Computational Engineering Commons^™

Numerical Modeling Of Tornado-Like Vortex And Its Interaction With Bluff- Bodies, Zoheb Nasir

Electronic Thesis and Dissertation Repository

The study the flow structure of tornado-like vortices and their impact over engineering structures is important due to the extent of tornado induced fatalities and damages observed each year in North America and around the world. In the present study, a numerical modeling approach inspired by the WindEEE Dome and the modified version of Ward’s Tornado Simulator has been developed. Using a full-scale numerical simulator, tornadoes of different intensities have been simulated for different swirl ratio values to study flow structures in comparison with previous studies. The effect of topographic features on the tornado-like vortex has been investigated for the …

Desarrollo De Una Herramienta Computacional Para Pruebas Visuales De Degeneración Macular Relacionada Con La Edad Dmre, Daniel Julian López Penagos

Ingeniería en Automatización

No abstract provided.

Augmenting Bottom-Up Metamodels With Predicates, Ross J. Gore, Saikou Diallo, Christopher Lynch, Jose Padilla

VMASC Publications

Metamodeling refers to modeling a model. There are two metamodeling approaches for ABMs: (1) top-down and (2) bottom-up. The top down approach enables users to decompose high-level mental models into behaviors and interactions of agents. In contrast, the bottom-up approach constructs a relatively small, simple model that approximates the structure and outcomes of a dataset gathered fromthe runs of an ABM. The bottom-up metamodel makes behavior of the ABM comprehensible and exploratory analyses feasible. Formost users the construction of a bottom-up metamodel entails: (1) creating an experimental design, (2) running the simulation for all cases specified by the design, (3) …

A Multiscale Model For Damage Progression And Detection In Piezo/Pyroelectric Composite Laminates, Yehia Bahei-El-Din, Amany Micheal

Centre for Advanced Materials

Assessment of damage initiation and progression in composite structures reinforced with electrically active filaments is modelled in a multiscale analysis. The analysis developed is a two-tier, interactive analysis, which involves two length scales; macroscopic, and microscopic. The proposed multiscale analysis provides seamless integration of the mechanics at the two length scales, including piezoelectric and pyroelectric coupling effects and damage under overall thermomechanical loads and an electric field applied to electroactive fibers. The macromechanical analysis is performed for multidirectional, fibrous laminates using the lamination theory, including bending, and the micromechanical analysis is performed using a two-phase model and a periodic array …

Detecting Laminate Damage Using Embedded Electrically Active Plies – An Analytical Approach, Amany Micheal, Yehia Bahei-El-Din

Centre for Advanced Materials

Assessment of damage initiation and progression in composite laminates with embedded electrically active plies is modeled. Utilizing electrically active layers embedded in composite laminates as damage sensors is proposed by several researchers and is mainly assessed experimentally. Sensing damage using embedded electrically active plies is generally preferred over the use of surface mounted PZT wafers since the range of the latter is limited to a very narrow area underneath the surface, while multiple damage mechanisms can generally be found in several plies of the laminate. The solution presented invokes two levels of analysis. Firstly, on the laminate level, applied membrane …

Seed Plant Drone For Reforestation, Erico Pinheiro Fortes

The Graduate Review

The desertification issue in the Cape Verde Islands over the past decades has proven to be a very serious problem which concerns the entire archipelago. Erosion, inaccessible land and the lack of field workers is making agricultural production increasingly inefficient. This project seeks to construct a viable and efficient solution to improve the agricultural system and soil erosion issues in the Cape Verde islands. To accomplish this goal, we will build an autonomous flying quadcopter that will mechanically dispense seeds to restore the arid and infertile regions for agriculture.

This project has three deliverables. The first is a custom-built quadcopter …

C.V. - Wojciech Budzianowski, Wojciech M. Budzianowski

Wojciech Budzianowski

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Renewable Energy And Sustainable Development (Resd) Group, Wojciech M. Budzianowski

Wojciech Budzianowski

No abstract provided.

A Comparison On The Classification Of Short-Text Documents Using Latent Dirichlet Allocation And Formal Concept Analysis, Noel Rogers, Luca Longo

Books/Book Chapters

With the increasing amounts of textual data being collected online, automated text classification techniques are becoming increasingly important. However, a lot of this data is in the form of short-text with just a handful of terms per document (e.g. Text messages, tweets or Facebook posts). This data is generally too sparse and noisy to obtain satisfactory classification. Two techniques which aim to alleviate this problem are Latent Dirichlet Allocation (LDA) and Formal Concept Analysis (FCA). Both techniques have been shown to improve the performance of short-text classification by reducing the sparsity of the input data. The relative performance of classifiers …

Blown To Bits Project, David Schmidt

Informatics Open Educational Resources

The book, Blown to Bits, uncovers the many ways that the new digital world has changed and is changing our whole environment. Some changes are incremental but others are more revolutionary. Some of the changes that we welcome are slowly eroding our privacy and are changing the rules of ownership. This book illuminates the complexities of these changes. I have attempted to capture the central points in selected chapters, and in some cases I have added new material or new examples to replace dated material. I picked chapters to summarize that address the following topics (and more). There are many …

A Hybrid Mpi-Openmp Strategy To Speedup The Compression Of Big Next-Generation Sequencing Datasets, Sandino Vargas-Perez, Fahad Saeed

Parallel Computing and Data Science Lab Technical Reports

DNA sequencing has moved into the realm of Big Data due to the rapid development of high-throughput, low cost Next-Generation Sequencing (NGS) technologies. Sequential data compression solutions that once were sufficient to efficiently store and distribute this information are now falling behind. In this paper we introduce phyNGSC, a hybrid MPI-OpenMP strategy to speedup the compression of big NGS data by combining the features of both distributed and shared memory architectures. Our algorithm balances work-load among processes and threads, alleviates memory latency by exploiting locality, and accelerates I/O by reducing excessive read/write operations and inter-node message exchange. To make the …

Gpu-Pcc: A Gpu Based Technique To Compute Pairwise Pearson’S Correlation Coefficients For Big Fmri Data, Taban Eslami, Muaaz Gul Awan, Fahad Saeed

Parallel Computing and Data Science Lab Technical Reports

Functional Magnetic Resonance Imaging (fMRI) is a non-invasive brain imaging technique for studying the brain’s functional activities. Pearson’s Correlation Coefficient is an important measure for capturing dynamic behaviors and functional connectivity between brain components. One bottleneck in computing Correlation Coefficients is the time it takes to process big fMRI data. In this paper, we propose GPU-PCC, a GPU based algorithm based on vector dot product, which is able to compute pairwise Pearson’s Correlation Coefficients while performing computation once for each pair. Our method is able to compute Correlation Coefficients in an ordered fashion without the need to do post-processing reordering …

An Out-Of-Core Gpu Based Dimensionality Reduction Algorithm For Big Mass Spectrometry Data And Its Application In Bottom-Up Proteomics, Muaaz Awan, Fahad Saeed

Parallel Computing and Data Science Lab Technical Reports

Modern high resolution Mass Spectrometry instruments can generate millions of spectra in a single systems biology experiment. Each spectrum consists of thousands of peaks but only a small number of peaks actively contribute to deduction of peptides. Therefore, pre-processing of MS data to detect noisy and non-useful peaks are an active area of research. Most of the sequential noise reducing algorithms are impractical to use as a pre-processing step due to high time-complexity. In this paper, we present a GPU based dimensionality-reduction algorithm, called G-MSR, for MS2 spectra. Our proposed algorithm uses novel data structures which optimize the memory and …

An Empirical Investigation Of Collaborative Web Search Tool On Novice's Query Behavior, Mareh Fakhir Al-Sammarraie

UNF Graduate Theses and Dissertations

In the past decade, research efforts dedicated to studying the process of collaborative web search have been on the rise. Yet, a limited number of studies have examined the impact of collaborative information search processes on novices’ query behaviors. Studying and analyzing factors that influence web search behaviors, specifically users’ patterns of queries when using collaborative search systems can help with making query suggestions for group users. Improvements in user query behaviors and system query suggestions help in reducing search time and increasing query success rates for novices.

This thesis investigates the influence of collaboration between experts and novices as …

Anomaly Detection In Rfid Networks, Alaa Alkadi

UNF Graduate Theses and Dissertations

Available security standards for RFID networks (e.g. ISO/IEC 29167) are designed to secure individual tag-reader sessions and do not protect against active attacks that could also compromise the system as a whole (e.g. tag cloning or replay attacks). Proper traffic characterization models of the communication within an RFID network can lead to better understanding of operation under “normal” system state conditions and can consequently help identify security breaches not addressed by current standards. This study of RFID traffic characterization considers two piecewise-constant data smoothing techniques, namely Bayesian blocks and Knuth’s algorithms, over time-tagged events and compares them in the context …

Multiscale Modeling: Thermal Conductivity Of Graphene/Cycloaliphatic Epoxy Composites, Sorayot Chinkanjanarot

Dissertations, Master's Theses and Master's Reports

The thermal property of epoxy as the binder in the Carbon Fiber (CF) composites, especially thermal conductivity is important to achieve the advance technology and to improve the performance of materials. Multiscale modeling including molecular dynamic (MD) modeling and micromechanical modeling is used to study the properties of neat Cycloaliphatic Epoxies (CE) and Graphene nanoplatelet (GNP)/CE with and without covalent functionalization.

The thermal properties (glass-transition temperature, thermal expansion coefficient, and thermal conductivity) and mechanical properties of CE system are investigated by MD modeling using OPLS-All Atom force field. A unique crosslinking technique is developed to achieve the cured CE models …

Mammogram And Tomosynthesis Classification Using Convolutional Neural Networks, Xiaofei Zhang

Theses and Dissertations--Computer Science

Mammography is the most widely used method of screening for breast cancer. Traditional mammography produces two-dimensional X-ray images, while advanced tomosynthesis mammography produces reconstructed three-dimensional images. Due to high variability in tumor size and shape, and the low signal-to-noise ratio inherent to mammography, manual classification yields a significant number of false positives, thereby contributing to an unnecessarily large number of biopsies performed to reduce the risk of misdiagnosis. Achieving high diagnostic accuracy requires expertise acquired over many years of experience as a radiologist.

The convolutional neural network (CNN) is a popular deep-learning construct used in image classification. The convolutional process …

A Comprehensive Analysis On Eeg Signal Classification Using Advanced Computational Analysis, Kaushik Bhimraj

Electronic Theses and Dissertations

Electroencephalogram (EEG) has been used in a wide array of applications to study mental disorders. Due to its non-invasive and low-cost features, EEG has become a viable instrument in Brain-Computer Interfaces (BCI). These BCI systems integrate user's neural features with robotic machines to perform tasks. However, due to EEG signals being highly dynamic in nature, BCI systems are still unstable and prone to unanticipated noise interference. An important application of this technology is to help facilitate the lives of the tetraplegic through assimilating human brain impulses and converting them into mechanical motion. However, BCI systems are remarkably challenging to implement …

Bruise Detection In Apples Using 3d Infrared Imaging And Machine Learning Technologies, Zilong Hu

Dissertations, Master's Theses and Master's Reports

Bruise detection plays an important role in fruit grading. A bruise detection system capable of finding and removing damaged products on the production lines will distinctly improve the quality of fruits for sale, and consequently improve the fruit economy. This dissertation presents a novel automatic detection system based on surface information obtained from 3D near-infrared imaging technique for bruised apple identification. The proposed 3D bruise detection system is expected to provide better performance in bruise detection than the existing 2D systems.

We first propose a mesh denoising filter to reduce noise effect while preserving the geometric features of the meshes. …

Comparing An Atomic Model Or Structure To A Corresponding Cryo-Electron Microscopy Image At The Central Axis Of A Helix, Stephanie Zeil, Julio Kovacs, Willy Wriggers, Jing He

Computer Science Faculty Publications

Three-dimensional density maps of biological specimens from cryo-electron microscopy (cryo-EM) can be interpreted in the form of atomic models that are modeled into the density, or they can be compared to known atomic structures. When the central axis of a helix is detectable in a cryo-EM density map, it is possible to quantify the agreement between this central axis and a central axis calculated from the atomic model or structure. We propose a novel arc-length association method to compare the two axes reliably. This method was applied to 79 helices in simulated density maps and six case studies using cryo-EM …