Theory and Algorithms Commons^™

The Effect Of Modeling Simultaneous Events On Simulation Results, John M. Carboni

Theses and Dissertations

This thesis explores the method that governs the prioritizing process for simultaneous events in relation to simulation results for discrete-event simulations. Specifically, it contrasts typical discrete-event simulation (DES) execution algorithms with how events are selected and ordered by the discrete-event system specification (DEVS) formalism. The motivation for this research stems from a desire to understand how the selection of events affects simulation output (i.e., response). As a particular use case, we briefly investigate the processing of simultaneous events by the Advanced Framework for Simulation, Integration and Modeling (AFSIM), a military discrete-event combat modeling and simulation package. To facilitate the building …

Performance Analysis Of Angle Of Arrival Algorithms Applied To Radiofrequency Interference Direction Finding, Taylor S. Barber

Theses and Dissertations

Radiofrequency (RF) interference threatens the functionality of systems that increasingly underpin the daily function of modern society. In recent years there have been multiple incidents of intentional RF spectrum denial using terrestrial interference sources. Because RF based systems are used in safety-of-life applications in both military and civilian contexts, there is need for systems that can quickly locate these interference sources. In order to meet this need, the Air Force Research Laboratory Weapons Directorate is sponsoring the following research to support systems that will be able to quickly geolocate RF interferers using passive angle-of-arrival estimation to triangulate interference sources. This …

A Generalized Phase Gradient Autofocus Algorithm, Aaron Evers

Theses and Dissertations

The phase gradient autofocus (PGA) algorithm has seen widespread use and success within the synthetic aperture radar (SAR) imaging community. However, its use and success has largely been limited to collection geometries where either the polar format algorithm (PFA) or range migration algorithm is suitable for SAR image formation. In this work, a generalized phase gradient autofocus (GPGA) algorithm is developed which is applicable with both the PFA and backprojection algorithm (BPA), thereby directly supporting a wide range of collection geometries and SAR imaging modalities. The GPGA algorithm preserves the four crucial signal processing steps comprising the PGA algorithm, while …

Two-On-One Pursuit With A Non-Zero Capture Radius, Patrick J. Wasz

Theses and Dissertations

In this paper, we revisit the "Two Cutters and Fugitive Ship" differential game that was addressed by Isaacs, but move away from point capture. We consider a two-on-one pursuit-evasion differential game with simple motion and pursuers endowed with circular capture sets of radius l > 0. The regions in the state space where only one pursuer effects the capture and the region in the state space where both pursuers cooperatively and isochronously capture the evader are characterized, thus solving the Game of Kind. Concerning the Game of Degree, the algorithm for the synthesis of the optimal state feedback strategies of the …

Pascal's Triangle Modulo N And Its Applications To Efficient Computation Of Binomial Coefficients, Zachary Warneke

Honors Program: Senior Projects (Public)

In this thesis, Pascal's Triangle modulo n will be explored for n prime and n a prime power. Using the results from the case when n is prime, a novel proof of Lucas' Theorem is given. Additionally, using both the results from the exploration of Pascal's Triangle here, as well as previous results, an efficient algorithm for computation of binomial coefficients modulo n (a choose b mod n) is described, and its time complexity is analyzed and compared to naive methods. In particular, the efficient algorithm runs in O(n log(a)) time (as opposed to …

Use Of Exploratory Data Analysis And Visualization In Identification Of Commingled Human Remains, Vivek Bhat Hosmat

UNO Student Research and Creative Activity Fair

The field of Exploratory data analysis and Visualization is revolutionizing the way we perceive things. At times, Visualization is seen as a subset of Exploratory data analysis and then there are branches in Visualization, types, technologies, tools which makes one feel that Visualization is a standalone pillar. Either way, they both work well together to extract meaningful information from almost any kind of data. These fields can very well be the stepping stone for in-depth or conclusive research. They can direct research based on facts and observations rather than one’s intuition or even a brute force technique. This project was …

Quantum Computing Is Here To Stay, Manoj Thulasidas

MITB Thought Leadership Series

QUANTUM COMPUTING is emerging from university laboratories and entering the industry arena at a painfully slow pace. The measured and deliberate progress is understandable given its complexity and promise. The stakes are high, because quantum computing presents the tantalising prospect of solving problems previously considered completely insoluble

Mirai Bot Scanner Summation Prototype, Charles V. Frank Jr.

Masters Theses & Doctoral Dissertations

The Mirai botnet deploys a distributed mechanism with each Bot continually scanning for a potential new Bot Victim. A Bot continually generates a random IP address to scan the network for discovering a potential new Bot Victim. The Bot establishes a connection with the potential new Bot Victim with a Transmission Control Protocol (TCP) handshake. The Mirai botnet has recruited hundreds of thousands of Bots. With 100,000 Bots, Mirai Distributed Denial of Service (DDoS) attacks on service provider Dyn in October 2016 triggered the inaccessibility to hundreds of websites in Europe and North America (Sinanović & Mrdovic, 2017). A month …

Distributed Gibbs: A Linear-Space Sampling-Based Dcop Algorithm, Duc Thien Nguyen, William Yeoh, Hoong Chuin Lau, Roie Zivan

Research Collection School Of Computing and Information Systems

Researchers have used distributed constraint optimization problems (DCOPs) to model various multi-agent coordination and resource allocation problems. Very recently, Ottens et al. proposed a promising new approach to solve DCOPs that is based on confidence bounds via their Distributed UCT (DUCT) sampling-based algorithm. Unfortunately, its memory requirement per agent is exponential in the number of agents in the problem, which prohibits it from scaling up to large problems. Thus, in this article, we introduce two new sampling-based DCOP algorithms called Sequential Distributed Gibbs (SD-Gibbs) and Parallel Distributed Gibbs (PD-Gibbs). Both algorithms have memory requirements per agent that is linear in …

Semantic And Influence Aware K-Representative Queries Over Social Streams, Yanhao Wang, Yuchen Li, Kianlee Tan

Research Collection School Of Computing and Information Systems

Massive volumes of data continuously generated on social platforms have become an important information source for users. A primary method to obtain fresh and valuable information from social streams is social search. Although there have been extensive studies on social search, existing methods only focus on the relevance of query results but ignore the representativeness. In this paper, we propose a novel Semantic and Influence aware k-Representative (k-SIR) query for social streams based on topic modeling. Specifically, we consider that both user queries and elements are represented as vectors in the topic space. A k-SIR query retrieves a set of …

A Theoretical Model Of Underground Dipole Antennas For Communications In Internet Of Underground Things, Abdul Salam, Mehmet C. Vuran, Xin Dong, Christos Argyropoulos, Suat Irmak

Faculty Publications

The realization of Internet of Underground Things (IOUT) relies on the establishment of reliable communication links, where the antenna becomes a major design component due to the significant impacts of soil. In this paper, a theoretical model is developed to capture the impacts of change of soil moisture on the return loss, resonant frequency, and bandwidth of a buried dipole antenna. Experiments are conducted in silty clay loam, sandy, and silt loam soil, to characterize the effects of soil, in an indoor testbed and field testbeds. It is shown that at subsurface burial depths (0.1-0.4m), change in soil moisture impacts …

Smart Parking Systems Design And Integration Into Iot, Charles M. Menne

Scholarly Horizons: University of Minnesota, Morris Undergraduate Journal

This paper looks at two smart parking reservation algorithms, and examines the ongoing efforts to connect smart systems of different domains in a city's infrastructure. The reservation algorithms are designed to improve the performance of smart parking systems. The first algorithm considers the distance between parking areas and the number of free parking spaces in determining a parking space. The second algorithm uses distance between parking areas and driver destination, parking price, and the number of unoccupied spaces for each parking area. Neither of these smart parking systems cover how they could fit into a larger scale smart system. As …

Bilateral Dependency Neural Networks For Cross-Language Algorithm Classification, Duy Quoc Nghi Bui, Yijun Yu, Lingxiao Jiang

Research Collection School Of Computing and Information Systems

Algorithm classification is to automatically identify the classes of a program based on the algorithm(s) and/or data structure(s) implemented in the program. It can be useful for various tasks, such as code reuse, code theft detection, and malware detection. Code similarity metrics, on the basis of features extracted from syntax and semantics, have been used to classify programs. Such features, however, often need manual selection effort and are specific to individual programming languages, limiting the classifiers to programs in the same language.To recognise the similarities and differences among algorithms implemented in different languages, this paper describes a framework of Bilateral …

Send Hardest Problems My Way: Probabilistic Path Prioritization For Hybrid Fuzzing, Lei Zhao, Yue Duan, Jifeng Xuan

Research Collection School Of Computing and Information Systems

Hybrid fuzzing which combines fuzzing and concolic execution has become an advanced technique for software vulnerability detection. Based on the observation that fuzzing and concolic execution are complementary in nature, the state-of-the-art hybrid fuzzing systems deploy ``demand launch'' and ``optimal switch'' strategies. Although these ideas sound intriguing, we point out several fundamental limitations in them, due to oversimplified assumptions. We then propose a novel ``discriminative dispatch'' strategy to better utilize the capability of concolic execution. We design a novel Monte Carlo based probabilistic path prioritization model to quantify each path's difficulty and prioritize them for concolic execution. This model treats …

A Sampling Approach For Proactive Project Scheduling Under Generalized Time-Dependent Workability Uncertainty, Wen Song, Donghun Kang, Jie Zhang, Zhiguang Cao, Hui Xi

Research Collection School Of Computing and Information Systems

In real-world project scheduling applications, activity durations are often uncertain. Proactive scheduling can effectively cope with the duration uncertainties, by generating robust baseline solutions according to a priori stochastic knowledge. However, most of the existing proactive approaches assume that the duration uncertainty of an activity is not related to its scheduled start time, which may not hold in many real-world scenarios. In this paper, we relax this assumption by allowing the duration uncertainty to be time-dependent, which is caused by the uncertainty of whether the activity can be executed on each time slot. We propose a stochastic optimization model to …

Dish: Democracy In State Houses, Nicholas A. Russo

Master's Theses

In our current political climate, state level legislators have become increasingly impor- tant. Due to cuts in funding and growing focus at the national level, public oversight for these legislators has drastically decreased. This makes it difficult for citizens and activists to understand the relationships and commonalities between legislators. This thesis provides three contributions to address this issue. First, we created a data set containing over 1200 features focused on a legislator’s activity on bills. Second, we created embeddings that represented a legislator’s level of activity and engagement for a given bill using a custom model called Democracy2Vec. Third, we …

Improving Vix Futures Forecasts Using Machine Learning Methods, James Hosker, Slobodan Djurdjevic, Hieu Nguyen, Robert Slater

SMU Data Science Review

The problem of forecasting market volatility is a difficult task for most fund managers. Volatility forecasts are used for risk management, alpha (risk) trading, and the reduction of trading friction. Improving the forecasts of future market volatility assists fund managers in adding or reducing risk in their portfolios as well as in increasing hedges to protect their portfolios in anticipation of a market sell-off event. Our analysis compares three existing financial models that forecast future market volatility using the Chicago Board Options Exchange Volatility Index (VIX) to six machine/deep learning supervised regression methods. This analysis determines which models provide best …

A Comparative Evaluation Of Recommender Systems For Hotel Reviews, Ryan Khaleghi, Kevin Cannon, Raghuram Srinivas

SMU Data Science Review

There has been increasing growth in deployment of recommender systems across Internet sites, with various models being used. These systems have been particularly valuable for review sites, as they seek to add value to the user experience to gain market share and to create new revenue streams through deals. Hotels are a prime target for this effort, as there is a large number for most destinations and a lot of differentiation between them. In this paper, we present an evaluation of two of the most popular methods for hotel review recommender systems: collaborative filtering and matrix factorization. The accuracy of …

A Machine Learning Recommender Model For Ride Sharing Based On Rider Characteristics And User Threshold Time, Govind Pramod Yatnalkar

Theses, Dissertations and Capstones

In the present age, human life is prospering incredibly due to the 4^th Industrial Revolution or The Age of Digitization and Computing. The ubiquitous availability of the Internet and advanced computing systems have resulted in the rapid development of smart cities. From connected devices to live vehicle tracking, technology is taking the field of transportation to a new level. An essential part of the transportation domain in smart cities is Ride Sharing. It is an excellent solution to issues like pollution, traffic, and the rapid consumption of fuel. Even though Ride Sharing has several benefits, the current usage is …

Radically Simplifying Gated Recurrent Architectures Without Loss Of Performance, Jonathan Boardman, Ying Xie

Published and Grey Literature from PhD Candidates

Long Short-Term Memory (LSTM) units are a family of Recurrent Neural Network (RNN) architectures that have proven incredibly effective at learning from sequence data. They are also extremely complex, making them expensive to train and difficult to understand. A recent trend towards simplification has produced the Gated Recurrent Unit (GRU) and the Minimal Gated Unit (MGU), both of which perform as well as the LSTM (or better) on a variety of tasks. The MGU is one of the simplest gated recurrent architectures at the moment. Our study demonstrates that it is possible to radically simplify the MGU without significant loss …

Squared Distance Matrix Of A Weighted Tree, Ravindra B. Bapat

Journal Articles

Let T be a tree with vertex set f1;: :: ; ng such that each edge is assigned a nonzero weight. The squared distance matrix of T; denoted by is the n n matrix with (i; j)-element d(i; j)2; where d(i; j) is the sum of the weights of the edges on the (ij)-path. We obtain a formula for the determinant of A formula for 1 is also obtained, under certain conditions. The results generalize known formulas for the unweighted case.

Statistical Analysis Of Tandem Queues With Markovian Passages In Porous Mediums, Gboyega David Adepoju

Theses, Dissertations and Capstones

Queuing theory is the mathematical study of queues or waiting lines. A queue is formed whenever the demand for service exceeds the capacity to provide service at that point in time. In this thesis, the birth-and-death process is used to model the movement of customers or units into and out of a network of queues in tandem. We start with the theoretical analysis of M/M/1 queues with Poisson arrival and exponential service time with first-come first-served (FCFS) discipline and one service station. We derive the global balance equation for each network. Using both the iterative and the probability generating function, …

Android Application For Mnist Handwritten Digits Classification, Mina Gabriel

Project Topics and Ideas

Use Neural Network architecture to classify MNIST handwritten digits dataset, student/s should implement a phone application (Android) to demonstrate their work, application will then be published to the app store for other students and CISC faculty members for evaluation and feedback.

Optimal Gateway Placement In Low-Cost Smart Cities, Oluwashina Madamori

Theses and Dissertations--Computer Science

Rapid urbanization burdens city infrastructure and creates the need for local governments to maximize the usage of resources to serve its citizens. Smart city projects aim to alleviate the urbanization problem by deploying a vast amount of Internet-of-things (IoT) devices to monitor and manage environmental conditions and infrastructure. However, smart city projects can be extremely expensive to deploy and manage partly due to the cost of providing Internet connectivity via 5G or WiFi to IoT devices. This thesis proposes the use of delay tolerant networks (DTNs) as a backbone for smart city communication; enabling developing communities to become smart cities …

Distributed Multi-Label Learning On Apache Spark, Jorge Gonzalez Lopez

Theses and Dissertations

This thesis proposes a series of multi-label learning algorithms for classification and feature selection implemented on the Apache Spark distributed computing model. Five approaches for determining the optimal architecture to speed up multi-label learning methods are presented. These approaches range from local parallelization using threads to distributed computing using independent or shared memory spaces. It is shown that the optimal approach performs hundreds of times faster than the baseline method. Three distributed multi-label k nearest neighbors methods built on top of the Spark architecture are proposed: an exact iterative method that computes pair-wise distances, an approximate tree-based method that indexes …

Who Should Be Invited To My Party: A Size-Constrained K-Core Problem In Social Networks, Yu-Liang Ma, Ye Yuan, Feida Zhu, Guo-Ren Wang, Jing Xiao, Jian-Zong Wang

Research Collection School Of Computing and Information Systems

In this paper, we investigate the problem of a size-constrained k-core group query (SCCGQ) in social networks, taking both user closeness and network topology into consideration. More specifically, SCCGQ intends to find a group of h users that has the highest social closeness while being a k-core. SCCGQ can be widely applied to event planning, task assignment, social analysis, and many other fields. In contrast to existing work on the k-core detection problem, which aims to find a k-core in a social network, SCCGQ not only focuses on k-core detection but also takes size constraints into consideration. Although the conventional …

Development Of A Sensing System For Underground Optic Fiber Cable Conduit Mapping, Sherif Bakr

All Graduate Theses, Dissertations, and Other Capstone Projects

The motivation of this research is to obtain an accurate three-dimensional (3D) layout of an underground conduit, which may be beneficial to optic fiber cable installers and engineers. A newly designed algorithm for 3D position tracking with the help of an inertial sensor and an encoder has been developed. Two types of representations (Euler angle and Quaternion) for orientation and rotation are also introduced, followed by several data pre-processing procedures. A sensing fusion method is utilized to overcome the accumulated errors introduced by the sensor drifting. Considering the application of 3D underground duct mapping in this research, a sensing system …

A Simulation Model For Estimating Human Error Probability, Nitisha Reddy Boyapati

Theses and Dissertations

This report describes the system dynamics architecture of a simulation model which estimates human error probability for humans performing certain tasks in a given scenario. Human error probability is estimated as a function of the type of tasks performed and the number of performance shaping factors. In this work, the Standardized Plant Analysis Risk-Human (SPAR-H) reliability analysis method is utilized for estimating the probability of human error. The system dynamics simulation model captures the cause and effect relationships of the SPAR-H defined performance shaping factors that affect human error and uses them to assess the overall human error probability of …

Modeling Stochastically Intransitive Relationships In Paired Comparison Data, Ryan Patrick Alexander Mcshane

Statistical Science Theses and Dissertations

If the Warriors beat the Rockets and the Rockets beat the Spurs, does that mean that the Warriors are better than the Spurs? Sophisticated fans would argue that the Warriors are better by the transitive property, but could Spurs fans make a legitimate argument that their team is better despite this chain of evidence?

We first explore the nature of intransitive (rock-scissors-paper) relationships with a graph theoretic approach to the method of paired comparisons framework popularized by Kendall and Smith (1940). Then, we focus on the setting where all pairs of items, teams, players, or objects have been compared to …

The Global Disinformation Order: 2019 Global Inventory Of Organised Social Media Manipulation, Samantha Bradshaw, Philip N. Howard

Copyright, Fair Use, Scholarly Communication, etc.

Executive Summary

Over the past three years, we have monitored the global organization of social media manipulation by governments and political parties. Our 2019 report analyses the trends of computational propaganda and the evolving tools, capacities, strategies, and resources.

1. Evidence of organized social media manipulation campaigns which have taken place in 70 countries, up from 48 countries in 2018 and 28 countries in 2017. In each country, there is at least one political party or government agency using social media to shape public attitudes domestically.

2.Social media has become co-opted by many authoritarian regimes. In 26 countries, computational propaganda …