih Li Hung
Learning Adaptivity In Support Of Flipped Learning: An Ontological Problem-Solving Approach, Yu Liang Chi, Tsang Yao Chen, Chih Li Hung
Business and Information Technology Faculty Research & Creative Works
In recent years, flipped learning has received tremendous attention from educational practitioners and researchers. However, this study argues that existing e-learning systems mainly serve for learning management and content delivery purposes, although they lack support for flipped learning. As an innovative educational approach, flipped learning requires more pedagogical elements, such as integrated instructional design and adaptive content delivery, to achieve effective direct instruction. This study aims to create a learning adaptivity design to support effective learning in the flipped individual learning space in which the teacher is absent. Because teaching involves various pedagogical and content knowledge sources, we propose a …
Design Of Robust And Efficient Topology Using Enhanced Gene Regulatory Networks, Satyaki Roy, Vijay K. Shah, Sajal K. Das
Design Of Robust And Efficient Topology Using Enhanced Gene Regulatory Networks, Satyaki Roy, Vijay K. Shah, Sajal K. Das
Computer Science Faculty Research & Creative Works
Biological networks are characterized by their inherent robustness against component failures. Gene regulatory networks (GRNs) are biological networks with graph properties contributing to their innate functional robustness. In this paper, we first propose a three-tier topological characterization to study the graph properties of GRN, namely scale free out-degree distribution, low graph density, and abundance of subgraphs, called motifs. We then present a novel edge rewiring mechanism, consisting of edge addition and deletion algorithms, to remedy its vulnerability against failure of well-connected nodes while preserving its graph properties. We discuss the preferential attachment growth-based edge addition and greedy edge deletion. We …