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Articles 901 - 930 of 1311
Full-Text Articles in Computational Engineering
A Hybrid Mpi-Openmp Strategy To Speedup The Compression Of Big Next-Generation Sequencing Datasets, Sandino Vargas-Perez, Fahad Saeed
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 …
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
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 …
Gpu-Pcc: A Gpu Based Technique To Compute Pairwise Pearson’S Correlation Coefficients For Big Fmri Data, Taban Eslami, Muaaz Gul Awan, Fahad Saeed
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 …
Convolutional Neural Networks For Predicting Skin Lesions Of Melanoma, Anuruddha Jayasekara Pathiranage
Convolutional Neural Networks For Predicting Skin Lesions Of Melanoma, Anuruddha Jayasekara Pathiranage
Regis University Student Publications (comprehensive collection)
Diagnosis of an unknown skin lesion is crucial to enable proper treatments. While curable with early diagnosis, only highly trained dermatologists are capable of accurately recognize melanoma skin lesions. Expert dermatologist classification for melanoma dermoscopic images is 65-66%. As expertise is in limited supply, systems that can automatically classify skin lesions as either benign or malignant melanoma are very useful as initial screening tools. Towards this goal, this study presents a convolutional neural network model, trained on features extracted from a highway convolutional neural network pretrained on dermoscopic images of skin lesions. This requires no lesion segmentation nor complex preprocessing. …
Seed Plant Drone For Reforestation, Erico Pinheiro Fortes
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 …
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
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 …
Augmenting Bottom-Up Metamodels With Predicates, Ross J. Gore, Saikou Diallo, Christopher Lynch, Jose Padilla
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) …
Generalized Interval Valued Neutrosophic Graphs Of First Type, Florentin Smarandache, Said Broumi, Mohamed Talea, Assia Bakali, Ali Hassan
Generalized Interval Valued Neutrosophic Graphs Of First Type, Florentin Smarandache, Said Broumi, Mohamed Talea, Assia Bakali, Ali Hassan
Branch Mathematics and Statistics Faculty and Staff Publications
In this paper, motivated by the notion of generalized single valued neutrosophic graphs of first type, we defined a new neutrosophic graphs named generalized interval valued neutrosophic graphs of first type (GIVNG1) and presented a matrix representation for it and studied few properties of this new concept. The concept of GIVNG1 is an extension of generalized fuzzy graphs (GFG1) and generalized single valued neutrosophic of first type (GSVNG1).
Mammogram And Tomosynthesis Classification Using Convolutional Neural Networks, Xiaofei Zhang
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 …
Multiscale Modeling: Thermal Conductivity Of Graphene/Cycloaliphatic Epoxy Composites, Sorayot Chinkanjanarot
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 …
A Comparison On The Classification Of Short-Text Documents Using Latent Dirichlet Allocation And Formal Concept Analysis, Noel Rogers, Luca Longo
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
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 …
Anomaly Detection In Rfid Networks, Alaa Alkadi
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 …
A Comprehensive Analysis On Eeg Signal Classification Using Advanced Computational Analysis, Kaushik Bhimraj
A Comprehensive Analysis On Eeg Signal Classification Using Advanced Computational Analysis, Kaushik Bhimraj
College of Graduate Studies: Theses & 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
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. …
An Empirical Investigation Of Collaborative Web Search Tool On Novice's Query Behavior, Mareh Fakhir Al-Sammarraie
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 …
An Operational View In Computational Construction Of Information, Florentin Smarandache, Stefan Vladutescu, Constantin Dima, Valeriu Voinea
An Operational View In Computational Construction Of Information, Florentin Smarandache, Stefan Vladutescu, Constantin Dima, Valeriu Voinea
Branch Mathematics and Statistics Faculty and Staff Publications
The paper aims to explain the technology of emergence of information. Our research proves that information as communicational product is the result of processing within some operations, actions, mechanisms and strategies of informational material meanings. Are determined eight computational-communicative operations of building information. Information occurs in two communication phases, syncretic and the segregation-synthetic. The syncretic phase consists of four operations: referral of significant field, primary delimitation of information, detection-looking information and an anticipative-draft constitution (feedforward). The segregation-synthetic phase also includes four operations: discrimination, identification, interpretation and confrontation (feedback). In the future we will investigate informational actions, mechanisms and strategies.
Leveraging Lexical Link Analysis (Lla) To Discover New Knowledge, Ying Zhao, Douglas J. Mackinnon, Shelley P. Gallup, Joseph L. Billingsley
Leveraging Lexical Link Analysis (Lla) To Discover New Knowledge, Ying Zhao, Douglas J. Mackinnon, Shelley P. Gallup, Joseph L. Billingsley
Military Cyber Affairs
Lexical Link Analysis (LLA) is a form of text mining in which word meanings represented in lexical terms (e.g., word pairs) are treated as if they are in a community of a word network. LLA can provide automated awareness for analyzing text data and reveal previously unknown, data-driven themed connections. We applied LLA to develop authentic archetypes and conversely determine potential imposters of that same archetype. We use publically available social media data to develop a cyber professional as an example. This paper reports the development of the algorithm, the collection and labeling of data, as well as the results …
Computational Fluid Dynamics Is Key To Better Flying Aircraft, Nihad E. Daidzic
Computational Fluid Dynamics Is Key To Better Flying Aircraft, Nihad E. Daidzic
Aviation Department Publications
No abstract provided.
Teaching The Internet Of Things: Bridging A Path From Cpe329, Steven Han, Rafael Lopez
Teaching The Internet Of Things: Bridging A Path From Cpe329, Steven Han, Rafael Lopez
Computer Engineering
“The ability to connect, communicate with, and remotely manage an incalculable number of networked, automated devices via the Internet is becoming pervasive, from the commercial kitchen to the residential basement room to the arm of the fitness buff.” - WSO2
In this report, we will investigate procedures and technologies used in IoT. A variety of cloud platforms will be described to demonstrate its strengths and usage on IoT applications. Furthermore, demonstrate the most popular hardware being used in several of these applications. This report is aimed to give a good understanding on what it takes to put together an IoT …
Characterization Of Molecular Communication Based On Cell Metabolism Through Mutual Information And Flux Balance Analysis, Zahmeeth Sayed Sakkaff
Characterization Of Molecular Communication Based On Cell Metabolism Through Mutual Information And Flux Balance Analysis, Zahmeeth Sayed Sakkaff
School of Computing: Dissertations, Theses, and Student Research
Synthetic biology is providing novel tools to engineer cells and access the basis of their molecular information processing, including their communication channels based on chemical reactions and molecule exchange. Molecular communication is a discipline in communication engineering that studies these types of communications and ways to exploit them for novel purposes, such as the development of ubiquitous and heterogeneous communication networks to interconnect biological cells with nano and biotechnology-enabled devices, i.e., the Internet of Bio-Nano Things. One major problem in realizing these goals stands in the development of reliable techniques to control the engineered cells and their behavior from the …
Coupled Fluid-Structure Interaction Modeling Of A Parafoil, Brandon Burnett
Coupled Fluid-Structure Interaction Modeling Of A Parafoil, Brandon Burnett
Doctoral Dissertations and Master's Theses
In the summer of 2014, Performance Designs, Inc. contacted Embry-Riddle Aeronautical University’s Eagle Flight Research Center to lead an investigation on square parachute design and optimization using modern computational methods to reduce costs in experimental testing. This thesis investigates the foundation for using an implicit fluid-structure interaction computational model to tackle the challenges of modeling a highly-flexible, porous fabric for design optimization of a parafoil parachute’s transient performance. Canopy deformations of a single-cell square parafoil using a fluid-structure interaction (FSI) model with nonlinear material modeling is compared to an experimental setup of matching geometry. The results of this thesis yielded …
Automatic Segmentation Of Coronal Holes In Solar Images And Solar Prediction Map Classification, Venkatesh Jatla
Automatic Segmentation Of Coronal Holes In Solar Images And Solar Prediction Map Classification, Venkatesh Jatla
Electrical and Computer Engineering ETDs
Solar image analysis relies on the detection of coronal holes for predicting disruptions to earth’s magnetic field. The coronal holes act as sources of solar wind that can reach the earth. Thus, coronal holes are used in physical models for predicting the evolution of solar wind and its potential for interfering with the earth’s magnetic field. Due to inherent uncertainties in the physical models, there is a need for a classification system that can be used to select the physical models that best match the observed coronal holes. The physical model classification problem is decomposed into three subproblems. First, the …
Finite Element Simulation Of Pzt-Aided Interrogation Of Composite Laminates Exhibiting Damage, Amany Micheal, Yehia Bahei-El-Din
Finite Element Simulation Of Pzt-Aided Interrogation Of Composite Laminates Exhibiting Damage, Amany Micheal, Yehia Bahei-El-Din
Centre for Advanced Materials
Piezoelectricity has proved effective in capturing changes in structures caused by various damage mechanisms. In one approach, piezoelectric wafer active sensors (PWAS) are mounted on the surface of the host structure and utilized as both actuators and sensors to interrogate the structure and monitor its health. This is achieved by subjecting the PWAS to a transient electric pulse and reading the resulting voltage. Changes in the stiffness of the substrate due to structural damage affect the response of the PWAS, which could be correlated to integrity of the structure. Applying this technique to fibrous composite laminates encounters particular challenges due …
Fractal Analysis Of Dna Sequences, Christian G. Arias, Pedro Antonio Moreno Phd, Carlos Tellez
Fractal Analysis Of Dna Sequences, Christian G. Arias, Pedro Antonio Moreno Phd, Carlos Tellez
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
The Wotan Beowulf Cluster Project, Carson Wang, Krist Pregracke
The Wotan Beowulf Cluster Project, Carson Wang, Krist Pregracke
ASA Multidisciplinary Research Symposium
The Wotan project moves into its second year in which high school students, in liaison with SIU, have implemented Hadoop and various experiments. Insight on the challenges and requirements of current practices in Big Data analysis will be presented.
A Cellular Automation Which Incorporates Finite Element Method And Meshless Algorithm, Yong Cai, Zeyun Chen, Weifeng Yuan
A Cellular Automation Which Incorporates Finite Element Method And Meshless Algorithm, Yong Cai, Zeyun Chen, Weifeng Yuan
The 8th International Conference on Physical and Numerical Simulation of Materials Processing
No abstract provided.
Numerical Modeling And Seismic Assessment Of Smart Isolation System For High-Speed Railway Rc Bridge Subjected To Near-Field Ground Motions, Lingkun Chen
The 8th International Conference on Physical and Numerical Simulation of Materials Processing
No abstract provided.
Application Of Numerical Simulation During The Development Of Ductile Iron Bearing Seat, Ping Li, Yanjie Zhao, Junquan Wei, Jitai Niu, Fengju Li
Application Of Numerical Simulation During The Development Of Ductile Iron Bearing Seat, Ping Li, Yanjie Zhao, Junquan Wei, Jitai Niu, Fengju Li
The 8th International Conference on Physical and Numerical Simulation of Materials Processing
No abstract provided.
Mhd Modeling Of A Copper Slag Cleaning Process, Hongkun Yang, Jörg Wolters, Helmut Soltner, Phillip Pischke, Sven Eckert, Jochen Fröhlich
Mhd Modeling Of A Copper Slag Cleaning Process, Hongkun Yang, Jörg Wolters, Helmut Soltner, Phillip Pischke, Sven Eckert, Jochen Fröhlich
The 8th International Conference on Physical and Numerical Simulation of Materials Processing
No abstract provided.