Computer Sciences Commons^™

Matching Multiple Rigid Domain Decompositions Of Proteins, Emily Flynn, Ileana Streinu

Computer Science: Faculty Publications

We describe efficient methods for consistently coloring and visualizing collections of rigid cluster decompositions obtained from variations of a protein structure, and lay the foundation for more complex setups, that may involve different computational and experimental methods. The focus here is on three biological applications: the conceptually simpler problems of visualizing results of dilution and mutation analyses, and the more complex task of matching decompositions of multiple Nucleic Magnetic Resonance (NMR) models of the same protein. Implemented into the KINematics And RIgidity (KINARI) web server application, the improved visualization techniques give useful information about protein folding cores, help examining the …

Matching Multiple Rigid Domain Decompositions Of Proteins, Emily Flynn, Ileana Streinu

Computer Science: Faculty Publications

We describe efficient methods for consistently coloring and visualizing collections of rigid cluster decompositions obtained from variations of a protein structure, and lay the foundation for more complex setups, that may involve different computational and experimental methods. The focus here is on three biological applications: the conceptually simpler problems of visualizing results of dilution and mutation analyses, and the more complex task of matching decompositions of multiple Nucleic Magnetic Resonance (NMR) models of the same protein. Implemented into the KINematics And RIgidity (KINARI) web server application, the improved visualization techniques give useful information about protein folding cores, help examining the …

Runtime Coordinated Heterogeneous Tasks In Charm++, Michael P. Robson, Ronak Buch, Laxmikant V. Kale

Computer Science: Faculty Publications

Effective utilization of the increasingly heterogeneous hardware in modern supercomputers is a significant challenge. Many applications have seen performance gains by using GPUs, but many implementations leave CPUs sitting idle.In this paper, we describe a runtime managed system for coordinating heterogeneous execution. This system manages data transfers to and from GPU devices and schedules work across the computational resources of the system. The programmer need only tag methods and parameters to enable heterogeneous execution.Using this system, we observe improvements in programmer productivity and application performance. For selected benchmarks, when using heterogeneous execution we observe speedups of up to 3.09x relative …

Conceptual Primitive Decomposition For Knowledge Sharing Via Natural Language, Jamie C. Macbeth

Computer Science: Faculty Publications

Natural language is an ideal mode of interaction and knowledge sharing between intelligent computer systems and their human users. But a major problem that natural language interaction poses is linguistic variation, or the "paraphrase problem": there are a variety of ways of referring to the same idea. This is a special problem for intelligent systems in domains such as information retrieval, where a query presented in natural language is matched against an ontology or knowledge base, particularly when its representation uses a vocabulary based in natural language. This paper proposes solutions to these problems in primitive decomposition methods that represent …

Image Schemas And Conceptual Dependency Primitives: A Comparison, Jamie C. Macbeth, Dagmar Gromann, Maria M. Hedblom

Computer Science: Faculty Publications

A major challenge in natural language understanding research in artificial intelligence (AI) has been and still is the grounding of symbols in a representation that allows for rich semantic interpretation, inference, and deduction. Across cognitive linguistics and other disciplines, a number of principled methods for meaning representation of natural language have been proposed that aim to emulate capacities of human cognition. However, little cross-fertilization among those methods has taken place. A joint effort of human-level meaning representation from AI research and from cognitive linguistics holds the potential of contributing new insights to this profound challenge. To this end, this paper …

Angle-Monotone Paths In Non-Obtuse Triangulations, Anna Lubiw, Joseph O'Rourke

Computer Science: Faculty Publications

We reprove a result of Dehkordi, Frati, and Gudmundsson: every two vertices in a non-obtuse triangulation of a point set are connected by an angle-monotone path-an xy-monotone path in an appropriately rotated coordinate system. We show that this result cannot be extended to angle-monotone spanning trees, but can be extended to boundary-rooted spanning forests. The latter leads to a conjectural edge-unfolding of sufficiently shallow polyhedral convex caps.

Toward Theoretical Techniques For Measuring The Use Of Human Effort In Visual Analytic Systems, R. Jordan Crouser, Lyndsey Franklin, Alex Endert, Kris Cook

Computer Science: Faculty Publications

Visual analytic systems have long relied on user studies and standard datasets to demonstrate advances to the state of the art, as well as to illustrate the efficiency of solutions to domain-specific challenges. This approach has enabled some important comparisons between systems, but unfortunately the narrow scope required to facilitate these comparisons has prevented many of these lessons from being generalized to new areas. At the same time, advanced visual analytic systems have made increasing use of human-machine collaboration to solve problems not tractable by machine computation alone. To continue to make progress in modeling user tasks in these hybrid …

Siam Data Mining "Brings It" To Annual Meeting, Jeremy Kepner, Sanjukta Bhowmick, Aydın Buluç, Rajmonda Caceres, R. Jordan Crouser, Vijay Gadepally, Ben Miller, Jennifer Webster

Computer Science: Faculty Publications

The Data Mining Activity Group is one of SIAM's most vibrant and dynamic activity groups. To better share our enthusiasm for data mining with the broader SIAM community, our activity group organized six minisymposia at the 2016 Annual Meeting. These minisymposia included 48 talks organized by 11 SIAM members on - GraphBLAS (Aydın Buluç) - Algorithms and statistical methods for noisy network analysis (Sanjukta Bhowmick & Ben Miller) - Inferring networks from non-network data (Rajmonda Caceres, Ivan Brugere & Tanya Y. Berger-Wolf) - Visual analytics (Jordan Crouser) - Mining in graph data (Jennifer Webster, Mahantesh Halappanavar & Emilie Hogan) - …

New Principles For Auxetic Periodic Design, Ciprian Borcea, Ileana Streinu

Computer Science: Faculty Publications

We show that, for any given dimension d ≥ 2, the range of distinct possible designs for periodic frameworks with auxetic capabilities is infinite. We rely on a purely geometric approach to auxetic trajectories developed within our general theory of deformations of periodic frameworks.

Crowdsourcing A Parallel Corpus For Conceptual Analysis Of Natural Language, Jamie C. Macbeth, Sandra Grandic

Computer Science: Faculty Publications

Computer users today are demanding greater performance from systems that understand and respond intelligently to human language as input. In the past, researchers proposed and built conceptual analysis systems that attempted to understand language in depth by decomposing a text into structures representing complex combinations of primitive acts, events, and state changes in the world the way people conceive them. However, these systems have traditionally been time-consuming and costly to build and maintain by hand. This paper presents two studies of crowdsourcing a parallel corpus to build conceptual analysis systems through machine learning. In the first study, we found that …

Text Summarization Techniques: A Brief Survey, Mehdi Allahyari, Seyedamin Pouriyeh, Mehdi Assefi, Saeid Safaei, Elizabeth D. Trippe, Juan B. Gutierrez, Krys Kochut

Computer Science: Faculty Publications

In recent years, there has been a explosion in the amount of text data from a variety of sources. This volume of text is an invaluable source of information and knowledge which needs to be effectively summarized to be useful. Text summarization is the task of shortening a text document into a condensed version keeping all the important information and content of the original document. In this review, the main approaches to automatic text summarization are described. We review the different processes for summarization and describe the effectiveness and shortcomings of the different methods.

A Knowledge-Based Topic Modeling Approach For Automatic Topic Labeling, Mehdi Allahyari, Seyedamin Pouriyeh, Krys Kochut, Hamid Reza Arabnia

Computer Science: Faculty Publications

Probabilistic topic models, which aim to discover latent topics in text corpora define each document as a multinomial distributions over topics and each topic as a multinomial distributions over words. Although, humans can infer a proper label for each topic by looking at top representative words of the topic but, it is not applicable for machines. Automatic Topic Labeling techniques try to address the problem. The ultimate goal of topic labeling techniques are to assign interpretable labels for the learned topics. In this paper, we are taking concepts of ontology into consideration instead of words alone to improve the quality …

A Survey Of Visual Analytics Tools For Effective Decision-Making, R. Jordan Crouser, Erina Fukuda, Subashini Sridhar

Computer Science: Faculty Publications

Over the past decade, the visualization for cybersecurity (VizSec) research community has adapted many information visualization techniques to support the critical work of cyber analysts. While these efforts have yielded many specialized tools and platforms, the community lacks a unified approach to the design and implementation of these systems. In this work, we provide a retrospective analysis of the past decade of VizSec publications, with an eye toward developing a more cohesive understanding of the emerging patterns of design:

• We identify common thematic groupings among existing work, as well as interesting patterns of design around the utilization of various …

Looking Into The Crystal Ball: Requirements Evolution Over Time, Alicia M. Grubb, Marsha Chechik

Computer Science: Faculty Publications

Goal modeling has long been used in the literature to model and reason about system requirements, constraints within the domain and environment, and stakeholders' goals. Goal model analysis helps stakeholders answer 'what if' questions enabling them to make tradeoff decisions about their project requirements. However, questions concerning the evolution over time of stakeholder requirements or changes in actor intentionality are not explicitly addressed by current approaches. In this paper, we tackle this problem by presenting a method for specifying changes in intentions over time, and a technique that uses simulation for asking a variety of 'what if' questions about such …

Inkball Models As Features For Handwriting Recognition, Nicholas Howe, Andreas Fischer, Baptiste Wicht

Computer Science: Faculty Publications

Inkball models provide a tool for matching and comparison of spatially structured markings such as handwritten characters and words. Hidden Markov models offer a framework for decoding a stream of text in terms of the most likely sequence of causal states. Prior work with HMM has relied on observation of features that are correlated with underlying characters, without modeling them directly. This paper proposes to use the results of inkball-based character matching as a feature set input directly to the HMM. Experiments indicate that this technique outperforms other tested methods at handwritten word recognition on a common benchmark when applied …

Segmentation-Free Spotting Of Cuneiform Using Part-Structured Models, Bartosz Bogacz, Nicholas Howe, Mara Mara

Computer Science: Faculty Publications

Cuneiform scripts constitute an immense source of information about ancient history, dating back almost four thousand years. Documents were written by imprinting wedgeshaped impressions into wet clay tablets, and current scholarly practice typically transcribes the resulting markings by hand with ink on paper. This work develops algorithmic methods for cuneiform script, combining feature extraction for cuneiform wedges with prior work on segmentation-free word spotting using part-structured models. We adapt the inkball model used for word spotting to treat wedge features as individual parts arranged in a tree structure. The geometric relationship between query and target is measured by the energy …

Unfolding Convex Polyhedra Via Radially Monotone Cut Trees, Joseph O'Rourke

Computer Science: Faculty Publications

A notion of "radially monotone" cut paths is introduced as an effective choice for finding a non-overlapping edge-unfolding of a convex polyhedron. These paths have the property that the two sides of the cut avoid overlap locally as the cut is infinitesimally opened by the curvature at the vertices along the path. It is shown that a class of planar, triangulated convex domains always have a radially monotone spanning forest, a forest that can be found by an essentially greedy algorithm. This algorithm can be mimicked in 3D and applied to polyhedra inscribed in a sphere. Although the algorithm does …

Deep Learning For Population Genetic Inference, Sara Sheehan, Yun S. Song

Computer Science: Faculty Publications

Given genomic variation data from multiple individuals, computing the likelihood of complex population genetic models is often infeasible. To circumvent this problem, we introduce a novel likelihood-free inference framework by applying deep learning, a powerful modern technique in machine learning. Deep learning makes use of multilayer neural networks to learn a feature-based function from the input (e.g., hundreds of correlated summary statis- tics of data) to the output (e.g., population genetic parameters of interest). We demonstrate that deep learning can be effectively employed for population genetic inference and learning informative features of data. As a concrete application, we focus on …

Beyond Detection: Investing In Practical And Theoretical Applications Of Emotion + Visualization, R. Jordan Crouser, Lane Harrison, Daniel Afergan, Evan M. Peck

Computer Science: Faculty Publications

Emotion is a dynamic variable that modulates how we perceive, reason about, and interact with our environment. Recent studies have established that emotion’s influence carries to data analysis and visualization, impacting performance in ways both positive and negative. While we are still in the infancy of understanding the role emotion plays in analytical contexts, advances in physiological sensing and emotion research have raised the possibility of creating emotion-aware systems. In this position paper, we argue that it is critical to consider the potential advances that can be made even in the face of imperfect sensing, while we continue to address …

Geodesic Universal Molecules, John C. Bowers, Ileana Streinu

Computer Science: Faculty Publications

The first phase of TreeMaker, a well-known method for origami design, decomposes a planar polygon (the “paper”) into regions. If some region is not convex, TreeMaker indicates it with an error message and stops. Otherwise, a second phases is invoked which computes a crease pattern called a “universal molecule”. In this paper we introduce and study geodesic universal molecules, which also work with non-convex polygons and thus extend the applicability of the TreeMaker method. We characterize the family of disk-like surfaces, crease patterns and folded states produced by our generalized algorithm. They include non-convex polygons drawn on the surface of …

Large Scale Rigidity-Based Flexibility Analysis Of Biomolecules, Ileana Streinu

Computer Science: Faculty Publications

KINematics And RIgidity (KINARI) is an on-going project for in silico flexibility analysis of proteins. The new version of the software, Kinari-2, extends the function- ality of our free web server KinariWeb, incorporates advanced web technologies, emphasizes the reproducibility of its experiments, and makes substantially improved tools available to the user. It is designed specifically for large scale experiments, in particular, for (a) very large molecules, including bioassemblies with high degree of symmetry such as viruses and crystals, (b) large collections of related biomolecules, such as those obtained through simulated dilutions, mutations, or conformational changes from various types of dynamics …

Gendermag: A Method For Evaluating Software’S Gender Inclusiveness, Margaret Burnett, Simone Stump, Jamie C. Macbeth, Stephann Makri, Laura Beckwith, Irwin Kwan, Anicia Peters, William Jernigan

Computer Science: Faculty Publications

In recent years, research into gender differences has established that individual differences in how people problem-solve often cluster by gender. Research also shows that these differences have direct implications for software that aims to support users’ problem-solving activities, and that much of this software is more supportive of problem-solving processes favored (statistically) more by males than by females. However, there is almost no work considering how software practitioners—such as User Experience (UX) professionals or software developers—can find genderinclusiveness issues like these in their software. To address this gap, we devised the GenderMag method for evaluating problem-solving software from a gender-inclusiveness …

Vast Challenge 2016: Streaming Visual Analytics, R. Jordan Crouser, Kristin Cook, John Fallon, Georges Grinstein, Kristin Liggett, Danko Nebesh, Mark A. Whiting, Kirsten Whitley

Computer Science: Faculty Publications

The 2016 VAST Challenge returns to the (fictional) island of Kronos to pose three Mini-Challenges. In Mini-Challenge 1, participants must design an innovative interactive visual interface that enables security investigators from the Euybia Island Resort and Conference Center to conduct real-time analysis of streaming data. In Mini-Challenge 2, the GAStech Corporation returns from the 2014 kidnapping disaster more committed than ever to tighten up operations at its new headquarters in Abila. Using data from stationary and mobile sensors of multiple types, participants must help the company to understand both operational issues as well as security issues. In Mini-Challenge 3, participants …

The Coherence Of Conceptual Primitives, Jamie C. Macbeth, Marydjina Barionnette

Computer Science: Faculty Publications

Intelligent systems that process natural language need representations of knowledge to support a human-like thought process, and they often use natural language words or phrases to name and represent concepts in a knowledge base. But some theories of cognition claim that language and thought are not the same thing, and that human thought processes occur at a deeper level of representation than words and phrases in language. In this paper we present results of a human subjects study of language-free primitive decomposition as a representation for commonsense knowledge. We found that our subjects could comprehend and use a primitive decomposition …

Automatically Processing Tweets From Gang-Involved Youth: Towards Detecting Loss And Aggression, Terra Blevins, Robert Kwiatkowski, Jamie C. Macbeth, Kathleen Mckeown, Desmond Patton, Owen Rambow

Computer Science: Faculty Publications

Violence is a serious problems for cities like Chicago and has been exacerbated by the use of social media by gang-involved youths for taunting rival gangs. We present a corpus of tweets from a young and powerful female gang member and her communicators, which we have annotated with discourse intention, using a deep read to understand how and what triggered conversations to escalate into aggression. We use this corpus to develop a part-of-speech tagger and phrase table for the variant of English that is used, as well as a classifier for identifying tweets that express grieving and aggression.

Understanding Challenges And Tradeoffs In Istar Tool Development, Tong Li, Alicia M. Grubb, Jennifer Horkoff

Computer Science: Faculty Publications

Many iStar-based modeling and analysis tools have been developed for specific iStar-related purposes (e.g., tools enumerated in iStar wiki). Despite the proliferation of tools, new tools keep being built, taking resources and time and possibly "reinventing the wheel" in terms of tool functionality. To gain an in-depth understanding of this situation, we are interested in the challenges and tradeoffs in creating iStar tools. In this paper, we examine three diverse tools as case studies, illustrating the challenges and tradeoffs from the developer's perspective. Based on such studies, we establish a goal model to capture the collected knowledge, which can help …

Geometric Deformations Of Sodalite Frameworks, Ciprian Borcea, Ileana Streinu

Computer Science: Faculty Publications

In mathematical crystallography and computational materials science, it is important to infer flexibility properties of framework materials from their geometric representation. We study combinatorial, geometric and kinematic properties for frameworks modeled on sodalite.

Single Machine Scheduling With Job-Dependent Machine Deterioration, Wenchang Luo, Xu Yao, Weitian Tong, Guohui Lin

Computer Science: Faculty Publications

We consider the single machine scheduling problem with job-dependent machine deterioration. In the problem, we are given a single machine with an initial non-negative maintenance level, and a set of jobs each with a non-preemptive processing time and a machine deterioration. Such a machine deterioration quantifies the decrement in the machine maintenance level after processing the job. To avoid machine breakdown, one should guarantee a non-negative maintenance level at any time point; and whenever necessary, a maintenance activity must be allocated for restoring the machine maintenance level. The goal of the problem is to schedule the jobs and the maintenance …

Mind The Gap: The Importance Of Pluralistic Discourse In Computing For Mental Health, R. Jordan Crouser, Morganne Ray Crouser

Computer Science: Faculty Publications

A large amount of HCI research leverages studies from psychology to try to understand how humans work. Unfortunately, there is often a disconnect between the tightly- controlled laboratory studies being referenced and the application of this knowledge in practice. At the same time, many mental health practitioners are beginning to turn toward computational tools to help stretch limited resources and support equitable access to mental healthcare. These efforts could be dramatically enhanced by leveraging what the HCI community has learned about promoting active engagement and designing unobtrusive interfaces. By facilitating collaboration between HCI researchers and practitioners in the field of …

Growingleaf: Supporting Requirements Evolution Over Time, Alicia M. Grubb, Gary Song, Marsha Chechik

Computer Science: Faculty Publications

Goal modeling and analysis techniques help stakeholders consider possible tradeoff alternatives in their requirements and answer "what if" questions about those alternatives. Software projects today exist in an ephemeral state, and current goal modeling approaches do not answer questions about model evolution and changes in actors' intentionality. We have developed a technique [8] that allows stakeholders to explicate the dynamic nature of their intentional elements, and ask questions about how this dynamicity affects project outcomes. In this paper, we present GrowingLeaf , a new web-based goal modeling and analysis tool that implements this technique for iStar models. We discuss its …