Blokus Game Solver, 2018 California Polytechnic State University, San Luis Obispo
Blokus Game Solver, Chin Chao
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 ...
A Validation Study Of Time Series Data Forecasting Using Neural Networks, 2018 Southwestern Oklahoma State University
A Validation Study Of Time Series Data Forecasting Using Neural Networks, Marco Martinez, Jeremy Evert
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, 2018 Louisiana State University
Toward Building Resilient, Sustainable, And Smart Infrastructure In The 21st Century, Aly Mousaad Aly
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, 2018 University of Nebraska - Lincoln
Dynamic Fracture Of Pmma, Intefacial Failure, And Local Heating, Javad Mehrmashhadi, Longzhen Wang, Florin Bobaru Ph.D.
Web-Based Archaeology And Collaborative Research, 2018 University of York
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
Esense 2.0: Modeling Biomimetic Predation With Multi-Agent Multi-Team Distributed Artificial Intelligence, 2018 Kennesaw State University
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, 2018 University of Science and Technology Beijing
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 ...
Fogfly: A Traffic Light Optimization Solution Based On Fog Computing, 2018 Singapore Management University
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
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, 2018 Technological University Dublin
Prediction Of Flood Hydrograph In Small River Catchments Using System Modelling Approach, Ahmed Nasr, Zeinab Bedri, Loreta Ramanauske
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 ...
Understanding Suspend/Resume Path Of Linux Device Drivers, 2018 Purdue University
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, 2018 Purdue University
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
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 ...
Advanced Recurrent Network-Based Hybrid Acoustic Models For Low Resource Speech Recognition, 2018 Tsinghua University, China
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, 2018 University of New Mexico
Fedsm 2018 Presentation, Nima Fathi, Peter Vorobieff, Seyed Sobhan Aleyasin, Goodarz Ahmadi
Formalizing Schoenberg’S Fundamentals Of Musical Composition Through Petri Nets, 2018 Marshall University
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, 2018 Louisiana State University and Agricultural and Mechanical College
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 ...
Computer Design Of Microfluidic Mixers For Protein/Rna Folding Studies, 2018 University of Massachusetts Amherst
Computer Design Of Microfluidic Mixers For Protein/Rna Folding Studies, Venkatesh Inguva, Sagar V. Kathuria, Osman Bilsel, Blair James Perot
Open Access Articles
Kinetic studies of biological macromolecules increasingly use microfluidic mixers to initiate and monitor reaction progress. A motivation for using microfluidic mixers is to reduce sample consumption and decrease mixing time to microseconds. Some applications, such as small-angle x-ray scattering, also require large ( > 10 micron) sampling areas to ensure high signal-to-noise ratios and to minimize parasitic scattering. Chaotic to marginally turbulent mixers are well suited for these applications because this class of mixers provides a good middle ground between existing laminar and turbulent mixers. In this study, we model various chaotic to marginally turbulent mixing concepts such as flow turning, flow ...
Investigating Scale Effects On Analytical Methods Of Predicting Peak Wind Loads On Buildings, 2018 Florida International University
Investigating Scale Effects On Analytical Methods Of Predicting Peak Wind Loads On Buildings, Mohammadtaghi Moravej
FIU Electronic Theses and Dissertations
Large-scale testing of low-rise buildings or components of tall buildings is essential as it provides more representative information about the realistic wind effects than the typical small scale studies, but as the model size increases, relatively less large-scale turbulence in the upcoming flow can be generated. This results in a turbulence power spectrum lacking low-frequency turbulence content. This deficiency is known to have significant effects on the estimated peak wind loads.
To overcome these limitations, the method of Partial Turbulence Simulation (PTS) has been developed recently in the FIU Wall of Wind lab to analytically compensate for the effects of ...
Effect Of Material Viscoelasticity On Frequency Tuning Of Dielectric Elastomer Membrane Resonators, 2018 The University of Western Ontario
Effect Of Material Viscoelasticity On Frequency Tuning Of Dielectric Elastomer Membrane Resonators, Liyang Tian
Electronic Thesis and Dissertation Repository
Dielectric elastomers (DEs) capable of large voltage-induced deformation show promise for applications such as resonators and oscillators. However, the dynamic performance of such vibrational devices is not only strongly affected by the nonlinear electromechanical coupling and material hyperelasticity, but also significantly by the material viscoelasticity. The material viscoelasticity of DEs originates from the highly mobile polymer chains that constitute the polymer networks of the DE. Moreover, due to the multiple viscous polymer subnetworks, DEs possess multiple relaxation processes. Therefore, in order to predict the dynamic performance of DE-based devices, a theoretical model that accounts for the multiple relaxation processes is ...