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Securecoin: A Robust Secure And Effi#14;Cient Protocol For Anonymous Bitcoin Ecosystem, Maged H. Ibrahim 2017 Helwan University

Securecoin: A Robust Secure And Effi#14;Cient Protocol For Anonymous Bitcoin Ecosystem, Maged H. Ibrahim

Maged Ibrahim

Bitcoin is the #12;rst decentralized peer-to-peer electronic
virtual asset and payment cryptocurrency, through which,
users can transact digital currency directly, without the
need for an intermediary (or authority), using a hashed
version of cryptographic public keys, as pseudonyms
called addresses. The Bitcoin ecosystem was supposed
to be anonymous and untraceable. However, transactions
from input to output addresses of the Bitcoin users are
observed to be linkable, therefore, missing unlinkability
as an important requirement of anonymity. Several pro-
tocols appeared to enhance Bitcoin users' anonymity and
to ensure unlinkability of input-output addresses, to make
input and output addresses of transactions ...


What's All The Fuss About Coding?, Tim Bell 2016 University of Canterbury

What's All The Fuss About Coding?, Tim Bell

2009 - 2016 ACER Research Conferences

The idea of teaching ‘coding’ to school students has become popular, and the term appears in the names of many initiatives, such as Hour of Code and Code Club. But what do we really mean by ‘coding’, and why would you want every child to learn it? Won’t it be outdated soon? This paper looks at these issues, and why topics such as computer science are being taught to all students. This includes an assessment of misunderstandings around the idea of compulsory programming for every student, and the challenges that accompany the introduction of such topics into schools.


Acer Research Conference Proceedings (2016), Australian Council for Educational Research (ACER) 2016 Australian Council for Educational Research (ACER)

Acer Research Conference Proceedings (2016), Australian Council For Educational Research (Acer)

2009 - 2016 ACER Research Conferences

The focus of ACER’s Research Conference 2016 will be on what we are learning from research about ways of improving levels of STEM learning. Australia faces significant challenges in promoting improved science, technology, engineering and mathematics (STEM) learning in our schools. Research Conference 2016 will showcase research into what it will take to address these challenges, which include: the decline in Australian students’ mathematical and scientific ‘literacy’; the decline in STEM study in senior school; a shortage of highly qualified STEM subject teachers, and curriculum challenges. You will hear from researchers who work with teachers to engage students in ...


Feature Extraction To Improve Nowcasting Using Social Media Event Detection On Cloud Computing And Sentiment Analysis, David L. Kimmey 2016 Indiana University - Purdue University Fort Wayne

Feature Extraction To Improve Nowcasting Using Social Media Event Detection On Cloud Computing And Sentiment Analysis, David L. Kimmey

Masters' Theses

Nowcasting is defined as the prediction of the present, the very near future, and the very recent past using real-time data. Nowcasting with social media creates challenges because of the HACE characteristics of big data (i.e., heterogeneous, autonomous, complex, and evolving associations). Thus, this thesis proposes a feature extraction method to improve nowcasting with social media. The proposed social media event detection algorithm utilizes K-SPRE methodology and the results are processed with sentiment analysis. In addition, we develop a parallel algorithm of the methodology on a cloud environment, and we adapt an artificial neural network to build a predictive ...


An Extendable Visualization And User Interface Design For Time-Varying Multivariate Geoscience Data, Yanfu Zhou 2016 University of Nebraska - Lincoln

An Extendable Visualization And User Interface Design For Time-Varying Multivariate Geoscience Data, Yanfu Zhou

Computer Science and Engineering: Theses, Dissertations, and Student Research

Geoscience data has unique and complex data structures, and its visualization has been challenging due to a lack of effective data models and visual representations to tackle the heterogeneity of geoscience data. In today’s big data era, the needs of visualizing geoscience data become urgent, especially driven by its potential value to human societies, such as environmental disaster prediction, urban growth simulation, and so on. In this thesis, I created a novel geoscience data visualization framework and applied interface automata theory to geoscience data visualization tasks. The framework can support heterogeneous geoscience data and facilitate data operations. The interface ...


Two Neural Network Based Decentralized Controller Designs For Large Scale Power Systems, Wenxin Liu, Jagannathan Sarangapani, Ganesh K. Venayagamoorthy, Donald C. Wunsch, Mariesa Crow, David A. Cartes 2016 Missouri University of Science and Technology

Two Neural Network Based Decentralized Controller Designs For Large Scale Power Systems, Wenxin Liu, Jagannathan Sarangapani, Ganesh K. Venayagamoorthy, Donald C. Wunsch, Mariesa Crow, David A. Cartes

Mariesa Crow

This paper presents two neural network (NN) based decentralized controller designs for large scale power systems' generators, one is for the excitation control and the other is for the steam valve control. Though the control signals are calculated using local signals only, the transient and overall system stabilities can be guaranteed. NNs are used to approximate the unknown and/or imprecise dynamics of the local power system and the interconnection terms, thus the requirements for exact system parameters are released. Simulation studies with a three machine power system demonstrate the effectiveness of the proposed controller designs.


Use Of Max-Flow On Facts Devices, Adam Lininger, Bruce M. McMillin, Badrul H. Chowdhury, Mariesa Crow 2016 Missouri University of Science and Technology

Use Of Max-Flow On Facts Devices, Adam Lininger, Bruce M. Mcmillin, Badrul H. Chowdhury, Mariesa Crow

Mariesa Crow

FACTS devices can be used to mitigate cascading failures in a power grid by controlling the power flow in individual lines. Placement and control are significant issues. We present a procedure for determining whether a scenario can be mitigated using the concept of maximum flow. If it can be mitigated, we determine what placement and control setting will solve the scenario. This paper treats fourteen cascading failure scenarios and reports on the use of the max-flow algorithm both in determining the mitigation of each scenario and in finding FACTS settings that will mitigate the scenario.


The Maximum Flow Algorithm Applied To The Placement And Distributed Steady-State Control Of Upfcs, Austin Armbruster, Bruce M. McMillin, Mariesa Crow, Michael R. Gosnell 2016 Missouri University of Science and Technology

The Maximum Flow Algorithm Applied To The Placement And Distributed Steady-State Control Of Upfcs, Austin Armbruster, Bruce M. Mcmillin, Mariesa Crow, Michael R. Gosnell

Mariesa Crow

The bulk power system is one of the largest man-made networks and its size makes control an extremely difficult task. This paper presents a method to control a power network using UPFCs set to levels determined by a maximum flow (max-flow) algorithm. The graph-theory-based max-flow is applied to the power system for UPFC placement and scheduling. A distributed version of max-flow is described to coordinate the actions of the UPFCs distributed in a power network. Two sample power systems were tested using max-flow for UPFC placement and settings. The resulting system characteristics are examined over all single-line contingencies and the ...


Power Transmission Control Using Distributed Max-Flow, Bruce M. McMillin, Austin Armbruster, Mariesa Crow, Michael R. Gosnell 2016 Missouri University of Science and Technology

Power Transmission Control Using Distributed Max-Flow, Bruce M. Mcmillin, Austin Armbruster, Mariesa Crow, Michael R. Gosnell

Mariesa Crow

Existing maximum flow algorithms use one processor for all calculations or one processor per vertex in a graph to calculate the maximum possible flow through a graph''s vertices. This is not suitable for practical implementation. We extend the max-flow work of Goldberg and Tarjan to a distributed algorithm to calculate maximum flow where the number of processors is less than the number of vertices in a graph. Our algorithm is applied to maximizing electrical flow within a power network where the power grid is modeled as a graph. Error detection measures are included to detect problems in a simulated ...


Neural Network Stabilizing Control Of Single Machine Power System With Control Limits, Wenxin Liu, Jagannathan Sarangapani, Ganesh K. Venayagamoorthy, Donald C. Wunsch, Mariesa Crow 2016 Missouri University of Science and Technology

Neural Network Stabilizing Control Of Single Machine Power System With Control Limits, Wenxin Liu, Jagannathan Sarangapani, Ganesh K. Venayagamoorthy, Donald C. Wunsch, Mariesa Crow

Mariesa Crow

Power system stabilizers are widely used to generate supplementary control signals for the excitation system in order to damp out the low frequency oscillations. This paper proposes a stable neural network (NN) controller for the stabilization of a single machine infinite bus power system. In the power system control literature, simplified analytical models are used to represent the power system and the controller designs are not based on rigorous stability analysis. This work overcomes the two major problems by using an accurate analytical model for controller development and presents the closed-loop stability analysis. The NN is used to approximate the ...


Novel Dynamic Representation And Control Of Power Networks Embedded With Facts Devices, Shahab Mehraeen, Jagannathan Sarangapani, Mariesa Crow 2016 Missouri University of Science and Technology

Novel Dynamic Representation And Control Of Power Networks Embedded With Facts Devices, Shahab Mehraeen, Jagannathan Sarangapani, Mariesa Crow

Mariesa Crow

FACTS devices have been shown to be powerful in damping power system oscillations caused by faults; however, in the multi machine control using FACTS, the control problem involves solving differential-algebraic equations of a power network which renders the available control schemes ineffective due to heuristic design and lack of know how to incorporate FACTS into the network. A method to generate nonlinear dynamic representation of a power system consisting of differential equations alone with universal power flow controller (UPFC) is introduced since differential equations are typically preferred for controller development. Subsequently, backstepping methodology is utilized to reduce the generator oscillations ...


Nonlinear Control Of Facts Controllers For Damping Interarea Oscillations In Power Systems, Mahyar Zarghami, Jagannathan Sarangapani, Mariesa Crow 2016 Missouri University of Science and Technology

Nonlinear Control Of Facts Controllers For Damping Interarea Oscillations In Power Systems, Mahyar Zarghami, Jagannathan Sarangapani, Mariesa Crow

Mariesa Crow

This paper introduces a new nonlinear control of flexible ac transmission systems (FACTS) controllers for the purpose of damping interarea oscillations in power systems. FACTS controllers consist of series, shunt, or a combination of series-shunt devices which are interfaced with the bulk power system through injection buses. Controlling the angle of these buses can effectively damp low frequency interarea oscillations in the system. The proposed control method is based on finding an equivalent reduced affine nonlinear system for the network from which the dominant machines are extracted based on dynamic coherency. It is shown that if properly selected, measurements obtained ...


Optimal Placement And Control Of Unified Power Flow Control Devices Using Evolutionary Computing And Sequential Quadratic Programming, Radha P. Kalyani, Mariesa Crow, Daniel R. Tauritz 2016 Missouri University of Science and Technology

Optimal Placement And Control Of Unified Power Flow Control Devices Using Evolutionary Computing And Sequential Quadratic Programming, Radha P. Kalyani, Mariesa Crow, Daniel R. Tauritz

Mariesa Crow

A crucial factor effecting modern power systems today is power flow control. An effective means for controlling and improving power flow is by installing fast reacting devices such as a unified power flow controller (UPFC). For maximum positive impact of this device on the power grid, it should be installed at an optimal location and employ an optimal realtime control algorithm. This paper proposes the combination of an evolutionary algorithm (EA) to find the optimal location and sequential quadratic programming (SQP) to optimize the UPFC control settings. Simulations are conducted using the classic IEEE 118 bus test system. For comparison ...


Neural Network Based Decentralized Controls Of Large Scale Power Systems, Wenxin Liu, Jagannathan Sarangapani, Ganesh K. Venayagamoorthy, Donald C. Wunsch, Mariesa Crow, Li Liu, David A. Cartes 2016 Missouri University of Science and Technology

Neural Network Based Decentralized Controls Of Large Scale Power Systems, Wenxin Liu, Jagannathan Sarangapani, Ganesh K. Venayagamoorthy, Donald C. Wunsch, Mariesa Crow, Li Liu, David A. Cartes

Mariesa Crow

This paper presents a suite of neural network (NN) based decentralized controller designs for large scale power systems' generators, one is for the excitation control and the other is for the steam valve control. Though the control inputs are calculated using local signals, the transient and overall system stability can be guaranteed. NNs are used to approximate the unknown and/or imprecise dynamics of the local power system dynamics and the inter-connection terms, thus the requirements for exact system parameters are relaxed. Simulation studies with a three-machine power system demonstrate the effectiveness of the proposed controller designs.


Distributed Power Balancing For The Freedm System, Rav Akella, Fanjun Meng, Derek Ditch, Bruce M. McMillin, Mariesa Crow 2016 Missouri University of Science and Technology

Distributed Power Balancing For The Freedm System, Rav Akella, Fanjun Meng, Derek Ditch, Bruce M. Mcmillin, Mariesa Crow

Mariesa Crow

The FREEDM microgrid is a test bed for a smart grid integrated with Distributed Grid Intelligence (DGI) to efficiently manage the distribution and storage of renewable energy. Within the FREEDM system, DGI applies distributed algorithms in a unique way to achieve economically feasible utilization and storage of alternative energy sources in a distributed fashion. The FREEDM microgrid consists of residential or industrial nodes with each node running a portion of the DGI process called Intelligent Energy Management (IEM). Such IEM nodes within FREEDM coordinate among themselves to efficiently and economically manage their power generation, utility and storage. Among a variety ...


Decentralized Neural Network Control Of A Class Of Large-Scale Systems With Unknown Interconnection, Wenxin Liu, Jagannathan Sarangapani, Donald C. Wunsch, Mariesa Crow 2016 Missouri University of Science and Technology

Decentralized Neural Network Control Of A Class Of Large-Scale Systems With Unknown Interconnection, Wenxin Liu, Jagannathan Sarangapani, Donald C. Wunsch, Mariesa Crow

Mariesa Crow

A novel decentralized neural network (DNN) controller is proposed for a class of large-scale nonlinear systems with unknown interconnections. The objective is to design a DNN for a class of large-scale systems which do not satisfy the matching condition requirement. The NNs are used to approximate the unknown subsystem dynamics and the interconnections. The DNN is designed using the back stepping methodology with only local signals for feedback. All of the signals in the closed loop (system states and weights estimation errors) are guaranteed to be uniformly ultimately bounded and eventually converge to a compact set.


Damping Inter-Area Oscillations By Upfcs Based On Selected Global Measurements, Mahyar Zarghami, Yilu Liu, Jagannathan Sarangapani, Mariesa Crow 2016 Missouri University of Science and Technology

Damping Inter-Area Oscillations By Upfcs Based On Selected Global Measurements, Mahyar Zarghami, Yilu Liu, Jagannathan Sarangapani, Mariesa Crow

Mariesa Crow

This paper introduces a method of using a selected set of the global data for controlling inter-area oscillations of the power network using unified power flow controllers. This novel algorithm utilizes reduced order observers for estimating the missing data the purpose of control when all the data is unavailable through frequency measurements in a wide area control approach. The paper will also address the problem of time-delay in data acquisition through examples.


Comparisons Of An Adaptive Neural Network Based Controller And An Optimized Conventional Power System Stabilizer, Wenxin Liu, Ganesh K. Venayagamoorthy, Jagannathan Sarangapani, Donald C. Wunsch, Mariesa Crow, Li Liu, David A. Cartes 2016 Missouri University of Science and Technology

Comparisons Of An Adaptive Neural Network Based Controller And An Optimized Conventional Power System Stabilizer, Wenxin Liu, Ganesh K. Venayagamoorthy, Jagannathan Sarangapani, Donald C. Wunsch, Mariesa Crow, Li Liu, David A. Cartes

Mariesa Crow

Power system stabilizers are widely used to damp out the low frequency oscillations in power systems. In power system control literature, there is a lack of stability analysis for proposed controller designs. This paper proposes a Neural Network (NN) based stabilizing controller design based on a sixth order single machine infinite bus power system model. The NN is used to compensate the complex nonlinear dynamics of power system. To speed up the learning process, an adaptive signal is introduced to the NN's weights updating rule. The NN can be directly used online without offline training process. Magnitude constraint of ...


An Open Framework For Highly Concurrent Real-Time Hardware-In-The-Loop Simulation, Ryan C. Underwood, Bruce M. McMillin, Mariesa Crow 2016 Missouri University of Science and Technology

An Open Framework For Highly Concurrent Real-Time Hardware-In-The-Loop Simulation, Ryan C. Underwood, Bruce M. Mcmillin, Mariesa Crow

Mariesa Crow

Hardware-in-the-loop (HIL) real-time simulation is becoming a significant tool in prototyping complex, highly available systems. The HIL approach permits testing of hardware prototypes of components that would be extremely costly or difficult to test in the deployed environment. In power system simulation, key issues are the ability to wrap the systems of equations (such as Partial Differential Equations) describing the deployed environment into real-time software models, provide low synchronization overhead between the hardware and software, and reduce reliance on proprietary platforms. This paper introduces an open source HIL simulation framework that can be ported to any standard Unix-like system on ...


An Improved Upfc Control For Oscillation Damping, Jagannathan Sarangapani, Mariesa Crow, Jianjun Guo 2016 Missouri University of Science and Technology

An Improved Upfc Control For Oscillation Damping, Jagannathan Sarangapani, Mariesa Crow, Jianjun Guo

Mariesa Crow

This paper proposes a new control approach for a unified power flow controller (UPFC) for power system oscillation damping. This control is simple to implement, yet is valid over a wide range of operating conditions. It is also effective in the presence of multiple modes of oscillation. The proposed control is implemented in several test systems and is compared against a traditional PI control.


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