Theory and Algorithms Commons^™

Ultra-Fast And Memory-Efficient Lookups For Cloud, Networked Systems, And Massive Data Management, Ye Yu

Theses and Dissertations--Computer Science

Systems that process big data (e.g., high-traffic networks and large-scale storage) prefer data structures and algorithms with small memory and fast processing speed. Efficient and fast algorithms play an essential role in system design, despite the improvement of hardware. This dissertation is organized around a novel algorithm called Othello Hashing. Othello Hashing supports ultra-fast and memory-efficient key-value lookup, and it fits the requirements of the core algorithms of many large-scale systems and big data applications. Using Othello hashing, combined with domain expertise in cloud, computer networks, big data, and bioinformatics, I developed the following applications that resolve several major …

Applying Machine Learning To Advance Cyber Security: Network Based Intrusion Detection Systems, Hassan Hadi Latheeth Al-Maksousy

Computer Science Theses & Dissertations

Many new devices, such as phones and tablets as well as traditional computer systems, rely on wireless connections to the Internet and are susceptible to attacks. Two important types of attacks are the use of malware and exploiting Internet protocol vulnerabilities in devices and network systems. These attacks form a threat on many levels and therefore any approach to dealing with these nefarious attacks will take several methods to counter. In this research, we utilize machine learning to detect and classify malware, visualize, detect and classify worms, as well as detect deauthentication attacks, a form of Denial of Service (DoS). …

An Iterated Local Search Algorithm For The Team Orienteering Problem With Variable Profits, Aldy Gunawan, Kien Ming Ng, Graham Kendall, Junhan Lai

Research Collection School Of Computing and Information Systems

The orienteering problem (OP) is a routing problem that has numerous applications in various domains such as logistics and tourism. The objective is to determine a subset of vertices to visit for a vehicle so that the total collected score is maximized and a given time budget is not exceeded. The extensive application of the OP has led to many different variants, including the team orienteering problem (TOP) and the team orienteering problem with time windows. The TOP extends the OP by considering multiple vehicles. In this article, the team orienteering problem with variable profits (TOPVP) is studied. The main …

Intersection Of Art And Science Ii, Petronio Bendito, Tim Korb

Lawson Building Exhibitions on the Intersection of Art and Science

The Intersection of Art and Science exhibition is an interdisciplinary educational project that examines a wide range of expressive approaches explored by international artists working at the intersection of art, mathematics, computer science, and technology. It is a joint collaboration between the Department of Computer Science and the Patti and Rusty Rueff School of Visual and Performing Arts at Purdue University. Featured artists: Manuel Baez, Sarah Berube, Robert Bosch, Sage Jenson, Jean-Marc Castera, Marc Chamberland, Marion Chamberland, Laura De Decker, Bathsheba Grossman, Colin Liotta, Vincent J. Matsko, Kerry Mitchell, Janna Schimka, Rolf Schmuck, and Markus Schwehm. The exhibition was curated …

Evaluating A Cluster Of Low-Power Arm64 Single-Board Computers With Mapreduce, Daniel Mcdermott

EWU Masters Thesis Collection

With the meteoric rise of enormous data collection in science, industry, and the cloud, methods for processing massive datasets have become more crucial than ever. MapReduce is a restricted programing model for expressing parallel computations as simple serial functions, and an execution framework for distributing those computations over large datasets residing on clusters of commodity hardware. MapReduce abstracts away the challenging low-level synchronization and scalability details which parallel and distributed computing often necessitate, reducing the concept burden on programmers and scientists who require data processing at-scale. Typically, MapReduce clusters are implemented using inexpensive commodity hardware, emphasizing quantity over quality due …

High-Order Integral Equation Methods For Quasi-Magnetostatic And Corrosion-Related Field Analysis With Maritime Applications, Robert Pfeiffer

Theses and Dissertations--Electrical and Computer Engineering

This dissertation presents techniques for high-order simulation of electromagnetic fields, particularly for problems involving ships with ferromagnetic hulls and active corrosion-protection systems.

A set of numerically constrained hexahedral basis functions for volume integral equation discretization is presented in a method-of-moments context. Test simulations demonstrate the accuracy achievable with these functions as well as the improvement brought about in system conditioning when compared to other basis sets.

A general method for converting between a locally-corrected Nyström discretization of an integral equation and a method-of-moments discretization is presented next. Several problems involving conducting and magnetic-conducting materials are solved to verify the accuracy …

Smartphone User Privacy Preserving Through Crowdsourcing, Bahman Rashidi

Theses and Dissertations

In current Android architecture, users have to decide whether an app is safe to use or not. Expert users can make savvy decisions to avoid unnecessary private data breach. However, the majority of regular users are not technically capable or do not care to consider privacy implications to make safe decisions. To assist the technically incapable crowd, we propose a permission control framework based on crowdsourcing. At its core, our framework runs new apps under probation mode without granting their permission requests up-front. It provides recommendations on whether to accept or not the permission requests based on decisions from peer …

Estimating The Respiratory Lung Motion Model Using Tensor Decomposition On Displacement Vector Field, Kingston Kang

Theses and Dissertations

Modern big data often emerge as tensors. Standard statistical methods are inadequate to deal with datasets of large volume, high dimensionality, and complex structure. Therefore, it is important to develop algorithms such as low-rank tensor decomposition for data compression, dimensionality reduction, and approximation.

With the advancement in technology, high-dimensional images are becoming ubiquitous in the medical field. In lung radiation therapy, the respiratory motion of the lung introduces variabilities during treatment as the tumor inside the lung is moving, which brings challenges to the precise delivery of radiation to the tumor. Several approaches to quantifying this uncertainty propose using a …

Logic -> Proof -> Rest, Maxwell Taylor

Senior Independent Study Theses

REST is a common architecture for networked applications. Applications that adhere to the REST constraints enjoy significant scaling advantages over other architectures. But REST is not a panacea for the task of building correct software. Algebraic models of computation, particularly CSP, prove useful to describe the composition of applications using REST. CSP enables us to describe and verify the behavior of RESTful systems. The descriptions of each component can be used independently to verify that a system behaves as expected. This thesis demonstrates and develops CSP methodology to verify the behavior of RESTful applications.

Big Networks: Analysis And Optimal Control, Hung The Nguyen

Theses and Dissertations

The study of networks has seen a tremendous breed of researches due to the explosive spectrum of practical problems that involve networks as the access point. Those problems widely range from detecting functionally correlated proteins in biology to finding people to give discounts and gain maximum popularity of a product in economics. Thus, understanding and further being able to manipulate/control the development and evolution of the networks become critical tasks for network scientists. Despite the vast research effort putting towards these studies, the present state-of-the-arts largely either lack of high quality solutions or require excessive amount of time in real-world …

A Parallel Mesh Generator In 3d/4d, Kirill Voronin

Portland Institute for Computational Science Publications

In the report a parallel mesh generator in 3d/4d is presented. The mesh generator was developed as a part of the research project on space-time discretizations for partial differential equations in the least-squares setting. The generator is capable of constructing meshes for space-time cylinders built on an arbitrary 3d space mesh in parallel. The parallel implementation was created in the form of an extension of the finite element software MFEM. The code is publicly available in the Github repository

Algorithmic Issues In Some Disjoint Clustering Problems In Combinatorial Circuits, Zola Nailah Donovan

Graduate Theses, Dissertations, and Problem Reports (ETD)

As the modern integrated circuit continues to grow in complexity, the design of very large-scale integrated (VLSI) circuits involves massive teams employing state-of-the-art computer-aided design (CAD) tools. An old, yet significant CAD problem for VLSI circuits is physical design automation. In this problem, one needs to compute the best physical layout of millions to billions of circuit components on a tiny silicon surface. The process of mapping an electronic design to a chip involves several physical design stages, one of which is clustering. Even for combinatorial circuits, there exist several models for the clustering problem. In particular, we consider the …

Dynamic Output Feedback Invariants Of Full Relative Degree Nonlinear Siso Systems, W. Steven Gray, Luis A. Duffaut Espinosa

Electrical & Computer Engineering Faculty Publications

The goal of this paper is to explicitly describe invariants of a plant described by a Chen--Fliess series under a class of dynamic output feedback laws using earlier work by the authors on feedback transformation groups. The main result requires the rather strong assumption that the plant has a generating series with both finite Lie rank and full relative degree. In which case, there is no loss of generality in working with state space realizations of the plant. An additional genericness assumption regarding the normal form of the plant is also required, but as shown by the examples, this condition …

Offline And Online Density Estimation For Large High-Dimensional Data, Aref Majdara

Dissertations, Master's Theses and Master's Reports

Density estimation has wide applications in machine learning and data analysis techniques including clustering, classification, multimodality analysis, bump hunting and anomaly detection. In high-dimensional space, sparsity of data in local neighborhood makes many of parametric and nonparametric density estimation methods mostly inefficient.

This work presents development of computationally efficient algorithms for high-dimensional density estimation, based on Bayesian sequential partitioning (BSP). Copula transform is used to separate the estimation of marginal and joint densities, with the purpose of reducing the computational complexity and estimation error. Using this separation, a parallel implementation of the density estimation algorithm on a 4-core CPU is …

Fast Identification Of High Utility Itemsets From Candidates, Jun-Feng Qu, Mengchi Liu, Chunsheng Xin, Zhongbo Wu

Electrical & Computer Engineering Faculty Publications

High utility itemsets (HUIs) are sets of items with high utility, like profit, in a database. Efficient mining of high utility itemsets is an important problem in the data mining area. Many mining algorithms adopt a two-phase framework. They first generate a set of candidate itemsets by roughly overestimating the utilities of all itemsets in a database, and subsequently compute the exact utility of each candidate to identify HUIs. Therefore, the major costs in these algorithms come from candidate generation and utility computation. Previous works mainly focus on how to reduce the number of candidates, without dedicating much attention to …

Resource Optimization In Wireless Sensor Networks For An Improved Field Coverage And Cooperative Target Tracking, Husam Sweidan

Dissertations, Master's Theses and Master's Reports

There are various challenges that face a wireless sensor network (WSN) that mainly originate from the limited resources a sensor node usually has. A sensor node often relies on a battery as a power supply which, due to its limited capacity, tends to shorten the life-time of the node and the network as a whole. Other challenges arise from the limited capabilities of the sensors/actuators a node is equipped with, leading to complication like a poor coverage of the event, or limited mobility in the environment. This dissertation deals with the coverage problem as well as the limited power and …

Implementing Write Compression In Flash Memory Using Zeckendorf Two-Round Rewriting Codes, Vincent T. Druschke

Dissertations, Master's Theses and Master's Reports

Flash memory has become increasingly popular as the underlying storage technology for high-performance nonvolatile storage devices. However, while flash offers several benefits over alternative storage media, a number of limitations still exist within the current technology. One such limitation is that programming (altering a bit from its default value) and erasing (returning a bit to its default value) are asymmetric operations in flash memory devices: a flash memory can be programmed arbitrarily, but can only be erased in relatively large batches of storage bits called blocks, with block sizes ranging from 512K up to several megabytes. This creates a situation …

Process Models Discovery And Traces Classification: A Fuzzy-Bpmn Mining Approach., Kingsley Okoye Dr, Usman Naeem Dr, Syed Islam Dr, Abdel-Rahman H. Tawil Dr, Elyes Lamine Dr

Journal of International Technology and Information Management

The discovery of useful or worthwhile process models must be performed with due regards to the transformation that needs to be achieved. The blend of the data representations (i.e data mining) and process modelling methods, often allied to the field of Process Mining (PM), has proven to be effective in the process analysis of the event logs readily available in many organisations information systems. Moreover, the Process Discovery has been lately seen as the most important and most visible intellectual challenge related to the process mining. The method involves automatic construction of process models from event logs about any domain …

Design And Implementation Of A Stand-Alone Tool For Metabolic Simulations, Milad Ghiasi Rad

School of Computing: Dissertations, Theses, and Student Research

In this thesis, we present the design and implementation of a stand-alone tool for metabolic simulations. This system is able to integrate custom-built SBML models along with external user’s input information and produces the estimation of any reactants participating in the chain of the reactions in the provided model, e.g., ATP, Glucose, Insulin, for the given duration using numerical analysis and simulations. This tool offers the food intake arguments in the calculations to consider the personalized metabolic characteristics in the simulations. The tool has also been generalized to take into consideration of temporal genomic information and be flexible for simulation …

Optimal Layout For A Component Grid, Michael W. Ebert

Computer Science and Software Engineering

Several puzzle games include a specific type of optimization problem: given components that produce and consume different resources and a grid of squares, find the optimal way to place the components to maximize output. I developed a method to evaluate potential solutions quickly and automated the solving of the problem using a genetic algorithm.