Digital Commons Network^™

Encasement: A Robust Method For Finding Intersections Of Semi-Algebraic Curves, Joseph Masterjohn

Open Access Theses

One of the fundamental concepts in computational geometry is deducing the combinatorial structure, or interactions, of a group of static geometric objects. In two dimensions, the objects in question include, but are not limited to: points, lines, line segments, polygons, and non-linear curves. There are various properties of interest describing a collection of such objects; examples include: distances, adjacencies, and most notably, intersections of these objects. Well studied, robust, and highly efficient algorithms exist for linear geometry and parametric curves. Problems involving non-linear, implicit, and high-dimensional objects however are an active area of research. Algebraic curves and algebraic surfaces arise …

Mapping Genetic Variations To Three-Dimensional Protein Structures To Enhance Variant Interpretation: A Proposed Framework., Gustavo Glusman, Peter W Rose, Andreas Prlić, Jennifer Dougherty, José M Duarte, Andrew S Hoffman, Geoffrey J Barton, Emøke Bendixen, Timothy Bergquist, Christian Bock, Elizabeth Brunk, Marija Buljan, Stephen K Burley, Binghuang Cai, Hannah Carter, Jianjiong Gao, Adam Godzik, Michael Heuer, Michael Hicks, Thomas Hrabe, Rachel Karchin, Julia Koehler Leman, Lydie Lane, David L Masica, Sean D Mooney, John Moult, Gilbert S Omenn, Frances Pearl, Vikas Pejaver, Sheila M Reynolds, Ariel Rokem, Torsten Schwede, Sicheng Song, Hagen Tilgner, Yana Valasatava, Yang Zhang, Eric W Deutsch

Articles, Abstracts, and Reports

The translation of personal genomics to precision medicine depends on the accurate interpretation of the multitude of genetic variants observed for each individual. However, even when genetic variants are predicted to modify a protein, their functional implications may be unclear. Many diseases are caused by genetic variants affecting important protein features, such as enzyme active sites or interaction interfaces. The scientific community has catalogued millions of genetic variants in genomic databases and thousands of protein structures in the Protein Data Bank. Mapping mutations onto three-dimensional (3D) structures enables atomic-level analyses of protein positions that may be important for the stability …

Regulating Black-Box Medicine, W. Nicholson Price Ii

Michigan Law Review

Data drive modern medicine. And our tools to analyze those data are growing ever more powerful. As health data are collected in greater and greater amounts, sophisticated algorithms based on those data can drive medical innovation, improve the process of care, and increase efficiency. Those algorithms, however, vary widely in quality. Some are accurate and powerful, while others may be riddled with errors or based on faulty science. When an opaque algorithm recommends an insulin dose to a diabetic patient, how do we know that dose is correct? Patients, providers, and insurers face substantial difficulties in identifying high-quality algorithms; they …

Automated Ecological Assessment Of Physical Activity: Advancing Direct Observation., Jordan A. Carlson, Bo Liu, James F. Sallis, Jacqueline Kerr, J Aaron Hipp, Vincent S. Staggs, Amy Papa, Kelsey Dean, Nuno M. Vasconcelos

Manuscripts, Articles, Book Chapters and Other Papers

Technological advances provide opportunities for automating direct observations of physical activity, which allow for continuous monitoring and feedback. This pilot study evaluated the initial validity of computer vision algorithms for ecological assessment of physical activity. The sample comprised 6630 seconds per camera (three cameras in total) of video capturing up to nine participants engaged in sitting, standing, walking, and jogging in an open outdoor space while wearing accelerometers. Computer vision algorithms were developed to assess the number and proportion of people in sedentary, light, moderate, and vigorous activity, and group-based metabolic equivalents of tasks (MET)-minutes. Means and standard deviations (SD) …

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 …

Artificial Intelligence In Health Care: Applications And Legal Implications, W. Nicholson Price Ii

Articles

Artificial intelligence (AI) is rapidly moving to change the healthcare system. Driven by the juxtaposition of big data and powerful machine learning techniques—terms I will explain momentarily—innovators have begun to develop tools to improve the process of clinical care, to advance medical research, and to improve efficiency. These tools rely on algorithms, programs created from healthcare data that can make predictions or recommendations. However, the algorithms themselves are often too complex for their reasoning to be understood or even stated explicitly. Such algorithms may be best described as “black-box.” This article briefly describes the concept of AI in medicine, including …

Moonlighting Newborn Screening Markers: The Incidental Discovery Of A Second-Tier Test For Pompe Disease, Silvia Tortorelli, Jason S. Eckerman, Joseph J. Orsini, Colleen Stevens, Jeremy Hart, Patricia L. Hall, John J. Alexander, Dimitar Gavrilov, Devin Oglesbee, Kimiyo Raymond, Dietrich Matern, Piero Rinaldo

Pathology and Laboratory Medicine Faculty Publications

Purpose: To describe a novel biochemical marker in dried blood spots suitable to improve the specificity of newborn screening for Pompe disease.

Methods: The new marker is a ratio calculated between the creatine/creatinine (Cre/Crn) ratio as the numerator and the activity of acid α-glucosidase (GAA) as the denominator. Using Collaborative Laboratory Integrated Reports (CLIR), the new marker was incorporated in a dual scatter plot that can achieve almost complete segregation between Pompe disease and false-positive cases.

Results: The (Cre/Crn)/GAA ratio was measured in residual dried blood spots of five Pompe cases and was found to be elevated (range 4.41–13.26; 99%ile …

Outlier Identification In Radiation Therapy Knowledge-Based Planning: A Study Of Pelvic Cases., Yang Sheng, Yaorong Ge, Lulin Yuan, Taoran Li, Fang-Fang Yin, Qingrong Jackie Wu

Department of Radiation Oncology Faculty Papers

PURPOSE: The purpose of this study was to apply statistical metrics to identify outliers and to investigate the impact of outliers on knowledge-based planning in radiation therapy of pelvic cases. We also aimed to develop a systematic workflow for identifying and analyzing geometric and dosimetric outliers.

METHODS: Four groups (G1-G4) of pelvic plans were sampled in this study. These include the following three groups of clinical IMRT cases: G1 (37 prostate cases), G2 (37 prostate plus lymph node cases) and G3 (37 prostate bed cases). Cases in G4 were planned in accordance with dynamic-arc radiation therapy procedure and include 10 …

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 …

Spring­11: Pdc In Cs1/2 And A Mobile/Cloud Intermediate Mobile/Cloud Intermediate Software Design Course, Joseph P. Kaylor, Konstantin Läufer, Chandra N. Sekharan, George K. Thiruvathukal

Konstantin Läufer

Recent changes in the environment of Loyola University Chicago’s Department of Computer Science include a better differentiation of our four undergraduate majors, growing interest in computing among science majors, and an increased demand for graduates with mobile and cloud skills. In our continued effort to incorporate parallel and distributed computing topics into the undergraduate curriculum, we are focusing on these three existing courses: CS1: In response to a request from the physics department, we started to offer a CS1 section aimed at majors in physics and other hard sciences this spring semester. This section includes some material on numerical methods …

Characterization Of Health Care Utilization In Patients Receiving Implantable Cardioverter-Defibrillator Therapies: An Analysis Of The Managed Ventricular Pacing Trial., John Rickard, David J. Whellan, Lou Sherfesee, Brett J. Peterson, Tara Nahey, Anthony S. Tang, Kenneth A. Ellenbogen, Alan Cheng

Division of Cardiology Faculty Papers

BACKGROUND: Implantable cardioverter-defibrillators (ICDs) are effective in terminating lethal arrhythmias, but little is known about the degree of health care utilization (HCU) after ICD therapies.

OBJECTIVE: Using data from the managed ventricular pacing trial, we sought to identify the incidence and types of HCU in ICD patients after receiving ICD therapy (shocks or antitachycardia pacing [ATP]).

METHODS: We analyzed HCU events (ventricular tachyarrhythmia [VTA]-related, heart failure-related, ICD implant procedure-related, ICD system-related, or other) and their association with ICD therapies (shocked ventricular tachycardia episode, ATP-terminated ventricular tachycardia episode, and inappropriately shocked episode).

RESULTS: A total of 1879 HCUs occurred in 695 …

Pursuit Evasion With Multiple Pursuers : Capturing A Ground Vehicle On A Road Network With Multiple Drones, Blake Wilson, Shreyas Sundaram, Amritha Prasad

The Summer Undergraduate Research Fellowship (SURF) Symposium

Unmanned Aerial Vehicles (UAV) have many military and civilian applications, one of which is monitoring a given area (such as a road network) for threats. An important question in this application is to determine the latest time to dispatch UAVs for the guaranteed capture of threats attempting to travel through the network. In this work, we consider a pursuit evasion scenario with multiple pursuers (UAVs) trying to catch a single evader (ground vehicle), where information about the evader’s path is provided by ground sensors. In this scenario, we consider the problem of finding the maximum delay with which the pursuers …

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 …

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 …

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 …

Multi-Mesh Reduced-Order Basis Method For Finite Element Analysis, Ashkan Akbariyeh

Mechanical and Aerospace Engineering Dissertations

Reduced order modeling of differential equations parametrized over a parameter space can be used to accelerate optimization and parameter estimation problems. The method of snapshots or reduced order basis is well established among researchers as a tool to build reduced order models of ordinary differential equations. The reduced order basis method has been utilized for numerical solution of parametric PDE problems by researchers in recent years and has many advantages over response surface methods. The application of ROB to finite element analysis has been restricted to using a fixed mesh for snapshots. In this work, a new method is developed …

Data For The Algorithm As A Human Artifact: Implications For Legal [Re]Search, Susan Nevelow Mart

Research Data

These documents underlie and are cited in this empirical study: Susan Nevelow Mart, The Algorithm as a Human Artifact: Implications for Legal [Re]Search, 109 Law Libr. J. 387, 409 n.123 (2017), available at http://scholar.law.colorado.edu/articles/755/.

The ZIP file contains three files: one PDF document ("Tables for Charts 1-3"), and two SPSS files ("Data Archive" and "Syntax Archive" (SPSS version 24)). The "Syntax Archive" file may be viewed in a text editor (e.g., Notepad) as well as in SPSS.

Appendix B: The Algorithm As A Human Artifact: Implications For Legal [Re]Search, Susan Nevelow Mart

Research Data

This document, "Search Instructions for Algorithm Study," is an electronic Appendix B to, and is cited in, the empirical study: Susan Nevelow Mart, The Algorithm as a Human Artifact: Implications for Legal [Re]Search, 109 Law Libr. J. 387, 400 n.78 (2017), available at http://scholar.law.colorado.edu/articles/755/.

Mechanism Design In Sequencing Problems., Parikshit De Dr.

Doctoral Theses

Collective decision making is an important social issue, since it depends on individual preferences that are not publicly observable. Therefore, the question is, whether it is possible to elicit the private information available to individuals and then how to extract the private information in various strategic environment; Mechanism design deals with these questions. The difference between game theory and mechanism design is that, the former tries to predict the outcome of a strategic environment in some “equilibrium” but the latter tries to design or restrict the environment in such a way that the desired objective is attained, that is, the …

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 …

Academic Packing For Commercial Fpga Architectures, Travis D. Haroldsen

Theses and Dissertations

With a few exceptions, academic packing algorithms for FPGAs are typically applied solely to theoretical architectures. This has allowed the algorithms to focus on the basic components of packing while abstracting away many of the details dictated by real hardware. As commercially available FPGAs have advanced, however, the academic algorithms and architectures have diverged significantly from their commercial counterparts. In this dissertation, the RapidSmith 2 framework is presented. This framework accurately reflects the architecture of Xilinx FPGAs and provides support for integrating custom tools into the commercial CAD tools. Using this framework, the RSVPack packing algorithm is implemented. The RSVPack …

Generalized Differential Calculus And Applications To Optimization, R. Blake Rector

Dissertations and Theses

This thesis contains contributions in three areas: the theory of generalized calculus, numerical algorithms for operations research, and applications of optimization to problems in modern electric power systems. A geometric approach is used to advance the theory and tools used for studying generalized notions of derivatives for nonsmooth functions. These advances specifically pertain to methods for calculating subdifferentials and to expanding our understanding of a certain notion of derivative of set-valued maps, called the coderivative, in infinite dimensions. A strong understanding of the subdifferential is essential for numerical optimization algorithms, which are developed and applied to nonsmooth problems in operations …

Solving The Influence Maximization Problem Reveals Regulatory Organization Of The Yeast Cell Cycle., David L Gibbs, Ilya Shmulevich

Articles, Abstracts, and Reports

The Influence Maximization Problem (IMP) aims to discover the set of nodes with the greatest influence on network dynamics. The problem has previously been applied in epidemiology and social network analysis. Here, we demonstrate the application to cell cycle regulatory network analysis for Saccharomyces cerevisiae. Fundamentally, gene regulation is linked to the flow of information. Therefore, our implementation of the IMP was framed as an information theoretic problem using network diffusion. Utilizing more than 26,000 regulatory edges from YeastMine, gene expression dynamics were encoded as edge weights using time lagged transfer entropy, a method for quantifying information transfer between variables. …

Data-Driven Discrimination At Work, Pauline T. Kim

AI-DR Collection

A data revolution is transforming the workplace. Employers are increasingly relying on algorithms to decide who gets interviewed, hired, or promoted. Although data algorithms can help to avoid biased human decision-making, they also risk introducing new sources of bias. Algorithms built on inaccurate, biased, or unrepresentative data can produce outcomes biased along lines of race, sex, or other protected characteristics. Data mining techniques may cause employment decisions to be based on correlations rather than causal relationships; they may obscure the basis on which employment decisions are made; and they may further exacerbate inequality because error detection is limited and feedback …

Energy Efficient Clustering Algorithms For Homogeneous Wireless Sensor Networks, John Robert Corn

Theses and Dissertations

Wireless sensor networks (WSNs) are systems of resource-constrained sensor nodes (SNs), distributed throughout a sensor field. Energy limitations persist due to the wireless nature of SNs and an interest in minimizing the cost and physical footprint of SNs. Due to the resource-constrained nature of SNs, much WSN research has focused on energy-efficient communication algorithms. Communication algorithms are necessary for energy-efficient data transmission between SNs and the transmission of data collected by SNs to a base station. A popular algorithm known as Low-Energy Adaptive Clustering Hierarchy (LEACH) achieves more energy-efficient communication by organizing SNs into clusters for localized communication. When SNs …

The Acttion-Aps-Aapm Pain Taxonomy (Aaapt) Multidimensional Approach To Classifying Acute Pain Conditions., Michael L Kent, Patrick J Tighe, Inna Belfer, Timothy J Brennan, Stephen Bruehl, Chad M Brummett, Chester C Buckenmaier, Asokumar Buvanendran, Robert I Cohen, Paul Desjardins, David Edwards, Roger Fillingim, Jennifer Gewandter, Debra B Gordon, Robert W Hurley, Henrik Kehlet, John D Loeser, Sean Mackey, Samuel A Mclean, Rosemary Polomano, Siamak Rahman, Srinivasa Raja, Michael Rowbotham, Santhanam Suresh, Bernard Schachtel, Kristin Schreiber, Mark Schumacher, Brett Stacey, Steven P Stanos, Knox Todd, Dennis C Turk, Steven J Weisman, Christopher Wu, Daniel B Carr, Robert H Dworkin, Gregory Terman

Articles, Abstracts, and Reports

Objective: With the increasing societal awareness of the prevalence and impact of acute pain, there is a need to develop an acute pain classification system that both reflects contemporary mechanistic insights and helps guide future research and treatment. Existing classifications of acute pain conditions are limiting, with a predominant focus on the sensory experience (e.g., pain intensity) and pharmacologic consumption. Consequently, there is a need to more broadly characterize and classify the multidimensional experience of acute pain.

Setting: Consensus report following expert panel involving the Analgesic, Anesthetic, and Addiction Clinical Trial Translations, Innovations, Opportunities, and Networks (ACTTION), American Pain Society …

Crowd Data Analytics And Optimization, Habibur Rahman

Computer Science and Engineering Dissertations

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 …

A Comment On Privacy And Accountability In Black-Box Medicine, Carl E. Schneider

Michigan Telecommunications & Technology Law Review

Human institutions and activities cannot avoid failures. Anxiety about them often provokes governments to try to prevent those failures. When that anxiety is vivid and urgent, government may do so without carefully asking whether regulation’s costs justify their benefits. Privacy and Accountability in Black Box Medicine admirably labors to bring discipline and rationality to thinking about an important development — the rise of “black-box medicine” — before it causes injuries regulation should have prevented and before it is impaired by improvident regulation. That is, Privacy and Accountability weighs the costs against the benefits of various forms of regulation across the …

The Racist Algorithm?, Anupam Chander

Michigan Law Review

Review of The Black Box Society: The Secret Algorithms That Control Money and Information by Frank Pasquale.