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Old Dominion University

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Articles 1351 - 1380 of 1996

Full-Text Articles in Computer Sciences

Generating Combinatorial Objects- A New Perspective, Alexander Chizoma Nwala May 2014

Generating Combinatorial Objects- A New Perspective, Alexander Chizoma Nwala

Computer Science Theses & Dissertations

Combinatorics is the science of "possibilities." This definition, while not formal is a fair statement because all too often, in order to gain insight into the solution of many counting problems, we explore the possibilities. In some cases we seek to know how many options, while in other cases we seek to enumerate or list the options. Irrespective of the scenario, combinatorics plays a vital role today. In many instances such as exploring the options for choosing a new password for a combination lock, we employ combinatorics. In considering the possible license plate permutations for a state, or to see …


Section Abstracts: Computer Science Apr 2014

Section Abstracts: Computer Science

Virginia Journal of Science

Abstracts of the Computer Science Section for the 92nd Annual Meeting of the Virginia Academy of Science, May 13-15, 2014, Virginia Commonwealth University, Richmond, Virginia


Transparent Spectrum Co-Access In Cognitive Radio Networks, Jonathan Daniel Backens Apr 2014

Transparent Spectrum Co-Access In Cognitive Radio Networks, Jonathan Daniel Backens

Electrical & Computer Engineering Theses & Dissertations

The licensed wireless spectrum is currently under-utilized by as much as 85%. Cognitive radio networks have been proposed to employ dynamic spectrum access to share this under-utilized spectrum between licensed primary user transmissions and unlicensed secondary user transmissions. Current secondary user opportunistic spectrum access methods, however, remain limited in their ability to provide enough incentive to convince primary users to share the licensed spectrum, and they rely on primary user absence to guarantee secondary user performance. These challenges are addressed by developing a Dynamic Spectrum Co-Access Architecture (DSCA) that allows secondary user transmissions to co-access transparently and concurrently with primary …


Simulation Modeling And Analysis Of Customs-Regulated Container Terminal Operations With Multimodal Transportation, Mariam A. Kotachi Apr 2014

Simulation Modeling And Analysis Of Customs-Regulated Container Terminal Operations With Multimodal Transportation, Mariam A. Kotachi

Engineering Management & Systems Engineering Theses & Dissertations

World trade has been increasing dramatically in the past two decades and, as a result, container exchange has grown significantly. Consequently and to meet this increase, several container terminals are expanding and many new ones are being established. A port with one or more container terminals is considered a complex system in which many entities interact to accomplish seamless handling of containers inbound and outbound. The level of complexity is drastically heightened for container terminals containing multimodal transportation systems as they typically involve ships, rail, and trucks arriving to one or more terminals delivering containers of different sizes to several …


Web Archive Services Framework For Tighter Integration Between The Past And Present Web, Ahmed Alsum Apr 2014

Web Archive Services Framework For Tighter Integration Between The Past And Present Web, Ahmed Alsum

Computer Science Theses & Dissertations

Web archives have contained the cultural history of the web for many years, but they still have a limited capability for access. Most of the web archiving research has focused on crawling and preservation activities, with little focus on the delivery methods. The current access methods are tightly coupled with web archive infrastructure, hard to replicate or integrate with other web archives, and do not cover all the users' needs. In this dissertation, we focus on the access methods for archived web data to enable users, third-party developers, researchers, and others to gain knowledge from the web archives. We build …


Document Classification In Support Of Automated Metadata Extraction Form Heterogeneous Collections, Paul K. Flynn Apr 2014

Document Classification In Support Of Automated Metadata Extraction Form Heterogeneous Collections, Paul K. Flynn

Computer Science Theses & Dissertations

A number of federal agencies, universities, laboratories, and companies are placing their documents online and making them searchable via metadata fields such as author, title, and publishing organization. To enable this, every document in the collection must be catalogued using the metadata fields. Though time consuming, the task of identifying metadata fields by inspecting the document is easy for a human. The visual cues in the formatting of the document along with accumulated knowledge and intelligence make it easy for a human to identify various metadata fields. Even with the best possible automated procedures, numerous sources of error exist, including …


Assessing The Impact Of Electronic Health Record Systems Implementation On Hospital Patient Perceptions Of Care, Katherine Sofia Palacio Salgar Apr 2014

Assessing The Impact Of Electronic Health Record Systems Implementation On Hospital Patient Perceptions Of Care, Katherine Sofia Palacio Salgar

Engineering Management & Systems Engineering Theses & Dissertations

The delivery of health care services has been impacted by advances in Knowledge Management Information Systems (KMIS) and Information Technology (IT). The literature reveals that Electronic Health Records Systems (EHRs) are a comprehensive KMIS. There is a wide recognition in the body of knowledge that demonstrates the potential of EHRs to transform all aspects of health care services and, in consequence, the performance of Health Care Delivery Organizations (HCDO). Authors of published research also agree that there is a need for more empirical contributions that demonstrate the impact of EHRs upon HCDO. It is argued that in most cases, studies …


Markov Chain Monte Carlo Bayesian Predictive Framework For Artificial Neural Network Committee Modeling And Simulation, Michael S. Goodrich Apr 2014

Markov Chain Monte Carlo Bayesian Predictive Framework For Artificial Neural Network Committee Modeling And Simulation, Michael S. Goodrich

Computational Modeling & Simulation Engineering Theses & Dissertations

A logical inference method of properly weighting the outputs of an Artificial Neural Network Committee for predictive purposes using Markov Chain Monte Carlo simulation and Bayesian probability is proposed and demonstrated on machine learning data for non-linear regression, binary classification, and 1-of-k classification. Both deterministic and stochastic models are constructed to model the properties of the data. Prediction strategies are compared based on formal Bayesian predictive distribution modeling of the network committee output data and a stochastic estimation method based on the subtraction of determinism from the given data to achieve a stochastic residual using cross validation. Performance for Bayesian …


Modeling Stem Cell Population Dynamics, Samiur Arif Apr 2014

Modeling Stem Cell Population Dynamics, Samiur Arif

Computer Science Theses & Dissertations

Because of the stochastic nature of biological systems, mathematical and computational modeling approaches have become more acceptable to experimentalists and clinicians in recent years as contributing to new understandings of complicated cell mechanisms and tissue physiology. Indeed, even single cell or small tissue samples are complex dynamic systems that adapt to environmental challenges in space and time which is poorly understood. Mathematical models and computer simulations can explain and uncover unknown aspects of cell behavior and tissue functions. Models based on key biological mechanisms can give interesting insights and formulate predictions that cannot be derived from physical experiments or statistical …


Engineering Collaborations In Medical Modeling And Simulation, Frederic D. Mckenzie, Salim Chemlal, Tom Hubbard, Robert E. Kelly, Roderick C. Borgie, David A. Besachio, Michel Audette Jan 2014

Engineering Collaborations In Medical Modeling And Simulation, Frederic D. Mckenzie, Salim Chemlal, Tom Hubbard, Robert E. Kelly, Roderick C. Borgie, David A. Besachio, Michel Audette

Computational Modeling & Simulation Engineering Faculty Publications

Fifty years ago computer science was just beginning to see common acceptance as a growing discipline and very few universities had a computer science department although other departments were utilizing computers and software to enhance their methodologies. We believe modeling and simulation (M&S) is on a similar path. Many other disciplines utilize M&S to enhance their methodologies but we also believe that M&S fundamentals can be essential in making better decisions by utilizing the appropriate model for the problem at hand, expanding the solution space through simulation, and understanding it through visualization and proper analyses. After our students learn these …


A Distributed Consensus Algorithm For Decision Making In Service-Oriented Internet Of Things, Shancang Li, George Oikonomou, Theo Tryfonas, Thomas M. Chen, Li Da Xu Jan 2014

A Distributed Consensus Algorithm For Decision Making In Service-Oriented Internet Of Things, Shancang Li, George Oikonomou, Theo Tryfonas, Thomas M. Chen, Li Da Xu

Information Technology & Decision Sciences Faculty Publications

In a service-oriented Internet of things (IoT) deployment, it is difficult to make consensus decisions for services at different IoT edge nodes where available information might be insufficient or overloaded. Existing statistical methods attempt to resolve the inconsistency, which requires adequate information to make decisions. Distributed consensus decision making (CDM) methods can provide an efficient and reliable means of synthesizing information by using a wider range of information than existing statistical methods. In this paper, we first discuss service composition for the IoT by minimizing the multi-parameter dependent matching value. Subsequently, a cluster-based distributed algorithm is proposed, whereby consensuses are …


Data Mining Based Hybridization Of Meta-Raps, Fatemah Al-Duoli, Ghaith Rabadi Jan 2014

Data Mining Based Hybridization Of Meta-Raps, Fatemah Al-Duoli, Ghaith Rabadi

Engineering Management & Systems Engineering Faculty Publications

Though metaheuristics have been frequently employed to improve the performance of data mining algorithms, the opposite is not true. This paper discusses the process of employing a data mining algorithm to improve the performance of a metaheuristic algorithm. The targeted algorithms to be hybridized are the Meta-heuristic for Randomized Priority Search (Meta-RaPS) and an algorithm used to create an Inductive Decision Tree. This hybridization focuses on using a decision tree to perform on-line tuning of the parameters in Meta-RaPS. The process makes use of the information collected during the iterative construction and improvement phases Meta-RaPS performs. The data mining algorithm …


Detection Of Seagrass Scars Using Sparse Coding And Morphological Filter, Ender Oguslu, Sertan Erkanli, Victoria J. Hill, W. Paul Bissett, Richard C. Zimmerman, Jiang Li, Charles R. Bostater Jr. (Ed.), Stelios P. Mertikas (Ed.), Xavier Neyt (Ed.) Jan 2014

Detection Of Seagrass Scars Using Sparse Coding And Morphological Filter, Ender Oguslu, Sertan Erkanli, Victoria J. Hill, W. Paul Bissett, Richard C. Zimmerman, Jiang Li, Charles R. Bostater Jr. (Ed.), Stelios P. Mertikas (Ed.), Xavier Neyt (Ed.)

OES Faculty Publications

We present a two-step algorithm for the detection of seafloor propeller seagrass scars in shallow water using panchromatic images. The first step is to classify image pixels into scar and non-scar categories based on a sparse coding algorithm. The first step produces an initial scar map in which false positive scar pixels may be present. In the second step, local orientation of each detected scar pixel is computed using the morphological directional profile, which is defined as outputs of a directional filter with a varying orientation parameter. The profile is then utilized to eliminate false positives and generate the final …


Industrial Wireless Sensor Networks, Shancang Li, Hongjian Sun, Arumugam Nallanathan, Li Xu, Shanshan Zhao, Qindong Sun Jan 2014

Industrial Wireless Sensor Networks, Shancang Li, Hongjian Sun, Arumugam Nallanathan, Li Xu, Shanshan Zhao, Qindong Sun

Information Technology & Decision Sciences Faculty Publications

(First Paragraph) Industrial wireless sensor networks (IWSNs) incorporate wireless sensor networks with intelligent industrial systems providing many advantages over existing industrial applications, such as wireless communication, low cost, rapid deployment, self-organization, intelligent controlling, and processing capability. With the proliferation of wireless sensor networks in industrial applications, IWSNs technologies promise to play a significant role in developing more reliable, efficient, stable, flexible, and application-centric industrial systems.


An Itk Implementation Of A Physics-Based Non-Rigid Registration Method For Brain Deformation In Image Guided Neurosurgery, Yixun Liu, Andriy Kot, Fotis Drakopoulos, Chengjun Yao, Andriy Fedorov, Andinet Enquobahrie, Oliver Clatz, Nikos P. Chrisochoides Jan 2014

An Itk Implementation Of A Physics-Based Non-Rigid Registration Method For Brain Deformation In Image Guided Neurosurgery, Yixun Liu, Andriy Kot, Fotis Drakopoulos, Chengjun Yao, Andriy Fedorov, Andinet Enquobahrie, Oliver Clatz, Nikos P. Chrisochoides

Electrical & Computer Engineering Faculty Publications

As part of the ITK v4 project efforts, we have developed ITK filters for physics-based non-rigid registration (PBNRR), which satisfies the following requirements: account for tissue properties in the registration, improve accuracy compared to rigid registration, and reduce execution time using GPU and multi-core accelerators. The implementation has three main components: (1) Feature Point Selection, (2) Block Matching (mapped to both multi-core and GPU processors), and (3) a Robust Finite Element Solver. The use of multi-core and GPU accelerators in ITK v4 provides substantial performance improvements. For example, for the non-rigid registration of brain MRIs, the performance of the block …


Sensor Selection And Integration To Improve Video Segmentation In Complex Environments, Adam R. Reckley, Wei-Wen Hsu, Chung-Hao Chen, Gangfeng Ma, E-Wen Huang Jan 2014

Sensor Selection And Integration To Improve Video Segmentation In Complex Environments, Adam R. Reckley, Wei-Wen Hsu, Chung-Hao Chen, Gangfeng Ma, E-Wen Huang

Electrical & Computer Engineering Faculty Publications

Background subtraction is often considered to be a required stage of any video surveillance system being used to detect objects in a single frame and/or track objects across multiple frames in a video sequence. Most current state-of-the-art techniques for object detection and tracking utilize some form of background subtraction that involves developing a model of the background at a pixel, region, or frame level and designating any elements that deviate from the background model as foreground. However, most existing approaches are capable of segmenting a number of distinct components but unable to distinguish between the desired object of interest and …


Nursing Pain Assessment & Management: A 3d Interactive Simulation, Enilda Romero-Hall, Ginger S. Watson, Yiannis Papelis, Hector Garcia Jan 2014

Nursing Pain Assessment & Management: A 3d Interactive Simulation, Enilda Romero-Hall, Ginger S. Watson, Yiannis Papelis, Hector Garcia

STEMPS Faculty Publications

In this design case, a team developed a 3D interactive simulation for nursing students and professional nurses to train and practice pain assessment and management procedures. In the simulation environment, the trainees interact with three emotionally expressive animated patients. The three patients vary in their ethnicity, age, and emotion intensity. Successful completion of the scenario requires that the trainee perform of a series of pain assessment and management tasks. The trainee is evaluated on the efficiency and appropriate sequencing of the tasks.

The purpose of this paper is to describe the decisions made regarding the type of virtual patients used, …


Do Groups Matter? An Agent-Based Modeling Approach To Pedestrian Egress, Andrew Collins, Terra Elzie, Erika Frydenlund, R. Michael Robinson Jan 2014

Do Groups Matter? An Agent-Based Modeling Approach To Pedestrian Egress, Andrew Collins, Terra Elzie, Erika Frydenlund, R. Michael Robinson

VMASC Publications

Festivals in city parks attended by individuals and families are a universal feature of urban life. These venues often have the common attributes of vendors and other obstacles that restrict pedestrian movement through certain areas, as well as fixed number of exits. In this study, the authors build an agent-based model (ABM) that incorporates group cohesion forces into this type of pedestrian egress scenario. The scenario considered was an evacuation of 500 people through a single exit. This allowed an investigation into the use of two different simulated pedestrian's heading updating rules.


Measuring Sense Of Presence And User Characteristics To Predict Effective Training In An Online Simulated Virtual Environment, Gianluca De Leo, Leigh A. Diggs, Elena Radici, Thomas W. Mastaglio Jan 2014

Measuring Sense Of Presence And User Characteristics To Predict Effective Training In An Online Simulated Virtual Environment, Gianluca De Leo, Leigh A. Diggs, Elena Radici, Thomas W. Mastaglio

VMASC Publications

Introduction: Virtual-reality solutions have successfully been used to train distributed teams. This study aimed to investigate the correlation between user characteristics and sense of presence in an online virtual-reality environment where distributed teams are trained. A greater sense of presence has the potential to make training in the virtual environment more effective, leading to the formation of teams that perform better in a real environment. Being able to identify, before starting online training, those user characteristics that are predictors of a greater sense of presence can lead to the selection of trainees who would benefit most from the online simulated …


Lattice-Boltzmann Simulations Of The Thermally Driven 2d Square Cavity At High Rayleigh Numbers, Dario Contrino, Pierre Lallemand, Pietro Asinari, Li-Shi Luo Jan 2014

Lattice-Boltzmann Simulations Of The Thermally Driven 2d Square Cavity At High Rayleigh Numbers, Dario Contrino, Pierre Lallemand, Pietro Asinari, Li-Shi Luo

Mathematics & Statistics Faculty Publications

The thermal lattice Boltzmann equation (TLBE) with multiple-relaxation-times (MRT) collision model is used to simulate the steady thermal convective flows in the two-dimensional square cavity with differentially heated vertical walls at high Rayleigh numbers. The MRT-TLBE consists of two sets of distribution functions, i.e., a D2Q9 model for the mass-momentum equations and a D2Q5 model for the temperature equation. The dimensionless flow parameters are the following: the Prandtl number Pr = 0.71 and the Rayleigh number Ra = 106, 107, and 108. The D2Q9 + D2Q5 MRT-TLBE is shown to be second-order accurate and …


Simultaneous Optimization Of The Cavity Heat Load And Trip Rates In Linacs Using A Genetic Algorithm, Balša Terzić, Alicia S. Hofler, Cody J. Reeves, Sabbir A. Khan, Geoffrey A. Krafft, Jay Benesch, Arne Freyberger, Desh Ranjan Jan 2014

Simultaneous Optimization Of The Cavity Heat Load And Trip Rates In Linacs Using A Genetic Algorithm, Balša Terzić, Alicia S. Hofler, Cody J. Reeves, Sabbir A. Khan, Geoffrey A. Krafft, Jay Benesch, Arne Freyberger, Desh Ranjan

Physics Faculty Publications

In this paper, a genetic algorithm-based optimization is used to simultaneously minimize two competing objectives guiding the operation of the Jefferson Lab's Continuous Electron Beam Accelerator Facility linacs: cavity heat load and radio frequency cavity trip rates. The results represent a significant improvement to the standard linac energy management tool and thereby could lead to a more efficient Continuous Electron Beam Accelerator Facility configuration. This study also serves as a proof of principle of how a genetic algorithm can be used for optimizing other linac-based machines.


Classification With Hidden Markov Model, Badreddine Benyacoub, Souad Elbernoussi, Abdelhak Zoglat, Ismail El Moudden Jan 2014

Classification With Hidden Markov Model, Badreddine Benyacoub, Souad Elbernoussi, Abdelhak Zoglat, Ismail El Moudden

Research and Infrastructure Service Enterprise (RISE) Faculty Publications

Classification and statistical learning by hidden markov model has achieved remarkable progress in the past decade. They have been applied in many areas like speech recognition and handwriting recognition. However, learning by Hidden Markov Model (HMM) is still restricted to supervised problems. In this paper, we propose a new learning method based on HMM techniques estimations, to built a model for classification. The approach consists of evaluation of the probability to belonging in one group, given the observations by a linear classifier. Our developed algorithm is based on discrete states and discrete observations cases of HMM. Experimental results show that …


Intelligent Sensing Based On Low Cost Unmanned Aerial Vehicles (Uav) For Bridge Condition Assessment, Theodore Teates, Austin Boyd, Chung-Hao Chen Jan 2014

Intelligent Sensing Based On Low Cost Unmanned Aerial Vehicles (Uav) For Bridge Condition Assessment, Theodore Teates, Austin Boyd, Chung-Hao Chen

Electrical & Computer Engineering Faculty Publications

The eventual completion of this project envisions the use of an Unmanned Aerial Vehicle (UAV) to inspect bridge infrastructure. This project may also be expanded to encompass general object detection and inspection in order to unburden this technology so that it may reach its fullest potential. The project requires research and development in three distinct areas of image processing, control structures, and integration of systems. Initial undergraduate research sets the base knowledge for the overall project, explores the areas of concentration that are desired to expand upon in the future project, and provides a base UAV model that new researchers …


Template-Based C8-Scorpion: A Protein 8 State Secondary Structure Prediction Method Using Structural Information And Context-Based Features, Ashraf Yaseen, Yaohang Li Jan 2014

Template-Based C8-Scorpion: A Protein 8 State Secondary Structure Prediction Method Using Structural Information And Context-Based Features, Ashraf Yaseen, Yaohang Li

Computer Science Faculty Publications

Background: Secondary structures prediction of proteins is important to many protein structure modeling applications. Correct prediction of secondary structures can significantly reduce the degrees of freedom in protein tertiary structure modeling and therefore reduces the difficulty of obtaining high resolution 3D models.

Methods: In this work, we investigate a template-based approach to enhance 8-state secondary structure prediction accuracy. We construct structural templates from known protein structures with certain sequence similarity. The structural templates are then incorporated as features with sequence and evolutionary information to train two-stage neural networks. In case of structural templates absence, heuristic structural information is incorporated instead. …


Automated Identification Of Cell Type Specific Genes In The Mouse Brain By Image Computing Of Expression Patterns, Rongjian Li, Wenlu Zhang, Shuiwang Ji Jan 2014

Automated Identification Of Cell Type Specific Genes In The Mouse Brain By Image Computing Of Expression Patterns, Rongjian Li, Wenlu Zhang, Shuiwang Ji

Computer Science Faculty Publications

Background: Differential gene expression patterns in cells of the mammalian brain result in the morphological, connectional, and functional diversity of cells. A wide variety of studies have shown that certain genes are expressed only in specific cell-types. Analysis of cell-type-specific gene expression patterns can provide insights into the relationship between genes, connectivity, brain regions, and cell-types. However, automated methods for identifying cell-type-specific genes are lacking to date.

Results: Here, we describe a set of computational methods for identifying cell-type-specific genes in the mouse brain by automated image computing of in situ hybridization (ISH) expression patterns. We applied invariant image feature …


Toward A Real Time Multi-Tissue Adaptive Physics Based Non-Rigid Registration Framework For Brain Tumor Resection, Fotis Drakopoulos, Panagiotis Foteinos, Yixun Liu, Nikos Chrisochoides Jan 2014

Toward A Real Time Multi-Tissue Adaptive Physics Based Non-Rigid Registration Framework For Brain Tumor Resection, Fotis Drakopoulos, Panagiotis Foteinos, Yixun Liu, Nikos Chrisochoides

Computer Science Faculty Publications

This paper presents an adaptive non-rigid registration method for aligning pre-operative MRI with intra-operative MRI (iMRI) to compensate for brain deformation during brain tumor resection. This method extends a successful existing Physics-Based Non-Rigid Registration (PBNRR) technique implemented in ITKv4.5. The new method relies on a parallel adaptive heterogeneous biomechanical Finite Element (FE) model for tissue/tumor removal depicted in the iMRI. In contrast the existing PBNRR in ITK relies on homogeneous static FE model designed for brain shift only (i.e., it is not designed to handle brain tumor resection). As a result, the new method (1) accurately captures the intra-operative deformations …


A Scalable Backward Chaining-Based Reasoner For A Semantic Web, Hui Shi, Kurt Maly, Steven Zeil Jan 2014

A Scalable Backward Chaining-Based Reasoner For A Semantic Web, Hui Shi, Kurt Maly, Steven Zeil

Computer Science Faculty Publications

In this paper we consider knowledge bases that organize information using ontologies. Specifically, we investigate reasoning over a semantic web where the underlying knowledge base covers linked data about science research that are being harvested from the Web and are supplemented and edited by community members. In the semantic web over which we want to reason, frequent changes occur in the underlying knowledge base, and less frequent changes occur in the underlying ontology or the rule set that governs the reasoning. Interposing a backward chaining reasoner between a knowledge base and a query manager yields an architecture that can support …


Automatic Curvilinear Quality Mesh Generation Driven By Smooth Boundary And Guaranteed Fidelity, Jing Xu, Andrey N. Chernikov Jan 2014

Automatic Curvilinear Quality Mesh Generation Driven By Smooth Boundary And Guaranteed Fidelity, Jing Xu, Andrey N. Chernikov

Computer Science Faculty Publications

The development of robust high-order finite element methods requires the construction of valid high-order meshes for complex geometries without user intervention. This paper presents a novel approach for automatically generating a high-order mesh with two main features: first, the boundary of the mesh is globally smooth; second, the mesh boundary satisfies a required fidelity tolerance. Invalid elements are eliminated. Example meshes demonstrate the features of the algorithm.


Gpu Accelerated Long-Term Simulations Of Beam-Beam Effects In Colliders, B. Terzić, V. Morozov, Y. Roblin, F. Lin, H. Zhang, M. Aturban, D. Ranjan, M. Zubair Jan 2014

Gpu Accelerated Long-Term Simulations Of Beam-Beam Effects In Colliders, B. Terzić, V. Morozov, Y. Roblin, F. Lin, H. Zhang, M. Aturban, D. Ranjan, M. Zubair

Computer Science Faculty Publications

We present an update on the development of the new code for long-term simulation of beam-beam effects in particle colliders. The underlying physical model relies on a matrix-based arbitrary-order particle tracking (including a symplectic option) for beam transport and the generalized Bassetti-Erskine approximation for beam-beam interaction. The computations are accelerated through a parallel implementation on a hybrid GPU/CPU platform. With the new code, previously computationally prohibitive long-term simulations become tractable. The new code will be used to model the proposed Medium-energy Electron-Ion Collider (MEIC) at Jefferson Lab.


Tracing Beta Strands Using Strandtwister From Cryo-Em Density Maps At Medium Resolutions, Dong Si, Jing He Jan 2014

Tracing Beta Strands Using Strandtwister From Cryo-Em Density Maps At Medium Resolutions, Dong Si, Jing He

Computer Science Faculty Publications

Major secondary structure elements such as α helices and β sheets can be computationally detected from cryoelectron microscopy (cryo-EM) density maps with medium resolutions of 5–10 A˚ . However, a critical piece of information for modeling atomic structures is missing, because there are no tools to detect β strands from cryo-EM maps at medium resolutions. We propose a method, StrandTwister, to detect the traces of β strands through the analysis of twist, an intrinsic nature of a β sheet. StrandTwister has been tested using 100 β sheets simulated at 10 A˚ resolution and 39 β sheets computationally detected from cryo-EM …