Physical Sciences and Mathematics Commons^™

The Use Of Visual-Based Simulated Environments In Teacher Preparation, Sharon Judge, Jonna Bobzien, Ann Maydosz, Sabra Gear, Petros Katsioloudis

Communication Disorders & Special Education Faculty Publications

While virtual technology for training in the simulation field has a long history in medicine, aviation, and the military, the application of similar emerging and innovative technologies in teacher preparation and education has been limited. TLE TeachLive™ (Teaching Learning Environment, Teaching in a Virtual Environment) [TLE] is an inventive mixed-reality environment (the blending of real and synthetic content) where prospective teachers can interact with a group of virtual students. The purpose of the virtual teaching environment of TLE is to strengthen teacher recruitment, preparation, and retention in education by allowing teachers to improve their skills with virtual students, providing a …

Special Issue: M&S Optimization Applications In Industry And Engineering, Part 2, Rafael Diaz, Andreas Tolk

VMASC Publications

(First paragraph) Welcome to the second part of the special issue on modeling and simulation (M&S) optimization applications in industry and engineering. This issue incorporates additional publications that reflect various applications and areas of simulation and optimization.

Special Issue On Medical Simulation, Michel Audette, Hanif M. Ladak

Computational Modeling & Simulation Engineering Faculty Publications

We would like to welcome you to this Special Issue on Medical Simulation, the first of its kind not only for SIMULATION: Transactions of The Society for Modeling and Simulation International, but for any technical journal. Our respective backgrounds are an indication of the technical and clinical breadth of medical simulation, as we approach the subject as primarily medical image analysis and biomechanics experts respectively, each with a variety of clinical interests spanning virtual reality (VR)–based neuro-, orthopedic and ear-nose-and-throat surgery. Moreover, we believe that the breadth of the papers that comprise this issue reflects an even broader perspective. After …

Using Architecture Models To Design Adaptive Socio-Technical Systems, Holly A. H. Handley

Engineering Management & Systems Engineering Faculty Publications

An architecture framework is used to capture the overall design and structure of a complex system. The Human Viewpoint was developed to augment existing architectural frameworks with additional information relevant to the human component in the system. The Human View models collect and organize social parameters in order to understand the way that humans interact with other elements of the system; the Human View models define the socio-technological boundaries of the system. Analyses performed with the architectural data provide information regarding the congruence, or fit of the human and the system. For example, different key thread analyses identify problematic paths …

The Root Cause Of Failure In Complex It Projects: Complexity Itself, Kaitlynn M. Whitney, Charles B. Daniels

Engineering Management & Systems Engineering Faculty Publications

Increased demand for better technology and perpetual global expansion continue to provide developers with many project opportunities for success, as well as failure. While no industry is immune from project failure, the Information Technology (IT) industry is shown to be more susceptible to risk and failure than those of other industries. Agile project management, which facilitates adaptation to changing circumstances and alleviates rigid formal controls, has become more popular in the software development industry though is not entirely compatible with traditional project management approaches.In this paper we will examine the primary causes of IT project management failure stated in modern …

Orientation Invariant Ecg-Based Stethoscope Tracking For Heart Auscultation Training On Augmented Standardized Patients, Nahom Kidane, Salim Chemlal, Jiang Li, Frederic D. Mckenzie, Tom Hubbard

Computational Modeling & Simulation Engineering Faculty Publications

Auscultation, the act of listening to the heart and lung sounds, can reveal substantial information about patients’ health and other cardiac-related problems; therefore, competent training can be a key for accurate and reliable diagnosis. Standardized patients (SPs), who are healthy individuals trained to portray real patients, have been extensively used for such training and other medical teaching techniques; however, the range of symptoms and conditions they can simulate remains limited since they are only patient actors. In this work, we describe a novel tracking method for placing virtual symptoms in correct auscultation areas based on recorded ECG signals with various …

Lattice Boltzmann Simulations Of Thermal Convective Flows In Two Dimensions, Jia Wang, Donghai Wang, Pierre Lallemand, Li-Shi Luo

Mathematics & Statistics Faculty Publications

In this paper we study the lattice Boltzmann equation (LBE) with multiple-relaxation-time (MRT) collision model for incompressible thermo-hydrodynamics with the Boussinesq approximation. We use the MRT thermal LBE (TLBE) to simulate the following two flows in two dimensions: the square cavity with differentially heated vertical walls and the Rayleigh-Benard convection in a rectangle heated from below. For the square cavity, the flow parameters in this study are the Rayleigh number Ra = 10³-10⁶, and the Prandtl number Pr = 0.71; and for the Rayleigh-Benard convection in a rectangle, Ra = 2 ^. 10³, 10 …

Hyperspectral Image Classification Using A Spectral-Spatial Sparse Coding Model, Ender Oguslu, Guoqing Zhou, Jiang Li, Lorenzo Bruzzone (Ed.)

Electrical & Computer Engineering Faculty Publications

We present a sparse coding based spectral-spatial classification model for hyperspectral image (HSI) datasets. The proposed method consists of an efficient sparse coding method in which the l₁/l_q regularized multi-class logistic regression technique was utilized to achieve a compact representation of hyperspectral image pixels for land cover classification. We applied the proposed algorithm to a HSI dataset collected at the Kennedy Space Center and compared our algorithm to a recently proposed method, Gaussian process maximum likelihood (GP-ML) classifier. Experimental results show that the proposed method can achieve significantly better performances than the GP-ML classifier when training data …

A Method For Identifying Personalized Representations In Web Archives, Mat Kelly, Justin F. Brunelle, Michele C. Weigle, Michael L. Nelson

Computer Science Faculty Publications

Web resources are becoming increasingly personalized — two different users clicking on the same link at the same time can see content customized for each individual user. These changes result in multiple representations of a resource that cannot be canonicalized in Web archives. We identify characteristics of this problem by presenting a potential solution to generalize personalized representations in archives. We also present our proof-of-concept prototype that analyzes WARC (Web ARChive) format files, inserts metadata establishing relationships, and provides archive users the ability to navigate on the additional dimension of environment variables in a modified Wayback Machine.

Employing Learning To Improve The Performance Of Meta-Raps, Fatemah Al-Duoli, Ghaith Rabadi

Engineering Management & Systems Engineering Faculty Publications

In their search for satisfactory solutions to complex combinatorial problems, metaheuristics methods are expected to intelligently explore the solution space. Various forms of memory have been used to achieve this goal and improve the performance of metaheuristics, which warranted the development of the Adaptive Memory Programming (AMP) framework [1]. This paper follows this framework by integrating Machine Learning (ML) concepts into metaheuristics as a way to guide metaheuristics while searching for solutions. The target metaheuristic method is Meta-heuristic for Randomized Priority Search (Meta-RaPS). Similar to most metaheuristics, Meta-RaPS consists of construction and improvement phases. Randomness coupled with a greedy heuristic …

Security Risks And Protection In Online Learning: A Survey, Yong Chen, Wu He

Distance Learning Faculty & Staff Publications

This paper describes a survey of online learning which attempts to determine online learning providers' awareness of potential security risks and the protection measures that will diminish them. The authors use a combination of two methods: blog mining and a traditional literature search. The findings indicate that, while scholars have identified diverse security risks and have proposed solutions to mitigate the security threats in online learning, bloggers have not discussed security in online learning with great frequency. The differences shown in the survey results generated by the two different methods confirm that online learning providers and practitioners have not considered …

A Technical Framework For Resource Synchronization, Martin Klein, Robert Sanderson, Herbert Van De Sompel, Simeon Warner, Bernhard Haslhofer, Carl Lagoze, Michael L. Nelson

Computer Science Faculty Publications

This is the second paper in D-Lib Magazine about the ResourceSync effort conducted by the National Information Standards Organization (NISO) and the Open Archives Initiative (OAI). The first part provided a perspective on the resource synchronization problem and introduced a template that organized possible components of a resource synchronization framework in a modular manner. This paper details a technical framework devised using that template.

Intensity-Based Skeletonization Of Cryoem Gray-Scale Images Using A True Segmentation-Free Algorithm, Kamal Al Nasr, Chunmei Liu, Mugizi Rwebangira, Legand Burge, Jing He

Computer Science Faculty Publications

Cryo-electron microscopy is an experimental technique that is able to produce 3D gray-scale images of protein molecules. In contrast to other experimental techniques, cryo-electron microscopy is capable of visualizing large molecular complexes such as viruses and ribosomes. At medium resolution, the positions of the atoms are not visible and the process cannot proceed. The medium-resolution images produced by cryo-electron microscopy are used to derive the atomic structure of the proteins in de novo modeling. The skeletons of the 3D gray-scale images are used to interpret important information that is helpful in de novo modeling. Unfortunately, not all features of the …

The 6th Computational Structural Bioinformatics Workshop Introduction, Jing He, Amarda Shehu, Nurit Haspel, Brian Chen

Computer Science Faculty Publications

No abstract provided.

Image-Level And Group-Level Models For Drosophila Gene Expression Pattern Annotation, Quian Sun, Sherin Muckatira, Lei Yuan, Shuiwang Ji, Stuart Newfeld, Sudhir Kumar, Jieping Ye

Computer Science Faculty Publications

Background: Drosophila melanogaster has been established as a model organism for investigating the developmental gene interactions. The spatio-temporal gene expression patterns of Drosophila melanogaster can be visualized by in situ hybridization and documented as digital images. Automated and efficient tools for analyzing these expression images will provide biological insights into the gene functions, interactions, and networks. To facilitate pattern recognition and comparison, many web-based resources have been created to conduct comparative analysis based on the body part keywords and the associated images. With the fast accumulation of images from high-throughput techniques, manual inspection of images will impose a serious impediment …

Estimating Loop Length From Cryoem Images At Medium Resolutions, Andrew Mcknight, Dong Si, Kamal Al Nasr, Andrey Chemikov, Nikos Chrisochoides, Jing He

Computer Science Faculty Publications

Background: De novo protein modeling approaches utilize 3-dimensional (3D) images derived from electron cryomicroscopy (CryoEM) experiments. The skeleton connecting two secondary structures such as α-helices represent the loop in the 3D image. The accuracy of the skeleton and of the detected secondary structures are critical in De novo modeling. It is important to measure the length along the skeleton accurately since the length can be used as a constraint in modeling the protein.

Results: We have developed a novel computational geometric approach to derive a simplified curve in order to estimate the loop length along the skeleton. The method was …

Computational Genetic Neuroanatomy Of The Developing Mouse Brain: Dimensionality Reduction, Visualization, And Clustering, Shuiwang Ji

Computer Science Faculty Publications

Background: The structured organization of cells in the brain plays a key role in its functional efficiency. This delicate organization is the consequence of unique molecular identity of each cell gradually established by precise spatiotemporal gene expression control during development. Currently, studies on the molecular-structural association are beginning to reveal how the spatiotemporal gene expression patterns are related to cellular differentiation and structural development.

Results: In this article, we aim at a global, data-driven study of the relationship between gene expressions and neuroanatomy in the developing mouse brain. To enable visual explorations of the high-dimensional data, we map the in …

Dinosolve: A Protein Disulfide Bonding Prediction Server Using Context-Based Features To Enhance Prediction Accuracy, Ashraf Yaseen, Yaohang Li

Computer Science Faculty Publications

Background: Disulfide bonds play an important role in protein folding and structure stability. Accurately predicting disulfide bonds from protein sequences is important for modeling the structural and functional characteristics of many proteins.

Methods: In this work, we introduce an approach of enhancing disulfide bonding prediction accuracy by taking advantage of context-based features. We firstly derive the first-order and second-order mean-force potentials according to the amino acid environment around the cysteine residues from large number of cysteine samples. The mean-force potentials are integrated as context-based scores to estimate the favorability of a cysteine residue in disulfide bonding state as well as …

A Mesh Generation And Machine Learning Framework For Drosophila Gene Expression Pattern Image Analysis, Wenlu Zhang, Daming Feng, Rongjian Li, Andrey Chernikov, Nikos Chrisochoides, Christopher Osgood, Charlotte Konikoff, Stuart Newfeld, Sudhir Kumar, Shuiwang Ji

Computer Science Faculty Publications

Background: Multicellular organisms consist of cells of many different types that are established during development. Each type of cell is characterized by the unique combination of expressed gene products as a result of spatiotemporal gene regulation. Currently, a fundamental challenge in regulatory biology is to elucidate the gene expression controls that generate the complex body plans during development. Recent advances in high-throughput biotechnologies have generated spatiotemporal expression patterns for thousands of genes in the model organism fruit fly Drosophila melanogaster. Existing qualitative methods enhanced by a quantitative analysis based on computational tools we present in this paper would provide …

Convergence Analysis Of Markov Chain Monte Carlo Linear Solvers Using Ulam--Von Neumann Algorithm, Hao Ji, Michael Mascagni, Yaohang Li

Computer Science Faculty Publications

The convergence of Markov chain--based Monte Carlo linear solvers using the Ulam--von Neumann algorithm for a linear system of the form x = Hx + b is investigated in this paper. We analyze the convergence of the Monte Carlo solver based on the original Ulam--von Neumann algorithm under the conditions that ||H|| < 1 as well as ρ(H) < 1, where ρ(H) is the spectral radius of H. We find that although the Monte Carlo solver is based on sampling the Neumann series, the convergence of Neumann series is not a sufficient condition for the convergence of the Monte Carlo solver. Actually, properties of H are not the only factors determining the convergence of the Monte Carlo solver; the underlying transition probability matrix plays an important role. An improper selection of the transition matrix may result in divergence even though the condition ||H|| <1 holds. However, if the condition ||H|| < 1 is satisfied, we show that there always exist certain transition matrices that guarantee convergence of the Monte Carlo solver. On the other hand, if ρ(H) <1 but ||H|| ≥ 1, the Monte Carlo linear solver may or may not converge. In particular, if the row sum ∑ n/j= 1|H_ij > 1 for every row in H or, more generally, ρ(H⁺) >1, where H⁺ is the nonnegative matrix where H+_ij = |H_ij|, we show that transition matrices leading to convergence of the Monte Carlo solver do not exist. Finally, given …

Conformational Sampling In Template Free Protein Loop Structure Modeling: An Overview, Yaohang Li

Computer Science Faculty Publications

Accurately modeling protein loops is an important step to predict three-dimensional structures as well as to understand functions of many proteins. Because of their high flexibility, modeling the three-dimensional structures of loops is difficult and is usually treated as a "mini protein folding problem" under geometric constraints. In the past decade, there has been remarkable progress in template-free loop structure modeling due to advances of computational methods as well as stably increasing number of known structures available in PDB. This mini review provides an overview on the recent computational approaches for loop structure modeling. In particular, we focus on the …

Gpu-Optimized Code For Long-Term Simulations Of Beam-Beam Effects In Colliders, Y. Roblin, V. Morozov, B. Terzić, M. Aturban, D. Ranjan, M. Zubair

Computer Science Faculty Publications

We report 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 symplectic particle tracking for beam transport and the 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, a previously computationally prohibitive long-term simulations become tractable. We use the new code to model the proposed medium-energy electron-ion collider (MEIC) at Jefferson Lab.

Warcreate And Wail: Warc, Wayback, And Heritrix Made Easy, Mat Kelly, Michael L. Nelson, Michele C. Weigle

Computer Science Faculty Publications

[First slide]

The Problem

Institutional Tools, Personal Archivists

• ON YOUR MACHINE

-Complex to Operate

-Require Infrastructure

• DELEGATED TO INSTITUTIONS

-$$$

-Lose original perspective

• Locale content tailoring (DC vs. San Francisco)
• Observation Medium (PC web browser vs. Crawler)

Integration Of Multispectral Face Recognition And Multi-Ptz Camera Automated Surveillance For Security Applications, Chung-Hao Chen, Yi Yao, Hong Chang, Andreas Koschan, Mongi Abidi

Electrical & Computer Engineering Faculty Publications

Due to increasing security concerns, a complete security system should consist of two major components, a computer-based face-recognition system and a real-time automated video surveillance system. A computer-based face-recognition system can be used in gate access control for identity authentication. In recent studies, multispectral imaging and fusion of multispectral narrow-band images in the visible spectrum have been employed and proven to enhance the recognition performance over conventional broad-band images, especially when the illumination changes. Thus, we present an automated method that specifies the optimal spectral ranges under the given illumination. Experimental results verify the consistent performance of our algorithm via …