Computer Sciences Commons^™

Toward High Performance Computing Education, Rajendra K. Raj, Carol J. Romanowski, Sherif G. Aly, Brett A. Becker, Juan Chen, Sheikh Ghafoor, Nasser Giacaman, Steven I. Gordon, Cruz Izu, Shahram Rahimi, Michael P. Robson, Neena Thota

Computer Science: Faculty Publications

High Performance Computing (HPC) is the ability to process data and perform complex calculations at extremely high speeds. Current HPC platforms can achieve calculations on the order of quadrillions of calculations per second with quintillions on the horizon. The past three decades witnessed a vast increase in the use of HPC across different scientific, engineering and business communities, for example, sequencing the genome, predicting climate changes, designing modern aerodynamics, or establishing customer preferences. Although HPC has been well incorporated into science curricula such as bioinformatics, the same cannot be said for most computing programs. This working group will explore how …

Survey On Individual Differences In Visualization, Zhengliang Liu, R. Jordan Crouser, Alvitta Ottley

Computer Science: Faculty Publications

Developments in data visualization research have enabled visualization systems to achieve great general usability and application across a variety of domains. These advancements have improved not only people's understanding of data, but also the general understanding of people themselves, and how they interact with visualization systems. In particular, researchers have gradually come to recognize the deficiency of having one-size-fits-all visualization interfaces, as well as the significance of individual differences in the use of data visualization systems. Unfortunately, the absence of comprehensive surveys of the existing literature impedes the development of this research. In this paper, we review the research perspectives, …

Crowdsourcing Classroom Observations To Identify Misconceptions In Data Science, Ruth E. H. Wertz, Karl Rb Schmitt, Linda Clark, Bjorn Sandstede, Katherine M. Kinnaird

Computer Science: Faculty Publications

Web-browsing histories, online newspapers, streaming music, and stock prices all show that we live in an age of data. Extracting meaning from data is necessary in many fields to comprehend the information flow. This need has fueled rapid growth in data science education aiming to serve the next generation of policy makers, data science researchers, and global citizens. Initially, teaching practices have been drawn from data science's parent disciplines (e.g., computer science and mathematics). This project addresses the early stages of developing a concept inventory of student difficulty within the newly emerging field of data science. In particular this project …

Iclab: A Global, Longitudinal Internet Censorship Measurement Platform, Arian Akhavan Niaki, Shinyoung Cho, Zachary Weinberg, Nguyen Phong Hoang, Abbas Razaghpanah, Nicolas Christin, Phillipa Gill

Computer Science: Faculty Publications

Researchers have studied Internet censorship for nearly as long as attempts to censor contents have taken place. Most studies have however been limited to a short period of time and / or a few countries; the few exceptions have traded off detail for breadth of coverage. Collecting enough data for a comprehensive, global, longitudinal perspective remains challenging.In this work, we present ICLab, an Internet measurement platform specialized for censorship research. It achieves a new balance between breadth of coverage and detail of measurements, by using commercial VPNs as vantage points distributed around the world. ICLab has been operated continuously since …

Towards A General Solution For Layout Of Visual Goal Models With Actors: Supplemental Material, Yilin Lucy Wang, Alicia M. Grubb

Computer Science: Faculty Publications

Supplemental material for the paper:

"Towards a General Solution for Layout of Visual Goal Models with Actors"

This paper presents early results and lays a foundation for discussion within our GORE community.

Reconstructing The Past: The Case Of The Spadina Expressway, Alicia M. Grubb, Marsha Chechik

Computer Science: Faculty Publications

In order to build resilient systems that can be operational for a long time, it is important that analysts are able to model the evolution of the requirements of that system. The Evolving Intentions framework models how stakeholders’ goals change over time. In this work, our aim is to validate applicability and effectiveness of this technique on a substantial case. In the absence of ground truth about future evolutions, we used historical data and rational reconstruction to understand how a project evolved in the past. Seeking a well-documented project with varying stakeholder intentions over a substantial period of time, we …

Enhancing Learning With Primitive-Decomposed Cognitive Representations, Jamie C. Macbeth

Computer Science: Faculty Publications

This paper proposes work that applies insights from meaning representation systems for in-depth natural language understanding to representations for self-supervised learning systems, which show promise in developing complex, deeply-nested symbolic structures through self-motivated exploration of their environments. The core of the representation system transforms language inputs into language-free structures that are complex combinations of conceptual primitives, forming a substrate for human-like understanding and common-sense reasoning. We focus on decomposing representations of expectation, intention, planning, and decision-making which are essential to a self-motivated learner. These meaning representations may enhance learning by enabling a rich array of mappings between new experiences and …

Towards An Evaluation Visualization With Color, Megan H. Varnum, Kate M.B. Spencer, Alicia M. Grubb

Computer Science: Faculty Publications

Goal models help stakeholders understand project scenarios and make decisions. In prior work, we used Tropos evaluation semantics to allow for automated analysis over time; however, formal evaluation labels (e.g., (F, ⊥)) are difficult for users to interpret across a large model. In this paper, we present our work towards understanding the extent to which using colors in goal modeling affects users’ ability to make decisions. Specifically, we are interested in studying if coloring intentions with evaluation information allows for better comparisons of initial states and simulations of future paths. To address this question, we developed a color visualization extension …

A Preliminary Investigation Of The Utility Of Goal Model Construction, Naomi Cebula, Lily Diao, Alicia M. Grubb

Computer Science: Faculty Publications

Goal models have long been used in the literature to model and reason about stakeholders’ intentions. Prior work proposed several studies aimed at investigating what utility stakeholders derive from constructing and analyzing goal models. We designed and conducted an initial empirical study that explores the construction stage of goal modeling, asking whether stakeholders benefit from manually drawing their own model. We recruited eight qualified participants and asked each to create a goal model for a decision they were considering while talking out loud. Half of the participants in this study used BloomingLeaf, while the remaining participants drew goal models by …

The Role Of Latency And Task Complexity In Predicting Visual Search Behavior, Leilani Battle, R. Jordan Crouser, Audace Nakeshimana, Ananda Montoly, Remco Chang, Michael Stonebraker

Computer Science: Faculty Publications

Latency in a visualization system is widely believed to affect user behavior in measurable ways, such as requiring the user to wait for the visualization system to respond, leading to interruption of the analytic flow. While this effect is frequently observed and widely accepted, precisely how latency affects different analysis scenarios is less well understood. In this paper, we examine the role of latency in the context of visual search, an essential task in data foraging and exploration using visualization. We conduct a series of studies on Amazon Mechanical Turk and find that under certain conditions, latency is a statistically …

Improving Structure Evaluation Through Automatic Hierarchy Expansion, Brian Mcfee, Katherine M. Kinnaird

Computer Science: Faculty Publications

Structural segmentation is the task of partitioning a recording into non-overlapping time intervals, and labeling each segment with an identifying marker such as A, B, or verse. Hierarchical structure annotation expands this idea to allow an annotator to segment a song with multiple levels of granularity. While there has been recent progress in developing evaluation criteria for comparing two hierarchical annotations of the same recording, the existing methods have known deficiencies when dealing with inexact label matchings and sequential label repetition. In this article, we investigate methods for automatically enhancing structural annotations by inferring (and expanding) hierarchical information from the …

Deformable Part Models For Automatically Georeferencing Historical Map Images, Nicholas Howe, Jerod Weinman, John Gouwar, Aabid Shamji

Computer Science: Faculty Publications

Libraries are digitizing their collections of maps from all eras, generating increasingly large online collections of historical cartographic resources. Aligning such maps to a modern geographic coordinate system greatly increases their utility. This work presents a method for such automatic georeferencing, matching raster image content to GIS vector coordinate data. Given an approximate initial alignment that has already been projected from a spherical geographic coordinate system to a Cartesian map coordinate system, a probabilistic shape-matching scheme determines an optimized match between the GIS contours and ink in the binarized map image. Using an evaluation set of 20 historical maps from …

Preface To Ieee Vast 2019 Conference Track And Vast Challenge, Remco Chang, Daniel Keim, Ross Maciejewski, Kristin Cook, R. Jordan Crouser

Computer Science: Faculty Publications

No abstract provided.

Symmetric Inkball Alignment With Loopy Models, Nicholas Howe, Ji Won Chung

Computer Science: Faculty Publications

Alignment tasks generally seek to establish a spatial correspondence between two versions of a text, for example between a set of manuscript images and their transcript. This paper examines a different form of alignment problem, namely pixel-scale alignment between two renditions of a handwritten word or phrase. Using loopy inkball graph models, the proposed technique finds spatial correspondences between two text images such that similar parts map to each other. The method has applications to word spotting and signature verification, and can provide analytical tools for the study of handwriting variation.

Design Of Wireless Sensors For Iot With Energy Storage And Communication Channel Heterogeneity, Paul N. Borza, Mihai Machedon-Pisu, Felix G. Hamza-Lup

Computer Science: Faculty Publications

Autonomous Wireless Sensors (AWSs) are at the core of every Wireless Sensor Network (WSN). Current AWS technology allows the development of many IoT-based applications, ranging from military to bioengineering and from industry to education. The energy optimization of AWSs depends mainly on: Structural, functional, and application specifications. The holistic design methodology addresses all the factors mentioned above. In this sense, we propose an original solution based on a novel architecture that duplicates the transceivers and also the power source using a hybrid storage system. By identifying the consumption needs of the transceivers, an appropriate methodology for sizing and controlling the …

Graph-Based Offline Signature Verification, Paul Maergner, Nicholas Howe, Kaspar Riesen, Andreas Fischer

Computer Science: Faculty Publications

Graphs provide a powerful representation formalism that offers great promise to benefit tasks like handwritten signature verification. While most state-of-the-art approaches to signature verification rely on fixed-size representations, graphs are flexible in size and allow modeling local features as well as the global structure of the handwriting. In this article, we present two recent graph-based approaches to offline signature verification: keypoint graphs with approximated graph edit distance and inkball models. We provide a comprehensive description of the methods, propose improvements both in terms of computational time and accuracy, and report experimental results for four benchmark datasets. The proposed methods achieve …

Efficient Gpu Tree Walks For Effective Distributed N-Body Simulations, Jianqiao Liu, Michael Robson, Thomas Quinn, Milind Kulkarni

Computer Science: Faculty Publications

N-body problems, such as simulating the motion of stars in a galaxy, are popularly solved using tree codes like Barnes-Hut. ChaNGa is a best-of-breed n-body platform that uses an asymptotically-efficient tree traversal strategy known as a dual-tree walk to quickly determine which bodies need to interact with each other to provide an accurate simulation result. However, this strategy does not work well on GPUs, due to the highly-irregular nature of the dual-tree algorithm. On GPUs, ChaNGa uses a hybrid strategy where the CPU performs the tree walk to determine which bodies interact while the GPU performs the force computation. In …

The Red Fox Y-Chromosome In Comparative Context, Halie M. Rando, William H. Wadlington, Jennifer L. Johnson, Jeremy T. Stutchman, Lyudmila N. Trut, Marta Farré, Anna V. Kukekova

Computer Science: Faculty Publications

While the number of mammalian genome assemblies has proliferated, Y-chromosome assemblies have lagged behind. This discrepancy is caused by biological features of the Y-chromosome, such as its high repeat content, that present challenges to assembly with short-read, next-generation sequencing technologies. Partial Y-chromosome assemblies have been developed for the cat (Felis catus), dog (Canis lupus familiaris), and grey wolf (Canis lupus lupus), providing the opportunity to examine the red fox (Vulpes vulpes) Y-chromosome in the context of closely related species. Here we present a data-driven approach to identifying Y-chromosome sequence among the scaffolds that comprise the short-read assembled red fox genome. …

Bgp Hijacking Classification, Shinyoung Cho, Romain Fontugne, Kenjiro Cho, Alberto Dainotti, Phillipa Gill

Computer Science: Faculty Publications

Recent reports show that BGP hijacking has increased substantially. BGP hijacking allows malicious ASes to obtain IP prefixes for spamming as well as intercepting or blackholing traffic. While systems to prevent hijacks are hard to deploy and require the cooperation of many other organizations, techniques to detect hijacks have been a popular area of study. In this paper, we classify detected hijack events in order to document BGP detectors output and understand the nature of reported events. We introduce four categories of BGP hijack: typos, prepending mistakes, origin changes, and forged AS paths. We leverage AS hegemony-a measure of dependency …

Support For User Generated Evolutions Of Goal Models, Boyue Caroline Hu, Alicia M. Grubb

Computer Science: Faculty Publications

Goal models are used in early phase requirements engineering to elicit stakeholders' intentions, analyze dependencies, and help stakeholders make trade-off decisions about the project and its interaction with the environment. The Evolving Intentions framework extended goal model analysis to evaluate how models change over time, by creating simulation paths showing possible evolutions of the model. More recently, we extended this analysis to allow users to explore states along the path and generate their own simulation paths. However, this approach is limited by users' ability to comprehend the state space, which grows exponentially with the size of the model. In this …

Four Structural Variants Associated With Human-Directed Sociability In Dogs Are Not Found In Tame Red Foxes (Vulpes Vulpes), Estelle R. Bastounes, Halie M. Rando, Jennifer L. Johnson, Lyudmila N. Trut, Benjamin N. Sacks, Carlos A. Driscoll, Bridgett Vonholdt, Anna V. Kukekova

Computer Science: Faculty Publications

No abstract provided.

Auxetic Regions In Large Deformations Of Periodic Frameworks, Ciprian S. Borcea, Ileana Streinu

Computer Science: Faculty Publications

In materials science, auxetic behavior refers to lateral widening upon stretching. We investigate the problem of finding domains of auxeticity in global deformation spaces of periodic frameworks. Case studies include planar periodic mechanisms constructed from quadrilaterals with diagonals as periods and other frameworks with two vertex orbits. We relate several geometric and kinematic descriptions.

Using The Vast Challenge In Undergraduate Cs Research, Christopher P. Andrews, R. Jordan Crouser

Computer Science: Faculty Publications

The Visual Analytics Science and Technology (VAST) Challenge is a yearly competition designed to push forward visual analytics research through synthetic, yet realistic analytic tasks. In this paper, we discuss the challenges and the successes we have experienced incorporating the VAST Challenge and associated datasets into undergraduate research programs at two liberal arts colleges. We advocate for increased undergraduate participation in this and similar competitions, arguing they afford unique opportunities for positive development in early researchers.

Details Of Deformable Part Models For Automatically Georeferencing Historical Map Images, Nicholas Howe, Jerod Weinman, John Gouwar, Aabid Shamji

Computer Science: Faculty Publications

Libraries are digitizing their collections of maps from all eras, generating increasingly large online collections of historical cartographic resources. Aligning such maps to a modern geographic coordinate system greatly increases their utility. This work presents a method for such automatic georeferencing, matching raster image content to GIS vector coordinate data. Given an approximate initial alignment that has already been projected from a spherical geographic coordinate system to a Cartesian map coordinate system, a probabilistic shape-matching scheme determines an optimized match between the GIS contours and ink in the binarized map image. Us- ing an evaluation set of 20 historical maps …

Crowdsourcing Image Schemas, Dagmar Gromann, Jamie C. Macbeth

Computer Science: Faculty Publications

With their potential to map experiental structures from the sensorimotor to the abstract cognitive realm, image schemas are believed to provide an embodied grounding to our cognitive conceptual system, including natural language. Few empirical studies have evaluated humans’ intuitive understanding of image schemas or the coherence of image-schematic annotations of natural language. In this paper we present the results of a human-subjects study in which 100 participants annotate 12 simple English sentences with one or more image schemas. We find that human subjects recruited from a crowdsourcing platform can understand image schema descriptions and use them to perform annotations of …

Reports Of The Aaai 2019 Spring Symposium Series, Ioana Baldini, Clark Barrett, Antonio Chella, Carlos Cinelli, David Gamez, Leilani H. Gilpin, Knut Hinkelmann, Dylan Holmes, Takashi Kido, Murat Kocaoglu, William F. Lawless, Alessio Lomuscio, Jamie C. Macbeth, Andreas Martin, Ranjeev Mittu, Evan Patterson, Donald Sofge, Prasad Tadepalli, Keiki Takadama, Shomir Wilson

Computer Science: Faculty Publications

Applications of machine learning combined with AI algorithms have propelled unprecedented economic disruptions across diverse fields in industry, military, medicine, finance, and others. With the forecast for even larger impacts, the present economic impact of machine learning is estimated in the trillions of dollars. But as autonomous machines become ubiquitous, recent problems have surfaced. Early on, and again in 2018, Judea Pearl warned AI scientists they must "build machines that make sense of what goes on in their environment," a warning still unheeded that may impede future development. For example, self-driving vehicles often rely on sparse data; self-driving cars have …

Linguistic Variation And Anomalies In Comparisons Of Human And Machine-Generated Image Captions, Minyue Dai, Sandra Grandic, Jamie C. Macbeth

Computer Science: Faculty Publications

Describing the content of a visual image is a fundamental ability of human vision and language systems. Over the past several years, researchers have published on major improvements on image captioning, largely due to the development of deep learning systems trained on large data sets of images and human-written captions. However, these systems have major limitations, and their development has been narrowly focused on improving scores on relatively simple “bag-of-words” metrics. Very little work has examined the overall complex patterns of the language produced by image-captioning systems and how it compares to captions written by humans. In this paper, we …

Data Usage In Mir: History & Future Recommendations, Wenqin Chen, Jessica Keast, Jordan Moody, Corinne Moriarty, Felicia Villalobos, Virtue Winter, Xueqi Zhang, Xuanqi Lyu, Elizabeth Freeman, Jessie Wang, Sherry Cai, Katherine M. Kinnaird

Computer Science: Faculty Publications

The MIR community faces unique challenges in terms of data access, due in large part to country-specific copyright laws. As a result, there is an emerging divide in the MIR research community between labs that have access to music through large companies with abundant funds, and independent labs at smaller institutions who do not have such expansive access. This paper explores how independent researchers have worked to overcome limitations of access to music data without contributing to the crisis of reproducibility. Acknowledging that there is no single solution for every data access problem that smaller labs face, we propose a …

Towards Modeling Conceptual Dependency Primitives With Image Schema Logic, Jamie C. Macbeth, Dagmar Gromann

Computer Science: Faculty Publications

Conceptual Dependency (CD) primitives and Image Schemas (IS) share a common goal of grounding symbols of natural language in a representation that allows for automated semantic interpretation. Both seek to establish a connection between high-level conceptualizations in natural language and abstract cognitive building blocks. Some previous approaches have established a CD-IS correspondence. In this paper, we build on this correspondence in order to apply a logic designed for image schemas to selected CD primitives with the goal of formally taking account of the CD inventory. The logic draws from Region Connection Calculus (RCC-8), Qualitative Trajectory Calculus (QTC), Cardinal Directions and …

Auxetic Regions In Large Deformations Of Periodic Frameworks, Ciprian S. Borcea, Ileana Streinu

Computer Science: Faculty Publications

In materials science, auxetic behavior refers to lateral widening upon stretching. We investigate the problem of finding domains of auxeticity in global deformation spaces of periodic frameworks. Case studies include planar periodic mechanisms constructed from quadrilaterals with diagonals as periods and other frameworks with two vertex orbits. We relate several geometric and kinematic descriptions.