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Articles 1 - 12 of 12
Full-Text Articles in Physical Sciences and Mathematics
Rigidity And Flexibility Of Protein-Nucleic Acid Complexes, Emily Flynn, Filip Jagodzinski, Sharon Pamela Santana, Ileana Streinu
Rigidity And Flexibility Of Protein-Nucleic Acid Complexes, Emily Flynn, Filip Jagodzinski, Sharon Pamela Santana, Ileana Streinu
Computer Science: Faculty Publications
The study of protein-nucleic acid complexes is relevant for the understanding of many biological processes, including transcription, translation, replication, and recombination. The individual molecules in such complexes must be rigid enough to allow geometric matching of complementary shapes, yet sufficiently flexible to perform their functions. © 2013 IEEE.
As Strong As The Weakest Link: Mining Diverse Cliques In Weighted Graphs, Petko Bogdanov, Ben Baumer, Prithwish Basu, Amotz Bar-Noy, Ambuj K. Singh
As Strong As The Weakest Link: Mining Diverse Cliques In Weighted Graphs, Petko Bogdanov, Ben Baumer, Prithwish Basu, Amotz Bar-Noy, Ambuj K. Singh
Statistical and Data Sciences: Faculty Publications
Mining for cliques in networks provides an essential tool for the discovery of strong associations among entities. Applications vary, from extracting core subgroups in team performance data arising in sports, entertainment, research and business; to the discovery of functional complexes in high-throughput gene interaction data. A challenge in all of these scenarios is the large size of real-world networks and the computational complexity associated with clique enumeration. Furthermore, when mining for multiple cliques within the same network, the results need to be diversified in order to extract meaningful information that is both comprehensive and representative of the whole dataset. We …
Wind Power Uncertainty And Power System Performance, C. Lindsay Anderson, Judith Cardell
Wind Power Uncertainty And Power System Performance, C. Lindsay Anderson, Judith Cardell
Engineering: Faculty Publications
The penetration of wind power into global electric power systems is steadily increasing, with the possibility of 30% to 80% of electrical energy coming from wind within the coming decades. At penetrations below 10% of electricity from wind, the impact of this variable resource on power system operations is manageable with historical operating strategies. As this penetration increases, new methods for operating the power system and electricity markets need to be developed. As part of this process, the expected impact of increased wind penetration needs to be better understood and quantified. This paper presents a comprehensive modeling framework, combining optimal …
Modeling The Impact Of Operator Trust On Performance In Multiple Robot Control, Fei Gao, Andrew S. Clare, Jamie C. Macbeth, M. L. Cummings
Modeling The Impact Of Operator Trust On Performance In Multiple Robot Control, Fei Gao, Andrew S. Clare, Jamie C. Macbeth, M. L. Cummings
Computer Science: Faculty Publications
We developed a system dynamics model to simulate the impact of operator trust on performance in multiple robot control. Analysis of a simulated urban search and rescue experiment showed that operators decided to manually control the robots when they lost trust in the autonomous planner that was directing the robots. Operators who rarely used manual control performed the worst. However, the operators who most frequently used manual control reported higher workload and did not perform any better than operators with moderate manual control usage. Based on these findings, we implemented a model where trust and performance form a feedback loop, …
Document Binarization With Automatic Parameter Tuning, Nicholas Howe
Document Binarization With Automatic Parameter Tuning, Nicholas Howe
Computer Science: Faculty Publications
Document analysis systems often begin with binarization as a first processing stage. Although numerous techniques for binarization have been proposed, the results produced can vary in quality and often prove sensitive to the settings of one or more control parameters. This paper examines a promising approach to binarization based upon simple principles, and shows that its success depends most significantly upon the values of two key parameters. It further describes an automatic technique for setting these parameters in a manner that tunes them to the individual image, yielding a final binarization algorithm that can cut total error by one-third with …
A 2-Chain Can Interlock With An Open 10-Chain, Bin Lu, Joseph O'Rourke, Jianyuan K. Zhong
A 2-Chain Can Interlock With An Open 10-Chain, Bin Lu, Joseph O'Rourke, Jianyuan K. Zhong
Computer Science: Faculty Publications
Abstract. It is an open problem, posed in [3], to determine the minimal k such that an open flexible k-chain can interlock with a flexible 2-chain. It was first established in [5] that there is an open 16-chain in a trapezoid frame that achieves interlocking. This was subsequently improved in [6] to establish interlocking between a 2-chain and an open 11-chain. Here we improve that result once more, establishing interlocking between a 2-chain and a 10-chain. We present arguments that indicate that 10 is likely the minimum.
Part-Structured Inkball Models For One-Shot Handwritten Word Spotting, Nicholas Howe
Part-Structured Inkball Models For One-Shot Handwritten Word Spotting, Nicholas Howe
Computer Science: Faculty Publications
Many document collections of historical interest are handwritten and lack transcripts. Scholars need tools for high-quality information retrieval in such environments, preferably without the burden of extensive system training. This paper presents a novel approach to word spotting designed for manuscripts or degraded print that requires minimal initial training. It can infer a generative word appearance model from a single instance, and then use the model to retrieve similar words from arbitrary documents. An approximation to the retrieval statistic runs efficiently on graphics processing hardware. Tested on two standard data sets, the method compares favorably with prior results.
Script-Based Story Matching For Cyberbullying Prevention, Jamie Macbeth, Hanna Adeyema, Henry Lieberman, Christopher Fry
Script-Based Story Matching For Cyberbullying Prevention, Jamie Macbeth, Hanna Adeyema, Henry Lieberman, Christopher Fry
Computer Science: Faculty Publications
While the Internet and social media help keep today’s youth better connected to their friends, family, and community, the same media are also the form of expression for an array of harmful social behaviors, such as cyberbullying and cyber-harassment. In this paper we present work in progress to develop intelligent interfaces to social media that use commonsense knowledge bases and automated narrative analyses of text communications between users to trigger selective interventions and prevent negative outcomes. While other approaches seek merely to classify the overall topic of the text, we try to match stories to finer-grained “scripts” that represent stereotypical …
Balancing Human And Machine Contributions In Human Computation Systems, R. Jordan Crouser, Alvitta Ottley, Remco Chang
Balancing Human And Machine Contributions In Human Computation Systems, R. Jordan Crouser, Alvitta Ottley, Remco Chang
Computer Science: Faculty Publications
Many interesting and successful human computation systems leverage the complementary computational strengths of both humans and machines to solve these problems. In this chapter, we examine Human Computation as a type of Human-Computer Collaboration—collaboration involving at least one human and at least one computational agent. We discuss recent advances in the open area of function allocation, and explore how to balance the contributions of humans and machines in computational systems. We then explore how human-computer collaborative strategies can be used to solve problems that are difficult or computationally infeasible for computers or humans alone.
Rigidity Analysis Of Protein Biological Assemblies And Periodic Crystal Structures, Filip Jagodzinski, Pamela Clark, Jessica Grant, Tiffany Liu, Samantha Monastra, Ileana Streinu
Rigidity Analysis Of Protein Biological Assemblies And Periodic Crystal Structures, Filip Jagodzinski, Pamela Clark, Jessica Grant, Tiffany Liu, Samantha Monastra, Ileana Streinu
Computer Science: Faculty Publications
Background: We initiate in silico rigidity-theoretical studies of biological assemblies and small crystals for protein structures. The goal is to determine if, and how, the interactions among neighboring cells and subchains affect the flexibility of a molecule in its crystallized state. We use experimental X-ray crystallography data from the Protein Data Bank (PDB). The analysis relies on an effcient graph-based algorithm. Computational experiments were performed using new protein rigidity analysis tools available in the new release of our KINARI-Web server http:// kinari.cs.umass.edu. Results: We provide two types of results: on biological assemblies and on crystals. We found that when only …
Towards Accurate Modeling Of Noncovalent Interactions For Protein Rigidity Analysis, Naomi Fox, Ileana Streinu
Towards Accurate Modeling Of Noncovalent Interactions For Protein Rigidity Analysis, Naomi Fox, Ileana Streinu
Computer Science: Faculty Publications
Background: Protein rigidity analysis is an efficient computational method for extracting flexibility information from static, X-ray crystallography protein data. Atoms and bonds are modeled as a mechanical structure and analyzed with a fast graph-based algorithm, producing a decomposition of the flexible molecule into interconnected rigid clusters. The result depends critically on noncovalent atomic interactions, primarily on how hydrogen bonds and hydrophobic interactions are computed and modeled. Ongoing research points to the stringent need for benchmarking rigidity analysis software systems, towards the goal of increasing their accuracy and validating their results, either against each other and against biologically relevant (functional) parameters. …
Predicting Application Performance Using Supervised Learning On Communication Features, Nikhil Jain, Abhinav Bhatele, Michael P. Robson, Todd Gamblin, Laxmikant V. Kale
Predicting Application Performance Using Supervised Learning On Communication Features, Nikhil Jain, Abhinav Bhatele, Michael P. Robson, Todd Gamblin, Laxmikant V. Kale
Computer Science: Faculty Publications
Task mapping on torus networks has traditionally focused on either reducing the maximum dilation or average number of hops per byte for messages in an application. These metrics make simplified assumptions about the cause of network congestion, and do not provide accurate correlation with execution time. Hence, these metrics cannot be used to reasonably predict or compare application performance for different mappings. In this paper, we attempt to model the performance of an application using communication data, such as the communication graph and network hardware counters. We use supervised learning algorithms, such as randomized decision trees, to correlate performance with …