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1. Optimal accuracy for linear sets of equations with the graph Laplacian

Author

Lehoucq, Richard B., Weylandt, Michael, and Berry, Jonathan W.

Subjects
Mathematics - Numerical Analysis, Computer Science - Social and Information Networks, Statistics - Computation
Abstract

We show that certain Graph Laplacian linear sets of equations exhibit optimal accuracy, guaranteeing that the relative error is no larger than the norm of the relative residual and that optimality occurs for carefully chosen right-hand sides. Such sets of equations arise in PageRank and Markov chain theory. We establish new relationships among the PageRank teleportation parameter, the Markov chain discount, and approximations to linear sets of equations. The set of optimally accurate systems can be separated into two groups for an undirected graph -- those that achieve optimality asymptotically with the graph size and those that do not -- determined by the angle between the right-hand side of the linear system and the vector of all ones. We provide supporting numerical experiments.

Published
2024

2. PGAbB: A Block-Based Graph Processing Framework for Heterogeneous Platforms

Author

Yasar, Abdurrahman, Rajamanickam, Sivasankaran, Berry, Jonathan W., and Catalyurek, Umit V.

Subjects
Computer Science - Distributed, Parallel, and Cluster Computing, Computer Science - Data Structures and Algorithms
Abstract

Designing flexible graph kernels that can run well on various platforms is a crucial research problem due to the frequent usage of graphs for modeling data and recent architectural advances and variety. In this work, we propose a novel graph processing framework, PGAbB (Parallel Graph Algorithms by Blocks), for modern shared-memory heterogeneous platforms. Our framework implements a block-based programming model. This allows a user to express a graph algorithm using kernels that operate on subgraphs. PGAbB support graph computations that fit in host DRAM but not in GPU device memory, and provides simple but effective scheduling techniques to schedule computations to all available resources in a heterogeneous architecture. We have demonstrated that one can easily implement a diverse set of graph algorithms in our framework by developing five algorithms. Our experimental results show that PGAbB implementations achieve better or competitive performance compared to hand-optimized implementations. Based on our experiments on five graph algorithms and forty-four graphs, in the median, PGAbB achieves 1.6, 1.6, 5.7, 3.4, 4.5, and 2.4 times better performance than GAPBS, Galois, Ligra, LAGraph Galois-GPU, and Gunrock graph processing systems, respectively.

Published
2022

3. Anaplasma bovis-Like Infections in Humans, United States, 2015-2017

Author

Karpathy, Sandor E., Kingry, Luke, Pritt, Bobbi S., Berry, Jonathan C., Chilton, Neil B., Dergousoff, Shaun J., Cortinas, Roberto, Sheldon, Sarah W., Oatman, Stephanie, Anacker, Melissa, Petersen, Jeannine, and Paddock, Christopher D.

Subjects
United States. Centers for Disease Control and Prevention, Tick-borne diseases -- Health aspects, Ethylenediaminetetraacetic acid -- Health aspects, Infection -- Health aspects, Zoonoses -- Health aspects, RNA -- Health aspects, Health
Abstract

The genus Anaplasma includes several species of tickborne, zoonotic pathogens of global importance. Three recognized species (Anaplasma phagocytophilum, Anaplasma ovis, and Anaplasma bovis) and one provisionally named species (Anaplasma capra) [...]

Published
2023
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4. Connected Components for Infinite Graph Streams: Theory and Practice

Author

Berry, Jonathan W., Phillips, Cynthia A, and Porter, Alexandra M.

Subjects
Computer Science - Data Structures and Algorithms, B.4, E.1, F.2
Abstract

Motivated by the properties of unending real-world cybersecurity streams, we present a new graph streaming model: XStream. We maintain a streaming graph and its connected components at single-edge granularity. In cybersecurity graph applications, input streams typically consist of edge insertions; individual deletions are not explicit. Analysts maintain as much history as possible and will trigger customized bulk deletions when necessary Despite a variety of dynamic graph processing systems and some canonical literature on theoretical sliding-window graph streaming, XStream is the first model explicitly designed to accommodate this usage model. Users can provide Boolean predicates to define bulk deletions. Edge arrivals are expected to occur continuously and must always be handled. XStream is implemented via a ring of finite-memory processors. We give algorithms to maintain connected components on the input stream, answer queries about connectivity, and to perform bulk deletion. The system requires bandwidth for internal messages that is some constant factor greater than the stream arrival rate. We prove a relationship among four quantities: the proportion of query downtime allowed, the proportion of edges that survive an aging event, the proportion of duplicated edges, and the bandwidth expansion factor. In addition to presenting the theory behind XStream, we present computational results for a single-threaded prototype implementation. Stream ingestion rates are bounded by computer architecture. We determine this bound for XStream inter-process message-passing rates in Intel TBB applications on Intel Sky Lake processors: between one and five million graph edges per second. Our single-threaded prototype runs our full protocols through multiple aging events at between one half and one a million edges per second, and we give ideas for speeding this up by orders of magnitude., Comment: 23 pages, 12 figures

Published
2021

7. A Deterministic Hitting-Time Moment Approach to Seed-set Expansion over a Graph

Author

Foss, Alexander H., Lehoucq, Richard B., Stuart, W. Zachary, Tucker, J. Derek, and Berry, Jonathan W.

Subjects
Computer Science - Social and Information Networks, Statistics - Computation, Statistics - Methodology
Abstract

We introduce HITMIX, a new technique for network seed-set expansion, i.e., the problem of identifying a set of graph vertices related to a given seed-set of vertices. We use the moments of the graph's hitting-time distribution to quantify the relationship of each non-seed vertex to the seed-set. This involves a deterministic calculation for the hitting-time moments that is scalable in the number of graph edges and so avoids directly sampling a Markov chain over the graph. The moments are used to fit a mixture model to estimate the probability that each non-seed vertex should be grouped with the seed set. This membership probability enables us to sort the non-seeds and threshold in a statistically-justified way. To the best of our knowledge, HITMIX is the first full statistical model for seed-set expansion that can give vertex-level membership probabilities. While HITMIX is a global method, its linear computation complexity in practice enables computations on large graphs. We have a high-performance implementation, and we present computational results on stochastic blockmodels and a small-world network from the SNAP repository. The state of the art in this problem is a collection of recently developed local methods, and we show that distinct advantages in solution quality are available if our global method can be used. In practice, we expect to be able to run HITMIX if the graph can be stored in memory., Comment: 21 pages, 5 figures

Published
2020

8. A Block-Based Triangle Counting Algorithm on Heterogeneous Environments

Author

Yaşar, Abdurrahman, Rajamanickam, Sivasankaran, Berry, Jonathan, and Çatalyürek, Ümit V.

Subjects
Computer Science - Data Structures and Algorithms
Abstract

Triangle counting is a fundamental building block in graph algorithms. In this paper, we propose a block-based triangle counting algorithm to reduce data movement during both sequential and parallel execution. Our block-based formulation makes the algorithm naturally suitable for heterogeneous architectures. The problem of partitioning the adjacency matrix of a graph is well-studied. Our task decomposition goes one step further: it partitions the set of triangles in the graph. By streaming these small tasks to compute resources, we can solve problems that do not fit on a device. We demonstrate the effectiveness of our approach by providing an implementation on a compute node with multiple sockets, cores and GPUs. The current state-of-the-art in triangle enumeration processes the Friendster graph in 2.1 seconds, not including data copy time between CPU and GPU. Using that metric, our approach is 20 percent faster. When copy times are included, our algorithm takes 3.2 seconds. This is 5.6 times faster than the fastest published CPU-only time.

Published
2020

11. Collaborative behaviours and professional culture traits in real-time interprofessional clinical simulation

Author

Berry, Jonathan David, Chapman, S. R., and Maddock, Katie

Subjects
362.1068, R Medicine (General)
Abstract

Interprofessional education (IPE) has been proposed as a method of creating a collaborative practice ready workforce in healthcare. Postulated benefits of the technique include improving communication between professional groups, which in turn should help to prevent serious untoward events and ultimately improve patient outcomes. Critics of the method have cited poorly designed IPE as a method of reinforcing physician power, and argued there is a paucity of data linking undergraduate IPE to tangible benefits in a patient-facing setting. Simulation has been increasingly used as a method for delivery of IPE, with positive outcomes cited by students and educators alike. Virtual Patients and avatars have been recently used as a delivery method for healthcare education, but there is a paucity of data regarding their use in IPE. Simulation is not a panacea for IPE, many simulations focus on the acute phase of care naturally excluding healthcare professions who are not involved in those situations. Findings from acute simulations may not apply to sub-acute scenarios. Method A sub-acute real-time virtual patient simulation was designed then delivered to educators (n=6) and undergraduate students (n=33) from the professions of medicine, nursing, pharmacy and physiotherapy. Qualitative data was gathered according to a constructivist paradigm using unstructured observation of in-simulation behaviour, focus groups and semi-structured interviews. Results Data was analysed according to Braun and Clarke’s method of thematic analysis. Five themes were identified: technology, education, collaboration, intrinsic behaviours and stereotyping. The simulation was educationally successful with participants citing improved recognition of the skills of other professional groups, and improved physiological and pharmacological knowledge. The real-time aspect of the simulation improved clinical reasoning and forced students to make prescribing decisions, which was cited as beneficial for future practice. The sub-acute nature of the simulation resulted in participants hyper-observing their VP to the detriment of patient care. Good levels of collaboration, team working and appropriate communication were facilitated but students were observed to subconsciously selfstereotype. Conclusions Sub-acute real-time virtual patient simulation appears to be a valid method of enabling students to learn with and from one another. It conveys benefit over traditional educational methods such as classroom-based, problem-based and experiential learning as students are given full responsibility for patient care with little supervision. Self-stereotyping amongst students suggests that students convey stereotypical messages about their own profession to others. This may aid team-building in the undergraduate setting, but if these stereotypical views are transferred to advanced practice, there may be detrimental consequences for team formation and patient care.

Published
2020

12. The Online Event-Detection Problem

Author

Bender, Michael A., Berry, Jonathan W., Farach-Colton, Martin, Johnson, Rob, Kroeger, Thomas M., Pandey, Prashant, Phillips, Cynthia A., and Singh, Shikha

Subjects
Computer Science - Data Structures and Algorithms
Abstract

Given a stream $S = (s_1, s_2, ..., s_N)$, a $\phi$-heavy hitter is an item $s_i$ that occurs at least $\phi N$ times in $S$. The problem of finding heavy-hitters has been extensively studied in the database literature. In this paper, we study a related problem. We say that there is a $\phi$-event at time $t$ if $s_t$ occurs exactly $\phi N$ times in $(s_1, s_2, ..., s_t)$. Thus, for each $\phi$-heavy hitter there is a single $\phi$-event which occurs when its count reaches the reporting threshold $\phi N$. We define the online event-detection problem (OEDP) as: given $\phi$ and a stream $S$, report all $\phi$-events as soon as they occur. Many real-world monitoring systems demand event detection where all events must be reported (no false negatives), in a timely manner, with no non-events reported (no false positives), and a low reporting threshold. As a result, the OEDP requires a large amount of space (Omega(N) words) and is not solvable in the streaming model or via standard sampling-based approaches. Since OEDP requires large space, we focus on cache-efficient algorithms in the external-memory model. We provide algorithms for the OEDP that are within a log factor of optimal. Our algorithms are tunable: its parameters can be set to allow for a bounded false-positives and a bounded delay in reporting. None of our relaxations allow false negatives since reporting all events is a strict requirement of our applications. Finally, we show improved results when the count of items in the input stream follows a power-law distribution.

Published
2018

13. Naomi: a new modelling tool for estimating HIV epidemic indicators at the district level in sub-Saharan Africa

Author

Eaton, Jeffrey W., Dwyer-Lindgren, Laura, Gutreuter, Steve, O'Driscoll, Megan, Stevens, Oliver, Bajaj, Sumali, Ashton, Rob, Hill, Alexandra, Russell, Emma, Esra, Rachel, Dolan, Nicolas, Anifowoshe, Yusuf O., Woodbridge, Mark, Fellows, Ian, Glaubius, Robert, Haeuser, Emily, Okonek, Taylor, Stover, John, Thomas, Matthew L., Wakefield, Jon, Wolock, Timothy M., Berry, Jonathan, Sabala, Tomasz, Heard, Nathan, Delgado, Stephen, Jahn, Andreas, Kalua, Thokozani, Chimpandule, Tiwonge, Auld, Andrew, Kim, Evelyn, Payne, Danielle, Johnson, Leigh F., FitzJohn, Richard G., Wanyeki, Ian, Mahy, Mary I., and Shiraishi, Ray W.

Subjects
Statistical models -- Methods -- Evaluation, Epidemics -- Models -- Forecasts and trends -- Sub-Saharan Africa, HIV infection -- Models -- Forecasts and trends -- Distribution, Market trend/market analysis, Company distribution practices, Health
Abstract

Introduction: HIV planning requires granular estimates for the number of people living with HIV (PLHIV), antiretroviral treatment (ART) coverage and unmet need, and new HIV infections by district, or equivalent subnational administrative level. We developed a Bayesian small-area estimation model, called Naomi, to estimate these quantities stratified by subnational administrative units, sex, and five-year age groups. Methods: Small-area regressions for HIV prevalence, ART coverage and HIV incidence were jointly calibrated using subnational household survey data on all three indicators, routine antenatal service delivery data on HIV prevalence and ART coverage among pregnant women, and service delivery data on the number of PLHIV receiving ART. Incidence was modelled by district-level HIV prevalence and ART coverage. Model outputs of counts and rates for each indicator were aggregated to multiple geographic and demographic stratifications of interest. The model was estimated in an empirical Bayes framework, furnishing probabilistic uncertainty ranges for all output indicators. Example results were presented using data from Malawi during 2016-2018. Results: Adult HIV prevalence in September 2018 ranged from 3.2% to 17.1% across Malawi's districts and was higher in southern districts and in metropolitan areas. ART coverage was more homogenous, ranging from 75% to 82%. The largest number of PLHIV was among ages 35 to 39 for both women and men, while the most untreated PLHIV were among ages 25 to 29 for women and 30 to 34 for men. Relative uncertainty was larger for the untreated PLHIV than the number on ART or total PLHIV. Among clients receiving ART at facilities in Lilongwe city, an estimated 71% (95% CI, 61% to 79%) resided in Lilongwe city, 20% (14% to 27%) in Lilongwe district outside the metropolis, and 9% (6% to 12%) in neighbouring Dowa district. Thirty-eight percent (26% to 50%) of Lilongwe rural residents and 39% (27% to 50%) of Dowa residents received treatment at facilities in Lilongwe city. Conclusions: The Naomi model synthesizes multiple subnational data sources to furnish estimates of key indicators for HIV programme planning, resource allocation, and target setting. Further model development to meet evolving HIV policy priorities and programme need should be accompanied by continued strengthening and understanding of routine health system data. Keywords: Bayesian statistics; HIV estimates; joint modelling; routine data; small-area estimation, 1 | INTRODUCTION The global community has established ambitious goals for expanding coverage of antiretroviral treatment (ART) and reducing new HIV infections to end AIDS as a public health threat [...]

Published
2021
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14. Second World War anti-invasion defences in South and South-West Wales : a comparative case study area based approach

Author

Berry, Jonathan Andrew

Subjects
941.084, D731 World War II, DA Great Britain, U Military Science (General)
Abstract

Conflict archaeology is a popular subject of academic research. Within the topic of British Second World War archaeology there are few studies examining anti-invasion defences, and none relating to the evidence or its use. This research was influenced by concepts in historical and conflict archaeology and the archaeologies of the recent and contemporary past. It was undertaken to determine the extent of survival of archaeological, documentary, aerial photographic and cartographic evidence for three cases in south and south-west Wales. Case study method was used to identify, select and analyse evidence. Grounded theory was used to induce meaning. The evidence was given equal primacy, assessed critically and analysed for its role, value and contribution. Official sources were used for their unique, informed and authoritative content. Knowledge of military organisational practices and formation/unit identities were required to use the evidence effectively. A rich but incomplete evidence base of a complex character was identified. Evidence was found to be complementary and inter-dependent, representing aspects of a common shared phenomenon. The diverse sources could be used to induce meaningful narratives. The research suggested that an archaeological approach was a valid and effective form of inquiry when applied to cross-disciplinary evidence from the recent past.

Published
2016

16. Why do simple algorithms for triangle enumeration work in the real world?

Author

Berry, Jonathan W., Fostvedt, Luke A., Nordman, Daniel J., Phillips, Cynthia A., Seshadhri, C., and Wilson, Alyson G.

Subjects
Computer Science - Social and Information Networks, Computer Science - Discrete Mathematics, Computer Science - Data Structures and Algorithms, Physics - Physics and Society
Abstract

Listing all triangles is a fundamental graph operation. Triangles can have important interpretations in real-world graphs, especially social and other interaction networks. Despite the lack of provably efficient (linear, or slightly super-linear) worst-case algorithms for this problem, practitioners run simple, efficient heuristics to find all triangles in graphs with millions of vertices. How are these heuristics exploiting the structure of these special graphs to provide major speedups in running time? We study one of the most prevalent algorithms used by practitioners. A trivial algorithm enumerates all paths of length $2$, and checks if each such path is incident to a triangle. A good heuristic is to enumerate only those paths of length $2$ where the middle vertex has the lowest degree. It is easily implemented and is empirically known to give remarkable speedups over the trivial algorithm. We study the behavior of this algorithm over graphs with heavy-tailed degree distributions, a defining feature of real-world graphs. The erased configuration model (ECM) efficiently generates a graph with asymptotically (almost) any desired degree sequence. We show that the expected running time of this algorithm over the distribution of graphs created by the ECM is controlled by the $\ell_{4/3}$-norm of the degree sequence. Norms of the degree sequence are a measure of the heaviness of the tail, and it is precisely this feature that allows non-trivial speedups of simple triangle enumeration algorithms. As a corollary of our main theorem, we prove expected linear-time performance for degree sequences following a power law with exponent $\alpha \geq 7/3$, and non-trivial speedup whenever $\alpha \in (2,3)$., Comment: Conference version in Innovations of Theoretical Computer Science (ITCS) 2014

Published
2014

17. Quality-controlled audio-visual depth in stereoscopic 3D media

Author

Berry, Jonathan Stuart

Subjects
006.6
Abstract

Background: The literature proposes several algorithms that produce “quality-controlled” stereoscopic depth in 3D films by limiting the stereoscopic depth to a defined depth budget. Like stereoscopic displays, spatial sound systems provide the listener with enhanced (auditory) depth cues, and are now commercially available in multiple forms. AIM: We investigate the implications of introducing auditory depth cues to quality-controlled 3D media, by asking: “Is it important to quality-control audio-visual depth by considering audio-visual interactions, when integrating stereoscopic display and spatial sound systems?” Motivation: There are several reports in literature of such “audio-visual interactions”, in which visual and auditory perception influence each other. We seek to answer our research question by investigating whether these audio-visual interactions could extend the depth budget used in quality-controlled 3D media. Method/Conclusions: The related literature is reviewed before presenting four novel experiments that build upon each other’s conclusions. In the first experiment, we show that content created with a stereoscopic depth budget creates measurable positive changes in audiences’ attitude towards 3D films. These changes are repeatable for different locations, displays and content. In the second experiment we calibrate an audio-visual display system and use it to measure the minimum audible depth difference. Our data is used to formulate recommendations for content designers and systems engineers. These recommendations include the design of an auditory depth perception screening test. We then show that an auditory-visual stimulus with a nearer auditory depth is perceived as nearer. We measure the impact of this effect upon a relative depth judgement, and investigate how the impact varies with audio-visual depth separation. Finally, the size of the cross-modal bias in depth is measured, from which we conclude that sound does have the potential to extend the depth budget by a small, but perceivable, amount.

Published
2015

18. Tolerating the Community Detection Resolution Limit with Edge Weighting

Author

Berry, Jonathan W., Hendrickson, Bruce, LaViolette, Randall A., and Phillips, Cynthia A.

Subjects
Physics - Physics and Society, Physics - Data Analysis, Statistics and Probability
Abstract

Communities of vertices within a giant network such as the World-Wide Web are likely to be vastly smaller than the network itself. However, Fortunato and Barth\'{e}lemy have proved that modularity maximization algorithms for community detection may fail to resolve communities with fewer than $\sqrt{L/2}$ edges, where $L$ is the number of edges in the entire network. This resolution limit leads modularity maximization algorithms to have notoriously poor accuracy on many real networks. Fortunato and Barth\'{e}lemy's argument can be extended to networks with weighted edges as well, and we derive this corollary argument. We conclude that weighted modularity algorithms may fail to resolve communities with fewer than $\sqrt{W \epsilon/2}$ total edge weight, where $W$ is the total edge weight in the network and $\epsilon$ is the maximum weight of an inter-community edge. If $\epsilon$ is small, then small communities can be resolved. Given a weighted or unweighted network, we describe how to derive new edge weights in order to achieve a low $\epsilon$, we modify the ``CNM'' community detection algorithm to maximize weighted modularity, and show that the resulting algorithm has greatly improved accuracy. In experiments with an emerging community standard benchmark, we find that our simple CNM variant is competitive with the most accurate community detection methods yet proposed., Comment: revision with 8 pages 3 figures 2 tables

Published
2009
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19. Community Detection via Facility Location

Author

Berry, Jonathan W., Hendrickson, Bruce, LaViolette, Randall A., Leung, Vitus J., and Phillips, Cynthia A.

Subjects
Physics - Physics and Society, Physics - Data Analysis, Statistics and Probability
Abstract

In this paper we apply theoretical and practical results from facility location theory to the problem of community detection in networks. The result is an algorithm that computes bounds on a minimization variant of local modularity. We also define the concept of an edge support and a new measure of the goodness of community structures with respect to this concept. We present preliminary results and note that our methods are massively parallelizable., Comment: 4 pages, 3 figures

Published
2007

20. An investigation into teachers' professional autonomy in England : implications for policy and practice

Author

Berry, Jonathan

Subjects
371.100942, teacher autonomy, neo-liberalism, history of education, policy, policy makers
Abstract

The current coalition government in England has expressed its commitment to establishing an autonomous teaching profession. This study argues that such autonomy cannot exist in a system that is ideologically driven by market forces and neo-liberal policy. The best situation that most teachers can hope to experience – barring a seismic shift in material conditions – is an earned and scrutinised autonomy, which is an oxymoronic concept. It is argued that the tight control exercised by the state over what happens in schools through its promotion of market forces, reinforces the ideological nature of schooling in England. The theoretical and ontological basis of the study resides in an orthodox Marxist perspective and analyses the way in which neo-liberalism has formed the basis for the material conditions under which teachers currently work. It develops this idea to demonstrate how this dominant ideology pervades current discourse about pedagogy and curriculum, reducing such discourse to a narrower consideration of ‘standards’. It considers how this diminution of what the curriculum has become has, in its turn, had an impact on teachers’ view of their professional autonomy. Data are gathered from two rounds of interviews with 22 serving teachers complemented by some written responses from them. Six others with a professional interest in education policy-making, four of whom are headteachers, are also interviewed. The conclusion is drawn that teachers’ autonomy remains restricted, with any independence of action largely contingent upon the production of outcomes measured against limited, pre-determined and ideologically driven outcomes. The study identifies a disconnection between the aspirations of teachers with regard to their professional autonomy and those of some, but not all, headteachers. A further disconnection between the aspirations of teachers and the policies of central government is also identified. Significantly, teachers may enjoy more professional autonomy in those schools which currently, and possibly temporarily, enjoy market popularity. In terms of a contribution to the debate about teacher autonomy, the study demonstrates that, notwithstanding the effects of the current policy ensemble, teachers maintain a sense of what education could offer young people that goes beyond the existing, reductive models that frame their working lives.

Published
2013

24. Patients who report night sweats

Author

Larnard, Jeffrey, primary, Berry, Jonathan, additional, Majety, Priyanka, additional, Moeng, Letumile, additional, Lille, Marianne, additional, and Lee, Matthew Shou Lun, additional

Published
2023
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27. Path optimization and near-greedy analysis for graph partitioning: an empirical study

Author

Berry, Jonathan and Goldberg, Mark

Subjects
Mathematics - Combinatorics, Computer Science - Computational Complexity, 68Q
Abstract

This paper presents the results of an experimental study of graph partitioning. We describe a new heuristic technique, path optimization, and its application to two variations of graph partitioning: the max_cut problem and the min_quotient_cut problem. We present the results of computational comparisons between this technique and the Kernighan-Lin algorithm, the simulated annealing algorithm, the FLOW-lagorithm the multilevel algorithm, and teh recent 0.878-approximation algorithm. The experiments were conducted on two classes of graphs that have become standard for such tests: random and random geometric. They show that for both classes of inputs and both variations of the problem, the new heuristic is competitive with the other algorithms and holds an advantage for min_quotient_cut when applied to very large, sparse geometric graphs. In the last part of the paper, we describe an approach to analyzing graph partitioning algorithms from the statistical point of view. Every partitioning of a graph is viewed as a result achieved by a "near gready" partitioning algorithm. The experiments show that for "good" partitionings, the number of non-greedy steps needed to obtain them is quite small; moreover, it is "statistically" smaller for better partitionings. This led us to conjecture that there exists an "optimal" distribution of the non-greedy steps that characterize the classes of graphs that we studied.

Published
1995

30. Multi-Level Memory Algorithmics for Large Sparse Problems.

Author

Berry, Jonathan W., primary, Butcher, Neil, additional, Catalyurek, Umit, additional, Kogge, Peter, additional, Lin, Paul, additional, Olivier, Stephen Lecler, additional, Phillips, Cynthia A., additional, Rajamanickam, Sivasankaran, additional, Slota, George M., additional, Voskuilen, Gwendolyn Renae, additional, Yasar, Abdurrahman, additional, and Young, Jeffrey G, additional

Published
2019
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31. Small intestinal microbial dysbiosis underlies symptoms associated with functional gastrointestinal disorders

Author

Saffouri, George B., Shields-Cutler, Robin R., Chen, Jun, Yang, Yi, Lekatz, Heather R., Hale, Vanessa L., Cho, Janice M., Battaglioli, Eric J., Bhattarai, Yogesh, Thompson, Kevin J., Kalari, Krishna K., Behera, Gaurav, Berry, Jonathan C., Peters, Stephanie A., Patel, Robin, Schuetz, Audrey N., Faith, Jeremiah J., Camilleri, Michael, Sonnenburg, Justin L., Farrugia, Gianrico, Swann, Jonathan R., Grover, Madhusudan, Knights, Dan, and Kashyap, Purna C.

Published
2019
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35. Write-Optimized Algorithms for Cybersecurity Stream Monitoring.

Author

Singh, Shikha, primary, Pandey, Prashant, additional, Bender, Michael, additional, Berry, Jonathan, additional, DeLayo, Daniel, additional, Farach-Colton, Martin, additional, Johnson, Rob, additional, Kroeger, Thomas, additional, Phillips, Cynthia, additional, Tench, David, additional, and Thomas, Eric, additional

Published
2022
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36. Automatic HBM Management

Author

DeLayo, Daniel, primary, Zhang, Kenny, additional, Agrawal, Kunal, additional, Bender, Michael A., additional, Berry, Jonathan W., additional, Das, Rathish, additional, Moseley, Benjamin, additional, and Phillips, Cynthia A., additional

Published
2022
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37. Limited-Memory Techniques for Sensor Placement in Water Distribution Networks

Author

Hart, William E., Berry, Jonathan W., Boman, Erik, Phillips, Cynthia A., Riesen, Lee Ann, Watson, Jean-Paul, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Maniezzo, Vittorio, editor, Battiti, Roberto, editor, and Watson, Jean-Paul, editor

Published
2008
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40. Scheduling an Industrial Production Facility

Author

Asgeirsson, Eyjolfur, Berry, Jonathan, Phillips, Cynthia A., Phillips, David J., Stein, Cliff, Wein, Joel, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Bienstock, Daniel, editor, and Nemhauser, George, editor

Published
2004
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43. Veteran Adherence to Oral Versus Injectable Alcohol Use Disorder Medication Treatment

Author

Dorflinger, Charles, Carey, Heather, Roche, Jennifer, Burant, Christopher, LeHew, Colleen, Stewart, Hayden, Mitchell, Brian, Ayanga, Daniel, Walder, Annette, Cooler, Jordan, Wu, Shuwen, Frey, Theresa, Wenthur, Cody, Burk, Bradley, Ward, Alex, Clark, Brooke, Leung, Jonathan G, Kutzke, Jade, May, Heather P, Maehler, Colin, Kummer, Bethany, Hamner, Jennifer, Ariefdjohan, Merlin, Stutzman, Danielle L, Kicklighter, Jackson, Musco, Shaina, Singson, Grace Marielle, Pamintuan, Claire, Francisco, Janelle, Phan, Tam, Sevak, Rajkumar J, Rogan, Edward L, Kehoe, William A, Halliwell, Robert F, Kanter, Joel, Ryan, Holly, Patel, Krupa, Moukaddam, Nidal, Saunders, John, Fernandez, Luis, Shah, Asim, Wong, Jerry, Erowele, Goldina, Ruppelt, Sara, Tillery, Erika E, Baker, Joni, Loflin, Bobbi Jo, Gray, Emily, Conley, Giulia, Hembree, Amanda, Sterling, Jacyntha, Buige, Ashley N, Nguyen, Mimi, Harris, Suzanne C, Bhavsar, Nisha, Shah, Niti, Lee, Bona, Jeong, Seoyoung, Maroney, Megan E, Whalen, Eric D, Maloney, Rebecca M, Hagemeier, Nicholas E, Takamura, Kay, Rice, Amanda G, Furbish, Amelia B, Hebbard, Amy M, Ross, Clint, Cumbie, Holly, Hickey, J. Scott, Lalani, Falak, Mucha, Hannah, Saklad, Stephen R, Ma, Connie, Lee, Kelly, O’Donnell, Carolyn, Jackson, Sarah, Albee, Jennifer Nelson, Yapel, Ann, Nash, Cynthia, MacDonald, Danielle, King, Amelia, Schneiderhan, Mark, Hager, Keri, Bell Lynum, Karimah S, Nash, Abigail, Fu, Dong Jing, Ionescu, Dawn F, Sliwa, Jennifer Kern, Turkoz, Ibrahim, Dorson, Peter G, Canuso, Carla, Hsia, Stephanie, Nguyen, Julie, La, Amenda, Gruenberg, Katherine, MacDougall, Conan, Brockbank, Josh, Wong, Kara, Schultz, Erica, Pinchinat, Jessica, Thibeaux, Taylor M, McCants, Tamara, Lam, Jason, Diaz-Luna, Jose, Nguyen, Jennifer, Yokoyama, Melissa, Albiar, Olivia, Bradley, Bridget, Popish, Sarah J, Bounthavong, Mark, Lau, Marcos K, Wells, Daina L, Kay, Chad L, Harvey, Michael A, Himstreet, Julianne E, Christopher, Melissa L.D, Weeda, Erin R, McGraw, Daniel J, Gonzalez, Misty L, Pardo-Pfeiffer, Carlos, Rodeghiero, Abigail, Zhang, Lusi, Brown, Sarah Jane, Shan, Yuting, Lee, Adam M, Allen, Josiah D, Eum, Seenae, Bishop, Jeffrey R, Gonzalez, Rolando, Wahl, Kimberly, Naglich, Andrew, Ayson, Marl, Thomas, Kelan, Renfro, Mandy L, Loera, Lindsey J, Hill, Lucas G, Tirado, Carlos, Delerme, Dante, Dean, Taylor, Cullen, Marissa, Straley, Craig M, Carr, Chelsea N, Sun, Wendy, Alzouby, Hiba, Harris, Suzanne, Banker, Christopher M, Cook, Sarah F, Muir, Justin, Brodie, Daniel, Cremers, Serge, Bies, Robert R, Dzierba, Amy L, Moton, Robert, Saklad, Stephen, Ferris, Ryan E, Noble, Brie N, Hartung, Daniel M, Tjia, Jennifer, Furuno, Jon P, Ibrahim, Hajer, Duong, Dat, Malcolm, Benjamin, Gogineni, Hyma P, Zahn, Amy L, Alibeckoff, Chloe C, Connor, Sharon, Buranosky, Raquel, Livezey, Sabrina N, Daniell, Jessica, DeClercq, Josh, Choi, Leena, Zuckerman, Autumn, Shah, Nisha B, Kang, Ashley, Anksorus, Heidi, Troglin, Courtney G, Bouldin, J. Brooke, Schreiner, Shannon, McKinney, Mariah, Brown, Stacy D, Pond, Brooks B, Nguyen, Thu, Chin, Hyun Ji, Dambly, Nicolle, Augsten, Alberto, Themas, Samantha, Vicencio, Claudia, Horner, Caroline, Covert, Kelly, Lewis, Paul, Tharp, Jen, Sommi, Roger W, Bidollari, Ilda, Still, Daniel, Du, Yangchun, Yagoda, Sergey, Weiden, Peter J, Long, Katelyn, Vandiver, Emily, Johnson, Stephanie, Darazs, Brooks, Tillery, Erika, Silvia, Richard J, Lee, Kelly C, Bien, Ivy, Farahmand, Khodayar, Goldsmith, Hannah, Farrar, Mallory, Le, Hadley, Huynh, Quynh, Kim, Jane, McCausland, Kristen, Haider, Batool, White, Michelle K, O’Sullivan, Amy K, Rychlec, Kaitlin, Akerman, Sarah, Fratantonio, James, Saxon, Andrew, Thase, Michael E, Parikh, Sagar V, Maheshwari, Priya, Rothschild, Anthony J, Dunlop, Boadie W, DeBattista, Charles, Conway, Charles R, Forester, Brent P, Shelton, Richard C, Macaluso, Matthew, Brown, Krystal, Li, James, Jablonski, Michael R, Greden, John F, Gidal, Barry, Patsalos, Philip, Szaflarski, Jerzy, VanLandingham, Kevan, Critchley, David, Morrison, Gilmour, Weiss, Catherine, Meehan, Stine Rasmussen, Ouyang, John, Hobart, Mary, Rowe, William, Vanover, Kimberly E, Kane, John M, Satlin, Andrew, Durgam, Suresh, Davis, Robert E, Mates, Sharon, Correll, Christoph U, Tamminga, Carol, Rabon, Hannah, Smith, Jordan, Squires, Karrie, VanDaele, Madeline, Logan, Linda D, Zhang, Feng, DeSousa, Norberto J, Sallee, F. Randy, Lickrish, David, Incledon, Bev, Smith, Joseph L, Candon, Molly, Fadeyibi, Oluwatoyin, Connolly, K. Ryan, Lim, Suet, Neimark, Geoffrey, Mandell, David, Newcomer, John W, Silverman, Bernard, DiPetrillo, Lauren, Graham, Christine, Jiang, Ying, Simmons, Adam, Hopkinson, Craig, McDonnell, David, Kahn, Rene, King, Thomas R, Kando, Judith C, Pardo, Antonio, King, Thomas, Edwards, John B, Chen, Richard, Huo, Jason, Cutler, Andrew J, Fawver, Jay, Flanagan, Mindy, Smith, Thomas, Drouin, Michelle, Mirro, Michael, Yatham, Lakshmi N, Vieta, Eduard, McIntyre, Roger S, Jain, Rakesh, Earley, Willie R, Patel, Mehul, Brown, Lisa, Sehgal, Rahul, Yu, Ken, Al Habbab, Talal, Johnson, Holly, Dechairo, Bryan, Chen, Jack J, Singer, Carlos, Marder, Stephen R, Comella, Cynthia L, Shah, Chirag, Jimenez, Roland, Goodwin, Heather, Morrow, Gina, Tewksbury, Ashley, Waters, Kristin, Eggert, Robyn, Tallian, Kimberly, Sepulveda, Joe A, Rojas, Sarah, Sikand, Harminder, Sutera, Nathan, Iuppa, Courtney A, Nelson, Leigh Anne, Kriz, Carrie R, Burns, Nicole A, Lang, Shelby E, Elliott, Ellie S.R, Luong, Uyen, Elsobky, Teresa, Abelleira, Audrey, Awan, Sundus, Dume, Roberta, Dilich, Adam, Anderson, Mikaela, Park, Priscilla, Moehnke, Austin, Aebi, Cydreese, Feighner, Lydia, Vernon, Martein, Streit, Jessica, Kauer, Jill, Lemons, Amber, Diefenderfer, Lauren A, Moon, Joseph, Smith, Jordan O, Franck, Hugh A, Randle, C. Hope, Hedgepeth Kennedy, M. Lindsey, James, Shannon, Coplan, Benjamin, Ruekert, Laura, Puri, Shilpa, Yeleti, Ramya, Cathright, Sela, Coveart, Stephanie, Regen, Sloan, Stewart, Shannon, Stratton, Miranda, Haight, Robert, Hoeft, Dawn, Bishop, Danielle, De La Cruz, Austin, Aurelio, Mariellee, Prestenback, Autumn, Price, Paul L, Makuch, Christian X, Salisbury, Nicole M, Koch, Jessa, Palmer, Melissa C, Chace, Ashley, Price, Cristofer, Putney, Jessica, Khan, Fatima, Huntsman, Amanda, Hutcheson, Brooklyn, Hightower, Sharae, Ott, Carol A, Scott, Catherine, Balser, Amanda, Karas, Andrew, Hsu, Michael, Malin, Maureen, Robert, Sophie, Leung, Edwina, Mierzwa, Mark, Kay, Lehua, Bowling, Dalia, Allen, Sabrina, Weingartner, Melissa, Ventricelli, Daniel, Santa, Heather, Nowalk, Alexandra, Downs, George, Le, N, Mospan, C, Burton, Caitlin, Mathys, Monica, Gutierrez, Erika, Ali, Sarah, Chang, Joni, Holzum, Dorothy N, Griffith, June A, Morgan, Katherine T, Laguado, S. Andrea, Steavenson, Rosana, Mehvar, Mina, Bechtold, Carson L, Kim, Heesoo, Dopheide, Julie Ann, Anderson, Lindsey, Kleyn, Thomas, DiRenzo, Baely, Walroth, Todd, Adamczyk, Raechel, Kendrick, Jenna, Thomas, Christopher, Mailloux, Lindsay M, Haas, Matthew T, Larew, Janel M, Stohs, Matthew E, DeJongh, Beth M, Satow, Britney A, Titus-Lay, Erika, Clark, Suzanne, Dike, Dozie, Pinsonnault, John, Gamber, Joy, Roseberry, Samantha, Mitchell, Brian G, Nguyen, Mai, Willborn, Robert, Roche-Desilets, Jennifer, Dailey, Alison, Ignatowski, Michael, Routhieaux, Melanie, Kawsky, Jaclyn, Stratman, Jennifer, Corboy, Alexander, Norberte, Cherisse, Gross, Tonya, Daniel, Jeremy, Tran, Aaron N, Wary, Megan, Kostric, Anna, Schaller, Samantha, Shin, Yunjung, Maroney, Megan, Hampton, Chanese, Krieger, Kelly, Hartwig, Rachel, Thamawatanakul, Rani, Wilbur, Eileen, Shofner, Steven, Butler, Justin, Moody, Breanna, Davis, Elizabeth, Hofammann, Elizabeth, Liveoak, Katie, Mitchell, McKinley, Lebrecht, Morgan, Hawley, Joanne, Smigiel, Joe, Radtke, Michelle, Walkerly, Autumn, King, Morgan, Wakefield, Andrew, Downs, Mona, Hudson, Nancy, Burghart, Steven, Reynoldson, Jill, Booth, Macey, Ishino, Risa, Lee, Tammie, Wright, Melissa, Boggs, Angela, Kaur, Rajandeep, Patel, Parth, Smith, Thomas R, Theriault, Sarah, Okusaga, Olaoluwa, Reinstatler, Kristina, Hawk, David, Rush, Stephen, Vachuska, Michaela, Powell, Elizabeth, Lacro, Jonathan, Chehovich, Charisse, Demler, Tammie Lee, deRosas, Andrea, Trigoboff, Eileen, Taylor, Aminah, Singh, Divita, Burdge, Gary, Reynolds, Jamie, Kriz, Carrie, Burns, Nicole, Sommi, Roger, Yabs, Melanie, Sarpal, Deepak, Fabian, Tanya, Bartos, Lindsey, Tallman, Kristin, Johnson, Dara, Taylor, Daniel, Hogan, Brendon, Kwan, Peter, Bast, Aubree, Sanchez, Apolinar, Maglalang, Patricia D, Scheible, Mahli M, Skurat, McKenzie K, Jackson, Sarah K, Belknap, Jazmin N, Ostfeld, Larissa, Fahy, Megan, Nguyen, Tuyen, Bui, Hoa, Little, Meg M, Seifert, Randall, Maister, Ashley, McCarthy, Caitlin, Burger, Emily, Mullen, Sandy, Cusimano, Joseph, VandenBerg, Amy, Duquette, Meghan, Guttenberg, Viktoria, Matsunaga, Candace, White, Shelby, Richard, Andrea, Jones, Jessica, Morgan, Kaitlyn, Kelsey, Taylor, Sartin, Carrie J, Rickert, Leah, Ferrill, Laine, Vallabh, Anuja, Jhawar, Archana, Barrett, Monica, Ward, Sarah, Colvard, Michelle, Phan, Joann, Preinitz, Jennifer, Ellis, Marcus, Gibu, Matthew, Kivlehan, Audrey, Chiulli, Dana, Rhodes, Kirby, Brewer, T. Amber, Richard, Michelle, Kirwan, Brigit, Flowers, Gary, Albritton, Melinda, Sutton, Caroline M, McEachern, Sydney, Miskle, Benjamin, Barr, Rachel, Thomas, Chris, Yang, Waverly, Vogt, Caitlin, Charles, Amanda, Mathews, Alisha, Bhandari, Deepali, Olsen, Emily, Garling, Ashley, Liszka, Jessica, Goodman, Courtney S, Smith, Tammy, Barron, Ana, Williams, Andrew, Zuloaga, Andrea, Parra, Brianne, Miller, Joy, Blake, Jennifer, Toney, Gregory, Galeano, Kathleen, Morabito, Brianna, Smith, Sydney, Miller, Lindsey, Fleisch, Sheryl, Kim, Erika, Kurz, Troy, Peterson, Angela M, Gruca, Justin, McGuire, Michael, Stummer, Lauren, Yip, Agustin, Rodriguez-Villa, Fernando, Wilson, Jennifer, Sutton, Caroline, Owings, R. Laney, Herbst, Claire, Hosmer, Kane, Wulff-Burchfield, Elizabeth, Ramion, Shelby, Brown, Lauren, Shishko, Ilona, Allen, Sarah, Nichols, Taylor, Fawcett, Janet, Trent, Kelley N, Eatmon, Courtney V, Hershberger, Allie, Roads, Mary, Pittenger, Amy L, Dadebo, Victoria, Tomko, John R, Simeone, Danielle, Sherwood, Devon A, Morgan, Katherine, White, C. Whitney, Holzum, Dorothy, Adetunji, Oluwaseyi, Blalock, Meredith, Snyder, Sabrina Domicoli, Kneebusch, Jamie, Mitchell, Melissa, Butala, Niyati, McHugh, Trisha, McGuire, J Michael, Moller, Karen, Melton, Brittany, Mitchell, Melissa M, Chaplin, Kyrsten, Canto, Samantha, Hang Vu, Thi Thuy, Rey, Jose A, Elmaoued, Amre Adel, Hopper, Jessica, Do, Annette, Leckband, Susan G, Abraham, Dana L, Haught, Emma J, Kobulinsky, Lawrence R, Fabian, Tanya J, Greenwood, Jessica, Rey, Jose, Chen, Emily, Farhadian, Sanaz, Smith, Austin M, Hopkins, Tiffany M, Deardorff, O. Greg, Jenne, Victoria, Wood, Joshua, Trout, Megan, Beck, Niels C, Pals, Hale, Frazier, Erica, Cavaliere, Vincent S, DiPaula, Bethany A, Glassman, Matthew, Wehring, Heidi J, Mackowick, Marie, Park, Jaeboon, Love, Raymond C, Kelly, Deanna L, Newbold, Mervan, Fioravanti, Nicole, Brown, Matthew J, Casey, Emily R, Nadkarni, Neha, Oh, Sarah, Patel, Romi, Riedley, Taylor, Mathis, Erin, Fadden, Patrick, Madden, Cristina, Schneiderhan, Mark E, Hintsala, Madelynn, Stenehjem, David, Rufus, Krystal M, Elhakim, Athar, Zolezzi, Monica, Elamin, Waad M, Homs, Shorouk, Qubaiah, Iman K, Mahmoud, Doaa A, Tawfik, Enge M, Fritz, Merideth, Alman, Brianne, Wartman, Carolanne, Clark, Megan, Ott, Carol, Rainey, Carly A, Mann, Elise, Modany, Madison, Schoettmer, Amanda, Buckley, Tiffany, Patwardhan, Vidisha, Boyle, Cynthia J, Gardner, Kristen N, Hamby, Kerri, Ngo, Nichol, Kim, Lila Q, Chen, Steven W, Mosley, Scott, Dadiomov, David, Goldstone, Lisa W, DellaVecchia, Matthew J, Cauffield, Jacintha, Grim, Hannah, Eschler, Anna, Aladeen, Traci, Blondell, Richard, Capote, Horacio, Rainka, Michelle, Lee, Ashley, Shelley, Maria, Stoncius, Kristina, Berry, Jonathan, Doroudgar, Shadi, Johnson, Kayla, Pouliot, Jonathon, Rarrick, Christine, Hebbard, Amy, Shikwana, Sara, Koller, Katherine, Reed, Ellen, Hoefling, Austin D, Miles, Talia M, Ansara, Elayne D, Titova, Viktoriya, Kandela, Dalea, Douglass, Amber R, Ehrhard, Kimberly, Stanley, Madison, Ganihong, Carissa, Liu, Mei T, Bohnenberger, Kristin, Zuber, Nicole, Plunkett, McKenzie, Axelrod, Chelsey, Lightfoot, Myaa, Moore, Miranda, Crouse, Ericka, Olazo, Muriel, Taormina, Stephanie, Reiss, Rebecca, Denno, Nora, Johnson, Braniesha, Wilkening, Gwendolyn Lucy, Andrews, Haley, Neumeister, Kristen, Murad, Muhammad Ubaidullah, Reid, Bailey, Franco, Ashley, Stutzman, Danielle, Jorgensen, Jennifer, Basit, Saadia, Jensen, Aimee, Nadal, Celeste N, Truong, Quynh-Nhu, Jameson, Melanie, Knox, Erin D, Bota, Robert G, Wieruszewski, Patrick M, and Leung, Sarah B

Subjects
CPNP Foundation Strategic Goals Award Finalists, Therapeutic Case Report Abstracts, Original Research Abstracts, Therapeutic Case Report Award Finalists, Article, Encore Presentation Abstracts, Work in Progress Abstracts, Neuropsychology and Physiological Psychology, Original Research Award Finalists, Research Trainee Award Finalists, Pharmacology (medical), Neurology (clinical), General Pharmacology, Toxicology and Pharmaceutics, Innovative Practices Abstracts, Innovative Practices Award Finalists, Scientific Posters
Published
2020

44. Graph drawing and manipulation with LINK

Author

Berry, Jonathan, Dean, Nathaniel, Goldberg, Mark, Shannon, Gregory, Skiena, Steven, Goos, Gerhard, editor, Hartmanis, Juris, editor, van Leeuwen, Jan, editor, and DiBattista, Giuseppe, editor

Published
1997
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47. Advanced Data Structures for Improved Cyber Resilience and Awareness in Untrusted Environments: LDRD Report

Author

Bender, Michael A., primary, Berry, Jonathan W., additional, Farach-Colton, Martin, additional, Jacobs, Justin, additional, Johnson, Rob, additional, Kroeger, Thomas M., additional, Mayer, Tyler, additional, McCauley, Samuel, additional, Pandey, Prashant, additional, Phillips, Cynthia A., additional, Porter, Alexandra, additional, Singh, Shikha, additional, Raizes, Justin, additional, Xu, Helen, additional, and Zage, David, additional

Published
2018
Full Text
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49. Timely Reporting of Heavy Hitters Using External Memory

Author

Singh, Shikha, primary, Pandey, Prashant, additional, Bender, Michael A., additional, Berry, Jonathan W., additional, Farach-Colton, Martín, additional, Johnson, Rob, additional, Kroeger, Thomas M., additional, and Phillips, Cynthia A., additional

Published
2021
Full Text
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