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Computational Engineering Commons

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2018

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Articles 1 - 30 of 89

Full-Text Articles in Computational Engineering

Elevated Temperature Progressive Damage And Failure Of Duplex Stainless Steel, Darren P. Luke Dec 2018

Elevated Temperature Progressive Damage And Failure Of Duplex Stainless Steel, Darren P. Luke

Civil Engineering ETDs

Ductile failure of metals has been the focus of research efforts within academia and industry for many years since it is tremendously important for understanding the failure of structures under extreme loading conditions. However, limited research has been dedicated to elevated temperature ductile failure, which is critical for evaluating catastrophic events such as industrial, structural or shipping vessel fires. A detailed investigation was conducted on the structural response of Duplex Stainless Steel at elevated temperatures. The temperature dependence of elastic modulus, yield strength, ultimate strength, and ductility was measured up to 1000°C and a continuum damage plasticity model was ...


Secured Data Masking Framework And Technique For Preserving Privacy In A Business Intelligence Analytics Platform, Osama Ali Dec 2018

Secured Data Masking Framework And Technique For Preserving Privacy In A Business Intelligence Analytics Platform, Osama Ali

Electronic Thesis and Dissertation Repository

The main concept behind business intelligence (BI) is how to use integrated data across different business systems within an enterprise to make strategic decisions. It is difficult to map internal and external BI’s users to subsets of the enterprise’s data warehouse (DW), resulting that protecting the privacy of this data while maintaining its utility is a challenging task. Today, such DW systems constitute one of the most serious privacy breach threats that an enterprise might face when many internal users of different security levels have access to BI components. This thesis proposes a data masking framework (iMaskU: Identify ...


Variable Input Observer For Nonstationary High-Rate Dynamic Systems, Jonathan Hong, Simon Laflamme, Liang Cao, Jacob Dodson, Bryan Joyce Dec 2018

Variable Input Observer For Nonstationary High-Rate Dynamic Systems, Jonathan Hong, Simon Laflamme, Liang Cao, Jacob Dodson, Bryan Joyce

Civil, Construction and Environmental Engineering Publications

Engineering systems experiencing events of amplitudes higher than 100 gn for a duration under 100 ms, here termed high-rate dynamics, can undergo rapid damaging effects. If the structural health of such systems could be accurately estimated in a timely manner, preventative measures could be employed to minimize adverse effects. For complex high-rate problems, adaptive observers have shown promise due to their capability to deal with nonstationary, noisy, and uncertain systems. However, adaptive observers have slow convergence rates, which impede their applicability to the high-rate problems. To improve on the convergence rate, we propose a variable input space concept for ...


A Computational Analysis Of The Gradient Concentration Profile Of Deet And The Mosquito Behavioral Response, Brandon Carver Dec 2018

A Computational Analysis Of The Gradient Concentration Profile Of Deet And The Mosquito Behavioral Response, Brandon Carver

Master's Theses

DEET is a common active ingredient in most spatial repellents. DEET is also a volatile organic compound. DEET prevents mosquitoes from detecting and coming into contact with an human individual. Gas sensing technologies such as metal oxide semiconductor sensors can detect VOCs. The World Health Organization provides the majority of efficacy testing methods. This research adapts methods from the WHO and use of MOS sensors to further understand how and why DEET affects mosquitos. A custom developed system is used to measure DEET dissipation and observe mosquito behavioral response to the DEET. DEET dissipations and mosquito behavior is measured within ...


Blokus Game Solver, Chin Chao Dec 2018

Blokus Game Solver, Chin Chao

Computer Engineering

Blokus (officially pronounced as “Block us”) is an abstract strategy board game with transparent Tetris-shaped, color pieces that players are trying to place onto the board. However, the players can only place a piece that touches at least one corner of their own pieces on the board. The ultimate goal of the game is to place as many pieces onto the board as a player can while blocking off the opponent’s ability to place more pieces onto the board. Each player has pieces with different shapes and sizes that can be placed onto the board, where each block within ...


Landmine Detection Using Semi-Supervised Learning., Graham Reid Dec 2018

Landmine Detection Using Semi-Supervised Learning., Graham Reid

Electronic Theses and Dissertations

Landmine detection is imperative for the preservation of both military and civilian lives. While landmines are easy to place, they are relatively difficult to remove. The classic method of detecting landmines was by using metal-detectors. However, many present-day landmines are composed of little to no metal, necessitating the use of additional technologies. One of the most successful and widely employed technologies is Ground Penetrating Radar (GPR). In order to maximize efficiency of GPR-based landmine detection and minimize wasted effort caused by false alarms, intelligent detection methods such as machine learning are used. Many sophisticated algorithms are developed and employed to ...


A Scalable, Chunk-Based Slicer For Cooperative 3d Printing, Jace J. Mcpherson Dec 2018

A Scalable, Chunk-Based Slicer For Cooperative 3d Printing, Jace J. Mcpherson

Computer Science and Computer Engineering Undergraduate Honors Theses

Cooperative 3D printing is an emerging technology that aims to increase the 3D printing speed and to overcome the size limit of the printable object by having multiple mobile 3D printers (printhead-carrying mobile robots) work together on a single print job on a factory floor. It differs from traditional layer-by-layer 3D printing due to requiring multiple mobile printers to work simultaneously without interfering with each other. Therefore, a new approach for slicing a digital model and generating commands for the mobile printers is needed, which has not been discussed in literature before. We propose a chunk-by-chunk based slicer that divides ...


Fingerprint Database Privacy Guard: An Open-Source System That Secures Fingerprints With Locality Sensitive Hashing Algorithms, Enrique Sanchez Dec 2018

Fingerprint Database Privacy Guard: An Open-Source System That Secures Fingerprints With Locality Sensitive Hashing Algorithms, Enrique Sanchez

Computer Science and Computer Engineering Undergraduate Honors Theses

Fingerprint identification is one of the most accurate sources of identification, yet it is not widely used in public facilities for security concerns. Moreover, the cost of fingerprint system is inaccessible for small-budget business because of their high cost. Therefore, this study created an open-source solution to secure fingerprint samples in the database while using low-cost hardware components. Locality Sensitive Hashing Algorithms such as ORB and Image hash were compared in this study as a potential alternative to SURF. To test the design, fifteen samples were collected and stored in a database without verifying the quality of the samples. Then ...


A Validation Study Of Time Series Data Forecasting Using Neural Networks, Marco Martinez, Jeremy Evert Nov 2018

A Validation Study Of Time Series Data Forecasting Using Neural Networks, Marco Martinez, Jeremy Evert

Student Research

Artificial Intelligence(AI) is a growing topic in Computer Science and has many uses in real world applications. One application is using Al, or more specifically Neural Networks to model data and predict outcomes. Neural Networks have been used in the past to predict weather changes, create facial recognition software , and to create self-driving cars. Our project is a validation study of, “Modeling Time Series Data With Deep Fourier Neural Networks” by Gashler and Ashmore, 2016. Here we show that a neural network can be trained to be an effective predictor of weather patterns in Alaska over several years. Our ...


Toward Building Resilient, Sustainable, And Smart Infrastructure In The 21st Century, Aly Mousaad Aly Nov 2018

Toward Building Resilient, Sustainable, And Smart Infrastructure In The 21st Century, Aly Mousaad Aly

Faculty Publications

In recent years, as a result of significant climate change, stringent windstorms are becoming more frequent than before. Given the threat that windstorms bring to people and property, wind/structural engineering research is imperative to improve the resilience of existing and new infrastructure, for community safety and assets protection. The Windstorm Impact, Science and Engineering (WISE) research program at Louisiana State University (LSU) focuses on creating new knowledge applicable to the mitigation of existing and new infrastructure, to survive and perform optimally under natural hazards. To achieve our research goals, we address two imperious challenges: (i) characterization of realistic wind ...


Dynamic Fracture Of Pmma, Intefacial Failure, And Local Heating, Javad Mehrmashhadi, Longzhen Wang, Florin Bobaru Ph.D. Nov 2018

Dynamic Fracture Of Pmma, Intefacial Failure, And Local Heating, Javad Mehrmashhadi, Longzhen Wang, Florin Bobaru Ph.D.

Javad Mehrmashhadi

Recent impact experiments showed the influence of a strong or weak interface in a bi-layered PMMA material has on dynamic fracture mechanisms. We show that a linear elastic with brittle damage peridynamic model, which works very well for glass, leads to crack propagation speeds significantly faster than those measured experimentally in the PMMA system. We propose an explanation for this behavior: localized heating in the region near the crack tip (due to high strain rates) softens the material sufficiently to make a difference. We introduce this effect in our peridynamic model, via a bi-linear bond force-strain relationship, and the computed ...


Web-Based Archaeology And Collaborative Research, Fabrizio Galeazzi, Heather Richards-Rissetto Nov 2018

Web-Based Archaeology And Collaborative Research, Fabrizio Galeazzi, Heather Richards-Rissetto

Anthropology Faculty Publications

While digital technologies have been part of archaeology for more than fifty years, archaeologists still look for more efficient methodologies to integrate digital practices of fieldwork recording with data management, analysis, and ultimately interpretation.This Special Issue of the Journal of Field Archaeology gathers international scholars affiliated with universities, organizations, and commercial enterprises working in the field of Digital Archaeology. Our goal is to offer a discussion to the international academic community and practitioners. While the approach is interdisciplinary, our primary audience remains readers interested in web technology and collaborative platforms in archaeology


A Multi-Task Approach To Incremental Dialogue State Tracking, Anh Duong Trinh, Robert J. Ross, John D. Kelleher Nov 2018

A Multi-Task Approach To Incremental Dialogue State Tracking, Anh Duong Trinh, Robert J. Ross, John D. Kelleher

Conference papers

Incrementality is a fundamental feature of language in real world use. To this point, however, the vast majority of work in automated dialogue processing has focused on language as turn based. In this paper we explore the challenge of incremental dialogue state tracking through the development and analysis of a multi-task approach to incremental dialogue state tracking. We present the design of our incremental dialogue state tracker in detail and provide evaluation against the well known Dialogue State Tracking Challenge 2 (DSTC2) dataset. In addition to a standard evaluation of the tracker, we also provide an analysis of the Incrementality ...


Esense 2.0: Modeling Biomimetic Predation With Multi-Agent Multi-Team Distributed Artificial Intelligence, D. Michael Franklin, Derek Martin Nov 2018

Esense 2.0: Modeling Biomimetic Predation With Multi-Agent Multi-Team Distributed Artificial Intelligence, D. Michael Franklin, Derek Martin

Georgia Undergraduate Research Conference (GURC)

Biologic predation is a complex interaction amongst sets of predators and prey operating within the same environment. There are many disparate factors for each member of each set to consider as they interact. Additionally, they each must seek food while avoiding other predators, meaning that they must prioritize their actions based on policies. eSense provides a powerful yet simplistic reinforcement learning algorithm that employs model-based behavior across multiple learning layers. These independent layers split the learning objectives across multiple layers, avoiding the learning-confusion common in many multi-agent systems. The new eSense 2.0 increases the number of layers and the ...


Resource Allocation In The Cognitive Radio Network-Aided Internet Of Things For The Cyber-Physical-Social System: An Efficient Jaya Algorithm, Xiong Luo, Zhijie He, Zhigang Zhao, Long Wang, Weiping Wang, Huansheng Ning, Jenq-Haur Wang, Wenbing Zhao, Jun Zhang Nov 2018

Resource Allocation In The Cognitive Radio Network-Aided Internet Of Things For The Cyber-Physical-Social System: An Efficient Jaya Algorithm, Xiong Luo, Zhijie He, Zhigang Zhao, Long Wang, Weiping Wang, Huansheng Ning, Jenq-Haur Wang, Wenbing Zhao, Jun Zhang

Electrical Engineering & Computer Science Faculty Publications

Currently, there is a growing demand for the use of communication network bandwidth for the Internet of Things (IoT) within the cyber-physical-social system (CPSS), while needing progressively more powerful technologies for using scarce spectrum resources. Then, cognitive radio networks (CRNs) as one of those important solutions mentioned above, are used to achieve IoT effectively. Generally, dynamic resource allocation plays a crucial role in the design of CRN-aided IoT systems. Aiming at this issue, orthogonal frequency division multiplexing (OFDM) has been identified as one of the successful technologies, which works with a multi-carrier parallel radio transmission strategy. In this article, through ...


Numerical Study Of Liquid Atomization And Breakup Using The Volume Of Fluid Method In Ansys Fluent, Sai Saran Kandati Oct 2018

Numerical Study Of Liquid Atomization And Breakup Using The Volume Of Fluid Method In Ansys Fluent, Sai Saran Kandati

LSU Master's Theses

The spherical metal particles produced from the centrifugal atomization process have been the topic of numerous theoretical, experimental and numerical studies from the past few years. This atomization process uses centrifugal force to break-up molten material into spherical droplets, which are quenched into solidified granules by the flow of cold air on the spherical droplets. In the present work, a transient three-dimensional multiphase CFD model is applied to three different materials: Molten slag, aqueous glycerol solution, and molten Ni-Nb to study the influence of the dimensionless parameters on the centrifugal atomization outcome.

Results from numerical experiments indicated that the droplet ...


Brain Connectivity Networks For The Study Of Nonlinear Dynamics And Phase Synchrony In Epilepsy, Hoda Rajaei Oct 2018

Brain Connectivity Networks For The Study Of Nonlinear Dynamics And Phase Synchrony In Epilepsy, Hoda Rajaei

FIU Electronic Theses and Dissertations

Assessing complex brain activity as a function of the type of epilepsy and in the context of the 3D source of seizure onset remains a critical and challenging endeavor. In this dissertation, we tried to extract the attributes of the epileptic brain by looking at the modular interactions from scalp electroencephalography (EEG). A classification algorithm is proposed for the connectivity-based separation of interictal epileptic EEG from normal. Connectivity patterns of interictal epileptic discharges were investigated in different types of epilepsy, and the relation between patterns and the epileptogenic zone are also explored in focal epilepsy.

A nonlinear recurrence-based method is ...


Fogfly: A Traffic Light Optimization Solution Based On Fog Computing, Quang Tran Minh, Chanh Minh Tran, Tuan An Le, Binh Thai Nguyen, Triet Minh Tran, Rajesh Krishna Balan Oct 2018

Fogfly: A Traffic Light Optimization Solution Based On Fog Computing, Quang Tran Minh, Chanh Minh Tran, Tuan An Le, Binh Thai Nguyen, Triet Minh Tran, Rajesh Krishna Balan

Research Collection School Of Information Systems

This paper provides a fog-based approach to solving the traffic light optimization problem which utilizes the Adaptive Traffic Signal Control (ATSC) model. ATSC systems demand the ability to strictly reflect real-time traffic state. The proposed fog computing framework, namely FogFly, aligns with this requirement by its natures in location-awareness, low latency and affordability to the changes in traffic conditions. As traffic data is updated timely and processed at fog nodes deployed close to data sources (i.e., vehicles at intersections) traffic light cycles can be optimized efficiently while virtualized resources available at network edges are efficiently utilized. Evaluation results show ...


Experimental Tests And Numerical Simulations For Failure Investigation On Corrugated Boxes Used On Household Appliance Packaging, Diego Fernandes Rodrigues, José Carlos Pereira Sep 2018

Experimental Tests And Numerical Simulations For Failure Investigation On Corrugated Boxes Used On Household Appliance Packaging, Diego Fernandes Rodrigues, José Carlos Pereira

Journal of Applied Packaging Research

Packages made of corrugated paper are fundamental to the protection, transportation and handling of the appliance product market. During the storage and sales stages of a product, the package must resist compressive loads in different directions beyond moderate impacts. In this context, the objective of this work is to develop and implement a post-processor that allows the simultaneous analysis of two of the most common failure modes of packages made of corrugated paper: failure due to tensile or compressive stress limit, and failure due to local buckling, when the buckling of the faces of the corrugated paper between two peaks ...


Prediction Of Flood Hydrograph In Small River Catchments Using System Modelling Approach, Ahmed Nasr, Zeinab Bedri, Loreta Ramanauske Aug 2018

Prediction Of Flood Hydrograph In Small River Catchments Using System Modelling Approach, Ahmed Nasr, Zeinab Bedri, Loreta Ramanauske

Conference papers

Floods remain to be one of the natural catastrophic disasters with serious adverse social and economic implications on individuals and communities all around the world. In Ireland, frequency of flood events have increased dramatically during the last forty years and is expected to continue to rise primarily due to changes in rainfall and temperature patterns as a result of the global climate change. Small river catchments are usually vulnerable to different types of flooding particularly those associated with “monster” rainfall events, which are characterised by short durations and high intensities. Therefore accurate prediction of flood hydrographs resulting from these rainfall ...


Multi-Objective Bayesian Optimization Of Super Hydrophobic Coatings On Asphalt Concrete Surfaces, Ali Nahvi, Ali Arabzadeh, Alireza Sassani, Mohammadkazem Sadoughi, Halil Ceylan Aug 2018

Multi-Objective Bayesian Optimization Of Super Hydrophobic Coatings On Asphalt Concrete Surfaces, Ali Nahvi, Ali Arabzadeh, Alireza Sassani, Mohammadkazem Sadoughi, Halil Ceylan

Ali Nahvi

Conventional snow removal strategies add direct and indirect expenses to the economy through profit lost due to passenger delays costs, pavement durability issues, contaminating the water runoff, and so on. The use of superhydrophobic (super-water-repellent) coating methods is an alternative to conventional snow and ice removal practices for alleviating snow removal operations issues. As an integrated experimental and analytical study, this work focused on optimizing superhydrophobicity and skid resistance of hydrophobic coatings on asphalt concrete surfaces. A layer-by-layer (LBL) method was utilized for spray depositing polytetrafluoroethylene (PTFE) on an asphalt concrete at different spray times and variable dosages of PTFE ...


Understanding Suspend/Resume Path Of Linux Device Drivers, Yi Qiao, Xiaozhu Felix Lin Aug 2018

Understanding Suspend/Resume Path Of Linux Device Drivers, Yi Qiao, Xiaozhu Felix Lin

The Summer Undergraduate Research Fellowship (SURF) Symposium

Suspend/Resume (S/R), stands for putting mobile devices into sleep mode and wakes them up. Such a S/R process is heavily used in mobile devices today. While controlling by the operating system (OS), S/R process consumes a dominating portion of energy. In order to minimize the power consumption, we have to understand what happens on the S/R Path of modern device drivers so that further solutions reducing the overhead in that process can be found. In a modern OS, device drivers can make up over 70% of the source code, while still heavily dependent on the ...


Spatial And Temporal Storm Generation From A Stochastic View, Jiaxiang Ding, Josept D. Revuelta-Acosta, Engel Bernard Aug 2018

Spatial And Temporal Storm Generation From A Stochastic View, Jiaxiang Ding, Josept D. Revuelta-Acosta, Engel Bernard

The Summer Undergraduate Research Fellowship (SURF) Symposium

Precipitation is one of the most important parameters in the study of hydrology and most of the research has been done on daily storm generation. Current weather generation models are used to replicate daily or monthly time resolution, which is not able to show the variability within one day or one month. This project deals with sub-daily storm generation with finer resolution and more accurate estimation, which also requires an independent storm separation method. And the Monte Carlo correlated multivariate simulation is applied to compute the variables. The description is essential for soil erosion and water quality research. Another reason ...


New Methods For Understanding And Controlling The Self-Assembly Of Reacting Systems Using Coarse-Grained Molecular Dynamics, Stephen Thomas Aug 2018

New Methods For Understanding And Controlling The Self-Assembly Of Reacting Systems Using Coarse-Grained Molecular Dynamics, Stephen Thomas

Boise State University Theses and Dissertations

This research aims at developing new computational methods to understand the molecular self-assembly of reacting systems whose complex structures depend on the thermodynamics of mixing, reaction kinetics, and diffusion kinetics. The specific reacting system examined in this study is epoxy, cured with linear chain thermoplastic tougheners whose complex microstructure is known from experiments to affect mechanical properties and to be sensitive to processing conditions. Mesoscale simulation techniques have helped to bridge the length and time scales needed to predict the microstructures of cured epoxies, but the prohibitive computational cost of simulating experimentally relevant system sizes has limited their impact. In ...


An Efficient Framework For The Stochastic Verification Of Computation And Communication Systems Using Emerging Technologies, Zhen Zhang Jul 2018

An Efficient Framework For The Stochastic Verification Of Computation And Communication Systems Using Emerging Technologies, Zhen Zhang

Funded Research Records

No abstract provided.


Advanced Recurrent Network-Based Hybrid Acoustic Models For Low Resource Speech Recognition, Jian Kang, Wei-Qiang Zhang, Wei-Wei Liu, Jia Liu, Michael T. Johnson Jul 2018

Advanced Recurrent Network-Based Hybrid Acoustic Models For Low Resource Speech Recognition, Jian Kang, Wei-Qiang Zhang, Wei-Wei Liu, Jia Liu, Michael T. Johnson

Electrical and Computer Engineering Faculty Publications

Recurrent neural networks (RNNs) have shown an ability to model temporal dependencies. However, the problem of exploding or vanishing gradients has limited their application. In recent years, long short-term memory RNNs (LSTM RNNs) have been proposed to solve this problem and have achieved excellent results. Bidirectional LSTM (BLSTM), which uses both preceding and following context, has shown particularly good performance. However, the computational requirements of BLSTM approaches are quite heavy, even when implemented efficiently with GPU-based high performance computers. In addition, because the output of LSTM units is bounded, there is often still a vanishing gradient issue over multiple layers ...


Fedsm 2018 Presentation, Nima Fathi, Peter Vorobieff, Seyed Sobhan Aleyasin, Goodarz Ahmadi Jul 2018

Fedsm 2018 Presentation, Nima Fathi, Peter Vorobieff, Seyed Sobhan Aleyasin, Goodarz Ahmadi

Nima Fathi

Horizontal linear shear stress apparatus offers a convenient way to study the rheology of rigid particles suspended in viscous shear flows in the laboratory. The single particle trajectories of a buoyant spherical solid particle in a linear shear flow are investigated. Reynolds numbers less than 0.1 are considered to provide the creeping flow in this investigating. The experimental apparatus provides a linear stress, Stokes, Couette flow where the wall boundary conditions of the set up can change. The two-dimensional CFD analysis is performed to simulate the primary and secondary phases of the domain. Our numerical assessment, discrete phase element ...


Data-Driven Uncertainty Quantification Interpretation With High Density Regions, Matthew Gregor Peterson Jul 2018

Data-Driven Uncertainty Quantification Interpretation With High Density Regions, Matthew Gregor Peterson

Computer Science ETDs

In a time when data is being constantly generated by phones, vehicles, sensor net- works, social media, etc. detecting anomalies with in the data can be very crucial. In cases where we know little prior knowledge about the data, it becomes difficult to extract uncertainty about our results. In this thesis, we will propose a framework in which we can extract uncertainty distributions from data-driven modeling prob- lems. We will show some concrete examples of how to apply framework and provide some insight into what the uncertainty distributions are telling us using High Density Regions (HDRs).


Formalizing Schoenberg’S Fundamentals Of Musical Composition Through Petri Nets, A. Baratè, G. Haus, L. A. Ludovico, Davide Andrea Mauro Jul 2018

Formalizing Schoenberg’S Fundamentals Of Musical Composition Through Petri Nets, A. Baratè, G. Haus, L. A. Ludovico, Davide Andrea Mauro

Weisberg Division of Computer Science Faculty Research

The formalization of musical composition rules is a topic that has been studied for a long time. It can lead to a better understanding of the underlying processes, and provide a useful tool for musicologist to aid and speed up the analysis process. In our attempt we introduce Schoenberg’s rules from Fundamentals of Musical Composition using a specialized version of Petri nets, called Music Petri nets. Petri nets are a formal tool for studying systems that are concurrent, asynchronous, distributed, parallel, nondeterministic, and/or stochastic. We present some examples highlighting how multiple approaches to the analysis task can find ...


A Study Of Scalability And Cost-Effectiveness Of Large-Scale Scientific Applications Over Heterogeneous Computing Environment, Arghya K. Das Jun 2018

A Study Of Scalability And Cost-Effectiveness Of Large-Scale Scientific Applications Over Heterogeneous Computing Environment, Arghya K. Das

LSU Doctoral Dissertations

Recent advances in large-scale experimental facilities ushered in an era of data-driven science. These large-scale data increase the opportunity to answer many fundamental questions in basic science. However, these data pose new challenges to the scientific community in terms of their optimal processing and transfer. Consequently, scientists are in dire need of robust high performance computing (HPC) solutions that can scale with terabytes of data.

In this thesis, I address the challenges in three major aspects of scientific big data processing as follows: 1) Developing scalable software and algorithms for data- and compute-intensive scientific applications. 2) Proposing new cluster architectures ...