Physical Sciences and Mathematics Commons^™

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 …

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, …

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 …

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 …

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 …

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 …

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 …

Ai Education: Birds Of A Feather, Todd W. Neller

Computer Science Faculty Publications

Games are beautifully crafted microworlds that invite players to explore complex terrains that spring into existence from even simple rules. As AI educators, games can offer fun ways of teaching important concepts and techniques. Just as Martin Gardner employed games and puzzles to engage both amateurs and professionals in the pursuit of Mathematics, a well-chosen game or puzzle can provide a catalyst for AI learning and research. [excerpt]

Greener And Smarter Phones For Future Cities: Characterizing The Impact Of Gps Signal Strength On Power Consumption, Lo'ai A. Tawalbeh, A. Basalamah, R. Mehmood, H. Tawalbeh

Computer Science Faculty Publications

Smart cities appear as the next stage of urbanization aiming to not only exploit physical and digital infrastructure for urban development but also the intellectual and social capital as its core ingredient for urbanization. Smart cities harness the power of data from sensors in order to understand and manage city systems. The most important of these sensing devices are smartphones as they provide the most important means to connect the smart city systems with its citizens, allowing personalization n and cocreation. The battery lifetime of smartphones is one of the most important parameters in achieving good user experience for the …

Export To Arduino: A Tool To Teach Processor Design On Real Hardware, Michael Black

Computer Science Faculty Publications

Many computer organization courses teach digital design and processor architecture without a hardware lab or physical equipment. This paper introduces a module to allow students to export digital designs as C programs that run on an inexpensive Arduino Uno, thereby allowing students to test and observe their designs in actual hardware with minimal setup time and equipment. The module runs within Emumaker86, an open-source digital design tool previously developed by the author for teaching microprocessor architecture, and can handle designs ranging from simple combinational circuits to a complete processor. Students were given this module in an undergraduate "Systems Computing" course, …

Experimental Comparison Of Simulation Tools For Efficient Cloud And Mobile Cloud Computing Applications, K. Bahwaireth, Lo'ai A. Tawalbeh, E. Benkhelifa, Y. Jararweh, M. A. Tawalbeh

Computer Science Faculty Publications

Cloud computing provides a convenient and on-demand access to virtually unlimited computing resources. Mobile cloud computing (MCC) is an emerging technology that integrates cloud computing technology with mobile devices. MCC provides access to cloud services for mobile devices. With the growing popularity of cloud computing, researchers in this area need to conduct real experiments in their studies. Setting up and running these experiments in real cloud environments are costly. However, modeling and simulation tools are suitable solutions that often provide good alternatives for emulating cloud computing environments. Several simulation tools have been developed especially for cloud computing. In this paper, …

Mobile Cloud Computing Model And Big Data Analysis For Healthcare Applications, Lo'ai A. Tawalbeh, R. Mehmood, E. Benkhlifa, H. Song

Computer Science Faculty Publications

Mobile devices are increasingly becoming an indispensable part of people's daily life, facilitating to perform a variety of useful tasks. Mobile cloud computing integrates mobile and cloud computing to expand their capabilities and benefits and overcomes their limitations, such as limited memory, CPU power, and battery life. Big data analytics technologies enable extracting value from data having four Vs: volume, variety, velocity, and veracity. This paper discusses networked healthcare and the role of mobile cloud computing and big data analytics in its enablement. The motivation and development of networked healthcare applications and systems is presented along with the adoption of …

Interactively Cutting And Constraining Vertices In Meshes Using Augmented Matrices, Yu-Hong Yeung, Jessica Crouch, Alex Pothen

Computer Science Faculty Publications

We present a finite-element solution method that is well suited for interactive simulations of cutting meshes in the regime of linear elastic models. Our approach features fast updates to the solution of the stiffness system of equations to account for real-time changes in mesh connectivity and boundary conditions. Updates are accomplished by augmenting the stiffness matrix to keep it consistent with changes to the underlying model, without refactoring the matrix at each step of cutting. The initial stiffness matrix and its Cholesky factors are used to implicitly form and solve a Schur complement system using an iterative solver. As changes …

Leveraging Heritrix And The Wayback Machine On A Corporate Intranet: A Case Study On Improving Corporate Archives, Justin F. Brunelle, Krista Ferrante, Eliot Wilczek, Michele C. Weigle, Michael L. Nelson

Computer Science Faculty Publications

In this work, we present a case study in which we investigate using open-source, web-scale web archiving tools (i.e., Heritrix and the Wayback Machine installed on the MITRE Intranet) to automatically archive a corporate Intranet. We use this case study to outline the challenges of Intranet web archiving, identify situations in which the open source tools are not well suited for the needs of the corporate archivists, and make recommendations for future corporate archivists wishing to use such tools. We performed a crawl of 143,268 URIs (125 GB and 25 hours) to demonstrate that the crawlers are easy to set …

A Hybrid Algorithm Based On Optimal Quadratic Spline Collocation And Parareal Deferred Correction For Parabolic Pdes, Jun Liu, Yan Wang, Rongjian Li

Computer Science Faculty Publications

Parareal is a kind of time parallel numerical methods for time-dependent systems. In this paper, we consider a general linear parabolic PDE, use optimal quadratic spline collocation (QSC) method for the space discretization, and proceed with the parareal technique on the time domain. Meanwhile, deferred correction technique is also used to improve the accuracy during the iterations. In fact, the optimal QSC method is a correction of general QSC method. Along the temporal direction we embed the iterations of deferred correction into parareal to construct a hybrid method, parareal deferred correction (PDC) method. The error estimation is presented and the …

Big Data-Enabled Multiscale Serviceability Analysis For Aging Bridges, Yu Liang, Dalei Wu, Guirong Liu, Yaohang Li, Cuilan Gao, Zhongguo John Ma, Weidong Wu

Computer Science Faculty Publications

This work is dedicated to constructing a multi-scale structural health monitoring system to monitor and evaluate the serviceability of bridges based on the Hadoop Ecosystem (MS-SHM-Hadoop). By taking the advantages of the fault-tolerant distributed file system called the Hadoop Distributed File System (HDFS) and high-performance parallel data processing engine called MapReduce programming paradigm, MS-SHM-Hadoop features include high scalability and robustness in data ingestion, fusion, processing, retrieval, and analytics. MS-SHM-Hadoop is a multi-scale reliability analysis framework, which ranges from nationwide bridge-surveys, global structural integrity analysis, and structural component reliability analysis. This Nationwide bridge survey uses deep-learning techniques to evaluate the bridge …

Flexc: Protein Flexibility Prediction Using Context-Based Statistics, Predicted Structural Features, And Sequence Information, Ashraf Yaseen, Mais Nijim, Brandon Williams, Lei Qian, Min Li, Jianxin Wang, Yaohang Li

Computer Science Faculty Publications

The fluctuation of atoms around their average positions in protein structures provides important information regarding protein dynamics. This flexibility of protein structures is associated with various biological processes. Predicting flexibility of residues from protein sequences is significant for analyzing the dynamic properties of proteins which will be helpful in predicting their functions.

Rcd+: Fast Loop Modeling Server, José R. López-Blanco, Alejandro J. Canosa-Valis, Yaohang Li, Pablo Chacón

Computer Science Faculty Publications

Modeling loops is a critical and challenging step in protein modeling and prediction. We have developed a quick online service (http://rcd.chaconlab.org) for ab initio loop modeling combining a coarse-grained conformational search with a full-atom refinement. Our original Random Coordinate Descent (RCD) loop closure algorithm has been greatly improved to enrich the sampling distribution towards near-native conformations. These improvements include a new workflow optimization, MPI-parallelization and fast backbone angle sampling based on neighbor-dependent Ramachandran probability distributions. The server starts by efficiently searching the vast conformational space from only the loop sequence information and the environment atomic coordinates. The generated closed loop …

A Hybrid Parallel Delaunay Image-To-Mesh Conversion Algorithm Scalable On Distributed-Memory Clusters, Daming Feng, Andrey N. Chernikov, Nikos Chrisochoides

Computer Science Faculty Publications

In this paper, we present a scalable three dimensional hybrid MPI+Threads parallel Delaunay image-to-mesh conversion algorithm. A nested master-worker communication model for parallel mesh generation is implemented which simultaneously explores process-level parallelization and thread-level parallelization: inter-node communication using MPI and inter-core communication inside one node using threads. In order to overlap the communication (task request and data movement) and computation (parallel mesh refinement), the inter-node MPI communication and intra-node local mesh refinement is separated. The master thread that initializes the MPI environment is in charge of the inter-node MPI communication while the worker threads of each process are only responsible …

Deep Models For Brain Em Image Segmentation: Novel Insights And Improved Performance, Ahmed Fakhry, Hanchuan Peng, Shuiwang Ji

Computer Science Faculty Publications

Motivation: Accurate segmentation of brain electron microscopy (EM) images is a critical step in dense circuit reconstruction. Although deep neural networks (DNNs) have been widely used in a number of applications in computer vision, most of these models that proved to be effective on image classification tasks cannot be applied directly to EM image segmentation, due to the different objectives of these tasks. As a result, it is desirable to develop an optimized architecture that uses the full power of DNNs and tailored specifically for EM image segmentation.

Results: In this work, we proposed a novel design of DNNs for …

Revisiting The Futamura Projections: A Diagrammatic Approach, Brandon Williams, Saverio Perugini

Computer Science Faculty Publications

The advent of language implementation tools such as PyPy and Truffle/Graal have reinvigorated and broadened interest in topics related to automatic compiler generation and optimization. Given this broader interest, we revisit the Futamura Projections using a novel diagram scheme. Through these diagrams we emphasize the recurring patterns in the Futamura Projections while addressing their complexity and abstract nature. We anticipate that this approach will improve the accessibility of the Futamura Projections and help foster analysis of those new tools through the lens of partial evaluation.