Computer Sciences Commons^™

Ai Education: Deep Neural Network Learning Resources, Todd W. Neller

Computer Science Faculty Publications

In this column, we focus on resources for learning and teaching deep neural network learning. Many exciting advances have been made in this area of late, and so many resources have become available online that the flood of relevant concepts and techniques can be overwhelming. Here, we hope to provide a sampling of high-quality resources to guide the newcomer into this booming field. [excerpt]

Cse: U: Mixed-Initiative Personal Assistant Agents, Joshua W. Buck, Saverio Perugini, Tam Nguyen

Computer Science Faculty Publications

Specification and implementation of flexible human-computer dialogs is challenging because of the complexity involved in rendering the dialog responsive to a vast number of varied paths through which users might desire to complete the dialog. To address this problem, we developed a toolkit for modeling and implementing task-based, mixed-initiative dialogs based on metaphors from lambda calculus. Our toolkit can automatically operationalize a dialog that involves multiple prompts and/or sub-dialogs, given a high-level dialog specification of it. The use of natural language with the resulting dialogs makes the flexibility in communicating user utterances commensurate with that in dialog completion paths—an aspect …

Universal Shape Replicators Via Self-Assembly With Attractive And Repulsive Forces, Cameron Chalk, Erik D. Demaine, Martin L. Demaine, Eric Martinez, Robert Schweller, Luis Vega, Tim Wylie

Computer Science Faculty Publications

We show how to design a universal shape replicator in a self- assembly system with both attractive and repulsive forces. More precisely, we show that there is a universal set of constant-size objects that, when added to any unknown holefree polyomino shape, produces an unbounded number of copies of that shape (plus constant-size garbage objects). The constant-size objects can be easily constructed from a constant number of individual tile types using a constant number of preprocessing self-assembly steps. Our construction uses the well-studied 2-Handed Assembly Model (2HAM) of tile self-assembly, in the simple model where glues interact only with identical …

Impact Of Uri Canonicalization On Memento Count, Mat Kelly, Lulwah M. Alkwai, Michael L. Nelson, Michele C. Weigle, Herbert Van De Sompel

Computer Science Faculty Publications

Quantifying the captures of a URI over time is useful for researchers to identify the extent to which a Web page has been archived. Memento TimeMaps provide a format to list mementos (URI-Ms) for captures along with brief metadata, like Memento-Datetime, for each URI-M. However, when some URI-Ms are dereferenced, they simply provide a redirect to a different URI-M (instead of a unique representation at the datetime), often also present in the TimeMap. This infers that confidently obtaining an accurate count quantifying the number of non-forwarding captures for a URI-R is not possible using a TimeMap alone and that the …

Modeling Beta-Traces For Beta-Barrels From Cryo-Em Density Maps, Dong Si, Jing He

Computer Science Faculty Publications

Cryo-electron microscopy (cryo-EM) has produced density maps of various resolutions. Although ά-helices can be detected from density maps at 5-8 angstrom resolutions, β-strands are challenging to detect at such density maps due to close-spacing of β-strands. The variety of shapes of β-sheets adds the complexity of β-strands detection from density maps. We propose a new approach to model traces of β-strands for β-barrel density regions that are extracted from cryo-EM density maps. In the test containing eight β-barrels extracted from experimental cryo-EM density maps at 5.5 angstrom-8.25 angstrom resolution, StrandRoller detected about 74.26% of the amino acids in the β-strands …

Homeomorphic Tetrahedralization Of Multi-Material Images With Quality And Fidelity Guarantees, Jing Xu, Andrey N. Chernikov

Computer Science Faculty Publications

We present a novel algorithm for generating three-dimensional unstructured tetrahedral meshes of multi-material images. The algorithm produces meshes with high quality since it provides a guaranteed dihedral angle bound of up to 19.47° for the output tetrahedra. In addition, it allows for user-specified guaranteed bounds on the two-sided Hausdorff distance between the boundaries of the mesh and the boundaries of the materials. Moreover, the mesh boundary is proved to be homeomorphic to the object surface. The algorithm is fast and robust, it produces a sufficiently small number of mesh elements that comply with these guarantees, as compared to other software. …

An Effective Computational Method Incorporating Multiple Secondary Structure Predictions In Topology Determination For Cryo-Em Images, Abhishek Biswas, Desh Ranjan, Mohammad Zubair, Stephanie Zeil, Kamal Al Nasr, Jing He

Computer Science Faculty Publications

A key idea in de novo modeling of a medium-resolution density image obtained from cryo-electron microscopy is to compute the optimal mapping between the secondary structure traces observed in the density image and those predicted on the protein sequence. When secondary structures are not determined precisely, either from the image or from the amino acid sequence of the protein, the computational problem becomes more complex. We present an efficient method that addresses the secondary structure placement problem in presence of multiple secondary structure predictions and computes the optimal mapping. We tested the method using 12 simulated images from alpha-proteins and …

Comparing An Atomic Model Or Structure To A Corresponding Cryo-Electron Microscopy Image At The Central Axis Of A Helix, Stephanie Zeil, Julio Kovacs, Willy Wriggers, Jing He

Computer Science Faculty Publications

Three-dimensional density maps of biological specimens from cryo-electron microscopy (cryo-EM) can be interpreted in the form of atomic models that are modeled into the density, or they can be compared to known atomic structures. When the central axis of a helix is detectable in a cryo-EM density map, it is possible to quantify the agreement between this central axis and a central axis calculated from the atomic model or structure. We propose a novel arc-length association method to compare the two axes reliably. This method was applied to 79 helices in simulated density maps and six case studies using cryo-EM …

Efficient Core Utilization In A Hybrid Parallel Delaunay Meshing Algorithm On Distributed-Memory Cluster, Daming Feng, Andrey N. Chernikov, Nikos P. Chrisochoides

Computer Science Faculty Publications

Most of the current supercomputer architectures consist of clusters of nodes that are used by many clients (users). A user wants his/her job submitted in the job queue to be scheduled promptly. However, the resource sharing and job scheduling policies that are used in the scheduling system to manage the jobs are usually beyond the control of users. Therefore, in order to reduce the waiting time of their jobs, it is becoming more and more crucial for the users to consider how to implement the algorithms that are suitable to the system scheduling policies and are able to effectively and …

Homeomorphic Tetrahedral Tessellation For Biomedical Images, Jing Xu, Andrey N. Chernikov

Computer Science Faculty Publications

We present a novel algorithm for generating three-dimensional unstructured tetrahedral meshes for biomedical images. The method uses an octree as the background grid from which to build the final graded conforming meshes. The algorithm is fast and robust. It produces meshes with high quality since it provides dihedral angle lower bound for the output tetrahedra. Moreover, the mesh boundary is a geometrically and topologically accurate approximation of the object surface in the sense that it allows for guaranteed bounds on the two-sided Hausdorff distance and the homeomorphism between the boundaries of the mesh and the boundaries of the materials. The …

An Iterative Bézier Method For Fitting Beta-Sheet Component Of A Cryo-Em Density Map, Michael Poteat, Jing He

Computer Science Faculty Publications

Cryo-electron microscopy (Cryo-EM) is a powerful technique to produce 3-dimensional density maps for large molecular complexes. Although many atomic structures have been solved from cryo-EM density maps, it is challenging to derive atomic structures when the resolution of density maps is not sufficiently high. Geometrical shape representation of secondary structural components in a medium-resolution density map enhances modeling of atomic structures. We compare two methods in producing surface representation of the β-sheet component of a density map. Given a 3-dimensional volume of β-sheet that is segmented from a density map, the performance of a polynomial fitting was compared with that …

Ansi/Niso Z39.99-2017 Resourcesync Framework Specification, Kevin Ruthen, Jill Emery, Mark Doyle, Mark Needleman, Sue Baughman, Evan Owens, Oliver Pesch, Mike Dicus, Nassib Nassar, Tim Auger, Amy Kirchhoff, Sally Mccallum, Diana Magnoni, Paul Swanson, Gregory Grazevich, Nara Newcomer, Gregory Grazevich, Juha Hakala, Barbara Rapp, Beverly Geckle, Carol Brent, Gary Van Overborg, Rick Burke, Kristin Antelman, Scott Bernier, Pascal Calarco, John Dove, Lucy Harrison, Peter Murray, Christine Stohn, Julie Zhu, Todd Carpenter, Bernhard Haslhofer, Richard Jones, Martin Klein, Graham Klyne, Carl Lagoze, Stuart Lewis, Peter Murray, Michael Nelson, Shlomo Sanders, Robert Sanderson, Herbert Van De Sompel, Paul Walk, Simeon Warner, Zhiwu Xie, Jeff Young

Computer Science Faculty Publications

This ResourceSync specification describes a synchronization framework for the web consisting of various capabilities that allow third-party systems to remain synchronized with a server’s evolving resources. The capabilities may be combined in a modular manner to meet local or community requirements. This specification also describes how a server should advertise the synchronization capabilities it supports and how third-party systems may discover this information. The specification repurposes the document formats defined by the Sitemap protocol and introduces extensions for them.

Avoiding Zombies In Archival Replay Using Serviceworker, Sawood Alam, Mat Kelly, Michele C. Weigle, Michael L. Nelson

Computer Science Faculty Publications

[First paragraph] A Composite Memento is an archived representation of a web page with all the page requisites such as images and stylesheets. All embedded resources have their own URIs, hence, they are archived independently. For a meaningful archival replay, it is important to load all the page requisites from the archive within the temporal neighborhood of the base HTML page. To achieve this goal, archival replay systems try to rewrite all the resource references to appropriate archived versions before serving HTML, CSS, or JS. However, an effective server-side URL rewriting is difficult when URLs are generated dynamically using JavaScript. …

What Is Answer Set Programming To Propositional Satisfiability, Yuliya Lierler

Computer Science Faculty Publications

Propositional satisfiability (or satisfiability) and answer set programming are two closely related subareas of Artificial Intelligence that are used to model and solve difficult combinatorial search problems. Satisfiability solvers and answer set solvers are the software systems that find satisfying interpretations and answer sets for given propositional formulas and logic programs, respectively. These systems are closely related in their common design patterns. In satisfiability, a propositional formula is used to encode problem specifications in a way that its satisfying interpretations correspond to the solutions of the problem. To find solutions to a problem it is then sufficient to use a …

Genetic Variants In Kcnj11, Tcf7l2 And Hnf4a Are Associated With Type 2 Diabetes, Bmi And Dyslipidemia In Families Of Northeastern Mexico: A Pilot Study, Hugo Leonid Gallardo-Blanco, Jesus Zacarias Villarreal-Perez, Ricardo Martin Cerda-Flores, Andres Figueroa

Computer Science Faculty Publications

The aim of the present study was to investigate whether genetic markers considered risk factors for metabolic syndromes, including dyslipidemia, obesity and type 2 diabetes mellitus (T2DM), can be applied to a Northeastern Mexican population. A total of 37 families were analyzed for 63 single nucleotide polymorphisms (SNPs), and the age, body mass index (BMI), glucose tolerance values and blood lipid levels, including those of cholesterol, low‑density lipoprotein (LDL), very LDL (VLDL), high‑density lipoprotein (HDL) and triglycerides were evaluated. Three genetic markers previously associated with metabolic syndromes were identified in the sample population, including KCNJ11, TCF7L2 and HNF4A. The KCNJ11 …

Identification Of The Emergent Leaders Within A Cse Professional Development Program, Tracie Evans Reding, Brian Dorn, Neal Grandgenett, Harvey Siy, Jon Youn, Qiuming Zhu, Carol A. Engelmann

Computer Science Faculty Publications

The need for high quality, sustainable Computer Science Education (CSE) professional development (PD) at the grades K-12 level is essential to the success of the global CSE initiatives. This study investigates the use of Social Network Analysis (SNA) to identify emergent teacher leaders within a high quality CSE PD program. The CSE PD program was designed and implemented through collaboration between the computer science and teacher education units at a Midwestern metropolitan university in North America. A unique feature of this specific program is in the intentional development of a social network. This study discusses the importance of social networks, …

Mining Mixed-Initiative Dialogs, Saverio Perugini

Computer Science Faculty Publications

Human-computer dialogs are an important vehicle through which to produce a rich and compelling form of human-computer interaction. We view the specification of a human-computer dialog as a set of sequences of progressive interactions between a user and a computer system, and mine partially ordered sets, which correspond to mixing dialog initiative, embedded in these sets of sequences—a process we refer to as dialog mining—because partially ordered sets can be advantageously exploited to reduce the control complexity of a dialog implementation. Our mining losslessly compresses the specification of a dialog. We describe our mining algorithm and report the results of …

Marim: Mobile Augmented Reality For Interactive Manuals, Tam Nguyen, Dorothy Tan, Bilal Mirza, Jose Sepulveda

Computer Science Faculty Publications

In this work, we present a practical system which uses mobile devices for interactive manuals. In particular, there are two modes provided in the system, namely, expert/trainer and trainee modes. Given the expert/trainer editor, experts design the step-by-step interactive manuals. For each step, the experts capture the images by using phones/tablets and provide visual instructions such as interest regions, text, and action animations. In the trainee mode, the system utilizes the existing object detection and tracking algorithms to identify the step scene and retrieve the respective instruction to be displayed on the mobile device. The trainee then follows the displayed …

From Damage To Discovery Via Virtual Unwrapping: Reading The Scroll From En-Gedi, W. Brent Seales, Clifford S. Parker, Michael Segal, Emanuel Tov, Pnina Shor, Yosef Porath

Computer Science Faculty Publications

Computer imaging techniques are commonly used to preserve and share readable manuscripts, but capturing writing locked away in ancient, deteriorated documents poses an entirely different challenge. This software pipeline—referred to as “virtual unwrapping”—allows textual artifacts to be read completely and noninvasively. The systematic digital analysis of the extremely fragile En-Gedi scroll (the oldest Pentateuchal scroll in Hebrew outside of the Dead Sea Scrolls) reveals the writing hidden on its untouchable, disintegrating sheets. Our approach for recovering substantial ink-based text from a damaged object results in readable columns at such high quality that serious critical textual analysis can occur. Hence, this …

Integrative Approach For Inference Of Gene Regulatory Networks Using Lasso-Based Random Featuring And Application To Psychiatric Disorders, Dongchul Kim, Mingon Kang, Ashis Kumer Biswas, Chunyu Liu, Jean Gao

Computer Science Faculty Publications

Background

Inferring gene regulatory networks is one of the most interesting research areas in the systems biology. Many inference methods have been developed by using a variety of computational models and approaches. However, there are two issues to solve. First, depending on the structural or computational model of inference method, the results tend to be inconsistent due to innately different advantages and limitations of the methods. Therefore the combination of dissimilar approaches is demanded as an alternative way in order to overcome the limitations of standalone methods through complementary integration. Second, sparse linear regression that is penalized by the regularization …

Leveraging Static Analysis Tools For Improving Usability Of Memory Error Sanitization Compilers, Rigel Gjomemo, Phu Huu Phung, Edmund Ballou, Kedar S. Namjoshi, V. N. Venkatakrishnan, Lenore Zuck

Computer Science Faculty Publications

Memory errors such as buffer overruns are notorious security vulnerabilities. There has been considerable interest in having a compiler to ensure the safety of compiled code either through static verification or through instrumented runtime checks. While certifying compilation has shown much promise, it has not been practical, leaving code instrumentation as the next best strategy for compilation. We term such compilers Memory Error Sanitization Compilers (MESCs). MESCs are available as part of GCC, LLVM and MSVC suites. Due to practical limitations, MESCs typically apply instrumentation indiscriminately to every memory access, and are consequently prohibitively expensive and practical to only small …

On Abstract Modular Inference Systems And Solvers, Yuliya Lierler, Miroslaw Truszczyński

Computer Science Faculty Publications

Integrating diverse formalisms into modular knowledge representation systems offers increased expressivity, modeling convenience, and computational benefits. We introduce the concepts of abstract inference modules and abstract modular inference systems to study general principles behind the design and analysis of model generating programs, or solvers, for integrated multi-logic systems. We show how modules and modular systems give rise to transition graphs, which are a natural and convenient representation of solvers, an idea pioneered by the SAT community. These graphs lend themselves well to extensions that capture such important solver design features as learning. In the paper, we consider two …

Training Learnings To Self-Explains: Designing Instructions And Examples To Improve Problem Solving, Lauren E. Margulieux, Briana B. Morrison, Richard Catrambone

Computer Science Faculty Publications

In this experiment, we integrated two learning methods – subgoal learning and constructive learning – to explore their interactions and effects on solving computer programming problems. We taught learners to solve problems using worked example and practice problem pairs with one of three kinds of instructional design that either did not highlight the subgoals, described the subgoals, or prompted participants to describe the subgoals for themselves. In addition, we varied the distance of transfer between the worked example and practice problem pairs. We found that instructions that highlighted subgoals improved performance on later problem solving tasks. The groups that performed …

Monte Carlo Approaches To Parameterized Poker Squares, Todd W. Neller, Zuozhi Yang, Colin M. Messinger, Calin Anton, Karo Castro-Wunsch, William Maga, Steven Bogaerts, Robert Arrington, Clay Langely

Computer Science Faculty Publications

The paper summarized a variety of Monte Carlo approaches employed in the top three performing entries to the Parameterized Poker Squares NSG Challenge competition. In all cases AI players benefited from real-time machine learning and various Monte Carlo game-tree search techniques.

A Language-Based Model For Specifying And Staging Mixed-Initiative Dialogs, Saverio Perugini, Joshua W. Buck

Computer Science Faculty Publications

Specifying and implementing flexible human-computer dialogs, such as those used in kiosks, is complex because of the numerous and varied directions in which each user might steer a dialog. The objective of this research is to improve dialog specification and implementation. To do so we developed a model for specifying and staging mixed-initiative dialogs. The model involves a dialog authoring notation, based on concepts from programming languages, for specifying a variety of unsolicited reporting, mixed-initiative dialogs in a concise representation that serves as a design for dialog implementation. Guided by this foundation, we built a dialog staging engine which operationalizes …

Graph Mining For Next Generation Sequencing: Leveraging The Assembly Graph For Biological Insights, Julia Warnke-Sommer, Hesham Ali

Computer Science Faculty Publications

Background: The assembly of Next Generation Sequencing (NGS) reads remains a challenging task. This is especially true for the assembly of metagenomics data that originate from environmental samples potentially containing hundreds to thousands of unique species. The principle objective of current assembly tools is to assemble NGS reads into contiguous stretches of sequence called contigs while maximizing for both accuracy and contig length. The end goal of this process is to produce longer contigs with the major focus being on assembly only. Sequence read assembly is an aggregative process, during which read overlap relationship information is lost as reads are …

Gecka3d: A 3d Game Engine For Commonsense Knowledge Acquisition, Erik Cambria, Tam Nguyen, Brian Cheng, Kenneth Kwok, Jose Sepulveda

Computer Science Faculty Publications

Commonsense knowledge representation and reasoning is key for tasks such as artificial intelligence and natural language understanding. Since commonsense consists of information that humans take for granted, gathering it is an extremely difficult task. In this paper, we introduce a novel 3D game engine for commonsense knowledge acquisition (GECKA3D) which aims to collect commonsense from game designers through the development of serious games. GECKA3D integrates the potential of serious games and games with a purpose. This provides a platform for the acquisition of reusable and multi-purpose knowledge and also enables the development of games that can provide entertainment value and …

Uncertainty Avoidance—A New Teaching/ Learning Method For An Introductory Programming Course, Zhen Jiang

Computer Science Faculty Publications

In this paper, we introduce a new procedure for under-represented students to quickly learn the use of the decision structure in computer programming. The challenge here is to help students, who lack sufficient background of mathematics and computer programming, to use this structure correctly without too much doubt and uncertainty. The traditional CS0 program elapses several semesters and requires many foundation courses to be taken before the students have knowledge of the program correctness. Our one-semester course CSC115 allows students to build up programming skills gradually case by case and program by program. Such a guideline is proven to be …

Inferring Causal Molecular Networks: Empirical Assessment Through A Community-Based Effort, Steven M. Hill, Laura M. Heiser, Thomas Cokelaer, Michael Unger, Nicole K. Nesser, Daniel E. Carlin, Yang Zhang, Artem Sokolov, Evan O. Paull, Dong-Chul Kim

Computer Science Faculty Publications

It remains unclear whether causal, rather than merely correlational, relationships in molecular networks can be inferred in complex biological settings. Here we describe the HPN-DREAM network inference challenge, which focused on learning causal influences in signaling networks. We used phosphoprotein data from cancer cell lines as well as in silico data from a nonlinear dynamical model. Using the phosphoprotein data, we scored more than 2,000 networks submitted by challenge participants. The networks spanned 32 biological contexts and were scored in terms of causal validity with respect to unseen interventional data. A number of approaches were effective, and incorporating known biology …

How Well Do Doodle Polls Do?, Danya Alrawi, Barbara M. Anthony, Christine Chung

Computer Science Faculty Publications

Web-based Doodle polls, where respondents indicate their availability for a collection of times provided by the poll initiator, are an increasingly common way of selecting a time for an event or meeting. Yet group dynamics can markedly influence an individual’s response, and thus the overall solution quality. Via theoretical worst-case analysis, we analyze certain common behaviors of Doodle poll respondents, including when participants are either more generous with or more protective of their time, showing that deviating from one’s “true availability” can have a substantial impact on the overall quality of the selected time. We show perhaps counter-intuitively that being …