Computer Sciences Commons^™

On Hybrid Temporal Basis Functions For Stable Numerical Solution Of Time Domain Boundary Integral Equations, Fang Q. Hu

Mathematics & Statistics Faculty Publications

Problems in unsteady aerodynamics and aeroacoustics can sometimes be formulated as integral equations, such as the boundary integral equations. Numerical discretization of integral equations in the time domain often leads to so-called March-On-in-Time (MOT) schemes. In the literature, the temporal basis functions used in MOT schemes have been largely limited to low-order shifted Lagrange basis functions. In order to evaluate the accuracy and effectiveness of the temporal basis functions, a Fourier analysis of the temporal interpolation schemes is carried out. Based on the Fourier analysis, the spectral resolutions of various temporal basis functions are quantified. It is argued that hybrid …

Crazy Sequential Representations Of Numbers For Small Bases, Tim Wylie

Computer Science Faculty Publications

Throughout history, recreational mathematics has always played a prominent role in advancing research. Following in this tradition, in this paper we extend some recent work with crazy sequential representations of numbers− equations made of sequences of one through nine (or nine through one) that evaluate to a number. All previous work on this type of puzzle has focused only on base ten numbers and whether a solution existed. We generalize this concept and examine how this extends to arbitrary bases, the ranges of possible numbers, the combinatorial challenge of finding the numbers, efficient algorithms, and some interesting patterns across any …

Zero-Knowledge De Novo Algorithms For Analyzing Small Molecules Using Mass Spectrometry, Patrick Anthony Kreitzberg

Graduate Student Theses, Dissertations, & Professional Papers

In the analysis of mass spectra, if a superset of the molecules thought to be in a sample is known a priori, then there are well established techniques for the identification of the molecules such as database search and spectral libraries. Linear molecules are chains of subunits. For example, a peptide is a linear molecule with an “alphabet” of 20 possible amino acid subunits. A peptide of length six will have 20⁶ = 64, 000, 000 different possible outcomes. Small molecules, such as sugars and metabolites, are not constrained to linear structures and may branch. These molecules are …

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 …

Electroencephalogram (Eeg) For Delineating Objective Measure Of Autism Spectrum Disorder, Sampath Jayarathna, Yasith Jayawardana, Mark Jaime, Sashi Thapaliya

Computer Science Faculty Publications

Autism spectrum disorder (ASD) is a developmental disorder that often impairs a child's normal development of the brain. According to CDC, it is estimated that 1 in 6 children in the US suffer from development disorders, and 1 in 68 children in the US suffer from ASD. This condition has a negative impact on a person's ability to hear, socialize, and communicate. Subjective measures often take more time, resources, and have false positives or false negatives. There is a need for efficient objective measures that can help in diagnosing this disease early as possible with less effort. EEG measures the …

Validation Study Of Image Recognition Algorithms, Jacob Miller, Jeremy Evert

Student Research

Developments in machine learning in recent years have created opportunities that previously never existed. One such field with an explosion of opportunity is image recognition, also known as computer vision; the process in which a machine analyzes a digital image.

In order for a machine to ‘see’ as a human does, it must break down the image in a process called image segmentation. The way the machine goes about doing this is important, and many algorithms exist to determine just how a machine will decide to group the pixels in an image.

This research is a validation study of related …

Phase Contrast Time-Lapse Microscopy Datasets With Automated And Manual Cell Tracking Annotations, Dai Fei Elmer Ker, Zhaozheng Yin, For Full List Of Authors, See Publisher's Website.

Computer Science Faculty Research & Creative Works

Phase contrast time-lapse microscopy is a non-destructive technique that generates large volumes of image-based information to quantify the behaviour of individual cells or cell populations. To guide the development of algorithms for computer-aided cell tracking and analysis, 48 time-lapse image sequences, each spanning approximately 3.5 days, were generated with accompanying ground truths for C2C12 myoblast cells cultured under 4 different media conditions, including with fibroblast growth factor 2 (FGF2), bone morphogenetic protein 2 (BMP2), FGF2 + BMP2, and control (no growth factor). The ground truths generated contain information for tracking at least 3 parent cells and their descendants within these …

Improving Time And Space Efficiency Of Trie Data Structure, Nirmik Milind Kale

Computer Science and Engineering Theses - Archive

Trie or prefix tree is a data structure that has been used widely in some applications such as prefix-matching, auto-complete suggestions, and IP routing tables for a long time. What makes tries even more interesting is that its time complexity is dependent on the length of the keys inserted or searched in the trie, instead of on the total number of keys in the data structure. Tries are also strong contenders to consider against hash tables in various applications due to two reasons - their almost deterministic time complexity based on average key length, especially when using large number of …

Algorithms For Exploratory Queries Over Web Database, Md Farhadur Rahman

Computer Science and Engineering Dissertations - Archive

In recent years we have seen an increase in the popularity of many web applications. The functionality of these applications range from allowing users to interact using online social network, to assist users in their everyday activity such as selecting a hotel in an area, locating a nearby restaurant etc. Google Maps, WeChat, FourSquare, AirBnB, TripAdvisor, and Hotels.com are a few such examples. The backed database of these applications can be a rich source of information for the corresponding application domain. For example, using Google Maps a user can find the ratings, reviews, and price of a restaurant, using Zillow …

Offensive And Defensive Security For Everyday Computer Systems, Ian Markwood

USF Tampa Graduate Theses and Dissertations

This dissertation treats a variety of topics in the computer security domain which have direct impact on everyday life. The first extends false data injection attacks against state estimation in electric power grids and then provides a novel power flow model camouflage method to hamper these attacks. The second deals with automotive theft response, detailing a method for a car to intelligently identify when it has been stolen, based on collected behavioral traits of its driver. The third demonstrates a new attack against the content integrity of the PDF file format, caus- ing humans and computers to see different information …

Geometric Algorithms For Intervals And Related Problems, Shimin Li

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

In this dissertation, we study several problems related to intervals and develop efficient algorithms for them. Interval problems have many applications in reality because many objects, values, and ranges are intervals in nature, such as time intervals, distances, line segments, probabilities, etc. Problems on intervals are gaining attention also because intervals are among the most basic geometric objects, and for the same reason, computational geometry techniques find useful for attacking these problems. Specifically, the problems we study in this dissertation includes the following: balanced splitting on weighted intervals, minimizing the movements of spreading points, dispersing points on intervals, multiple barrier …

Application Of Cosine Similarity In Bioinformatics, Srikanth Maturu

School of Computing: Dissertations, Theses, and Student Research

Finding similar sequences to an input query sequence (DNA or proteins) from a sequence data set is an important problem in bioinformatics. It provides researchers an intuition of what could be related or how the search space can be reduced for further tasks. An exact brute-force nearest-neighbor algorithm used for this task has complexity O(m * n) where n is the database size and m is the query size. Such an algorithm faces time-complexity issues as the database and query sizes increase. Furthermore, the use of alignment-based similarity measures such as minimum edit distance adds an additional complexity to the …

A Legal Perspective On The Trials And Tribulations Of Ai: How Artificial Intelligence, The Internet Of Things, Smart Contracts, And Other Technologies Will Affect The Law, Iria Giuffrida, Fredric Lederer, Nicolas Vermeys

Faculty Publications

No abstract provided.

Opportunity Identification For New Product Planning: Ontological Semantic Patent Classification, Farshad Madani

Dissertations and Theses

Intelligence tools have been developed and applied widely in many different areas in engineering, business and management. Many commercialized tools for business intelligence are available in the market. However, no practically useful tools for technology intelligence are available at this time, and very little academic research in technology intelligence methods has been conducted to date.

Patent databases are the most important data source for technology intelligence tools, but patents inherently contain unstructured data. Consequently, extracting text data from patent databases, converting that data to meaningful information and generating useful knowledge from this information become complex tasks. These tasks are currently …

Auditing Snomed Ct Hierarchical Relations Based On Lexical Features Of Concepts In Non-Lattice Subgraphs, Licong Cui, Olivier Bodenreider, Jay Shi, Guo-Qiang Zhang

Computer Science Faculty Publications

Objective—We introduce a structural-lexical approach for auditing SNOMED CT using a combination of non-lattice subgraphs of the underlying hierarchical relations and enriched lexical attributes of fully specified concept names. Our goal is to develop a scalable and effective approach that automatically identifies missing hierarchical IS-A relations.

Methods—Our approach involves 3 stages. In stage 1, all non-lattice subgraphs of SNOMED CT’s IS-A hierarchical relations are extracted. In stage 2, lexical attributes of fully-specified concept names in such non-lattice subgraphs are extracted. For each concept in a non-lattice subgraph, we enrich its set of attributes with attributes from its ancestor …

The Accuracy, Fairness, And Limits Of Predicting Recidivism, Julie Dressel, Hany Farid

Dartmouth Scholarship

Algorithms for predicting recidivism are commonly used to assess a criminal defendant’s likelihood of committing a crime. These predictions are used in pretrial, parole, and sentencing decisions. Proponents of these systems argue that big data and advanced machine learning make these analyses more accurate and less biased than humans. We show, however, that the widely used commercial risk assessment software COMPAS is no more accurate or fair than predictions made by people with little or no criminal justice expertise. We further show that a simple linear predictor provided with only two features is nearly equivalent to COMPAS with its 137 …

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 …

Equity Trading Evaluation Strategies In Switzerland After The European Mifid Ii, Linn Kristina Karstadt

Walden Dissertations and Doctoral Studies

Swiss bank traders are affected by technological and regulatory challenges, which may affect their broker voting process and may result in a change of trading and evaluation behavior in 2018. Compounded challenges exist when broker evaluation strategies are not effective or Markets in Financial Instruments Directive (MiFID) II compliant. This qualitative, single case study, built on efficient capital market hypothesis and innovative disruption theory, was focused on effective broker evaluation strategies after MiFID II in Switzerland. The sample consisted of 4 buy-side traders, who shared their unique perspectives. Methodological triangulation was achieved through semistructured interviews, a review of the institution's …

A Selective-Discrete Particle Swarm Optimization Algorithm For Solving A Class Of Orienteering Problems, Aldy Gunawan, Vincent F. Yu, Perwira Redi, Parida Jewpanya, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

This study addresses a class of NP-hard problem called the Orienteering Problem (OP), which belongs to a well-known class of vehicle routing problems. In the OP, a set of nodes that associated with a location and a score is given. The time required to travel between each pair of nodes is known in advance. The total travel time is limited by a predetermined time budget. The objective is to select a subset of nodes to be visited that maximizes the total collected score within a path. The Team OP (TOP) is an extension of OP that incorporates multiple paths. Another …

Temporal Understanding Of Human Mobility: A Multi-Time Scale Analysis, Tongtong Liu, Zheng Yang, Yi Zhao, Chenshu Wu, Zimu Zhou, Yunhao Liu

Research Collection School Of Computing and Information Systems

The recent availability of digital traces generated by cellphone calls has significantly increased the scientific understanding of human mobility. Until now, however, based on low time resolution measurements, previous works have ignored to study human mobility under various time scales due to sparse and irregular calls, particularly in the era of mobile Internet. In this paper, we introduced Mobile Flow Records, flow-level data access records of online activity of smartphone users, to explore human mobility. Mobile Flow Records collect high-resolution information of large populations. By exploiting this kind of data, we show the models and statistics of human mobility at …

Registration And Grouping Algorithms In Protein Nmr Derived Peak Lists And Their Application In Protein Nmr Reference Correction, Andrey Smelter, Xi Chen, Eric C. Rouchka, Hunter N. B. Moseley

Commonwealth Computational Summit

Nuclear magnetic resonance spectroscopy of proteins (protein NMR) is a powerful analytical technique for studying structure and dynamics of proteins. Almost all aspects of protein NMR have been accelerated by the development of software tools that enable the analysis of NMR spectral data and its utilization in studying protein structure and dynamics. This includes software for raw NMR processing, spectral visualization, protein resonance assignment, and structure determination. However, full automation of protein NMR data analysis is still a work in progress and data analysis still requires an expert NMR spectroscopist utilizing an array of software tools.

While manual resonance assignment …

Detecting And Accounting For Multiple Sources Of Positional Variance In Peak List Registration Analysis And Spin System Grouping, Andrey Smelter, Eric C. Rouchka, Hunter N. B. Moseley

Molecular and Cellular Biochemistry Faculty Publications

Peak lists derived from nuclear magnetic resonance (NMR) spectra are commonly used as input data for a variety of computer assisted and automated analyses. These include automated protein resonance assignment and protein structure calculation software tools. Prior to these analyses, peak lists must be aligned to each other and sets of related peaks must be grouped based on common chemical shift dimensions. Even when programs can perform peak grouping, they require the user to provide uniform match tolerances or use default values. However, peak grouping is further complicated by multiple sources of variance in peak position limiting the effectiveness of …

Geometric Facility Location Problems On Uncertain Data, Jingru Zhang

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

In this dissertation, we study several facility location problems on uncertain data. We mainly consider the k-center problem and many of its variations. These are classical problems in computer science and operations research. These problems on deterministic data have been studied extensively in the literature. We consider them on uncertain data because data in the real world is often associated with uncertainty due to measurement inaccuracy, sampling discrepancy, outdated data sources, resource limitation, etc. Although we focus on the theoretical study, the algorithms developed in this dissertation may find applications in other areas such as data clustering, wireless sensor …

Accelerating Dynamic Graph Analytics On Gpus, Mo Shan, Yuchen Li, Bingsheng He, Kian-Lee Tan

Research Collection School Of Computing and Information Systems

As graph analytics often involves compute-intensive operations,GPUs have been extensively used to accelerate the processing. However, in many applications such as social networks, cyber security, and fraud detection, their representative graphs evolve frequently and one has to perform are build of the graph structure on GPUs to incorporate the updates. Hence, rebuilding the graphs becomes the bottleneck of processing high-speed graph streams. In this paper,we propose a GPU-based dynamic graph storage scheme to support existing graph algorithms easily. Furthermore,we propose parallel update algorithms to support efficient stream updates so that the maintained graph is immediately available for high-speed analytic processing …

Os2: Oblivious Similarity Based Searching For Encrypted Data Outsourced To An Untrusted Domain, Zeeshan Pervez, Mahmood Ahmad, Asad Masood Khattak, Naeem Ramzan, Wajahat Ali Khan

All Works

© 2017 Pervez et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Public cloud storage services are becoming prevalent and myriad data sharing, archiving and collaborative services have emerged which harness the pay-as-you-go business model of public cloud. To ensure privacy and confidentiality often encrypted data is outsourced to such services, which further complicates the process of accessing relevant data by using search queries. Search over encrypted data schemes solve this problem by …

Crowd Data Analytics And Optimization, Habibur Rahman

Computer Science and Engineering Dissertations - Archive

Crowdsourcing can be defined as outsourcing with crowd, where crowd refers to the online workers who are willing to complete simple tasks for small monetary compensation. The overwhelming reach of internet has enabled us to exploit crowd in an unprecedented way. Crowdsourcing, nowadays, is considered as a tool to solve both simple tasks (such as labeling ground truth, image recognition etc.) and complex tasks (such as collaborative writing, citizen journalism etc.). Furthermore, it is also used to solve computational problems such as Entity Resolution, Top-k, Group-by etc. While crowdsourcing provides us with plenty of opportunities, it also presents us with …

Satellite Detection And Ranging System, A S M Sarwar Zahan

Theses and Dissertations

The thrust on Nano-satellite technologies is increasing day by day. Research is going on to detect satellites in austere environment. However, the technology of tracking the satellite in both in-formation and out of formation is yet to discover. I propose a novel algorithm to detect satellites in regular orbit and even in different close operations, i.e. docking, inspection and rendezvous. I aim to modify two existing and promising image processing algorithms and apply towards my own satellite detection problem. Various image processing algorithms have incorporated to enable tracking of the Target Flight Unit (T-FU) from the Chase Flight Unit (C-FU). …

Certifying Loop Pipelining Transformations In Behavioral Synthesis, Disha Puri

Dissertations and Theses

Due to the rapidly increasing complexity in hardware designs and competitive time to market trends in the industry, there is an inherent need to move designs to a higher level of abstraction. Behavioral Synthesis is the process of automatically compiling such Electronic System Level (ESL) designs written in high-level languages such as C, C++ or SystemC into Register-Transfer Level (RTL) implementation in hardware description languages such as Verilog or VHDL. However, the adoption of this flow is dependent on designers' faith in the correctness of behavioral synthesis tools.

Loop pipelining is a critical transformation employed in behavioral synthesis process, and …

Incorporating A Spatial Prior Into Nonlinear D-Bar Eit Imaging For Complex Admittivities, Sarah J. Hamilton, Jennifer L. Mueller, Melody Alsaker

Mathematics, Statistics and Computer Science Faculty Research and Publications

Electrical Impedance Tomography (EIT) aims to recover the internal conductivity and permittivity distributions of a body from electrical measurements taken on electrodes on the surface of the body. The reconstruction task is a severely ill-posed nonlinear inverse problem that is highly sensitive to measurement noise and modeling errors. Regularized D-bar methods have shown great promise in producing noise-robust algorithms by employing a low-pass filtering of nonlinear (nonphysical) Fourier transform data specific to the EIT problem. Including prior data with the approximate locations of major organ boundaries in the scattering transform provides a means of extending the radius of the low-pass …

Normal Surfaces And 3-Manifold Algorithms, Josh D. Hews

Honors Theses

This survey will develop the theory of normal surfaces as they apply to the S3 recognition algorithm. Sections 2 and 3 provide necessary background on manifold theory. Section 4 presents the theory of normal surfaces in triangulations of 3-manifolds. Section 6 discusses issues related to implementing algorithms based on normal surfaces, as well as an overview of the Regina, a program that implements many 3-manifold algorithms. Finally section 7 presents the proof of the 3-sphere recognition algorithm and discusses how Regina implements the algorithm.