Engineering Commons^™

Development Of Guidelines For Collecting Transit Ridership Data, Hong Yang, Kun Xie, Sherif Ishak, Qingyu Ma, Yang Liu

Computational Modeling & Simulation Engineering Faculty Publications

Transit ridership is a critical determinant for many transit applications such as operation optimizations and project prioritization under performance-based funding mechanisms. As a result, the quality of ridership data is of utmost importance to both transit administrative agencies and transit operators. Many transit operators in Virginia report their ridership data to the Department of Rail and Public Transportation (DRPT) and the National Transit Database (NTD). However, with no specific guidelines available to transit agencies in Virginia for collecting ridership data, the heterogeneous mixture of diverse data collection methods and technologies has often raised concerns about the consistency and quality of …

Core Point Pixel-Level Localization By Fingerprint Features In Spatial Domain, Xueyi Ye, Yuzhong Shen, Maosheng Zeng, Yirui Liu, Huahua Chen, Zhijing Zhao

Computational Modeling & Simulation Engineering Faculty Publications

Singular point detection is a primary step in fingerprint recognition, especially for fingerprint alignment and classification. But in present there are still some problems and challenges such as more false-positive singular points or inaccurate reference point localization. This paper proposes an accurate core point localization method based on spatial domain features of fingerprint images from a completely different viewpoint to improve the fingerprint core point displacement problem of singular point detection. The method first defines new fingerprint features, called furcation and confluence, to represent specific ridge/valley distribution in a core point area, and uses them to extract the innermost Curve …

Supporting Transportation System Management And Operations Using Internet Of Things Technology, Hong Yang, Yuzhong Shen, Mecit Cetin, Zhenyu Wang

Computational Modeling & Simulation Engineering Faculty Publications

Low power wide-area network (LPWAN) technology aims to provide long range and low power wireless communication. It can serve as an alternative technology for data transmissions in many application scenarios (e.g., parking monitoring and remote flood sensing). In order to explore its feasibility in transportation systems, this project conducted a review of relevant literature to understand the current status of LPWAN applications. An online survey that targeted professionals concerned with transportation was also developed to elicit input about their experiences in using LPWAN technology for their projects. The literature review and survey results showed that LPWAN’s application in the U.S. …

Hybrid Models As Transdisciplinary Research Enablers, Andreas Tolk, Alison Harper, Navonil Mustafee

Computational Modeling & Simulation Engineering Faculty Publications

Modelling and simulation (M&S) techniques are frequently used in Operations Research (OR) to aid decision-making. With growing complexity of systems to be modelled, an increasing number of studies now apply multiple M&S techniques or hybrid simulation (HS) to represent the underlying system of interest. A parallel but related theme of research is extending the HS approach to include the development of hybrid models (HM). HM extends the M&S discipline by combining theories, methods and tools from across disciplines and applying multidisciplinary, interdisciplinary and transdisciplinary solutions to practice. In the broader OR literature, there are numerous examples of cross-disciplinary approaches in …

Electroosmotic Mixing Of Non-Newtonian Fluid In A Microchannel With Obstacles And Zeta Potential Heterogeneity, Lanju Mei, Defu Cui, Jiayue Shen, Diganta Dutta, Willie Brown, Lei Zhang, Ibibia K. Dabipi

Computational Modeling & Simulation Engineering Faculty Publications

This paper investigates the electroosmotic micromixing of non-Newtonian fluid in a microchannel with wall-mounted obstacles and surface potential heterogeneity on the obstacle surface. In the numerical simulation, the full model consisting of the Navier–Stokes equations and the Poisson–Nernst–Plank equations are solved for the electroosmotic fluid field, ion transport, and electric field, and the power law model is used to characterize the rheological behavior of the aqueous solution. The mixing performance is investigated under different parameters, such as electric double layer thickness, flow behavior index, obstacle surface zeta potential, obstacle dimension. Due to the zeta potential heterogeneity at the obstacle surface, …

Modeling And Simulation Of Cascading Failures In Transportation Systems During Hurricane Evacuations, Yuan Zhu, Kaan Ozbay, Hong Yang, Fan Zuo, Di Sha

Computational Modeling & Simulation Engineering Faculty Publications

Effective and timely evacuation is critical in alleviating the impact of hurricanes. As such, evacuation models are often sought to support the preparedness of evacuations. One important task in the modeling process is to evaluate exogenous factors that cause transportation system capacity loss during evacuation. Typical factors include direct damage to the roadway network due to storm surge and cascading impacts because of other facilities failures. For example, power outage can lead to signal failure and subway suspension. This paper aims to develop a macroscopic simulation-based approach to study the capacity loss of the roadway network in evacuation due to …

Hidden Markov Model And Cyber Deception For The Prevention Of Adversarial Lateral Movement, Md Ali Reza Al Amin, Sachin Shetty, Laurent Njilla, Deepak K. Tosh, Charles Kamhoua

Computational Modeling & Simulation Engineering Faculty Publications

Advanced persistent threats (APTs) have emerged as multi-stage attacks that have targeted nation-states and their associated entities, including private and corporate sectors. Cyber deception has emerged as a defense approach to secure our cyber infrastructure from APTs. Practical deployment of cyber deception relies on defenders' ability to place decoy nodes along the APT path optimally. This paper presents a cyber deception approach focused on predicting the most likely sequence of attack paths and deploying decoy nodes along the predicted path. Our proposed approach combines reactive (graph analysis) and proactive (cyber deception technology) defense to thwart the adversaries' lateral movement. The …

Guidelines For Using Streetlight Data For Planning Tasks, Hong Yang, Mecit Cetin, Qingyu Ma

Computational Modeling & Simulation Engineering Faculty Publications

The Virginia Department of Transportation (VDOT) has purchased a subscription to the StreetLight (SL) Data products that mainly offer origin-destination (OD) related metrics through crowdsourcing data. Users can manipulate a data source like this to quickly estimate origin-destination trip tables. Nonetheless, the SL metrics heavily rely on the data points sampled from smartphone applications and global positioning services (GPS) devices, which may be subject to potential bias and coverage issues. In particular, the quality of the SL metrics in relation to meeting the needs of various VDOT work tasks is not clear. Guidelines on the use of the SL metrics …

Short-Term Truckload Spot Rates' Prediction In Consideration Of Temporal And Between-Route Correlations, Wei Xiao, Chuan Xu, Hongling Liu, Hong Yang, Xiaobo Liu

Computational Modeling & Simulation Engineering Faculty Publications

Truckload spot rate (TSR), defined as a price offered on the spot to transport a certain cargo by using an entire truck on a target transportation line, usually price per kilometer-ton, is a key factor in shaping the freight market. In particular, the prediction of short-term TSR is of great importance to the daily operations of the trucking industry. However, existing predictive practices have been limited largely by the availability of multilateral information, such as detailed intraday TSR information. Fortunately, the emerging online freight exchange (OFEX) platforms provide unique opportunities to access and fuse more data for probing the trucking …

Recent Developments In The General Atomic And Molecular Electronic Structure System, Guiseppe M.J. Barca, Colleen Bertoni, Laura Carrington, Dipayan Datta, Nuwan De Silva, J. Emillano Deustua, Dmitri G. Fedorov, Jeffrey R. Cour, Anastasia O. Gunina, Emilie Guidez, Taylor Harville, Stephan Irle, Joe Ivanic, Karol Kowalski, Sarom S. Leang, Wei Li, Jesse J. Lutz, Ilias Magoulas, Joani Mato, Vladimir Mironov, Hiroya Nakata, Buu Q. Pham, Piotr Piecuch, David Poole, Spencer R. Pruitt, Alistair P. Rendell, Luke B. Roskop, Klaus Ruedenberg, Tosaporn Sattasathuchana, Michael W. Schmidt, Jun Shen, Lyudmila Slipchenko, Masha Sosonkina, Vaibhav Sundriyal, Ananta Tiwari, Jorge L. Galvez Vallejo, Bryce Westheimer, Marta Włoch, Peng Xu, Federico Zahariev, Mark S. Gordon

Computational Modeling & Simulation Engineering Faculty Publications

A discussion of many of the recently implemented features of GAMESS (General Atomic and Molecular Electronic Structure System) and LibCChem (the C++ CPU/GPU library associated with GAMESS) is presented. These features include fragmentation methods such as the fragment molecular orbital, effective fragment potential and effective fragment molecular orbital methods, hybrid MPI/OpenMP approaches to Hartree-Fock, and resolution of the identity second order perturbation theory. Many new coupled cluster theory methods have been implemented in GAMESS, as have multiple levels of density functional/tight binding theory. The role of accelerators, especially graphical processing units, is discussed in the context of the new features …

Deformable Multisurface Segmentation Of The Spine For Orthopedic Surgery Planning And Simulation, Rabia Haq, Jérôme Schmid, Roderick Borgie, Joshua Cates, Michel Audette

Computational Modeling & Simulation Engineering Faculty Publications

Purpose: We describe a shape-aware multisurface simplex deformable model for the segmentation of healthy as well as pathological lumbar spine in medical image data.

Approach: This model provides an accurate and robust segmentation scheme for the identification of intervertebral disc pathologies to enable the minimally supervised planning and patient-specific simulation of spine surgery, in a manner that combines multisurface and shape statistics-based variants of the deformable simplex model. Statistical shape variation within the dataset has been captured by application of principal component analysis and incorporated during the segmentation process to refine results. In the case where shape statistics hinder detection …

A Tutorial And Future Research For Building A Blockchain-Based Secure Communication Scheme For Internet Of Intelligent Things, Mohammad Wazid, Ashok Kumar Das, Sachin Shetty, Minho Jo

Computational Modeling & Simulation Engineering Faculty Publications

The Internet of Intelligent Things (IoIT) communication environment can be utilized in various types of applications (for example, intelligent battlefields, smart healthcare systems, the industrial internet, home automation, and many more). Communications that happen in such environments can have different types of security and privacy issues, which can be resolved through the utilization of blockchain. In this paper, we propose a tutorial that aims in desiging a generalized blockchain-based secure authentication key management scheme for the IoIT environment. Moreover, some issues with using blockchain for a communication environment are discussed as future research directions. The details of different types of …

Implementing Asynchronous Linear Solvers Using Non-Uniform Distributions, Erik Jensen, Evan C. Coleman, Masha Sosonkina

Computational Modeling & Simulation Engineering Faculty Publications

Asynchronous iterative methods present a mechanism to improve the performance of algorithms for highly parallel computational platforms by removing the overhead associated with synchronization among computing elements. This paper considers a class of asynchronous iterative linear system solvers that employ randomization to determine the component update orders, specifically focusing on the effects of drawing the order from non-uniform distributions. Results from shared-memory experiments with a two-dimensional finite-difference discrete Laplacian problem show that using distributions favoring the selection of components with a larger contribution to the residual may lead to faster convergence than selecting uniformly. Multiple implementations of the randomized asynchronous …

Emerging Roles Of Virtual Patients In The Age Of Ai, C. Donald Combs, P. Ford Combs

Computational Modeling & Simulation Engineering Faculty Publications

Today's web-enabled and virtual approach to medical education is different from the 20th century's Flexner-dominated approach. Now, lectures get less emphasis and more emphasis is placed on learning via early clinical exposure, standardized patients, and other simulations. This article reviews literature on virtual patients (VPs) and their underlying virtual reality technology, examines VPs' potential through the example of psychiatric intake teaching, and identifies promises and perils posed by VP use in medical education.

Hurricane Evacuation Modeling Using Behavior Models And Scenario-Driven Agent-Based Simulations, Yuan Zhu, Kun Xie, Kaan Ozbay, Hong Yang

Computational Modeling & Simulation Engineering Faculty Publications

Transportation modeling and simulation play an important role in the planning and management of emergency evacuation. It is often indispensable for the preparedness and timely response to extreme events occurring in highly populated areas. Reliable and robust agent-based evacuation models are of great importance to support evacuation decision making. Nevertheless, these models rely on numerous hypothetical causal relationships between the evacuation behavior and a variety of factors including socio-economic characteristics and storm intensity. Understanding the impacts of these factors on evacuation behaviors (e.g., destination and route choices) is crucial in preparing optimal evacuation plans. This paper aims to contribute to …

Data-Driven Spatial Modeling For Quantifying Networkwide Resilience In The Aftermath Of Hurricanes Irene And Sandy, Yuan Zhu, Kun Xie, Kaan Ozbay, Fan Zuo, Hong Yang

Computational Modeling & Simulation Engineering Faculty Publications

In recent years, the New York City metropolitan area was hit by two major hurricanes, Irene and Sandy. These extreme weather events disrupted and devastated the transportation infrastructure, including road and subway networks. As an extension of the authors' recent research on this topic, this study explored the spatial patterns of infrastructure resilience in New York City with the use of taxi and subway ridership data. Neighborhood tabulation areas were used as the units of analysis. The recovery curve of each neighborhood tabulation area was modeled with the logistic function to quantify the resilience of road and subway systems. Moran's …

Controlling The Error On Target Motion Through Real-Time Mesh Adaptation: Applications To Deep Brain Stimulation, Huu Phuoc Bui, Satyendra Tomar, Hadrien Courtecuisse, M. Audette, Stéphane Cotin, Stéphane P.A. Bordas

Computational Modeling & Simulation Engineering Faculty Publications

We present an error-controlled mesh refinement procedure for needle insertion simulation and apply it to the simulation of electrode implantation for deep brain stimulation, including brain shift.

Our approach enables to control the error in the computation of the displacement and stress fields around the needle tip and needle shaft by suitably refining the mesh, whilst maintaining a coarser mesh in other parts of the domain.

We demonstrate through academic and practical examples that our approach increases the accuracy of the displacement and stress fields around the needle without increasing the computational expense. This enables real-time simulations.

The proposed methodology …

Secrecy Rates And Optimal Power Allocation For Full-Duplex Decode-And-Forward Relay Wire-Tap Channels, Lubna Elsaid, Leonardo Jimenez-Rodriguez, Nghi H. Tran, Sachin Shetty, Shivakumar Sastry

Computational Modeling & Simulation Engineering Faculty Publications

This paper investigates the secrecy rates and optimal power allocation schemes for a decode-and-forward wiretap relay channel where the transmission from a source to a destination is aided by a relay operating in a full-duplex (FD) mode under practical residual self-interference. By first considering static channels, we address the non-convex optimal power allocation problems between the source and relay nodes under individual and joint power constraints to establish closed-form solutions. An asymptotic analysis is then given to provide important insights on the derived power allocation solutions. Specifically, by using the method of dominant balance, it is demonstrated that full power …

Impact Of Connected Vehicles On Mitigating Secondary Crash Risk, Hong Yang, Zhenyu Wang, Kun Xie

Computational Modeling & Simulation Engineering Faculty Publications

Reducing the risk of secondary crashes is a key goal for effective traffic incident management. However, only few countermeasures have been established in practices to achieve the goal. This is mainly due to the stochastic nature of both primary and secondary crashes. Given the emerging connected vehicle (CV) technologies, it is highly likely that CVs will soon be able to communicate with each other through the ad-hoc wireless vehicular network. Information sharing among vehicles is deemed to change traffic operations and allow motorists for more proactive actions. Motorists who receive safety messages can be motivated to approach queues and incident …

Hoeffding Tree Algorithms For Anomaly Detection In Streaming Datasets: A Survey, Asmah Muallem, Sachin Shetty, Jan W. Pan, Juan Zhao, Biswajit Biswal

Computational Modeling & Simulation Engineering Faculty Publications

This survey aims to deliver an extensive and well-constructed overview of using machine learning for the problem of detecting anomalies in streaming datasets. The objective is to provide the effectiveness of using Hoeffding Trees as a machine learning algorithm solution for the problem of detecting anomalies in streaming cyber datasets. In this survey we categorize the existing research works of Hoeffding Trees which can be feasible for this type of study into the following: surveying distributed Hoeffding Trees, surveying ensembles of Hoeffding Trees and surveying existing techniques using Hoeffding Trees for anomaly detection. These categories are referred to as compositions …

N3lo Nn Interaction Adjusted To Light Nuclei In Ab Exitu Approach, A. M. Shirokov, I. J. Shin, Y. Kim, M. Sosonkina, P. Maris, J. P. Vary

Computational Modeling & Simulation Engineering Faculty Publications

We use phase-equivalent transformations to adjust off-shell properties of similarity renormalization group evolved chiral effective field theory NN interaction (Idaho N3LO) to fit selected binding energies and spectra of light nuclei in an ab exitu approach. We then test the transformed interaction on a set of additional observables in light nuclei to verify that it provides reasonable descriptions of these observables with an apparent reduced need for three- and many-nucleon interactions.

Transformation Model With Constraints For High Accuracy Of 2d-3d Building Registration In Aerial Imagery, Guoqing Zhou, Qingli Luo, Wenhan Xie, Tao Yue, Jingjin Huang, Yuzhong Shen

Computational Modeling & Simulation Engineering Faculty Publications

This paper proposes a novel rigorous transformation model for 2D-3D registration to address the difficult problem of obtaining a sufficient number of well-distributed ground control points (GCPs) in urban areas with tall buildings. The proposed model applies two types of geometric constraints, co-planarity and perpendicularity, to the conventional photogrammetric collinearity model. Both types of geometric information are directly obtained from geometric building structures, with which the geometric constraints are automatically created and combined into the conventional transformation model. A test field located in downtown Denver, Colorado, is used to evaluate the accuracy and reliability of the proposed method. The comparison …

Stability And Sensitivity Measures For Solutions In Complex, Intelligent, Adaptive And Autonomous Systems, Andreas Tolk

Computational Modeling & Simulation Engineering Faculty Publications

Simulation has become a pivotal tool for the design, analysis, and control of complex, intelligent, adaptive and autonomous systems and its components. However, due to the nature of these systems, traditional evaluation practices are often not sufficient. As the components follow adaptive rules, the cumulative events often exploit bifurcation enabling events, leading to clusters of solutions that do not follow the usual rules for standard distributed events. When using simulation for design, analysis, and control of such systems, the evaluation needs to be richer, applying bifurcation and cluster analysis to understand the distribution, applying factor analysis to understand the important …

Energy-Efficient Computational Chemistry: Comparison Of X86 And Arm Systems, Kristopher Keipert, Gaurav Mitra, Vaibhav Sunriyal, Sarom S. Leang, Masha Sosonkina, Alistair P. Rendell, Mark S. Gordon

Computational Modeling & Simulation Engineering Faculty Publications

The computational efficiency and energy-to-solution of several applications using the GAMESS quantum chemistry suite of codes is evaluated for 32-bit and 64-bit ARM-based computers, and compared to an x86 machine. The x86 system completes all benchmark computations more quickly than either ARM system and is the best choice to minimize time to solution. The ARM64 and ARM32 computational performances are similar to each other for Hartree-Fock and density functional theory energy calculations. However, for memory-intensive second-order perturbation theory energy and gradient computations the lower ARM32 read/write memory bandwidth results in computation times as much as 86% longer than on the …

Merging Two Worlds: Agent-Based Simulation Methods For Autonomous Systems, Andreas Tolk

Computational Modeling & Simulation Engineering Faculty Publications

This chapter recommends the increased use of agent-based simulation methods to support the design, development, testing, and operational use of autonomous systems. This recommendation is motivated by deriving taxonomies for intelligent software agents and autonomous robotic systems from the public literature, which shows their similarity: intelligent software agents can be interpreted as the virtual counterparts of autonomous robotic systems. This leads to examples of how simulation can be used to significantly improve autonomous system research and development in selected use cases. The chapter closes with observations on the operational effects of possible emergent behaviour and the need to align the …

Adaptive Double Chain Quantum Genetic Algorithm For Constrained Optimization Problems, Kong Haipeng, Li Ni, Yuzhong Shen

Computational Modeling & Simulation Engineering Faculty Publications

Optimization problems are often highly constrained and evolutionary algorithms (EAs) are effective methods to tackle this kind of problems. To further improve search efficiency and convergence rate of EAs, this paper presents an adaptive double chain quantum genetic algorithm (ADCQGA) for solving constrained optimization problems. ADCQGA makes use of double-individuals to represent solutions that are classified as feasible and infeasible solutions. Fitness (or evaluation) functions are defined for both types of solutions. Based on the fitness function, three types of step evolution (SE) are defined and utilized for judging evolutionary individuals. An adaptive rotation is proposed and used to facilitate …

Neuroimaging And Neuromodulation Approaches To Study Eating Behavior And Prevent And Treat Eating Disorders And Obesity, D. Val-Laillet, E. Aarts, B. Weber, M. Ferrari, V. Quaresima, L. E. Stoeckel, M. Alonso-Alonso, M. Audette, C. H. Malbert, E. Stice

Computational Modeling & Simulation Engineering Faculty Publications

Functional, molecular and genetic neuroimaging has highlighted the existence of brain anomalies and neural vulnerability factors related to obesity and eating disorders such as binge eating or anorexia nervosa. In particular, decreased basal metabolism in the prefrontal cortex and striatum as well as dopaminergic alterations have been described in obese subjects, in parallel with increased activation of reward brain areas in response to palatable food cues. Elevated reward region responsivity may trigger food craving and predict future weight gain. This opens the way to prevention studies using functional and molecular neuroimaging to perform early diagnostics and to phenotype subjects at …

Changing Cpu Frequency In Comd Proxy Application Offloaded To Intel Xeon Phi Co-Processors, Gary Lawson, Masha Sosonkina, Yuzhong Shen

Computational Modeling & Simulation Engineering Faculty Publications

Obtaining exascale performance is a challenge. Although the technology of today features hardware with very high levels of concurrency, exascale performance is primarily limited by energy consumption. This limitation has lead to the use of GPUs and specialized hardware such as many integrated core (MIC) co-processors and FPGAs for computation acceleration. The Intel Xeon Phi co-processor, built upon the MIC architecture, features many low frequency, energy efficient cores. Applications, even those which do not saturate the large vector processing unit in each core, may benefit from the energy-efficient hardware and software of the Xeon Phi. This work explores the energy …

Potential Of Cognitive Computing And Cognitive Systems, Ahmed K. Noor

Computational Modeling & Simulation Engineering Faculty Publications

Cognitive computing and cognitive technologies are game changers for future engineering systems, as well as for engineering practice and training. They are major drivers for knowledge automation work, and the creation of cognitive products with higher levels of intelligence than current smart products. This paper gives a brief review of cognitive computing and some of the cognitive engineering systems activities. The potential of cognitive technologies is outlined, along with a brief description of future cognitive environments, incorporating cognitive assistants - specialized proactive intelligent software agents designed to follow and interact with humans and other cognitive assistants across the environments. The …

Design And Comparison Of Immersive Interactive Learning And Instructional Techniques For 3d Virtual Laboratories, Shuo Ren, Frederic D. Mckenzie, Sushil K. Chaturvedi, Ramamurthy Prabhakaran, Jaewan Yoon, Petros J. Katsioloudis, Hector Garcia

Computational Modeling & Simulation Engineering Faculty Publications

This work presents the design, development, and testing of 3D virtual laboratories for practice, specifically in undergraduate mechanical engineering laboratories. The 3D virtual laboratories, implemented under two virtual environments3DTV and Computer Automated Virtual Environment (CAVE)serve as pre-lab sessions performed before the actual physical laboratory experiment. The current study compares the influence of two instructional methods (conventional lecture-based and inquiry-based) under two virtual environments, and the results are compared with the pre-lab sessions using a traditional paper-based lab manual. Subsequently, the evaluation is done by conducting performance and quantitative assessments from students pre-and post-laboratory performances. The research results demonstrate that students …